v1

package
v0.32.0 Latest Latest
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 Go to latest Published: Nov 29, 2023 License: Apache-2.0 Imports: 9 Imported by: 0

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Index

Constants

View Source 
const (
	// Unspecified state for the Artifact.
	ArtifactStateEnumStateUnspecified = ArtifactStateEnum("STATE_UNSPECIFIED")
	// A state used by systems like Vertex AI Pipelines to indicate that the underlying data item represented by this Artifact is being created.
	ArtifactStateEnumPending = ArtifactStateEnum("PENDING")
	// A state indicating that the Artifact should exist, unless something external to the system deletes it.
	ArtifactStateEnumLive = ArtifactStateEnum("LIVE")
)
View Source 
const (
	// Unspecified Execution state
	ExecutionStateEnumStateUnspecified = ExecutionStateEnum("STATE_UNSPECIFIED")
	// The Execution is new
	ExecutionStateEnumNew = ExecutionStateEnum("NEW")
	// The Execution is running
	ExecutionStateEnumRunning = ExecutionStateEnum("RUNNING")
	// The Execution has finished running
	ExecutionStateEnumComplete = ExecutionStateEnum("COMPLETE")
	// The Execution has failed
	ExecutionStateEnumFailed = ExecutionStateEnum("FAILED")
	// The Execution completed through Cache hit.
	ExecutionStateEnumCached = ExecutionStateEnum("CACHED")
	// The Execution was cancelled.
	ExecutionStateEnumCancelled = ExecutionStateEnum("CANCELLED")
)
View Source 
const (
	// The value type is unspecified.
	FeatureGroupFeatureValueTypeValueTypeUnspecified = FeatureGroupFeatureValueType("VALUE_TYPE_UNSPECIFIED")
	// Used for Feature that is a boolean.
	FeatureGroupFeatureValueTypeBool = FeatureGroupFeatureValueType("BOOL")
	// Used for Feature that is a list of boolean.
	FeatureGroupFeatureValueTypeBoolArray = FeatureGroupFeatureValueType("BOOL_ARRAY")
	// Used for Feature that is double.
	FeatureGroupFeatureValueTypeDouble = FeatureGroupFeatureValueType("DOUBLE")
	// Used for Feature that is a list of double.
	FeatureGroupFeatureValueTypeDoubleArray = FeatureGroupFeatureValueType("DOUBLE_ARRAY")
	// Used for Feature that is INT64.
	FeatureGroupFeatureValueTypeInt64 = FeatureGroupFeatureValueType("INT64")
	// Used for Feature that is a list of INT64.
	FeatureGroupFeatureValueTypeInt64Array = FeatureGroupFeatureValueType("INT64_ARRAY")
	// Used for Feature that is string.
	FeatureGroupFeatureValueTypeString = FeatureGroupFeatureValueType("STRING")
	// Used for Feature that is a list of String.
	FeatureGroupFeatureValueTypeStringArray = FeatureGroupFeatureValueType("STRING_ARRAY")
	// Used for Feature that is bytes.
	FeatureGroupFeatureValueTypeBytes = FeatureGroupFeatureValueType("BYTES")
)
View Source 
const (
	// The value type is unspecified.
	FeatureStoreFeatureValueTypeValueTypeUnspecified = FeatureStoreFeatureValueType("VALUE_TYPE_UNSPECIFIED")
	// Used for Feature that is a boolean.
	FeatureStoreFeatureValueTypeBool = FeatureStoreFeatureValueType("BOOL")
	// Used for Feature that is a list of boolean.
	FeatureStoreFeatureValueTypeBoolArray = FeatureStoreFeatureValueType("BOOL_ARRAY")
	// Used for Feature that is double.
	FeatureStoreFeatureValueTypeDouble = FeatureStoreFeatureValueType("DOUBLE")
	// Used for Feature that is a list of double.
	FeatureStoreFeatureValueTypeDoubleArray = FeatureStoreFeatureValueType("DOUBLE_ARRAY")
	// Used for Feature that is INT64.
	FeatureStoreFeatureValueTypeInt64 = FeatureStoreFeatureValueType("INT64")
	// Used for Feature that is a list of INT64.
	FeatureStoreFeatureValueTypeInt64Array = FeatureStoreFeatureValueType("INT64_ARRAY")
	// Used for Feature that is string.
	FeatureStoreFeatureValueTypeString = FeatureStoreFeatureValueType("STRING")
	// Used for Feature that is a list of String.
	FeatureStoreFeatureValueTypeStringArray = FeatureStoreFeatureValueType("STRING_ARRAY")
	// Used for Feature that is bytes.
	FeatureStoreFeatureValueTypeBytes = FeatureStoreFeatureValueType("BYTES")
)
View Source 
const (
	// Format unspecified, used when unset.
	GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatDataFormatUnspecified = GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat("DATA_FORMAT_UNSPECIFIED")
	// Examples are stored in JSONL files.
	GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatJsonl = GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat("JSONL")
)
View Source 
const (
	// Should not be used.
	GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineBaselineUnspecified = GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline("BASELINE_UNSPECIFIED")
	// Choose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
	GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineLatestStats = GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline("LATEST_STATS")
	// Use the statistics generated by the most recent snapshot analysis if exists.
	GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineMostRecentSnapshotStats = GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline("MOST_RECENT_SNAPSHOT_STATS")
	// Use the statistics generated by the previous import features analysis if exists.
	GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePreviousImportFeaturesStats = GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline("PREVIOUS_IMPORT_FEATURES_STATS")
)
View Source 
const (
	// Should not be used.
	GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateStateUnspecified = GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState("STATE_UNSPECIFIED")
	// The default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.
	GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateDefault = GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState("DEFAULT")
	// Explicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.
	GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateEnabled = GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState("ENABLED")
	// Explicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config.
	GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateDisabled = GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState("DISABLED")
)
View Source 
const (
	// Unspecified accelerator type, which means no accelerator.
	GoogleCloudAiplatformV1MachineSpecAcceleratorTypeAcceleratorTypeUnspecified = GoogleCloudAiplatformV1MachineSpecAcceleratorType("ACCELERATOR_TYPE_UNSPECIFIED")
	// Nvidia Tesla K80 GPU.
	GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaTeslaK80 = GoogleCloudAiplatformV1MachineSpecAcceleratorType("NVIDIA_TESLA_K80")
	// Nvidia Tesla P100 GPU.
	GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaTeslaP100 = GoogleCloudAiplatformV1MachineSpecAcceleratorType("NVIDIA_TESLA_P100")
	// Nvidia Tesla V100 GPU.
	GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaTeslaV100 = GoogleCloudAiplatformV1MachineSpecAcceleratorType("NVIDIA_TESLA_V100")
	// Nvidia Tesla P4 GPU.
	GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaTeslaP4 = GoogleCloudAiplatformV1MachineSpecAcceleratorType("NVIDIA_TESLA_P4")
	// Nvidia Tesla T4 GPU.
	GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaTeslaT4 = GoogleCloudAiplatformV1MachineSpecAcceleratorType("NVIDIA_TESLA_T4")
	// Nvidia Tesla A100 GPU.
	GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaTeslaA100 = GoogleCloudAiplatformV1MachineSpecAcceleratorType("NVIDIA_TESLA_A100")
	// Nvidia A100 80GB GPU.
	GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaA10080gb = GoogleCloudAiplatformV1MachineSpecAcceleratorType("NVIDIA_A100_80GB")
	// Nvidia L4 GPU.
	GoogleCloudAiplatformV1MachineSpecAcceleratorTypeNvidiaL4 = GoogleCloudAiplatformV1MachineSpecAcceleratorType("NVIDIA_L4")
	// TPU v2.
	GoogleCloudAiplatformV1MachineSpecAcceleratorTypeTpuV2 = GoogleCloudAiplatformV1MachineSpecAcceleratorType("TPU_V2")
	// TPU v3.
	GoogleCloudAiplatformV1MachineSpecAcceleratorTypeTpuV3 = GoogleCloudAiplatformV1MachineSpecAcceleratorType("TPU_V3")
	// TPU v4.
	GoogleCloudAiplatformV1MachineSpecAcceleratorTypeTpuV4Pod = GoogleCloudAiplatformV1MachineSpecAcceleratorType("TPU_V4_POD")
)
View Source 
const (
	// Should not be set.
	GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPredictionFormatUnspecified = GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat("PREDICTION_FORMAT_UNSPECIFIED")
	// Predictions are in JSONL files.
	GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatJsonl = GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat("JSONL")
	// Predictions are in BigQuery.
	GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatBigquery = GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat("BIGQUERY")
)
View Source 
const (
	// Goal Type will default to maximize.
	GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalGoalTypeUnspecified = GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal("GOAL_TYPE_UNSPECIFIED")
	// Maximize the goal metric.
	GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalMaximize = GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal("MAXIMIZE")
	// Minimize the goal metric.
	GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalMinimize = GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal("MINIMIZE")
)
View Source 
const (
	// Defaults to `REINFORCEMENT_LEARNING`.
	GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmMultiTrialAlgorithmUnspecified = GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm("MULTI_TRIAL_ALGORITHM_UNSPECIFIED")
	// The Reinforcement Learning Algorithm for Multi-trial Neural Architecture Search (NAS).
	GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmReinforcementLearning = GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm("REINFORCEMENT_LEARNING")
	// The Grid Search Algorithm for Multi-trial Neural Architecture Search (NAS).
	GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmGridSearch = GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm("GRID_SEARCH")
)
View Source 
const (
	// Default value, and follows fail slow behavior.
	GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPipelineFailurePolicyUnspecified = GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy("PIPELINE_FAILURE_POLICY_UNSPECIFIED")
	// Indicates that the pipeline should continue to run until all possible tasks have been scheduled and completed.
	GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPipelineFailurePolicyFailSlow = GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy("PIPELINE_FAILURE_POLICY_FAIL_SLOW")
	// Indicates that the pipeline should stop scheduling new tasks after a task has failed.
	GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPipelineFailurePolicyFailFast = GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy("PIPELINE_FAILURE_POLICY_FAIL_FAST")
)
View Source 
const (
	// Should not be set. Added as a recommended best practice for enums
	GoogleCloudAiplatformV1PresetsModalityModalityUnspecified = GoogleCloudAiplatformV1PresetsModality("MODALITY_UNSPECIFIED")
	// IMAGE modality
	GoogleCloudAiplatformV1PresetsModalityImage = GoogleCloudAiplatformV1PresetsModality("IMAGE")
	// TEXT modality
	GoogleCloudAiplatformV1PresetsModalityText = GoogleCloudAiplatformV1PresetsModality("TEXT")
	// TABULAR modality
	GoogleCloudAiplatformV1PresetsModalityTabular = GoogleCloudAiplatformV1PresetsModality("TABULAR")
)
View Source 
const (
	// More precise neighbors as a trade-off against slower response.
	GoogleCloudAiplatformV1PresetsQueryPrecise = GoogleCloudAiplatformV1PresetsQuery("PRECISE")
	// Faster response as a trade-off against less precise neighbors.
	GoogleCloudAiplatformV1PresetsQueryFast = GoogleCloudAiplatformV1PresetsQuery("FAST")
)
View Source 
const (
	// Default will be treated as UNCERTAINTY.
	GoogleCloudAiplatformV1SampleConfigSampleStrategySampleStrategyUnspecified = GoogleCloudAiplatformV1SampleConfigSampleStrategy("SAMPLE_STRATEGY_UNSPECIFIED")
	// Sample the most uncertain data to label.
	GoogleCloudAiplatformV1SampleConfigSampleStrategyUncertainty = GoogleCloudAiplatformV1SampleConfigSampleStrategy("UNCERTAINTY")
)
View Source 
const (
	// The default algorithm used by Vertex AI for [hyperparameter tuning](https://cloud.google.com/vertex-ai/docs/training/hyperparameter-tuning-overview) and [Vertex AI Vizier](https://cloud.google.com/vertex-ai/docs/vizier).
	GoogleCloudAiplatformV1StudySpecAlgorithmAlgorithmUnspecified = GoogleCloudAiplatformV1StudySpecAlgorithm("ALGORITHM_UNSPECIFIED")
	// Simple grid search within the feasible space. To use grid search, all parameters must be `INTEGER`, `CATEGORICAL`, or `DISCRETE`.
	GoogleCloudAiplatformV1StudySpecAlgorithmGridSearch = GoogleCloudAiplatformV1StudySpecAlgorithm("GRID_SEARCH")
	// Simple random search within the feasible space.
	GoogleCloudAiplatformV1StudySpecAlgorithmRandomSearch = GoogleCloudAiplatformV1StudySpecAlgorithm("RANDOM_SEARCH")
)
View Source 
const (
	// Will be treated as LAST_MEASUREMENT.
	GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeMeasurementSelectionTypeUnspecified = GoogleCloudAiplatformV1StudySpecMeasurementSelectionType("MEASUREMENT_SELECTION_TYPE_UNSPECIFIED")
	// Use the last measurement reported.
	GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeLastMeasurement = GoogleCloudAiplatformV1StudySpecMeasurementSelectionType("LAST_MEASUREMENT")
	// Use the best measurement reported.
	GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeBestMeasurement = GoogleCloudAiplatformV1StudySpecMeasurementSelectionType("BEST_MEASUREMENT")
)
View Source 
const (
	// Goal Type will default to maximize.
	GoogleCloudAiplatformV1StudySpecMetricSpecGoalGoalTypeUnspecified = GoogleCloudAiplatformV1StudySpecMetricSpecGoal("GOAL_TYPE_UNSPECIFIED")
	// Maximize the goal metric.
	GoogleCloudAiplatformV1StudySpecMetricSpecGoalMaximize = GoogleCloudAiplatformV1StudySpecMetricSpecGoal("MAXIMIZE")
	// Minimize the goal metric.
	GoogleCloudAiplatformV1StudySpecMetricSpecGoalMinimize = GoogleCloudAiplatformV1StudySpecMetricSpecGoal("MINIMIZE")
)
View Source 
const (
	// The default noise level chosen by Vertex AI.
	GoogleCloudAiplatformV1StudySpecObservationNoiseObservationNoiseUnspecified = GoogleCloudAiplatformV1StudySpecObservationNoise("OBSERVATION_NOISE_UNSPECIFIED")
	// Vertex AI assumes that the objective function is (nearly) perfectly reproducible, and will never repeat the same Trial parameters.
	GoogleCloudAiplatformV1StudySpecObservationNoiseLow = GoogleCloudAiplatformV1StudySpecObservationNoise("LOW")
	// Vertex AI will estimate the amount of noise in metric evaluations, it may repeat the same Trial parameters more than once.
	GoogleCloudAiplatformV1StudySpecObservationNoiseHigh = GoogleCloudAiplatformV1StudySpecObservationNoise("HIGH")
)
View Source 
const (
	// By default, no scaling is applied.
	GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeScaleTypeUnspecified = GoogleCloudAiplatformV1StudySpecParameterSpecScaleType("SCALE_TYPE_UNSPECIFIED")
	// Scales the feasible space to (0, 1) linearly.
	GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeUnitLinearScale = GoogleCloudAiplatformV1StudySpecParameterSpecScaleType("UNIT_LINEAR_SCALE")
	// Scales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.
	GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeUnitLogScale = GoogleCloudAiplatformV1StudySpecParameterSpecScaleType("UNIT_LOG_SCALE")
	// Scales the feasible space "reverse" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive.
	GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeUnitReverseLogScale = GoogleCloudAiplatformV1StudySpecParameterSpecScaleType("UNIT_REVERSE_LOG_SCALE")
)
View Source 
const (
	// Should not be used.
	IndexIndexUpdateMethodIndexUpdateMethodUnspecified = IndexIndexUpdateMethod("INDEX_UPDATE_METHOD_UNSPECIFIED")
	// BatchUpdate: user can call UpdateIndex with files on Cloud Storage of Datapoints to update.
	IndexIndexUpdateMethodBatchUpdate = IndexIndexUpdateMethod("BATCH_UPDATE")
	// StreamUpdate: user can call UpsertDatapoints/DeleteDatapoints to update the Index and the updates will be applied in corresponding DeployedIndexes in nearly real-time.
	IndexIndexUpdateMethodStreamUpdate = IndexIndexUpdateMethod("STREAM_UPDATE")
)
View Source 
const (
	// Unspecified type for the MetadataSchema.
	MetadataSchemaSchemaTypeMetadataSchemaTypeUnspecified = MetadataSchemaSchemaType("METADATA_SCHEMA_TYPE_UNSPECIFIED")
	// A type indicating that the MetadataSchema will be used by Artifacts.
	MetadataSchemaSchemaTypeArtifactType = MetadataSchemaSchemaType("ARTIFACT_TYPE")
	// A typee indicating that the MetadataSchema will be used by Executions.
	MetadataSchemaSchemaTypeExecutionType = MetadataSchemaSchemaType("EXECUTION_TYPE")
	// A state indicating that the MetadataSchema will be used by Contexts.
	MetadataSchemaSchemaTypeContextType = MetadataSchemaSchemaType("CONTEXT_TYPE")
)
View Source 
const (
	// Unspecified notebook runtime type, NotebookRuntimeType will default to USER_DEFINED.
	NotebookRuntimeTemplateNotebookRuntimeTypeNotebookRuntimeTypeUnspecified = NotebookRuntimeTemplateNotebookRuntimeType("NOTEBOOK_RUNTIME_TYPE_UNSPECIFIED")
	// runtime or template with coustomized configurations from user.
	NotebookRuntimeTemplateNotebookRuntimeTypeUserDefined = NotebookRuntimeTemplateNotebookRuntimeType("USER_DEFINED")
	// runtime or template with system defined configurations.
	NotebookRuntimeTemplateNotebookRuntimeTypeOneClick = NotebookRuntimeTemplateNotebookRuntimeType("ONE_CLICK")
)
View Source 
const (
	// The value type is unspecified.
	TimeSeriesValueTypeValueTypeUnspecified = TimeSeriesValueType("VALUE_TYPE_UNSPECIFIED")
	// Used for TensorboardTimeSeries that is a list of scalars. E.g. accuracy of a model over epochs/time.
	TimeSeriesValueTypeScalar = TimeSeriesValueType("SCALAR")
	// Used for TensorboardTimeSeries that is a list of tensors. E.g. histograms of weights of layer in a model over epoch/time.
	TimeSeriesValueTypeTensor = TimeSeriesValueType("TENSOR")
	// Used for TensorboardTimeSeries that is a list of blob sequences. E.g. set of sample images with labels over epochs/time.
	TimeSeriesValueTypeBlobSequence = TimeSeriesValueType("BLOB_SEQUENCE")
)

Variables

This section is empty.

Functions

This section is empty.

Types

type Artifact 

type Artifact struct {
	pulumi.CustomResourceState

	// The {artifact} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}` If not provided, the Artifact's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Artifacts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Artifact.)
	ArtifactId pulumi.StringPtrOutput `pulumi:"artifactId"`
	// Timestamp when this Artifact was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Description of the Artifact
	Description pulumi.StringOutput `pulumi:"description"`
	// User provided display name of the Artifact. May be up to 128 Unicode characters.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
	Metadata        pulumi.StringMapOutput `pulumi:"metadata"`
	MetadataStoreId pulumi.StringOutput    `pulumi:"metadataStoreId"`
	// The resource name of the Artifact.
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaTitle pulumi.StringOutput `pulumi:"schemaTitle"`
	// The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaVersion pulumi.StringOutput `pulumi:"schemaVersion"`
	// The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
	State pulumi.StringOutput `pulumi:"state"`
	// Timestamp when this Artifact was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
	// The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
	Uri pulumi.StringOutput `pulumi:"uri"`
}

Creates an Artifact associated with a MetadataStore. Auto-naming is currently not supported for this resource.

func GetArtifact 

func GetArtifact(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *ArtifactState, opts ...pulumi.ResourceOption) (*Artifact, error)

GetArtifact gets an existing Artifact resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewArtifact 

func NewArtifact(ctx *pulumi.Context,
	name string, args *ArtifactArgs, opts ...pulumi.ResourceOption) (*Artifact, error)

NewArtifact registers a new resource with the given unique name, arguments, and options.

func (*Artifact) ElementType 

func (*Artifact) ElementType() reflect.Type

func (*Artifact) ToArtifactOutput 

func (i *Artifact) ToArtifactOutput() ArtifactOutput

func (*Artifact) ToArtifactOutputWithContext 

func (i *Artifact) ToArtifactOutputWithContext(ctx context.Context) ArtifactOutput

type ArtifactArgs 

type ArtifactArgs struct {
	// The {artifact} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}` If not provided, the Artifact's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Artifacts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Artifact.)
	ArtifactId pulumi.StringPtrInput
	// Description of the Artifact
	Description pulumi.StringPtrInput
	// User provided display name of the Artifact. May be up to 128 Unicode characters.
	DisplayName pulumi.StringPtrInput
	// An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
	Metadata        pulumi.StringMapInput
	MetadataStoreId pulumi.StringInput
	Project         pulumi.StringPtrInput
	// The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaTitle pulumi.StringPtrInput
	// The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaVersion pulumi.StringPtrInput
	// The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
	State ArtifactStateEnumPtrInput
	// The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
	Uri pulumi.StringPtrInput
}

The set of arguments for constructing a Artifact resource.

func (ArtifactArgs) ElementType 

func (ArtifactArgs) ElementType() reflect.Type

type ArtifactInput 

type ArtifactInput interface {
	pulumi.Input

	ToArtifactOutput() ArtifactOutput
	ToArtifactOutputWithContext(ctx context.Context) ArtifactOutput
}

type ArtifactOutput 

type ArtifactOutput struct{ *pulumi.OutputState }

func (ArtifactOutput) ArtifactId 

func (o ArtifactOutput) ArtifactId() pulumi.StringPtrOutput

The {artifact} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}` If not provided, the Artifact's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Artifacts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Artifact.)

func (ArtifactOutput) CreateTime 

func (o ArtifactOutput) CreateTime() pulumi.StringOutput

Timestamp when this Artifact was created.

func (ArtifactOutput) Description 

func (o ArtifactOutput) Description() pulumi.StringOutput

Description of the Artifact

func (ArtifactOutput) DisplayName 

func (o ArtifactOutput) DisplayName() pulumi.StringOutput

User provided display name of the Artifact. May be up to 128 Unicode characters.

func (ArtifactOutput) ElementType 

func (ArtifactOutput) ElementType() reflect.Type

func (ArtifactOutput) Etag 

func (o ArtifactOutput) Etag() pulumi.StringOutput

An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (ArtifactOutput) Labels 

func (o ArtifactOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).

func (ArtifactOutput) Location 

func (o ArtifactOutput) Location() pulumi.StringOutput

func (ArtifactOutput) Metadata 

func (o ArtifactOutput) Metadata() pulumi.StringMapOutput

Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.

func (ArtifactOutput) MetadataStoreId 

func (o ArtifactOutput) MetadataStoreId() pulumi.StringOutput

func (ArtifactOutput) Name 

func (o ArtifactOutput) Name() pulumi.StringOutput

The resource name of the Artifact.

func (ArtifactOutput) Project 

func (o ArtifactOutput) Project() pulumi.StringOutput

func (ArtifactOutput) SchemaTitle 

func (o ArtifactOutput) SchemaTitle() pulumi.StringOutput

The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (ArtifactOutput) SchemaVersion 

func (o ArtifactOutput) SchemaVersion() pulumi.StringOutput

The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (ArtifactOutput) State 

func (o ArtifactOutput) State() pulumi.StringOutput

The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.

func (ArtifactOutput) ToArtifactOutput 

func (o ArtifactOutput) ToArtifactOutput() ArtifactOutput

func (ArtifactOutput) ToArtifactOutputWithContext 

func (o ArtifactOutput) ToArtifactOutputWithContext(ctx context.Context) ArtifactOutput

func (ArtifactOutput) UpdateTime 

func (o ArtifactOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Artifact was last updated.

func (ArtifactOutput) Uri 

func (o ArtifactOutput) Uri() pulumi.StringOutput

The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.

type ArtifactState 

type ArtifactState struct {
}

func (ArtifactState) ElementType 

func (ArtifactState) ElementType() reflect.Type

type ArtifactStateEnum 

type ArtifactStateEnum string

The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.

func (ArtifactStateEnum) ElementType 

func (ArtifactStateEnum) ElementType() reflect.Type

func (ArtifactStateEnum) ToArtifactStateEnumOutput 

func (e ArtifactStateEnum) ToArtifactStateEnumOutput() ArtifactStateEnumOutput

func (ArtifactStateEnum) ToArtifactStateEnumOutputWithContext 

func (e ArtifactStateEnum) ToArtifactStateEnumOutputWithContext(ctx context.Context) ArtifactStateEnumOutput

func (ArtifactStateEnum) ToArtifactStateEnumPtrOutput 

func (e ArtifactStateEnum) ToArtifactStateEnumPtrOutput() ArtifactStateEnumPtrOutput

func (ArtifactStateEnum) ToArtifactStateEnumPtrOutputWithContext 

func (e ArtifactStateEnum) ToArtifactStateEnumPtrOutputWithContext(ctx context.Context) ArtifactStateEnumPtrOutput

func (ArtifactStateEnum) ToStringOutput 

func (e ArtifactStateEnum) ToStringOutput() pulumi.StringOutput

func (ArtifactStateEnum) ToStringOutputWithContext 

func (e ArtifactStateEnum) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (ArtifactStateEnum) ToStringPtrOutput 

func (e ArtifactStateEnum) ToStringPtrOutput() pulumi.StringPtrOutput

func (ArtifactStateEnum) ToStringPtrOutputWithContext 

func (e ArtifactStateEnum) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type ArtifactStateEnumInput 

type ArtifactStateEnumInput interface {
	pulumi.Input

	ToArtifactStateEnumOutput() ArtifactStateEnumOutput
	ToArtifactStateEnumOutputWithContext(context.Context) ArtifactStateEnumOutput
}

ArtifactStateEnumInput is an input type that accepts ArtifactStateEnumArgs and ArtifactStateEnumOutput values. You can construct a concrete instance of `ArtifactStateEnumInput` via: 

ArtifactStateEnumArgs{...}

type ArtifactStateEnumOutput 

type ArtifactStateEnumOutput struct{ *pulumi.OutputState }

func (ArtifactStateEnumOutput) ElementType 

func (ArtifactStateEnumOutput) ElementType() reflect.Type

func (ArtifactStateEnumOutput) ToArtifactStateEnumOutput 

func (o ArtifactStateEnumOutput) ToArtifactStateEnumOutput() ArtifactStateEnumOutput

func (ArtifactStateEnumOutput) ToArtifactStateEnumOutputWithContext 

func (o ArtifactStateEnumOutput) ToArtifactStateEnumOutputWithContext(ctx context.Context) ArtifactStateEnumOutput

func (ArtifactStateEnumOutput) ToArtifactStateEnumPtrOutput 

func (o ArtifactStateEnumOutput) ToArtifactStateEnumPtrOutput() ArtifactStateEnumPtrOutput

func (ArtifactStateEnumOutput) ToArtifactStateEnumPtrOutputWithContext 

func (o ArtifactStateEnumOutput) ToArtifactStateEnumPtrOutputWithContext(ctx context.Context) ArtifactStateEnumPtrOutput

func (ArtifactStateEnumOutput) ToStringOutput 

func (o ArtifactStateEnumOutput) ToStringOutput() pulumi.StringOutput

func (ArtifactStateEnumOutput) ToStringOutputWithContext 

func (o ArtifactStateEnumOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (ArtifactStateEnumOutput) ToStringPtrOutput 

func (o ArtifactStateEnumOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (ArtifactStateEnumOutput) ToStringPtrOutputWithContext 

func (o ArtifactStateEnumOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type ArtifactStateEnumPtrInput 

type ArtifactStateEnumPtrInput interface {
	pulumi.Input

	ToArtifactStateEnumPtrOutput() ArtifactStateEnumPtrOutput
	ToArtifactStateEnumPtrOutputWithContext(context.Context) ArtifactStateEnumPtrOutput
}

func ArtifactStateEnumPtr 

func ArtifactStateEnumPtr(v string) ArtifactStateEnumPtrInput

type ArtifactStateEnumPtrOutput 

type ArtifactStateEnumPtrOutput struct{ *pulumi.OutputState }

func (ArtifactStateEnumPtrOutput) Elem 

func (o ArtifactStateEnumPtrOutput) Elem() ArtifactStateEnumOutput

func (ArtifactStateEnumPtrOutput) ElementType 

func (ArtifactStateEnumPtrOutput) ElementType() reflect.Type

func (ArtifactStateEnumPtrOutput) ToArtifactStateEnumPtrOutput 

func (o ArtifactStateEnumPtrOutput) ToArtifactStateEnumPtrOutput() ArtifactStateEnumPtrOutput

func (ArtifactStateEnumPtrOutput) ToArtifactStateEnumPtrOutputWithContext 

func (o ArtifactStateEnumPtrOutput) ToArtifactStateEnumPtrOutputWithContext(ctx context.Context) ArtifactStateEnumPtrOutput

func (ArtifactStateEnumPtrOutput) ToStringPtrOutput 

func (o ArtifactStateEnumPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (ArtifactStateEnumPtrOutput) ToStringPtrOutputWithContext 

func (o ArtifactStateEnumPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type BatchPredictionJob 

type BatchPredictionJob struct {
	pulumi.CustomResourceState

	// Statistics on completed and failed prediction instances.
	CompletionStats GoogleCloudAiplatformV1CompletionStatsResponseOutput `pulumi:"completionStats"`
	// Time when the BatchPredictionJob was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// The config of resources used by the Model during the batch prediction. If the Model supports DEDICATED_RESOURCES this config may be provided (and the job will use these resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config must be provided.
	DedicatedResources GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput `pulumi:"dedicatedResources"`
	// For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.
	DisableContainerLogging pulumi.BoolOutput `pulumi:"disableContainerLogging"`
	// The user-defined name of this BatchPredictionJob.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// Time when the BatchPredictionJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
	EndTime pulumi.StringOutput `pulumi:"endTime"`
	// Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
	Error GoogleRpcStatusResponseOutput `pulumi:"error"`
	// Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to `true`. This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited.
	ExplanationSpec GoogleCloudAiplatformV1ExplanationSpecResponseOutput `pulumi:"explanationSpec"`
	// Generate explanation with the batch prediction results. When set to `true`, the batch prediction output changes based on the `predictions_format` field of the BatchPredictionJob.output_config object: * `bigquery`: output includes a column named `explanation`. The value is a struct that conforms to the Explanation object. * `jsonl`: The JSON objects on each line include an additional entry keyed `explanation`. The value of the entry is a JSON object that conforms to the Explanation object. * `csv`: Generating explanations for CSV format is not supported. If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated.
	GenerateExplanation pulumi.BoolOutput `pulumi:"generateExplanation"`
	// Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri.
	InputConfig GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput `pulumi:"inputConfig"`
	// Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.
	InstanceConfig GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput `pulumi:"instanceConfig"`
	// The labels with user-defined metadata to organize BatchPredictionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself).
	ManualBatchTuningParameters GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput `pulumi:"manualBatchTuningParameters"`
	// The name of the Model resource that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources. Exactly one of model and unmanaged_container_model must be set. The model resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed. The model resource could also be a publisher model. Example: `publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`
	Model pulumi.StringOutput `pulumi:"model"`
	// The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.
	ModelParameters pulumi.AnyOutput `pulumi:"modelParameters"`
	// The version ID of the Model that produces the predictions via this job.
	ModelVersionId pulumi.StringOutput `pulumi:"modelVersionId"`
	// Resource name of the BatchPredictionJob.
	Name pulumi.StringOutput `pulumi:"name"`
	// The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of Model's PredictSchemata's instance_schema_uri and prediction_schema_uri.
	OutputConfig GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput `pulumi:"outputConfig"`
	// Information further describing the output of this job.
	OutputInfo GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput `pulumi:"outputInfo"`
	// Partial failures encountered. For example, single files that can't be read. This field never exceeds 20 entries. Status details fields contain standard Google Cloud error details.
	PartialFailures GoogleRpcStatusResponseArrayOutput `pulumi:"partialFailures"`
	Project         pulumi.StringOutput                `pulumi:"project"`
	// Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes. Note: This field currently may be not populated for batch predictions that use AutoML Models.
	ResourcesConsumed GoogleCloudAiplatformV1ResourcesConsumedResponseOutput `pulumi:"resourcesConsumed"`
	// The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.
	ServiceAccount pulumi.StringOutput `pulumi:"serviceAccount"`
	// Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state.
	StartTime pulumi.StringOutput `pulumi:"startTime"`
	// The detailed state of the job.
	State pulumi.StringOutput `pulumi:"state"`
	// Contains model information necessary to perform batch prediction without requiring uploading to model registry. Exactly one of model and unmanaged_container_model must be set.
	UnmanagedContainerModel GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput `pulumi:"unmanagedContainerModel"`
	// Time when the BatchPredictionJob was most recently updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a BatchPredictionJob. A BatchPredictionJob once created will right away be attempted to start. Auto-naming is currently not supported for this resource.

func GetBatchPredictionJob 

func GetBatchPredictionJob(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *BatchPredictionJobState, opts ...pulumi.ResourceOption) (*BatchPredictionJob, error)

GetBatchPredictionJob gets an existing BatchPredictionJob resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewBatchPredictionJob 

func NewBatchPredictionJob(ctx *pulumi.Context,
	name string, args *BatchPredictionJobArgs, opts ...pulumi.ResourceOption) (*BatchPredictionJob, error)

NewBatchPredictionJob registers a new resource with the given unique name, arguments, and options.

func (*BatchPredictionJob) ElementType 

func (*BatchPredictionJob) ElementType() reflect.Type

func (*BatchPredictionJob) ToBatchPredictionJobOutput 

func (i *BatchPredictionJob) ToBatchPredictionJobOutput() BatchPredictionJobOutput

func (*BatchPredictionJob) ToBatchPredictionJobOutputWithContext 

func (i *BatchPredictionJob) ToBatchPredictionJobOutputWithContext(ctx context.Context) BatchPredictionJobOutput

type BatchPredictionJobArgs 

type BatchPredictionJobArgs struct {
	// The config of resources used by the Model during the batch prediction. If the Model supports DEDICATED_RESOURCES this config may be provided (and the job will use these resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config must be provided.
	DedicatedResources GoogleCloudAiplatformV1BatchDedicatedResourcesPtrInput
	// For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.
	DisableContainerLogging pulumi.BoolPtrInput
	// The user-defined name of this BatchPredictionJob.
	DisplayName pulumi.StringInput
	// Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to `true`. This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited.
	ExplanationSpec GoogleCloudAiplatformV1ExplanationSpecPtrInput
	// Generate explanation with the batch prediction results. When set to `true`, the batch prediction output changes based on the `predictions_format` field of the BatchPredictionJob.output_config object: * `bigquery`: output includes a column named `explanation`. The value is a struct that conforms to the Explanation object. * `jsonl`: The JSON objects on each line include an additional entry keyed `explanation`. The value of the entry is a JSON object that conforms to the Explanation object. * `csv`: Generating explanations for CSV format is not supported. If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated.
	GenerateExplanation pulumi.BoolPtrInput
	// Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri.
	InputConfig GoogleCloudAiplatformV1BatchPredictionJobInputConfigInput
	// Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.
	InstanceConfig GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrInput
	// The labels with user-defined metadata to organize BatchPredictionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself).
	ManualBatchTuningParameters GoogleCloudAiplatformV1ManualBatchTuningParametersPtrInput
	// The name of the Model resource that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources. Exactly one of model and unmanaged_container_model must be set. The model resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed. The model resource could also be a publisher model. Example: `publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`
	Model pulumi.StringPtrInput
	// The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.
	ModelParameters pulumi.Input
	// The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of Model's PredictSchemata's instance_schema_uri and prediction_schema_uri.
	OutputConfig GoogleCloudAiplatformV1BatchPredictionJobOutputConfigInput
	Project      pulumi.StringPtrInput
	// The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.
	ServiceAccount pulumi.StringPtrInput
	// Contains model information necessary to perform batch prediction without requiring uploading to model registry. Exactly one of model and unmanaged_container_model must be set.
	UnmanagedContainerModel GoogleCloudAiplatformV1UnmanagedContainerModelPtrInput
}

The set of arguments for constructing a BatchPredictionJob resource.

func (BatchPredictionJobArgs) ElementType 

func (BatchPredictionJobArgs) ElementType() reflect.Type

type BatchPredictionJobInput 

type BatchPredictionJobInput interface {
	pulumi.Input

	ToBatchPredictionJobOutput() BatchPredictionJobOutput
	ToBatchPredictionJobOutputWithContext(ctx context.Context) BatchPredictionJobOutput
}

type BatchPredictionJobOutput 

type BatchPredictionJobOutput struct{ *pulumi.OutputState }

func (BatchPredictionJobOutput) CompletionStats 

func (o BatchPredictionJobOutput) CompletionStats() GoogleCloudAiplatformV1CompletionStatsResponseOutput

Statistics on completed and failed prediction instances.

func (BatchPredictionJobOutput) CreateTime 

func (o BatchPredictionJobOutput) CreateTime() pulumi.StringOutput

Time when the BatchPredictionJob was created.

func (BatchPredictionJobOutput) DedicatedResources 

func (o BatchPredictionJobOutput) DedicatedResources() GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput

The config of resources used by the Model during the batch prediction. If the Model supports DEDICATED_RESOURCES this config may be provided (and the job will use these resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config must be provided.

func (BatchPredictionJobOutput) DisableContainerLogging 

func (o BatchPredictionJobOutput) DisableContainerLogging() pulumi.BoolOutput

For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.

func (BatchPredictionJobOutput) DisplayName 

func (o BatchPredictionJobOutput) DisplayName() pulumi.StringOutput

The user-defined name of this BatchPredictionJob.

func (BatchPredictionJobOutput) ElementType 

func (BatchPredictionJobOutput) ElementType() reflect.Type

func (BatchPredictionJobOutput) EncryptionSpec 

func (o BatchPredictionJobOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key.

func (BatchPredictionJobOutput) EndTime 

func (o BatchPredictionJobOutput) EndTime() pulumi.StringOutput

Time when the BatchPredictionJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.

func (BatchPredictionJobOutput) Error 

func (o BatchPredictionJobOutput) Error() GoogleRpcStatusResponseOutput

Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

func (BatchPredictionJobOutput) ExplanationSpec 

func (o BatchPredictionJobOutput) ExplanationSpec() GoogleCloudAiplatformV1ExplanationSpecResponseOutput

Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to `true`. This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited.

func (BatchPredictionJobOutput) GenerateExplanation 

func (o BatchPredictionJobOutput) GenerateExplanation() pulumi.BoolOutput

Generate explanation with the batch prediction results. When set to `true`, the batch prediction output changes based on the `predictions_format` field of the BatchPredictionJob.output_config object: * `bigquery`: output includes a column named `explanation`. The value is a struct that conforms to the Explanation object. * `jsonl`: The JSON objects on each line include an additional entry keyed `explanation`. The value of the entry is a JSON object that conforms to the Explanation object. * `csv`: Generating explanations for CSV format is not supported. If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated.

func (BatchPredictionJobOutput) InputConfig 

func (o BatchPredictionJobOutput) InputConfig() GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput

Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri.

func (BatchPredictionJobOutput) InstanceConfig 

func (o BatchPredictionJobOutput) InstanceConfig() GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput

Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.

func (BatchPredictionJobOutput) Labels 

func (o BatchPredictionJobOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize BatchPredictionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (BatchPredictionJobOutput) Location 

func (o BatchPredictionJobOutput) Location() pulumi.StringOutput

func (BatchPredictionJobOutput) ManualBatchTuningParameters 

func (o BatchPredictionJobOutput) ManualBatchTuningParameters() GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput

Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself).

func (BatchPredictionJobOutput) Model 

func (o BatchPredictionJobOutput) Model() pulumi.StringOutput

The name of the Model resource that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources. Exactly one of model and unmanaged_container_model must be set. The model resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed. The model resource could also be a publisher model. Example: `publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`

func (BatchPredictionJobOutput) ModelParameters 

func (o BatchPredictionJobOutput) ModelParameters() pulumi.AnyOutput

The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.

func (BatchPredictionJobOutput) ModelVersionId 

func (o BatchPredictionJobOutput) ModelVersionId() pulumi.StringOutput

The version ID of the Model that produces the predictions via this job.

func (BatchPredictionJobOutput) Name 

func (o BatchPredictionJobOutput) Name() pulumi.StringOutput

Resource name of the BatchPredictionJob.

func (BatchPredictionJobOutput) OutputConfig 

func (o BatchPredictionJobOutput) OutputConfig() GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput

The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of Model's PredictSchemata's instance_schema_uri and prediction_schema_uri.

func (BatchPredictionJobOutput) OutputInfo 

func (o BatchPredictionJobOutput) OutputInfo() GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput

Information further describing the output of this job.

func (BatchPredictionJobOutput) PartialFailures 

func (o BatchPredictionJobOutput) PartialFailures() GoogleRpcStatusResponseArrayOutput

Partial failures encountered. For example, single files that can't be read. This field never exceeds 20 entries. Status details fields contain standard Google Cloud error details.

func (BatchPredictionJobOutput) Project 

func (o BatchPredictionJobOutput) Project() pulumi.StringOutput

func (BatchPredictionJobOutput) ResourcesConsumed 

func (o BatchPredictionJobOutput) ResourcesConsumed() GoogleCloudAiplatformV1ResourcesConsumedResponseOutput

Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes. Note: This field currently may be not populated for batch predictions that use AutoML Models.

func (BatchPredictionJobOutput) ServiceAccount 

func (o BatchPredictionJobOutput) ServiceAccount() pulumi.StringOutput

The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.

func (BatchPredictionJobOutput) StartTime 

func (o BatchPredictionJobOutput) StartTime() pulumi.StringOutput

Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state.

func (BatchPredictionJobOutput) State 

func (o BatchPredictionJobOutput) State() pulumi.StringOutput

The detailed state of the job.

func (BatchPredictionJobOutput) ToBatchPredictionJobOutput 

func (o BatchPredictionJobOutput) ToBatchPredictionJobOutput() BatchPredictionJobOutput

func (BatchPredictionJobOutput) ToBatchPredictionJobOutputWithContext 

func (o BatchPredictionJobOutput) ToBatchPredictionJobOutputWithContext(ctx context.Context) BatchPredictionJobOutput

func (BatchPredictionJobOutput) UnmanagedContainerModel 

func (o BatchPredictionJobOutput) UnmanagedContainerModel() GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput

Contains model information necessary to perform batch prediction without requiring uploading to model registry. Exactly one of model and unmanaged_container_model must be set.

func (BatchPredictionJobOutput) UpdateTime 

func (o BatchPredictionJobOutput) UpdateTime() pulumi.StringOutput

Time when the BatchPredictionJob was most recently updated.

type BatchPredictionJobState 

type BatchPredictionJobState struct {
}

func (BatchPredictionJobState) ElementType 

func (BatchPredictionJobState) ElementType() reflect.Type

type Context 

type Context struct {
	pulumi.CustomResourceState

	// The {context} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`. If not provided, the Context's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Contexts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Context.)
	ContextId pulumi.StringPtrOutput `pulumi:"contextId"`
	// Timestamp when this Context was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Description of the Context
	Description pulumi.StringOutput `pulumi:"description"`
	// User provided display name of the Context. May be up to 128 Unicode characters.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
	Metadata        pulumi.StringMapOutput `pulumi:"metadata"`
	MetadataStoreId pulumi.StringOutput    `pulumi:"metadataStoreId"`
	// Immutable. The resource name of the Context.
	Name pulumi.StringOutput `pulumi:"name"`
	// A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
	ParentContexts pulumi.StringArrayOutput `pulumi:"parentContexts"`
	Project        pulumi.StringOutput      `pulumi:"project"`
	// The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaTitle pulumi.StringOutput `pulumi:"schemaTitle"`
	// The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaVersion pulumi.StringOutput `pulumi:"schemaVersion"`
	// Timestamp when this Context was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a Context associated with a MetadataStore.

func GetContext 

func GetContext(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *ContextState, opts ...pulumi.ResourceOption) (*Context, error)

GetContext gets an existing Context resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewContext 

func NewContext(ctx *pulumi.Context,
	name string, args *ContextArgs, opts ...pulumi.ResourceOption) (*Context, error)

NewContext registers a new resource with the given unique name, arguments, and options.

func (*Context) ElementType 

func (*Context) ElementType() reflect.Type

func (*Context) ToContextOutput 

func (i *Context) ToContextOutput() ContextOutput

func (*Context) ToContextOutputWithContext 

func (i *Context) ToContextOutputWithContext(ctx context.Context) ContextOutput

type ContextArgs 

type ContextArgs struct {
	// The {context} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`. If not provided, the Context's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Contexts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Context.)
	ContextId pulumi.StringPtrInput
	// Description of the Context
	Description pulumi.StringPtrInput
	// User provided display name of the Context. May be up to 128 Unicode characters.
	DisplayName pulumi.StringPtrInput
	// An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
	Metadata        pulumi.StringMapInput
	MetadataStoreId pulumi.StringInput
	// Immutable. The resource name of the Context.
	Name    pulumi.StringPtrInput
	Project pulumi.StringPtrInput
	// The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaTitle pulumi.StringPtrInput
	// The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaVersion pulumi.StringPtrInput
}

The set of arguments for constructing a Context resource.

func (ContextArgs) ElementType 

func (ContextArgs) ElementType() reflect.Type

type ContextInput 

type ContextInput interface {
	pulumi.Input

	ToContextOutput() ContextOutput
	ToContextOutputWithContext(ctx context.Context) ContextOutput
}

type ContextOutput 

type ContextOutput struct{ *pulumi.OutputState }

func (ContextOutput) ContextId 

func (o ContextOutput) ContextId() pulumi.StringPtrOutput

The {context} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`. If not provided, the Context's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Contexts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Context.)

func (ContextOutput) CreateTime 

func (o ContextOutput) CreateTime() pulumi.StringOutput

Timestamp when this Context was created.

func (ContextOutput) Description 

func (o ContextOutput) Description() pulumi.StringOutput

Description of the Context

func (ContextOutput) DisplayName 

func (o ContextOutput) DisplayName() pulumi.StringOutput

User provided display name of the Context. May be up to 128 Unicode characters.

func (ContextOutput) ElementType 

func (ContextOutput) ElementType() reflect.Type

func (ContextOutput) Etag 

func (o ContextOutput) Etag() pulumi.StringOutput

An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (ContextOutput) Labels 

func (o ContextOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).

func (ContextOutput) Location 

func (o ContextOutput) Location() pulumi.StringOutput

func (ContextOutput) Metadata 

func (o ContextOutput) Metadata() pulumi.StringMapOutput

Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.

func (ContextOutput) MetadataStoreId 

func (o ContextOutput) MetadataStoreId() pulumi.StringOutput

func (ContextOutput) Name 

func (o ContextOutput) Name() pulumi.StringOutput

Immutable. The resource name of the Context.

func (ContextOutput) ParentContexts 

func (o ContextOutput) ParentContexts() pulumi.StringArrayOutput

A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.

func (ContextOutput) Project 

func (o ContextOutput) Project() pulumi.StringOutput

func (ContextOutput) SchemaTitle 

func (o ContextOutput) SchemaTitle() pulumi.StringOutput

The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (ContextOutput) SchemaVersion 

func (o ContextOutput) SchemaVersion() pulumi.StringOutput

The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (ContextOutput) ToContextOutput 

func (o ContextOutput) ToContextOutput() ContextOutput

func (ContextOutput) ToContextOutputWithContext 

func (o ContextOutput) ToContextOutputWithContext(ctx context.Context) ContextOutput

func (ContextOutput) UpdateTime 

func (o ContextOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Context was last updated.

type ContextState 

type ContextState struct {
}

func (ContextState) ElementType 

func (ContextState) ElementType() reflect.Type

type CustomJob 

type CustomJob struct {
	pulumi.CustomResourceState

	// Time when the CustomJob was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// The display name of the CustomJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Customer-managed encryption key options for a CustomJob. If this is set, then all resources created by the CustomJob will be encrypted with the provided encryption key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// Time when the CustomJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
	EndTime pulumi.StringOutput `pulumi:"endTime"`
	// Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.
	Error GoogleRpcStatusResponseOutput `pulumi:"error"`
	// Job spec.
	JobSpec GoogleCloudAiplatformV1CustomJobSpecResponseOutput `pulumi:"jobSpec"`
	// The labels with user-defined metadata to organize CustomJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Resource name of a CustomJob.
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.
	StartTime pulumi.StringOutput `pulumi:"startTime"`
	// The detailed state of the job.
	State pulumi.StringOutput `pulumi:"state"`
	// Time when the CustomJob was most recently updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
	// URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if job_spec.enable_web_access is `true`. The keys are names of each node in the training job; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.
	WebAccessUris pulumi.StringMapOutput `pulumi:"webAccessUris"`
}

Creates a CustomJob. A created CustomJob right away will be attempted to be run. Auto-naming is currently not supported for this resource.

func GetCustomJob 

func GetCustomJob(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *CustomJobState, opts ...pulumi.ResourceOption) (*CustomJob, error)

GetCustomJob gets an existing CustomJob resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewCustomJob 

func NewCustomJob(ctx *pulumi.Context,
	name string, args *CustomJobArgs, opts ...pulumi.ResourceOption) (*CustomJob, error)

NewCustomJob registers a new resource with the given unique name, arguments, and options.

func (*CustomJob) ElementType 

func (*CustomJob) ElementType() reflect.Type

func (*CustomJob) ToCustomJobOutput 

func (i *CustomJob) ToCustomJobOutput() CustomJobOutput

func (*CustomJob) ToCustomJobOutputWithContext 

func (i *CustomJob) ToCustomJobOutputWithContext(ctx context.Context) CustomJobOutput

type CustomJobArgs 

type CustomJobArgs struct {
	// The display name of the CustomJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringInput
	// Customer-managed encryption key options for a CustomJob. If this is set, then all resources created by the CustomJob will be encrypted with the provided encryption key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// Job spec.
	JobSpec GoogleCloudAiplatformV1CustomJobSpecInput
	// The labels with user-defined metadata to organize CustomJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	Project  pulumi.StringPtrInput
}

The set of arguments for constructing a CustomJob resource.

func (CustomJobArgs) ElementType 

func (CustomJobArgs) ElementType() reflect.Type

type CustomJobInput 

type CustomJobInput interface {
	pulumi.Input

	ToCustomJobOutput() CustomJobOutput
	ToCustomJobOutputWithContext(ctx context.Context) CustomJobOutput
}

type CustomJobOutput 

type CustomJobOutput struct{ *pulumi.OutputState }

func (CustomJobOutput) CreateTime 

func (o CustomJobOutput) CreateTime() pulumi.StringOutput

Time when the CustomJob was created.

func (CustomJobOutput) DisplayName 

func (o CustomJobOutput) DisplayName() pulumi.StringOutput

The display name of the CustomJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (CustomJobOutput) ElementType 

func (CustomJobOutput) ElementType() reflect.Type

func (CustomJobOutput) EncryptionSpec 

func (o CustomJobOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key options for a CustomJob. If this is set, then all resources created by the CustomJob will be encrypted with the provided encryption key.

func (CustomJobOutput) EndTime 

func (o CustomJobOutput) EndTime() pulumi.StringOutput

Time when the CustomJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.

func (CustomJobOutput) Error 

func (o CustomJobOutput) Error() GoogleRpcStatusResponseOutput

Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.

func (CustomJobOutput) JobSpec 

func (o CustomJobOutput) JobSpec() GoogleCloudAiplatformV1CustomJobSpecResponseOutput

Job spec.

func (CustomJobOutput) Labels 

func (o CustomJobOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize CustomJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (CustomJobOutput) Location 

func (o CustomJobOutput) Location() pulumi.StringOutput

func (CustomJobOutput) Name 

func (o CustomJobOutput) Name() pulumi.StringOutput

Resource name of a CustomJob.

func (CustomJobOutput) Project 

func (o CustomJobOutput) Project() pulumi.StringOutput

func (CustomJobOutput) StartTime 

func (o CustomJobOutput) StartTime() pulumi.StringOutput

Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.

func (CustomJobOutput) State 

func (o CustomJobOutput) State() pulumi.StringOutput

The detailed state of the job.

func (CustomJobOutput) ToCustomJobOutput 

func (o CustomJobOutput) ToCustomJobOutput() CustomJobOutput

func (CustomJobOutput) ToCustomJobOutputWithContext 

func (o CustomJobOutput) ToCustomJobOutputWithContext(ctx context.Context) CustomJobOutput

func (CustomJobOutput) UpdateTime 

func (o CustomJobOutput) UpdateTime() pulumi.StringOutput

Time when the CustomJob was most recently updated.

func (CustomJobOutput) WebAccessUris 

func (o CustomJobOutput) WebAccessUris() pulumi.StringMapOutput

URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if job_spec.enable_web_access is `true`. The keys are names of each node in the training job; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.

type CustomJobState 

type CustomJobState struct {
}

func (CustomJobState) ElementType 

func (CustomJobState) ElementType() reflect.Type

type DataLabelingJob 

type DataLabelingJob struct {
	pulumi.CustomResourceState

	// Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy.
	ActiveLearningConfig GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput `pulumi:"activeLearningConfig"`
	// Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	AnnotationLabels pulumi.StringMapOutput `pulumi:"annotationLabels"`
	// Timestamp when this DataLabelingJob was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.
	CurrentSpend GoogleTypeMoneyResponseOutput `pulumi:"currentSpend"`
	// Dataset resource names. Right now we only support labeling from a single Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`
	Datasets pulumi.StringArrayOutput `pulumi:"datasets"`
	// The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// DataLabelingJob errors. It is only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.
	Error GoogleRpcStatusResponseOutput `pulumi:"error"`
	// Input config parameters for the DataLabelingJob.
	Inputs pulumi.AnyOutput `pulumi:"inputs"`
	// Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder.
	InputsSchemaUri pulumi.StringOutput `pulumi:"inputsSchemaUri"`
	// The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.
	InstructionUri pulumi.StringOutput `pulumi:"instructionUri"`
	// Number of labelers to work on each DataItem.
	LabelerCount pulumi.IntOutput `pulumi:"labelerCount"`
	// Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.
	LabelingProgress pulumi.IntOutput `pulumi:"labelingProgress"`
	// The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Resource name of the DataLabelingJob.
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// The SpecialistPools' resource names associated with this job.
	SpecialistPools pulumi.StringArrayOutput `pulumi:"specialistPools"`
	// The detailed state of the job.
	State pulumi.StringOutput `pulumi:"state"`
	// Timestamp when this DataLabelingJob was updated most recently.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a DataLabelingJob. Auto-naming is currently not supported for this resource.

func GetDataLabelingJob 

func GetDataLabelingJob(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *DataLabelingJobState, opts ...pulumi.ResourceOption) (*DataLabelingJob, error)

GetDataLabelingJob gets an existing DataLabelingJob resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewDataLabelingJob 

func NewDataLabelingJob(ctx *pulumi.Context,
	name string, args *DataLabelingJobArgs, opts ...pulumi.ResourceOption) (*DataLabelingJob, error)

NewDataLabelingJob registers a new resource with the given unique name, arguments, and options.

func (*DataLabelingJob) ElementType 

func (*DataLabelingJob) ElementType() reflect.Type

func (*DataLabelingJob) ToDataLabelingJobOutput 

func (i *DataLabelingJob) ToDataLabelingJobOutput() DataLabelingJobOutput

func (*DataLabelingJob) ToDataLabelingJobOutputWithContext 

func (i *DataLabelingJob) ToDataLabelingJobOutputWithContext(ctx context.Context) DataLabelingJobOutput

type DataLabelingJobArgs 

type DataLabelingJobArgs struct {
	// Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy.
	ActiveLearningConfig GoogleCloudAiplatformV1ActiveLearningConfigPtrInput
	// Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	AnnotationLabels pulumi.StringMapInput
	// Dataset resource names. Right now we only support labeling from a single Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`
	Datasets pulumi.StringArrayInput
	// The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.
	DisplayName pulumi.StringInput
	// Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// Input config parameters for the DataLabelingJob.
	Inputs pulumi.Input
	// Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder.
	InputsSchemaUri pulumi.StringInput
	// The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.
	InstructionUri pulumi.StringInput
	// Number of labelers to work on each DataItem.
	LabelerCount pulumi.IntInput
	// The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	Project  pulumi.StringPtrInput
	// The SpecialistPools' resource names associated with this job.
	SpecialistPools pulumi.StringArrayInput
}

The set of arguments for constructing a DataLabelingJob resource.

func (DataLabelingJobArgs) ElementType 

func (DataLabelingJobArgs) ElementType() reflect.Type

type DataLabelingJobInput 

type DataLabelingJobInput interface {
	pulumi.Input

	ToDataLabelingJobOutput() DataLabelingJobOutput
	ToDataLabelingJobOutputWithContext(ctx context.Context) DataLabelingJobOutput
}

type DataLabelingJobOutput 

type DataLabelingJobOutput struct{ *pulumi.OutputState }

func (DataLabelingJobOutput) ActiveLearningConfig 

func (o DataLabelingJobOutput) ActiveLearningConfig() GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput

Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy.

func (DataLabelingJobOutput) AnnotationLabels 

func (o DataLabelingJobOutput) AnnotationLabels() pulumi.StringMapOutput

Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (DataLabelingJobOutput) CreateTime 

func (o DataLabelingJobOutput) CreateTime() pulumi.StringOutput

Timestamp when this DataLabelingJob was created.

func (DataLabelingJobOutput) CurrentSpend 

func (o DataLabelingJobOutput) CurrentSpend() GoogleTypeMoneyResponseOutput

Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.

func (DataLabelingJobOutput) Datasets 

func (o DataLabelingJobOutput) Datasets() pulumi.StringArrayOutput

Dataset resource names. Right now we only support labeling from a single Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`

func (DataLabelingJobOutput) DisplayName 

func (o DataLabelingJobOutput) DisplayName() pulumi.StringOutput

The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.

func (DataLabelingJobOutput) ElementType 

func (DataLabelingJobOutput) ElementType() reflect.Type

func (DataLabelingJobOutput) EncryptionSpec 

func (o DataLabelingJobOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.

func (DataLabelingJobOutput) Error 

func (o DataLabelingJobOutput) Error() GoogleRpcStatusResponseOutput

DataLabelingJob errors. It is only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.

func (DataLabelingJobOutput) Inputs 

func (o DataLabelingJobOutput) Inputs() pulumi.AnyOutput

Input config parameters for the DataLabelingJob.

func (DataLabelingJobOutput) InputsSchemaUri 

func (o DataLabelingJobOutput) InputsSchemaUri() pulumi.StringOutput

Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder.

func (DataLabelingJobOutput) InstructionUri 

func (o DataLabelingJobOutput) InstructionUri() pulumi.StringOutput

The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.

func (DataLabelingJobOutput) LabelerCount 

func (o DataLabelingJobOutput) LabelerCount() pulumi.IntOutput

Number of labelers to work on each DataItem.

func (DataLabelingJobOutput) LabelingProgress 

func (o DataLabelingJobOutput) LabelingProgress() pulumi.IntOutput

Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.

func (DataLabelingJobOutput) Labels 

func (o DataLabelingJobOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title.

func (DataLabelingJobOutput) Location 

func (o DataLabelingJobOutput) Location() pulumi.StringOutput

func (DataLabelingJobOutput) Name 

func (o DataLabelingJobOutput) Name() pulumi.StringOutput

Resource name of the DataLabelingJob.

func (DataLabelingJobOutput) Project 

func (o DataLabelingJobOutput) Project() pulumi.StringOutput

func (DataLabelingJobOutput) SpecialistPools 

func (o DataLabelingJobOutput) SpecialistPools() pulumi.StringArrayOutput

The SpecialistPools' resource names associated with this job.

func (DataLabelingJobOutput) State 

func (o DataLabelingJobOutput) State() pulumi.StringOutput

The detailed state of the job.

func (DataLabelingJobOutput) ToDataLabelingJobOutput 

func (o DataLabelingJobOutput) ToDataLabelingJobOutput() DataLabelingJobOutput

func (DataLabelingJobOutput) ToDataLabelingJobOutputWithContext 

func (o DataLabelingJobOutput) ToDataLabelingJobOutputWithContext(ctx context.Context) DataLabelingJobOutput

func (DataLabelingJobOutput) UpdateTime 

func (o DataLabelingJobOutput) UpdateTime() pulumi.StringOutput

Timestamp when this DataLabelingJob was updated most recently.

type DataLabelingJobState 

type DataLabelingJobState struct {
}

func (DataLabelingJobState) ElementType 

func (DataLabelingJobState) ElementType() reflect.Type

type Dataset 

type Dataset struct {
	pulumi.CustomResourceState

	// Timestamp when this Dataset was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// The number of DataItems in this Dataset. Only apply for non-structured Dataset.
	DataItemCount pulumi.StringOutput `pulumi:"dataItemCount"`
	// The description of the Dataset.
	Description pulumi.StringOutput `pulumi:"description"`
	// The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Dataset: * "aiplatform.googleapis.com/dataset_metadata_schema": output only, its value is the metadata_schema's title.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Additional information about the Dataset.
	Metadata pulumi.AnyOutput `pulumi:"metadata"`
	// The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
	MetadataArtifact pulumi.StringOutput `pulumi:"metadataArtifact"`
	// Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
	MetadataSchemaUri pulumi.StringOutput `pulumi:"metadataSchemaUri"`
	// The resource name of the Dataset.
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
	SavedQueries GoogleCloudAiplatformV1SavedQueryResponseArrayOutput `pulumi:"savedQueries"`
	// Timestamp when this Dataset was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a Dataset. Auto-naming is currently not supported for this resource.

func GetDataset 

func GetDataset(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *DatasetState, opts ...pulumi.ResourceOption) (*Dataset, error)

GetDataset gets an existing Dataset resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewDataset 

func NewDataset(ctx *pulumi.Context,
	name string, args *DatasetArgs, opts ...pulumi.ResourceOption) (*Dataset, error)

NewDataset registers a new resource with the given unique name, arguments, and options.

func (*Dataset) ElementType 

func (*Dataset) ElementType() reflect.Type

func (*Dataset) ToDatasetOutput 

func (i *Dataset) ToDatasetOutput() DatasetOutput

func (*Dataset) ToDatasetOutputWithContext 

func (i *Dataset) ToDatasetOutputWithContext(ctx context.Context) DatasetOutput

type DatasetArgs 

type DatasetArgs struct {
	// The description of the Dataset.
	Description pulumi.StringPtrInput
	// The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringInput
	// Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Dataset: * "aiplatform.googleapis.com/dataset_metadata_schema": output only, its value is the metadata_schema's title.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// Additional information about the Dataset.
	Metadata pulumi.Input
	// Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
	MetadataSchemaUri pulumi.StringInput
	Project           pulumi.StringPtrInput
	// All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
	SavedQueries GoogleCloudAiplatformV1SavedQueryArrayInput
}

The set of arguments for constructing a Dataset resource.

func (DatasetArgs) ElementType 

func (DatasetArgs) ElementType() reflect.Type

type DatasetInput 

type DatasetInput interface {
	pulumi.Input

	ToDatasetOutput() DatasetOutput
	ToDatasetOutputWithContext(ctx context.Context) DatasetOutput
}

type DatasetOutput 

type DatasetOutput struct{ *pulumi.OutputState }

func (DatasetOutput) CreateTime 

func (o DatasetOutput) CreateTime() pulumi.StringOutput

Timestamp when this Dataset was created.

func (DatasetOutput) DataItemCount 

func (o DatasetOutput) DataItemCount() pulumi.StringOutput

The number of DataItems in this Dataset. Only apply for non-structured Dataset.

func (DatasetOutput) Description 

func (o DatasetOutput) Description() pulumi.StringOutput

The description of the Dataset.

func (DatasetOutput) DisplayName 

func (o DatasetOutput) DisplayName() pulumi.StringOutput

The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (DatasetOutput) ElementType 

func (DatasetOutput) ElementType() reflect.Type

func (DatasetOutput) EncryptionSpec 

func (o DatasetOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key.

func (DatasetOutput) Etag 

func (o DatasetOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (DatasetOutput) Labels 

func (o DatasetOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Dataset: * "aiplatform.googleapis.com/dataset_metadata_schema": output only, its value is the metadata_schema's title.

func (DatasetOutput) Location 

func (o DatasetOutput) Location() pulumi.StringOutput

func (DatasetOutput) Metadata 

func (o DatasetOutput) Metadata() pulumi.AnyOutput

Additional information about the Dataset.

func (DatasetOutput) MetadataArtifact 

func (o DatasetOutput) MetadataArtifact() pulumi.StringOutput

The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.

func (DatasetOutput) MetadataSchemaUri 

func (o DatasetOutput) MetadataSchemaUri() pulumi.StringOutput

Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.

func (DatasetOutput) Name 

func (o DatasetOutput) Name() pulumi.StringOutput

The resource name of the Dataset.

func (DatasetOutput) Project 

func (o DatasetOutput) Project() pulumi.StringOutput

func (DatasetOutput) SavedQueries 

func (o DatasetOutput) SavedQueries() GoogleCloudAiplatformV1SavedQueryResponseArrayOutput

All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.

func (DatasetOutput) ToDatasetOutput 

func (o DatasetOutput) ToDatasetOutput() DatasetOutput

func (DatasetOutput) ToDatasetOutputWithContext 

func (o DatasetOutput) ToDatasetOutputWithContext(ctx context.Context) DatasetOutput

func (DatasetOutput) UpdateTime 

func (o DatasetOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Dataset was last updated.

type DatasetState 

type DatasetState struct {
}

func (DatasetState) ElementType 

func (DatasetState) ElementType() reflect.Type

type DatasetVersion 

type DatasetVersion struct {
	pulumi.CustomResourceState

	// Name of the associated BigQuery dataset.
	BigQueryDatasetName pulumi.StringOutput `pulumi:"bigQueryDatasetName"`
	// Timestamp when this DatasetVersion was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	DatasetId  pulumi.StringOutput `pulumi:"datasetId"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag     pulumi.StringOutput `pulumi:"etag"`
	Location pulumi.StringOutput `pulumi:"location"`
	// The resource name of the DatasetVersion.
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// Timestamp when this DatasetVersion was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Create a version from a Dataset. Auto-naming is currently not supported for this resource.

func GetDatasetVersion 

func GetDatasetVersion(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *DatasetVersionState, opts ...pulumi.ResourceOption) (*DatasetVersion, error)

GetDatasetVersion gets an existing DatasetVersion resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewDatasetVersion 

func NewDatasetVersion(ctx *pulumi.Context,
	name string, args *DatasetVersionArgs, opts ...pulumi.ResourceOption) (*DatasetVersion, error)

NewDatasetVersion registers a new resource with the given unique name, arguments, and options.

func (*DatasetVersion) ElementType 

func (*DatasetVersion) ElementType() reflect.Type

func (*DatasetVersion) ToDatasetVersionOutput 

func (i *DatasetVersion) ToDatasetVersionOutput() DatasetVersionOutput

func (*DatasetVersion) ToDatasetVersionOutputWithContext 

func (i *DatasetVersion) ToDatasetVersionOutputWithContext(ctx context.Context) DatasetVersionOutput

type DatasetVersionArgs 

type DatasetVersionArgs struct {
	DatasetId pulumi.StringInput
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag     pulumi.StringPtrInput
	Location pulumi.StringPtrInput
	Project  pulumi.StringPtrInput
}

The set of arguments for constructing a DatasetVersion resource.

func (DatasetVersionArgs) ElementType 

func (DatasetVersionArgs) ElementType() reflect.Type

type DatasetVersionInput 

type DatasetVersionInput interface {
	pulumi.Input

	ToDatasetVersionOutput() DatasetVersionOutput
	ToDatasetVersionOutputWithContext(ctx context.Context) DatasetVersionOutput
}

type DatasetVersionOutput 

type DatasetVersionOutput struct{ *pulumi.OutputState }

func (DatasetVersionOutput) BigQueryDatasetName 

func (o DatasetVersionOutput) BigQueryDatasetName() pulumi.StringOutput

Name of the associated BigQuery dataset.

func (DatasetVersionOutput) CreateTime 

func (o DatasetVersionOutput) CreateTime() pulumi.StringOutput

Timestamp when this DatasetVersion was created.

func (DatasetVersionOutput) DatasetId 

func (o DatasetVersionOutput) DatasetId() pulumi.StringOutput

func (DatasetVersionOutput) ElementType 

func (DatasetVersionOutput) ElementType() reflect.Type

func (DatasetVersionOutput) Etag 

func (o DatasetVersionOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (DatasetVersionOutput) Location 

func (o DatasetVersionOutput) Location() pulumi.StringOutput

func (DatasetVersionOutput) Name 

func (o DatasetVersionOutput) Name() pulumi.StringOutput

The resource name of the DatasetVersion.

func (DatasetVersionOutput) Project 

func (o DatasetVersionOutput) Project() pulumi.StringOutput

func (DatasetVersionOutput) ToDatasetVersionOutput 

func (o DatasetVersionOutput) ToDatasetVersionOutput() DatasetVersionOutput

func (DatasetVersionOutput) ToDatasetVersionOutputWithContext 

func (o DatasetVersionOutput) ToDatasetVersionOutputWithContext(ctx context.Context) DatasetVersionOutput

func (DatasetVersionOutput) UpdateTime 

func (o DatasetVersionOutput) UpdateTime() pulumi.StringOutput

Timestamp when this DatasetVersion was last updated.

type DatasetVersionState 

type DatasetVersionState struct {
}

func (DatasetVersionState) ElementType 

func (DatasetVersionState) ElementType() reflect.Type

type DeploymentResourcePool 

type DeploymentResourcePool struct {
	pulumi.CustomResourceState

	// Timestamp when this DeploymentResourcePool was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// The underlying DedicatedResources that the DeploymentResourcePool uses.
	DedicatedResources GoogleCloudAiplatformV1DedicatedResourcesResponseOutput `pulumi:"dedicatedResources"`
	Location           pulumi.StringOutput                                     `pulumi:"location"`
	// Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
}

Create a DeploymentResourcePool.

func GetDeploymentResourcePool 

func GetDeploymentResourcePool(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *DeploymentResourcePoolState, opts ...pulumi.ResourceOption) (*DeploymentResourcePool, error)

GetDeploymentResourcePool gets an existing DeploymentResourcePool resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewDeploymentResourcePool 

func NewDeploymentResourcePool(ctx *pulumi.Context,
	name string, args *DeploymentResourcePoolArgs, opts ...pulumi.ResourceOption) (*DeploymentResourcePool, error)

NewDeploymentResourcePool registers a new resource with the given unique name, arguments, and options.

func (*DeploymentResourcePool) ElementType 

func (*DeploymentResourcePool) ElementType() reflect.Type

func (*DeploymentResourcePool) ToDeploymentResourcePoolOutput 

func (i *DeploymentResourcePool) ToDeploymentResourcePoolOutput() DeploymentResourcePoolOutput

func (*DeploymentResourcePool) ToDeploymentResourcePoolOutputWithContext 

func (i *DeploymentResourcePool) ToDeploymentResourcePoolOutputWithContext(ctx context.Context) DeploymentResourcePoolOutput

type DeploymentResourcePoolArgs 

type DeploymentResourcePoolArgs struct {
	// The underlying DedicatedResources that the DeploymentResourcePool uses.
	DedicatedResources GoogleCloudAiplatformV1DedicatedResourcesInput
	// The ID to use for the DeploymentResourcePool, which will become the final component of the DeploymentResourcePool's resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`.
	DeploymentResourcePoolId pulumi.StringInput
	Location                 pulumi.StringPtrInput
	// Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`
	Name    pulumi.StringPtrInput
	Project pulumi.StringPtrInput
}

The set of arguments for constructing a DeploymentResourcePool resource.

func (DeploymentResourcePoolArgs) ElementType 

func (DeploymentResourcePoolArgs) ElementType() reflect.Type

type DeploymentResourcePoolInput 

type DeploymentResourcePoolInput interface {
	pulumi.Input

	ToDeploymentResourcePoolOutput() DeploymentResourcePoolOutput
	ToDeploymentResourcePoolOutputWithContext(ctx context.Context) DeploymentResourcePoolOutput
}

type DeploymentResourcePoolOutput 

type DeploymentResourcePoolOutput struct{ *pulumi.OutputState }

func (DeploymentResourcePoolOutput) CreateTime 

func (o DeploymentResourcePoolOutput) CreateTime() pulumi.StringOutput

Timestamp when this DeploymentResourcePool was created.

func (DeploymentResourcePoolOutput) DedicatedResources 

func (o DeploymentResourcePoolOutput) DedicatedResources() GoogleCloudAiplatformV1DedicatedResourcesResponseOutput

The underlying DedicatedResources that the DeploymentResourcePool uses.

func (DeploymentResourcePoolOutput) ElementType 

func (DeploymentResourcePoolOutput) ElementType() reflect.Type

func (DeploymentResourcePoolOutput) Location 

func (o DeploymentResourcePoolOutput) Location() pulumi.StringOutput

func (DeploymentResourcePoolOutput) Name 

func (o DeploymentResourcePoolOutput) Name() pulumi.StringOutput

Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`

func (DeploymentResourcePoolOutput) Project 

func (o DeploymentResourcePoolOutput) Project() pulumi.StringOutput

func (DeploymentResourcePoolOutput) ToDeploymentResourcePoolOutput 

func (o DeploymentResourcePoolOutput) ToDeploymentResourcePoolOutput() DeploymentResourcePoolOutput

func (DeploymentResourcePoolOutput) ToDeploymentResourcePoolOutputWithContext 

func (o DeploymentResourcePoolOutput) ToDeploymentResourcePoolOutputWithContext(ctx context.Context) DeploymentResourcePoolOutput

type DeploymentResourcePoolState 

type DeploymentResourcePoolState struct {
}

func (DeploymentResourcePoolState) ElementType 

func (DeploymentResourcePoolState) ElementType() reflect.Type

type Endpoint 

type Endpoint struct {
	pulumi.CustomResourceState

	// Timestamp when this Endpoint was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// The models deployed in this Endpoint. To add or remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel respectively.
	DeployedModels GoogleCloudAiplatformV1DeployedModelResponseArrayOutput `pulumi:"deployedModels"`
	// The description of the Endpoint.
	Description pulumi.StringOutput `pulumi:"description"`
	// The display name of the Endpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.
	//
	// Deprecated: Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.
	EnablePrivateServiceConnect pulumi.BoolOutput `pulumi:"enablePrivateServiceConnect"`
	// Customer-managed encryption key spec for an Endpoint. If set, this Endpoint and all sub-resources of this Endpoint will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// Immutable. The ID to use for endpoint, which will become the final component of the endpoint resource name. If not provided, Vertex AI will generate a value for this ID. If the first character is a letter, this value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The last character must be a letter or number. If the first character is a number, this value may be up to 9 characters, and valid characters are `[0-9]` with no leading zeros. When using HTTP/JSON, this field is populated based on a query string argument, such as `?endpoint_id=12345`. This is the fallback for fields that are not included in either the URI or the body.
	EndpointId pulumi.StringPtrOutput `pulumi:"endpointId"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Resource name of the Model Monitoring job associated with this Endpoint if monitoring is enabled by JobService.CreateModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`
	ModelDeploymentMonitoringJob pulumi.StringOutput `pulumi:"modelDeploymentMonitoringJob"`
	// The resource name of the Endpoint.
	Name pulumi.StringOutput `pulumi:"name"`
	// Optional. The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks) to which the Endpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. Only one of the fields, network or enable_private_service_connect, can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where `{project}` is a project number, as in `12345`, and `{network}` is network name.
	Network pulumi.StringOutput `pulumi:"network"`
	// Configures the request-response logging for online prediction.
	PredictRequestResponseLoggingConfig GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput `pulumi:"predictRequestResponseLoggingConfig"`
	Project                             pulumi.StringOutput                                                      `pulumi:"project"`
	// A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If a DeployedModel's ID is not listed in this map, then it receives no traffic. The traffic percentage values must add up to 100, or map must be empty if the Endpoint is to not accept any traffic at a moment.
	TrafficSplit pulumi.StringMapOutput `pulumi:"trafficSplit"`
	// Timestamp when this Endpoint was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates an Endpoint. Auto-naming is currently not supported for this resource.

func GetEndpoint 

func GetEndpoint(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *EndpointState, opts ...pulumi.ResourceOption) (*Endpoint, error)

GetEndpoint gets an existing Endpoint resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewEndpoint 

func NewEndpoint(ctx *pulumi.Context,
	name string, args *EndpointArgs, opts ...pulumi.ResourceOption) (*Endpoint, error)

NewEndpoint registers a new resource with the given unique name, arguments, and options.

func (*Endpoint) ElementType 

func (*Endpoint) ElementType() reflect.Type

func (*Endpoint) ToEndpointOutput 

func (i *Endpoint) ToEndpointOutput() EndpointOutput

func (*Endpoint) ToEndpointOutputWithContext 

func (i *Endpoint) ToEndpointOutputWithContext(ctx context.Context) EndpointOutput

type EndpointArgs 

type EndpointArgs struct {
	// The description of the Endpoint.
	Description pulumi.StringPtrInput
	// The display name of the Endpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringInput
	// Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.
	//
	// Deprecated: Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.
	EnablePrivateServiceConnect pulumi.BoolPtrInput
	// Customer-managed encryption key spec for an Endpoint. If set, this Endpoint and all sub-resources of this Endpoint will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// Immutable. The ID to use for endpoint, which will become the final component of the endpoint resource name. If not provided, Vertex AI will generate a value for this ID. If the first character is a letter, this value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The last character must be a letter or number. If the first character is a number, this value may be up to 9 characters, and valid characters are `[0-9]` with no leading zeros. When using HTTP/JSON, this field is populated based on a query string argument, such as `?endpoint_id=12345`. This is the fallback for fields that are not included in either the URI or the body.
	EndpointId pulumi.StringPtrInput
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// Optional. The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks) to which the Endpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. Only one of the fields, network or enable_private_service_connect, can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where `{project}` is a project number, as in `12345`, and `{network}` is network name.
	Network pulumi.StringPtrInput
	// Configures the request-response logging for online prediction.
	PredictRequestResponseLoggingConfig GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrInput
	Project                             pulumi.StringPtrInput
	// A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If a DeployedModel's ID is not listed in this map, then it receives no traffic. The traffic percentage values must add up to 100, or map must be empty if the Endpoint is to not accept any traffic at a moment.
	TrafficSplit pulumi.StringMapInput
}

The set of arguments for constructing a Endpoint resource.

func (EndpointArgs) ElementType 

func (EndpointArgs) ElementType() reflect.Type

type EndpointInput 

type EndpointInput interface {
	pulumi.Input

	ToEndpointOutput() EndpointOutput
	ToEndpointOutputWithContext(ctx context.Context) EndpointOutput
}

type EndpointOutput 

type EndpointOutput struct{ *pulumi.OutputState }

func (EndpointOutput) CreateTime 

func (o EndpointOutput) CreateTime() pulumi.StringOutput

Timestamp when this Endpoint was created.

func (EndpointOutput) DeployedModels 

func (o EndpointOutput) DeployedModels() GoogleCloudAiplatformV1DeployedModelResponseArrayOutput

The models deployed in this Endpoint. To add or remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel respectively.

func (EndpointOutput) Description 

func (o EndpointOutput) Description() pulumi.StringOutput

The description of the Endpoint.

func (EndpointOutput) DisplayName 

func (o EndpointOutput) DisplayName() pulumi.StringOutput

The display name of the Endpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (EndpointOutput) ElementType 

func (EndpointOutput) ElementType() reflect.Type

func (EndpointOutput) EnablePrivateServiceConnect deprecated 

func (o EndpointOutput) EnablePrivateServiceConnect() pulumi.BoolOutput

Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.

Deprecated: Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.

func (EndpointOutput) EncryptionSpec 

func (o EndpointOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for an Endpoint. If set, this Endpoint and all sub-resources of this Endpoint will be secured by this key.

func (EndpointOutput) EndpointId 

func (o EndpointOutput) EndpointId() pulumi.StringPtrOutput

Immutable. The ID to use for endpoint, which will become the final component of the endpoint resource name. If not provided, Vertex AI will generate a value for this ID. If the first character is a letter, this value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The last character must be a letter or number. If the first character is a number, this value may be up to 9 characters, and valid characters are `[0-9]` with no leading zeros. When using HTTP/JSON, this field is populated based on a query string argument, such as `?endpoint_id=12345`. This is the fallback for fields that are not included in either the URI or the body.

func (EndpointOutput) Etag 

func (o EndpointOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (EndpointOutput) Labels 

func (o EndpointOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (EndpointOutput) Location 

func (o EndpointOutput) Location() pulumi.StringOutput

func (EndpointOutput) ModelDeploymentMonitoringJob 

func (o EndpointOutput) ModelDeploymentMonitoringJob() pulumi.StringOutput

Resource name of the Model Monitoring job associated with this Endpoint if monitoring is enabled by JobService.CreateModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`

func (EndpointOutput) Name 

func (o EndpointOutput) Name() pulumi.StringOutput

The resource name of the Endpoint.

func (EndpointOutput) Network 

func (o EndpointOutput) Network() pulumi.StringOutput

Optional. The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks) to which the Endpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. Only one of the fields, network or enable_private_service_connect, can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where `{project}` is a project number, as in `12345`, and `{network}` is network name.

func (EndpointOutput) PredictRequestResponseLoggingConfig 

func (o EndpointOutput) PredictRequestResponseLoggingConfig() GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput

Configures the request-response logging for online prediction.

func (EndpointOutput) Project 

func (o EndpointOutput) Project() pulumi.StringOutput

func (EndpointOutput) ToEndpointOutput 

func (o EndpointOutput) ToEndpointOutput() EndpointOutput

func (EndpointOutput) ToEndpointOutputWithContext 

func (o EndpointOutput) ToEndpointOutputWithContext(ctx context.Context) EndpointOutput

func (EndpointOutput) TrafficSplit 

func (o EndpointOutput) TrafficSplit() pulumi.StringMapOutput

A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If a DeployedModel's ID is not listed in this map, then it receives no traffic. The traffic percentage values must add up to 100, or map must be empty if the Endpoint is to not accept any traffic at a moment.

func (EndpointOutput) UpdateTime 

func (o EndpointOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Endpoint was last updated.

type EndpointState 

type EndpointState struct {
}

func (EndpointState) ElementType 

func (EndpointState) ElementType() reflect.Type

type EntityType 

type EntityType struct {
	pulumi.CustomResourceState

	// Timestamp when this EntityType was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Optional. Description of the EntityType.
	Description pulumi.StringOutput `pulumi:"description"`
	// Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a featurestore.
	EntityTypeId pulumi.StringOutput `pulumi:"entityTypeId"`
	// Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag           pulumi.StringOutput `pulumi:"etag"`
	FeaturestoreId pulumi.StringOutput `pulumi:"featurestoreId"`
	// Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
	MonitoringConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput `pulumi:"monitoringConfig"`
	// Immutable. Name of the EntityType. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
	Name pulumi.StringOutput `pulumi:"name"`
	// Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than `offline_storage_ttl_days` since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
	OfflineStorageTtlDays pulumi.IntOutput    `pulumi:"offlineStorageTtlDays"`
	Project               pulumi.StringOutput `pulumi:"project"`
	// Timestamp when this EntityType was most recently updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a new EntityType in a given Featurestore.

func GetEntityType 

func GetEntityType(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *EntityTypeState, opts ...pulumi.ResourceOption) (*EntityType, error)

GetEntityType gets an existing EntityType resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewEntityType 

func NewEntityType(ctx *pulumi.Context,
	name string, args *EntityTypeArgs, opts ...pulumi.ResourceOption) (*EntityType, error)

NewEntityType registers a new resource with the given unique name, arguments, and options.

func (*EntityType) ElementType 

func (*EntityType) ElementType() reflect.Type

func (*EntityType) ToEntityTypeOutput 

func (i *EntityType) ToEntityTypeOutput() EntityTypeOutput

func (*EntityType) ToEntityTypeOutputWithContext 

func (i *EntityType) ToEntityTypeOutputWithContext(ctx context.Context) EntityTypeOutput

type EntityTypeArgs 

type EntityTypeArgs struct {
	// Optional. Description of the EntityType.
	Description pulumi.StringPtrInput
	// Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a featurestore.
	EntityTypeId pulumi.StringInput
	// Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag           pulumi.StringPtrInput
	FeaturestoreId pulumi.StringInput
	// Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
	MonitoringConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrInput
	// Immutable. Name of the EntityType. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
	Name pulumi.StringPtrInput
	// Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than `offline_storage_ttl_days` since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
	OfflineStorageTtlDays pulumi.IntPtrInput
	Project               pulumi.StringPtrInput
}

The set of arguments for constructing a EntityType resource.

func (EntityTypeArgs) ElementType 

func (EntityTypeArgs) ElementType() reflect.Type

type EntityTypeInput 

type EntityTypeInput interface {
	pulumi.Input

	ToEntityTypeOutput() EntityTypeOutput
	ToEntityTypeOutputWithContext(ctx context.Context) EntityTypeOutput
}

type EntityTypeOutput 

type EntityTypeOutput struct{ *pulumi.OutputState }

func (EntityTypeOutput) CreateTime 

func (o EntityTypeOutput) CreateTime() pulumi.StringOutput

Timestamp when this EntityType was created.

func (EntityTypeOutput) Description 

func (o EntityTypeOutput) Description() pulumi.StringOutput

Optional. Description of the EntityType.

func (EntityTypeOutput) ElementType 

func (EntityTypeOutput) ElementType() reflect.Type

func (EntityTypeOutput) EntityTypeId 

func (o EntityTypeOutput) EntityTypeId() pulumi.StringOutput

Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a featurestore.

func (EntityTypeOutput) Etag 

func (o EntityTypeOutput) Etag() pulumi.StringOutput

Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (EntityTypeOutput) FeaturestoreId 

func (o EntityTypeOutput) FeaturestoreId() pulumi.StringOutput

func (EntityTypeOutput) Labels 

func (o EntityTypeOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (EntityTypeOutput) Location 

func (o EntityTypeOutput) Location() pulumi.StringOutput

func (EntityTypeOutput) MonitoringConfig 

func (o EntityTypeOutput) MonitoringConfig() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput

Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.

func (EntityTypeOutput) Name 

func (o EntityTypeOutput) Name() pulumi.StringOutput

Immutable. Name of the EntityType. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.

func (EntityTypeOutput) OfflineStorageTtlDays 

func (o EntityTypeOutput) OfflineStorageTtlDays() pulumi.IntOutput

Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than `offline_storage_ttl_days` since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.

func (EntityTypeOutput) Project 

func (o EntityTypeOutput) Project() pulumi.StringOutput

func (EntityTypeOutput) ToEntityTypeOutput 

func (o EntityTypeOutput) ToEntityTypeOutput() EntityTypeOutput

func (EntityTypeOutput) ToEntityTypeOutputWithContext 

func (o EntityTypeOutput) ToEntityTypeOutputWithContext(ctx context.Context) EntityTypeOutput

func (EntityTypeOutput) UpdateTime 

func (o EntityTypeOutput) UpdateTime() pulumi.StringOutput

Timestamp when this EntityType was most recently updated.

type EntityTypeState 

type EntityTypeState struct {
}

func (EntityTypeState) ElementType 

func (EntityTypeState) ElementType() reflect.Type

type Execution 

type Execution struct {
	pulumi.CustomResourceState

	// Timestamp when this Execution was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Description of the Execution
	Description pulumi.StringOutput `pulumi:"description"`
	// User provided display name of the Execution. May be up to 128 Unicode characters.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// The {execution} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}` If not provided, the Execution's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Executions in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Execution.)
	ExecutionId pulumi.StringPtrOutput `pulumi:"executionId"`
	// The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
	Metadata        pulumi.StringMapOutput `pulumi:"metadata"`
	MetadataStoreId pulumi.StringOutput    `pulumi:"metadataStoreId"`
	// The resource name of the Execution.
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaTitle pulumi.StringOutput `pulumi:"schemaTitle"`
	// The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaVersion pulumi.StringOutput `pulumi:"schemaVersion"`
	// The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
	State pulumi.StringOutput `pulumi:"state"`
	// Timestamp when this Execution was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates an Execution associated with a MetadataStore. Auto-naming is currently not supported for this resource.

func GetExecution 

func GetExecution(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *ExecutionState, opts ...pulumi.ResourceOption) (*Execution, error)

GetExecution gets an existing Execution resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewExecution 

func NewExecution(ctx *pulumi.Context,
	name string, args *ExecutionArgs, opts ...pulumi.ResourceOption) (*Execution, error)

NewExecution registers a new resource with the given unique name, arguments, and options.

func (*Execution) ElementType 

func (*Execution) ElementType() reflect.Type

func (*Execution) ToExecutionOutput 

func (i *Execution) ToExecutionOutput() ExecutionOutput

func (*Execution) ToExecutionOutputWithContext 

func (i *Execution) ToExecutionOutputWithContext(ctx context.Context) ExecutionOutput

type ExecutionArgs 

type ExecutionArgs struct {
	// Description of the Execution
	Description pulumi.StringPtrInput
	// User provided display name of the Execution. May be up to 128 Unicode characters.
	DisplayName pulumi.StringPtrInput
	// An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// The {execution} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}` If not provided, the Execution's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Executions in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Execution.)
	ExecutionId pulumi.StringPtrInput
	// The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
	Metadata        pulumi.StringMapInput
	MetadataStoreId pulumi.StringInput
	Project         pulumi.StringPtrInput
	// The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaTitle pulumi.StringPtrInput
	// The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaVersion pulumi.StringPtrInput
	// The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
	State ExecutionStateEnumPtrInput
}

The set of arguments for constructing a Execution resource.

func (ExecutionArgs) ElementType 

func (ExecutionArgs) ElementType() reflect.Type

type ExecutionInput 

type ExecutionInput interface {
	pulumi.Input

	ToExecutionOutput() ExecutionOutput
	ToExecutionOutputWithContext(ctx context.Context) ExecutionOutput
}

type ExecutionOutput 

type ExecutionOutput struct{ *pulumi.OutputState }

func (ExecutionOutput) CreateTime 

func (o ExecutionOutput) CreateTime() pulumi.StringOutput

Timestamp when this Execution was created.

func (ExecutionOutput) Description 

func (o ExecutionOutput) Description() pulumi.StringOutput

Description of the Execution

func (ExecutionOutput) DisplayName 

func (o ExecutionOutput) DisplayName() pulumi.StringOutput

User provided display name of the Execution. May be up to 128 Unicode characters.

func (ExecutionOutput) ElementType 

func (ExecutionOutput) ElementType() reflect.Type

func (ExecutionOutput) Etag 

func (o ExecutionOutput) Etag() pulumi.StringOutput

An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (ExecutionOutput) ExecutionId 

func (o ExecutionOutput) ExecutionId() pulumi.StringPtrOutput

The {execution} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}` If not provided, the Execution's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Executions in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Execution.)

func (ExecutionOutput) Labels 

func (o ExecutionOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).

func (ExecutionOutput) Location 

func (o ExecutionOutput) Location() pulumi.StringOutput

func (ExecutionOutput) Metadata 

func (o ExecutionOutput) Metadata() pulumi.StringMapOutput

Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.

func (ExecutionOutput) MetadataStoreId 

func (o ExecutionOutput) MetadataStoreId() pulumi.StringOutput

func (ExecutionOutput) Name 

func (o ExecutionOutput) Name() pulumi.StringOutput

The resource name of the Execution.

func (ExecutionOutput) Project 

func (o ExecutionOutput) Project() pulumi.StringOutput

func (ExecutionOutput) SchemaTitle 

func (o ExecutionOutput) SchemaTitle() pulumi.StringOutput

The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (ExecutionOutput) SchemaVersion 

func (o ExecutionOutput) SchemaVersion() pulumi.StringOutput

The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (ExecutionOutput) State 

func (o ExecutionOutput) State() pulumi.StringOutput

The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.

func (ExecutionOutput) ToExecutionOutput 

func (o ExecutionOutput) ToExecutionOutput() ExecutionOutput

func (ExecutionOutput) ToExecutionOutputWithContext 

func (o ExecutionOutput) ToExecutionOutputWithContext(ctx context.Context) ExecutionOutput

func (ExecutionOutput) UpdateTime 

func (o ExecutionOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Execution was last updated.

type ExecutionState 

type ExecutionState struct {
}

func (ExecutionState) ElementType 

func (ExecutionState) ElementType() reflect.Type

type ExecutionStateEnum 

type ExecutionStateEnum string

The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.

func (ExecutionStateEnum) ElementType 

func (ExecutionStateEnum) ElementType() reflect.Type

func (ExecutionStateEnum) ToExecutionStateEnumOutput 

func (e ExecutionStateEnum) ToExecutionStateEnumOutput() ExecutionStateEnumOutput

func (ExecutionStateEnum) ToExecutionStateEnumOutputWithContext 

func (e ExecutionStateEnum) ToExecutionStateEnumOutputWithContext(ctx context.Context) ExecutionStateEnumOutput

func (ExecutionStateEnum) ToExecutionStateEnumPtrOutput 

func (e ExecutionStateEnum) ToExecutionStateEnumPtrOutput() ExecutionStateEnumPtrOutput

func (ExecutionStateEnum) ToExecutionStateEnumPtrOutputWithContext 

func (e ExecutionStateEnum) ToExecutionStateEnumPtrOutputWithContext(ctx context.Context) ExecutionStateEnumPtrOutput

func (ExecutionStateEnum) ToStringOutput 

func (e ExecutionStateEnum) ToStringOutput() pulumi.StringOutput

func (ExecutionStateEnum) ToStringOutputWithContext 

func (e ExecutionStateEnum) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (ExecutionStateEnum) ToStringPtrOutput 

func (e ExecutionStateEnum) ToStringPtrOutput() pulumi.StringPtrOutput

func (ExecutionStateEnum) ToStringPtrOutputWithContext 

func (e ExecutionStateEnum) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type ExecutionStateEnumInput 

type ExecutionStateEnumInput interface {
	pulumi.Input

	ToExecutionStateEnumOutput() ExecutionStateEnumOutput
	ToExecutionStateEnumOutputWithContext(context.Context) ExecutionStateEnumOutput
}

ExecutionStateEnumInput is an input type that accepts ExecutionStateEnumArgs and ExecutionStateEnumOutput values. You can construct a concrete instance of `ExecutionStateEnumInput` via: 

ExecutionStateEnumArgs{...}

type ExecutionStateEnumOutput 

type ExecutionStateEnumOutput struct{ *pulumi.OutputState }

func (ExecutionStateEnumOutput) ElementType 

func (ExecutionStateEnumOutput) ElementType() reflect.Type

func (ExecutionStateEnumOutput) ToExecutionStateEnumOutput 

func (o ExecutionStateEnumOutput) ToExecutionStateEnumOutput() ExecutionStateEnumOutput

func (ExecutionStateEnumOutput) ToExecutionStateEnumOutputWithContext 

func (o ExecutionStateEnumOutput) ToExecutionStateEnumOutputWithContext(ctx context.Context) ExecutionStateEnumOutput

func (ExecutionStateEnumOutput) ToExecutionStateEnumPtrOutput 

func (o ExecutionStateEnumOutput) ToExecutionStateEnumPtrOutput() ExecutionStateEnumPtrOutput

func (ExecutionStateEnumOutput) ToExecutionStateEnumPtrOutputWithContext 

func (o ExecutionStateEnumOutput) ToExecutionStateEnumPtrOutputWithContext(ctx context.Context) ExecutionStateEnumPtrOutput

func (ExecutionStateEnumOutput) ToStringOutput 

func (o ExecutionStateEnumOutput) ToStringOutput() pulumi.StringOutput

func (ExecutionStateEnumOutput) ToStringOutputWithContext 

func (o ExecutionStateEnumOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (ExecutionStateEnumOutput) ToStringPtrOutput 

func (o ExecutionStateEnumOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (ExecutionStateEnumOutput) ToStringPtrOutputWithContext 

func (o ExecutionStateEnumOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type ExecutionStateEnumPtrInput 

type ExecutionStateEnumPtrInput interface {
	pulumi.Input

	ToExecutionStateEnumPtrOutput() ExecutionStateEnumPtrOutput
	ToExecutionStateEnumPtrOutputWithContext(context.Context) ExecutionStateEnumPtrOutput
}

func ExecutionStateEnumPtr 

func ExecutionStateEnumPtr(v string) ExecutionStateEnumPtrInput

type ExecutionStateEnumPtrOutput 

type ExecutionStateEnumPtrOutput struct{ *pulumi.OutputState }

func (ExecutionStateEnumPtrOutput) Elem 

func (o ExecutionStateEnumPtrOutput) Elem() ExecutionStateEnumOutput

func (ExecutionStateEnumPtrOutput) ElementType 

func (ExecutionStateEnumPtrOutput) ElementType() reflect.Type

func (ExecutionStateEnumPtrOutput) ToExecutionStateEnumPtrOutput 

func (o ExecutionStateEnumPtrOutput) ToExecutionStateEnumPtrOutput() ExecutionStateEnumPtrOutput

func (ExecutionStateEnumPtrOutput) ToExecutionStateEnumPtrOutputWithContext 

func (o ExecutionStateEnumPtrOutput) ToExecutionStateEnumPtrOutputWithContext(ctx context.Context) ExecutionStateEnumPtrOutput

func (ExecutionStateEnumPtrOutput) ToStringPtrOutput 

func (o ExecutionStateEnumPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (ExecutionStateEnumPtrOutput) ToStringPtrOutputWithContext 

func (o ExecutionStateEnumPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type Experiment 

type Experiment struct {
	pulumi.CustomResourceState

	// Timestamp when this TensorboardExperiment was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Description of this TensorboardExperiment.
	Description pulumi.StringOutput `pulumi:"description"`
	// User provided name of this TensorboardExperiment.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// The labels with user-defined metadata to organize your TensorboardExperiment. Label keys and values cannot be longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with `aiplatform.googleapis.com/` and are immutable. The following system labels exist for each Dataset: * `aiplatform.googleapis.com/dataset_metadata_schema`: output only. Its value is the metadata_schema's title.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Name of the TensorboardExperiment. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// Immutable. Source of the TensorboardExperiment. Example: a custom training job.
	Source pulumi.StringOutput `pulumi:"source"`
	// Required. The ID to use for the Tensorboard experiment, which becomes the final component of the Tensorboard experiment's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.
	TensorboardExperimentId pulumi.StringOutput `pulumi:"tensorboardExperimentId"`
	TensorboardId           pulumi.StringOutput `pulumi:"tensorboardId"`
	// Timestamp when this TensorboardExperiment was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a TensorboardExperiment. Auto-naming is currently not supported for this resource.

func GetExperiment 

func GetExperiment(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *ExperimentState, opts ...pulumi.ResourceOption) (*Experiment, error)

GetExperiment gets an existing Experiment resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewExperiment 

func NewExperiment(ctx *pulumi.Context,
	name string, args *ExperimentArgs, opts ...pulumi.ResourceOption) (*Experiment, error)

NewExperiment registers a new resource with the given unique name, arguments, and options.

func (*Experiment) ElementType 

func (*Experiment) ElementType() reflect.Type

func (*Experiment) ToExperimentOutput 

func (i *Experiment) ToExperimentOutput() ExperimentOutput

func (*Experiment) ToExperimentOutputWithContext 

func (i *Experiment) ToExperimentOutputWithContext(ctx context.Context) ExperimentOutput

type ExperimentArgs 

type ExperimentArgs struct {
	// Description of this TensorboardExperiment.
	Description pulumi.StringPtrInput
	// User provided name of this TensorboardExperiment.
	DisplayName pulumi.StringPtrInput
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// The labels with user-defined metadata to organize your TensorboardExperiment. Label keys and values cannot be longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with `aiplatform.googleapis.com/` and are immutable. The following system labels exist for each Dataset: * `aiplatform.googleapis.com/dataset_metadata_schema`: output only. Its value is the metadata_schema's title.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	Project  pulumi.StringPtrInput
	// Immutable. Source of the TensorboardExperiment. Example: a custom training job.
	Source pulumi.StringPtrInput
	// Required. The ID to use for the Tensorboard experiment, which becomes the final component of the Tensorboard experiment's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.
	TensorboardExperimentId pulumi.StringInput
	TensorboardId           pulumi.StringInput
}

The set of arguments for constructing a Experiment resource.

func (ExperimentArgs) ElementType 

func (ExperimentArgs) ElementType() reflect.Type

type ExperimentInput 

type ExperimentInput interface {
	pulumi.Input

	ToExperimentOutput() ExperimentOutput
	ToExperimentOutputWithContext(ctx context.Context) ExperimentOutput
}

type ExperimentOutput 

type ExperimentOutput struct{ *pulumi.OutputState }

func (ExperimentOutput) CreateTime 

func (o ExperimentOutput) CreateTime() pulumi.StringOutput

Timestamp when this TensorboardExperiment was created.

func (ExperimentOutput) Description 

func (o ExperimentOutput) Description() pulumi.StringOutput

Description of this TensorboardExperiment.

func (ExperimentOutput) DisplayName 

func (o ExperimentOutput) DisplayName() pulumi.StringOutput

User provided name of this TensorboardExperiment.

func (ExperimentOutput) ElementType 

func (ExperimentOutput) ElementType() reflect.Type

func (ExperimentOutput) Etag 

func (o ExperimentOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (ExperimentOutput) Labels 

func (o ExperimentOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your TensorboardExperiment. Label keys and values cannot be longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with `aiplatform.googleapis.com/` and are immutable. The following system labels exist for each Dataset: * `aiplatform.googleapis.com/dataset_metadata_schema`: output only. Its value is the metadata_schema's title.

func (ExperimentOutput) Location 

func (o ExperimentOutput) Location() pulumi.StringOutput

func (ExperimentOutput) Name 

func (o ExperimentOutput) Name() pulumi.StringOutput

Name of the TensorboardExperiment. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`

func (ExperimentOutput) Project 

func (o ExperimentOutput) Project() pulumi.StringOutput

func (ExperimentOutput) Source 

func (o ExperimentOutput) Source() pulumi.StringOutput

Immutable. Source of the TensorboardExperiment. Example: a custom training job.

func (ExperimentOutput) TensorboardExperimentId 

func (o ExperimentOutput) TensorboardExperimentId() pulumi.StringOutput

Required. The ID to use for the Tensorboard experiment, which becomes the final component of the Tensorboard experiment's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.

func (ExperimentOutput) TensorboardId 

func (o ExperimentOutput) TensorboardId() pulumi.StringOutput

func (ExperimentOutput) ToExperimentOutput 

func (o ExperimentOutput) ToExperimentOutput() ExperimentOutput

func (ExperimentOutput) ToExperimentOutputWithContext 

func (o ExperimentOutput) ToExperimentOutputWithContext(ctx context.Context) ExperimentOutput

func (ExperimentOutput) UpdateTime 

func (o ExperimentOutput) UpdateTime() pulumi.StringOutput

Timestamp when this TensorboardExperiment was last updated.

type ExperimentState 

type ExperimentState struct {
}

func (ExperimentState) ElementType 

func (ExperimentState) ElementType() reflect.Type

type FeatureGroup 

type FeatureGroup struct {
	pulumi.CustomResourceState

	// Indicates that features for this group come from BigQuery Table/View. By default treats the source as a sparse time series source, which is required to have an entity_id and a feature_timestamp column in the source.
	BigQuery GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput `pulumi:"bigQuery"`
	// Timestamp when this FeatureGroup was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Optional. Description of the FeatureGroup.
	Description pulumi.StringOutput `pulumi:"description"`
	// Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Required. The ID to use for this FeatureGroup, which will become the final component of the FeatureGroup's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.
	FeatureGroupId pulumi.StringOutput `pulumi:"featureGroupId"`
	// Optional. The labels with user-defined metadata to organize your FeatureGroup. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureGroup(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// Timestamp when this FeatureGroup was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a new FeatureGroup in a given project and location. Auto-naming is currently not supported for this resource.

func GetFeatureGroup 

func GetFeatureGroup(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *FeatureGroupState, opts ...pulumi.ResourceOption) (*FeatureGroup, error)

GetFeatureGroup gets an existing FeatureGroup resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewFeatureGroup 

func NewFeatureGroup(ctx *pulumi.Context,
	name string, args *FeatureGroupArgs, opts ...pulumi.ResourceOption) (*FeatureGroup, error)

NewFeatureGroup registers a new resource with the given unique name, arguments, and options.

func (*FeatureGroup) ElementType 

func (*FeatureGroup) ElementType() reflect.Type

func (*FeatureGroup) ToFeatureGroupOutput 

func (i *FeatureGroup) ToFeatureGroupOutput() FeatureGroupOutput

func (*FeatureGroup) ToFeatureGroupOutputWithContext 

func (i *FeatureGroup) ToFeatureGroupOutputWithContext(ctx context.Context) FeatureGroupOutput

type FeatureGroupArgs 

type FeatureGroupArgs struct {
	// Indicates that features for this group come from BigQuery Table/View. By default treats the source as a sparse time series source, which is required to have an entity_id and a feature_timestamp column in the source.
	BigQuery GoogleCloudAiplatformV1FeatureGroupBigQueryPtrInput
	// Optional. Description of the FeatureGroup.
	Description pulumi.StringPtrInput
	// Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// Required. The ID to use for this FeatureGroup, which will become the final component of the FeatureGroup's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.
	FeatureGroupId pulumi.StringInput
	// Optional. The labels with user-defined metadata to organize your FeatureGroup. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureGroup(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	Project  pulumi.StringPtrInput
}

The set of arguments for constructing a FeatureGroup resource.

func (FeatureGroupArgs) ElementType 

func (FeatureGroupArgs) ElementType() reflect.Type

type FeatureGroupFeature 

type FeatureGroupFeature struct {
	pulumi.CustomResourceState

	// Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Description of the Feature.
	Description pulumi.StringOutput `pulumi:"description"`
	// Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
	DisableMonitoring pulumi.BoolOutput `pulumi:"disableMonitoring"`
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag           pulumi.StringOutput `pulumi:"etag"`
	FeatureGroupId pulumi.StringOutput `pulumi:"featureGroupId"`
	// Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.
	FeatureId pulumi.StringOutput `pulumi:"featureId"`
	// Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
	MonitoringStatsAnomalies GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput `pulumi:"monitoringStatsAnomalies"`
	// Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
	// Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
	ValueType pulumi.StringOutput `pulumi:"valueType"`
	// Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
	VersionColumnName pulumi.StringOutput `pulumi:"versionColumnName"`
}

Creates a new Feature in a given FeatureGroup. Auto-naming is currently not supported for this resource.

func GetFeatureGroupFeature 

func GetFeatureGroupFeature(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *FeatureGroupFeatureState, opts ...pulumi.ResourceOption) (*FeatureGroupFeature, error)

GetFeatureGroupFeature gets an existing FeatureGroupFeature resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewFeatureGroupFeature 

func NewFeatureGroupFeature(ctx *pulumi.Context,
	name string, args *FeatureGroupFeatureArgs, opts ...pulumi.ResourceOption) (*FeatureGroupFeature, error)

NewFeatureGroupFeature registers a new resource with the given unique name, arguments, and options.

func (*FeatureGroupFeature) ElementType 

func (*FeatureGroupFeature) ElementType() reflect.Type

func (*FeatureGroupFeature) ToFeatureGroupFeatureOutput 

func (i *FeatureGroupFeature) ToFeatureGroupFeatureOutput() FeatureGroupFeatureOutput

func (*FeatureGroupFeature) ToFeatureGroupFeatureOutputWithContext 

func (i *FeatureGroupFeature) ToFeatureGroupFeatureOutputWithContext(ctx context.Context) FeatureGroupFeatureOutput

type FeatureGroupFeatureArgs 

type FeatureGroupFeatureArgs struct {
	// Description of the Feature.
	Description pulumi.StringPtrInput
	// Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
	DisableMonitoring pulumi.BoolPtrInput
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag           pulumi.StringPtrInput
	FeatureGroupId pulumi.StringInput
	// Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.
	FeatureId pulumi.StringInput
	// Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.
	Name    pulumi.StringPtrInput
	Project pulumi.StringPtrInput
	// Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
	ValueType FeatureGroupFeatureValueTypePtrInput
	// Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
	VersionColumnName pulumi.StringPtrInput
}

The set of arguments for constructing a FeatureGroupFeature resource.

func (FeatureGroupFeatureArgs) ElementType 

func (FeatureGroupFeatureArgs) ElementType() reflect.Type

type FeatureGroupFeatureInput 

type FeatureGroupFeatureInput interface {
	pulumi.Input

	ToFeatureGroupFeatureOutput() FeatureGroupFeatureOutput
	ToFeatureGroupFeatureOutputWithContext(ctx context.Context) FeatureGroupFeatureOutput
}

type FeatureGroupFeatureOutput 

type FeatureGroupFeatureOutput struct{ *pulumi.OutputState }

func (FeatureGroupFeatureOutput) CreateTime 

func (o FeatureGroupFeatureOutput) CreateTime() pulumi.StringOutput

Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.

func (FeatureGroupFeatureOutput) Description 

func (o FeatureGroupFeatureOutput) Description() pulumi.StringOutput

Description of the Feature.

func (FeatureGroupFeatureOutput) DisableMonitoring 

func (o FeatureGroupFeatureOutput) DisableMonitoring() pulumi.BoolOutput

Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.

func (FeatureGroupFeatureOutput) ElementType 

func (FeatureGroupFeatureOutput) ElementType() reflect.Type

func (FeatureGroupFeatureOutput) Etag 

func (o FeatureGroupFeatureOutput) Etag() pulumi.StringOutput

Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (FeatureGroupFeatureOutput) FeatureGroupId 

func (o FeatureGroupFeatureOutput) FeatureGroupId() pulumi.StringOutput

func (FeatureGroupFeatureOutput) FeatureId 

func (o FeatureGroupFeatureOutput) FeatureId() pulumi.StringOutput

Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.

func (FeatureGroupFeatureOutput) Labels 

func (o FeatureGroupFeatureOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (FeatureGroupFeatureOutput) Location 

func (o FeatureGroupFeatureOutput) Location() pulumi.StringOutput

func (FeatureGroupFeatureOutput) MonitoringStatsAnomalies 

func (o FeatureGroupFeatureOutput) MonitoringStatsAnomalies() GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput

Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.

func (FeatureGroupFeatureOutput) Name 

func (o FeatureGroupFeatureOutput) Name() pulumi.StringOutput

Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.

func (FeatureGroupFeatureOutput) Project 

func (o FeatureGroupFeatureOutput) Project() pulumi.StringOutput

func (FeatureGroupFeatureOutput) ToFeatureGroupFeatureOutput 

func (o FeatureGroupFeatureOutput) ToFeatureGroupFeatureOutput() FeatureGroupFeatureOutput

func (FeatureGroupFeatureOutput) ToFeatureGroupFeatureOutputWithContext 

func (o FeatureGroupFeatureOutput) ToFeatureGroupFeatureOutputWithContext(ctx context.Context) FeatureGroupFeatureOutput

func (FeatureGroupFeatureOutput) UpdateTime 

func (o FeatureGroupFeatureOutput) UpdateTime() pulumi.StringOutput

Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.

func (FeatureGroupFeatureOutput) ValueType 

func (o FeatureGroupFeatureOutput) ValueType() pulumi.StringOutput

Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.

func (FeatureGroupFeatureOutput) VersionColumnName 

func (o FeatureGroupFeatureOutput) VersionColumnName() pulumi.StringOutput

Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.

type FeatureGroupFeatureState 

type FeatureGroupFeatureState struct {
}

func (FeatureGroupFeatureState) ElementType 

func (FeatureGroupFeatureState) ElementType() reflect.Type

type FeatureGroupFeatureValueType 

type FeatureGroupFeatureValueType string

Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.

func (FeatureGroupFeatureValueType) ElementType 

func (FeatureGroupFeatureValueType) ElementType() reflect.Type

func (FeatureGroupFeatureValueType) ToFeatureGroupFeatureValueTypeOutput 

func (e FeatureGroupFeatureValueType) ToFeatureGroupFeatureValueTypeOutput() FeatureGroupFeatureValueTypeOutput

func (FeatureGroupFeatureValueType) ToFeatureGroupFeatureValueTypeOutputWithContext 

func (e FeatureGroupFeatureValueType) ToFeatureGroupFeatureValueTypeOutputWithContext(ctx context.Context) FeatureGroupFeatureValueTypeOutput

func (FeatureGroupFeatureValueType) ToFeatureGroupFeatureValueTypePtrOutput 

func (e FeatureGroupFeatureValueType) ToFeatureGroupFeatureValueTypePtrOutput() FeatureGroupFeatureValueTypePtrOutput

func (FeatureGroupFeatureValueType) ToFeatureGroupFeatureValueTypePtrOutputWithContext 

func (e FeatureGroupFeatureValueType) ToFeatureGroupFeatureValueTypePtrOutputWithContext(ctx context.Context) FeatureGroupFeatureValueTypePtrOutput

func (FeatureGroupFeatureValueType) ToStringOutput 

func (e FeatureGroupFeatureValueType) ToStringOutput() pulumi.StringOutput

func (FeatureGroupFeatureValueType) ToStringOutputWithContext 

func (e FeatureGroupFeatureValueType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (FeatureGroupFeatureValueType) ToStringPtrOutput 

func (e FeatureGroupFeatureValueType) ToStringPtrOutput() pulumi.StringPtrOutput

func (FeatureGroupFeatureValueType) ToStringPtrOutputWithContext 

func (e FeatureGroupFeatureValueType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type FeatureGroupFeatureValueTypeInput 

type FeatureGroupFeatureValueTypeInput interface {
	pulumi.Input

	ToFeatureGroupFeatureValueTypeOutput() FeatureGroupFeatureValueTypeOutput
	ToFeatureGroupFeatureValueTypeOutputWithContext(context.Context) FeatureGroupFeatureValueTypeOutput
}

FeatureGroupFeatureValueTypeInput is an input type that accepts FeatureGroupFeatureValueTypeArgs and FeatureGroupFeatureValueTypeOutput values. You can construct a concrete instance of `FeatureGroupFeatureValueTypeInput` via: 

FeatureGroupFeatureValueTypeArgs{...}

type FeatureGroupFeatureValueTypeOutput 

type FeatureGroupFeatureValueTypeOutput struct{ *pulumi.OutputState }

func (FeatureGroupFeatureValueTypeOutput) ElementType 

func (FeatureGroupFeatureValueTypeOutput) ElementType() reflect.Type

func (FeatureGroupFeatureValueTypeOutput) ToFeatureGroupFeatureValueTypeOutput 

func (o FeatureGroupFeatureValueTypeOutput) ToFeatureGroupFeatureValueTypeOutput() FeatureGroupFeatureValueTypeOutput

func (FeatureGroupFeatureValueTypeOutput) ToFeatureGroupFeatureValueTypeOutputWithContext 

func (o FeatureGroupFeatureValueTypeOutput) ToFeatureGroupFeatureValueTypeOutputWithContext(ctx context.Context) FeatureGroupFeatureValueTypeOutput

func (FeatureGroupFeatureValueTypeOutput) ToFeatureGroupFeatureValueTypePtrOutput 

func (o FeatureGroupFeatureValueTypeOutput) ToFeatureGroupFeatureValueTypePtrOutput() FeatureGroupFeatureValueTypePtrOutput

func (FeatureGroupFeatureValueTypeOutput) ToFeatureGroupFeatureValueTypePtrOutputWithContext 

func (o FeatureGroupFeatureValueTypeOutput) ToFeatureGroupFeatureValueTypePtrOutputWithContext(ctx context.Context) FeatureGroupFeatureValueTypePtrOutput

func (FeatureGroupFeatureValueTypeOutput) ToStringOutput 

func (o FeatureGroupFeatureValueTypeOutput) ToStringOutput() pulumi.StringOutput

func (FeatureGroupFeatureValueTypeOutput) ToStringOutputWithContext 

func (o FeatureGroupFeatureValueTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (FeatureGroupFeatureValueTypeOutput) ToStringPtrOutput 

func (o FeatureGroupFeatureValueTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (FeatureGroupFeatureValueTypeOutput) ToStringPtrOutputWithContext 

func (o FeatureGroupFeatureValueTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type FeatureGroupFeatureValueTypePtrInput 

type FeatureGroupFeatureValueTypePtrInput interface {
	pulumi.Input

	ToFeatureGroupFeatureValueTypePtrOutput() FeatureGroupFeatureValueTypePtrOutput
	ToFeatureGroupFeatureValueTypePtrOutputWithContext(context.Context) FeatureGroupFeatureValueTypePtrOutput
}

func FeatureGroupFeatureValueTypePtr 

func FeatureGroupFeatureValueTypePtr(v string) FeatureGroupFeatureValueTypePtrInput

type FeatureGroupFeatureValueTypePtrOutput 

type FeatureGroupFeatureValueTypePtrOutput struct{ *pulumi.OutputState }

func (FeatureGroupFeatureValueTypePtrOutput) Elem 

func (o FeatureGroupFeatureValueTypePtrOutput) Elem() FeatureGroupFeatureValueTypeOutput

func (FeatureGroupFeatureValueTypePtrOutput) ElementType 

func (FeatureGroupFeatureValueTypePtrOutput) ElementType() reflect.Type

func (FeatureGroupFeatureValueTypePtrOutput) ToFeatureGroupFeatureValueTypePtrOutput 

func (o FeatureGroupFeatureValueTypePtrOutput) ToFeatureGroupFeatureValueTypePtrOutput() FeatureGroupFeatureValueTypePtrOutput

func (FeatureGroupFeatureValueTypePtrOutput) ToFeatureGroupFeatureValueTypePtrOutputWithContext 

func (o FeatureGroupFeatureValueTypePtrOutput) ToFeatureGroupFeatureValueTypePtrOutputWithContext(ctx context.Context) FeatureGroupFeatureValueTypePtrOutput

func (FeatureGroupFeatureValueTypePtrOutput) ToStringPtrOutput 

func (o FeatureGroupFeatureValueTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (FeatureGroupFeatureValueTypePtrOutput) ToStringPtrOutputWithContext 

func (o FeatureGroupFeatureValueTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type FeatureGroupInput 

type FeatureGroupInput interface {
	pulumi.Input

	ToFeatureGroupOutput() FeatureGroupOutput
	ToFeatureGroupOutputWithContext(ctx context.Context) FeatureGroupOutput
}

type FeatureGroupOutput 

type FeatureGroupOutput struct{ *pulumi.OutputState }

func (FeatureGroupOutput) BigQuery 

func (o FeatureGroupOutput) BigQuery() GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput

Indicates that features for this group come from BigQuery Table/View. By default treats the source as a sparse time series source, which is required to have an entity_id and a feature_timestamp column in the source.

func (FeatureGroupOutput) CreateTime 

func (o FeatureGroupOutput) CreateTime() pulumi.StringOutput

Timestamp when this FeatureGroup was created.

func (FeatureGroupOutput) Description 

func (o FeatureGroupOutput) Description() pulumi.StringOutput

Optional. Description of the FeatureGroup.

func (FeatureGroupOutput) ElementType 

func (FeatureGroupOutput) ElementType() reflect.Type

func (FeatureGroupOutput) Etag 

func (o FeatureGroupOutput) Etag() pulumi.StringOutput

Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (FeatureGroupOutput) FeatureGroupId 

func (o FeatureGroupOutput) FeatureGroupId() pulumi.StringOutput

Required. The ID to use for this FeatureGroup, which will become the final component of the FeatureGroup's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.

func (FeatureGroupOutput) Labels 

func (o FeatureGroupOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your FeatureGroup. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureGroup(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (FeatureGroupOutput) Location 

func (o FeatureGroupOutput) Location() pulumi.StringOutput

func (FeatureGroupOutput) Name 

func (o FeatureGroupOutput) Name() pulumi.StringOutput

Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`

func (FeatureGroupOutput) Project 

func (o FeatureGroupOutput) Project() pulumi.StringOutput

func (FeatureGroupOutput) ToFeatureGroupOutput 

func (o FeatureGroupOutput) ToFeatureGroupOutput() FeatureGroupOutput

func (FeatureGroupOutput) ToFeatureGroupOutputWithContext 

func (o FeatureGroupOutput) ToFeatureGroupOutputWithContext(ctx context.Context) FeatureGroupOutput

func (FeatureGroupOutput) UpdateTime 

func (o FeatureGroupOutput) UpdateTime() pulumi.StringOutput

Timestamp when this FeatureGroup was last updated.

type FeatureGroupState 

type FeatureGroupState struct {
}

func (FeatureGroupState) ElementType 

func (FeatureGroupState) ElementType() reflect.Type

type FeatureOnlineStore 

type FeatureOnlineStore struct {
	pulumi.CustomResourceState

	// Contains settings for the Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore.
	Bigtable GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput `pulumi:"bigtable"`
	// Timestamp when this FeatureOnlineStore was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Required. The ID to use for this FeatureOnlineStore, which will become the final component of the FeatureOnlineStore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.
	FeatureOnlineStoreId pulumi.StringOutput `pulumi:"featureOnlineStoreId"`
	// Optional. The labels with user-defined metadata to organize your FeatureOnlineStore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Name of the FeatureOnlineStore. Format: `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}`
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// State of the featureOnlineStore.
	State pulumi.StringOutput `pulumi:"state"`
	// Timestamp when this FeatureOnlineStore was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a new FeatureOnlineStore in a given project and location. Auto-naming is currently not supported for this resource.

func GetFeatureOnlineStore 

func GetFeatureOnlineStore(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *FeatureOnlineStoreState, opts ...pulumi.ResourceOption) (*FeatureOnlineStore, error)

GetFeatureOnlineStore gets an existing FeatureOnlineStore resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewFeatureOnlineStore 

func NewFeatureOnlineStore(ctx *pulumi.Context,
	name string, args *FeatureOnlineStoreArgs, opts ...pulumi.ResourceOption) (*FeatureOnlineStore, error)

NewFeatureOnlineStore registers a new resource with the given unique name, arguments, and options.

func (*FeatureOnlineStore) ElementType 

func (*FeatureOnlineStore) ElementType() reflect.Type

func (*FeatureOnlineStore) ToFeatureOnlineStoreOutput 

func (i *FeatureOnlineStore) ToFeatureOnlineStoreOutput() FeatureOnlineStoreOutput

func (*FeatureOnlineStore) ToFeatureOnlineStoreOutputWithContext 

func (i *FeatureOnlineStore) ToFeatureOnlineStoreOutputWithContext(ctx context.Context) FeatureOnlineStoreOutput

type FeatureOnlineStoreArgs 

type FeatureOnlineStoreArgs struct {
	// Contains settings for the Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore.
	Bigtable GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrInput
	// Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// Required. The ID to use for this FeatureOnlineStore, which will become the final component of the FeatureOnlineStore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.
	FeatureOnlineStoreId pulumi.StringInput
	// Optional. The labels with user-defined metadata to organize your FeatureOnlineStore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	Project  pulumi.StringPtrInput
}

The set of arguments for constructing a FeatureOnlineStore resource.

func (FeatureOnlineStoreArgs) ElementType 

func (FeatureOnlineStoreArgs) ElementType() reflect.Type

type FeatureOnlineStoreInput 

type FeatureOnlineStoreInput interface {
	pulumi.Input

	ToFeatureOnlineStoreOutput() FeatureOnlineStoreOutput
	ToFeatureOnlineStoreOutputWithContext(ctx context.Context) FeatureOnlineStoreOutput
}

type FeatureOnlineStoreOutput 

type FeatureOnlineStoreOutput struct{ *pulumi.OutputState }

func (FeatureOnlineStoreOutput) Bigtable 

func (o FeatureOnlineStoreOutput) Bigtable() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput

Contains settings for the Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore.

func (FeatureOnlineStoreOutput) CreateTime 

func (o FeatureOnlineStoreOutput) CreateTime() pulumi.StringOutput

Timestamp when this FeatureOnlineStore was created.

func (FeatureOnlineStoreOutput) ElementType 

func (FeatureOnlineStoreOutput) ElementType() reflect.Type

func (FeatureOnlineStoreOutput) Etag 

func (o FeatureOnlineStoreOutput) Etag() pulumi.StringOutput

Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (FeatureOnlineStoreOutput) FeatureOnlineStoreId 

func (o FeatureOnlineStoreOutput) FeatureOnlineStoreId() pulumi.StringOutput

Required. The ID to use for this FeatureOnlineStore, which will become the final component of the FeatureOnlineStore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.

func (FeatureOnlineStoreOutput) Labels 

func (o FeatureOnlineStoreOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your FeatureOnlineStore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (FeatureOnlineStoreOutput) Location 

func (o FeatureOnlineStoreOutput) Location() pulumi.StringOutput

func (FeatureOnlineStoreOutput) Name 

func (o FeatureOnlineStoreOutput) Name() pulumi.StringOutput

Name of the FeatureOnlineStore. Format: `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}`

func (FeatureOnlineStoreOutput) Project 

func (o FeatureOnlineStoreOutput) Project() pulumi.StringOutput

func (FeatureOnlineStoreOutput) State 

func (o FeatureOnlineStoreOutput) State() pulumi.StringOutput

State of the featureOnlineStore.

func (FeatureOnlineStoreOutput) ToFeatureOnlineStoreOutput 

func (o FeatureOnlineStoreOutput) ToFeatureOnlineStoreOutput() FeatureOnlineStoreOutput

func (FeatureOnlineStoreOutput) ToFeatureOnlineStoreOutputWithContext 

func (o FeatureOnlineStoreOutput) ToFeatureOnlineStoreOutputWithContext(ctx context.Context) FeatureOnlineStoreOutput

func (FeatureOnlineStoreOutput) UpdateTime 

func (o FeatureOnlineStoreOutput) UpdateTime() pulumi.StringOutput

Timestamp when this FeatureOnlineStore was last updated.

type FeatureOnlineStoreState 

type FeatureOnlineStoreState struct {
}

func (FeatureOnlineStoreState) ElementType 

func (FeatureOnlineStoreState) ElementType() reflect.Type

type FeatureStoreFeature 

type FeatureStoreFeature struct {
	pulumi.CustomResourceState

	// Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Description of the Feature.
	Description pulumi.StringOutput `pulumi:"description"`
	// Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
	DisableMonitoring pulumi.BoolOutput   `pulumi:"disableMonitoring"`
	EntityTypeId      pulumi.StringOutput `pulumi:"entityTypeId"`
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.
	FeatureId      pulumi.StringOutput `pulumi:"featureId"`
	FeaturestoreId pulumi.StringOutput `pulumi:"featurestoreId"`
	// Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
	MonitoringStatsAnomalies GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput `pulumi:"monitoringStatsAnomalies"`
	// Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
	// Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
	ValueType pulumi.StringOutput `pulumi:"valueType"`
	// Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
	VersionColumnName pulumi.StringOutput `pulumi:"versionColumnName"`
}

Creates a new Feature in a given EntityType.

func GetFeatureStoreFeature 

func GetFeatureStoreFeature(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *FeatureStoreFeatureState, opts ...pulumi.ResourceOption) (*FeatureStoreFeature, error)

GetFeatureStoreFeature gets an existing FeatureStoreFeature resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewFeatureStoreFeature 

func NewFeatureStoreFeature(ctx *pulumi.Context,
	name string, args *FeatureStoreFeatureArgs, opts ...pulumi.ResourceOption) (*FeatureStoreFeature, error)

NewFeatureStoreFeature registers a new resource with the given unique name, arguments, and options.

func (*FeatureStoreFeature) ElementType 

func (*FeatureStoreFeature) ElementType() reflect.Type

func (*FeatureStoreFeature) ToFeatureStoreFeatureOutput 

func (i *FeatureStoreFeature) ToFeatureStoreFeatureOutput() FeatureStoreFeatureOutput

func (*FeatureStoreFeature) ToFeatureStoreFeatureOutputWithContext 

func (i *FeatureStoreFeature) ToFeatureStoreFeatureOutputWithContext(ctx context.Context) FeatureStoreFeatureOutput

type FeatureStoreFeatureArgs 

type FeatureStoreFeatureArgs struct {
	// Description of the Feature.
	Description pulumi.StringPtrInput
	// Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
	DisableMonitoring pulumi.BoolPtrInput
	EntityTypeId      pulumi.StringInput
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.
	FeatureId      pulumi.StringInput
	FeaturestoreId pulumi.StringInput
	// Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.
	Name    pulumi.StringPtrInput
	Project pulumi.StringPtrInput
	// Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
	ValueType FeatureStoreFeatureValueTypePtrInput
	// Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
	VersionColumnName pulumi.StringPtrInput
}

The set of arguments for constructing a FeatureStoreFeature resource.

func (FeatureStoreFeatureArgs) ElementType 

func (FeatureStoreFeatureArgs) ElementType() reflect.Type

type FeatureStoreFeatureInput 

type FeatureStoreFeatureInput interface {
	pulumi.Input

	ToFeatureStoreFeatureOutput() FeatureStoreFeatureOutput
	ToFeatureStoreFeatureOutputWithContext(ctx context.Context) FeatureStoreFeatureOutput
}

type FeatureStoreFeatureOutput 

type FeatureStoreFeatureOutput struct{ *pulumi.OutputState }

func (FeatureStoreFeatureOutput) CreateTime 

func (o FeatureStoreFeatureOutput) CreateTime() pulumi.StringOutput

Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.

func (FeatureStoreFeatureOutput) Description 

func (o FeatureStoreFeatureOutput) Description() pulumi.StringOutput

Description of the Feature.

func (FeatureStoreFeatureOutput) DisableMonitoring 

func (o FeatureStoreFeatureOutput) DisableMonitoring() pulumi.BoolOutput

Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.

func (FeatureStoreFeatureOutput) ElementType 

func (FeatureStoreFeatureOutput) ElementType() reflect.Type

func (FeatureStoreFeatureOutput) EntityTypeId 

func (o FeatureStoreFeatureOutput) EntityTypeId() pulumi.StringOutput

func (FeatureStoreFeatureOutput) Etag 

func (o FeatureStoreFeatureOutput) Etag() pulumi.StringOutput

Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (FeatureStoreFeatureOutput) FeatureId 

func (o FeatureStoreFeatureOutput) FeatureId() pulumi.StringOutput

Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.

func (FeatureStoreFeatureOutput) FeaturestoreId 

func (o FeatureStoreFeatureOutput) FeaturestoreId() pulumi.StringOutput

func (FeatureStoreFeatureOutput) Labels 

func (o FeatureStoreFeatureOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (FeatureStoreFeatureOutput) Location 

func (o FeatureStoreFeatureOutput) Location() pulumi.StringOutput

func (FeatureStoreFeatureOutput) MonitoringStatsAnomalies 

func (o FeatureStoreFeatureOutput) MonitoringStatsAnomalies() GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput

Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.

func (FeatureStoreFeatureOutput) Name 

func (o FeatureStoreFeatureOutput) Name() pulumi.StringOutput

Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.

func (FeatureStoreFeatureOutput) Project 

func (o FeatureStoreFeatureOutput) Project() pulumi.StringOutput

func (FeatureStoreFeatureOutput) ToFeatureStoreFeatureOutput 

func (o FeatureStoreFeatureOutput) ToFeatureStoreFeatureOutput() FeatureStoreFeatureOutput

func (FeatureStoreFeatureOutput) ToFeatureStoreFeatureOutputWithContext 

func (o FeatureStoreFeatureOutput) ToFeatureStoreFeatureOutputWithContext(ctx context.Context) FeatureStoreFeatureOutput

func (FeatureStoreFeatureOutput) UpdateTime 

func (o FeatureStoreFeatureOutput) UpdateTime() pulumi.StringOutput

Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.

func (FeatureStoreFeatureOutput) ValueType 

func (o FeatureStoreFeatureOutput) ValueType() pulumi.StringOutput

Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.

func (FeatureStoreFeatureOutput) VersionColumnName 

func (o FeatureStoreFeatureOutput) VersionColumnName() pulumi.StringOutput

Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.

type FeatureStoreFeatureState 

type FeatureStoreFeatureState struct {
}

func (FeatureStoreFeatureState) ElementType 

func (FeatureStoreFeatureState) ElementType() reflect.Type

type FeatureStoreFeatureValueType 

type FeatureStoreFeatureValueType string

Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.

func (FeatureStoreFeatureValueType) ElementType 

func (FeatureStoreFeatureValueType) ElementType() reflect.Type

func (FeatureStoreFeatureValueType) ToFeatureStoreFeatureValueTypeOutput 

func (e FeatureStoreFeatureValueType) ToFeatureStoreFeatureValueTypeOutput() FeatureStoreFeatureValueTypeOutput

func (FeatureStoreFeatureValueType) ToFeatureStoreFeatureValueTypeOutputWithContext 

func (e FeatureStoreFeatureValueType) ToFeatureStoreFeatureValueTypeOutputWithContext(ctx context.Context) FeatureStoreFeatureValueTypeOutput

func (FeatureStoreFeatureValueType) ToFeatureStoreFeatureValueTypePtrOutput 

func (e FeatureStoreFeatureValueType) ToFeatureStoreFeatureValueTypePtrOutput() FeatureStoreFeatureValueTypePtrOutput

func (FeatureStoreFeatureValueType) ToFeatureStoreFeatureValueTypePtrOutputWithContext 

func (e FeatureStoreFeatureValueType) ToFeatureStoreFeatureValueTypePtrOutputWithContext(ctx context.Context) FeatureStoreFeatureValueTypePtrOutput

func (FeatureStoreFeatureValueType) ToStringOutput 

func (e FeatureStoreFeatureValueType) ToStringOutput() pulumi.StringOutput

func (FeatureStoreFeatureValueType) ToStringOutputWithContext 

func (e FeatureStoreFeatureValueType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (FeatureStoreFeatureValueType) ToStringPtrOutput 

func (e FeatureStoreFeatureValueType) ToStringPtrOutput() pulumi.StringPtrOutput

func (FeatureStoreFeatureValueType) ToStringPtrOutputWithContext 

func (e FeatureStoreFeatureValueType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type FeatureStoreFeatureValueTypeInput 

type FeatureStoreFeatureValueTypeInput interface {
	pulumi.Input

	ToFeatureStoreFeatureValueTypeOutput() FeatureStoreFeatureValueTypeOutput
	ToFeatureStoreFeatureValueTypeOutputWithContext(context.Context) FeatureStoreFeatureValueTypeOutput
}

FeatureStoreFeatureValueTypeInput is an input type that accepts FeatureStoreFeatureValueTypeArgs and FeatureStoreFeatureValueTypeOutput values. You can construct a concrete instance of `FeatureStoreFeatureValueTypeInput` via: 

FeatureStoreFeatureValueTypeArgs{...}

type FeatureStoreFeatureValueTypeOutput 

type FeatureStoreFeatureValueTypeOutput struct{ *pulumi.OutputState }

func (FeatureStoreFeatureValueTypeOutput) ElementType 

func (FeatureStoreFeatureValueTypeOutput) ElementType() reflect.Type

func (FeatureStoreFeatureValueTypeOutput) ToFeatureStoreFeatureValueTypeOutput 

func (o FeatureStoreFeatureValueTypeOutput) ToFeatureStoreFeatureValueTypeOutput() FeatureStoreFeatureValueTypeOutput

func (FeatureStoreFeatureValueTypeOutput) ToFeatureStoreFeatureValueTypeOutputWithContext 

func (o FeatureStoreFeatureValueTypeOutput) ToFeatureStoreFeatureValueTypeOutputWithContext(ctx context.Context) FeatureStoreFeatureValueTypeOutput

func (FeatureStoreFeatureValueTypeOutput) ToFeatureStoreFeatureValueTypePtrOutput 

func (o FeatureStoreFeatureValueTypeOutput) ToFeatureStoreFeatureValueTypePtrOutput() FeatureStoreFeatureValueTypePtrOutput

func (FeatureStoreFeatureValueTypeOutput) ToFeatureStoreFeatureValueTypePtrOutputWithContext 

func (o FeatureStoreFeatureValueTypeOutput) ToFeatureStoreFeatureValueTypePtrOutputWithContext(ctx context.Context) FeatureStoreFeatureValueTypePtrOutput

func (FeatureStoreFeatureValueTypeOutput) ToStringOutput 

func (o FeatureStoreFeatureValueTypeOutput) ToStringOutput() pulumi.StringOutput

func (FeatureStoreFeatureValueTypeOutput) ToStringOutputWithContext 

func (o FeatureStoreFeatureValueTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (FeatureStoreFeatureValueTypeOutput) ToStringPtrOutput 

func (o FeatureStoreFeatureValueTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (FeatureStoreFeatureValueTypeOutput) ToStringPtrOutputWithContext 

func (o FeatureStoreFeatureValueTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type FeatureStoreFeatureValueTypePtrInput 

type FeatureStoreFeatureValueTypePtrInput interface {
	pulumi.Input

	ToFeatureStoreFeatureValueTypePtrOutput() FeatureStoreFeatureValueTypePtrOutput
	ToFeatureStoreFeatureValueTypePtrOutputWithContext(context.Context) FeatureStoreFeatureValueTypePtrOutput
}

func FeatureStoreFeatureValueTypePtr 

func FeatureStoreFeatureValueTypePtr(v string) FeatureStoreFeatureValueTypePtrInput

type FeatureStoreFeatureValueTypePtrOutput 

type FeatureStoreFeatureValueTypePtrOutput struct{ *pulumi.OutputState }

func (FeatureStoreFeatureValueTypePtrOutput) Elem 

func (o FeatureStoreFeatureValueTypePtrOutput) Elem() FeatureStoreFeatureValueTypeOutput

func (FeatureStoreFeatureValueTypePtrOutput) ElementType 

func (FeatureStoreFeatureValueTypePtrOutput) ElementType() reflect.Type

func (FeatureStoreFeatureValueTypePtrOutput) ToFeatureStoreFeatureValueTypePtrOutput 

func (o FeatureStoreFeatureValueTypePtrOutput) ToFeatureStoreFeatureValueTypePtrOutput() FeatureStoreFeatureValueTypePtrOutput

func (FeatureStoreFeatureValueTypePtrOutput) ToFeatureStoreFeatureValueTypePtrOutputWithContext 

func (o FeatureStoreFeatureValueTypePtrOutput) ToFeatureStoreFeatureValueTypePtrOutputWithContext(ctx context.Context) FeatureStoreFeatureValueTypePtrOutput

func (FeatureStoreFeatureValueTypePtrOutput) ToStringPtrOutput 

func (o FeatureStoreFeatureValueTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (FeatureStoreFeatureValueTypePtrOutput) ToStringPtrOutputWithContext 

func (o FeatureStoreFeatureValueTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type FeatureView 

type FeatureView struct {
	pulumi.CustomResourceState

	// Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore.
	BigQuerySource GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput `pulumi:"bigQuerySource"`
	// Timestamp when this FeatureView was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag                 pulumi.StringOutput `pulumi:"etag"`
	FeatureOnlineStoreId pulumi.StringOutput `pulumi:"featureOnlineStoreId"`
	// Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore.
	FeatureRegistrySource GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput `pulumi:"featureRegistrySource"`
	// Required. The ID to use for the FeatureView, which will become the final component of the FeatureView's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a FeatureOnlineStore.
	FeatureViewId pulumi.StringOutput `pulumi:"featureViewId"`
	// Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// Immutable. If set to true, one on demand sync will be run immediately, regardless whether the FeatureView.sync_config is configured or not.
	RunSyncImmediately pulumi.BoolPtrOutput `pulumi:"runSyncImmediately"`
	// Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving.
	SyncConfig GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput `pulumi:"syncConfig"`
	// Timestamp when this FeatureView was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a new FeatureView in a given FeatureOnlineStore. Auto-naming is currently not supported for this resource.

func GetFeatureView 

func GetFeatureView(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *FeatureViewState, opts ...pulumi.ResourceOption) (*FeatureView, error)

GetFeatureView gets an existing FeatureView resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewFeatureView 

func NewFeatureView(ctx *pulumi.Context,
	name string, args *FeatureViewArgs, opts ...pulumi.ResourceOption) (*FeatureView, error)

NewFeatureView registers a new resource with the given unique name, arguments, and options.

func (*FeatureView) ElementType 

func (*FeatureView) ElementType() reflect.Type

func (*FeatureView) ToFeatureViewOutput 

func (i *FeatureView) ToFeatureViewOutput() FeatureViewOutput

func (*FeatureView) ToFeatureViewOutputWithContext 

func (i *FeatureView) ToFeatureViewOutputWithContext(ctx context.Context) FeatureViewOutput

type FeatureViewArgs 

type FeatureViewArgs struct {
	// Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore.
	BigQuerySource GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrInput
	// Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag                 pulumi.StringPtrInput
	FeatureOnlineStoreId pulumi.StringInput
	// Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore.
	FeatureRegistrySource GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrInput
	// Required. The ID to use for the FeatureView, which will become the final component of the FeatureView's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a FeatureOnlineStore.
	FeatureViewId pulumi.StringInput
	// Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	Project  pulumi.StringPtrInput
	// Immutable. If set to true, one on demand sync will be run immediately, regardless whether the FeatureView.sync_config is configured or not.
	RunSyncImmediately pulumi.BoolPtrInput
	// Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving.
	SyncConfig GoogleCloudAiplatformV1FeatureViewSyncConfigPtrInput
}

The set of arguments for constructing a FeatureView resource.

func (FeatureViewArgs) ElementType 

func (FeatureViewArgs) ElementType() reflect.Type

type FeatureViewInput 

type FeatureViewInput interface {
	pulumi.Input

	ToFeatureViewOutput() FeatureViewOutput
	ToFeatureViewOutputWithContext(ctx context.Context) FeatureViewOutput
}

type FeatureViewOutput 

type FeatureViewOutput struct{ *pulumi.OutputState }

func (FeatureViewOutput) BigQuerySource 

func (o FeatureViewOutput) BigQuerySource() GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput

Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore.

func (FeatureViewOutput) CreateTime 

func (o FeatureViewOutput) CreateTime() pulumi.StringOutput

Timestamp when this FeatureView was created.

func (FeatureViewOutput) ElementType 

func (FeatureViewOutput) ElementType() reflect.Type

func (FeatureViewOutput) Etag 

func (o FeatureViewOutput) Etag() pulumi.StringOutput

Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (FeatureViewOutput) FeatureOnlineStoreId 

func (o FeatureViewOutput) FeatureOnlineStoreId() pulumi.StringOutput

func (FeatureViewOutput) FeatureRegistrySource 

func (o FeatureViewOutput) FeatureRegistrySource() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput

Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore.

func (FeatureViewOutput) FeatureViewId 

func (o FeatureViewOutput) FeatureViewId() pulumi.StringOutput

Required. The ID to use for the FeatureView, which will become the final component of the FeatureView's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a FeatureOnlineStore.

func (FeatureViewOutput) Labels 

func (o FeatureViewOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (FeatureViewOutput) Location 

func (o FeatureViewOutput) Location() pulumi.StringOutput

func (FeatureViewOutput) Name 

func (o FeatureViewOutput) Name() pulumi.StringOutput

Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`

func (FeatureViewOutput) Project 

func (o FeatureViewOutput) Project() pulumi.StringOutput

func (FeatureViewOutput) RunSyncImmediately 

func (o FeatureViewOutput) RunSyncImmediately() pulumi.BoolPtrOutput

Immutable. If set to true, one on demand sync will be run immediately, regardless whether the FeatureView.sync_config is configured or not.

func (FeatureViewOutput) SyncConfig 

func (o FeatureViewOutput) SyncConfig() GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput

Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving.

func (FeatureViewOutput) ToFeatureViewOutput 

func (o FeatureViewOutput) ToFeatureViewOutput() FeatureViewOutput

func (FeatureViewOutput) ToFeatureViewOutputWithContext 

func (o FeatureViewOutput) ToFeatureViewOutputWithContext(ctx context.Context) FeatureViewOutput

func (FeatureViewOutput) UpdateTime 

func (o FeatureViewOutput) UpdateTime() pulumi.StringOutput

Timestamp when this FeatureView was last updated.

type FeatureViewState 

type FeatureViewState struct {
}

func (FeatureViewState) ElementType 

func (FeatureViewState) ElementType() reflect.Type

type Featurestore 

type Featurestore struct {
	pulumi.CustomResourceState

	// Timestamp when this Featurestore was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Optional. Customer-managed encryption key spec for data storage. If set, both of the online and offline data storage will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Required. The ID to use for this Featurestore, which will become the final component of the Featurestore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.
	FeaturestoreId pulumi.StringOutput `pulumi:"featurestoreId"`
	// Optional. The labels with user-defined metadata to organize your Featurestore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Featurestore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`
	Name pulumi.StringOutput `pulumi:"name"`
	// Optional. Config for online storage resources. The field should not co-exist with the field of `OnlineStoreReplicationConfig`. If both of it and OnlineStoreReplicationConfig are unset, the feature store will not have an online store and cannot be used for online serving.
	OnlineServingConfig GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput `pulumi:"onlineServingConfig"`
	// Optional. TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than `online_storage_ttl_days` since the feature generation time. Note that `online_storage_ttl_days` should be less than or equal to `offline_storage_ttl_days` for each EntityType under a featurestore. If not set, default to 4000 days
	OnlineStorageTtlDays pulumi.IntOutput    `pulumi:"onlineStorageTtlDays"`
	Project              pulumi.StringOutput `pulumi:"project"`
	// State of the featurestore.
	State pulumi.StringOutput `pulumi:"state"`
	// Timestamp when this Featurestore was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a new Featurestore in a given project and location. Auto-naming is currently not supported for this resource.

func GetFeaturestore 

func GetFeaturestore(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *FeaturestoreState, opts ...pulumi.ResourceOption) (*Featurestore, error)

GetFeaturestore gets an existing Featurestore resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewFeaturestore 

func NewFeaturestore(ctx *pulumi.Context,
	name string, args *FeaturestoreArgs, opts ...pulumi.ResourceOption) (*Featurestore, error)

NewFeaturestore registers a new resource with the given unique name, arguments, and options.

func (*Featurestore) ElementType 

func (*Featurestore) ElementType() reflect.Type

func (*Featurestore) ToFeaturestoreOutput 

func (i *Featurestore) ToFeaturestoreOutput() FeaturestoreOutput

func (*Featurestore) ToFeaturestoreOutputWithContext 

func (i *Featurestore) ToFeaturestoreOutputWithContext(ctx context.Context) FeaturestoreOutput

type FeaturestoreArgs 

type FeaturestoreArgs struct {
	// Optional. Customer-managed encryption key spec for data storage. If set, both of the online and offline data storage will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// Required. The ID to use for this Featurestore, which will become the final component of the Featurestore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.
	FeaturestoreId pulumi.StringInput
	// Optional. The labels with user-defined metadata to organize your Featurestore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Featurestore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// Optional. Config for online storage resources. The field should not co-exist with the field of `OnlineStoreReplicationConfig`. If both of it and OnlineStoreReplicationConfig are unset, the feature store will not have an online store and cannot be used for online serving.
	OnlineServingConfig GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrInput
	// Optional. TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than `online_storage_ttl_days` since the feature generation time. Note that `online_storage_ttl_days` should be less than or equal to `offline_storage_ttl_days` for each EntityType under a featurestore. If not set, default to 4000 days
	OnlineStorageTtlDays pulumi.IntPtrInput
	Project              pulumi.StringPtrInput
}

The set of arguments for constructing a Featurestore resource.

func (FeaturestoreArgs) ElementType 

func (FeaturestoreArgs) ElementType() reflect.Type

type FeaturestoreEntityTypeIamBinding 

type FeaturestoreEntityTypeIamBinding struct {
	pulumi.CustomResourceState

	// An IAM Condition for a given binding. See https://cloud.google.com/iam/docs/conditions-overview for additional details.
	Condition iam.ConditionPtrOutput `pulumi:"condition"`
	// The etag of the resource's IAM policy.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Identities that will be granted the privilege in role. Each entry can have one of the following values:
	//
	//  * user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
	//  * serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
	//  * group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
	//  * domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
	Members pulumi.StringArrayOutput `pulumi:"members"`
	// The name of the resource to manage IAM policies for.
	Name pulumi.StringOutput `pulumi:"name"`
	// The project in which the resource belongs. If it is not provided, a default will be supplied.
	Project pulumi.StringOutput `pulumi:"project"`
	// The role that should be applied. Only one `IamBinding` can be used per role.
	Role pulumi.StringOutput `pulumi:"role"`
}

Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.

func GetFeaturestoreEntityTypeIamBinding 

func GetFeaturestoreEntityTypeIamBinding(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *FeaturestoreEntityTypeIamBindingState, opts ...pulumi.ResourceOption) (*FeaturestoreEntityTypeIamBinding, error)

GetFeaturestoreEntityTypeIamBinding gets an existing FeaturestoreEntityTypeIamBinding resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewFeaturestoreEntityTypeIamBinding 

func NewFeaturestoreEntityTypeIamBinding(ctx *pulumi.Context,
	name string, args *FeaturestoreEntityTypeIamBindingArgs, opts ...pulumi.ResourceOption) (*FeaturestoreEntityTypeIamBinding, error)

NewFeaturestoreEntityTypeIamBinding registers a new resource with the given unique name, arguments, and options.

func (*FeaturestoreEntityTypeIamBinding) ElementType 

func (*FeaturestoreEntityTypeIamBinding) ElementType() reflect.Type

func (*FeaturestoreEntityTypeIamBinding) ToFeaturestoreEntityTypeIamBindingOutput 

func (i *FeaturestoreEntityTypeIamBinding) ToFeaturestoreEntityTypeIamBindingOutput() FeaturestoreEntityTypeIamBindingOutput

func (*FeaturestoreEntityTypeIamBinding) ToFeaturestoreEntityTypeIamBindingOutputWithContext 

func (i *FeaturestoreEntityTypeIamBinding) ToFeaturestoreEntityTypeIamBindingOutputWithContext(ctx context.Context) FeaturestoreEntityTypeIamBindingOutput

type FeaturestoreEntityTypeIamBindingArgs 

type FeaturestoreEntityTypeIamBindingArgs struct {
	// An IAM Condition for a given binding.
	Condition iam.ConditionPtrInput
	// Identities that will be granted the privilege in role. Each entry can have one of the following values:
	//
	//  * user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
	//  * serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
	//  * group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
	//  * domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
	Members pulumi.StringArrayInput
	// The name of the resource to manage IAM policies for.
	Name pulumi.StringInput
	// The role that should be applied. Only one `IamBinding` can be used per role.
	Role pulumi.StringInput
}

The set of arguments for constructing a FeaturestoreEntityTypeIamBinding resource.

func (FeaturestoreEntityTypeIamBindingArgs) ElementType 

func (FeaturestoreEntityTypeIamBindingArgs) ElementType() reflect.Type

type FeaturestoreEntityTypeIamBindingInput 

type FeaturestoreEntityTypeIamBindingInput interface {
	pulumi.Input

	ToFeaturestoreEntityTypeIamBindingOutput() FeaturestoreEntityTypeIamBindingOutput
	ToFeaturestoreEntityTypeIamBindingOutputWithContext(ctx context.Context) FeaturestoreEntityTypeIamBindingOutput
}

type FeaturestoreEntityTypeIamBindingOutput 

type FeaturestoreEntityTypeIamBindingOutput struct{ *pulumi.OutputState }

func (FeaturestoreEntityTypeIamBindingOutput) Condition 

func (o FeaturestoreEntityTypeIamBindingOutput) Condition() iam.ConditionPtrOutput

An IAM Condition for a given binding. See https://cloud.google.com/iam/docs/conditions-overview for additional details.

func (FeaturestoreEntityTypeIamBindingOutput) ElementType 

func (FeaturestoreEntityTypeIamBindingOutput) ElementType() reflect.Type

func (FeaturestoreEntityTypeIamBindingOutput) Etag 

func (o FeaturestoreEntityTypeIamBindingOutput) Etag() pulumi.StringOutput

The etag of the resource's IAM policy.

func (FeaturestoreEntityTypeIamBindingOutput) Members 

func (o FeaturestoreEntityTypeIamBindingOutput) Members() pulumi.StringArrayOutput

Identities that will be granted the privilege in role. Each entry can have one of the following values:

  • user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
  • serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
  • group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
  • domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.

func (FeaturestoreEntityTypeIamBindingOutput) Name 

func (o FeaturestoreEntityTypeIamBindingOutput) Name() pulumi.StringOutput

The name of the resource to manage IAM policies for.

func (FeaturestoreEntityTypeIamBindingOutput) Project 

func (o FeaturestoreEntityTypeIamBindingOutput) Project() pulumi.StringOutput

The project in which the resource belongs. If it is not provided, a default will be supplied.

func (FeaturestoreEntityTypeIamBindingOutput) Role 

func (o FeaturestoreEntityTypeIamBindingOutput) Role() pulumi.StringOutput

The role that should be applied. Only one `IamBinding` can be used per role.

func (FeaturestoreEntityTypeIamBindingOutput) ToFeaturestoreEntityTypeIamBindingOutput 

func (o FeaturestoreEntityTypeIamBindingOutput) ToFeaturestoreEntityTypeIamBindingOutput() FeaturestoreEntityTypeIamBindingOutput

func (FeaturestoreEntityTypeIamBindingOutput) ToFeaturestoreEntityTypeIamBindingOutputWithContext 

func (o FeaturestoreEntityTypeIamBindingOutput) ToFeaturestoreEntityTypeIamBindingOutputWithContext(ctx context.Context) FeaturestoreEntityTypeIamBindingOutput

type FeaturestoreEntityTypeIamBindingState 

type FeaturestoreEntityTypeIamBindingState struct {
}

func (FeaturestoreEntityTypeIamBindingState) ElementType 

func (FeaturestoreEntityTypeIamBindingState) ElementType() reflect.Type

type FeaturestoreEntityTypeIamMember 

type FeaturestoreEntityTypeIamMember struct {
	pulumi.CustomResourceState

	// An IAM Condition for a given binding. See https://cloud.google.com/iam/docs/conditions-overview for additional details.
	Condition iam.ConditionPtrOutput `pulumi:"condition"`
	// The etag of the resource's IAM policy.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Identity that will be granted the privilege in role. The entry can have one of the following values:
	//
	//  * user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
	//  * serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
	//  * group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
	//  * domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
	Member pulumi.StringOutput `pulumi:"member"`
	// The name of the resource to manage IAM policies for.
	Name pulumi.StringOutput `pulumi:"name"`
	// The project in which the resource belongs. If it is not provided, a default will be supplied.
	Project pulumi.StringOutput `pulumi:"project"`
	// The role that should be applied.
	Role pulumi.StringOutput `pulumi:"role"`
}

Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.

func GetFeaturestoreEntityTypeIamMember 

func GetFeaturestoreEntityTypeIamMember(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *FeaturestoreEntityTypeIamMemberState, opts ...pulumi.ResourceOption) (*FeaturestoreEntityTypeIamMember, error)

GetFeaturestoreEntityTypeIamMember gets an existing FeaturestoreEntityTypeIamMember resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewFeaturestoreEntityTypeIamMember 

func NewFeaturestoreEntityTypeIamMember(ctx *pulumi.Context,
	name string, args *FeaturestoreEntityTypeIamMemberArgs, opts ...pulumi.ResourceOption) (*FeaturestoreEntityTypeIamMember, error)

NewFeaturestoreEntityTypeIamMember registers a new resource with the given unique name, arguments, and options.

func (*FeaturestoreEntityTypeIamMember) ElementType 

func (*FeaturestoreEntityTypeIamMember) ElementType() reflect.Type

func (*FeaturestoreEntityTypeIamMember) ToFeaturestoreEntityTypeIamMemberOutput 

func (i *FeaturestoreEntityTypeIamMember) ToFeaturestoreEntityTypeIamMemberOutput() FeaturestoreEntityTypeIamMemberOutput

func (*FeaturestoreEntityTypeIamMember) ToFeaturestoreEntityTypeIamMemberOutputWithContext 

func (i *FeaturestoreEntityTypeIamMember) ToFeaturestoreEntityTypeIamMemberOutputWithContext(ctx context.Context) FeaturestoreEntityTypeIamMemberOutput

type FeaturestoreEntityTypeIamMemberArgs 

type FeaturestoreEntityTypeIamMemberArgs struct {
	// An IAM Condition for a given binding.
	Condition iam.ConditionPtrInput
	// Identity that will be granted the privilege in role. The entry can have one of the following values:
	//
	//  * user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
	//  * serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
	//  * group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
	//  * domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
	Member pulumi.StringInput
	// The name of the resource to manage IAM policies for.
	Name pulumi.StringInput
	// The role that should be applied.
	Role pulumi.StringInput
}

The set of arguments for constructing a FeaturestoreEntityTypeIamMember resource.

func (FeaturestoreEntityTypeIamMemberArgs) ElementType 

func (FeaturestoreEntityTypeIamMemberArgs) ElementType() reflect.Type

type FeaturestoreEntityTypeIamMemberInput 

type FeaturestoreEntityTypeIamMemberInput interface {
	pulumi.Input

	ToFeaturestoreEntityTypeIamMemberOutput() FeaturestoreEntityTypeIamMemberOutput
	ToFeaturestoreEntityTypeIamMemberOutputWithContext(ctx context.Context) FeaturestoreEntityTypeIamMemberOutput
}

type FeaturestoreEntityTypeIamMemberOutput 

type FeaturestoreEntityTypeIamMemberOutput struct{ *pulumi.OutputState }

func (FeaturestoreEntityTypeIamMemberOutput) Condition 

func (o FeaturestoreEntityTypeIamMemberOutput) Condition() iam.ConditionPtrOutput

An IAM Condition for a given binding. See https://cloud.google.com/iam/docs/conditions-overview for additional details.

func (FeaturestoreEntityTypeIamMemberOutput) ElementType 

func (FeaturestoreEntityTypeIamMemberOutput) ElementType() reflect.Type

func (FeaturestoreEntityTypeIamMemberOutput) Etag 

func (o FeaturestoreEntityTypeIamMemberOutput) Etag() pulumi.StringOutput

The etag of the resource's IAM policy.

func (FeaturestoreEntityTypeIamMemberOutput) Member 

func (o FeaturestoreEntityTypeIamMemberOutput) Member() pulumi.StringOutput

Identity that will be granted the privilege in role. The entry can have one of the following values:

  • user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
  • serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
  • group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
  • domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.

func (FeaturestoreEntityTypeIamMemberOutput) Name 

func (o FeaturestoreEntityTypeIamMemberOutput) Name() pulumi.StringOutput

The name of the resource to manage IAM policies for.

func (FeaturestoreEntityTypeIamMemberOutput) Project 

func (o FeaturestoreEntityTypeIamMemberOutput) Project() pulumi.StringOutput

The project in which the resource belongs. If it is not provided, a default will be supplied.

func (FeaturestoreEntityTypeIamMemberOutput) Role 

func (o FeaturestoreEntityTypeIamMemberOutput) Role() pulumi.StringOutput

The role that should be applied.

func (FeaturestoreEntityTypeIamMemberOutput) ToFeaturestoreEntityTypeIamMemberOutput 

func (o FeaturestoreEntityTypeIamMemberOutput) ToFeaturestoreEntityTypeIamMemberOutput() FeaturestoreEntityTypeIamMemberOutput

func (FeaturestoreEntityTypeIamMemberOutput) ToFeaturestoreEntityTypeIamMemberOutputWithContext 

func (o FeaturestoreEntityTypeIamMemberOutput) ToFeaturestoreEntityTypeIamMemberOutputWithContext(ctx context.Context) FeaturestoreEntityTypeIamMemberOutput

type FeaturestoreEntityTypeIamMemberState 

type FeaturestoreEntityTypeIamMemberState struct {
}

func (FeaturestoreEntityTypeIamMemberState) ElementType 

func (FeaturestoreEntityTypeIamMemberState) ElementType() reflect.Type

type FeaturestoreEntityTypeIamPolicy 

type FeaturestoreEntityTypeIamPolicy struct {
	pulumi.CustomResourceState

	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings     GoogleIamV1BindingResponseArrayOutput `pulumi:"bindings"`
	EntityTypeId pulumi.StringOutput                   `pulumi:"entityTypeId"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag           pulumi.StringOutput `pulumi:"etag"`
	FeaturestoreId pulumi.StringOutput `pulumi:"featurestoreId"`
	Location       pulumi.StringOutput `pulumi:"location"`
	Project        pulumi.StringOutput `pulumi:"project"`
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version pulumi.IntOutput `pulumi:"version"`
}

Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors. Note - this resource's API doesn't support deletion. When deleted, the resource will persist on Google Cloud even though it will be deleted from Pulumi state.

func GetFeaturestoreEntityTypeIamPolicy 

func GetFeaturestoreEntityTypeIamPolicy(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *FeaturestoreEntityTypeIamPolicyState, opts ...pulumi.ResourceOption) (*FeaturestoreEntityTypeIamPolicy, error)

GetFeaturestoreEntityTypeIamPolicy gets an existing FeaturestoreEntityTypeIamPolicy resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewFeaturestoreEntityTypeIamPolicy 

func NewFeaturestoreEntityTypeIamPolicy(ctx *pulumi.Context,
	name string, args *FeaturestoreEntityTypeIamPolicyArgs, opts ...pulumi.ResourceOption) (*FeaturestoreEntityTypeIamPolicy, error)

NewFeaturestoreEntityTypeIamPolicy registers a new resource with the given unique name, arguments, and options.

func (*FeaturestoreEntityTypeIamPolicy) ElementType 

func (*FeaturestoreEntityTypeIamPolicy) ElementType() reflect.Type

func (*FeaturestoreEntityTypeIamPolicy) ToFeaturestoreEntityTypeIamPolicyOutput 

func (i *FeaturestoreEntityTypeIamPolicy) ToFeaturestoreEntityTypeIamPolicyOutput() FeaturestoreEntityTypeIamPolicyOutput

func (*FeaturestoreEntityTypeIamPolicy) ToFeaturestoreEntityTypeIamPolicyOutputWithContext 

func (i *FeaturestoreEntityTypeIamPolicy) ToFeaturestoreEntityTypeIamPolicyOutputWithContext(ctx context.Context) FeaturestoreEntityTypeIamPolicyOutput

type FeaturestoreEntityTypeIamPolicyArgs 

type FeaturestoreEntityTypeIamPolicyArgs struct {
	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings     GoogleIamV1BindingArrayInput
	EntityTypeId pulumi.StringInput
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag           pulumi.StringPtrInput
	FeaturestoreId pulumi.StringInput
	Location       pulumi.StringPtrInput
	Project        pulumi.StringPtrInput
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version pulumi.IntPtrInput
}

The set of arguments for constructing a FeaturestoreEntityTypeIamPolicy resource.

func (FeaturestoreEntityTypeIamPolicyArgs) ElementType 

func (FeaturestoreEntityTypeIamPolicyArgs) ElementType() reflect.Type

type FeaturestoreEntityTypeIamPolicyInput 

type FeaturestoreEntityTypeIamPolicyInput interface {
	pulumi.Input

	ToFeaturestoreEntityTypeIamPolicyOutput() FeaturestoreEntityTypeIamPolicyOutput
	ToFeaturestoreEntityTypeIamPolicyOutputWithContext(ctx context.Context) FeaturestoreEntityTypeIamPolicyOutput
}

type FeaturestoreEntityTypeIamPolicyOutput 

type FeaturestoreEntityTypeIamPolicyOutput struct{ *pulumi.OutputState }

func (FeaturestoreEntityTypeIamPolicyOutput) Bindings 

func (o FeaturestoreEntityTypeIamPolicyOutput) Bindings() GoogleIamV1BindingResponseArrayOutput

Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.

func (FeaturestoreEntityTypeIamPolicyOutput) ElementType 

func (FeaturestoreEntityTypeIamPolicyOutput) ElementType() reflect.Type

func (FeaturestoreEntityTypeIamPolicyOutput) EntityTypeId 

func (o FeaturestoreEntityTypeIamPolicyOutput) EntityTypeId() pulumi.StringOutput

func (FeaturestoreEntityTypeIamPolicyOutput) Etag 

func (o FeaturestoreEntityTypeIamPolicyOutput) Etag() pulumi.StringOutput

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.

func (FeaturestoreEntityTypeIamPolicyOutput) FeaturestoreId 

func (o FeaturestoreEntityTypeIamPolicyOutput) FeaturestoreId() pulumi.StringOutput

func (FeaturestoreEntityTypeIamPolicyOutput) Location 

func (o FeaturestoreEntityTypeIamPolicyOutput) Location() pulumi.StringOutput

func (FeaturestoreEntityTypeIamPolicyOutput) Project 

func (o FeaturestoreEntityTypeIamPolicyOutput) Project() pulumi.StringOutput

func (FeaturestoreEntityTypeIamPolicyOutput) ToFeaturestoreEntityTypeIamPolicyOutput 

func (o FeaturestoreEntityTypeIamPolicyOutput) ToFeaturestoreEntityTypeIamPolicyOutput() FeaturestoreEntityTypeIamPolicyOutput

func (FeaturestoreEntityTypeIamPolicyOutput) ToFeaturestoreEntityTypeIamPolicyOutputWithContext 

func (o FeaturestoreEntityTypeIamPolicyOutput) ToFeaturestoreEntityTypeIamPolicyOutputWithContext(ctx context.Context) FeaturestoreEntityTypeIamPolicyOutput

func (FeaturestoreEntityTypeIamPolicyOutput) Version 

func (o FeaturestoreEntityTypeIamPolicyOutput) Version() pulumi.IntOutput

Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).

type FeaturestoreEntityTypeIamPolicyState 

type FeaturestoreEntityTypeIamPolicyState struct {
}

func (FeaturestoreEntityTypeIamPolicyState) ElementType 

func (FeaturestoreEntityTypeIamPolicyState) ElementType() reflect.Type

type FeaturestoreIamBinding 

type FeaturestoreIamBinding struct {
	pulumi.CustomResourceState

	// An IAM Condition for a given binding. See https://cloud.google.com/iam/docs/conditions-overview for additional details.
	Condition iam.ConditionPtrOutput `pulumi:"condition"`
	// The etag of the resource's IAM policy.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Identities that will be granted the privilege in role. Each entry can have one of the following values:
	//
	//  * user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
	//  * serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
	//  * group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
	//  * domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
	Members pulumi.StringArrayOutput `pulumi:"members"`
	// The name of the resource to manage IAM policies for.
	Name pulumi.StringOutput `pulumi:"name"`
	// The project in which the resource belongs. If it is not provided, a default will be supplied.
	Project pulumi.StringOutput `pulumi:"project"`
	// The role that should be applied. Only one `IamBinding` can be used per role.
	Role pulumi.StringOutput `pulumi:"role"`
}

Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.

func GetFeaturestoreIamBinding 

func GetFeaturestoreIamBinding(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *FeaturestoreIamBindingState, opts ...pulumi.ResourceOption) (*FeaturestoreIamBinding, error)

GetFeaturestoreIamBinding gets an existing FeaturestoreIamBinding resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewFeaturestoreIamBinding 

func NewFeaturestoreIamBinding(ctx *pulumi.Context,
	name string, args *FeaturestoreIamBindingArgs, opts ...pulumi.ResourceOption) (*FeaturestoreIamBinding, error)

NewFeaturestoreIamBinding registers a new resource with the given unique name, arguments, and options.

func (*FeaturestoreIamBinding) ElementType 

func (*FeaturestoreIamBinding) ElementType() reflect.Type

func (*FeaturestoreIamBinding) ToFeaturestoreIamBindingOutput 

func (i *FeaturestoreIamBinding) ToFeaturestoreIamBindingOutput() FeaturestoreIamBindingOutput

func (*FeaturestoreIamBinding) ToFeaturestoreIamBindingOutputWithContext 

func (i *FeaturestoreIamBinding) ToFeaturestoreIamBindingOutputWithContext(ctx context.Context) FeaturestoreIamBindingOutput

type FeaturestoreIamBindingArgs 

type FeaturestoreIamBindingArgs struct {
	// An IAM Condition for a given binding.
	Condition iam.ConditionPtrInput
	// Identities that will be granted the privilege in role. Each entry can have one of the following values:
	//
	//  * user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
	//  * serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
	//  * group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
	//  * domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
	Members pulumi.StringArrayInput
	// The name of the resource to manage IAM policies for.
	Name pulumi.StringInput
	// The role that should be applied. Only one `IamBinding` can be used per role.
	Role pulumi.StringInput
}

The set of arguments for constructing a FeaturestoreIamBinding resource.

func (FeaturestoreIamBindingArgs) ElementType 

func (FeaturestoreIamBindingArgs) ElementType() reflect.Type

type FeaturestoreIamBindingInput 

type FeaturestoreIamBindingInput interface {
	pulumi.Input

	ToFeaturestoreIamBindingOutput() FeaturestoreIamBindingOutput
	ToFeaturestoreIamBindingOutputWithContext(ctx context.Context) FeaturestoreIamBindingOutput
}

type FeaturestoreIamBindingOutput 

type FeaturestoreIamBindingOutput struct{ *pulumi.OutputState }

func (FeaturestoreIamBindingOutput) Condition 

func (o FeaturestoreIamBindingOutput) Condition() iam.ConditionPtrOutput

An IAM Condition for a given binding. See https://cloud.google.com/iam/docs/conditions-overview for additional details.

func (FeaturestoreIamBindingOutput) ElementType 

func (FeaturestoreIamBindingOutput) ElementType() reflect.Type

func (FeaturestoreIamBindingOutput) Etag 

func (o FeaturestoreIamBindingOutput) Etag() pulumi.StringOutput

The etag of the resource's IAM policy.

func (FeaturestoreIamBindingOutput) Members 

func (o FeaturestoreIamBindingOutput) Members() pulumi.StringArrayOutput

Identities that will be granted the privilege in role. Each entry can have one of the following values:

  • user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
  • serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
  • group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
  • domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.

func (FeaturestoreIamBindingOutput) Name 

func (o FeaturestoreIamBindingOutput) Name() pulumi.StringOutput

The name of the resource to manage IAM policies for.

func (FeaturestoreIamBindingOutput) Project 

func (o FeaturestoreIamBindingOutput) Project() pulumi.StringOutput

The project in which the resource belongs. If it is not provided, a default will be supplied.

func (FeaturestoreIamBindingOutput) Role 

func (o FeaturestoreIamBindingOutput) Role() pulumi.StringOutput

The role that should be applied. Only one `IamBinding` can be used per role.

func (FeaturestoreIamBindingOutput) ToFeaturestoreIamBindingOutput 

func (o FeaturestoreIamBindingOutput) ToFeaturestoreIamBindingOutput() FeaturestoreIamBindingOutput

func (FeaturestoreIamBindingOutput) ToFeaturestoreIamBindingOutputWithContext 

func (o FeaturestoreIamBindingOutput) ToFeaturestoreIamBindingOutputWithContext(ctx context.Context) FeaturestoreIamBindingOutput

type FeaturestoreIamBindingState 

type FeaturestoreIamBindingState struct {
}

func (FeaturestoreIamBindingState) ElementType 

func (FeaturestoreIamBindingState) ElementType() reflect.Type

type FeaturestoreIamMember 

type FeaturestoreIamMember struct {
	pulumi.CustomResourceState

	// An IAM Condition for a given binding. See https://cloud.google.com/iam/docs/conditions-overview for additional details.
	Condition iam.ConditionPtrOutput `pulumi:"condition"`
	// The etag of the resource's IAM policy.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Identity that will be granted the privilege in role. The entry can have one of the following values:
	//
	//  * user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
	//  * serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
	//  * group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
	//  * domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
	Member pulumi.StringOutput `pulumi:"member"`
	// The name of the resource to manage IAM policies for.
	Name pulumi.StringOutput `pulumi:"name"`
	// The project in which the resource belongs. If it is not provided, a default will be supplied.
	Project pulumi.StringOutput `pulumi:"project"`
	// The role that should be applied.
	Role pulumi.StringOutput `pulumi:"role"`
}

Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.

func GetFeaturestoreIamMember 

func GetFeaturestoreIamMember(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *FeaturestoreIamMemberState, opts ...pulumi.ResourceOption) (*FeaturestoreIamMember, error)

GetFeaturestoreIamMember gets an existing FeaturestoreIamMember resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewFeaturestoreIamMember 

func NewFeaturestoreIamMember(ctx *pulumi.Context,
	name string, args *FeaturestoreIamMemberArgs, opts ...pulumi.ResourceOption) (*FeaturestoreIamMember, error)

NewFeaturestoreIamMember registers a new resource with the given unique name, arguments, and options.

func (*FeaturestoreIamMember) ElementType 

func (*FeaturestoreIamMember) ElementType() reflect.Type

func (*FeaturestoreIamMember) ToFeaturestoreIamMemberOutput 

func (i *FeaturestoreIamMember) ToFeaturestoreIamMemberOutput() FeaturestoreIamMemberOutput

func (*FeaturestoreIamMember) ToFeaturestoreIamMemberOutputWithContext 

func (i *FeaturestoreIamMember) ToFeaturestoreIamMemberOutputWithContext(ctx context.Context) FeaturestoreIamMemberOutput

type FeaturestoreIamMemberArgs 

type FeaturestoreIamMemberArgs struct {
	// An IAM Condition for a given binding.
	Condition iam.ConditionPtrInput
	// Identity that will be granted the privilege in role. The entry can have one of the following values:
	//
	//  * user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
	//  * serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
	//  * group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
	//  * domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
	Member pulumi.StringInput
	// The name of the resource to manage IAM policies for.
	Name pulumi.StringInput
	// The role that should be applied.
	Role pulumi.StringInput
}

The set of arguments for constructing a FeaturestoreIamMember resource.

func (FeaturestoreIamMemberArgs) ElementType 

func (FeaturestoreIamMemberArgs) ElementType() reflect.Type

type FeaturestoreIamMemberInput 

type FeaturestoreIamMemberInput interface {
	pulumi.Input

	ToFeaturestoreIamMemberOutput() FeaturestoreIamMemberOutput
	ToFeaturestoreIamMemberOutputWithContext(ctx context.Context) FeaturestoreIamMemberOutput
}

type FeaturestoreIamMemberOutput 

type FeaturestoreIamMemberOutput struct{ *pulumi.OutputState }

func (FeaturestoreIamMemberOutput) Condition 

func (o FeaturestoreIamMemberOutput) Condition() iam.ConditionPtrOutput

An IAM Condition for a given binding. See https://cloud.google.com/iam/docs/conditions-overview for additional details.

func (FeaturestoreIamMemberOutput) ElementType 

func (FeaturestoreIamMemberOutput) ElementType() reflect.Type

func (FeaturestoreIamMemberOutput) Etag 

func (o FeaturestoreIamMemberOutput) Etag() pulumi.StringOutput

The etag of the resource's IAM policy.

func (FeaturestoreIamMemberOutput) Member 

func (o FeaturestoreIamMemberOutput) Member() pulumi.StringOutput

Identity that will be granted the privilege in role. The entry can have one of the following values:

  • user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
  • serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
  • group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
  • domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.

func (FeaturestoreIamMemberOutput) Name 

func (o FeaturestoreIamMemberOutput) Name() pulumi.StringOutput

The name of the resource to manage IAM policies for.

func (FeaturestoreIamMemberOutput) Project 

func (o FeaturestoreIamMemberOutput) Project() pulumi.StringOutput

The project in which the resource belongs. If it is not provided, a default will be supplied.

func (FeaturestoreIamMemberOutput) Role 

func (o FeaturestoreIamMemberOutput) Role() pulumi.StringOutput

The role that should be applied.

func (FeaturestoreIamMemberOutput) ToFeaturestoreIamMemberOutput 

func (o FeaturestoreIamMemberOutput) ToFeaturestoreIamMemberOutput() FeaturestoreIamMemberOutput

func (FeaturestoreIamMemberOutput) ToFeaturestoreIamMemberOutputWithContext 

func (o FeaturestoreIamMemberOutput) ToFeaturestoreIamMemberOutputWithContext(ctx context.Context) FeaturestoreIamMemberOutput

type FeaturestoreIamMemberState 

type FeaturestoreIamMemberState struct {
}

func (FeaturestoreIamMemberState) ElementType 

func (FeaturestoreIamMemberState) ElementType() reflect.Type

type FeaturestoreIamPolicy 

type FeaturestoreIamPolicy struct {
	pulumi.CustomResourceState

	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings GoogleIamV1BindingResponseArrayOutput `pulumi:"bindings"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag           pulumi.StringOutput `pulumi:"etag"`
	FeaturestoreId pulumi.StringOutput `pulumi:"featurestoreId"`
	Location       pulumi.StringOutput `pulumi:"location"`
	Project        pulumi.StringOutput `pulumi:"project"`
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version pulumi.IntOutput `pulumi:"version"`
}

Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors. Note - this resource's API doesn't support deletion. When deleted, the resource will persist on Google Cloud even though it will be deleted from Pulumi state.

func GetFeaturestoreIamPolicy 

func GetFeaturestoreIamPolicy(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *FeaturestoreIamPolicyState, opts ...pulumi.ResourceOption) (*FeaturestoreIamPolicy, error)

GetFeaturestoreIamPolicy gets an existing FeaturestoreIamPolicy resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewFeaturestoreIamPolicy 

func NewFeaturestoreIamPolicy(ctx *pulumi.Context,
	name string, args *FeaturestoreIamPolicyArgs, opts ...pulumi.ResourceOption) (*FeaturestoreIamPolicy, error)

NewFeaturestoreIamPolicy registers a new resource with the given unique name, arguments, and options.

func (*FeaturestoreIamPolicy) ElementType 

func (*FeaturestoreIamPolicy) ElementType() reflect.Type

func (*FeaturestoreIamPolicy) ToFeaturestoreIamPolicyOutput 

func (i *FeaturestoreIamPolicy) ToFeaturestoreIamPolicyOutput() FeaturestoreIamPolicyOutput

func (*FeaturestoreIamPolicy) ToFeaturestoreIamPolicyOutputWithContext 

func (i *FeaturestoreIamPolicy) ToFeaturestoreIamPolicyOutputWithContext(ctx context.Context) FeaturestoreIamPolicyOutput

type FeaturestoreIamPolicyArgs 

type FeaturestoreIamPolicyArgs struct {
	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings GoogleIamV1BindingArrayInput
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag           pulumi.StringPtrInput
	FeaturestoreId pulumi.StringInput
	Location       pulumi.StringPtrInput
	Project        pulumi.StringPtrInput
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version pulumi.IntPtrInput
}

The set of arguments for constructing a FeaturestoreIamPolicy resource.

func (FeaturestoreIamPolicyArgs) ElementType 

func (FeaturestoreIamPolicyArgs) ElementType() reflect.Type

type FeaturestoreIamPolicyInput 

type FeaturestoreIamPolicyInput interface {
	pulumi.Input

	ToFeaturestoreIamPolicyOutput() FeaturestoreIamPolicyOutput
	ToFeaturestoreIamPolicyOutputWithContext(ctx context.Context) FeaturestoreIamPolicyOutput
}

type FeaturestoreIamPolicyOutput 

type FeaturestoreIamPolicyOutput struct{ *pulumi.OutputState }

func (FeaturestoreIamPolicyOutput) Bindings 

func (o FeaturestoreIamPolicyOutput) Bindings() GoogleIamV1BindingResponseArrayOutput

Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.

func (FeaturestoreIamPolicyOutput) ElementType 

func (FeaturestoreIamPolicyOutput) ElementType() reflect.Type

func (FeaturestoreIamPolicyOutput) Etag 

func (o FeaturestoreIamPolicyOutput) Etag() pulumi.StringOutput

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.

func (FeaturestoreIamPolicyOutput) FeaturestoreId 

func (o FeaturestoreIamPolicyOutput) FeaturestoreId() pulumi.StringOutput

func (FeaturestoreIamPolicyOutput) Location 

func (o FeaturestoreIamPolicyOutput) Location() pulumi.StringOutput

func (FeaturestoreIamPolicyOutput) Project 

func (o FeaturestoreIamPolicyOutput) Project() pulumi.StringOutput

func (FeaturestoreIamPolicyOutput) ToFeaturestoreIamPolicyOutput 

func (o FeaturestoreIamPolicyOutput) ToFeaturestoreIamPolicyOutput() FeaturestoreIamPolicyOutput

func (FeaturestoreIamPolicyOutput) ToFeaturestoreIamPolicyOutputWithContext 

func (o FeaturestoreIamPolicyOutput) ToFeaturestoreIamPolicyOutputWithContext(ctx context.Context) FeaturestoreIamPolicyOutput

func (FeaturestoreIamPolicyOutput) Version 

func (o FeaturestoreIamPolicyOutput) Version() pulumi.IntOutput

Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).

type FeaturestoreIamPolicyState 

type FeaturestoreIamPolicyState struct {
}

func (FeaturestoreIamPolicyState) ElementType 

func (FeaturestoreIamPolicyState) ElementType() reflect.Type

type FeaturestoreInput 

type FeaturestoreInput interface {
	pulumi.Input

	ToFeaturestoreOutput() FeaturestoreOutput
	ToFeaturestoreOutputWithContext(ctx context.Context) FeaturestoreOutput
}

type FeaturestoreOutput 

type FeaturestoreOutput struct{ *pulumi.OutputState }

func (FeaturestoreOutput) CreateTime 

func (o FeaturestoreOutput) CreateTime() pulumi.StringOutput

Timestamp when this Featurestore was created.

func (FeaturestoreOutput) ElementType 

func (FeaturestoreOutput) ElementType() reflect.Type

func (FeaturestoreOutput) EncryptionSpec 

func (o FeaturestoreOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Optional. Customer-managed encryption key spec for data storage. If set, both of the online and offline data storage will be secured by this key.

func (FeaturestoreOutput) Etag 

func (o FeaturestoreOutput) Etag() pulumi.StringOutput

Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (FeaturestoreOutput) FeaturestoreId 

func (o FeaturestoreOutput) FeaturestoreId() pulumi.StringOutput

Required. The ID to use for this Featurestore, which will become the final component of the Featurestore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location.

func (FeaturestoreOutput) Labels 

func (o FeaturestoreOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your Featurestore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Featurestore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (FeaturestoreOutput) Location 

func (o FeaturestoreOutput) Location() pulumi.StringOutput

func (FeaturestoreOutput) Name 

func (o FeaturestoreOutput) Name() pulumi.StringOutput

Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`

func (FeaturestoreOutput) OnlineServingConfig 

func (o FeaturestoreOutput) OnlineServingConfig() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput

Optional. Config for online storage resources. The field should not co-exist with the field of `OnlineStoreReplicationConfig`. If both of it and OnlineStoreReplicationConfig are unset, the feature store will not have an online store and cannot be used for online serving.

func (FeaturestoreOutput) OnlineStorageTtlDays 

func (o FeaturestoreOutput) OnlineStorageTtlDays() pulumi.IntOutput

Optional. TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than `online_storage_ttl_days` since the feature generation time. Note that `online_storage_ttl_days` should be less than or equal to `offline_storage_ttl_days` for each EntityType under a featurestore. If not set, default to 4000 days

func (FeaturestoreOutput) Project 

func (o FeaturestoreOutput) Project() pulumi.StringOutput

func (FeaturestoreOutput) State 

func (o FeaturestoreOutput) State() pulumi.StringOutput

State of the featurestore.

func (FeaturestoreOutput) ToFeaturestoreOutput 

func (o FeaturestoreOutput) ToFeaturestoreOutput() FeaturestoreOutput

func (FeaturestoreOutput) ToFeaturestoreOutputWithContext 

func (o FeaturestoreOutput) ToFeaturestoreOutputWithContext(ctx context.Context) FeaturestoreOutput

func (FeaturestoreOutput) UpdateTime 

func (o FeaturestoreOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Featurestore was last updated.

type FeaturestoreState 

type FeaturestoreState struct {
}

func (FeaturestoreState) ElementType 

func (FeaturestoreState) ElementType() reflect.Type

type GoogleCloudAiplatformV1ActiveLearningConfig 

type GoogleCloudAiplatformV1ActiveLearningConfig struct {
	// Max number of human labeled DataItems.
	MaxDataItemCount *string `pulumi:"maxDataItemCount"`
	// Max percent of total DataItems for human labeling.
	MaxDataItemPercentage *int `pulumi:"maxDataItemPercentage"`
	// Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
	SampleConfig *GoogleCloudAiplatformV1SampleConfig `pulumi:"sampleConfig"`
	// CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.
	TrainingConfig *GoogleCloudAiplatformV1TrainingConfig `pulumi:"trainingConfig"`
}

Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.

type GoogleCloudAiplatformV1ActiveLearningConfigArgs 

type GoogleCloudAiplatformV1ActiveLearningConfigArgs struct {
	// Max number of human labeled DataItems.
	MaxDataItemCount pulumi.StringPtrInput `pulumi:"maxDataItemCount"`
	// Max percent of total DataItems for human labeling.
	MaxDataItemPercentage pulumi.IntPtrInput `pulumi:"maxDataItemPercentage"`
	// Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
	SampleConfig GoogleCloudAiplatformV1SampleConfigPtrInput `pulumi:"sampleConfig"`
	// CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.
	TrainingConfig GoogleCloudAiplatformV1TrainingConfigPtrInput `pulumi:"trainingConfig"`
}

Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.

func (GoogleCloudAiplatformV1ActiveLearningConfigArgs) ElementType 

func (GoogleCloudAiplatformV1ActiveLearningConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ActiveLearningConfigArgs) ToGoogleCloudAiplatformV1ActiveLearningConfigOutput 

func (i GoogleCloudAiplatformV1ActiveLearningConfigArgs) ToGoogleCloudAiplatformV1ActiveLearningConfigOutput() GoogleCloudAiplatformV1ActiveLearningConfigOutput

func (GoogleCloudAiplatformV1ActiveLearningConfigArgs) ToGoogleCloudAiplatformV1ActiveLearningConfigOutputWithContext 

func (i GoogleCloudAiplatformV1ActiveLearningConfigArgs) ToGoogleCloudAiplatformV1ActiveLearningConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ActiveLearningConfigOutput

func (GoogleCloudAiplatformV1ActiveLearningConfigArgs) ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutput 

func (i GoogleCloudAiplatformV1ActiveLearningConfigArgs) ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutput() GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput

func (GoogleCloudAiplatformV1ActiveLearningConfigArgs) ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ActiveLearningConfigArgs) ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput

type GoogleCloudAiplatformV1ActiveLearningConfigInput 

type GoogleCloudAiplatformV1ActiveLearningConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ActiveLearningConfigOutput() GoogleCloudAiplatformV1ActiveLearningConfigOutput
	ToGoogleCloudAiplatformV1ActiveLearningConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1ActiveLearningConfigOutput
}

GoogleCloudAiplatformV1ActiveLearningConfigInput is an input type that accepts GoogleCloudAiplatformV1ActiveLearningConfigArgs and GoogleCloudAiplatformV1ActiveLearningConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ActiveLearningConfigInput` via: 

GoogleCloudAiplatformV1ActiveLearningConfigArgs{...}

type GoogleCloudAiplatformV1ActiveLearningConfigOutput 

type GoogleCloudAiplatformV1ActiveLearningConfigOutput struct{ *pulumi.OutputState }

Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.

func (GoogleCloudAiplatformV1ActiveLearningConfigOutput) ElementType 

func (GoogleCloudAiplatformV1ActiveLearningConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ActiveLearningConfigOutput) MaxDataItemCount 

func (o GoogleCloudAiplatformV1ActiveLearningConfigOutput) MaxDataItemCount() pulumi.StringPtrOutput

Max number of human labeled DataItems.

func (GoogleCloudAiplatformV1ActiveLearningConfigOutput) MaxDataItemPercentage 

func (o GoogleCloudAiplatformV1ActiveLearningConfigOutput) MaxDataItemPercentage() pulumi.IntPtrOutput

Max percent of total DataItems for human labeling.

func (GoogleCloudAiplatformV1ActiveLearningConfigOutput) SampleConfig 

func (o GoogleCloudAiplatformV1ActiveLearningConfigOutput) SampleConfig() GoogleCloudAiplatformV1SampleConfigPtrOutput

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

func (GoogleCloudAiplatformV1ActiveLearningConfigOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigOutput 

func (o GoogleCloudAiplatformV1ActiveLearningConfigOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigOutput() GoogleCloudAiplatformV1ActiveLearningConfigOutput

func (GoogleCloudAiplatformV1ActiveLearningConfigOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigOutputWithContext 

func (o GoogleCloudAiplatformV1ActiveLearningConfigOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ActiveLearningConfigOutput

func (GoogleCloudAiplatformV1ActiveLearningConfigOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutput 

func (o GoogleCloudAiplatformV1ActiveLearningConfigOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutput() GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput

func (GoogleCloudAiplatformV1ActiveLearningConfigOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ActiveLearningConfigOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput

func (GoogleCloudAiplatformV1ActiveLearningConfigOutput) TrainingConfig 

func (o GoogleCloudAiplatformV1ActiveLearningConfigOutput) TrainingConfig() GoogleCloudAiplatformV1TrainingConfigPtrOutput

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

type GoogleCloudAiplatformV1ActiveLearningConfigPtrInput 

type GoogleCloudAiplatformV1ActiveLearningConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutput() GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput
	ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput
}

GoogleCloudAiplatformV1ActiveLearningConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1ActiveLearningConfigArgs, GoogleCloudAiplatformV1ActiveLearningConfigPtr and GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ActiveLearningConfigPtrInput` via: 

        GoogleCloudAiplatformV1ActiveLearningConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ActiveLearningConfigPtr 

func GoogleCloudAiplatformV1ActiveLearningConfigPtr(v *GoogleCloudAiplatformV1ActiveLearningConfigArgs) GoogleCloudAiplatformV1ActiveLearningConfigPtrInput

type GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput 

type GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) Elem() GoogleCloudAiplatformV1ActiveLearningConfigOutput

func (GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) MaxDataItemCount 

func (o GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) MaxDataItemCount() pulumi.StringPtrOutput

Max number of human labeled DataItems.

func (GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) MaxDataItemPercentage 

func (o GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) MaxDataItemPercentage() pulumi.IntPtrOutput

Max percent of total DataItems for human labeling.

func (GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) SampleConfig 

func (o GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) SampleConfig() GoogleCloudAiplatformV1SampleConfigPtrOutput

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

func (GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutput 

func (o GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutput() GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput

func (GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput

func (GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) TrainingConfig 

func (o GoogleCloudAiplatformV1ActiveLearningConfigPtrOutput) TrainingConfig() GoogleCloudAiplatformV1TrainingConfigPtrOutput

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

type GoogleCloudAiplatformV1ActiveLearningConfigResponse 

type GoogleCloudAiplatformV1ActiveLearningConfigResponse struct {
	// Max number of human labeled DataItems.
	MaxDataItemCount string `pulumi:"maxDataItemCount"`
	// Max percent of total DataItems for human labeling.
	MaxDataItemPercentage int `pulumi:"maxDataItemPercentage"`
	// Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
	SampleConfig GoogleCloudAiplatformV1SampleConfigResponse `pulumi:"sampleConfig"`
	// CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.
	TrainingConfig GoogleCloudAiplatformV1TrainingConfigResponse `pulumi:"trainingConfig"`
}

Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.

type GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput 

type GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput struct{ *pulumi.OutputState }

Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.

func (GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) MaxDataItemCount 

func (o GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) MaxDataItemCount() pulumi.StringOutput

Max number of human labeled DataItems.

func (GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) MaxDataItemPercentage 

func (o GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) MaxDataItemPercentage() pulumi.IntOutput

Max percent of total DataItems for human labeling.

func (GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) SampleConfig 

func (o GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) SampleConfig() GoogleCloudAiplatformV1SampleConfigResponseOutput

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

func (GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigResponseOutput 

func (o GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigResponseOutput() GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput

func (GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) ToGoogleCloudAiplatformV1ActiveLearningConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput

func (GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) TrainingConfig 

func (o GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput) TrainingConfig() GoogleCloudAiplatformV1TrainingConfigResponseOutput

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

type GoogleCloudAiplatformV1AutomaticResourcesResponse 

type GoogleCloudAiplatformV1AutomaticResourcesResponse struct {
	// Immutable. The maximum number of replicas this DeployedModel may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale the model to that many replicas is guaranteed (barring service outages). If traffic against the DeployedModel increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, a no upper bound for scaling under heavy traffic will be assume, though Vertex AI may be unable to scale beyond certain replica number.
	MaxReplicaCount int `pulumi:"maxReplicaCount"`
	// Immutable. The minimum number of replicas this DeployedModel will be always deployed on. If traffic against it increases, it may dynamically be deployed onto more replicas up to max_replica_count, and as traffic decreases, some of these extra replicas may be freed. If the requested value is too large, the deployment will error.
	MinReplicaCount int `pulumi:"minReplicaCount"`
}

A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. Each Model supporting these resources documents its specific guidelines.

type GoogleCloudAiplatformV1AutomaticResourcesResponseOutput 

type GoogleCloudAiplatformV1AutomaticResourcesResponseOutput struct{ *pulumi.OutputState }

A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. Each Model supporting these resources documents its specific guidelines.

func (GoogleCloudAiplatformV1AutomaticResourcesResponseOutput) ElementType 

func (GoogleCloudAiplatformV1AutomaticResourcesResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1AutomaticResourcesResponseOutput) MaxReplicaCount 

func (o GoogleCloudAiplatformV1AutomaticResourcesResponseOutput) MaxReplicaCount() pulumi.IntOutput

Immutable. The maximum number of replicas this DeployedModel may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale the model to that many replicas is guaranteed (barring service outages). If traffic against the DeployedModel increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, a no upper bound for scaling under heavy traffic will be assume, though Vertex AI may be unable to scale beyond certain replica number.

func (GoogleCloudAiplatformV1AutomaticResourcesResponseOutput) MinReplicaCount 

func (o GoogleCloudAiplatformV1AutomaticResourcesResponseOutput) MinReplicaCount() pulumi.IntOutput

Immutable. The minimum number of replicas this DeployedModel will be always deployed on. If traffic against it increases, it may dynamically be deployed onto more replicas up to max_replica_count, and as traffic decreases, some of these extra replicas may be freed. If the requested value is too large, the deployment will error.

func (GoogleCloudAiplatformV1AutomaticResourcesResponseOutput) ToGoogleCloudAiplatformV1AutomaticResourcesResponseOutput 

func (o GoogleCloudAiplatformV1AutomaticResourcesResponseOutput) ToGoogleCloudAiplatformV1AutomaticResourcesResponseOutput() GoogleCloudAiplatformV1AutomaticResourcesResponseOutput

func (GoogleCloudAiplatformV1AutomaticResourcesResponseOutput) ToGoogleCloudAiplatformV1AutomaticResourcesResponseOutputWithContext 

func (o GoogleCloudAiplatformV1AutomaticResourcesResponseOutput) ToGoogleCloudAiplatformV1AutomaticResourcesResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1AutomaticResourcesResponseOutput

type GoogleCloudAiplatformV1AutoscalingMetricSpec 

type GoogleCloudAiplatformV1AutoscalingMetricSpec struct {
	// The resource metric name. Supported metrics: * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle` * `aiplatform.googleapis.com/prediction/online/cpu/utilization`
	MetricName string `pulumi:"metricName"`
	// The target resource utilization in percentage (1% - 100%) for the given metric; once the real usage deviates from the target by a certain percentage, the machine replicas change. The default value is 60 (representing 60%) if not provided.
	Target *int `pulumi:"target"`
}

The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count.

type GoogleCloudAiplatformV1AutoscalingMetricSpecArgs 

type GoogleCloudAiplatformV1AutoscalingMetricSpecArgs struct {
	// The resource metric name. Supported metrics: * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle` * `aiplatform.googleapis.com/prediction/online/cpu/utilization`
	MetricName pulumi.StringInput `pulumi:"metricName"`
	// The target resource utilization in percentage (1% - 100%) for the given metric; once the real usage deviates from the target by a certain percentage, the machine replicas change. The default value is 60 (representing 60%) if not provided.
	Target pulumi.IntPtrInput `pulumi:"target"`
}

The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count.

func (GoogleCloudAiplatformV1AutoscalingMetricSpecArgs) ElementType 

func (GoogleCloudAiplatformV1AutoscalingMetricSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1AutoscalingMetricSpecArgs) ToGoogleCloudAiplatformV1AutoscalingMetricSpecOutput 

func (i GoogleCloudAiplatformV1AutoscalingMetricSpecArgs) ToGoogleCloudAiplatformV1AutoscalingMetricSpecOutput() GoogleCloudAiplatformV1AutoscalingMetricSpecOutput

func (GoogleCloudAiplatformV1AutoscalingMetricSpecArgs) ToGoogleCloudAiplatformV1AutoscalingMetricSpecOutputWithContext 

func (i GoogleCloudAiplatformV1AutoscalingMetricSpecArgs) ToGoogleCloudAiplatformV1AutoscalingMetricSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1AutoscalingMetricSpecOutput

type GoogleCloudAiplatformV1AutoscalingMetricSpecArray 

type GoogleCloudAiplatformV1AutoscalingMetricSpecArray []GoogleCloudAiplatformV1AutoscalingMetricSpecInput

func (GoogleCloudAiplatformV1AutoscalingMetricSpecArray) ElementType 

func (GoogleCloudAiplatformV1AutoscalingMetricSpecArray) ElementType() reflect.Type

func (GoogleCloudAiplatformV1AutoscalingMetricSpecArray) ToGoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput 

func (i GoogleCloudAiplatformV1AutoscalingMetricSpecArray) ToGoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput() GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput

func (GoogleCloudAiplatformV1AutoscalingMetricSpecArray) ToGoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutputWithContext 

func (i GoogleCloudAiplatformV1AutoscalingMetricSpecArray) ToGoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput

type GoogleCloudAiplatformV1AutoscalingMetricSpecArrayInput 

type GoogleCloudAiplatformV1AutoscalingMetricSpecArrayInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput() GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput
	ToGoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutputWithContext(context.Context) GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput
}

GoogleCloudAiplatformV1AutoscalingMetricSpecArrayInput is an input type that accepts GoogleCloudAiplatformV1AutoscalingMetricSpecArray and GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1AutoscalingMetricSpecArrayInput` via: 

GoogleCloudAiplatformV1AutoscalingMetricSpecArray{ GoogleCloudAiplatformV1AutoscalingMetricSpecArgs{...} }

type GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput 

type GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput) ElementType 

func (GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput) Index 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1AutoscalingMetricSpecOutput

func (GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput() GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput

func (GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutputWithContext 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput

type GoogleCloudAiplatformV1AutoscalingMetricSpecInput 

type GoogleCloudAiplatformV1AutoscalingMetricSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1AutoscalingMetricSpecOutput() GoogleCloudAiplatformV1AutoscalingMetricSpecOutput
	ToGoogleCloudAiplatformV1AutoscalingMetricSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1AutoscalingMetricSpecOutput
}

GoogleCloudAiplatformV1AutoscalingMetricSpecInput is an input type that accepts GoogleCloudAiplatformV1AutoscalingMetricSpecArgs and GoogleCloudAiplatformV1AutoscalingMetricSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1AutoscalingMetricSpecInput` via: 

GoogleCloudAiplatformV1AutoscalingMetricSpecArgs{...}

type GoogleCloudAiplatformV1AutoscalingMetricSpecOutput 

type GoogleCloudAiplatformV1AutoscalingMetricSpecOutput struct{ *pulumi.OutputState }

The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count.

func (GoogleCloudAiplatformV1AutoscalingMetricSpecOutput) ElementType 

func (GoogleCloudAiplatformV1AutoscalingMetricSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1AutoscalingMetricSpecOutput) MetricName 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecOutput) MetricName() pulumi.StringOutput

The resource metric name. Supported metrics: * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle` * `aiplatform.googleapis.com/prediction/online/cpu/utilization`

func (GoogleCloudAiplatformV1AutoscalingMetricSpecOutput) Target 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecOutput) Target() pulumi.IntPtrOutput

The target resource utilization in percentage (1% - 100%) for the given metric; once the real usage deviates from the target by a certain percentage, the machine replicas change. The default value is 60 (representing 60%) if not provided.

func (GoogleCloudAiplatformV1AutoscalingMetricSpecOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecOutput 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecOutput() GoogleCloudAiplatformV1AutoscalingMetricSpecOutput

func (GoogleCloudAiplatformV1AutoscalingMetricSpecOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecOutputWithContext 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1AutoscalingMetricSpecOutput

type GoogleCloudAiplatformV1AutoscalingMetricSpecResponse 

type GoogleCloudAiplatformV1AutoscalingMetricSpecResponse struct {
	// The resource metric name. Supported metrics: * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle` * `aiplatform.googleapis.com/prediction/online/cpu/utilization`
	MetricName string `pulumi:"metricName"`
	// The target resource utilization in percentage (1% - 100%) for the given metric; once the real usage deviates from the target by a certain percentage, the machine replicas change. The default value is 60 (representing 60%) if not provided.
	Target int `pulumi:"target"`
}

The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count.

type GoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput 

type GoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput

func (GoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput() GoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput

func (GoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput

type GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput 

type GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput struct{ *pulumi.OutputState }

The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count.

func (GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput) MetricName 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput) MetricName() pulumi.StringOutput

The resource metric name. Supported metrics: * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle` * `aiplatform.googleapis.com/prediction/online/cpu/utilization`

func (GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput) Target 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput) Target() pulumi.IntOutput

The target resource utilization in percentage (1% - 100%) for the given metric; once the real usage deviates from the target by a certain percentage, the machine replicas change. The default value is 60 (representing 60%) if not provided.

func (GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput() GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput

func (GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput) ToGoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1AutoscalingMetricSpecResponseOutput

type GoogleCloudAiplatformV1BatchDedicatedResources 

type GoogleCloudAiplatformV1BatchDedicatedResources struct {
	// Immutable. The specification of a single machine.
	MachineSpec GoogleCloudAiplatformV1MachineSpec `pulumi:"machineSpec"`
	// Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.
	MaxReplicaCount *int `pulumi:"maxReplicaCount"`
	// Immutable. The number of machine replicas used at the start of the batch operation. If not set, Vertex AI decides starting number, not greater than max_replica_count
	StartingReplicaCount *int `pulumi:"startingReplicaCount"`
}

A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.

type GoogleCloudAiplatformV1BatchDedicatedResourcesArgs 

type GoogleCloudAiplatformV1BatchDedicatedResourcesArgs struct {
	// Immutable. The specification of a single machine.
	MachineSpec GoogleCloudAiplatformV1MachineSpecInput `pulumi:"machineSpec"`
	// Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.
	MaxReplicaCount pulumi.IntPtrInput `pulumi:"maxReplicaCount"`
	// Immutable. The number of machine replicas used at the start of the batch operation. If not set, Vertex AI decides starting number, not greater than max_replica_count
	StartingReplicaCount pulumi.IntPtrInput `pulumi:"startingReplicaCount"`
}

A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.

func (GoogleCloudAiplatformV1BatchDedicatedResourcesArgs) ElementType 

func (GoogleCloudAiplatformV1BatchDedicatedResourcesArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchDedicatedResourcesArgs) ToGoogleCloudAiplatformV1BatchDedicatedResourcesOutput 

func (i GoogleCloudAiplatformV1BatchDedicatedResourcesArgs) ToGoogleCloudAiplatformV1BatchDedicatedResourcesOutput() GoogleCloudAiplatformV1BatchDedicatedResourcesOutput

func (GoogleCloudAiplatformV1BatchDedicatedResourcesArgs) ToGoogleCloudAiplatformV1BatchDedicatedResourcesOutputWithContext 

func (i GoogleCloudAiplatformV1BatchDedicatedResourcesArgs) ToGoogleCloudAiplatformV1BatchDedicatedResourcesOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchDedicatedResourcesOutput

func (GoogleCloudAiplatformV1BatchDedicatedResourcesArgs) ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput 

func (i GoogleCloudAiplatformV1BatchDedicatedResourcesArgs) ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput() GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput

func (GoogleCloudAiplatformV1BatchDedicatedResourcesArgs) ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutputWithContext 

func (i GoogleCloudAiplatformV1BatchDedicatedResourcesArgs) ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput

type GoogleCloudAiplatformV1BatchDedicatedResourcesInput 

type GoogleCloudAiplatformV1BatchDedicatedResourcesInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1BatchDedicatedResourcesOutput() GoogleCloudAiplatformV1BatchDedicatedResourcesOutput
	ToGoogleCloudAiplatformV1BatchDedicatedResourcesOutputWithContext(context.Context) GoogleCloudAiplatformV1BatchDedicatedResourcesOutput
}

GoogleCloudAiplatformV1BatchDedicatedResourcesInput is an input type that accepts GoogleCloudAiplatformV1BatchDedicatedResourcesArgs and GoogleCloudAiplatformV1BatchDedicatedResourcesOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1BatchDedicatedResourcesInput` via: 

GoogleCloudAiplatformV1BatchDedicatedResourcesArgs{...}

type GoogleCloudAiplatformV1BatchDedicatedResourcesOutput 

type GoogleCloudAiplatformV1BatchDedicatedResourcesOutput struct{ *pulumi.OutputState }

A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.

func (GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) ElementType 

func (GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) MachineSpec 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) MachineSpec() GoogleCloudAiplatformV1MachineSpecOutput

Immutable. The specification of a single machine.

func (GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) MaxReplicaCount 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) MaxReplicaCount() pulumi.IntPtrOutput

Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.

func (GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) StartingReplicaCount 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) StartingReplicaCount() pulumi.IntPtrOutput

Immutable. The number of machine replicas used at the start of the batch operation. If not set, Vertex AI decides starting number, not greater than max_replica_count

func (GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesOutput 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesOutput() GoogleCloudAiplatformV1BatchDedicatedResourcesOutput

func (GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesOutputWithContext 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchDedicatedResourcesOutput

func (GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput() GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput

func (GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutputWithContext 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput

type GoogleCloudAiplatformV1BatchDedicatedResourcesPtrInput 

type GoogleCloudAiplatformV1BatchDedicatedResourcesPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput() GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput
	ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput
}

GoogleCloudAiplatformV1BatchDedicatedResourcesPtrInput is an input type that accepts GoogleCloudAiplatformV1BatchDedicatedResourcesArgs, GoogleCloudAiplatformV1BatchDedicatedResourcesPtr and GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1BatchDedicatedResourcesPtrInput` via: 

        GoogleCloudAiplatformV1BatchDedicatedResourcesArgs{...}

or:

        nil

func GoogleCloudAiplatformV1BatchDedicatedResourcesPtr 

func GoogleCloudAiplatformV1BatchDedicatedResourcesPtr(v *GoogleCloudAiplatformV1BatchDedicatedResourcesArgs) GoogleCloudAiplatformV1BatchDedicatedResourcesPtrInput

type GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput 

type GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) Elem 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) Elem() GoogleCloudAiplatformV1BatchDedicatedResourcesOutput

func (GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) ElementType 

func (GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) MachineSpec 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) MachineSpec() GoogleCloudAiplatformV1MachineSpecPtrOutput

Immutable. The specification of a single machine.

func (GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) MaxReplicaCount 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) MaxReplicaCount() pulumi.IntPtrOutput

Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.

func (GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) StartingReplicaCount 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) StartingReplicaCount() pulumi.IntPtrOutput

Immutable. The number of machine replicas used at the start of the batch operation. If not set, Vertex AI decides starting number, not greater than max_replica_count

func (GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput() GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput

func (GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutputWithContext 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchDedicatedResourcesPtrOutput

type GoogleCloudAiplatformV1BatchDedicatedResourcesResponse 

type GoogleCloudAiplatformV1BatchDedicatedResourcesResponse struct {
	// Immutable. The specification of a single machine.
	MachineSpec GoogleCloudAiplatformV1MachineSpecResponse `pulumi:"machineSpec"`
	// Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.
	MaxReplicaCount int `pulumi:"maxReplicaCount"`
	// Immutable. The number of machine replicas used at the start of the batch operation. If not set, Vertex AI decides starting number, not greater than max_replica_count
	StartingReplicaCount int `pulumi:"startingReplicaCount"`
}

A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.

type GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput 

type GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput struct{ *pulumi.OutputState }

A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.

func (GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput) ElementType 

func (GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput) MachineSpec 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput) MachineSpec() GoogleCloudAiplatformV1MachineSpecResponseOutput

Immutable. The specification of a single machine.

func (GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput) MaxReplicaCount 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput) MaxReplicaCount() pulumi.IntOutput

Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.

func (GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput) StartingReplicaCount 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput) StartingReplicaCount() pulumi.IntOutput

Immutable. The number of machine replicas used at the start of the batch operation. If not set, Vertex AI decides starting number, not greater than max_replica_count

func (GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput() GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput

func (GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutputWithContext 

func (o GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput) ToGoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput

type GoogleCloudAiplatformV1BatchPredictionJobInputConfig 

type GoogleCloudAiplatformV1BatchPredictionJobInputConfig struct {
	// The BigQuery location of the input table. The schema of the table should be in the format described by the given context OpenAPI Schema, if one is provided. The table may contain additional columns that are not described by the schema, and they will be ignored.
	BigquerySource *GoogleCloudAiplatformV1BigQuerySource `pulumi:"bigquerySource"`
	// The Cloud Storage location for the input instances.
	GcsSource *GoogleCloudAiplatformV1GcsSource `pulumi:"gcsSource"`
	// The format in which instances are given, must be one of the Model's supported_input_storage_formats.
	InstancesFormat string `pulumi:"instancesFormat"`
}

Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them.

type GoogleCloudAiplatformV1BatchPredictionJobInputConfigArgs 

type GoogleCloudAiplatformV1BatchPredictionJobInputConfigArgs struct {
	// The BigQuery location of the input table. The schema of the table should be in the format described by the given context OpenAPI Schema, if one is provided. The table may contain additional columns that are not described by the schema, and they will be ignored.
	BigquerySource GoogleCloudAiplatformV1BigQuerySourcePtrInput `pulumi:"bigquerySource"`
	// The Cloud Storage location for the input instances.
	GcsSource GoogleCloudAiplatformV1GcsSourcePtrInput `pulumi:"gcsSource"`
	// The format in which instances are given, must be one of the Model's supported_input_storage_formats.
	InstancesFormat pulumi.StringInput `pulumi:"instancesFormat"`
}

Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them.

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigArgs) ElementType 

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput 

func (i GoogleCloudAiplatformV1BatchPredictionJobInputConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput() GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigOutputWithContext 

func (i GoogleCloudAiplatformV1BatchPredictionJobInputConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput

type GoogleCloudAiplatformV1BatchPredictionJobInputConfigInput 

type GoogleCloudAiplatformV1BatchPredictionJobInputConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput() GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput
	ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput
}

GoogleCloudAiplatformV1BatchPredictionJobInputConfigInput is an input type that accepts GoogleCloudAiplatformV1BatchPredictionJobInputConfigArgs and GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1BatchPredictionJobInputConfigInput` via: 

GoogleCloudAiplatformV1BatchPredictionJobInputConfigArgs{...}

type GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput 

type GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput struct{ *pulumi.OutputState }

Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them.

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput) BigquerySource 

func (o GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput) BigquerySource() GoogleCloudAiplatformV1BigQuerySourcePtrOutput

The BigQuery location of the input table. The schema of the table should be in the format described by the given context OpenAPI Schema, if one is provided. The table may contain additional columns that are not described by the schema, and they will be ignored.

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput) ElementType 

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput) GcsSource 

func (o GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput) GcsSource() GoogleCloudAiplatformV1GcsSourcePtrOutput

The Cloud Storage location for the input instances.

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput) InstancesFormat 

func (o GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput) InstancesFormat() pulumi.StringOutput

The format in which instances are given, must be one of the Model's supported_input_storage_formats.

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput 

func (o GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput() GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigOutputWithContext 

func (o GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchPredictionJobInputConfigOutput

type GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponse 

type GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponse struct {
	// The BigQuery location of the input table. The schema of the table should be in the format described by the given context OpenAPI Schema, if one is provided. The table may contain additional columns that are not described by the schema, and they will be ignored.
	BigquerySource GoogleCloudAiplatformV1BigQuerySourceResponse `pulumi:"bigquerySource"`
	// The Cloud Storage location for the input instances.
	GcsSource GoogleCloudAiplatformV1GcsSourceResponse `pulumi:"gcsSource"`
	// The format in which instances are given, must be one of the Model's supported_input_storage_formats.
	InstancesFormat string `pulumi:"instancesFormat"`
}

Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them.

type GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput 

type GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput struct{ *pulumi.OutputState }

Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them.

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput) BigquerySource 

func (o GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput) BigquerySource() GoogleCloudAiplatformV1BigQuerySourceResponseOutput

The BigQuery location of the input table. The schema of the table should be in the format described by the given context OpenAPI Schema, if one is provided. The table may contain additional columns that are not described by the schema, and they will be ignored.

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput) GcsSource 

func (o GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput) GcsSource() GoogleCloudAiplatformV1GcsSourceResponseOutput

The Cloud Storage location for the input instances.

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput) InstancesFormat 

func (o GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput) InstancesFormat() pulumi.StringOutput

The format in which instances are given, must be one of the Model's supported_input_storage_formats.

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput 

func (o GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput() GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput

func (GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfig 

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfig struct {
	// Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
	ExcludedFields []string `pulumi:"excludedFields"`
	// Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
	IncludedFields []string `pulumi:"includedFields"`
	// The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf-record-gzip`, each record will be converted to an object in the format of `{"b64": }`, where “is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{"b64": }`, where“ is the Base64-encoded string of the content of the file.
	InstanceType *string `pulumi:"instanceType"`
	// The name of the field that is considered as a key. The values identified by the key field is not included in the transformed instances that is sent to the Model. This is similar to specifying this name of the field in excluded_fields. In addition, the batch prediction output will not include the instances. Instead the output will only include the value of the key field, in a field named `key` in the output: * For `jsonl` output format, the output will have a `key` field instead of the `instance` field. * For `csv`/`bigquery` output format, the output will have have a `key` column instead of the instance feature columns. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
	KeyField *string `pulumi:"keyField"`
}

Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs 

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs struct {
	// Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
	ExcludedFields pulumi.StringArrayInput `pulumi:"excludedFields"`
	// Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
	IncludedFields pulumi.StringArrayInput `pulumi:"includedFields"`
	// The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf-record-gzip`, each record will be converted to an object in the format of `{"b64": }`, where “is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{"b64": }`, where“ is the Base64-encoded string of the content of the file.
	InstanceType pulumi.StringPtrInput `pulumi:"instanceType"`
	// The name of the field that is considered as a key. The values identified by the key field is not included in the transformed instances that is sent to the Model. This is similar to specifying this name of the field in excluded_fields. In addition, the batch prediction output will not include the instances. Instead the output will only include the value of the key field, in a field named `key` in the output: * For `jsonl` output format, the output will have a `key` field instead of the `instance` field. * For `csv`/`bigquery` output format, the output will have have a `key` column instead of the instance feature columns. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
	KeyField pulumi.StringPtrInput `pulumi:"keyField"`
}

Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs) ElementType 

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput 

func (i GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput() GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutputWithContext 

func (i GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput 

func (i GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput() GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigInput 

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput() GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput
	ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput
}

GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigInput is an input type that accepts GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs and GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigInput` via: 

GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs{...}

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput 

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput struct{ *pulumi.OutputState }

Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) ElementType 

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) ExcludedFields 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) ExcludedFields() pulumi.StringArrayOutput

Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) IncludedFields 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) IncludedFields() pulumi.StringArrayOutput

Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) InstanceType 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) InstanceType() pulumi.StringPtrOutput

The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf-record-gzip`, each record will be converted to an object in the format of `{"b64": }`, where “is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{"b64": }`, where“ is the Base64-encoded string of the content of the file.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) KeyField 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) KeyField() pulumi.StringPtrOutput

The name of the field that is considered as a key. The values identified by the key field is not included in the transformed instances that is sent to the Model. This is similar to specifying this name of the field in excluded_fields. In addition, the batch prediction output will not include the instances. Instead the output will only include the value of the key field, in a field named `key` in the output: * For `jsonl` output format, the output will have a `key` field instead of the `instance` field. * For `csv`/`bigquery` output format, the output will have have a `key` column instead of the instance feature columns. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput() GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutputWithContext 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput() GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrInput 

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput() GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput
	ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput
}

GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs, GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtr and GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrInput` via: 

        GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtr 

func GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtr(v *GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigArgs) GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrInput

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput 

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) Elem() GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigOutput

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) ExcludedFields 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) ExcludedFields() pulumi.StringArrayOutput

Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) IncludedFields 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) IncludedFields() pulumi.StringArrayOutput

Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) InstanceType 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) InstanceType() pulumi.StringPtrOutput

The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf-record-gzip`, each record will be converted to an object in the format of `{"b64": }`, where “is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{"b64": }`, where“ is the Base64-encoded string of the content of the file.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) KeyField 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) KeyField() pulumi.StringPtrOutput

The name of the field that is considered as a key. The values identified by the key field is not included in the transformed instances that is sent to the Model. This is similar to specifying this name of the field in excluded_fields. In addition, the batch prediction output will not include the instances. Instead the output will only include the value of the key field, in a field named `key` in the output: * For `jsonl` output format, the output will have a `key` field instead of the `instance` field. * For `csv`/`bigquery` output format, the output will have have a `key` column instead of the instance feature columns. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput() GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigPtrOutput

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponse 

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponse struct {
	// Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
	ExcludedFields []string `pulumi:"excludedFields"`
	// Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
	IncludedFields []string `pulumi:"includedFields"`
	// The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf-record-gzip`, each record will be converted to an object in the format of `{"b64": }`, where “is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{"b64": }`, where“ is the Base64-encoded string of the content of the file.
	InstanceType string `pulumi:"instanceType"`
	// The name of the field that is considered as a key. The values identified by the key field is not included in the transformed instances that is sent to the Model. This is similar to specifying this name of the field in excluded_fields. In addition, the batch prediction output will not include the instances. Instead the output will only include the value of the key field, in a field named `key` in the output: * For `jsonl` output format, the output will have a `key` field instead of the `instance` field. * For `csv`/`bigquery` output format, the output will have have a `key` column instead of the instance feature columns. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.
	KeyField string `pulumi:"keyField"`
}

Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput 

type GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput struct{ *pulumi.OutputState }

Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) ExcludedFields 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) ExcludedFields() pulumi.StringArrayOutput

Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) IncludedFields 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) IncludedFields() pulumi.StringArrayOutput

Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) InstanceType 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) InstanceType() pulumi.StringOutput

The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf-record-gzip`, each record will be converted to an object in the format of `{"b64": }`, where “is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{"b64": }`, where“ is the Base64-encoded string of the content of the file.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) KeyField 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) KeyField() pulumi.StringOutput

The name of the field that is considered as a key. The values identified by the key field is not included in the transformed instances that is sent to the Model. This is similar to specifying this name of the field in excluded_fields. In addition, the batch prediction output will not include the instances. Instead the output will only include the value of the key field, in a field named `key` in the output: * For `jsonl` output format, the output will have a `key` field instead of the `instance` field. * For `csv`/`bigquery` output format, the output will have have a `key` column instead of the instance feature columns. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord.

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput() GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput

func (GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput

type GoogleCloudAiplatformV1BatchPredictionJobOutputConfig 

type GoogleCloudAiplatformV1BatchPredictionJobOutputConfig struct {
	// The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name `prediction__` where is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, `predictions`, and `errors`. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The `predictions` table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The `errors` table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only `code` and `message`.
	BigqueryDestination *GoogleCloudAiplatformV1BigQueryDestination `pulumi:"bigqueryDestination"`
	// The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is `prediction--`, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files `predictions_0001.`, `predictions_0002.`, ..., `predictions_N.` are created where “ depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional `errors_0001.`, `errors_0002.`,..., `errors_N.` files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional `error` field which as value has google.rpc.Status containing only `code` and `message` fields.
	GcsDestination *GoogleCloudAiplatformV1GcsDestination `pulumi:"gcsDestination"`
	// The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.
	PredictionsFormat string `pulumi:"predictionsFormat"`
}

Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.

type GoogleCloudAiplatformV1BatchPredictionJobOutputConfigArgs 

type GoogleCloudAiplatformV1BatchPredictionJobOutputConfigArgs struct {
	// The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name `prediction__` where is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, `predictions`, and `errors`. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The `predictions` table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The `errors` table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only `code` and `message`.
	BigqueryDestination GoogleCloudAiplatformV1BigQueryDestinationPtrInput `pulumi:"bigqueryDestination"`
	// The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is `prediction--`, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files `predictions_0001.`, `predictions_0002.`, ..., `predictions_N.` are created where “ depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional `errors_0001.`, `errors_0002.`,..., `errors_N.` files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional `error` field which as value has google.rpc.Status containing only `code` and `message` fields.
	GcsDestination GoogleCloudAiplatformV1GcsDestinationPtrInput `pulumi:"gcsDestination"`
	// The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.
	PredictionsFormat pulumi.StringInput `pulumi:"predictionsFormat"`
}

Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigArgs) ElementType 

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput 

func (i GoogleCloudAiplatformV1BatchPredictionJobOutputConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput() GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutputWithContext 

func (i GoogleCloudAiplatformV1BatchPredictionJobOutputConfigArgs) ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput

type GoogleCloudAiplatformV1BatchPredictionJobOutputConfigInput 

type GoogleCloudAiplatformV1BatchPredictionJobOutputConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput() GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput
	ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput
}

GoogleCloudAiplatformV1BatchPredictionJobOutputConfigInput is an input type that accepts GoogleCloudAiplatformV1BatchPredictionJobOutputConfigArgs and GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1BatchPredictionJobOutputConfigInput` via: 

GoogleCloudAiplatformV1BatchPredictionJobOutputConfigArgs{...}

type GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput 

type GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput struct{ *pulumi.OutputState }

Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput) BigqueryDestination 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput) BigqueryDestination() GoogleCloudAiplatformV1BigQueryDestinationPtrOutput

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name `prediction__` where is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, `predictions`, and `errors`. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The `predictions` table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The `errors` table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only `code` and `message`.

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput) ElementType 

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput) GcsDestination 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput) GcsDestination() GoogleCloudAiplatformV1GcsDestinationPtrOutput

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is `prediction--`, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files `predictions_0001.`, `predictions_0002.`, ..., `predictions_N.` are created where “ depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional `errors_0001.`, `errors_0002.`,..., `errors_N.` files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional `error` field which as value has google.rpc.Status containing only `code` and `message` fields.

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput) PredictionsFormat 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput) PredictionsFormat() pulumi.StringOutput

The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput() GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutputWithContext 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput) ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchPredictionJobOutputConfigOutput

type GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponse 

type GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponse struct {
	// The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name `prediction__` where is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, `predictions`, and `errors`. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The `predictions` table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The `errors` table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only `code` and `message`.
	BigqueryDestination GoogleCloudAiplatformV1BigQueryDestinationResponse `pulumi:"bigqueryDestination"`
	// The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is `prediction--`, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files `predictions_0001.`, `predictions_0002.`, ..., `predictions_N.` are created where “ depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional `errors_0001.`, `errors_0002.`,..., `errors_N.` files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional `error` field which as value has google.rpc.Status containing only `code` and `message` fields.
	GcsDestination GoogleCloudAiplatformV1GcsDestinationResponse `pulumi:"gcsDestination"`
	// The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.
	PredictionsFormat string `pulumi:"predictionsFormat"`
}

Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.

type GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput 

type GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput struct{ *pulumi.OutputState }

Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput) BigqueryDestination 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput) BigqueryDestination() GoogleCloudAiplatformV1BigQueryDestinationResponseOutput

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name `prediction__` where is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, `predictions`, and `errors`. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The `predictions` table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The `errors` table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only `code` and `message`.

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput) GcsDestination 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput) GcsDestination() GoogleCloudAiplatformV1GcsDestinationResponseOutput

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is `prediction--`, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files `predictions_0001.`, `predictions_0002.`, ..., `predictions_N.` are created where “ depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional `errors_0001.`, `errors_0002.`,..., `errors_N.` files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional `error` field which as value has google.rpc.Status containing only `code` and `message` fields.

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput) PredictionsFormat 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput) PredictionsFormat() pulumi.StringOutput

The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput() GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput

func (GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput

type GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponse 

type GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponse struct {
	// The path of the BigQuery dataset created, in `bq://projectId.bqDatasetId` format, into which the prediction output is written.
	BigqueryOutputDataset string `pulumi:"bigqueryOutputDataset"`
	// The name of the BigQuery table created, in `predictions_` format, into which the prediction output is written. Can be used by UI to generate the BigQuery output path, for example.
	BigqueryOutputTable string `pulumi:"bigqueryOutputTable"`
	// The full path of the Cloud Storage directory created, into which the prediction output is written.
	GcsOutputDirectory string `pulumi:"gcsOutputDirectory"`
}

Further describes this job's output. Supplements output_config.

type GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput 

type GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput struct{ *pulumi.OutputState }

Further describes this job's output. Supplements output_config.

func (GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput) BigqueryOutputDataset 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput) BigqueryOutputDataset() pulumi.StringOutput

The path of the BigQuery dataset created, in `bq://projectId.bqDatasetId` format, into which the prediction output is written.

func (GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput) BigqueryOutputTable 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput) BigqueryOutputTable() pulumi.StringOutput

The name of the BigQuery table created, in `predictions_` format, into which the prediction output is written. Can be used by UI to generate the BigQuery output path, for example.

func (GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput) ElementType 

func (GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput) GcsOutputDirectory 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput) GcsOutputDirectory() pulumi.StringOutput

The full path of the Cloud Storage directory created, into which the prediction output is written.

func (GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput() GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput

func (GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutputWithContext 

func (o GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput) ToGoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput

type GoogleCloudAiplatformV1BigQueryDestination 

type GoogleCloudAiplatformV1BigQueryDestination struct {
	// BigQuery URI to a project or table, up to 2000 characters long. When only the project is specified, the Dataset and Table is created. When the full table reference is specified, the Dataset must exist and table must not exist. Accepted forms: * BigQuery path. For example: `bq://projectId` or `bq://projectId.bqDatasetId` or `bq://projectId.bqDatasetId.bqTableId`.
	OutputUri string `pulumi:"outputUri"`
}

The BigQuery location for the output content.

type GoogleCloudAiplatformV1BigQueryDestinationArgs 

type GoogleCloudAiplatformV1BigQueryDestinationArgs struct {
	// BigQuery URI to a project or table, up to 2000 characters long. When only the project is specified, the Dataset and Table is created. When the full table reference is specified, the Dataset must exist and table must not exist. Accepted forms: * BigQuery path. For example: `bq://projectId` or `bq://projectId.bqDatasetId` or `bq://projectId.bqDatasetId.bqTableId`.
	OutputUri pulumi.StringInput `pulumi:"outputUri"`
}

The BigQuery location for the output content.

func (GoogleCloudAiplatformV1BigQueryDestinationArgs) ElementType 

func (GoogleCloudAiplatformV1BigQueryDestinationArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BigQueryDestinationArgs) ToGoogleCloudAiplatformV1BigQueryDestinationOutput 

func (i GoogleCloudAiplatformV1BigQueryDestinationArgs) ToGoogleCloudAiplatformV1BigQueryDestinationOutput() GoogleCloudAiplatformV1BigQueryDestinationOutput

func (GoogleCloudAiplatformV1BigQueryDestinationArgs) ToGoogleCloudAiplatformV1BigQueryDestinationOutputWithContext 

func (i GoogleCloudAiplatformV1BigQueryDestinationArgs) ToGoogleCloudAiplatformV1BigQueryDestinationOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BigQueryDestinationOutput

func (GoogleCloudAiplatformV1BigQueryDestinationArgs) ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutput 

func (i GoogleCloudAiplatformV1BigQueryDestinationArgs) ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutput() GoogleCloudAiplatformV1BigQueryDestinationPtrOutput

func (GoogleCloudAiplatformV1BigQueryDestinationArgs) ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutputWithContext 

func (i GoogleCloudAiplatformV1BigQueryDestinationArgs) ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BigQueryDestinationPtrOutput

type GoogleCloudAiplatformV1BigQueryDestinationInput 

type GoogleCloudAiplatformV1BigQueryDestinationInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1BigQueryDestinationOutput() GoogleCloudAiplatformV1BigQueryDestinationOutput
	ToGoogleCloudAiplatformV1BigQueryDestinationOutputWithContext(context.Context) GoogleCloudAiplatformV1BigQueryDestinationOutput
}

GoogleCloudAiplatformV1BigQueryDestinationInput is an input type that accepts GoogleCloudAiplatformV1BigQueryDestinationArgs and GoogleCloudAiplatformV1BigQueryDestinationOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1BigQueryDestinationInput` via: 

GoogleCloudAiplatformV1BigQueryDestinationArgs{...}

type GoogleCloudAiplatformV1BigQueryDestinationOutput 

type GoogleCloudAiplatformV1BigQueryDestinationOutput struct{ *pulumi.OutputState }

The BigQuery location for the output content.

func (GoogleCloudAiplatformV1BigQueryDestinationOutput) ElementType 

func (GoogleCloudAiplatformV1BigQueryDestinationOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BigQueryDestinationOutput) OutputUri 

func (o GoogleCloudAiplatformV1BigQueryDestinationOutput) OutputUri() pulumi.StringOutput

BigQuery URI to a project or table, up to 2000 characters long. When only the project is specified, the Dataset and Table is created. When the full table reference is specified, the Dataset must exist and table must not exist. Accepted forms: * BigQuery path. For example: `bq://projectId` or `bq://projectId.bqDatasetId` or `bq://projectId.bqDatasetId.bqTableId`.

func (GoogleCloudAiplatformV1BigQueryDestinationOutput) ToGoogleCloudAiplatformV1BigQueryDestinationOutput 

func (o GoogleCloudAiplatformV1BigQueryDestinationOutput) ToGoogleCloudAiplatformV1BigQueryDestinationOutput() GoogleCloudAiplatformV1BigQueryDestinationOutput

func (GoogleCloudAiplatformV1BigQueryDestinationOutput) ToGoogleCloudAiplatformV1BigQueryDestinationOutputWithContext 

func (o GoogleCloudAiplatformV1BigQueryDestinationOutput) ToGoogleCloudAiplatformV1BigQueryDestinationOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BigQueryDestinationOutput

func (GoogleCloudAiplatformV1BigQueryDestinationOutput) ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutput 

func (o GoogleCloudAiplatformV1BigQueryDestinationOutput) ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutput() GoogleCloudAiplatformV1BigQueryDestinationPtrOutput

func (GoogleCloudAiplatformV1BigQueryDestinationOutput) ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutputWithContext 

func (o GoogleCloudAiplatformV1BigQueryDestinationOutput) ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BigQueryDestinationPtrOutput

type GoogleCloudAiplatformV1BigQueryDestinationPtrInput 

type GoogleCloudAiplatformV1BigQueryDestinationPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutput() GoogleCloudAiplatformV1BigQueryDestinationPtrOutput
	ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1BigQueryDestinationPtrOutput
}

GoogleCloudAiplatformV1BigQueryDestinationPtrInput is an input type that accepts GoogleCloudAiplatformV1BigQueryDestinationArgs, GoogleCloudAiplatformV1BigQueryDestinationPtr and GoogleCloudAiplatformV1BigQueryDestinationPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1BigQueryDestinationPtrInput` via: 

        GoogleCloudAiplatformV1BigQueryDestinationArgs{...}

or:

        nil

func GoogleCloudAiplatformV1BigQueryDestinationPtr 

func GoogleCloudAiplatformV1BigQueryDestinationPtr(v *GoogleCloudAiplatformV1BigQueryDestinationArgs) GoogleCloudAiplatformV1BigQueryDestinationPtrInput

type GoogleCloudAiplatformV1BigQueryDestinationPtrOutput 

type GoogleCloudAiplatformV1BigQueryDestinationPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1BigQueryDestinationPtrOutput) Elem 

func (o GoogleCloudAiplatformV1BigQueryDestinationPtrOutput) Elem() GoogleCloudAiplatformV1BigQueryDestinationOutput

func (GoogleCloudAiplatformV1BigQueryDestinationPtrOutput) ElementType 

func (GoogleCloudAiplatformV1BigQueryDestinationPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BigQueryDestinationPtrOutput) OutputUri 

func (o GoogleCloudAiplatformV1BigQueryDestinationPtrOutput) OutputUri() pulumi.StringPtrOutput

BigQuery URI to a project or table, up to 2000 characters long. When only the project is specified, the Dataset and Table is created. When the full table reference is specified, the Dataset must exist and table must not exist. Accepted forms: * BigQuery path. For example: `bq://projectId` or `bq://projectId.bqDatasetId` or `bq://projectId.bqDatasetId.bqTableId`.

func (GoogleCloudAiplatformV1BigQueryDestinationPtrOutput) ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutput 

func (o GoogleCloudAiplatformV1BigQueryDestinationPtrOutput) ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutput() GoogleCloudAiplatformV1BigQueryDestinationPtrOutput

func (GoogleCloudAiplatformV1BigQueryDestinationPtrOutput) ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutputWithContext 

func (o GoogleCloudAiplatformV1BigQueryDestinationPtrOutput) ToGoogleCloudAiplatformV1BigQueryDestinationPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BigQueryDestinationPtrOutput

type GoogleCloudAiplatformV1BigQueryDestinationResponse 

type GoogleCloudAiplatformV1BigQueryDestinationResponse struct {
	// BigQuery URI to a project or table, up to 2000 characters long. When only the project is specified, the Dataset and Table is created. When the full table reference is specified, the Dataset must exist and table must not exist. Accepted forms: * BigQuery path. For example: `bq://projectId` or `bq://projectId.bqDatasetId` or `bq://projectId.bqDatasetId.bqTableId`.
	OutputUri string `pulumi:"outputUri"`
}

The BigQuery location for the output content.

type GoogleCloudAiplatformV1BigQueryDestinationResponseOutput 

type GoogleCloudAiplatformV1BigQueryDestinationResponseOutput struct{ *pulumi.OutputState }

The BigQuery location for the output content.

func (GoogleCloudAiplatformV1BigQueryDestinationResponseOutput) ElementType 

func (GoogleCloudAiplatformV1BigQueryDestinationResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BigQueryDestinationResponseOutput) OutputUri 

func (o GoogleCloudAiplatformV1BigQueryDestinationResponseOutput) OutputUri() pulumi.StringOutput

BigQuery URI to a project or table, up to 2000 characters long. When only the project is specified, the Dataset and Table is created. When the full table reference is specified, the Dataset must exist and table must not exist. Accepted forms: * BigQuery path. For example: `bq://projectId` or `bq://projectId.bqDatasetId` or `bq://projectId.bqDatasetId.bqTableId`.

func (GoogleCloudAiplatformV1BigQueryDestinationResponseOutput) ToGoogleCloudAiplatformV1BigQueryDestinationResponseOutput 

func (o GoogleCloudAiplatformV1BigQueryDestinationResponseOutput) ToGoogleCloudAiplatformV1BigQueryDestinationResponseOutput() GoogleCloudAiplatformV1BigQueryDestinationResponseOutput

func (GoogleCloudAiplatformV1BigQueryDestinationResponseOutput) ToGoogleCloudAiplatformV1BigQueryDestinationResponseOutputWithContext 

func (o GoogleCloudAiplatformV1BigQueryDestinationResponseOutput) ToGoogleCloudAiplatformV1BigQueryDestinationResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BigQueryDestinationResponseOutput

type GoogleCloudAiplatformV1BigQuerySource 

type GoogleCloudAiplatformV1BigQuerySource struct {
	// BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.
	InputUri string `pulumi:"inputUri"`
}

The BigQuery location for the input content.

type GoogleCloudAiplatformV1BigQuerySourceArgs 

type GoogleCloudAiplatformV1BigQuerySourceArgs struct {
	// BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.
	InputUri pulumi.StringInput `pulumi:"inputUri"`
}

The BigQuery location for the input content.

func (GoogleCloudAiplatformV1BigQuerySourceArgs) ElementType 

func (GoogleCloudAiplatformV1BigQuerySourceArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BigQuerySourceArgs) ToGoogleCloudAiplatformV1BigQuerySourceOutput 

func (i GoogleCloudAiplatformV1BigQuerySourceArgs) ToGoogleCloudAiplatformV1BigQuerySourceOutput() GoogleCloudAiplatformV1BigQuerySourceOutput

func (GoogleCloudAiplatformV1BigQuerySourceArgs) ToGoogleCloudAiplatformV1BigQuerySourceOutputWithContext 

func (i GoogleCloudAiplatformV1BigQuerySourceArgs) ToGoogleCloudAiplatformV1BigQuerySourceOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BigQuerySourceOutput

func (GoogleCloudAiplatformV1BigQuerySourceArgs) ToGoogleCloudAiplatformV1BigQuerySourcePtrOutput 

func (i GoogleCloudAiplatformV1BigQuerySourceArgs) ToGoogleCloudAiplatformV1BigQuerySourcePtrOutput() GoogleCloudAiplatformV1BigQuerySourcePtrOutput

func (GoogleCloudAiplatformV1BigQuerySourceArgs) ToGoogleCloudAiplatformV1BigQuerySourcePtrOutputWithContext 

func (i GoogleCloudAiplatformV1BigQuerySourceArgs) ToGoogleCloudAiplatformV1BigQuerySourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BigQuerySourcePtrOutput

type GoogleCloudAiplatformV1BigQuerySourceInput 

type GoogleCloudAiplatformV1BigQuerySourceInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1BigQuerySourceOutput() GoogleCloudAiplatformV1BigQuerySourceOutput
	ToGoogleCloudAiplatformV1BigQuerySourceOutputWithContext(context.Context) GoogleCloudAiplatformV1BigQuerySourceOutput
}

GoogleCloudAiplatformV1BigQuerySourceInput is an input type that accepts GoogleCloudAiplatformV1BigQuerySourceArgs and GoogleCloudAiplatformV1BigQuerySourceOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1BigQuerySourceInput` via: 

GoogleCloudAiplatformV1BigQuerySourceArgs{...}

type GoogleCloudAiplatformV1BigQuerySourceOutput 

type GoogleCloudAiplatformV1BigQuerySourceOutput struct{ *pulumi.OutputState }

The BigQuery location for the input content.

func (GoogleCloudAiplatformV1BigQuerySourceOutput) ElementType 

func (GoogleCloudAiplatformV1BigQuerySourceOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BigQuerySourceOutput) InputUri 

func (o GoogleCloudAiplatformV1BigQuerySourceOutput) InputUri() pulumi.StringOutput

BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.

func (GoogleCloudAiplatformV1BigQuerySourceOutput) ToGoogleCloudAiplatformV1BigQuerySourceOutput 

func (o GoogleCloudAiplatformV1BigQuerySourceOutput) ToGoogleCloudAiplatformV1BigQuerySourceOutput() GoogleCloudAiplatformV1BigQuerySourceOutput

func (GoogleCloudAiplatformV1BigQuerySourceOutput) ToGoogleCloudAiplatformV1BigQuerySourceOutputWithContext 

func (o GoogleCloudAiplatformV1BigQuerySourceOutput) ToGoogleCloudAiplatformV1BigQuerySourceOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BigQuerySourceOutput

func (GoogleCloudAiplatformV1BigQuerySourceOutput) ToGoogleCloudAiplatformV1BigQuerySourcePtrOutput 

func (o GoogleCloudAiplatformV1BigQuerySourceOutput) ToGoogleCloudAiplatformV1BigQuerySourcePtrOutput() GoogleCloudAiplatformV1BigQuerySourcePtrOutput

func (GoogleCloudAiplatformV1BigQuerySourceOutput) ToGoogleCloudAiplatformV1BigQuerySourcePtrOutputWithContext 

func (o GoogleCloudAiplatformV1BigQuerySourceOutput) ToGoogleCloudAiplatformV1BigQuerySourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BigQuerySourcePtrOutput

type GoogleCloudAiplatformV1BigQuerySourcePtrInput 

type GoogleCloudAiplatformV1BigQuerySourcePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1BigQuerySourcePtrOutput() GoogleCloudAiplatformV1BigQuerySourcePtrOutput
	ToGoogleCloudAiplatformV1BigQuerySourcePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1BigQuerySourcePtrOutput
}

GoogleCloudAiplatformV1BigQuerySourcePtrInput is an input type that accepts GoogleCloudAiplatformV1BigQuerySourceArgs, GoogleCloudAiplatformV1BigQuerySourcePtr and GoogleCloudAiplatformV1BigQuerySourcePtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1BigQuerySourcePtrInput` via: 

        GoogleCloudAiplatformV1BigQuerySourceArgs{...}

or:

        nil

func GoogleCloudAiplatformV1BigQuerySourcePtr 

func GoogleCloudAiplatformV1BigQuerySourcePtr(v *GoogleCloudAiplatformV1BigQuerySourceArgs) GoogleCloudAiplatformV1BigQuerySourcePtrInput

type GoogleCloudAiplatformV1BigQuerySourcePtrOutput 

type GoogleCloudAiplatformV1BigQuerySourcePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1BigQuerySourcePtrOutput) Elem 

func (o GoogleCloudAiplatformV1BigQuerySourcePtrOutput) Elem() GoogleCloudAiplatformV1BigQuerySourceOutput

func (GoogleCloudAiplatformV1BigQuerySourcePtrOutput) ElementType 

func (GoogleCloudAiplatformV1BigQuerySourcePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BigQuerySourcePtrOutput) InputUri 

func (o GoogleCloudAiplatformV1BigQuerySourcePtrOutput) InputUri() pulumi.StringPtrOutput

BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.

func (GoogleCloudAiplatformV1BigQuerySourcePtrOutput) ToGoogleCloudAiplatformV1BigQuerySourcePtrOutput 

func (o GoogleCloudAiplatformV1BigQuerySourcePtrOutput) ToGoogleCloudAiplatformV1BigQuerySourcePtrOutput() GoogleCloudAiplatformV1BigQuerySourcePtrOutput

func (GoogleCloudAiplatformV1BigQuerySourcePtrOutput) ToGoogleCloudAiplatformV1BigQuerySourcePtrOutputWithContext 

func (o GoogleCloudAiplatformV1BigQuerySourcePtrOutput) ToGoogleCloudAiplatformV1BigQuerySourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BigQuerySourcePtrOutput

type GoogleCloudAiplatformV1BigQuerySourceResponse 

type GoogleCloudAiplatformV1BigQuerySourceResponse struct {
	// BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.
	InputUri string `pulumi:"inputUri"`
}

The BigQuery location for the input content.

type GoogleCloudAiplatformV1BigQuerySourceResponseOutput 

type GoogleCloudAiplatformV1BigQuerySourceResponseOutput struct{ *pulumi.OutputState }

The BigQuery location for the input content.

func (GoogleCloudAiplatformV1BigQuerySourceResponseOutput) ElementType 

func (GoogleCloudAiplatformV1BigQuerySourceResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BigQuerySourceResponseOutput) InputUri 

func (o GoogleCloudAiplatformV1BigQuerySourceResponseOutput) InputUri() pulumi.StringOutput

BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.

func (GoogleCloudAiplatformV1BigQuerySourceResponseOutput) ToGoogleCloudAiplatformV1BigQuerySourceResponseOutput 

func (o GoogleCloudAiplatformV1BigQuerySourceResponseOutput) ToGoogleCloudAiplatformV1BigQuerySourceResponseOutput() GoogleCloudAiplatformV1BigQuerySourceResponseOutput

func (GoogleCloudAiplatformV1BigQuerySourceResponseOutput) ToGoogleCloudAiplatformV1BigQuerySourceResponseOutputWithContext 

func (o GoogleCloudAiplatformV1BigQuerySourceResponseOutput) ToGoogleCloudAiplatformV1BigQuerySourceResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BigQuerySourceResponseOutput

type GoogleCloudAiplatformV1BlurBaselineConfig 

type GoogleCloudAiplatformV1BlurBaselineConfig struct {
	// The standard deviation of the blur kernel for the blurred baseline. The same blurring parameter is used for both the height and the width dimension. If not set, the method defaults to the zero (i.e. black for images) baseline.
	MaxBlurSigma *float64 `pulumi:"maxBlurSigma"`
}

Config for blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383

type GoogleCloudAiplatformV1BlurBaselineConfigArgs 

type GoogleCloudAiplatformV1BlurBaselineConfigArgs struct {
	// The standard deviation of the blur kernel for the blurred baseline. The same blurring parameter is used for both the height and the width dimension. If not set, the method defaults to the zero (i.e. black for images) baseline.
	MaxBlurSigma pulumi.Float64PtrInput `pulumi:"maxBlurSigma"`
}

Config for blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383

func (GoogleCloudAiplatformV1BlurBaselineConfigArgs) ElementType 

func (GoogleCloudAiplatformV1BlurBaselineConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BlurBaselineConfigArgs) ToGoogleCloudAiplatformV1BlurBaselineConfigOutput 

func (i GoogleCloudAiplatformV1BlurBaselineConfigArgs) ToGoogleCloudAiplatformV1BlurBaselineConfigOutput() GoogleCloudAiplatformV1BlurBaselineConfigOutput

func (GoogleCloudAiplatformV1BlurBaselineConfigArgs) ToGoogleCloudAiplatformV1BlurBaselineConfigOutputWithContext 

func (i GoogleCloudAiplatformV1BlurBaselineConfigArgs) ToGoogleCloudAiplatformV1BlurBaselineConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BlurBaselineConfigOutput

func (GoogleCloudAiplatformV1BlurBaselineConfigArgs) ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutput 

func (i GoogleCloudAiplatformV1BlurBaselineConfigArgs) ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutput() GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput

func (GoogleCloudAiplatformV1BlurBaselineConfigArgs) ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1BlurBaselineConfigArgs) ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput

type GoogleCloudAiplatformV1BlurBaselineConfigInput 

type GoogleCloudAiplatformV1BlurBaselineConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1BlurBaselineConfigOutput() GoogleCloudAiplatformV1BlurBaselineConfigOutput
	ToGoogleCloudAiplatformV1BlurBaselineConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1BlurBaselineConfigOutput
}

GoogleCloudAiplatformV1BlurBaselineConfigInput is an input type that accepts GoogleCloudAiplatformV1BlurBaselineConfigArgs and GoogleCloudAiplatformV1BlurBaselineConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1BlurBaselineConfigInput` via: 

GoogleCloudAiplatformV1BlurBaselineConfigArgs{...}

type GoogleCloudAiplatformV1BlurBaselineConfigOutput 

type GoogleCloudAiplatformV1BlurBaselineConfigOutput struct{ *pulumi.OutputState }

Config for blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383

func (GoogleCloudAiplatformV1BlurBaselineConfigOutput) ElementType 

func (GoogleCloudAiplatformV1BlurBaselineConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BlurBaselineConfigOutput) MaxBlurSigma 

func (o GoogleCloudAiplatformV1BlurBaselineConfigOutput) MaxBlurSigma() pulumi.Float64PtrOutput

The standard deviation of the blur kernel for the blurred baseline. The same blurring parameter is used for both the height and the width dimension. If not set, the method defaults to the zero (i.e. black for images) baseline.

func (GoogleCloudAiplatformV1BlurBaselineConfigOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigOutput 

func (o GoogleCloudAiplatformV1BlurBaselineConfigOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigOutput() GoogleCloudAiplatformV1BlurBaselineConfigOutput

func (GoogleCloudAiplatformV1BlurBaselineConfigOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigOutputWithContext 

func (o GoogleCloudAiplatformV1BlurBaselineConfigOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BlurBaselineConfigOutput

func (GoogleCloudAiplatformV1BlurBaselineConfigOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutput 

func (o GoogleCloudAiplatformV1BlurBaselineConfigOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutput() GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput

func (GoogleCloudAiplatformV1BlurBaselineConfigOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1BlurBaselineConfigOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput

type GoogleCloudAiplatformV1BlurBaselineConfigPtrInput 

type GoogleCloudAiplatformV1BlurBaselineConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutput() GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput
	ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput
}

GoogleCloudAiplatformV1BlurBaselineConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1BlurBaselineConfigArgs, GoogleCloudAiplatformV1BlurBaselineConfigPtr and GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1BlurBaselineConfigPtrInput` via: 

        GoogleCloudAiplatformV1BlurBaselineConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1BlurBaselineConfigPtr 

func GoogleCloudAiplatformV1BlurBaselineConfigPtr(v *GoogleCloudAiplatformV1BlurBaselineConfigArgs) GoogleCloudAiplatformV1BlurBaselineConfigPtrInput

type GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput 

type GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput) Elem() GoogleCloudAiplatformV1BlurBaselineConfigOutput

func (GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput) MaxBlurSigma 

func (o GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput) MaxBlurSigma() pulumi.Float64PtrOutput

The standard deviation of the blur kernel for the blurred baseline. The same blurring parameter is used for both the height and the width dimension. If not set, the method defaults to the zero (i.e. black for images) baseline.

func (GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutput 

func (o GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutput() GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput

func (GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput

type GoogleCloudAiplatformV1BlurBaselineConfigResponse 

type GoogleCloudAiplatformV1BlurBaselineConfigResponse struct {
	// The standard deviation of the blur kernel for the blurred baseline. The same blurring parameter is used for both the height and the width dimension. If not set, the method defaults to the zero (i.e. black for images) baseline.
	MaxBlurSigma float64 `pulumi:"maxBlurSigma"`
}

Config for blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383

type GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput 

type GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput struct{ *pulumi.OutputState }

Config for blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383

func (GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput) MaxBlurSigma 

func (o GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput) MaxBlurSigma() pulumi.Float64Output

The standard deviation of the blur kernel for the blurred baseline. The same blurring parameter is used for both the height and the width dimension. If not set, the method defaults to the zero (i.e. black for images) baseline.

func (GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigResponseOutput 

func (o GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigResponseOutput() GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput

func (GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput) ToGoogleCloudAiplatformV1BlurBaselineConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput

type GoogleCloudAiplatformV1CompletionStatsResponse 

type GoogleCloudAiplatformV1CompletionStatsResponse struct {
	// The number of entities for which any error was encountered.
	FailedCount string `pulumi:"failedCount"`
	// In cases when enough errors are encountered a job, pipeline, or operation may be failed as a whole. Below is the number of entities for which the processing had not been finished (either in successful or failed state). Set to -1 if the number is unknown (for example, the operation failed before the total entity number could be collected).
	IncompleteCount string `pulumi:"incompleteCount"`
	// The number of entities that had been processed successfully.
	SuccessfulCount string `pulumi:"successfulCount"`
	// The number of the successful forecast points that are generated by the forecasting model. This is ONLY used by the forecasting batch prediction.
	SuccessfulForecastPointCount string `pulumi:"successfulForecastPointCount"`
}

Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.

type GoogleCloudAiplatformV1CompletionStatsResponseOutput 

type GoogleCloudAiplatformV1CompletionStatsResponseOutput struct{ *pulumi.OutputState }

Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.

func (GoogleCloudAiplatformV1CompletionStatsResponseOutput) ElementType 

func (GoogleCloudAiplatformV1CompletionStatsResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1CompletionStatsResponseOutput) FailedCount 

func (o GoogleCloudAiplatformV1CompletionStatsResponseOutput) FailedCount() pulumi.StringOutput

The number of entities for which any error was encountered.

func (GoogleCloudAiplatformV1CompletionStatsResponseOutput) IncompleteCount 

func (o GoogleCloudAiplatformV1CompletionStatsResponseOutput) IncompleteCount() pulumi.StringOutput

In cases when enough errors are encountered a job, pipeline, or operation may be failed as a whole. Below is the number of entities for which the processing had not been finished (either in successful or failed state). Set to -1 if the number is unknown (for example, the operation failed before the total entity number could be collected).

func (GoogleCloudAiplatformV1CompletionStatsResponseOutput) SuccessfulCount 

func (o GoogleCloudAiplatformV1CompletionStatsResponseOutput) SuccessfulCount() pulumi.StringOutput

The number of entities that had been processed successfully.

func (GoogleCloudAiplatformV1CompletionStatsResponseOutput) SuccessfulForecastPointCount 

func (o GoogleCloudAiplatformV1CompletionStatsResponseOutput) SuccessfulForecastPointCount() pulumi.StringOutput

The number of the successful forecast points that are generated by the forecasting model. This is ONLY used by the forecasting batch prediction.

func (GoogleCloudAiplatformV1CompletionStatsResponseOutput) ToGoogleCloudAiplatformV1CompletionStatsResponseOutput 

func (o GoogleCloudAiplatformV1CompletionStatsResponseOutput) ToGoogleCloudAiplatformV1CompletionStatsResponseOutput() GoogleCloudAiplatformV1CompletionStatsResponseOutput

func (GoogleCloudAiplatformV1CompletionStatsResponseOutput) ToGoogleCloudAiplatformV1CompletionStatsResponseOutputWithContext 

func (o GoogleCloudAiplatformV1CompletionStatsResponseOutput) ToGoogleCloudAiplatformV1CompletionStatsResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1CompletionStatsResponseOutput

type GoogleCloudAiplatformV1ContainerSpec 

type GoogleCloudAiplatformV1ContainerSpec struct {
	// The arguments to be passed when starting the container.
	Args []string `pulumi:"args"`
	// The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
	Command []string `pulumi:"command"`
	// Environment variables to be passed to the container. Maximum limit is 100.
	Env []GoogleCloudAiplatformV1EnvVar `pulumi:"env"`
	// The URI of a container image in the Container Registry that is to be run on each worker replica.
	ImageUri string `pulumi:"imageUri"`
}

The spec of a Container.

type GoogleCloudAiplatformV1ContainerSpecArgs 

type GoogleCloudAiplatformV1ContainerSpecArgs struct {
	// The arguments to be passed when starting the container.
	Args pulumi.StringArrayInput `pulumi:"args"`
	// The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
	Command pulumi.StringArrayInput `pulumi:"command"`
	// Environment variables to be passed to the container. Maximum limit is 100.
	Env GoogleCloudAiplatformV1EnvVarArrayInput `pulumi:"env"`
	// The URI of a container image in the Container Registry that is to be run on each worker replica.
	ImageUri pulumi.StringInput `pulumi:"imageUri"`
}

The spec of a Container.

func (GoogleCloudAiplatformV1ContainerSpecArgs) ElementType 

func (GoogleCloudAiplatformV1ContainerSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ContainerSpecArgs) ToGoogleCloudAiplatformV1ContainerSpecOutput 

func (i GoogleCloudAiplatformV1ContainerSpecArgs) ToGoogleCloudAiplatformV1ContainerSpecOutput() GoogleCloudAiplatformV1ContainerSpecOutput

func (GoogleCloudAiplatformV1ContainerSpecArgs) ToGoogleCloudAiplatformV1ContainerSpecOutputWithContext 

func (i GoogleCloudAiplatformV1ContainerSpecArgs) ToGoogleCloudAiplatformV1ContainerSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ContainerSpecOutput

func (GoogleCloudAiplatformV1ContainerSpecArgs) ToGoogleCloudAiplatformV1ContainerSpecPtrOutput 

func (i GoogleCloudAiplatformV1ContainerSpecArgs) ToGoogleCloudAiplatformV1ContainerSpecPtrOutput() GoogleCloudAiplatformV1ContainerSpecPtrOutput

func (GoogleCloudAiplatformV1ContainerSpecArgs) ToGoogleCloudAiplatformV1ContainerSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ContainerSpecArgs) ToGoogleCloudAiplatformV1ContainerSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ContainerSpecPtrOutput

type GoogleCloudAiplatformV1ContainerSpecInput 

type GoogleCloudAiplatformV1ContainerSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ContainerSpecOutput() GoogleCloudAiplatformV1ContainerSpecOutput
	ToGoogleCloudAiplatformV1ContainerSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1ContainerSpecOutput
}

GoogleCloudAiplatformV1ContainerSpecInput is an input type that accepts GoogleCloudAiplatformV1ContainerSpecArgs and GoogleCloudAiplatformV1ContainerSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ContainerSpecInput` via: 

GoogleCloudAiplatformV1ContainerSpecArgs{...}

type GoogleCloudAiplatformV1ContainerSpecOutput 

type GoogleCloudAiplatformV1ContainerSpecOutput struct{ *pulumi.OutputState }

The spec of a Container.

func (GoogleCloudAiplatformV1ContainerSpecOutput) Args 

func (o GoogleCloudAiplatformV1ContainerSpecOutput) Args() pulumi.StringArrayOutput

The arguments to be passed when starting the container.

func (GoogleCloudAiplatformV1ContainerSpecOutput) Command 

func (o GoogleCloudAiplatformV1ContainerSpecOutput) Command() pulumi.StringArrayOutput

The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.

func (GoogleCloudAiplatformV1ContainerSpecOutput) ElementType 

func (GoogleCloudAiplatformV1ContainerSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ContainerSpecOutput) Env 

func (o GoogleCloudAiplatformV1ContainerSpecOutput) Env() GoogleCloudAiplatformV1EnvVarArrayOutput

Environment variables to be passed to the container. Maximum limit is 100.

func (GoogleCloudAiplatformV1ContainerSpecOutput) ImageUri 

func (o GoogleCloudAiplatformV1ContainerSpecOutput) ImageUri() pulumi.StringOutput

The URI of a container image in the Container Registry that is to be run on each worker replica.

func (GoogleCloudAiplatformV1ContainerSpecOutput) ToGoogleCloudAiplatformV1ContainerSpecOutput 

func (o GoogleCloudAiplatformV1ContainerSpecOutput) ToGoogleCloudAiplatformV1ContainerSpecOutput() GoogleCloudAiplatformV1ContainerSpecOutput

func (GoogleCloudAiplatformV1ContainerSpecOutput) ToGoogleCloudAiplatformV1ContainerSpecOutputWithContext 

func (o GoogleCloudAiplatformV1ContainerSpecOutput) ToGoogleCloudAiplatformV1ContainerSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ContainerSpecOutput

func (GoogleCloudAiplatformV1ContainerSpecOutput) ToGoogleCloudAiplatformV1ContainerSpecPtrOutput 

func (o GoogleCloudAiplatformV1ContainerSpecOutput) ToGoogleCloudAiplatformV1ContainerSpecPtrOutput() GoogleCloudAiplatformV1ContainerSpecPtrOutput

func (GoogleCloudAiplatformV1ContainerSpecOutput) ToGoogleCloudAiplatformV1ContainerSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ContainerSpecOutput) ToGoogleCloudAiplatformV1ContainerSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ContainerSpecPtrOutput

type GoogleCloudAiplatformV1ContainerSpecPtrInput 

type GoogleCloudAiplatformV1ContainerSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ContainerSpecPtrOutput() GoogleCloudAiplatformV1ContainerSpecPtrOutput
	ToGoogleCloudAiplatformV1ContainerSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ContainerSpecPtrOutput
}

GoogleCloudAiplatformV1ContainerSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1ContainerSpecArgs, GoogleCloudAiplatformV1ContainerSpecPtr and GoogleCloudAiplatformV1ContainerSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ContainerSpecPtrInput` via: 

        GoogleCloudAiplatformV1ContainerSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ContainerSpecPtr 

func GoogleCloudAiplatformV1ContainerSpecPtr(v *GoogleCloudAiplatformV1ContainerSpecArgs) GoogleCloudAiplatformV1ContainerSpecPtrInput

type GoogleCloudAiplatformV1ContainerSpecPtrOutput 

type GoogleCloudAiplatformV1ContainerSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ContainerSpecPtrOutput) Args 

func (o GoogleCloudAiplatformV1ContainerSpecPtrOutput) Args() pulumi.StringArrayOutput

The arguments to be passed when starting the container.

func (GoogleCloudAiplatformV1ContainerSpecPtrOutput) Command 

func (o GoogleCloudAiplatformV1ContainerSpecPtrOutput) Command() pulumi.StringArrayOutput

The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.

func (GoogleCloudAiplatformV1ContainerSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ContainerSpecPtrOutput) Elem() GoogleCloudAiplatformV1ContainerSpecOutput

func (GoogleCloudAiplatformV1ContainerSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ContainerSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ContainerSpecPtrOutput) Env 

func (o GoogleCloudAiplatformV1ContainerSpecPtrOutput) Env() GoogleCloudAiplatformV1EnvVarArrayOutput

Environment variables to be passed to the container. Maximum limit is 100.

func (GoogleCloudAiplatformV1ContainerSpecPtrOutput) ImageUri 

func (o GoogleCloudAiplatformV1ContainerSpecPtrOutput) ImageUri() pulumi.StringPtrOutput

The URI of a container image in the Container Registry that is to be run on each worker replica.

func (GoogleCloudAiplatformV1ContainerSpecPtrOutput) ToGoogleCloudAiplatformV1ContainerSpecPtrOutput 

func (o GoogleCloudAiplatformV1ContainerSpecPtrOutput) ToGoogleCloudAiplatformV1ContainerSpecPtrOutput() GoogleCloudAiplatformV1ContainerSpecPtrOutput

func (GoogleCloudAiplatformV1ContainerSpecPtrOutput) ToGoogleCloudAiplatformV1ContainerSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ContainerSpecPtrOutput) ToGoogleCloudAiplatformV1ContainerSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ContainerSpecPtrOutput

type GoogleCloudAiplatformV1ContainerSpecResponse 

type GoogleCloudAiplatformV1ContainerSpecResponse struct {
	// The arguments to be passed when starting the container.
	Args []string `pulumi:"args"`
	// The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.
	Command []string `pulumi:"command"`
	// Environment variables to be passed to the container. Maximum limit is 100.
	Env []GoogleCloudAiplatformV1EnvVarResponse `pulumi:"env"`
	// The URI of a container image in the Container Registry that is to be run on each worker replica.
	ImageUri string `pulumi:"imageUri"`
}

The spec of a Container.

type GoogleCloudAiplatformV1ContainerSpecResponseOutput 

type GoogleCloudAiplatformV1ContainerSpecResponseOutput struct{ *pulumi.OutputState }

The spec of a Container.

func (GoogleCloudAiplatformV1ContainerSpecResponseOutput) Args 

func (o GoogleCloudAiplatformV1ContainerSpecResponseOutput) Args() pulumi.StringArrayOutput

The arguments to be passed when starting the container.

func (GoogleCloudAiplatformV1ContainerSpecResponseOutput) Command 

func (o GoogleCloudAiplatformV1ContainerSpecResponseOutput) Command() pulumi.StringArrayOutput

The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.

func (GoogleCloudAiplatformV1ContainerSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ContainerSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ContainerSpecResponseOutput) Env 

func (o GoogleCloudAiplatformV1ContainerSpecResponseOutput) Env() GoogleCloudAiplatformV1EnvVarResponseArrayOutput

Environment variables to be passed to the container. Maximum limit is 100.

func (GoogleCloudAiplatformV1ContainerSpecResponseOutput) ImageUri 

func (o GoogleCloudAiplatformV1ContainerSpecResponseOutput) ImageUri() pulumi.StringOutput

The URI of a container image in the Container Registry that is to be run on each worker replica.

func (GoogleCloudAiplatformV1ContainerSpecResponseOutput) ToGoogleCloudAiplatformV1ContainerSpecResponseOutput 

func (o GoogleCloudAiplatformV1ContainerSpecResponseOutput) ToGoogleCloudAiplatformV1ContainerSpecResponseOutput() GoogleCloudAiplatformV1ContainerSpecResponseOutput

func (GoogleCloudAiplatformV1ContainerSpecResponseOutput) ToGoogleCloudAiplatformV1ContainerSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ContainerSpecResponseOutput) ToGoogleCloudAiplatformV1ContainerSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ContainerSpecResponseOutput

type GoogleCloudAiplatformV1ContextResponse 

type GoogleCloudAiplatformV1ContextResponse struct {
	// Timestamp when this Context was created.
	CreateTime string `pulumi:"createTime"`
	// Description of the Context
	Description string `pulumi:"description"`
	// User provided display name of the Context. May be up to 128 Unicode characters.
	DisplayName string `pulumi:"displayName"`
	// An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
	Labels map[string]string `pulumi:"labels"`
	// Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
	Metadata map[string]string `pulumi:"metadata"`
	// Immutable. The resource name of the Context.
	Name string `pulumi:"name"`
	// A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
	ParentContexts []string `pulumi:"parentContexts"`
	// The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaTitle string `pulumi:"schemaTitle"`
	// The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaVersion string `pulumi:"schemaVersion"`
	// Timestamp when this Context was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

Instance of a general context.

type GoogleCloudAiplatformV1ContextResponseOutput 

type GoogleCloudAiplatformV1ContextResponseOutput struct{ *pulumi.OutputState }

Instance of a general context.

func (GoogleCloudAiplatformV1ContextResponseOutput) CreateTime 

func (o GoogleCloudAiplatformV1ContextResponseOutput) CreateTime() pulumi.StringOutput

Timestamp when this Context was created.

func (GoogleCloudAiplatformV1ContextResponseOutput) Description 

func (o GoogleCloudAiplatformV1ContextResponseOutput) Description() pulumi.StringOutput

Description of the Context

func (GoogleCloudAiplatformV1ContextResponseOutput) DisplayName 

func (o GoogleCloudAiplatformV1ContextResponseOutput) DisplayName() pulumi.StringOutput

User provided display name of the Context. May be up to 128 Unicode characters.

func (GoogleCloudAiplatformV1ContextResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ContextResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ContextResponseOutput) Etag 

func (o GoogleCloudAiplatformV1ContextResponseOutput) Etag() pulumi.StringOutput

An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (GoogleCloudAiplatformV1ContextResponseOutput) Labels 

func (o GoogleCloudAiplatformV1ContextResponseOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).

func (GoogleCloudAiplatformV1ContextResponseOutput) Metadata 

func (o GoogleCloudAiplatformV1ContextResponseOutput) Metadata() pulumi.StringMapOutput

Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.

func (GoogleCloudAiplatformV1ContextResponseOutput) Name 

func (o GoogleCloudAiplatformV1ContextResponseOutput) Name() pulumi.StringOutput

Immutable. The resource name of the Context.

func (GoogleCloudAiplatformV1ContextResponseOutput) ParentContexts 

func (o GoogleCloudAiplatformV1ContextResponseOutput) ParentContexts() pulumi.StringArrayOutput

A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.

func (GoogleCloudAiplatformV1ContextResponseOutput) SchemaTitle 

func (o GoogleCloudAiplatformV1ContextResponseOutput) SchemaTitle() pulumi.StringOutput

The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (GoogleCloudAiplatformV1ContextResponseOutput) SchemaVersion 

func (o GoogleCloudAiplatformV1ContextResponseOutput) SchemaVersion() pulumi.StringOutput

The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (GoogleCloudAiplatformV1ContextResponseOutput) ToGoogleCloudAiplatformV1ContextResponseOutput 

func (o GoogleCloudAiplatformV1ContextResponseOutput) ToGoogleCloudAiplatformV1ContextResponseOutput() GoogleCloudAiplatformV1ContextResponseOutput

func (GoogleCloudAiplatformV1ContextResponseOutput) ToGoogleCloudAiplatformV1ContextResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ContextResponseOutput) ToGoogleCloudAiplatformV1ContextResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ContextResponseOutput

func (GoogleCloudAiplatformV1ContextResponseOutput) UpdateTime 

func (o GoogleCloudAiplatformV1ContextResponseOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Context was last updated.

type GoogleCloudAiplatformV1CreatePipelineJobRequest 

type GoogleCloudAiplatformV1CreatePipelineJobRequest struct {
	// The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`
	Parent string `pulumi:"parent"`
	// The PipelineJob to create.
	PipelineJob GoogleCloudAiplatformV1PipelineJob `pulumi:"pipelineJob"`
	// The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.
	PipelineJobId *string `pulumi:"pipelineJobId"`
}

Request message for PipelineService.CreatePipelineJob.

type GoogleCloudAiplatformV1CreatePipelineJobRequestArgs 

type GoogleCloudAiplatformV1CreatePipelineJobRequestArgs struct {
	// The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`
	Parent pulumi.StringInput `pulumi:"parent"`
	// The PipelineJob to create.
	PipelineJob GoogleCloudAiplatformV1PipelineJobInput `pulumi:"pipelineJob"`
	// The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.
	PipelineJobId pulumi.StringPtrInput `pulumi:"pipelineJobId"`
}

Request message for PipelineService.CreatePipelineJob.

func (GoogleCloudAiplatformV1CreatePipelineJobRequestArgs) ElementType 

func (GoogleCloudAiplatformV1CreatePipelineJobRequestArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1CreatePipelineJobRequestArgs) ToGoogleCloudAiplatformV1CreatePipelineJobRequestOutput 

func (i GoogleCloudAiplatformV1CreatePipelineJobRequestArgs) ToGoogleCloudAiplatformV1CreatePipelineJobRequestOutput() GoogleCloudAiplatformV1CreatePipelineJobRequestOutput

func (GoogleCloudAiplatformV1CreatePipelineJobRequestArgs) ToGoogleCloudAiplatformV1CreatePipelineJobRequestOutputWithContext 

func (i GoogleCloudAiplatformV1CreatePipelineJobRequestArgs) ToGoogleCloudAiplatformV1CreatePipelineJobRequestOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1CreatePipelineJobRequestOutput

func (GoogleCloudAiplatformV1CreatePipelineJobRequestArgs) ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput 

func (i GoogleCloudAiplatformV1CreatePipelineJobRequestArgs) ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput() GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput

func (GoogleCloudAiplatformV1CreatePipelineJobRequestArgs) ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutputWithContext 

func (i GoogleCloudAiplatformV1CreatePipelineJobRequestArgs) ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput

type GoogleCloudAiplatformV1CreatePipelineJobRequestInput 

type GoogleCloudAiplatformV1CreatePipelineJobRequestInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1CreatePipelineJobRequestOutput() GoogleCloudAiplatformV1CreatePipelineJobRequestOutput
	ToGoogleCloudAiplatformV1CreatePipelineJobRequestOutputWithContext(context.Context) GoogleCloudAiplatformV1CreatePipelineJobRequestOutput
}

GoogleCloudAiplatformV1CreatePipelineJobRequestInput is an input type that accepts GoogleCloudAiplatformV1CreatePipelineJobRequestArgs and GoogleCloudAiplatformV1CreatePipelineJobRequestOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1CreatePipelineJobRequestInput` via: 

GoogleCloudAiplatformV1CreatePipelineJobRequestArgs{...}

type GoogleCloudAiplatformV1CreatePipelineJobRequestOutput 

type GoogleCloudAiplatformV1CreatePipelineJobRequestOutput struct{ *pulumi.OutputState }

Request message for PipelineService.CreatePipelineJob.

func (GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) ElementType 

func (GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) Parent 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) Parent() pulumi.StringOutput

The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`

func (GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) PipelineJob 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) PipelineJob() GoogleCloudAiplatformV1PipelineJobOutput

The PipelineJob to create.

func (GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) PipelineJobId 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) PipelineJobId() pulumi.StringPtrOutput

The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.

func (GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestOutput 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestOutput() GoogleCloudAiplatformV1CreatePipelineJobRequestOutput

func (GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestOutputWithContext 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1CreatePipelineJobRequestOutput

func (GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput() GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput

func (GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutputWithContext 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput

type GoogleCloudAiplatformV1CreatePipelineJobRequestPtrInput 

type GoogleCloudAiplatformV1CreatePipelineJobRequestPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput() GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput
	ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput
}

GoogleCloudAiplatformV1CreatePipelineJobRequestPtrInput is an input type that accepts GoogleCloudAiplatformV1CreatePipelineJobRequestArgs, GoogleCloudAiplatformV1CreatePipelineJobRequestPtr and GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1CreatePipelineJobRequestPtrInput` via: 

        GoogleCloudAiplatformV1CreatePipelineJobRequestArgs{...}

or:

        nil

func GoogleCloudAiplatformV1CreatePipelineJobRequestPtr 

func GoogleCloudAiplatformV1CreatePipelineJobRequestPtr(v *GoogleCloudAiplatformV1CreatePipelineJobRequestArgs) GoogleCloudAiplatformV1CreatePipelineJobRequestPtrInput

type GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput 

type GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) Elem 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) Elem() GoogleCloudAiplatformV1CreatePipelineJobRequestOutput

func (GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) ElementType 

func (GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) Parent 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) Parent() pulumi.StringPtrOutput

The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`

func (GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) PipelineJob 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) PipelineJob() GoogleCloudAiplatformV1PipelineJobPtrOutput

The PipelineJob to create.

func (GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) PipelineJobId 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) PipelineJobId() pulumi.StringPtrOutput

The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.

func (GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput() GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput

func (GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutputWithContext 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1CreatePipelineJobRequestPtrOutput

type GoogleCloudAiplatformV1CreatePipelineJobRequestResponse 

type GoogleCloudAiplatformV1CreatePipelineJobRequestResponse struct {
	// The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`
	Parent string `pulumi:"parent"`
	// The PipelineJob to create.
	PipelineJob GoogleCloudAiplatformV1PipelineJobResponse `pulumi:"pipelineJob"`
	// The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.
	PipelineJobId string `pulumi:"pipelineJobId"`
}

Request message for PipelineService.CreatePipelineJob.

type GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput 

type GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput struct{ *pulumi.OutputState }

Request message for PipelineService.CreatePipelineJob.

func (GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput) ElementType 

func (GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput) Parent 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput) Parent() pulumi.StringOutput

The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`

func (GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput) PipelineJob 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput) PipelineJob() GoogleCloudAiplatformV1PipelineJobResponseOutput

The PipelineJob to create.

func (GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput) PipelineJobId 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput) PipelineJobId() pulumi.StringOutput

The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.

func (GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput() GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput

func (GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutputWithContext 

func (o GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput) ToGoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput

type GoogleCloudAiplatformV1CustomJobSpec 

type GoogleCloudAiplatformV1CustomJobSpec struct {
	// The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = `/model/` * AIP_CHECKPOINT_DIR = `/checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `/logs/` For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = `//model/` * AIP_CHECKPOINT_DIR = `//checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `//logs/`
	BaseOutputDirectory *GoogleCloudAiplatformV1GcsDestination `pulumi:"baseOutputDirectory"`
	// Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to `true`, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
	EnableDashboardAccess *bool `pulumi:"enableDashboardAccess"`
	// Optional. Whether you want Vertex AI to enable [interactive shell access](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
	EnableWebAccess *bool `pulumi:"enableWebAccess"`
	// Optional. The Experiment associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}`
	Experiment *string `pulumi:"experiment"`
	// Optional. The Experiment Run associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}`
	ExperimentRun *string `pulumi:"experimentRun"`
	// Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Job should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering). If this field is left unspecified, the job is not peered with any network.
	Network *string `pulumi:"network"`
	// The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
	ProtectedArtifactLocationId *string `pulumi:"protectedArtifactLocationId"`
	// Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
	ReservedIpRanges []string `pulumi:"reservedIpRanges"`
	// Scheduling options for a CustomJob.
	Scheduling *GoogleCloudAiplatformV1Scheduling `pulumi:"scheduling"`
	// Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) for the CustomJob's project is used.
	ServiceAccount *string `pulumi:"serviceAccount"`
	// Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
	Tensorboard *string `pulumi:"tensorboard"`
	// The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
	WorkerPoolSpecs []GoogleCloudAiplatformV1WorkerPoolSpec `pulumi:"workerPoolSpecs"`
}

Represents the spec of a CustomJob.

type GoogleCloudAiplatformV1CustomJobSpecArgs 

type GoogleCloudAiplatformV1CustomJobSpecArgs struct {
	// The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = `/model/` * AIP_CHECKPOINT_DIR = `/checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `/logs/` For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = `//model/` * AIP_CHECKPOINT_DIR = `//checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `//logs/`
	BaseOutputDirectory GoogleCloudAiplatformV1GcsDestinationPtrInput `pulumi:"baseOutputDirectory"`
	// Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to `true`, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
	EnableDashboardAccess pulumi.BoolPtrInput `pulumi:"enableDashboardAccess"`
	// Optional. Whether you want Vertex AI to enable [interactive shell access](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
	EnableWebAccess pulumi.BoolPtrInput `pulumi:"enableWebAccess"`
	// Optional. The Experiment associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}`
	Experiment pulumi.StringPtrInput `pulumi:"experiment"`
	// Optional. The Experiment Run associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}`
	ExperimentRun pulumi.StringPtrInput `pulumi:"experimentRun"`
	// Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Job should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering). If this field is left unspecified, the job is not peered with any network.
	Network pulumi.StringPtrInput `pulumi:"network"`
	// The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
	ProtectedArtifactLocationId pulumi.StringPtrInput `pulumi:"protectedArtifactLocationId"`
	// Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
	ReservedIpRanges pulumi.StringArrayInput `pulumi:"reservedIpRanges"`
	// Scheduling options for a CustomJob.
	Scheduling GoogleCloudAiplatformV1SchedulingPtrInput `pulumi:"scheduling"`
	// Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) for the CustomJob's project is used.
	ServiceAccount pulumi.StringPtrInput `pulumi:"serviceAccount"`
	// Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
	Tensorboard pulumi.StringPtrInput `pulumi:"tensorboard"`
	// The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
	WorkerPoolSpecs GoogleCloudAiplatformV1WorkerPoolSpecArrayInput `pulumi:"workerPoolSpecs"`
}

Represents the spec of a CustomJob.

func (GoogleCloudAiplatformV1CustomJobSpecArgs) ElementType 

func (GoogleCloudAiplatformV1CustomJobSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1CustomJobSpecArgs) ToGoogleCloudAiplatformV1CustomJobSpecOutput 

func (i GoogleCloudAiplatformV1CustomJobSpecArgs) ToGoogleCloudAiplatformV1CustomJobSpecOutput() GoogleCloudAiplatformV1CustomJobSpecOutput

func (GoogleCloudAiplatformV1CustomJobSpecArgs) ToGoogleCloudAiplatformV1CustomJobSpecOutputWithContext 

func (i GoogleCloudAiplatformV1CustomJobSpecArgs) ToGoogleCloudAiplatformV1CustomJobSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1CustomJobSpecOutput

func (GoogleCloudAiplatformV1CustomJobSpecArgs) ToGoogleCloudAiplatformV1CustomJobSpecPtrOutput 

func (i GoogleCloudAiplatformV1CustomJobSpecArgs) ToGoogleCloudAiplatformV1CustomJobSpecPtrOutput() GoogleCloudAiplatformV1CustomJobSpecPtrOutput

func (GoogleCloudAiplatformV1CustomJobSpecArgs) ToGoogleCloudAiplatformV1CustomJobSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1CustomJobSpecArgs) ToGoogleCloudAiplatformV1CustomJobSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1CustomJobSpecPtrOutput

type GoogleCloudAiplatformV1CustomJobSpecInput 

type GoogleCloudAiplatformV1CustomJobSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1CustomJobSpecOutput() GoogleCloudAiplatformV1CustomJobSpecOutput
	ToGoogleCloudAiplatformV1CustomJobSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1CustomJobSpecOutput
}

GoogleCloudAiplatformV1CustomJobSpecInput is an input type that accepts GoogleCloudAiplatformV1CustomJobSpecArgs and GoogleCloudAiplatformV1CustomJobSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1CustomJobSpecInput` via: 

GoogleCloudAiplatformV1CustomJobSpecArgs{...}

type GoogleCloudAiplatformV1CustomJobSpecOutput 

type GoogleCloudAiplatformV1CustomJobSpecOutput struct{ *pulumi.OutputState }

Represents the spec of a CustomJob.

func (GoogleCloudAiplatformV1CustomJobSpecOutput) BaseOutputDirectory 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) BaseOutputDirectory() GoogleCloudAiplatformV1GcsDestinationPtrOutput

The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = `/model/` * AIP_CHECKPOINT_DIR = `/checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `/logs/` For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = `//model/` * AIP_CHECKPOINT_DIR = `//checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `//logs/`

func (GoogleCloudAiplatformV1CustomJobSpecOutput) ElementType 

func (GoogleCloudAiplatformV1CustomJobSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1CustomJobSpecOutput) EnableDashboardAccess 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) EnableDashboardAccess() pulumi.BoolPtrOutput

Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to `true`, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).

func (GoogleCloudAiplatformV1CustomJobSpecOutput) EnableWebAccess 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) EnableWebAccess() pulumi.BoolPtrOutput

Optional. Whether you want Vertex AI to enable [interactive shell access](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).

func (GoogleCloudAiplatformV1CustomJobSpecOutput) Experiment 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) Experiment() pulumi.StringPtrOutput

Optional. The Experiment associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}`

func (GoogleCloudAiplatformV1CustomJobSpecOutput) ExperimentRun 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) ExperimentRun() pulumi.StringPtrOutput

Optional. The Experiment Run associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}`

func (GoogleCloudAiplatformV1CustomJobSpecOutput) Network 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) Network() pulumi.StringPtrOutput

Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Job should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering). If this field is left unspecified, the job is not peered with any network.

func (GoogleCloudAiplatformV1CustomJobSpecOutput) ProtectedArtifactLocationId 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) ProtectedArtifactLocationId() pulumi.StringPtrOutput

The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations

func (GoogleCloudAiplatformV1CustomJobSpecOutput) ReservedIpRanges 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) ReservedIpRanges() pulumi.StringArrayOutput

Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

func (GoogleCloudAiplatformV1CustomJobSpecOutput) Scheduling 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) Scheduling() GoogleCloudAiplatformV1SchedulingPtrOutput

Scheduling options for a CustomJob.

func (GoogleCloudAiplatformV1CustomJobSpecOutput) ServiceAccount 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) ServiceAccount() pulumi.StringPtrOutput

Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) for the CustomJob's project is used.

func (GoogleCloudAiplatformV1CustomJobSpecOutput) Tensorboard 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) Tensorboard() pulumi.StringPtrOutput

Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`

func (GoogleCloudAiplatformV1CustomJobSpecOutput) ToGoogleCloudAiplatformV1CustomJobSpecOutput 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) ToGoogleCloudAiplatformV1CustomJobSpecOutput() GoogleCloudAiplatformV1CustomJobSpecOutput

func (GoogleCloudAiplatformV1CustomJobSpecOutput) ToGoogleCloudAiplatformV1CustomJobSpecOutputWithContext 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) ToGoogleCloudAiplatformV1CustomJobSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1CustomJobSpecOutput

func (GoogleCloudAiplatformV1CustomJobSpecOutput) ToGoogleCloudAiplatformV1CustomJobSpecPtrOutput 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) ToGoogleCloudAiplatformV1CustomJobSpecPtrOutput() GoogleCloudAiplatformV1CustomJobSpecPtrOutput

func (GoogleCloudAiplatformV1CustomJobSpecOutput) ToGoogleCloudAiplatformV1CustomJobSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) ToGoogleCloudAiplatformV1CustomJobSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1CustomJobSpecPtrOutput

func (GoogleCloudAiplatformV1CustomJobSpecOutput) WorkerPoolSpecs 

func (o GoogleCloudAiplatformV1CustomJobSpecOutput) WorkerPoolSpecs() GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput

The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.

type GoogleCloudAiplatformV1CustomJobSpecPtrInput 

type GoogleCloudAiplatformV1CustomJobSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1CustomJobSpecPtrOutput() GoogleCloudAiplatformV1CustomJobSpecPtrOutput
	ToGoogleCloudAiplatformV1CustomJobSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1CustomJobSpecPtrOutput
}

GoogleCloudAiplatformV1CustomJobSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1CustomJobSpecArgs, GoogleCloudAiplatformV1CustomJobSpecPtr and GoogleCloudAiplatformV1CustomJobSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1CustomJobSpecPtrInput` via: 

        GoogleCloudAiplatformV1CustomJobSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1CustomJobSpecPtr 

func GoogleCloudAiplatformV1CustomJobSpecPtr(v *GoogleCloudAiplatformV1CustomJobSpecArgs) GoogleCloudAiplatformV1CustomJobSpecPtrInput

type GoogleCloudAiplatformV1CustomJobSpecPtrOutput 

type GoogleCloudAiplatformV1CustomJobSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) BaseOutputDirectory 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) BaseOutputDirectory() GoogleCloudAiplatformV1GcsDestinationPtrOutput

The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = `/model/` * AIP_CHECKPOINT_DIR = `/checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `/logs/` For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = `//model/` * AIP_CHECKPOINT_DIR = `//checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `//logs/`

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) Elem() GoogleCloudAiplatformV1CustomJobSpecOutput

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) EnableDashboardAccess 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) EnableDashboardAccess() pulumi.BoolPtrOutput

Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to `true`, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) EnableWebAccess 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) EnableWebAccess() pulumi.BoolPtrOutput

Optional. Whether you want Vertex AI to enable [interactive shell access](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) Experiment 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) Experiment() pulumi.StringPtrOutput

Optional. The Experiment associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}`

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ExperimentRun 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ExperimentRun() pulumi.StringPtrOutput

Optional. The Experiment Run associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}`

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) Network 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) Network() pulumi.StringPtrOutput

Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Job should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering). If this field is left unspecified, the job is not peered with any network.

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ProtectedArtifactLocationId 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ProtectedArtifactLocationId() pulumi.StringPtrOutput

The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ReservedIpRanges 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ReservedIpRanges() pulumi.StringArrayOutput

Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) Scheduling 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) Scheduling() GoogleCloudAiplatformV1SchedulingPtrOutput

Scheduling options for a CustomJob.

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ServiceAccount 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ServiceAccount() pulumi.StringPtrOutput

Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) for the CustomJob's project is used.

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) Tensorboard 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) Tensorboard() pulumi.StringPtrOutput

Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ToGoogleCloudAiplatformV1CustomJobSpecPtrOutput 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ToGoogleCloudAiplatformV1CustomJobSpecPtrOutput() GoogleCloudAiplatformV1CustomJobSpecPtrOutput

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ToGoogleCloudAiplatformV1CustomJobSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) ToGoogleCloudAiplatformV1CustomJobSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1CustomJobSpecPtrOutput

func (GoogleCloudAiplatformV1CustomJobSpecPtrOutput) WorkerPoolSpecs 

func (o GoogleCloudAiplatformV1CustomJobSpecPtrOutput) WorkerPoolSpecs() GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput

The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.

type GoogleCloudAiplatformV1CustomJobSpecResponse 

type GoogleCloudAiplatformV1CustomJobSpecResponse struct {
	// The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = `/model/` * AIP_CHECKPOINT_DIR = `/checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `/logs/` For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = `//model/` * AIP_CHECKPOINT_DIR = `//checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `//logs/`
	BaseOutputDirectory GoogleCloudAiplatformV1GcsDestinationResponse `pulumi:"baseOutputDirectory"`
	// Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to `true`, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
	EnableDashboardAccess bool `pulumi:"enableDashboardAccess"`
	// Optional. Whether you want Vertex AI to enable [interactive shell access](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).
	EnableWebAccess bool `pulumi:"enableWebAccess"`
	// Optional. The Experiment associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}`
	Experiment string `pulumi:"experiment"`
	// Optional. The Experiment Run associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}`
	ExperimentRun string `pulumi:"experimentRun"`
	// Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Job should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering). If this field is left unspecified, the job is not peered with any network.
	Network string `pulumi:"network"`
	// The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations
	ProtectedArtifactLocationId string `pulumi:"protectedArtifactLocationId"`
	// Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
	ReservedIpRanges []string `pulumi:"reservedIpRanges"`
	// Scheduling options for a CustomJob.
	Scheduling GoogleCloudAiplatformV1SchedulingResponse `pulumi:"scheduling"`
	// Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) for the CustomJob's project is used.
	ServiceAccount string `pulumi:"serviceAccount"`
	// Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
	Tensorboard string `pulumi:"tensorboard"`
	// The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.
	WorkerPoolSpecs []GoogleCloudAiplatformV1WorkerPoolSpecResponse `pulumi:"workerPoolSpecs"`
}

Represents the spec of a CustomJob.

type GoogleCloudAiplatformV1CustomJobSpecResponseOutput 

type GoogleCloudAiplatformV1CustomJobSpecResponseOutput struct{ *pulumi.OutputState }

Represents the spec of a CustomJob.

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) BaseOutputDirectory 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) BaseOutputDirectory() GoogleCloudAiplatformV1GcsDestinationResponseOutput

The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = `/model/` * AIP_CHECKPOINT_DIR = `/checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `/logs/` For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = `//model/` * AIP_CHECKPOINT_DIR = `//checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `//logs/`

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) EnableDashboardAccess 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) EnableDashboardAccess() pulumi.BoolOutput

Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to `true`, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) EnableWebAccess 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) EnableWebAccess() pulumi.BoolOutput

Optional. Whether you want Vertex AI to enable [interactive shell access](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials).

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) Experiment 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) Experiment() pulumi.StringOutput

Optional. The Experiment associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}`

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ExperimentRun 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ExperimentRun() pulumi.StringOutput

Optional. The Experiment Run associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadataStores}/contexts/{experiment-name}-{experiment-run-name}`

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) Network 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) Network() pulumi.StringOutput

Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Job should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex-ai/docs/general/vpc-peering). If this field is left unspecified, the job is not peered with any network.

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ProtectedArtifactLocationId 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ProtectedArtifactLocationId() pulumi.StringOutput

The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ReservedIpRanges 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ReservedIpRanges() pulumi.StringArrayOutput

Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) Scheduling 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) Scheduling() GoogleCloudAiplatformV1SchedulingResponseOutput

Scheduling options for a CustomJob.

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ServiceAccount 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ServiceAccount() pulumi.StringOutput

Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) for the CustomJob's project is used.

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) Tensorboard 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) Tensorboard() pulumi.StringOutput

Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ToGoogleCloudAiplatformV1CustomJobSpecResponseOutput 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ToGoogleCloudAiplatformV1CustomJobSpecResponseOutput() GoogleCloudAiplatformV1CustomJobSpecResponseOutput

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ToGoogleCloudAiplatformV1CustomJobSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) ToGoogleCloudAiplatformV1CustomJobSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1CustomJobSpecResponseOutput

func (GoogleCloudAiplatformV1CustomJobSpecResponseOutput) WorkerPoolSpecs 

func (o GoogleCloudAiplatformV1CustomJobSpecResponseOutput) WorkerPoolSpecs() GoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput

The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value.

type GoogleCloudAiplatformV1DedicatedResources 

type GoogleCloudAiplatformV1DedicatedResources struct {
	// Immutable. The metric specifications that overrides a resource utilization metric (CPU utilization, accelerator's duty cycle, and so on) target value (default to 60 if not set). At most one entry is allowed per metric. If machine_spec.accelerator_count is above 0, the autoscaling will be based on both CPU utilization and accelerator's duty cycle metrics and scale up when either metrics exceeds its target value while scale down if both metrics are under their target value. The default target value is 60 for both metrics. If machine_spec.accelerator_count is 0, the autoscaling will be based on CPU utilization metric only with default target value 60 if not explicitly set. For example, in the case of Online Prediction, if you want to override target CPU utilization to 80, you should set autoscaling_metric_specs.metric_name to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and autoscaling_metric_specs.target to `80`.
	AutoscalingMetricSpecs []GoogleCloudAiplatformV1AutoscalingMetricSpec `pulumi:"autoscalingMetricSpecs"`
	// Immutable. The specification of a single machine used by the prediction.
	MachineSpec GoogleCloudAiplatformV1MachineSpec `pulumi:"machineSpec"`
	// Immutable. The maximum number of replicas this DeployedModel may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale the model to that many replicas is guaranteed (barring service outages). If traffic against the DeployedModel increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, will use min_replica_count as the default value. The value of this field impacts the charge against Vertex CPU and GPU quotas. Specifically, you will be charged for (max_replica_count * number of cores in the selected machine type) and (max_replica_count * number of GPUs per replica in the selected machine type).
	MaxReplicaCount *int `pulumi:"maxReplicaCount"`
	// Immutable. The minimum number of machine replicas this DeployedModel will be always deployed on. This value must be greater than or equal to 1. If traffic against the DeployedModel increases, it may dynamically be deployed onto more replicas, and as traffic decreases, some of these extra replicas may be freed.
	MinReplicaCount int `pulumi:"minReplicaCount"`
}

A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.

type GoogleCloudAiplatformV1DedicatedResourcesArgs 

type GoogleCloudAiplatformV1DedicatedResourcesArgs struct {
	// Immutable. The metric specifications that overrides a resource utilization metric (CPU utilization, accelerator's duty cycle, and so on) target value (default to 60 if not set). At most one entry is allowed per metric. If machine_spec.accelerator_count is above 0, the autoscaling will be based on both CPU utilization and accelerator's duty cycle metrics and scale up when either metrics exceeds its target value while scale down if both metrics are under their target value. The default target value is 60 for both metrics. If machine_spec.accelerator_count is 0, the autoscaling will be based on CPU utilization metric only with default target value 60 if not explicitly set. For example, in the case of Online Prediction, if you want to override target CPU utilization to 80, you should set autoscaling_metric_specs.metric_name to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and autoscaling_metric_specs.target to `80`.
	AutoscalingMetricSpecs GoogleCloudAiplatformV1AutoscalingMetricSpecArrayInput `pulumi:"autoscalingMetricSpecs"`
	// Immutable. The specification of a single machine used by the prediction.
	MachineSpec GoogleCloudAiplatformV1MachineSpecInput `pulumi:"machineSpec"`
	// Immutable. The maximum number of replicas this DeployedModel may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale the model to that many replicas is guaranteed (barring service outages). If traffic against the DeployedModel increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, will use min_replica_count as the default value. The value of this field impacts the charge against Vertex CPU and GPU quotas. Specifically, you will be charged for (max_replica_count * number of cores in the selected machine type) and (max_replica_count * number of GPUs per replica in the selected machine type).
	MaxReplicaCount pulumi.IntPtrInput `pulumi:"maxReplicaCount"`
	// Immutable. The minimum number of machine replicas this DeployedModel will be always deployed on. This value must be greater than or equal to 1. If traffic against the DeployedModel increases, it may dynamically be deployed onto more replicas, and as traffic decreases, some of these extra replicas may be freed.
	MinReplicaCount pulumi.IntInput `pulumi:"minReplicaCount"`
}

A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.

func (GoogleCloudAiplatformV1DedicatedResourcesArgs) ElementType 

func (GoogleCloudAiplatformV1DedicatedResourcesArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DedicatedResourcesArgs) ToGoogleCloudAiplatformV1DedicatedResourcesOutput 

func (i GoogleCloudAiplatformV1DedicatedResourcesArgs) ToGoogleCloudAiplatformV1DedicatedResourcesOutput() GoogleCloudAiplatformV1DedicatedResourcesOutput

func (GoogleCloudAiplatformV1DedicatedResourcesArgs) ToGoogleCloudAiplatformV1DedicatedResourcesOutputWithContext 

func (i GoogleCloudAiplatformV1DedicatedResourcesArgs) ToGoogleCloudAiplatformV1DedicatedResourcesOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DedicatedResourcesOutput

type GoogleCloudAiplatformV1DedicatedResourcesInput 

type GoogleCloudAiplatformV1DedicatedResourcesInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1DedicatedResourcesOutput() GoogleCloudAiplatformV1DedicatedResourcesOutput
	ToGoogleCloudAiplatformV1DedicatedResourcesOutputWithContext(context.Context) GoogleCloudAiplatformV1DedicatedResourcesOutput
}

GoogleCloudAiplatformV1DedicatedResourcesInput is an input type that accepts GoogleCloudAiplatformV1DedicatedResourcesArgs and GoogleCloudAiplatformV1DedicatedResourcesOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1DedicatedResourcesInput` via: 

GoogleCloudAiplatformV1DedicatedResourcesArgs{...}

type GoogleCloudAiplatformV1DedicatedResourcesOutput 

type GoogleCloudAiplatformV1DedicatedResourcesOutput struct{ *pulumi.OutputState }

A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.

func (GoogleCloudAiplatformV1DedicatedResourcesOutput) AutoscalingMetricSpecs 

func (o GoogleCloudAiplatformV1DedicatedResourcesOutput) AutoscalingMetricSpecs() GoogleCloudAiplatformV1AutoscalingMetricSpecArrayOutput

Immutable. The metric specifications that overrides a resource utilization metric (CPU utilization, accelerator's duty cycle, and so on) target value (default to 60 if not set). At most one entry is allowed per metric. If machine_spec.accelerator_count is above 0, the autoscaling will be based on both CPU utilization and accelerator's duty cycle metrics and scale up when either metrics exceeds its target value while scale down if both metrics are under their target value. The default target value is 60 for both metrics. If machine_spec.accelerator_count is 0, the autoscaling will be based on CPU utilization metric only with default target value 60 if not explicitly set. For example, in the case of Online Prediction, if you want to override target CPU utilization to 80, you should set autoscaling_metric_specs.metric_name to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and autoscaling_metric_specs.target to `80`.

func (GoogleCloudAiplatformV1DedicatedResourcesOutput) ElementType 

func (GoogleCloudAiplatformV1DedicatedResourcesOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DedicatedResourcesOutput) MachineSpec 

func (o GoogleCloudAiplatformV1DedicatedResourcesOutput) MachineSpec() GoogleCloudAiplatformV1MachineSpecOutput

Immutable. The specification of a single machine used by the prediction.

func (GoogleCloudAiplatformV1DedicatedResourcesOutput) MaxReplicaCount 

func (o GoogleCloudAiplatformV1DedicatedResourcesOutput) MaxReplicaCount() pulumi.IntPtrOutput

Immutable. The maximum number of replicas this DeployedModel may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale the model to that many replicas is guaranteed (barring service outages). If traffic against the DeployedModel increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, will use min_replica_count as the default value. The value of this field impacts the charge against Vertex CPU and GPU quotas. Specifically, you will be charged for (max_replica_count * number of cores in the selected machine type) and (max_replica_count * number of GPUs per replica in the selected machine type).

func (GoogleCloudAiplatformV1DedicatedResourcesOutput) MinReplicaCount 

func (o GoogleCloudAiplatformV1DedicatedResourcesOutput) MinReplicaCount() pulumi.IntOutput

Immutable. The minimum number of machine replicas this DeployedModel will be always deployed on. This value must be greater than or equal to 1. If traffic against the DeployedModel increases, it may dynamically be deployed onto more replicas, and as traffic decreases, some of these extra replicas may be freed.

func (GoogleCloudAiplatformV1DedicatedResourcesOutput) ToGoogleCloudAiplatformV1DedicatedResourcesOutput 

func (o GoogleCloudAiplatformV1DedicatedResourcesOutput) ToGoogleCloudAiplatformV1DedicatedResourcesOutput() GoogleCloudAiplatformV1DedicatedResourcesOutput

func (GoogleCloudAiplatformV1DedicatedResourcesOutput) ToGoogleCloudAiplatformV1DedicatedResourcesOutputWithContext 

func (o GoogleCloudAiplatformV1DedicatedResourcesOutput) ToGoogleCloudAiplatformV1DedicatedResourcesOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DedicatedResourcesOutput

type GoogleCloudAiplatformV1DedicatedResourcesResponse 

type GoogleCloudAiplatformV1DedicatedResourcesResponse struct {
	// Immutable. The metric specifications that overrides a resource utilization metric (CPU utilization, accelerator's duty cycle, and so on) target value (default to 60 if not set). At most one entry is allowed per metric. If machine_spec.accelerator_count is above 0, the autoscaling will be based on both CPU utilization and accelerator's duty cycle metrics and scale up when either metrics exceeds its target value while scale down if both metrics are under their target value. The default target value is 60 for both metrics. If machine_spec.accelerator_count is 0, the autoscaling will be based on CPU utilization metric only with default target value 60 if not explicitly set. For example, in the case of Online Prediction, if you want to override target CPU utilization to 80, you should set autoscaling_metric_specs.metric_name to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and autoscaling_metric_specs.target to `80`.
	AutoscalingMetricSpecs []GoogleCloudAiplatformV1AutoscalingMetricSpecResponse `pulumi:"autoscalingMetricSpecs"`
	// Immutable. The specification of a single machine used by the prediction.
	MachineSpec GoogleCloudAiplatformV1MachineSpecResponse `pulumi:"machineSpec"`
	// Immutable. The maximum number of replicas this DeployedModel may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale the model to that many replicas is guaranteed (barring service outages). If traffic against the DeployedModel increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, will use min_replica_count as the default value. The value of this field impacts the charge against Vertex CPU and GPU quotas. Specifically, you will be charged for (max_replica_count * number of cores in the selected machine type) and (max_replica_count * number of GPUs per replica in the selected machine type).
	MaxReplicaCount int `pulumi:"maxReplicaCount"`
	// Immutable. The minimum number of machine replicas this DeployedModel will be always deployed on. This value must be greater than or equal to 1. If traffic against the DeployedModel increases, it may dynamically be deployed onto more replicas, and as traffic decreases, some of these extra replicas may be freed.
	MinReplicaCount int `pulumi:"minReplicaCount"`
}

A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.

type GoogleCloudAiplatformV1DedicatedResourcesResponseOutput 

type GoogleCloudAiplatformV1DedicatedResourcesResponseOutput struct{ *pulumi.OutputState }

A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.

func (GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) AutoscalingMetricSpecs 

func (o GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) AutoscalingMetricSpecs() GoogleCloudAiplatformV1AutoscalingMetricSpecResponseArrayOutput

Immutable. The metric specifications that overrides a resource utilization metric (CPU utilization, accelerator's duty cycle, and so on) target value (default to 60 if not set). At most one entry is allowed per metric. If machine_spec.accelerator_count is above 0, the autoscaling will be based on both CPU utilization and accelerator's duty cycle metrics and scale up when either metrics exceeds its target value while scale down if both metrics are under their target value. The default target value is 60 for both metrics. If machine_spec.accelerator_count is 0, the autoscaling will be based on CPU utilization metric only with default target value 60 if not explicitly set. For example, in the case of Online Prediction, if you want to override target CPU utilization to 80, you should set autoscaling_metric_specs.metric_name to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and autoscaling_metric_specs.target to `80`.

func (GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) ElementType 

func (GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) MachineSpec 

func (o GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) MachineSpec() GoogleCloudAiplatformV1MachineSpecResponseOutput

Immutable. The specification of a single machine used by the prediction.

func (GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) MaxReplicaCount 

func (o GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) MaxReplicaCount() pulumi.IntOutput

Immutable. The maximum number of replicas this DeployedModel may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale the model to that many replicas is guaranteed (barring service outages). If traffic against the DeployedModel increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, will use min_replica_count as the default value. The value of this field impacts the charge against Vertex CPU and GPU quotas. Specifically, you will be charged for (max_replica_count * number of cores in the selected machine type) and (max_replica_count * number of GPUs per replica in the selected machine type).

func (GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) MinReplicaCount 

func (o GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) MinReplicaCount() pulumi.IntOutput

Immutable. The minimum number of machine replicas this DeployedModel will be always deployed on. This value must be greater than or equal to 1. If traffic against the DeployedModel increases, it may dynamically be deployed onto more replicas, and as traffic decreases, some of these extra replicas may be freed.

func (GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) ToGoogleCloudAiplatformV1DedicatedResourcesResponseOutput 

func (o GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) ToGoogleCloudAiplatformV1DedicatedResourcesResponseOutput() GoogleCloudAiplatformV1DedicatedResourcesResponseOutput

func (GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) ToGoogleCloudAiplatformV1DedicatedResourcesResponseOutputWithContext 

func (o GoogleCloudAiplatformV1DedicatedResourcesResponseOutput) ToGoogleCloudAiplatformV1DedicatedResourcesResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DedicatedResourcesResponseOutput

type GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponse 

type GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponse struct {
	// A list of allowed JWT issuers. Each entry must be a valid Google service account, in the following format: `service-account-name@project-id.iam.gserviceaccount.com`
	AllowedIssuers []string `pulumi:"allowedIssuers"`
	// The list of JWT [audiences](https://tools.ietf.org/html/draft-ietf-oauth-json-web-token-32#section-4.1.3). that are allowed to access. A JWT containing any of these audiences will be accepted.
	Audiences []string `pulumi:"audiences"`
}

Configuration for an authentication provider, including support for [JSON Web Token (JWT)](https://tools.ietf.org/html/draft-ietf-oauth-json-web-token-32).

type GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput 

type GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput struct{ *pulumi.OutputState }

Configuration for an authentication provider, including support for [JSON Web Token (JWT)](https://tools.ietf.org/html/draft-ietf-oauth-json-web-token-32).

func (GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput) AllowedIssuers 

func (o GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput) AllowedIssuers() pulumi.StringArrayOutput

A list of allowed JWT issuers. Each entry must be a valid Google service account, in the following format: `service-account-name@project-id.iam.gserviceaccount.com`

func (GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput) Audiences 

func (o GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput) Audiences() pulumi.StringArrayOutput

The list of JWT [audiences](https://tools.ietf.org/html/draft-ietf-oauth-json-web-token-32#section-4.1.3). that are allowed to access. A JWT containing any of these audiences will be accepted.

func (GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput) ElementType 

func (GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput 

func (o GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput() GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput

func (GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutputWithContext 

func (o GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput

type GoogleCloudAiplatformV1DeployedIndexAuthConfigResponse 

type GoogleCloudAiplatformV1DeployedIndexAuthConfigResponse struct {
	// Defines the authentication provider that the DeployedIndex uses.
	AuthProvider GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponse `pulumi:"authProvider"`
}

Used to set up the auth on the DeployedIndex's private endpoint.

type GoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput 

type GoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput struct{ *pulumi.OutputState }

Used to set up the auth on the DeployedIndex's private endpoint.

func (GoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput) AuthProvider 

func (o GoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput) AuthProvider() GoogleCloudAiplatformV1DeployedIndexAuthConfigAuthProviderResponseOutput

Defines the authentication provider that the DeployedIndex uses.

func (GoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput 

func (o GoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput() GoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput

func (GoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput

type GoogleCloudAiplatformV1DeployedIndexRefResponse 

type GoogleCloudAiplatformV1DeployedIndexRefResponse struct {
	// Immutable. The ID of the DeployedIndex in the above IndexEndpoint.
	DeployedIndexId string `pulumi:"deployedIndexId"`
	// Immutable. A resource name of the IndexEndpoint.
	IndexEndpoint string `pulumi:"indexEndpoint"`
}

Points to a DeployedIndex.

type GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput 

type GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1DeployedIndexRefResponseOutput

func (GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput 

func (o GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput() GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput

func (GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput

type GoogleCloudAiplatformV1DeployedIndexRefResponseOutput 

type GoogleCloudAiplatformV1DeployedIndexRefResponseOutput struct{ *pulumi.OutputState }

Points to a DeployedIndex.

func (GoogleCloudAiplatformV1DeployedIndexRefResponseOutput) DeployedIndexId 

func (o GoogleCloudAiplatformV1DeployedIndexRefResponseOutput) DeployedIndexId() pulumi.StringOutput

Immutable. The ID of the DeployedIndex in the above IndexEndpoint.

func (GoogleCloudAiplatformV1DeployedIndexRefResponseOutput) ElementType 

func (GoogleCloudAiplatformV1DeployedIndexRefResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DeployedIndexRefResponseOutput) IndexEndpoint 

func (o GoogleCloudAiplatformV1DeployedIndexRefResponseOutput) IndexEndpoint() pulumi.StringOutput

Immutable. A resource name of the IndexEndpoint.

func (GoogleCloudAiplatformV1DeployedIndexRefResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexRefResponseOutput 

func (o GoogleCloudAiplatformV1DeployedIndexRefResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexRefResponseOutput() GoogleCloudAiplatformV1DeployedIndexRefResponseOutput

func (GoogleCloudAiplatformV1DeployedIndexRefResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexRefResponseOutputWithContext 

func (o GoogleCloudAiplatformV1DeployedIndexRefResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexRefResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DeployedIndexRefResponseOutput

type GoogleCloudAiplatformV1DeployedIndexResponse 

type GoogleCloudAiplatformV1DeployedIndexResponse struct {
	// Optional. A description of resources that the DeployedIndex uses, which to large degree are decided by Vertex AI, and optionally allows only a modest additional configuration. If min_replica_count is not set, the default value is 2 (we don't provide SLA when min_replica_count=1). If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000.
	AutomaticResources GoogleCloudAiplatformV1AutomaticResourcesResponse `pulumi:"automaticResources"`
	// Timestamp when the DeployedIndex was created.
	CreateTime string `pulumi:"createTime"`
	// Optional. A description of resources that are dedicated to the DeployedIndex, and that need a higher degree of manual configuration. The field min_replica_count must be set to a value strictly greater than 0, or else validation will fail. We don't provide SLA when min_replica_count=1. If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000. Available machine types for SMALL shard: e2-standard-2 and all machine types available for MEDIUM and LARGE shard. Available machine types for MEDIUM shard: e2-standard-16 and all machine types available for LARGE shard. Available machine types for LARGE shard: e2-highmem-16, n2d-standard-32. n1-standard-16 and n1-standard-32 are still available, but we recommend e2-standard-16 and e2-highmem-16 for cost efficiency.
	DedicatedResources GoogleCloudAiplatformV1DedicatedResourcesResponse `pulumi:"dedicatedResources"`
	// Optional. If set, the authentication is enabled for the private endpoint.
	DeployedIndexAuthConfig GoogleCloudAiplatformV1DeployedIndexAuthConfigResponse `pulumi:"deployedIndexAuthConfig"`
	// Optional. The deployment group can be no longer than 64 characters (eg: 'test', 'prod'). If not set, we will use the 'default' deployment group. Creating `deployment_groups` with `reserved_ip_ranges` is a recommended practice when the peered network has multiple peering ranges. This creates your deployments from predictable IP spaces for easier traffic administration. Also, one deployment_group (except 'default') can only be used with the same reserved_ip_ranges which means if the deployment_group has been used with reserved_ip_ranges: [a, b, c], using it with [a, b] or [d, e] is disallowed. Note: we only support up to 5 deployment groups(not including 'default').
	DeploymentGroup string `pulumi:"deploymentGroup"`
	// The display name of the DeployedIndex. If not provided upon creation, the Index's display_name is used.
	DisplayName string `pulumi:"displayName"`
	// Optional. If true, private endpoint's access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each MatchRequest. Note that logs may incur a cost, especially if the deployed index receives a high queries per second rate (QPS). Estimate your costs before enabling this option.
	EnableAccessLogging bool `pulumi:"enableAccessLogging"`
	// The name of the Index this is the deployment of. We may refer to this Index as the DeployedIndex's "original" Index.
	Index string `pulumi:"index"`
	// The DeployedIndex may depend on various data on its original Index. Additionally when certain changes to the original Index are being done (e.g. when what the Index contains is being changed) the DeployedIndex may be asynchronously updated in the background to reflect these changes. If this timestamp's value is at least the Index.update_time of the original Index, it means that this DeployedIndex and the original Index are in sync. If this timestamp is older, then to see which updates this DeployedIndex already contains (and which it does not), one must list the operations that are running on the original Index. Only the successfully completed Operations with update_time equal or before this sync time are contained in this DeployedIndex.
	IndexSyncTime string `pulumi:"indexSyncTime"`
	// Provides paths for users to send requests directly to the deployed index services running on Cloud via private services access. This field is populated if network is configured.
	PrivateEndpoints GoogleCloudAiplatformV1IndexPrivateEndpointsResponse `pulumi:"privateEndpoints"`
	// Optional. A list of reserved ip ranges under the VPC network that can be used for this DeployedIndex. If set, we will deploy the index within the provided ip ranges. Otherwise, the index might be deployed to any ip ranges under the provided VPC network. The value should be the name of the address (https://cloud.google.com/compute/docs/reference/rest/v1/addresses) Example: ['vertex-ai-ip-range']. For more information about subnets and network IP ranges, please see https://cloud.google.com/vpc/docs/subnets#manually_created_subnet_ip_ranges.
	ReservedIpRanges []string `pulumi:"reservedIpRanges"`
}

A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes.

type GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput 

type GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1DeployedIndexResponseOutput

func (GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedIndexResponseArrayOutput 

func (o GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedIndexResponseArrayOutput() GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput

func (GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedIndexResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedIndexResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput

type GoogleCloudAiplatformV1DeployedIndexResponseOutput 

type GoogleCloudAiplatformV1DeployedIndexResponseOutput struct{ *pulumi.OutputState }

A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes.

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) AutomaticResources 

func (o GoogleCloudAiplatformV1DeployedIndexResponseOutput) AutomaticResources() GoogleCloudAiplatformV1AutomaticResourcesResponseOutput

Optional. A description of resources that the DeployedIndex uses, which to large degree are decided by Vertex AI, and optionally allows only a modest additional configuration. If min_replica_count is not set, the default value is 2 (we don't provide SLA when min_replica_count=1). If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000.

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) CreateTime 

func (o GoogleCloudAiplatformV1DeployedIndexResponseOutput) CreateTime() pulumi.StringOutput

Timestamp when the DeployedIndex was created.

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) DedicatedResources 

func (o GoogleCloudAiplatformV1DeployedIndexResponseOutput) DedicatedResources() GoogleCloudAiplatformV1DedicatedResourcesResponseOutput

Optional. A description of resources that are dedicated to the DeployedIndex, and that need a higher degree of manual configuration. The field min_replica_count must be set to a value strictly greater than 0, or else validation will fail. We don't provide SLA when min_replica_count=1. If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000. Available machine types for SMALL shard: e2-standard-2 and all machine types available for MEDIUM and LARGE shard. Available machine types for MEDIUM shard: e2-standard-16 and all machine types available for LARGE shard. Available machine types for LARGE shard: e2-highmem-16, n2d-standard-32. n1-standard-16 and n1-standard-32 are still available, but we recommend e2-standard-16 and e2-highmem-16 for cost efficiency.

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) DeployedIndexAuthConfig 

func (o GoogleCloudAiplatformV1DeployedIndexResponseOutput) DeployedIndexAuthConfig() GoogleCloudAiplatformV1DeployedIndexAuthConfigResponseOutput

Optional. If set, the authentication is enabled for the private endpoint.

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) DeploymentGroup 

func (o GoogleCloudAiplatformV1DeployedIndexResponseOutput) DeploymentGroup() pulumi.StringOutput

Optional. The deployment group can be no longer than 64 characters (eg: 'test', 'prod'). If not set, we will use the 'default' deployment group. Creating `deployment_groups` with `reserved_ip_ranges` is a recommended practice when the peered network has multiple peering ranges. This creates your deployments from predictable IP spaces for easier traffic administration. Also, one deployment_group (except 'default') can only be used with the same reserved_ip_ranges which means if the deployment_group has been used with reserved_ip_ranges: [a, b, c], using it with [a, b] or [d, e] is disallowed. Note: we only support up to 5 deployment groups(not including 'default').

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) DisplayName 

func (o GoogleCloudAiplatformV1DeployedIndexResponseOutput) DisplayName() pulumi.StringOutput

The display name of the DeployedIndex. If not provided upon creation, the Index's display_name is used.

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) ElementType 

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) EnableAccessLogging 

func (o GoogleCloudAiplatformV1DeployedIndexResponseOutput) EnableAccessLogging() pulumi.BoolOutput

Optional. If true, private endpoint's access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each MatchRequest. Note that logs may incur a cost, especially if the deployed index receives a high queries per second rate (QPS). Estimate your costs before enabling this option.

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) Index 

func (o GoogleCloudAiplatformV1DeployedIndexResponseOutput) Index() pulumi.StringOutput

The name of the Index this is the deployment of. We may refer to this Index as the DeployedIndex's "original" Index.

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) IndexSyncTime 

func (o GoogleCloudAiplatformV1DeployedIndexResponseOutput) IndexSyncTime() pulumi.StringOutput

The DeployedIndex may depend on various data on its original Index. Additionally when certain changes to the original Index are being done (e.g. when what the Index contains is being changed) the DeployedIndex may be asynchronously updated in the background to reflect these changes. If this timestamp's value is at least the Index.update_time of the original Index, it means that this DeployedIndex and the original Index are in sync. If this timestamp is older, then to see which updates this DeployedIndex already contains (and which it does not), one must list the operations that are running on the original Index. Only the successfully completed Operations with update_time equal or before this sync time are contained in this DeployedIndex.

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) PrivateEndpoints 

func (o GoogleCloudAiplatformV1DeployedIndexResponseOutput) PrivateEndpoints() GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput

Provides paths for users to send requests directly to the deployed index services running on Cloud via private services access. This field is populated if network is configured.

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) ReservedIpRanges 

func (o GoogleCloudAiplatformV1DeployedIndexResponseOutput) ReservedIpRanges() pulumi.StringArrayOutput

Optional. A list of reserved ip ranges under the VPC network that can be used for this DeployedIndex. If set, we will deploy the index within the provided ip ranges. Otherwise, the index might be deployed to any ip ranges under the provided VPC network. The value should be the name of the address (https://cloud.google.com/compute/docs/reference/rest/v1/addresses) Example: ['vertex-ai-ip-range']. For more information about subnets and network IP ranges, please see https://cloud.google.com/vpc/docs/subnets#manually_created_subnet_ip_ranges.

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexResponseOutput 

func (o GoogleCloudAiplatformV1DeployedIndexResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexResponseOutput() GoogleCloudAiplatformV1DeployedIndexResponseOutput

func (GoogleCloudAiplatformV1DeployedIndexResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexResponseOutputWithContext 

func (o GoogleCloudAiplatformV1DeployedIndexResponseOutput) ToGoogleCloudAiplatformV1DeployedIndexResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DeployedIndexResponseOutput

type GoogleCloudAiplatformV1DeployedModelRefResponse 

type GoogleCloudAiplatformV1DeployedModelRefResponse struct {
	// Immutable. An ID of a DeployedModel in the above Endpoint.
	DeployedModelId string `pulumi:"deployedModelId"`
	// Immutable. A resource name of an Endpoint.
	Endpoint string `pulumi:"endpoint"`
}

Points to a DeployedModel.

type GoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput 

type GoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1DeployedModelRefResponseOutput

func (GoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput 

func (o GoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput() GoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput

func (GoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedModelRefResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedModelRefResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput

type GoogleCloudAiplatformV1DeployedModelRefResponseOutput 

type GoogleCloudAiplatformV1DeployedModelRefResponseOutput struct{ *pulumi.OutputState }

Points to a DeployedModel.

func (GoogleCloudAiplatformV1DeployedModelRefResponseOutput) DeployedModelId 

func (o GoogleCloudAiplatformV1DeployedModelRefResponseOutput) DeployedModelId() pulumi.StringOutput

Immutable. An ID of a DeployedModel in the above Endpoint.

func (GoogleCloudAiplatformV1DeployedModelRefResponseOutput) ElementType 

func (GoogleCloudAiplatformV1DeployedModelRefResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DeployedModelRefResponseOutput) Endpoint 

func (o GoogleCloudAiplatformV1DeployedModelRefResponseOutput) Endpoint() pulumi.StringOutput

Immutable. A resource name of an Endpoint.

func (GoogleCloudAiplatformV1DeployedModelRefResponseOutput) ToGoogleCloudAiplatformV1DeployedModelRefResponseOutput 

func (o GoogleCloudAiplatformV1DeployedModelRefResponseOutput) ToGoogleCloudAiplatformV1DeployedModelRefResponseOutput() GoogleCloudAiplatformV1DeployedModelRefResponseOutput

func (GoogleCloudAiplatformV1DeployedModelRefResponseOutput) ToGoogleCloudAiplatformV1DeployedModelRefResponseOutputWithContext 

func (o GoogleCloudAiplatformV1DeployedModelRefResponseOutput) ToGoogleCloudAiplatformV1DeployedModelRefResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DeployedModelRefResponseOutput

type GoogleCloudAiplatformV1DeployedModelResponse 

type GoogleCloudAiplatformV1DeployedModelResponse struct {
	// A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.
	AutomaticResources GoogleCloudAiplatformV1AutomaticResourcesResponse `pulumi:"automaticResources"`
	// Timestamp when the DeployedModel was created.
	CreateTime string `pulumi:"createTime"`
	// A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.
	DedicatedResources GoogleCloudAiplatformV1DedicatedResourcesResponse `pulumi:"dedicatedResources"`
	// For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.
	DisableContainerLogging bool `pulumi:"disableContainerLogging"`
	// The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.
	DisplayName string `pulumi:"displayName"`
	// If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each prediction request. Note that logs may incur a cost, especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option.
	EnableAccessLogging bool `pulumi:"enableAccessLogging"`
	// Explanation configuration for this DeployedModel. When deploying a Model using EndpointService.DeployModel, this value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of explanation_spec is not populated, the value of the same field of Model.explanation_spec is inherited. If the corresponding Model.explanation_spec is not populated, all fields of the explanation_spec will be used for the explanation configuration.
	ExplanationSpec GoogleCloudAiplatformV1ExplanationSpecResponse `pulumi:"explanationSpec"`
	// The resource name of the Model that this is the deployment of. Note that the Model may be in a different location than the DeployedModel's Endpoint. The resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed.
	Model string `pulumi:"model"`
	// The version ID of the model that is deployed.
	ModelVersionId string `pulumi:"modelVersionId"`
	// Provide paths for users to send predict/explain/health requests directly to the deployed model services running on Cloud via private services access. This field is populated if network is configured.
	PrivateEndpoints GoogleCloudAiplatformV1PrivateEndpointsResponse `pulumi:"privateEndpoints"`
	// The service account that the DeployedModel's container runs as. Specify the email address of the service account. If this service account is not specified, the container runs as a service account that doesn't have access to the resource project. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.
	ServiceAccount string `pulumi:"serviceAccount"`
}

A deployment of a Model. Endpoints contain one or more DeployedModels.

type GoogleCloudAiplatformV1DeployedModelResponseArrayOutput 

type GoogleCloudAiplatformV1DeployedModelResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1DeployedModelResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1DeployedModelResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DeployedModelResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1DeployedModelResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1DeployedModelResponseOutput

func (GoogleCloudAiplatformV1DeployedModelResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedModelResponseArrayOutput 

func (o GoogleCloudAiplatformV1DeployedModelResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedModelResponseArrayOutput() GoogleCloudAiplatformV1DeployedModelResponseArrayOutput

func (GoogleCloudAiplatformV1DeployedModelResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedModelResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1DeployedModelResponseArrayOutput) ToGoogleCloudAiplatformV1DeployedModelResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DeployedModelResponseArrayOutput

type GoogleCloudAiplatformV1DeployedModelResponseOutput 

type GoogleCloudAiplatformV1DeployedModelResponseOutput struct{ *pulumi.OutputState }

A deployment of a Model. Endpoints contain one or more DeployedModels.

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) AutomaticResources 

func (o GoogleCloudAiplatformV1DeployedModelResponseOutput) AutomaticResources() GoogleCloudAiplatformV1AutomaticResourcesResponseOutput

A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) CreateTime 

func (o GoogleCloudAiplatformV1DeployedModelResponseOutput) CreateTime() pulumi.StringOutput

Timestamp when the DeployedModel was created.

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) DedicatedResources 

func (o GoogleCloudAiplatformV1DeployedModelResponseOutput) DedicatedResources() GoogleCloudAiplatformV1DedicatedResourcesResponseOutput

A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) DisableContainerLogging 

func (o GoogleCloudAiplatformV1DeployedModelResponseOutput) DisableContainerLogging() pulumi.BoolOutput

For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) DisplayName 

func (o GoogleCloudAiplatformV1DeployedModelResponseOutput) DisplayName() pulumi.StringOutput

The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) ElementType 

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) EnableAccessLogging 

func (o GoogleCloudAiplatformV1DeployedModelResponseOutput) EnableAccessLogging() pulumi.BoolOutput

If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each prediction request. Note that logs may incur a cost, especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option.

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) ExplanationSpec 

func (o GoogleCloudAiplatformV1DeployedModelResponseOutput) ExplanationSpec() GoogleCloudAiplatformV1ExplanationSpecResponseOutput

Explanation configuration for this DeployedModel. When deploying a Model using EndpointService.DeployModel, this value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of explanation_spec is not populated, the value of the same field of Model.explanation_spec is inherited. If the corresponding Model.explanation_spec is not populated, all fields of the explanation_spec will be used for the explanation configuration.

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) Model 

func (o GoogleCloudAiplatformV1DeployedModelResponseOutput) Model() pulumi.StringOutput

The resource name of the Model that this is the deployment of. Note that the Model may be in a different location than the DeployedModel's Endpoint. The resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed.

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) ModelVersionId 

func (o GoogleCloudAiplatformV1DeployedModelResponseOutput) ModelVersionId() pulumi.StringOutput

The version ID of the model that is deployed.

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) PrivateEndpoints 

func (o GoogleCloudAiplatformV1DeployedModelResponseOutput) PrivateEndpoints() GoogleCloudAiplatformV1PrivateEndpointsResponseOutput

Provide paths for users to send predict/explain/health requests directly to the deployed model services running on Cloud via private services access. This field is populated if network is configured.

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) ServiceAccount 

func (o GoogleCloudAiplatformV1DeployedModelResponseOutput) ServiceAccount() pulumi.StringOutput

The service account that the DeployedModel's container runs as. Specify the email address of the service account. If this service account is not specified, the container runs as a service account that doesn't have access to the resource project. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) ToGoogleCloudAiplatformV1DeployedModelResponseOutput 

func (o GoogleCloudAiplatformV1DeployedModelResponseOutput) ToGoogleCloudAiplatformV1DeployedModelResponseOutput() GoogleCloudAiplatformV1DeployedModelResponseOutput

func (GoogleCloudAiplatformV1DeployedModelResponseOutput) ToGoogleCloudAiplatformV1DeployedModelResponseOutputWithContext 

func (o GoogleCloudAiplatformV1DeployedModelResponseOutput) ToGoogleCloudAiplatformV1DeployedModelResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DeployedModelResponseOutput

type GoogleCloudAiplatformV1DiskSpec 

type GoogleCloudAiplatformV1DiskSpec struct {
	// Size in GB of the boot disk (default is 100GB).
	BootDiskSizeGb *int `pulumi:"bootDiskSizeGb"`
	// Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
	BootDiskType *string `pulumi:"bootDiskType"`
}

Represents the spec of disk options.

type GoogleCloudAiplatformV1DiskSpecArgs 

type GoogleCloudAiplatformV1DiskSpecArgs struct {
	// Size in GB of the boot disk (default is 100GB).
	BootDiskSizeGb pulumi.IntPtrInput `pulumi:"bootDiskSizeGb"`
	// Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
	BootDiskType pulumi.StringPtrInput `pulumi:"bootDiskType"`
}

Represents the spec of disk options.

func (GoogleCloudAiplatformV1DiskSpecArgs) ElementType 

func (GoogleCloudAiplatformV1DiskSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DiskSpecArgs) ToGoogleCloudAiplatformV1DiskSpecOutput 

func (i GoogleCloudAiplatformV1DiskSpecArgs) ToGoogleCloudAiplatformV1DiskSpecOutput() GoogleCloudAiplatformV1DiskSpecOutput

func (GoogleCloudAiplatformV1DiskSpecArgs) ToGoogleCloudAiplatformV1DiskSpecOutputWithContext 

func (i GoogleCloudAiplatformV1DiskSpecArgs) ToGoogleCloudAiplatformV1DiskSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DiskSpecOutput

func (GoogleCloudAiplatformV1DiskSpecArgs) ToGoogleCloudAiplatformV1DiskSpecPtrOutput 

func (i GoogleCloudAiplatformV1DiskSpecArgs) ToGoogleCloudAiplatformV1DiskSpecPtrOutput() GoogleCloudAiplatformV1DiskSpecPtrOutput

func (GoogleCloudAiplatformV1DiskSpecArgs) ToGoogleCloudAiplatformV1DiskSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1DiskSpecArgs) ToGoogleCloudAiplatformV1DiskSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DiskSpecPtrOutput

type GoogleCloudAiplatformV1DiskSpecInput 

type GoogleCloudAiplatformV1DiskSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1DiskSpecOutput() GoogleCloudAiplatformV1DiskSpecOutput
	ToGoogleCloudAiplatformV1DiskSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1DiskSpecOutput
}

GoogleCloudAiplatformV1DiskSpecInput is an input type that accepts GoogleCloudAiplatformV1DiskSpecArgs and GoogleCloudAiplatformV1DiskSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1DiskSpecInput` via: 

GoogleCloudAiplatformV1DiskSpecArgs{...}

type GoogleCloudAiplatformV1DiskSpecOutput 

type GoogleCloudAiplatformV1DiskSpecOutput struct{ *pulumi.OutputState }

Represents the spec of disk options.

func (GoogleCloudAiplatformV1DiskSpecOutput) BootDiskSizeGb 

func (o GoogleCloudAiplatformV1DiskSpecOutput) BootDiskSizeGb() pulumi.IntPtrOutput

Size in GB of the boot disk (default is 100GB).

func (GoogleCloudAiplatformV1DiskSpecOutput) BootDiskType 

func (o GoogleCloudAiplatformV1DiskSpecOutput) BootDiskType() pulumi.StringPtrOutput

Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

func (GoogleCloudAiplatformV1DiskSpecOutput) ElementType 

func (GoogleCloudAiplatformV1DiskSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DiskSpecOutput) ToGoogleCloudAiplatformV1DiskSpecOutput 

func (o GoogleCloudAiplatformV1DiskSpecOutput) ToGoogleCloudAiplatformV1DiskSpecOutput() GoogleCloudAiplatformV1DiskSpecOutput

func (GoogleCloudAiplatformV1DiskSpecOutput) ToGoogleCloudAiplatformV1DiskSpecOutputWithContext 

func (o GoogleCloudAiplatformV1DiskSpecOutput) ToGoogleCloudAiplatformV1DiskSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DiskSpecOutput

func (GoogleCloudAiplatformV1DiskSpecOutput) ToGoogleCloudAiplatformV1DiskSpecPtrOutput 

func (o GoogleCloudAiplatformV1DiskSpecOutput) ToGoogleCloudAiplatformV1DiskSpecPtrOutput() GoogleCloudAiplatformV1DiskSpecPtrOutput

func (GoogleCloudAiplatformV1DiskSpecOutput) ToGoogleCloudAiplatformV1DiskSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1DiskSpecOutput) ToGoogleCloudAiplatformV1DiskSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DiskSpecPtrOutput

type GoogleCloudAiplatformV1DiskSpecPtrInput 

type GoogleCloudAiplatformV1DiskSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1DiskSpecPtrOutput() GoogleCloudAiplatformV1DiskSpecPtrOutput
	ToGoogleCloudAiplatformV1DiskSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1DiskSpecPtrOutput
}

GoogleCloudAiplatformV1DiskSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1DiskSpecArgs, GoogleCloudAiplatformV1DiskSpecPtr and GoogleCloudAiplatformV1DiskSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1DiskSpecPtrInput` via: 

        GoogleCloudAiplatformV1DiskSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1DiskSpecPtr 

func GoogleCloudAiplatformV1DiskSpecPtr(v *GoogleCloudAiplatformV1DiskSpecArgs) GoogleCloudAiplatformV1DiskSpecPtrInput

type GoogleCloudAiplatformV1DiskSpecPtrOutput 

type GoogleCloudAiplatformV1DiskSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1DiskSpecPtrOutput) BootDiskSizeGb 

func (o GoogleCloudAiplatformV1DiskSpecPtrOutput) BootDiskSizeGb() pulumi.IntPtrOutput

Size in GB of the boot disk (default is 100GB).

func (GoogleCloudAiplatformV1DiskSpecPtrOutput) BootDiskType 

func (o GoogleCloudAiplatformV1DiskSpecPtrOutput) BootDiskType() pulumi.StringPtrOutput

Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

func (GoogleCloudAiplatformV1DiskSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1DiskSpecPtrOutput) Elem() GoogleCloudAiplatformV1DiskSpecOutput

func (GoogleCloudAiplatformV1DiskSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1DiskSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DiskSpecPtrOutput) ToGoogleCloudAiplatformV1DiskSpecPtrOutput 

func (o GoogleCloudAiplatformV1DiskSpecPtrOutput) ToGoogleCloudAiplatformV1DiskSpecPtrOutput() GoogleCloudAiplatformV1DiskSpecPtrOutput

func (GoogleCloudAiplatformV1DiskSpecPtrOutput) ToGoogleCloudAiplatformV1DiskSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1DiskSpecPtrOutput) ToGoogleCloudAiplatformV1DiskSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DiskSpecPtrOutput

type GoogleCloudAiplatformV1DiskSpecResponse 

type GoogleCloudAiplatformV1DiskSpecResponse struct {
	// Size in GB of the boot disk (default is 100GB).
	BootDiskSizeGb int `pulumi:"bootDiskSizeGb"`
	// Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
	BootDiskType string `pulumi:"bootDiskType"`
}

Represents the spec of disk options.

type GoogleCloudAiplatformV1DiskSpecResponseOutput 

type GoogleCloudAiplatformV1DiskSpecResponseOutput struct{ *pulumi.OutputState }

Represents the spec of disk options.

func (GoogleCloudAiplatformV1DiskSpecResponseOutput) BootDiskSizeGb 

func (o GoogleCloudAiplatformV1DiskSpecResponseOutput) BootDiskSizeGb() pulumi.IntOutput

Size in GB of the boot disk (default is 100GB).

func (GoogleCloudAiplatformV1DiskSpecResponseOutput) BootDiskType 

func (o GoogleCloudAiplatformV1DiskSpecResponseOutput) BootDiskType() pulumi.StringOutput

Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

func (GoogleCloudAiplatformV1DiskSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1DiskSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1DiskSpecResponseOutput) ToGoogleCloudAiplatformV1DiskSpecResponseOutput 

func (o GoogleCloudAiplatformV1DiskSpecResponseOutput) ToGoogleCloudAiplatformV1DiskSpecResponseOutput() GoogleCloudAiplatformV1DiskSpecResponseOutput

func (GoogleCloudAiplatformV1DiskSpecResponseOutput) ToGoogleCloudAiplatformV1DiskSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1DiskSpecResponseOutput) ToGoogleCloudAiplatformV1DiskSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1DiskSpecResponseOutput

type GoogleCloudAiplatformV1EncryptionSpec 

type GoogleCloudAiplatformV1EncryptionSpec struct {
	// The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
	KmsKeyName string `pulumi:"kmsKeyName"`
}

Represents a customer-managed encryption key spec that can be applied to a top-level resource.

type GoogleCloudAiplatformV1EncryptionSpecArgs 

type GoogleCloudAiplatformV1EncryptionSpecArgs struct {
	// The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
	KmsKeyName pulumi.StringInput `pulumi:"kmsKeyName"`
}

Represents a customer-managed encryption key spec that can be applied to a top-level resource.

func (GoogleCloudAiplatformV1EncryptionSpecArgs) ElementType 

func (GoogleCloudAiplatformV1EncryptionSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1EncryptionSpecArgs) ToGoogleCloudAiplatformV1EncryptionSpecOutput 

func (i GoogleCloudAiplatformV1EncryptionSpecArgs) ToGoogleCloudAiplatformV1EncryptionSpecOutput() GoogleCloudAiplatformV1EncryptionSpecOutput

func (GoogleCloudAiplatformV1EncryptionSpecArgs) ToGoogleCloudAiplatformV1EncryptionSpecOutputWithContext 

func (i GoogleCloudAiplatformV1EncryptionSpecArgs) ToGoogleCloudAiplatformV1EncryptionSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1EncryptionSpecOutput

func (GoogleCloudAiplatformV1EncryptionSpecArgs) ToGoogleCloudAiplatformV1EncryptionSpecPtrOutput 

func (i GoogleCloudAiplatformV1EncryptionSpecArgs) ToGoogleCloudAiplatformV1EncryptionSpecPtrOutput() GoogleCloudAiplatformV1EncryptionSpecPtrOutput

func (GoogleCloudAiplatformV1EncryptionSpecArgs) ToGoogleCloudAiplatformV1EncryptionSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1EncryptionSpecArgs) ToGoogleCloudAiplatformV1EncryptionSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1EncryptionSpecPtrOutput

type GoogleCloudAiplatformV1EncryptionSpecInput 

type GoogleCloudAiplatformV1EncryptionSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1EncryptionSpecOutput() GoogleCloudAiplatformV1EncryptionSpecOutput
	ToGoogleCloudAiplatformV1EncryptionSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1EncryptionSpecOutput
}

GoogleCloudAiplatformV1EncryptionSpecInput is an input type that accepts GoogleCloudAiplatformV1EncryptionSpecArgs and GoogleCloudAiplatformV1EncryptionSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1EncryptionSpecInput` via: 

GoogleCloudAiplatformV1EncryptionSpecArgs{...}

type GoogleCloudAiplatformV1EncryptionSpecOutput 

type GoogleCloudAiplatformV1EncryptionSpecOutput struct{ *pulumi.OutputState }

Represents a customer-managed encryption key spec that can be applied to a top-level resource.

func (GoogleCloudAiplatformV1EncryptionSpecOutput) ElementType 

func (GoogleCloudAiplatformV1EncryptionSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1EncryptionSpecOutput) KmsKeyName 

func (o GoogleCloudAiplatformV1EncryptionSpecOutput) KmsKeyName() pulumi.StringOutput

The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.

func (GoogleCloudAiplatformV1EncryptionSpecOutput) ToGoogleCloudAiplatformV1EncryptionSpecOutput 

func (o GoogleCloudAiplatformV1EncryptionSpecOutput) ToGoogleCloudAiplatformV1EncryptionSpecOutput() GoogleCloudAiplatformV1EncryptionSpecOutput

func (GoogleCloudAiplatformV1EncryptionSpecOutput) ToGoogleCloudAiplatformV1EncryptionSpecOutputWithContext 

func (o GoogleCloudAiplatformV1EncryptionSpecOutput) ToGoogleCloudAiplatformV1EncryptionSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1EncryptionSpecOutput

func (GoogleCloudAiplatformV1EncryptionSpecOutput) ToGoogleCloudAiplatformV1EncryptionSpecPtrOutput 

func (o GoogleCloudAiplatformV1EncryptionSpecOutput) ToGoogleCloudAiplatformV1EncryptionSpecPtrOutput() GoogleCloudAiplatformV1EncryptionSpecPtrOutput

func (GoogleCloudAiplatformV1EncryptionSpecOutput) ToGoogleCloudAiplatformV1EncryptionSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1EncryptionSpecOutput) ToGoogleCloudAiplatformV1EncryptionSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1EncryptionSpecPtrOutput

type GoogleCloudAiplatformV1EncryptionSpecPtrInput 

type GoogleCloudAiplatformV1EncryptionSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1EncryptionSpecPtrOutput() GoogleCloudAiplatformV1EncryptionSpecPtrOutput
	ToGoogleCloudAiplatformV1EncryptionSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1EncryptionSpecPtrOutput
}

GoogleCloudAiplatformV1EncryptionSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1EncryptionSpecArgs, GoogleCloudAiplatformV1EncryptionSpecPtr and GoogleCloudAiplatformV1EncryptionSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1EncryptionSpecPtrInput` via: 

        GoogleCloudAiplatformV1EncryptionSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1EncryptionSpecPtr 

func GoogleCloudAiplatformV1EncryptionSpecPtr(v *GoogleCloudAiplatformV1EncryptionSpecArgs) GoogleCloudAiplatformV1EncryptionSpecPtrInput

type GoogleCloudAiplatformV1EncryptionSpecPtrOutput 

type GoogleCloudAiplatformV1EncryptionSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1EncryptionSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1EncryptionSpecPtrOutput) Elem() GoogleCloudAiplatformV1EncryptionSpecOutput

func (GoogleCloudAiplatformV1EncryptionSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1EncryptionSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1EncryptionSpecPtrOutput) KmsKeyName 

func (o GoogleCloudAiplatformV1EncryptionSpecPtrOutput) KmsKeyName() pulumi.StringPtrOutput

The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.

func (GoogleCloudAiplatformV1EncryptionSpecPtrOutput) ToGoogleCloudAiplatformV1EncryptionSpecPtrOutput 

func (o GoogleCloudAiplatformV1EncryptionSpecPtrOutput) ToGoogleCloudAiplatformV1EncryptionSpecPtrOutput() GoogleCloudAiplatformV1EncryptionSpecPtrOutput

func (GoogleCloudAiplatformV1EncryptionSpecPtrOutput) ToGoogleCloudAiplatformV1EncryptionSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1EncryptionSpecPtrOutput) ToGoogleCloudAiplatformV1EncryptionSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1EncryptionSpecPtrOutput

type GoogleCloudAiplatformV1EncryptionSpecResponse 

type GoogleCloudAiplatformV1EncryptionSpecResponse struct {
	// The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.
	KmsKeyName string `pulumi:"kmsKeyName"`
}

Represents a customer-managed encryption key spec that can be applied to a top-level resource.

type GoogleCloudAiplatformV1EncryptionSpecResponseOutput 

type GoogleCloudAiplatformV1EncryptionSpecResponseOutput struct{ *pulumi.OutputState }

Represents a customer-managed encryption key spec that can be applied to a top-level resource.

func (GoogleCloudAiplatformV1EncryptionSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1EncryptionSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1EncryptionSpecResponseOutput) KmsKeyName 

func (o GoogleCloudAiplatformV1EncryptionSpecResponseOutput) KmsKeyName() pulumi.StringOutput

The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`. The key needs to be in the same region as where the compute resource is created.

func (GoogleCloudAiplatformV1EncryptionSpecResponseOutput) ToGoogleCloudAiplatformV1EncryptionSpecResponseOutput 

func (o GoogleCloudAiplatformV1EncryptionSpecResponseOutput) ToGoogleCloudAiplatformV1EncryptionSpecResponseOutput() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

func (GoogleCloudAiplatformV1EncryptionSpecResponseOutput) ToGoogleCloudAiplatformV1EncryptionSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1EncryptionSpecResponseOutput) ToGoogleCloudAiplatformV1EncryptionSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1EncryptionSpecResponseOutput

type GoogleCloudAiplatformV1EnvVar 

type GoogleCloudAiplatformV1EnvVar struct {
	// Name of the environment variable. Must be a valid C identifier.
	Name string `pulumi:"name"`
	// Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
	Value string `pulumi:"value"`
}

Represents an environment variable present in a Container or Python Module.

type GoogleCloudAiplatformV1EnvVarArgs 

type GoogleCloudAiplatformV1EnvVarArgs struct {
	// Name of the environment variable. Must be a valid C identifier.
	Name pulumi.StringInput `pulumi:"name"`
	// Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
	Value pulumi.StringInput `pulumi:"value"`
}

Represents an environment variable present in a Container or Python Module.

func (GoogleCloudAiplatformV1EnvVarArgs) ElementType 

func (GoogleCloudAiplatformV1EnvVarArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1EnvVarArgs) ToGoogleCloudAiplatformV1EnvVarOutput 

func (i GoogleCloudAiplatformV1EnvVarArgs) ToGoogleCloudAiplatformV1EnvVarOutput() GoogleCloudAiplatformV1EnvVarOutput

func (GoogleCloudAiplatformV1EnvVarArgs) ToGoogleCloudAiplatformV1EnvVarOutputWithContext 

func (i GoogleCloudAiplatformV1EnvVarArgs) ToGoogleCloudAiplatformV1EnvVarOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1EnvVarOutput

type GoogleCloudAiplatformV1EnvVarArray 

type GoogleCloudAiplatformV1EnvVarArray []GoogleCloudAiplatformV1EnvVarInput

func (GoogleCloudAiplatformV1EnvVarArray) ElementType 

func (GoogleCloudAiplatformV1EnvVarArray) ElementType() reflect.Type

func (GoogleCloudAiplatformV1EnvVarArray) ToGoogleCloudAiplatformV1EnvVarArrayOutput 

func (i GoogleCloudAiplatformV1EnvVarArray) ToGoogleCloudAiplatformV1EnvVarArrayOutput() GoogleCloudAiplatformV1EnvVarArrayOutput

func (GoogleCloudAiplatformV1EnvVarArray) ToGoogleCloudAiplatformV1EnvVarArrayOutputWithContext 

func (i GoogleCloudAiplatformV1EnvVarArray) ToGoogleCloudAiplatformV1EnvVarArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1EnvVarArrayOutput

type GoogleCloudAiplatformV1EnvVarArrayInput 

type GoogleCloudAiplatformV1EnvVarArrayInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1EnvVarArrayOutput() GoogleCloudAiplatformV1EnvVarArrayOutput
	ToGoogleCloudAiplatformV1EnvVarArrayOutputWithContext(context.Context) GoogleCloudAiplatformV1EnvVarArrayOutput
}

GoogleCloudAiplatformV1EnvVarArrayInput is an input type that accepts GoogleCloudAiplatformV1EnvVarArray and GoogleCloudAiplatformV1EnvVarArrayOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1EnvVarArrayInput` via: 

GoogleCloudAiplatformV1EnvVarArray{ GoogleCloudAiplatformV1EnvVarArgs{...} }

type GoogleCloudAiplatformV1EnvVarArrayOutput 

type GoogleCloudAiplatformV1EnvVarArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1EnvVarArrayOutput) ElementType 

func (GoogleCloudAiplatformV1EnvVarArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1EnvVarArrayOutput) Index 

func (o GoogleCloudAiplatformV1EnvVarArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1EnvVarOutput

func (GoogleCloudAiplatformV1EnvVarArrayOutput) ToGoogleCloudAiplatformV1EnvVarArrayOutput 

func (o GoogleCloudAiplatformV1EnvVarArrayOutput) ToGoogleCloudAiplatformV1EnvVarArrayOutput() GoogleCloudAiplatformV1EnvVarArrayOutput

func (GoogleCloudAiplatformV1EnvVarArrayOutput) ToGoogleCloudAiplatformV1EnvVarArrayOutputWithContext 

func (o GoogleCloudAiplatformV1EnvVarArrayOutput) ToGoogleCloudAiplatformV1EnvVarArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1EnvVarArrayOutput

type GoogleCloudAiplatformV1EnvVarInput 

type GoogleCloudAiplatformV1EnvVarInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1EnvVarOutput() GoogleCloudAiplatformV1EnvVarOutput
	ToGoogleCloudAiplatformV1EnvVarOutputWithContext(context.Context) GoogleCloudAiplatformV1EnvVarOutput
}

GoogleCloudAiplatformV1EnvVarInput is an input type that accepts GoogleCloudAiplatformV1EnvVarArgs and GoogleCloudAiplatformV1EnvVarOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1EnvVarInput` via: 

GoogleCloudAiplatformV1EnvVarArgs{...}

type GoogleCloudAiplatformV1EnvVarOutput 

type GoogleCloudAiplatformV1EnvVarOutput struct{ *pulumi.OutputState }

Represents an environment variable present in a Container or Python Module.

func (GoogleCloudAiplatformV1EnvVarOutput) ElementType 

func (GoogleCloudAiplatformV1EnvVarOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1EnvVarOutput) Name 

func (o GoogleCloudAiplatformV1EnvVarOutput) Name() pulumi.StringOutput

Name of the environment variable. Must be a valid C identifier.

func (GoogleCloudAiplatformV1EnvVarOutput) ToGoogleCloudAiplatformV1EnvVarOutput 

func (o GoogleCloudAiplatformV1EnvVarOutput) ToGoogleCloudAiplatformV1EnvVarOutput() GoogleCloudAiplatformV1EnvVarOutput

func (GoogleCloudAiplatformV1EnvVarOutput) ToGoogleCloudAiplatformV1EnvVarOutputWithContext 

func (o GoogleCloudAiplatformV1EnvVarOutput) ToGoogleCloudAiplatformV1EnvVarOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1EnvVarOutput

func (GoogleCloudAiplatformV1EnvVarOutput) Value 

func (o GoogleCloudAiplatformV1EnvVarOutput) Value() pulumi.StringOutput

Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.

type GoogleCloudAiplatformV1EnvVarResponse 

type GoogleCloudAiplatformV1EnvVarResponse struct {
	// Name of the environment variable. Must be a valid C identifier.
	Name string `pulumi:"name"`
	// Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
	Value string `pulumi:"value"`
}

Represents an environment variable present in a Container or Python Module.

type GoogleCloudAiplatformV1EnvVarResponseArrayOutput 

type GoogleCloudAiplatformV1EnvVarResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1EnvVarResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1EnvVarResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1EnvVarResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1EnvVarResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1EnvVarResponseOutput

func (GoogleCloudAiplatformV1EnvVarResponseArrayOutput) ToGoogleCloudAiplatformV1EnvVarResponseArrayOutput 

func (o GoogleCloudAiplatformV1EnvVarResponseArrayOutput) ToGoogleCloudAiplatformV1EnvVarResponseArrayOutput() GoogleCloudAiplatformV1EnvVarResponseArrayOutput

func (GoogleCloudAiplatformV1EnvVarResponseArrayOutput) ToGoogleCloudAiplatformV1EnvVarResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1EnvVarResponseArrayOutput) ToGoogleCloudAiplatformV1EnvVarResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1EnvVarResponseArrayOutput

type GoogleCloudAiplatformV1EnvVarResponseOutput 

type GoogleCloudAiplatformV1EnvVarResponseOutput struct{ *pulumi.OutputState }

Represents an environment variable present in a Container or Python Module.

func (GoogleCloudAiplatformV1EnvVarResponseOutput) ElementType 

func (GoogleCloudAiplatformV1EnvVarResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1EnvVarResponseOutput) Name 

func (o GoogleCloudAiplatformV1EnvVarResponseOutput) Name() pulumi.StringOutput

Name of the environment variable. Must be a valid C identifier.

func (GoogleCloudAiplatformV1EnvVarResponseOutput) ToGoogleCloudAiplatformV1EnvVarResponseOutput 

func (o GoogleCloudAiplatformV1EnvVarResponseOutput) ToGoogleCloudAiplatformV1EnvVarResponseOutput() GoogleCloudAiplatformV1EnvVarResponseOutput

func (GoogleCloudAiplatformV1EnvVarResponseOutput) ToGoogleCloudAiplatformV1EnvVarResponseOutputWithContext 

func (o GoogleCloudAiplatformV1EnvVarResponseOutput) ToGoogleCloudAiplatformV1EnvVarResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1EnvVarResponseOutput

func (GoogleCloudAiplatformV1EnvVarResponseOutput) Value 

func (o GoogleCloudAiplatformV1EnvVarResponseOutput) Value() pulumi.StringOutput

Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.

type GoogleCloudAiplatformV1Examples 

type GoogleCloudAiplatformV1Examples struct {
	// The Cloud Storage input instances.
	ExampleGcsSource *GoogleCloudAiplatformV1ExamplesExampleGcsSource `pulumi:"exampleGcsSource"`
	// The full configuration for the generated index, the semantics are the same as metadata and should match [NearestNeighborSearchConfig](https://cloud.google.com/vertex-ai/docs/explainable-ai/configuring-explanations-example-based#nearest-neighbor-search-config).
	NearestNeighborSearchConfig interface{} `pulumi:"nearestNeighborSearchConfig"`
	// The number of neighbors to return when querying for examples.
	NeighborCount *int `pulumi:"neighborCount"`
	// Simplified preset configuration, which automatically sets configuration values based on the desired query speed-precision trade-off and modality.
	Presets *GoogleCloudAiplatformV1Presets `pulumi:"presets"`
}

Example-based explainability that returns the nearest neighbors from the provided dataset.

type GoogleCloudAiplatformV1ExamplesArgs 

type GoogleCloudAiplatformV1ExamplesArgs struct {
	// The Cloud Storage input instances.
	ExampleGcsSource GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrInput `pulumi:"exampleGcsSource"`
	// The full configuration for the generated index, the semantics are the same as metadata and should match [NearestNeighborSearchConfig](https://cloud.google.com/vertex-ai/docs/explainable-ai/configuring-explanations-example-based#nearest-neighbor-search-config).
	NearestNeighborSearchConfig pulumi.Input `pulumi:"nearestNeighborSearchConfig"`
	// The number of neighbors to return when querying for examples.
	NeighborCount pulumi.IntPtrInput `pulumi:"neighborCount"`
	// Simplified preset configuration, which automatically sets configuration values based on the desired query speed-precision trade-off and modality.
	Presets GoogleCloudAiplatformV1PresetsPtrInput `pulumi:"presets"`
}

Example-based explainability that returns the nearest neighbors from the provided dataset.

func (GoogleCloudAiplatformV1ExamplesArgs) ElementType 

func (GoogleCloudAiplatformV1ExamplesArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExamplesArgs) ToGoogleCloudAiplatformV1ExamplesOutput 

func (i GoogleCloudAiplatformV1ExamplesArgs) ToGoogleCloudAiplatformV1ExamplesOutput() GoogleCloudAiplatformV1ExamplesOutput

func (GoogleCloudAiplatformV1ExamplesArgs) ToGoogleCloudAiplatformV1ExamplesOutputWithContext 

func (i GoogleCloudAiplatformV1ExamplesArgs) ToGoogleCloudAiplatformV1ExamplesOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesOutput

func (GoogleCloudAiplatformV1ExamplesArgs) ToGoogleCloudAiplatformV1ExamplesPtrOutput 

func (i GoogleCloudAiplatformV1ExamplesArgs) ToGoogleCloudAiplatformV1ExamplesPtrOutput() GoogleCloudAiplatformV1ExamplesPtrOutput

func (GoogleCloudAiplatformV1ExamplesArgs) ToGoogleCloudAiplatformV1ExamplesPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ExamplesArgs) ToGoogleCloudAiplatformV1ExamplesPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesPtrOutput

type GoogleCloudAiplatformV1ExamplesExampleGcsSource 

type GoogleCloudAiplatformV1ExamplesExampleGcsSource struct {
	// The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported.
	DataFormat *GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat `pulumi:"dataFormat"`
	// The Cloud Storage location for the input instances.
	GcsSource *GoogleCloudAiplatformV1GcsSource `pulumi:"gcsSource"`
}

The Cloud Storage input instances.

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs 

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs struct {
	// The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported.
	DataFormat GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrInput `pulumi:"dataFormat"`
	// The Cloud Storage location for the input instances.
	GcsSource GoogleCloudAiplatformV1GcsSourcePtrInput `pulumi:"gcsSource"`
}

The Cloud Storage input instances.

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs) ElementType 

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput 

func (i GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceOutputWithContext 

func (i GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput 

func (i GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutputWithContext 

func (i GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat 

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat string

The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported.

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ElementType 

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput 

func (e GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutputWithContext 

func (e GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput 

func (e GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutputWithContext 

func (e GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToStringOutput 

func (e GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormat) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatInput 

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput
	ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutputWithContext(context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput
}

GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatInput is an input type that accepts GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatArgs and GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatInput` via: 

GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatArgs{...}

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput 

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ElementType 

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrInput 

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput
	ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput
}

func GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtr 

func GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtr(v string) GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrInput

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput 

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput) Elem() GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceInput 

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput
	ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceOutputWithContext(context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput
}

GoogleCloudAiplatformV1ExamplesExampleGcsSourceInput is an input type that accepts GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs and GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ExamplesExampleGcsSourceInput` via: 

GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs{...}

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput 

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput struct{ *pulumi.OutputState }

The Cloud Storage input instances.

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) DataFormat 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) DataFormat() GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput

The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported.

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) ElementType 

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) GcsSource 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) GcsSource() GoogleCloudAiplatformV1GcsSourcePtrOutput

The Cloud Storage location for the input instances.

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput

type GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrInput 

type GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput
	ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput
}

GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrInput is an input type that accepts GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs, GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtr and GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrInput` via: 

        GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtr 

func GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtr(v *GoogleCloudAiplatformV1ExamplesExampleGcsSourceArgs) GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrInput

type GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput 

type GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput) DataFormat 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput) DataFormat() GoogleCloudAiplatformV1ExamplesExampleGcsSourceDataFormatPtrOutput

The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported.

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput) Elem 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput) Elem() GoogleCloudAiplatformV1ExamplesExampleGcsSourceOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput) ElementType 

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput) GcsSource 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput) GcsSource() GoogleCloudAiplatformV1GcsSourcePtrOutput

The Cloud Storage location for the input instances.

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponse 

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponse struct {
	// The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported.
	DataFormat string `pulumi:"dataFormat"`
	// The Cloud Storage location for the input instances.
	GcsSource GoogleCloudAiplatformV1GcsSourceResponse `pulumi:"gcsSource"`
}

The Cloud Storage input instances.

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput 

type GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput struct{ *pulumi.OutputState }

The Cloud Storage input instances.

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput) DataFormat 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput) DataFormat() pulumi.StringOutput

The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported.

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput) GcsSource 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput) GcsSource() GoogleCloudAiplatformV1GcsSourceResponseOutput

The Cloud Storage location for the input instances.

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput() GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput

func (GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput) ToGoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput

type GoogleCloudAiplatformV1ExamplesInput 

type GoogleCloudAiplatformV1ExamplesInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ExamplesOutput() GoogleCloudAiplatformV1ExamplesOutput
	ToGoogleCloudAiplatformV1ExamplesOutputWithContext(context.Context) GoogleCloudAiplatformV1ExamplesOutput
}

GoogleCloudAiplatformV1ExamplesInput is an input type that accepts GoogleCloudAiplatformV1ExamplesArgs and GoogleCloudAiplatformV1ExamplesOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ExamplesInput` via: 

GoogleCloudAiplatformV1ExamplesArgs{...}

type GoogleCloudAiplatformV1ExamplesOutput 

type GoogleCloudAiplatformV1ExamplesOutput struct{ *pulumi.OutputState }

Example-based explainability that returns the nearest neighbors from the provided dataset.

func (GoogleCloudAiplatformV1ExamplesOutput) ElementType 

func (GoogleCloudAiplatformV1ExamplesOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExamplesOutput) ExampleGcsSource 

func (o GoogleCloudAiplatformV1ExamplesOutput) ExampleGcsSource() GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput

The Cloud Storage input instances.

func (GoogleCloudAiplatformV1ExamplesOutput) NearestNeighborSearchConfig 

func (o GoogleCloudAiplatformV1ExamplesOutput) NearestNeighborSearchConfig() pulumi.AnyOutput

The full configuration for the generated index, the semantics are the same as metadata and should match [NearestNeighborSearchConfig](https://cloud.google.com/vertex-ai/docs/explainable-ai/configuring-explanations-example-based#nearest-neighbor-search-config).

func (GoogleCloudAiplatformV1ExamplesOutput) NeighborCount 

func (o GoogleCloudAiplatformV1ExamplesOutput) NeighborCount() pulumi.IntPtrOutput

The number of neighbors to return when querying for examples.

func (GoogleCloudAiplatformV1ExamplesOutput) Presets 

func (o GoogleCloudAiplatformV1ExamplesOutput) Presets() GoogleCloudAiplatformV1PresetsPtrOutput

Simplified preset configuration, which automatically sets configuration values based on the desired query speed-precision trade-off and modality.

func (GoogleCloudAiplatformV1ExamplesOutput) ToGoogleCloudAiplatformV1ExamplesOutput 

func (o GoogleCloudAiplatformV1ExamplesOutput) ToGoogleCloudAiplatformV1ExamplesOutput() GoogleCloudAiplatformV1ExamplesOutput

func (GoogleCloudAiplatformV1ExamplesOutput) ToGoogleCloudAiplatformV1ExamplesOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesOutput) ToGoogleCloudAiplatformV1ExamplesOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesOutput

func (GoogleCloudAiplatformV1ExamplesOutput) ToGoogleCloudAiplatformV1ExamplesPtrOutput 

func (o GoogleCloudAiplatformV1ExamplesOutput) ToGoogleCloudAiplatformV1ExamplesPtrOutput() GoogleCloudAiplatformV1ExamplesPtrOutput

func (GoogleCloudAiplatformV1ExamplesOutput) ToGoogleCloudAiplatformV1ExamplesPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesOutput) ToGoogleCloudAiplatformV1ExamplesPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesPtrOutput

type GoogleCloudAiplatformV1ExamplesPtrInput 

type GoogleCloudAiplatformV1ExamplesPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ExamplesPtrOutput() GoogleCloudAiplatformV1ExamplesPtrOutput
	ToGoogleCloudAiplatformV1ExamplesPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ExamplesPtrOutput
}

GoogleCloudAiplatformV1ExamplesPtrInput is an input type that accepts GoogleCloudAiplatformV1ExamplesArgs, GoogleCloudAiplatformV1ExamplesPtr and GoogleCloudAiplatformV1ExamplesPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ExamplesPtrInput` via: 

        GoogleCloudAiplatformV1ExamplesArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ExamplesPtr 

func GoogleCloudAiplatformV1ExamplesPtr(v *GoogleCloudAiplatformV1ExamplesArgs) GoogleCloudAiplatformV1ExamplesPtrInput

type GoogleCloudAiplatformV1ExamplesPtrOutput 

type GoogleCloudAiplatformV1ExamplesPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ExamplesPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ExamplesPtrOutput) Elem() GoogleCloudAiplatformV1ExamplesOutput

func (GoogleCloudAiplatformV1ExamplesPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ExamplesPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExamplesPtrOutput) ExampleGcsSource 

func (o GoogleCloudAiplatformV1ExamplesPtrOutput) ExampleGcsSource() GoogleCloudAiplatformV1ExamplesExampleGcsSourcePtrOutput

The Cloud Storage input instances.

func (GoogleCloudAiplatformV1ExamplesPtrOutput) NearestNeighborSearchConfig 

func (o GoogleCloudAiplatformV1ExamplesPtrOutput) NearestNeighborSearchConfig() pulumi.AnyOutput

The full configuration for the generated index, the semantics are the same as metadata and should match [NearestNeighborSearchConfig](https://cloud.google.com/vertex-ai/docs/explainable-ai/configuring-explanations-example-based#nearest-neighbor-search-config).

func (GoogleCloudAiplatformV1ExamplesPtrOutput) NeighborCount 

func (o GoogleCloudAiplatformV1ExamplesPtrOutput) NeighborCount() pulumi.IntPtrOutput

The number of neighbors to return when querying for examples.

func (GoogleCloudAiplatformV1ExamplesPtrOutput) Presets 

func (o GoogleCloudAiplatformV1ExamplesPtrOutput) Presets() GoogleCloudAiplatformV1PresetsPtrOutput

Simplified preset configuration, which automatically sets configuration values based on the desired query speed-precision trade-off and modality.

func (GoogleCloudAiplatformV1ExamplesPtrOutput) ToGoogleCloudAiplatformV1ExamplesPtrOutput 

func (o GoogleCloudAiplatformV1ExamplesPtrOutput) ToGoogleCloudAiplatformV1ExamplesPtrOutput() GoogleCloudAiplatformV1ExamplesPtrOutput

func (GoogleCloudAiplatformV1ExamplesPtrOutput) ToGoogleCloudAiplatformV1ExamplesPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesPtrOutput) ToGoogleCloudAiplatformV1ExamplesPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesPtrOutput

type GoogleCloudAiplatformV1ExamplesResponse 

type GoogleCloudAiplatformV1ExamplesResponse struct {
	// The Cloud Storage input instances.
	ExampleGcsSource GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponse `pulumi:"exampleGcsSource"`
	// The full configuration for the generated index, the semantics are the same as metadata and should match [NearestNeighborSearchConfig](https://cloud.google.com/vertex-ai/docs/explainable-ai/configuring-explanations-example-based#nearest-neighbor-search-config).
	NearestNeighborSearchConfig interface{} `pulumi:"nearestNeighborSearchConfig"`
	// The number of neighbors to return when querying for examples.
	NeighborCount int `pulumi:"neighborCount"`
	// Simplified preset configuration, which automatically sets configuration values based on the desired query speed-precision trade-off and modality.
	Presets GoogleCloudAiplatformV1PresetsResponse `pulumi:"presets"`
}

Example-based explainability that returns the nearest neighbors from the provided dataset.

type GoogleCloudAiplatformV1ExamplesResponseOutput 

type GoogleCloudAiplatformV1ExamplesResponseOutput struct{ *pulumi.OutputState }

Example-based explainability that returns the nearest neighbors from the provided dataset.

func (GoogleCloudAiplatformV1ExamplesResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ExamplesResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExamplesResponseOutput) ExampleGcsSource 

func (o GoogleCloudAiplatformV1ExamplesResponseOutput) ExampleGcsSource() GoogleCloudAiplatformV1ExamplesExampleGcsSourceResponseOutput

The Cloud Storage input instances.

func (GoogleCloudAiplatformV1ExamplesResponseOutput) NearestNeighborSearchConfig 

func (o GoogleCloudAiplatformV1ExamplesResponseOutput) NearestNeighborSearchConfig() pulumi.AnyOutput

The full configuration for the generated index, the semantics are the same as metadata and should match [NearestNeighborSearchConfig](https://cloud.google.com/vertex-ai/docs/explainable-ai/configuring-explanations-example-based#nearest-neighbor-search-config).

func (GoogleCloudAiplatformV1ExamplesResponseOutput) NeighborCount 

func (o GoogleCloudAiplatformV1ExamplesResponseOutput) NeighborCount() pulumi.IntOutput

The number of neighbors to return when querying for examples.

func (GoogleCloudAiplatformV1ExamplesResponseOutput) Presets 

func (o GoogleCloudAiplatformV1ExamplesResponseOutput) Presets() GoogleCloudAiplatformV1PresetsResponseOutput

Simplified preset configuration, which automatically sets configuration values based on the desired query speed-precision trade-off and modality.

func (GoogleCloudAiplatformV1ExamplesResponseOutput) ToGoogleCloudAiplatformV1ExamplesResponseOutput 

func (o GoogleCloudAiplatformV1ExamplesResponseOutput) ToGoogleCloudAiplatformV1ExamplesResponseOutput() GoogleCloudAiplatformV1ExamplesResponseOutput

func (GoogleCloudAiplatformV1ExamplesResponseOutput) ToGoogleCloudAiplatformV1ExamplesResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ExamplesResponseOutput) ToGoogleCloudAiplatformV1ExamplesResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExamplesResponseOutput

type GoogleCloudAiplatformV1ExecutionResponse 

type GoogleCloudAiplatformV1ExecutionResponse struct {
	// Timestamp when this Execution was created.
	CreateTime string `pulumi:"createTime"`
	// Description of the Execution
	Description string `pulumi:"description"`
	// User provided display name of the Execution. May be up to 128 Unicode characters.
	DisplayName string `pulumi:"displayName"`
	// An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).
	Labels map[string]string `pulumi:"labels"`
	// Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
	Metadata map[string]string `pulumi:"metadata"`
	// The resource name of the Execution.
	Name string `pulumi:"name"`
	// The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaTitle string `pulumi:"schemaTitle"`
	// The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaVersion string `pulumi:"schemaVersion"`
	// The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
	State string `pulumi:"state"`
	// Timestamp when this Execution was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

Instance of a general execution.

type GoogleCloudAiplatformV1ExecutionResponseOutput 

type GoogleCloudAiplatformV1ExecutionResponseOutput struct{ *pulumi.OutputState }

Instance of a general execution.

func (GoogleCloudAiplatformV1ExecutionResponseOutput) CreateTime 

func (o GoogleCloudAiplatformV1ExecutionResponseOutput) CreateTime() pulumi.StringOutput

Timestamp when this Execution was created.

func (GoogleCloudAiplatformV1ExecutionResponseOutput) Description 

func (o GoogleCloudAiplatformV1ExecutionResponseOutput) Description() pulumi.StringOutput

Description of the Execution

func (GoogleCloudAiplatformV1ExecutionResponseOutput) DisplayName 

func (o GoogleCloudAiplatformV1ExecutionResponseOutput) DisplayName() pulumi.StringOutput

User provided display name of the Execution. May be up to 128 Unicode characters.

func (GoogleCloudAiplatformV1ExecutionResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ExecutionResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExecutionResponseOutput) Etag 

func (o GoogleCloudAiplatformV1ExecutionResponseOutput) Etag() pulumi.StringOutput

An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (GoogleCloudAiplatformV1ExecutionResponseOutput) Labels 

func (o GoogleCloudAiplatformV1ExecutionResponseOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).

func (GoogleCloudAiplatformV1ExecutionResponseOutput) Metadata 

func (o GoogleCloudAiplatformV1ExecutionResponseOutput) Metadata() pulumi.StringMapOutput

Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.

func (GoogleCloudAiplatformV1ExecutionResponseOutput) Name 

func (o GoogleCloudAiplatformV1ExecutionResponseOutput) Name() pulumi.StringOutput

The resource name of the Execution.

func (GoogleCloudAiplatformV1ExecutionResponseOutput) SchemaTitle 

func (o GoogleCloudAiplatformV1ExecutionResponseOutput) SchemaTitle() pulumi.StringOutput

The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (GoogleCloudAiplatformV1ExecutionResponseOutput) SchemaVersion 

func (o GoogleCloudAiplatformV1ExecutionResponseOutput) SchemaVersion() pulumi.StringOutput

The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (GoogleCloudAiplatformV1ExecutionResponseOutput) State 

func (o GoogleCloudAiplatformV1ExecutionResponseOutput) State() pulumi.StringOutput

The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.

func (GoogleCloudAiplatformV1ExecutionResponseOutput) ToGoogleCloudAiplatformV1ExecutionResponseOutput 

func (o GoogleCloudAiplatformV1ExecutionResponseOutput) ToGoogleCloudAiplatformV1ExecutionResponseOutput() GoogleCloudAiplatformV1ExecutionResponseOutput

func (GoogleCloudAiplatformV1ExecutionResponseOutput) ToGoogleCloudAiplatformV1ExecutionResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ExecutionResponseOutput) ToGoogleCloudAiplatformV1ExecutionResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExecutionResponseOutput

func (GoogleCloudAiplatformV1ExecutionResponseOutput) UpdateTime 

func (o GoogleCloudAiplatformV1ExecutionResponseOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Execution was last updated.

type GoogleCloudAiplatformV1ExplanationMetadata 

type GoogleCloudAiplatformV1ExplanationMetadata struct {
	// Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML tabular Models always have this field populated by Vertex AI. Note: The URI given on output may be different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	FeatureAttributionsSchemaUri *string `pulumi:"featureAttributionsSchemaUri"`
	// Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI-provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance.
	Inputs map[string]string `pulumi:"inputs"`
	// Name of the source to generate embeddings for example based explanations.
	LatentSpaceSource *string `pulumi:"latentSpaceSource"`
	// Map from output names to output metadata. For Vertex AI-provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed.
	Outputs map[string]string `pulumi:"outputs"`
}

Metadata describing the Model's input and output for explanation.

type GoogleCloudAiplatformV1ExplanationMetadataArgs 

type GoogleCloudAiplatformV1ExplanationMetadataArgs struct {
	// Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML tabular Models always have this field populated by Vertex AI. Note: The URI given on output may be different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	FeatureAttributionsSchemaUri pulumi.StringPtrInput `pulumi:"featureAttributionsSchemaUri"`
	// Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI-provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance.
	Inputs pulumi.StringMapInput `pulumi:"inputs"`
	// Name of the source to generate embeddings for example based explanations.
	LatentSpaceSource pulumi.StringPtrInput `pulumi:"latentSpaceSource"`
	// Map from output names to output metadata. For Vertex AI-provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed.
	Outputs pulumi.StringMapInput `pulumi:"outputs"`
}

Metadata describing the Model's input and output for explanation.

func (GoogleCloudAiplatformV1ExplanationMetadataArgs) ElementType 

func (GoogleCloudAiplatformV1ExplanationMetadataArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExplanationMetadataArgs) ToGoogleCloudAiplatformV1ExplanationMetadataOutput 

func (i GoogleCloudAiplatformV1ExplanationMetadataArgs) ToGoogleCloudAiplatformV1ExplanationMetadataOutput() GoogleCloudAiplatformV1ExplanationMetadataOutput

func (GoogleCloudAiplatformV1ExplanationMetadataArgs) ToGoogleCloudAiplatformV1ExplanationMetadataOutputWithContext 

func (i GoogleCloudAiplatformV1ExplanationMetadataArgs) ToGoogleCloudAiplatformV1ExplanationMetadataOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationMetadataOutput

func (GoogleCloudAiplatformV1ExplanationMetadataArgs) ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutput 

func (i GoogleCloudAiplatformV1ExplanationMetadataArgs) ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutput() GoogleCloudAiplatformV1ExplanationMetadataPtrOutput

func (GoogleCloudAiplatformV1ExplanationMetadataArgs) ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ExplanationMetadataArgs) ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationMetadataPtrOutput

type GoogleCloudAiplatformV1ExplanationMetadataInput 

type GoogleCloudAiplatformV1ExplanationMetadataInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ExplanationMetadataOutput() GoogleCloudAiplatformV1ExplanationMetadataOutput
	ToGoogleCloudAiplatformV1ExplanationMetadataOutputWithContext(context.Context) GoogleCloudAiplatformV1ExplanationMetadataOutput
}

GoogleCloudAiplatformV1ExplanationMetadataInput is an input type that accepts GoogleCloudAiplatformV1ExplanationMetadataArgs and GoogleCloudAiplatformV1ExplanationMetadataOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ExplanationMetadataInput` via: 

GoogleCloudAiplatformV1ExplanationMetadataArgs{...}

type GoogleCloudAiplatformV1ExplanationMetadataOutput 

type GoogleCloudAiplatformV1ExplanationMetadataOutput struct{ *pulumi.OutputState }

Metadata describing the Model's input and output for explanation.

func (GoogleCloudAiplatformV1ExplanationMetadataOutput) ElementType 

func (GoogleCloudAiplatformV1ExplanationMetadataOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExplanationMetadataOutput) FeatureAttributionsSchemaUri 

func (o GoogleCloudAiplatformV1ExplanationMetadataOutput) FeatureAttributionsSchemaUri() pulumi.StringPtrOutput

Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML tabular Models always have this field populated by Vertex AI. Note: The URI given on output may be different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1ExplanationMetadataOutput) Inputs 

func (o GoogleCloudAiplatformV1ExplanationMetadataOutput) Inputs() pulumi.StringMapOutput

Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI-provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance.

func (GoogleCloudAiplatformV1ExplanationMetadataOutput) LatentSpaceSource 

func (o GoogleCloudAiplatformV1ExplanationMetadataOutput) LatentSpaceSource() pulumi.StringPtrOutput

Name of the source to generate embeddings for example based explanations.

func (GoogleCloudAiplatformV1ExplanationMetadataOutput) Outputs 

func (o GoogleCloudAiplatformV1ExplanationMetadataOutput) Outputs() pulumi.StringMapOutput

Map from output names to output metadata. For Vertex AI-provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed.

func (GoogleCloudAiplatformV1ExplanationMetadataOutput) ToGoogleCloudAiplatformV1ExplanationMetadataOutput 

func (o GoogleCloudAiplatformV1ExplanationMetadataOutput) ToGoogleCloudAiplatformV1ExplanationMetadataOutput() GoogleCloudAiplatformV1ExplanationMetadataOutput

func (GoogleCloudAiplatformV1ExplanationMetadataOutput) ToGoogleCloudAiplatformV1ExplanationMetadataOutputWithContext 

func (o GoogleCloudAiplatformV1ExplanationMetadataOutput) ToGoogleCloudAiplatformV1ExplanationMetadataOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationMetadataOutput

func (GoogleCloudAiplatformV1ExplanationMetadataOutput) ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutput 

func (o GoogleCloudAiplatformV1ExplanationMetadataOutput) ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutput() GoogleCloudAiplatformV1ExplanationMetadataPtrOutput

func (GoogleCloudAiplatformV1ExplanationMetadataOutput) ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExplanationMetadataOutput) ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationMetadataPtrOutput

type GoogleCloudAiplatformV1ExplanationMetadataPtrInput 

type GoogleCloudAiplatformV1ExplanationMetadataPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutput() GoogleCloudAiplatformV1ExplanationMetadataPtrOutput
	ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ExplanationMetadataPtrOutput
}

GoogleCloudAiplatformV1ExplanationMetadataPtrInput is an input type that accepts GoogleCloudAiplatformV1ExplanationMetadataArgs, GoogleCloudAiplatformV1ExplanationMetadataPtr and GoogleCloudAiplatformV1ExplanationMetadataPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ExplanationMetadataPtrInput` via: 

        GoogleCloudAiplatformV1ExplanationMetadataArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ExplanationMetadataPtr 

func GoogleCloudAiplatformV1ExplanationMetadataPtr(v *GoogleCloudAiplatformV1ExplanationMetadataArgs) GoogleCloudAiplatformV1ExplanationMetadataPtrInput

type GoogleCloudAiplatformV1ExplanationMetadataPtrOutput 

type GoogleCloudAiplatformV1ExplanationMetadataPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) Elem() GoogleCloudAiplatformV1ExplanationMetadataOutput

func (GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) FeatureAttributionsSchemaUri 

func (o GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) FeatureAttributionsSchemaUri() pulumi.StringPtrOutput

Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML tabular Models always have this field populated by Vertex AI. Note: The URI given on output may be different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) Inputs 

func (o GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) Inputs() pulumi.StringMapOutput

Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI-provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance.

func (GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) LatentSpaceSource 

func (o GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) LatentSpaceSource() pulumi.StringPtrOutput

Name of the source to generate embeddings for example based explanations.

func (GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) Outputs 

func (o GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) Outputs() pulumi.StringMapOutput

Map from output names to output metadata. For Vertex AI-provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed.

func (GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutput 

func (o GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutput() GoogleCloudAiplatformV1ExplanationMetadataPtrOutput

func (GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExplanationMetadataPtrOutput) ToGoogleCloudAiplatformV1ExplanationMetadataPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationMetadataPtrOutput

type GoogleCloudAiplatformV1ExplanationMetadataResponse 

type GoogleCloudAiplatformV1ExplanationMetadataResponse struct {
	// Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML tabular Models always have this field populated by Vertex AI. Note: The URI given on output may be different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	FeatureAttributionsSchemaUri string `pulumi:"featureAttributionsSchemaUri"`
	// Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI-provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance.
	Inputs map[string]string `pulumi:"inputs"`
	// Name of the source to generate embeddings for example based explanations.
	LatentSpaceSource string `pulumi:"latentSpaceSource"`
	// Map from output names to output metadata. For Vertex AI-provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed.
	Outputs map[string]string `pulumi:"outputs"`
}

Metadata describing the Model's input and output for explanation.

type GoogleCloudAiplatformV1ExplanationMetadataResponseOutput 

type GoogleCloudAiplatformV1ExplanationMetadataResponseOutput struct{ *pulumi.OutputState }

Metadata describing the Model's input and output for explanation.

func (GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) FeatureAttributionsSchemaUri 

func (o GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) FeatureAttributionsSchemaUri() pulumi.StringOutput

Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML tabular Models always have this field populated by Vertex AI. Note: The URI given on output may be different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) Inputs 

func (o GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) Inputs() pulumi.StringMapOutput

Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI-provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance.

func (GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) LatentSpaceSource 

func (o GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) LatentSpaceSource() pulumi.StringOutput

Name of the source to generate embeddings for example based explanations.

func (GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) Outputs 

func (o GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) Outputs() pulumi.StringMapOutput

Map from output names to output metadata. For Vertex AI-provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed.

func (GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) ToGoogleCloudAiplatformV1ExplanationMetadataResponseOutput 

func (o GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) ToGoogleCloudAiplatformV1ExplanationMetadataResponseOutput() GoogleCloudAiplatformV1ExplanationMetadataResponseOutput

func (GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) ToGoogleCloudAiplatformV1ExplanationMetadataResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ExplanationMetadataResponseOutput) ToGoogleCloudAiplatformV1ExplanationMetadataResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationMetadataResponseOutput

type GoogleCloudAiplatformV1ExplanationParameters 

type GoogleCloudAiplatformV1ExplanationParameters struct {
	// Example-based explanations that returns the nearest neighbors from the provided dataset.
	Examples *GoogleCloudAiplatformV1Examples `pulumi:"examples"`
	// An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365
	IntegratedGradientsAttribution *GoogleCloudAiplatformV1IntegratedGradientsAttribution `pulumi:"integratedGradientsAttribution"`
	// If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining. If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indices is populated, returns the argmax index of the outputs. Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes).
	OutputIndices []interface{} `pulumi:"outputIndices"`
	// An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265.
	SampledShapleyAttribution *GoogleCloudAiplatformV1SampledShapleyAttribution `pulumi:"sampledShapleyAttribution"`
	// If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs.
	TopK *int `pulumi:"topK"`
	// An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead.
	XraiAttribution *GoogleCloudAiplatformV1XraiAttribution `pulumi:"xraiAttribution"`
}

Parameters to configure explaining for Model's predictions.

type GoogleCloudAiplatformV1ExplanationParametersArgs 

type GoogleCloudAiplatformV1ExplanationParametersArgs struct {
	// Example-based explanations that returns the nearest neighbors from the provided dataset.
	Examples GoogleCloudAiplatformV1ExamplesPtrInput `pulumi:"examples"`
	// An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365
	IntegratedGradientsAttribution GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrInput `pulumi:"integratedGradientsAttribution"`
	// If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining. If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indices is populated, returns the argmax index of the outputs. Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes).
	OutputIndices pulumi.ArrayInput `pulumi:"outputIndices"`
	// An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265.
	SampledShapleyAttribution GoogleCloudAiplatformV1SampledShapleyAttributionPtrInput `pulumi:"sampledShapleyAttribution"`
	// If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs.
	TopK pulumi.IntPtrInput `pulumi:"topK"`
	// An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead.
	XraiAttribution GoogleCloudAiplatformV1XraiAttributionPtrInput `pulumi:"xraiAttribution"`
}

Parameters to configure explaining for Model's predictions.

func (GoogleCloudAiplatformV1ExplanationParametersArgs) ElementType 

func (GoogleCloudAiplatformV1ExplanationParametersArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExplanationParametersArgs) ToGoogleCloudAiplatformV1ExplanationParametersOutput 

func (i GoogleCloudAiplatformV1ExplanationParametersArgs) ToGoogleCloudAiplatformV1ExplanationParametersOutput() GoogleCloudAiplatformV1ExplanationParametersOutput

func (GoogleCloudAiplatformV1ExplanationParametersArgs) ToGoogleCloudAiplatformV1ExplanationParametersOutputWithContext 

func (i GoogleCloudAiplatformV1ExplanationParametersArgs) ToGoogleCloudAiplatformV1ExplanationParametersOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationParametersOutput

func (GoogleCloudAiplatformV1ExplanationParametersArgs) ToGoogleCloudAiplatformV1ExplanationParametersPtrOutput 

func (i GoogleCloudAiplatformV1ExplanationParametersArgs) ToGoogleCloudAiplatformV1ExplanationParametersPtrOutput() GoogleCloudAiplatformV1ExplanationParametersPtrOutput

func (GoogleCloudAiplatformV1ExplanationParametersArgs) ToGoogleCloudAiplatformV1ExplanationParametersPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ExplanationParametersArgs) ToGoogleCloudAiplatformV1ExplanationParametersPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationParametersPtrOutput

type GoogleCloudAiplatformV1ExplanationParametersInput 

type GoogleCloudAiplatformV1ExplanationParametersInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ExplanationParametersOutput() GoogleCloudAiplatformV1ExplanationParametersOutput
	ToGoogleCloudAiplatformV1ExplanationParametersOutputWithContext(context.Context) GoogleCloudAiplatformV1ExplanationParametersOutput
}

GoogleCloudAiplatformV1ExplanationParametersInput is an input type that accepts GoogleCloudAiplatformV1ExplanationParametersArgs and GoogleCloudAiplatformV1ExplanationParametersOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ExplanationParametersInput` via: 

GoogleCloudAiplatformV1ExplanationParametersArgs{...}

type GoogleCloudAiplatformV1ExplanationParametersOutput 

type GoogleCloudAiplatformV1ExplanationParametersOutput struct{ *pulumi.OutputState }

Parameters to configure explaining for Model's predictions.

func (GoogleCloudAiplatformV1ExplanationParametersOutput) ElementType 

func (GoogleCloudAiplatformV1ExplanationParametersOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExplanationParametersOutput) Examples 

func (o GoogleCloudAiplatformV1ExplanationParametersOutput) Examples() GoogleCloudAiplatformV1ExamplesPtrOutput

Example-based explanations that returns the nearest neighbors from the provided dataset.

func (GoogleCloudAiplatformV1ExplanationParametersOutput) IntegratedGradientsAttribution 

func (o GoogleCloudAiplatformV1ExplanationParametersOutput) IntegratedGradientsAttribution() GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput

An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

func (GoogleCloudAiplatformV1ExplanationParametersOutput) OutputIndices 

func (o GoogleCloudAiplatformV1ExplanationParametersOutput) OutputIndices() pulumi.ArrayOutput

If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining. If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indices is populated, returns the argmax index of the outputs. Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes).

func (GoogleCloudAiplatformV1ExplanationParametersOutput) SampledShapleyAttribution 

func (o GoogleCloudAiplatformV1ExplanationParametersOutput) SampledShapleyAttribution() GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265.

func (GoogleCloudAiplatformV1ExplanationParametersOutput) ToGoogleCloudAiplatformV1ExplanationParametersOutput 

func (o GoogleCloudAiplatformV1ExplanationParametersOutput) ToGoogleCloudAiplatformV1ExplanationParametersOutput() GoogleCloudAiplatformV1ExplanationParametersOutput

func (GoogleCloudAiplatformV1ExplanationParametersOutput) ToGoogleCloudAiplatformV1ExplanationParametersOutputWithContext 

func (o GoogleCloudAiplatformV1ExplanationParametersOutput) ToGoogleCloudAiplatformV1ExplanationParametersOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationParametersOutput

func (GoogleCloudAiplatformV1ExplanationParametersOutput) ToGoogleCloudAiplatformV1ExplanationParametersPtrOutput 

func (o GoogleCloudAiplatformV1ExplanationParametersOutput) ToGoogleCloudAiplatformV1ExplanationParametersPtrOutput() GoogleCloudAiplatformV1ExplanationParametersPtrOutput

func (GoogleCloudAiplatformV1ExplanationParametersOutput) ToGoogleCloudAiplatformV1ExplanationParametersPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExplanationParametersOutput) ToGoogleCloudAiplatformV1ExplanationParametersPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationParametersPtrOutput

func (GoogleCloudAiplatformV1ExplanationParametersOutput) TopK 

func (o GoogleCloudAiplatformV1ExplanationParametersOutput) TopK() pulumi.IntPtrOutput

If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs.

func (GoogleCloudAiplatformV1ExplanationParametersOutput) XraiAttribution 

func (o GoogleCloudAiplatformV1ExplanationParametersOutput) XraiAttribution() GoogleCloudAiplatformV1XraiAttributionPtrOutput

An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead.

type GoogleCloudAiplatformV1ExplanationParametersPtrInput 

type GoogleCloudAiplatformV1ExplanationParametersPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ExplanationParametersPtrOutput() GoogleCloudAiplatformV1ExplanationParametersPtrOutput
	ToGoogleCloudAiplatformV1ExplanationParametersPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ExplanationParametersPtrOutput
}

GoogleCloudAiplatformV1ExplanationParametersPtrInput is an input type that accepts GoogleCloudAiplatformV1ExplanationParametersArgs, GoogleCloudAiplatformV1ExplanationParametersPtr and GoogleCloudAiplatformV1ExplanationParametersPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ExplanationParametersPtrInput` via: 

        GoogleCloudAiplatformV1ExplanationParametersArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ExplanationParametersPtr 

func GoogleCloudAiplatformV1ExplanationParametersPtr(v *GoogleCloudAiplatformV1ExplanationParametersArgs) GoogleCloudAiplatformV1ExplanationParametersPtrInput

type GoogleCloudAiplatformV1ExplanationParametersPtrOutput 

type GoogleCloudAiplatformV1ExplanationParametersPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ExplanationParametersPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ExplanationParametersPtrOutput) Elem() GoogleCloudAiplatformV1ExplanationParametersOutput

func (GoogleCloudAiplatformV1ExplanationParametersPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ExplanationParametersPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExplanationParametersPtrOutput) Examples 

func (o GoogleCloudAiplatformV1ExplanationParametersPtrOutput) Examples() GoogleCloudAiplatformV1ExamplesPtrOutput

Example-based explanations that returns the nearest neighbors from the provided dataset.

func (GoogleCloudAiplatformV1ExplanationParametersPtrOutput) IntegratedGradientsAttribution 

func (o GoogleCloudAiplatformV1ExplanationParametersPtrOutput) IntegratedGradientsAttribution() GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput

An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

func (GoogleCloudAiplatformV1ExplanationParametersPtrOutput) OutputIndices 

func (o GoogleCloudAiplatformV1ExplanationParametersPtrOutput) OutputIndices() pulumi.ArrayOutput

If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining. If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indices is populated, returns the argmax index of the outputs. Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes).

func (GoogleCloudAiplatformV1ExplanationParametersPtrOutput) SampledShapleyAttribution 

func (o GoogleCloudAiplatformV1ExplanationParametersPtrOutput) SampledShapleyAttribution() GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265.

func (GoogleCloudAiplatformV1ExplanationParametersPtrOutput) ToGoogleCloudAiplatformV1ExplanationParametersPtrOutput 

func (o GoogleCloudAiplatformV1ExplanationParametersPtrOutput) ToGoogleCloudAiplatformV1ExplanationParametersPtrOutput() GoogleCloudAiplatformV1ExplanationParametersPtrOutput

func (GoogleCloudAiplatformV1ExplanationParametersPtrOutput) ToGoogleCloudAiplatformV1ExplanationParametersPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExplanationParametersPtrOutput) ToGoogleCloudAiplatformV1ExplanationParametersPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationParametersPtrOutput

func (GoogleCloudAiplatformV1ExplanationParametersPtrOutput) TopK 

func (o GoogleCloudAiplatformV1ExplanationParametersPtrOutput) TopK() pulumi.IntPtrOutput

If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs.

func (GoogleCloudAiplatformV1ExplanationParametersPtrOutput) XraiAttribution 

func (o GoogleCloudAiplatformV1ExplanationParametersPtrOutput) XraiAttribution() GoogleCloudAiplatformV1XraiAttributionPtrOutput

An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead.

type GoogleCloudAiplatformV1ExplanationParametersResponse 

type GoogleCloudAiplatformV1ExplanationParametersResponse struct {
	// Example-based explanations that returns the nearest neighbors from the provided dataset.
	Examples GoogleCloudAiplatformV1ExamplesResponse `pulumi:"examples"`
	// An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365
	IntegratedGradientsAttribution GoogleCloudAiplatformV1IntegratedGradientsAttributionResponse `pulumi:"integratedGradientsAttribution"`
	// If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining. If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indices is populated, returns the argmax index of the outputs. Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes).
	OutputIndices []interface{} `pulumi:"outputIndices"`
	// An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265.
	SampledShapleyAttribution GoogleCloudAiplatformV1SampledShapleyAttributionResponse `pulumi:"sampledShapleyAttribution"`
	// If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs.
	TopK int `pulumi:"topK"`
	// An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead.
	XraiAttribution GoogleCloudAiplatformV1XraiAttributionResponse `pulumi:"xraiAttribution"`
}

Parameters to configure explaining for Model's predictions.

type GoogleCloudAiplatformV1ExplanationParametersResponseOutput 

type GoogleCloudAiplatformV1ExplanationParametersResponseOutput struct{ *pulumi.OutputState }

Parameters to configure explaining for Model's predictions.

func (GoogleCloudAiplatformV1ExplanationParametersResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ExplanationParametersResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExplanationParametersResponseOutput) Examples 

func (o GoogleCloudAiplatformV1ExplanationParametersResponseOutput) Examples() GoogleCloudAiplatformV1ExamplesResponseOutput

Example-based explanations that returns the nearest neighbors from the provided dataset.

func (GoogleCloudAiplatformV1ExplanationParametersResponseOutput) IntegratedGradientsAttribution 

func (o GoogleCloudAiplatformV1ExplanationParametersResponseOutput) IntegratedGradientsAttribution() GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput

An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

func (GoogleCloudAiplatformV1ExplanationParametersResponseOutput) OutputIndices 

func (o GoogleCloudAiplatformV1ExplanationParametersResponseOutput) OutputIndices() pulumi.ArrayOutput

If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining. If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indices is populated, returns the argmax index of the outputs. Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes).

func (GoogleCloudAiplatformV1ExplanationParametersResponseOutput) SampledShapleyAttribution 

func (o GoogleCloudAiplatformV1ExplanationParametersResponseOutput) SampledShapleyAttribution() GoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265.

func (GoogleCloudAiplatformV1ExplanationParametersResponseOutput) ToGoogleCloudAiplatformV1ExplanationParametersResponseOutput 

func (o GoogleCloudAiplatformV1ExplanationParametersResponseOutput) ToGoogleCloudAiplatformV1ExplanationParametersResponseOutput() GoogleCloudAiplatformV1ExplanationParametersResponseOutput

func (GoogleCloudAiplatformV1ExplanationParametersResponseOutput) ToGoogleCloudAiplatformV1ExplanationParametersResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ExplanationParametersResponseOutput) ToGoogleCloudAiplatformV1ExplanationParametersResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationParametersResponseOutput

func (GoogleCloudAiplatformV1ExplanationParametersResponseOutput) TopK 

func (o GoogleCloudAiplatformV1ExplanationParametersResponseOutput) TopK() pulumi.IntOutput

If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs.

func (GoogleCloudAiplatformV1ExplanationParametersResponseOutput) XraiAttribution 

func (o GoogleCloudAiplatformV1ExplanationParametersResponseOutput) XraiAttribution() GoogleCloudAiplatformV1XraiAttributionResponseOutput

An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead.

type GoogleCloudAiplatformV1ExplanationSpec 

type GoogleCloudAiplatformV1ExplanationSpec struct {
	// Optional. Metadata describing the Model's input and output for explanation.
	Metadata *GoogleCloudAiplatformV1ExplanationMetadata `pulumi:"metadata"`
	// Parameters that configure explaining of the Model's predictions.
	Parameters GoogleCloudAiplatformV1ExplanationParameters `pulumi:"parameters"`
}

Specification of Model explanation.

type GoogleCloudAiplatformV1ExplanationSpecArgs 

type GoogleCloudAiplatformV1ExplanationSpecArgs struct {
	// Optional. Metadata describing the Model's input and output for explanation.
	Metadata GoogleCloudAiplatformV1ExplanationMetadataPtrInput `pulumi:"metadata"`
	// Parameters that configure explaining of the Model's predictions.
	Parameters GoogleCloudAiplatformV1ExplanationParametersInput `pulumi:"parameters"`
}

Specification of Model explanation.

func (GoogleCloudAiplatformV1ExplanationSpecArgs) ElementType 

func (GoogleCloudAiplatformV1ExplanationSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExplanationSpecArgs) ToGoogleCloudAiplatformV1ExplanationSpecOutput 

func (i GoogleCloudAiplatformV1ExplanationSpecArgs) ToGoogleCloudAiplatformV1ExplanationSpecOutput() GoogleCloudAiplatformV1ExplanationSpecOutput

func (GoogleCloudAiplatformV1ExplanationSpecArgs) ToGoogleCloudAiplatformV1ExplanationSpecOutputWithContext 

func (i GoogleCloudAiplatformV1ExplanationSpecArgs) ToGoogleCloudAiplatformV1ExplanationSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationSpecOutput

func (GoogleCloudAiplatformV1ExplanationSpecArgs) ToGoogleCloudAiplatformV1ExplanationSpecPtrOutput 

func (i GoogleCloudAiplatformV1ExplanationSpecArgs) ToGoogleCloudAiplatformV1ExplanationSpecPtrOutput() GoogleCloudAiplatformV1ExplanationSpecPtrOutput

func (GoogleCloudAiplatformV1ExplanationSpecArgs) ToGoogleCloudAiplatformV1ExplanationSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ExplanationSpecArgs) ToGoogleCloudAiplatformV1ExplanationSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationSpecPtrOutput

type GoogleCloudAiplatformV1ExplanationSpecInput 

type GoogleCloudAiplatformV1ExplanationSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ExplanationSpecOutput() GoogleCloudAiplatformV1ExplanationSpecOutput
	ToGoogleCloudAiplatformV1ExplanationSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1ExplanationSpecOutput
}

GoogleCloudAiplatformV1ExplanationSpecInput is an input type that accepts GoogleCloudAiplatformV1ExplanationSpecArgs and GoogleCloudAiplatformV1ExplanationSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ExplanationSpecInput` via: 

GoogleCloudAiplatformV1ExplanationSpecArgs{...}

type GoogleCloudAiplatformV1ExplanationSpecOutput 

type GoogleCloudAiplatformV1ExplanationSpecOutput struct{ *pulumi.OutputState }

Specification of Model explanation.

func (GoogleCloudAiplatformV1ExplanationSpecOutput) ElementType 

func (GoogleCloudAiplatformV1ExplanationSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExplanationSpecOutput) Metadata 

func (o GoogleCloudAiplatformV1ExplanationSpecOutput) Metadata() GoogleCloudAiplatformV1ExplanationMetadataPtrOutput

Optional. Metadata describing the Model's input and output for explanation.

func (GoogleCloudAiplatformV1ExplanationSpecOutput) Parameters 

func (o GoogleCloudAiplatformV1ExplanationSpecOutput) Parameters() GoogleCloudAiplatformV1ExplanationParametersOutput

Parameters that configure explaining of the Model's predictions.

func (GoogleCloudAiplatformV1ExplanationSpecOutput) ToGoogleCloudAiplatformV1ExplanationSpecOutput 

func (o GoogleCloudAiplatformV1ExplanationSpecOutput) ToGoogleCloudAiplatformV1ExplanationSpecOutput() GoogleCloudAiplatformV1ExplanationSpecOutput

func (GoogleCloudAiplatformV1ExplanationSpecOutput) ToGoogleCloudAiplatformV1ExplanationSpecOutputWithContext 

func (o GoogleCloudAiplatformV1ExplanationSpecOutput) ToGoogleCloudAiplatformV1ExplanationSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationSpecOutput

func (GoogleCloudAiplatformV1ExplanationSpecOutput) ToGoogleCloudAiplatformV1ExplanationSpecPtrOutput 

func (o GoogleCloudAiplatformV1ExplanationSpecOutput) ToGoogleCloudAiplatformV1ExplanationSpecPtrOutput() GoogleCloudAiplatformV1ExplanationSpecPtrOutput

func (GoogleCloudAiplatformV1ExplanationSpecOutput) ToGoogleCloudAiplatformV1ExplanationSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExplanationSpecOutput) ToGoogleCloudAiplatformV1ExplanationSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationSpecPtrOutput

type GoogleCloudAiplatformV1ExplanationSpecPtrInput 

type GoogleCloudAiplatformV1ExplanationSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ExplanationSpecPtrOutput() GoogleCloudAiplatformV1ExplanationSpecPtrOutput
	ToGoogleCloudAiplatformV1ExplanationSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ExplanationSpecPtrOutput
}

GoogleCloudAiplatformV1ExplanationSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1ExplanationSpecArgs, GoogleCloudAiplatformV1ExplanationSpecPtr and GoogleCloudAiplatformV1ExplanationSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ExplanationSpecPtrInput` via: 

        GoogleCloudAiplatformV1ExplanationSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ExplanationSpecPtr 

func GoogleCloudAiplatformV1ExplanationSpecPtr(v *GoogleCloudAiplatformV1ExplanationSpecArgs) GoogleCloudAiplatformV1ExplanationSpecPtrInput

type GoogleCloudAiplatformV1ExplanationSpecPtrOutput 

type GoogleCloudAiplatformV1ExplanationSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ExplanationSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ExplanationSpecPtrOutput) Elem() GoogleCloudAiplatformV1ExplanationSpecOutput

func (GoogleCloudAiplatformV1ExplanationSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ExplanationSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExplanationSpecPtrOutput) Metadata 

func (o GoogleCloudAiplatformV1ExplanationSpecPtrOutput) Metadata() GoogleCloudAiplatformV1ExplanationMetadataPtrOutput

Optional. Metadata describing the Model's input and output for explanation.

func (GoogleCloudAiplatformV1ExplanationSpecPtrOutput) Parameters 

func (o GoogleCloudAiplatformV1ExplanationSpecPtrOutput) Parameters() GoogleCloudAiplatformV1ExplanationParametersPtrOutput

Parameters that configure explaining of the Model's predictions.

func (GoogleCloudAiplatformV1ExplanationSpecPtrOutput) ToGoogleCloudAiplatformV1ExplanationSpecPtrOutput 

func (o GoogleCloudAiplatformV1ExplanationSpecPtrOutput) ToGoogleCloudAiplatformV1ExplanationSpecPtrOutput() GoogleCloudAiplatformV1ExplanationSpecPtrOutput

func (GoogleCloudAiplatformV1ExplanationSpecPtrOutput) ToGoogleCloudAiplatformV1ExplanationSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ExplanationSpecPtrOutput) ToGoogleCloudAiplatformV1ExplanationSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationSpecPtrOutput

type GoogleCloudAiplatformV1ExplanationSpecResponse 

type GoogleCloudAiplatformV1ExplanationSpecResponse struct {
	// Optional. Metadata describing the Model's input and output for explanation.
	Metadata GoogleCloudAiplatformV1ExplanationMetadataResponse `pulumi:"metadata"`
	// Parameters that configure explaining of the Model's predictions.
	Parameters GoogleCloudAiplatformV1ExplanationParametersResponse `pulumi:"parameters"`
}

Specification of Model explanation.

type GoogleCloudAiplatformV1ExplanationSpecResponseOutput 

type GoogleCloudAiplatformV1ExplanationSpecResponseOutput struct{ *pulumi.OutputState }

Specification of Model explanation.

func (GoogleCloudAiplatformV1ExplanationSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ExplanationSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ExplanationSpecResponseOutput) Metadata 

func (o GoogleCloudAiplatformV1ExplanationSpecResponseOutput) Metadata() GoogleCloudAiplatformV1ExplanationMetadataResponseOutput

Optional. Metadata describing the Model's input and output for explanation.

func (GoogleCloudAiplatformV1ExplanationSpecResponseOutput) Parameters 

func (o GoogleCloudAiplatformV1ExplanationSpecResponseOutput) Parameters() GoogleCloudAiplatformV1ExplanationParametersResponseOutput

Parameters that configure explaining of the Model's predictions.

func (GoogleCloudAiplatformV1ExplanationSpecResponseOutput) ToGoogleCloudAiplatformV1ExplanationSpecResponseOutput 

func (o GoogleCloudAiplatformV1ExplanationSpecResponseOutput) ToGoogleCloudAiplatformV1ExplanationSpecResponseOutput() GoogleCloudAiplatformV1ExplanationSpecResponseOutput

func (GoogleCloudAiplatformV1ExplanationSpecResponseOutput) ToGoogleCloudAiplatformV1ExplanationSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ExplanationSpecResponseOutput) ToGoogleCloudAiplatformV1ExplanationSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ExplanationSpecResponseOutput

type GoogleCloudAiplatformV1FeatureGroupBigQuery 

type GoogleCloudAiplatformV1FeatureGroupBigQuery struct {
	// Immutable. The BigQuery source URI that points to either a BigQuery Table or View.
	BigQuerySource GoogleCloudAiplatformV1BigQuerySource `pulumi:"bigQuerySource"`
	// Optional. Columns to construct entity_id / row keys. Currently only supports 1 entity_id_column. If not provided defaults to `entity_id`.
	EntityIdColumns []string `pulumi:"entityIdColumns"`
}

Input source type for BigQuery Tables and Views.

type GoogleCloudAiplatformV1FeatureGroupBigQueryArgs 

type GoogleCloudAiplatformV1FeatureGroupBigQueryArgs struct {
	// Immutable. The BigQuery source URI that points to either a BigQuery Table or View.
	BigQuerySource GoogleCloudAiplatformV1BigQuerySourceInput `pulumi:"bigQuerySource"`
	// Optional. Columns to construct entity_id / row keys. Currently only supports 1 entity_id_column. If not provided defaults to `entity_id`.
	EntityIdColumns pulumi.StringArrayInput `pulumi:"entityIdColumns"`
}

Input source type for BigQuery Tables and Views.

func (GoogleCloudAiplatformV1FeatureGroupBigQueryArgs) ElementType 

func (GoogleCloudAiplatformV1FeatureGroupBigQueryArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureGroupBigQueryArgs) ToGoogleCloudAiplatformV1FeatureGroupBigQueryOutput 

func (i GoogleCloudAiplatformV1FeatureGroupBigQueryArgs) ToGoogleCloudAiplatformV1FeatureGroupBigQueryOutput() GoogleCloudAiplatformV1FeatureGroupBigQueryOutput

func (GoogleCloudAiplatformV1FeatureGroupBigQueryArgs) ToGoogleCloudAiplatformV1FeatureGroupBigQueryOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureGroupBigQueryArgs) ToGoogleCloudAiplatformV1FeatureGroupBigQueryOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureGroupBigQueryOutput

func (GoogleCloudAiplatformV1FeatureGroupBigQueryArgs) ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput 

func (i GoogleCloudAiplatformV1FeatureGroupBigQueryArgs) ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput() GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput

func (GoogleCloudAiplatformV1FeatureGroupBigQueryArgs) ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureGroupBigQueryArgs) ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput

type GoogleCloudAiplatformV1FeatureGroupBigQueryInput 

type GoogleCloudAiplatformV1FeatureGroupBigQueryInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureGroupBigQueryOutput() GoogleCloudAiplatformV1FeatureGroupBigQueryOutput
	ToGoogleCloudAiplatformV1FeatureGroupBigQueryOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureGroupBigQueryOutput
}

GoogleCloudAiplatformV1FeatureGroupBigQueryInput is an input type that accepts GoogleCloudAiplatformV1FeatureGroupBigQueryArgs and GoogleCloudAiplatformV1FeatureGroupBigQueryOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureGroupBigQueryInput` via: 

GoogleCloudAiplatformV1FeatureGroupBigQueryArgs{...}

type GoogleCloudAiplatformV1FeatureGroupBigQueryOutput 

type GoogleCloudAiplatformV1FeatureGroupBigQueryOutput struct{ *pulumi.OutputState }

Input source type for BigQuery Tables and Views.

func (GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) BigQuerySource 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) BigQuerySource() GoogleCloudAiplatformV1BigQuerySourceOutput

Immutable. The BigQuery source URI that points to either a BigQuery Table or View.

func (GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) EntityIdColumns 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) EntityIdColumns() pulumi.StringArrayOutput

Optional. Columns to construct entity_id / row keys. Currently only supports 1 entity_id_column. If not provided defaults to `entity_id`.

func (GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryOutput 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryOutput() GoogleCloudAiplatformV1FeatureGroupBigQueryOutput

func (GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureGroupBigQueryOutput

func (GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput() GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput

func (GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput

type GoogleCloudAiplatformV1FeatureGroupBigQueryPtrInput 

type GoogleCloudAiplatformV1FeatureGroupBigQueryPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput() GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput
	ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput
}

GoogleCloudAiplatformV1FeatureGroupBigQueryPtrInput is an input type that accepts GoogleCloudAiplatformV1FeatureGroupBigQueryArgs, GoogleCloudAiplatformV1FeatureGroupBigQueryPtr and GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureGroupBigQueryPtrInput` via: 

        GoogleCloudAiplatformV1FeatureGroupBigQueryArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FeatureGroupBigQueryPtr 

func GoogleCloudAiplatformV1FeatureGroupBigQueryPtr(v *GoogleCloudAiplatformV1FeatureGroupBigQueryArgs) GoogleCloudAiplatformV1FeatureGroupBigQueryPtrInput

type GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput 

type GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput) BigQuerySource 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput) BigQuerySource() GoogleCloudAiplatformV1BigQuerySourcePtrOutput

Immutable. The BigQuery source URI that points to either a BigQuery Table or View.

func (GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput) Elem() GoogleCloudAiplatformV1FeatureGroupBigQueryOutput

func (GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput) EntityIdColumns 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput) EntityIdColumns() pulumi.StringArrayOutput

Optional. Columns to construct entity_id / row keys. Currently only supports 1 entity_id_column. If not provided defaults to `entity_id`.

func (GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput() GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput

func (GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureGroupBigQueryPtrOutput

type GoogleCloudAiplatformV1FeatureGroupBigQueryResponse 

type GoogleCloudAiplatformV1FeatureGroupBigQueryResponse struct {
	// Immutable. The BigQuery source URI that points to either a BigQuery Table or View.
	BigQuerySource GoogleCloudAiplatformV1BigQuerySourceResponse `pulumi:"bigQuerySource"`
	// Optional. Columns to construct entity_id / row keys. Currently only supports 1 entity_id_column. If not provided defaults to `entity_id`.
	EntityIdColumns []string `pulumi:"entityIdColumns"`
}

Input source type for BigQuery Tables and Views.

type GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput 

type GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput struct{ *pulumi.OutputState }

Input source type for BigQuery Tables and Views.

func (GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput) BigQuerySource 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput) BigQuerySource() GoogleCloudAiplatformV1BigQuerySourceResponseOutput

Immutable. The BigQuery source URI that points to either a BigQuery Table or View.

func (GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput) EntityIdColumns 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput) EntityIdColumns() pulumi.StringArrayOutput

Optional. Columns to construct entity_id / row keys. Currently only supports 1 entity_id_column. If not provided defaults to `entity_id`.

func (GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput() GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput

func (GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput) ToGoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput

type GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponse 

type GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponse struct {
	// The stats and anomalies generated at specific timestamp.
	FeatureStatsAnomaly GoogleCloudAiplatformV1FeatureStatsAnomalyResponse `pulumi:"featureStatsAnomaly"`
	// The objective for each stats.
	Objective string `pulumi:"objective"`
}

A list of historical SnapshotAnalysis or ImportFeaturesAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending.

type GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput 

type GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput

func (GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput) ToGoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput 

func (o GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput) ToGoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput() GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput

func (GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput) ToGoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput) ToGoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput

type GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput 

type GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput struct{ *pulumi.OutputState }

A list of historical SnapshotAnalysis or ImportFeaturesAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending.

func (GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput) FeatureStatsAnomaly 

func (o GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput) FeatureStatsAnomaly() GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput

The stats and anomalies generated at specific timestamp.

func (GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput) Objective 

func (o GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput) Objective() pulumi.StringOutput

The objective for each stats.

func (GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput) ToGoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput 

func (o GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput) ToGoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput() GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput

func (GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput) ToGoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput) ToGoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseOutput

type GoogleCloudAiplatformV1FeatureNoiseSigma 

type GoogleCloudAiplatformV1FeatureNoiseSigma struct {
	// Noise sigma per feature. No noise is added to features that are not set.
	NoiseSigma []GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature `pulumi:"noiseSigma"`
}

Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.

type GoogleCloudAiplatformV1FeatureNoiseSigmaArgs 

type GoogleCloudAiplatformV1FeatureNoiseSigmaArgs struct {
	// Noise sigma per feature. No noise is added to features that are not set.
	NoiseSigma GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayInput `pulumi:"noiseSigma"`
}

Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.

func (GoogleCloudAiplatformV1FeatureNoiseSigmaArgs) ElementType 

func (GoogleCloudAiplatformV1FeatureNoiseSigmaArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureNoiseSigmaArgs) ToGoogleCloudAiplatformV1FeatureNoiseSigmaOutput 

func (i GoogleCloudAiplatformV1FeatureNoiseSigmaArgs) ToGoogleCloudAiplatformV1FeatureNoiseSigmaOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaArgs) ToGoogleCloudAiplatformV1FeatureNoiseSigmaOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureNoiseSigmaArgs) ToGoogleCloudAiplatformV1FeatureNoiseSigmaOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaArgs) ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput 

func (i GoogleCloudAiplatformV1FeatureNoiseSigmaArgs) ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaArgs) ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureNoiseSigmaArgs) ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput

type GoogleCloudAiplatformV1FeatureNoiseSigmaInput 

type GoogleCloudAiplatformV1FeatureNoiseSigmaInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureNoiseSigmaOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaOutput
	ToGoogleCloudAiplatformV1FeatureNoiseSigmaOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaOutput
}

GoogleCloudAiplatformV1FeatureNoiseSigmaInput is an input type that accepts GoogleCloudAiplatformV1FeatureNoiseSigmaArgs and GoogleCloudAiplatformV1FeatureNoiseSigmaOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureNoiseSigmaInput` via: 

GoogleCloudAiplatformV1FeatureNoiseSigmaArgs{...}

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature 

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature struct {
	// The name of the input feature for which noise sigma is provided. The features are defined in explanation metadata inputs.
	Name *string `pulumi:"name"`
	// This represents the standard deviation of the Gaussian kernel that will be used to add noise to the feature prior to computing gradients. Similar to noise_sigma but represents the noise added to the current feature. Defaults to 0.1.
	Sigma *float64 `pulumi:"sigma"`
}

Noise sigma for a single feature.

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArgs 

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArgs struct {
	// The name of the input feature for which noise sigma is provided. The features are defined in explanation metadata inputs.
	Name pulumi.StringPtrInput `pulumi:"name"`
	// This represents the standard deviation of the Gaussian kernel that will be used to add noise to the feature prior to computing gradients. Similar to noise_sigma but represents the noise added to the current feature. Defaults to 0.1.
	Sigma pulumi.Float64PtrInput `pulumi:"sigma"`
}

Noise sigma for a single feature.

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArgs) ElementType 

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArgs) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput 

func (i GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArgs) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArgs) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArgs) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArray 

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArray []GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureInput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArray) ElementType 

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArray) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArray) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput 

func (i GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArray) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArray) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArray) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayInput 

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput
	ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput
}

GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayInput is an input type that accepts GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArray and GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayInput` via: 

GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArray{ GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArgs{...} }

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput 

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput) Index 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureInput 

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput
	ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput
}

GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureInput is an input type that accepts GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArgs and GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureInput` via: 

GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArgs{...}

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput 

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput struct{ *pulumi.OutputState }

Noise sigma for a single feature.

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput) Name 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput) Name() pulumi.StringPtrOutput

The name of the input feature for which noise sigma is provided. The features are defined in explanation metadata inputs.

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput) Sigma 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput) Sigma() pulumi.Float64PtrOutput

This represents the standard deviation of the Gaussian kernel that will be used to add noise to the feature prior to computing gradients. Similar to noise_sigma but represents the noise added to the current feature. Defaults to 0.1.

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureOutput

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponse 

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponse struct {
	// The name of the input feature for which noise sigma is provided. The features are defined in explanation metadata inputs.
	Name string `pulumi:"name"`
	// This represents the standard deviation of the Gaussian kernel that will be used to add noise to the feature prior to computing gradients. Similar to noise_sigma but represents the noise added to the current feature. Defaults to 0.1.
	Sigma float64 `pulumi:"sigma"`
}

Noise sigma for a single feature.

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput 

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput 

type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput struct{ *pulumi.OutputState }

Noise sigma for a single feature.

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput) Name 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput) Name() pulumi.StringOutput

The name of the input feature for which noise sigma is provided. The features are defined in explanation metadata inputs.

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput) Sigma 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput) Sigma() pulumi.Float64Output

This represents the standard deviation of the Gaussian kernel that will be used to add noise to the feature prior to computing gradients. Similar to noise_sigma but represents the noise added to the current feature. Defaults to 0.1.

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseOutput

type GoogleCloudAiplatformV1FeatureNoiseSigmaOutput 

type GoogleCloudAiplatformV1FeatureNoiseSigmaOutput struct{ *pulumi.OutputState }

Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.

func (GoogleCloudAiplatformV1FeatureNoiseSigmaOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureNoiseSigmaOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureNoiseSigmaOutput) NoiseSigma 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaOutput) NoiseSigma() GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput

Noise sigma per feature. No noise is added to features that are not set.

func (GoogleCloudAiplatformV1FeatureNoiseSigmaOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaOutput 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput

type GoogleCloudAiplatformV1FeatureNoiseSigmaPtrInput 

type GoogleCloudAiplatformV1FeatureNoiseSigmaPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput
	ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput
}

GoogleCloudAiplatformV1FeatureNoiseSigmaPtrInput is an input type that accepts GoogleCloudAiplatformV1FeatureNoiseSigmaArgs, GoogleCloudAiplatformV1FeatureNoiseSigmaPtr and GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureNoiseSigmaPtrInput` via: 

        GoogleCloudAiplatformV1FeatureNoiseSigmaArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FeatureNoiseSigmaPtr 

func GoogleCloudAiplatformV1FeatureNoiseSigmaPtr(v *GoogleCloudAiplatformV1FeatureNoiseSigmaArgs) GoogleCloudAiplatformV1FeatureNoiseSigmaPtrInput

type GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput 

type GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput) Elem() GoogleCloudAiplatformV1FeatureNoiseSigmaOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput) NoiseSigma 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput) NoiseSigma() GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureArrayOutput

Noise sigma per feature. No noise is added to features that are not set.

func (GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput

type GoogleCloudAiplatformV1FeatureNoiseSigmaResponse 

type GoogleCloudAiplatformV1FeatureNoiseSigmaResponse struct {
	// Noise sigma per feature. No noise is added to features that are not set.
	NoiseSigma []GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponse `pulumi:"noiseSigma"`
}

Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.

type GoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput 

type GoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput struct{ *pulumi.OutputState }

Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.

func (GoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput) NoiseSigma 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput) NoiseSigma() GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeatureResponseArrayOutput

Noise sigma per feature. No noise is added to features that are not set.

func (GoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput() GoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput

func (GoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput) ToGoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtable 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtable struct {
	// Autoscaling config applied to Bigtable Instance.
	AutoScaling GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScaling `pulumi:"autoScaling"`
}

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs struct {
	// Autoscaling config applied to Bigtable Instance.
	AutoScaling GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingInput `pulumi:"autoScaling"`
}

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs) ElementType 

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput 

func (i GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput 

func (i GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScaling 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScaling struct {
	// Optional. A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.
	CpuUtilizationTarget *int `pulumi:"cpuUtilizationTarget"`
	// The maximum number of nodes to scale up to. Must be greater than or equal to min_node_count, and less than or equal to 10 times of 'min_node_count'.
	MaxNodeCount int `pulumi:"maxNodeCount"`
	// The minimum number of nodes to scale down to. Must be greater than or equal to 1.
	MinNodeCount int `pulumi:"minNodeCount"`
}

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs struct {
	// Optional. A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.
	CpuUtilizationTarget pulumi.IntPtrInput `pulumi:"cpuUtilizationTarget"`
	// The maximum number of nodes to scale up to. Must be greater than or equal to min_node_count, and less than or equal to 10 times of 'min_node_count'.
	MaxNodeCount pulumi.IntInput `pulumi:"maxNodeCount"`
	// The minimum number of nodes to scale down to. Must be greater than or equal to 1.
	MinNodeCount pulumi.IntInput `pulumi:"minNodeCount"`
}

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs) ElementType 

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput 

func (i GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput 

func (i GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingInput 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput
	ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput
}

GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingInput is an input type that accepts GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs and GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingInput` via: 

GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs{...}

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) CpuUtilizationTarget 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) CpuUtilizationTarget() pulumi.IntPtrOutput

Optional. A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) MaxNodeCount 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) MaxNodeCount() pulumi.IntOutput

The maximum number of nodes to scale up to. Must be greater than or equal to min_node_count, and less than or equal to 10 times of 'min_node_count'.

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) MinNodeCount 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) MinNodeCount() pulumi.IntOutput

The minimum number of nodes to scale down to. Must be greater than or equal to 1.

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrInput 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput
	ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput
}

GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrInput is an input type that accepts GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs, GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtr and GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrInput` via: 

        GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtr 

func GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtr(v *GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingArgs) GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrInput

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) CpuUtilizationTarget 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) CpuUtilizationTarget() pulumi.IntPtrOutput

Optional. A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) Elem() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) MaxNodeCount 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) MaxNodeCount() pulumi.IntPtrOutput

The maximum number of nodes to scale up to. Must be greater than or equal to min_node_count, and less than or equal to 10 times of 'min_node_count'.

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) MinNodeCount 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) MinNodeCount() pulumi.IntPtrOutput

The minimum number of nodes to scale down to. Must be greater than or equal to 1.

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponse 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponse struct {
	// Optional. A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.
	CpuUtilizationTarget int `pulumi:"cpuUtilizationTarget"`
	// The maximum number of nodes to scale up to. Must be greater than or equal to min_node_count, and less than or equal to 10 times of 'min_node_count'.
	MaxNodeCount int `pulumi:"maxNodeCount"`
	// The minimum number of nodes to scale down to. Must be greater than or equal to 1.
	MinNodeCount int `pulumi:"minNodeCount"`
}

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput) CpuUtilizationTarget 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput) CpuUtilizationTarget() pulumi.IntOutput

Optional. A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput) MaxNodeCount 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput) MaxNodeCount() pulumi.IntOutput

The maximum number of nodes to scale up to. Must be greater than or equal to min_node_count, and less than or equal to 10 times of 'min_node_count'.

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput) MinNodeCount 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput) MinNodeCount() pulumi.IntOutput

The minimum number of nodes to scale down to. Must be greater than or equal to 1.

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableInput 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput
	ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput
}

GoogleCloudAiplatformV1FeatureOnlineStoreBigtableInput is an input type that accepts GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs and GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureOnlineStoreBigtableInput` via: 

GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs{...}

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput) AutoScaling 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput) AutoScaling() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingOutput

Autoscaling config applied to Bigtable Instance.

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrInput 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput
	ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput
}

GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrInput is an input type that accepts GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs, GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtr and GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrInput` via: 

        GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtr 

func GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtr(v *GoogleCloudAiplatformV1FeatureOnlineStoreBigtableArgs) GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrInput

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput) AutoScaling 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput) AutoScaling() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingPtrOutput

Autoscaling config applied to Bigtable Instance.

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput) Elem() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtablePtrOutput

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponse 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponse struct {
	// Autoscaling config applied to Bigtable Instance.
	AutoScaling GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponse `pulumi:"autoScaling"`
}

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput 

type GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput) AutoScaling 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput) AutoScaling() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableAutoScalingResponseOutput

Autoscaling config applied to Bigtable Instance.

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput

func (GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput) ToGoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput

type GoogleCloudAiplatformV1FeatureStatsAnomalyResponse 

type GoogleCloudAiplatformV1FeatureStatsAnomalyResponse struct {
	// This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
	AnomalyDetectionThreshold float64 `pulumi:"anomalyDetectionThreshold"`
	// Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
	AnomalyUri string `pulumi:"anomalyUri"`
	// Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.
	DistributionDeviation float64 `pulumi:"distributionDeviation"`
	// The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).
	EndTime string `pulumi:"endTime"`
	// Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.
	Score float64 `pulumi:"score"`
	// The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).
	StartTime string `pulumi:"startTime"`
	// Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message [tensorflow.metadata.v0.FeatureNameStatistics](https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/statistics.proto).
	StatsUri string `pulumi:"statsUri"`
}

Stats and Anomaly generated at specific timestamp for specific Feature. The start_time and end_time are used to define the time range of the dataset that current stats belongs to, e.g. prediction traffic is bucketed into prediction datasets by time window. If the Dataset is not defined by time window, start_time = end_time. Timestamp of the stats and anomalies always refers to end_time. Raw stats and anomalies are stored in stats_uri or anomaly_uri in the tensorflow defined protos. Field data_stats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display.

type GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput 

type GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput struct{ *pulumi.OutputState }

Stats and Anomaly generated at specific timestamp for specific Feature. The start_time and end_time are used to define the time range of the dataset that current stats belongs to, e.g. prediction traffic is bucketed into prediction datasets by time window. If the Dataset is not defined by time window, start_time = end_time. Timestamp of the stats and anomalies always refers to end_time. Raw stats and anomalies are stored in stats_uri or anomaly_uri in the tensorflow defined protos. Field data_stats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display.

func (GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) AnomalyDetectionThreshold 

func (o GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) AnomalyDetectionThreshold() pulumi.Float64Output

This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.

func (GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) AnomalyUri 

func (o GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) AnomalyUri() pulumi.StringOutput

Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).

func (GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) DistributionDeviation 

func (o GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) DistributionDeviation() pulumi.Float64Output

Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.

func (GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) EndTime 

func (o GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) EndTime() pulumi.StringOutput

The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).

func (GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) Score 

func (o GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) Score() pulumi.Float64Output

Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.

func (GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) StartTime 

func (o GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) StartTime() pulumi.StringOutput

The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).

func (GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) StatsUri 

func (o GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) StatsUri() pulumi.StringOutput

Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message [tensorflow.metadata.v0.FeatureNameStatistics](https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/statistics.proto).

func (GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) ToGoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput 

func (o GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) ToGoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput() GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput

func (GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) ToGoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput) ToGoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureStatsAnomalyResponseOutput

type GoogleCloudAiplatformV1FeatureViewBigQuerySource 

type GoogleCloudAiplatformV1FeatureViewBigQuerySource struct {
	// Columns to construct entity_id / row keys. Start by supporting 1 only.
	EntityIdColumns []string `pulumi:"entityIdColumns"`
	// The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig.
	Uri string `pulumi:"uri"`
}

type GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs 

type GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs struct {
	// Columns to construct entity_id / row keys. Start by supporting 1 only.
	EntityIdColumns pulumi.StringArrayInput `pulumi:"entityIdColumns"`
	// The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig.
	Uri pulumi.StringInput `pulumi:"uri"`
}

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs) ElementType 

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput 

func (i GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput() GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput 

func (i GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput() GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput

type GoogleCloudAiplatformV1FeatureViewBigQuerySourceInput 

type GoogleCloudAiplatformV1FeatureViewBigQuerySourceInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput() GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput
	ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput
}

GoogleCloudAiplatformV1FeatureViewBigQuerySourceInput is an input type that accepts GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs and GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureViewBigQuerySourceInput` via: 

GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs{...}

type GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput 

type GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) EntityIdColumns 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) EntityIdColumns() pulumi.StringArrayOutput

Columns to construct entity_id / row keys. Start by supporting 1 only.

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput() GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput() GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) Uri 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput) Uri() pulumi.StringOutput

The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig.

type GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrInput 

type GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput() GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput
	ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput
}

GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrInput is an input type that accepts GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs, GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtr and GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrInput` via: 

        GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtr 

func GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtr(v *GoogleCloudAiplatformV1FeatureViewBigQuerySourceArgs) GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrInput

type GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput 

type GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput) Elem() GoogleCloudAiplatformV1FeatureViewBigQuerySourceOutput

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput) EntityIdColumns 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput) EntityIdColumns() pulumi.StringArrayOutput

Columns to construct entity_id / row keys. Start by supporting 1 only.

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput() GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput) Uri 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourcePtrOutput) Uri() pulumi.StringPtrOutput

The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig.

type GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponse 

type GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponse struct {
	// Columns to construct entity_id / row keys. Start by supporting 1 only.
	EntityIdColumns []string `pulumi:"entityIdColumns"`
	// The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig.
	Uri string `pulumi:"uri"`
}

type GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput 

type GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput) EntityIdColumns 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput) EntityIdColumns() pulumi.StringArrayOutput

Columns to construct entity_id / row keys. Start by supporting 1 only.

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput() GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput) ToGoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput

func (GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput) Uri 

func (o GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput) Uri() pulumi.StringOutput

The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig.

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySource 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySource struct {
	// List of features that need to be synced to Online Store.
	FeatureGroups []GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroup `pulumi:"featureGroups"`
}

A Feature Registry source for features that need to be synced to Online Store.

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs struct {
	// List of features that need to be synced to Online Store.
	FeatureGroups GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayInput `pulumi:"featureGroups"`
}

A Feature Registry source for features that need to be synced to Online Store.

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs) ElementType 

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput 

func (i GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput 

func (i GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroup 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroup struct {
	// Identifier of the feature group.
	FeatureGroupId string `pulumi:"featureGroupId"`
	// Identifiers of features under the feature group.
	FeatureIds []string `pulumi:"featureIds"`
}

Features belonging to a single feature group that will be synced to Online Store.

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArgs 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArgs struct {
	// Identifier of the feature group.
	FeatureGroupId pulumi.StringInput `pulumi:"featureGroupId"`
	// Identifiers of features under the feature group.
	FeatureIds pulumi.StringArrayInput `pulumi:"featureIds"`
}

Features belonging to a single feature group that will be synced to Online Store.

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArgs) ElementType 

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArgs) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput 

func (i GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArgs) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArgs) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArgs) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArray 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArray []GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupInput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArray) ElementType 

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArray) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArray) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput 

func (i GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArray) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArray) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArray) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayInput 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput
	ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput
}

GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayInput is an input type that accepts GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArray and GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayInput` via: 

GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArray{ GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArgs{...} }

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput) Index 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupInput 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput
	ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput
}

GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupInput is an input type that accepts GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArgs and GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupInput` via: 

GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArgs{...}

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput struct{ *pulumi.OutputState }

Features belonging to a single feature group that will be synced to Online Store.

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput) FeatureGroupId 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput) FeatureGroupId() pulumi.StringOutput

Identifier of the feature group.

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput) FeatureIds 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput) FeatureIds() pulumi.StringArrayOutput

Identifiers of features under the feature group.

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupOutput

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponse 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponse struct {
	// Identifier of the feature group.
	FeatureGroupId string `pulumi:"featureGroupId"`
	// Identifiers of features under the feature group.
	FeatureIds []string `pulumi:"featureIds"`
}

Features belonging to a single feature group that will be synced to Online Store.

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput struct{ *pulumi.OutputState }

Features belonging to a single feature group that will be synced to Online Store.

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput) FeatureGroupId 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput) FeatureGroupId() pulumi.StringOutput

Identifier of the feature group.

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput) FeatureIds 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput) FeatureIds() pulumi.StringArrayOutput

Identifiers of features under the feature group.

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseOutput

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceInput 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput
	ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput
}

GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceInput is an input type that accepts GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs and GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceInput` via: 

GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs{...}

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput struct{ *pulumi.OutputState }

A Feature Registry source for features that need to be synced to Online Store.

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput) FeatureGroups 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput) FeatureGroups() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput

List of features that need to be synced to Online Store.

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrInput 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput
	ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput
}

GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrInput is an input type that accepts GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs, GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtr and GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrInput` via: 

        GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtr 

func GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtr(v *GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceArgs) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrInput

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput) Elem() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput) FeatureGroups 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput) FeatureGroups() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupArrayOutput

List of features that need to be synced to Online Store.

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourcePtrOutput

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponse 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponse struct {
	// List of features that need to be synced to Online Store.
	FeatureGroups []GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponse `pulumi:"featureGroups"`
}

A Feature Registry source for features that need to be synced to Online Store.

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput 

type GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput struct{ *pulumi.OutputState }

A Feature Registry source for features that need to be synced to Online Store.

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput) FeatureGroups 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput) FeatureGroups() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceFeatureGroupResponseArrayOutput

List of features that need to be synced to Online Store.

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput

func (GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput) ToGoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput

type GoogleCloudAiplatformV1FeatureViewSyncConfig 

type GoogleCloudAiplatformV1FeatureViewSyncConfig struct {
	// Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".
	Cron *string `pulumi:"cron"`
}

type GoogleCloudAiplatformV1FeatureViewSyncConfigArgs 

type GoogleCloudAiplatformV1FeatureViewSyncConfigArgs struct {
	// Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".
	Cron pulumi.StringPtrInput `pulumi:"cron"`
}

func (GoogleCloudAiplatformV1FeatureViewSyncConfigArgs) ElementType 

func (GoogleCloudAiplatformV1FeatureViewSyncConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewSyncConfigArgs) ToGoogleCloudAiplatformV1FeatureViewSyncConfigOutput 

func (i GoogleCloudAiplatformV1FeatureViewSyncConfigArgs) ToGoogleCloudAiplatformV1FeatureViewSyncConfigOutput() GoogleCloudAiplatformV1FeatureViewSyncConfigOutput

func (GoogleCloudAiplatformV1FeatureViewSyncConfigArgs) ToGoogleCloudAiplatformV1FeatureViewSyncConfigOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureViewSyncConfigArgs) ToGoogleCloudAiplatformV1FeatureViewSyncConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewSyncConfigOutput

func (GoogleCloudAiplatformV1FeatureViewSyncConfigArgs) ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput 

func (i GoogleCloudAiplatformV1FeatureViewSyncConfigArgs) ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput() GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput

func (GoogleCloudAiplatformV1FeatureViewSyncConfigArgs) ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1FeatureViewSyncConfigArgs) ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput

type GoogleCloudAiplatformV1FeatureViewSyncConfigInput 

type GoogleCloudAiplatformV1FeatureViewSyncConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureViewSyncConfigOutput() GoogleCloudAiplatformV1FeatureViewSyncConfigOutput
	ToGoogleCloudAiplatformV1FeatureViewSyncConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureViewSyncConfigOutput
}

GoogleCloudAiplatformV1FeatureViewSyncConfigInput is an input type that accepts GoogleCloudAiplatformV1FeatureViewSyncConfigArgs and GoogleCloudAiplatformV1FeatureViewSyncConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureViewSyncConfigInput` via: 

GoogleCloudAiplatformV1FeatureViewSyncConfigArgs{...}

type GoogleCloudAiplatformV1FeatureViewSyncConfigOutput 

type GoogleCloudAiplatformV1FeatureViewSyncConfigOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureViewSyncConfigOutput) Cron 

func (o GoogleCloudAiplatformV1FeatureViewSyncConfigOutput) Cron() pulumi.StringPtrOutput

Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".

func (GoogleCloudAiplatformV1FeatureViewSyncConfigOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureViewSyncConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewSyncConfigOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigOutput 

func (o GoogleCloudAiplatformV1FeatureViewSyncConfigOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigOutput() GoogleCloudAiplatformV1FeatureViewSyncConfigOutput

func (GoogleCloudAiplatformV1FeatureViewSyncConfigOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewSyncConfigOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewSyncConfigOutput

func (GoogleCloudAiplatformV1FeatureViewSyncConfigOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput 

func (o GoogleCloudAiplatformV1FeatureViewSyncConfigOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput() GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput

func (GoogleCloudAiplatformV1FeatureViewSyncConfigOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewSyncConfigOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput

type GoogleCloudAiplatformV1FeatureViewSyncConfigPtrInput 

type GoogleCloudAiplatformV1FeatureViewSyncConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput() GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput
	ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput
}

GoogleCloudAiplatformV1FeatureViewSyncConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1FeatureViewSyncConfigArgs, GoogleCloudAiplatformV1FeatureViewSyncConfigPtr and GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeatureViewSyncConfigPtrInput` via: 

        GoogleCloudAiplatformV1FeatureViewSyncConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FeatureViewSyncConfigPtr 

func GoogleCloudAiplatformV1FeatureViewSyncConfigPtr(v *GoogleCloudAiplatformV1FeatureViewSyncConfigArgs) GoogleCloudAiplatformV1FeatureViewSyncConfigPtrInput

type GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput 

type GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput) Cron 

func (o GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput) Cron() pulumi.StringPtrOutput

Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".

func (GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput) Elem() GoogleCloudAiplatformV1FeatureViewSyncConfigOutput

func (GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput 

func (o GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput() GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput

func (GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewSyncConfigPtrOutput

type GoogleCloudAiplatformV1FeatureViewSyncConfigResponse 

type GoogleCloudAiplatformV1FeatureViewSyncConfigResponse struct {
	// Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".
	Cron string `pulumi:"cron"`
}

type GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput 

type GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput) Cron 

func (o GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput) Cron() pulumi.StringOutput

Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".

func (GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput 

func (o GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput() GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput

func (GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput) ToGoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfig 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfig struct {
	// Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
	CategoricalThresholdConfig *GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig `pulumi:"categoricalThresholdConfig"`
	// The config for ImportFeatures Analysis Based Feature Monitoring.
	ImportFeaturesAnalysis *GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis `pulumi:"importFeaturesAnalysis"`
	// Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
	NumericalThresholdConfig *GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig `pulumi:"numericalThresholdConfig"`
	// The config for Snapshot Analysis Based Feature Monitoring.
	SnapshotAnalysis *GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis `pulumi:"snapshotAnalysis"`
}

Configuration of how features in Featurestore are monitored.

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs struct {
	// Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
	CategoricalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrInput `pulumi:"categoricalThresholdConfig"`
	// The config for ImportFeatures Analysis Based Feature Monitoring.
	ImportFeaturesAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrInput `pulumi:"importFeaturesAnalysis"`
	// Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
	NumericalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrInput `pulumi:"numericalThresholdConfig"`
	// The config for Snapshot Analysis Based Feature Monitoring.
	SnapshotAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrInput `pulumi:"snapshotAnalysis"`
}

Configuration of how features in Featurestore are monitored.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutputWithContext 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis struct {
	// The baseline used to do anomaly detection for the statistics generated by import features analysis.
	AnomalyDetectionBaseline *GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline `pulumi:"anomalyDetectionBaseline"`
	// Whether to enable / disable / inherite default hebavior for import features analysis.
	State *GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState `pulumi:"state"`
}

Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each Feature imported by every ImportFeatureValues operation.

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline string

The baseline used to do anomaly detection for the statistics generated by import features analysis.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutputWithContext 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutputWithContext 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToStringOutput 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineInput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput
	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput
}

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineArgs and GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineInput` via: 

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineArgs{...}

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrInput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput
	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput
}

func GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtr 

func GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtr(v string) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrInput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput) Elem() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs struct {
	// The baseline used to do anomaly detection for the statistics generated by import features analysis.
	AnomalyDetectionBaseline GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrInput `pulumi:"anomalyDetectionBaseline"`
	// Whether to enable / disable / inherite default hebavior for import features analysis.
	State GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrInput `pulumi:"state"`
}

Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each Feature imported by every ImportFeatureValues operation.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutputWithContext 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutputWithContext 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisInput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput
	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput
}

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs and GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisInput` via: 

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs{...}

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput struct{ *pulumi.OutputState }

Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each Feature imported by every ImportFeatureValues operation.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) AnomalyDetectionBaseline 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) AnomalyDetectionBaseline() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput

The baseline used to do anomaly detection for the statistics generated by import features analysis.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) State 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) State() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput

Whether to enable / disable / inherite default hebavior for import features analysis.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrInput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput
	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput
}

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtr and GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrInput` via: 

        GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtr 

func GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtr(v *GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrInput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput) AnomalyDetectionBaseline 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput) AnomalyDetectionBaseline() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePtrOutput

The baseline used to do anomaly detection for the statistics generated by import features analysis.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput) Elem() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput) State 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput) State() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput

Whether to enable / disable / inherite default hebavior for import features analysis.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse struct {
	// The baseline used to do anomaly detection for the statistics generated by import features analysis.
	AnomalyDetectionBaseline string `pulumi:"anomalyDetectionBaseline"`
	// Whether to enable / disable / inherite default hebavior for import features analysis.
	State string `pulumi:"state"`
}

Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each Feature imported by every ImportFeatureValues operation.

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput struct{ *pulumi.OutputState }

Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each Feature imported by every ImportFeatureValues operation.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput) AnomalyDetectionBaseline 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput) AnomalyDetectionBaseline() pulumi.StringOutput

The baseline used to do anomaly detection for the statistics generated by import features analysis.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput) State 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput) State() pulumi.StringOutput

Whether to enable / disable / inherite default hebavior for import features analysis.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState string

Whether to enable / disable / inherite default hebavior for import features analysis.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutputWithContext 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutputWithContext 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToStringOutput 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateInput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput
	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput
}

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateArgs and GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateInput` via: 

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateArgs{...}

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrInput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput
	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput
}

func GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtr 

func GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtr(v string) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrInput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput) Elem() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStatePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigInput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput
	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput
}

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs and GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreMonitoringConfigInput` via: 

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs{...}

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput struct{ *pulumi.OutputState }

Configuration of how features in Featurestore are monitored.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) CategoricalThresholdConfig 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) CategoricalThresholdConfig() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput

Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) ImportFeaturesAnalysis 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) ImportFeaturesAnalysis() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput

The config for ImportFeatures Analysis Based Feature Monitoring.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) NumericalThresholdConfig 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) NumericalThresholdConfig() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput

Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) SnapshotAnalysis 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) SnapshotAnalysis() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput

The config for Snapshot Analysis Based Feature Monitoring.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrInput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput
	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput
}

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtr and GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrInput` via: 

        GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtr 

func GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtr(v *GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrInput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) CategoricalThresholdConfig 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) CategoricalThresholdConfig() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput

Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) Elem() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) ImportFeaturesAnalysis 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) ImportFeaturesAnalysis() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisPtrOutput

The config for ImportFeatures Analysis Based Feature Monitoring.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) NumericalThresholdConfig 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) NumericalThresholdConfig() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput

Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) SnapshotAnalysis 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) SnapshotAnalysis() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput

The config for Snapshot Analysis Based Feature Monitoring.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponse 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponse struct {
	// Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
	CategoricalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse `pulumi:"categoricalThresholdConfig"`
	// The config for ImportFeatures Analysis Based Feature Monitoring.
	ImportFeaturesAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse `pulumi:"importFeaturesAnalysis"`
	// Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
	NumericalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse `pulumi:"numericalThresholdConfig"`
	// The config for Snapshot Analysis Based Feature Monitoring.
	SnapshotAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse `pulumi:"snapshotAnalysis"`
}

Configuration of how features in Featurestore are monitored.

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput struct{ *pulumi.OutputState }

Configuration of how features in Featurestore are monitored.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) CategoricalThresholdConfig 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) CategoricalThresholdConfig() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput

Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) ImportFeaturesAnalysis 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) ImportFeaturesAnalysis() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseOutput

The config for ImportFeatures Analysis Based Feature Monitoring.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) NumericalThresholdConfig 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) NumericalThresholdConfig() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput

Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) SnapshotAnalysis 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) SnapshotAnalysis() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput

The config for Snapshot Analysis Based Feature Monitoring.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis struct {
	// The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
	Disabled *bool `pulumi:"disabled"`
	// Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
	MonitoringIntervalDays *int `pulumi:"monitoringIntervalDays"`
	// Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
	StalenessDays *int `pulumi:"stalenessDays"`
}

Configuration of the Featurestore's Snapshot Analysis Based Monitoring. This type of analysis generates statistics for each Feature based on a snapshot of the latest feature value of each entities every monitoring_interval.

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs struct {
	// The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
	Disabled pulumi.BoolPtrInput `pulumi:"disabled"`
	// Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
	MonitoringIntervalDays pulumi.IntPtrInput `pulumi:"monitoringIntervalDays"`
	// Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
	StalenessDays pulumi.IntPtrInput `pulumi:"stalenessDays"`
}

Configuration of the Featurestore's Snapshot Analysis Based Monitoring. This type of analysis generates statistics for each Feature based on a snapshot of the latest feature value of each entities every monitoring_interval.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutputWithContext 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutputWithContext 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisInput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput
	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput
}

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs and GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisInput` via: 

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs{...}

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput struct{ *pulumi.OutputState }

Configuration of the Featurestore's Snapshot Analysis Based Monitoring. This type of analysis generates statistics for each Feature based on a snapshot of the latest feature value of each entities every monitoring_interval.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) Disabled 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) Disabled() pulumi.BoolPtrOutput

The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) MonitoringIntervalDays 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) MonitoringIntervalDays() pulumi.IntPtrOutput

Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) StalenessDays 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) StalenessDays() pulumi.IntPtrOutput

Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrInput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput
	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput
}

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtr and GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrInput` via: 

        GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtr 

func GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtr(v *GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrInput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) Disabled 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) Disabled() pulumi.BoolPtrOutput

The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) Elem() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) MonitoringIntervalDays 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) MonitoringIntervalDays() pulumi.IntPtrOutput

Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) StalenessDays 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) StalenessDays() pulumi.IntPtrOutput

Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse struct {
	// The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
	Disabled bool `pulumi:"disabled"`
	// Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
	MonitoringIntervalDays int `pulumi:"monitoringIntervalDays"`
	// Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
	StalenessDays int `pulumi:"stalenessDays"`
}

Configuration of the Featurestore's Snapshot Analysis Based Monitoring. This type of analysis generates statistics for each Feature based on a snapshot of the latest feature value of each entities every monitoring_interval.

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput struct{ *pulumi.OutputState }

Configuration of the Featurestore's Snapshot Analysis Based Monitoring. This type of analysis generates statistics for each Feature based on a snapshot of the latest feature value of each entities every monitoring_interval.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput) Disabled 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput) Disabled() pulumi.BoolOutput

The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput) MonitoringIntervalDays 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput) MonitoringIntervalDays() pulumi.IntOutput

Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput) StalenessDays 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput) StalenessDays() pulumi.IntOutput

Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig struct {
	// Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
	Value *float64 `pulumi:"value"`
}

The config for Featurestore Monitoring threshold.

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs struct {
	// Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
	Value pulumi.Float64PtrInput `pulumi:"value"`
}

The config for Featurestore Monitoring threshold.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutputWithContext 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigInput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput
	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput
}

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs and GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigInput` via: 

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs{...}

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput struct{ *pulumi.OutputState }

The config for Featurestore Monitoring threshold.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput) Value 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput) Value() pulumi.Float64PtrOutput

Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrInput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput
	ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput
}

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtr and GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrInput` via: 

        GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtr 

func GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtr(v *GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrInput

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput) Elem() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput) Value 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigPtrOutput) Value() pulumi.Float64PtrOutput

Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse struct {
	// Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
	Value float64 `pulumi:"value"`
}

The config for Featurestore Monitoring threshold.

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput 

type GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput struct{ *pulumi.OutputState }

The config for Featurestore Monitoring threshold.

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput

func (GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput) Value 

func (o GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseOutput) Value() pulumi.Float64Output

Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfig 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfig struct {
	// The number of nodes for the online store. The number of nodes doesn't scale automatically, but you can manually update the number of nodes. If set to 0, the featurestore will not have an online store and cannot be used for online serving.
	FixedNodeCount *int `pulumi:"fixedNodeCount"`
	// Online serving scaling configuration. Only one of `fixed_node_count` and `scaling` can be set. Setting one will reset the other.
	Scaling *GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScaling `pulumi:"scaling"`
}

OnlineServingConfig specifies the details for provisioning online serving resources.

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs struct {
	// The number of nodes for the online store. The number of nodes doesn't scale automatically, but you can manually update the number of nodes. If set to 0, the featurestore will not have an online store and cannot be used for online serving.
	FixedNodeCount pulumi.IntPtrInput `pulumi:"fixedNodeCount"`
	// Online serving scaling configuration. Only one of `fixed_node_count` and `scaling` can be set. Setting one will reset the other.
	Scaling GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrInput `pulumi:"scaling"`
}

OnlineServingConfig specifies the details for provisioning online serving resources.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput 

func (i GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutputWithContext 

func (i GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput 

func (i GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigInput 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput
	ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput
}

GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs and GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigInput` via: 

GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs{...}

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput struct{ *pulumi.OutputState }

OnlineServingConfig specifies the details for provisioning online serving resources.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) FixedNodeCount 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) FixedNodeCount() pulumi.IntPtrOutput

The number of nodes for the online store. The number of nodes doesn't scale automatically, but you can manually update the number of nodes. If set to 0, the featurestore will not have an online store and cannot be used for online serving.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) Scaling 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) Scaling() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput

Online serving scaling configuration. Only one of `fixed_node_count` and `scaling` can be set. Setting one will reset the other.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrInput 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput
	ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput
}

GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs, GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtr and GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrInput` via: 

        GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtr 

func GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtr(v *GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigArgs) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrInput

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput) Elem() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput) FixedNodeCount 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput) FixedNodeCount() pulumi.IntPtrOutput

The number of nodes for the online store. The number of nodes doesn't scale automatically, but you can manually update the number of nodes. If set to 0, the featurestore will not have an online store and cannot be used for online serving.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput) Scaling 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput) Scaling() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput

Online serving scaling configuration. Only one of `fixed_node_count` and `scaling` can be set. Setting one will reset the other.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigPtrOutput

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponse 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponse struct {
	// The number of nodes for the online store. The number of nodes doesn't scale automatically, but you can manually update the number of nodes. If set to 0, the featurestore will not have an online store and cannot be used for online serving.
	FixedNodeCount int `pulumi:"fixedNodeCount"`
	// Online serving scaling configuration. Only one of `fixed_node_count` and `scaling` can be set. Setting one will reset the other.
	Scaling GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponse `pulumi:"scaling"`
}

OnlineServingConfig specifies the details for provisioning online serving resources.

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput struct{ *pulumi.OutputState }

OnlineServingConfig specifies the details for provisioning online serving resources.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput) FixedNodeCount 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput) FixedNodeCount() pulumi.IntOutput

The number of nodes for the online store. The number of nodes doesn't scale automatically, but you can manually update the number of nodes. If set to 0, the featurestore will not have an online store and cannot be used for online serving.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput) Scaling 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput) Scaling() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput

Online serving scaling configuration. Only one of `fixed_node_count` and `scaling` can be set. Setting one will reset the other.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScaling 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScaling struct {
	// Optional. The cpu utilization that the Autoscaler should be trying to achieve. This number is on a scale from 0 (no utilization) to 100 (total utilization), and is limited between 10 and 80. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set or set to 0, default to 50.
	CpuUtilizationTarget *int `pulumi:"cpuUtilizationTarget"`
	// The maximum number of nodes to scale up to. Must be greater than min_node_count, and less than or equal to 10 times of 'min_node_count'.
	MaxNodeCount *int `pulumi:"maxNodeCount"`
	// The minimum number of nodes to scale down to. Must be greater than or equal to 1.
	MinNodeCount int `pulumi:"minNodeCount"`
}

Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling).

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs struct {
	// Optional. The cpu utilization that the Autoscaler should be trying to achieve. This number is on a scale from 0 (no utilization) to 100 (total utilization), and is limited between 10 and 80. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set or set to 0, default to 50.
	CpuUtilizationTarget pulumi.IntPtrInput `pulumi:"cpuUtilizationTarget"`
	// The maximum number of nodes to scale up to. Must be greater than min_node_count, and less than or equal to 10 times of 'min_node_count'.
	MaxNodeCount pulumi.IntPtrInput `pulumi:"maxNodeCount"`
	// The minimum number of nodes to scale down to. Must be greater than or equal to 1.
	MinNodeCount pulumi.IntInput `pulumi:"minNodeCount"`
}

Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling).

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput 

func (i GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutputWithContext 

func (i GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput 

func (i GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutputWithContext 

func (i GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingInput 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput
	ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput
}

GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs and GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingInput` via: 

GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs{...}

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput struct{ *pulumi.OutputState }

Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling).

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) CpuUtilizationTarget 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) CpuUtilizationTarget() pulumi.IntPtrOutput

Optional. The cpu utilization that the Autoscaler should be trying to achieve. This number is on a scale from 0 (no utilization) to 100 (total utilization), and is limited between 10 and 80. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set or set to 0, default to 50.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) MaxNodeCount 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) MaxNodeCount() pulumi.IntPtrOutput

The maximum number of nodes to scale up to. Must be greater than min_node_count, and less than or equal to 10 times of 'min_node_count'.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) MinNodeCount 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) MinNodeCount() pulumi.IntOutput

The minimum number of nodes to scale down to. Must be greater than or equal to 1.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrInput 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput
	ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput
}

GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrInput is an input type that accepts GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs, GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtr and GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrInput` via: 

        GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtr 

func GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtr(v *GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingArgs) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrInput

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) CpuUtilizationTarget 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) CpuUtilizationTarget() pulumi.IntPtrOutput

Optional. The cpu utilization that the Autoscaler should be trying to achieve. This number is on a scale from 0 (no utilization) to 100 (total utilization), and is limited between 10 and 80. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set or set to 0, default to 50.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) Elem 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) Elem() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) MaxNodeCount 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) MaxNodeCount() pulumi.IntPtrOutput

The maximum number of nodes to scale up to. Must be greater than min_node_count, and less than or equal to 10 times of 'min_node_count'.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) MinNodeCount 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) MinNodeCount() pulumi.IntPtrOutput

The minimum number of nodes to scale down to. Must be greater than or equal to 1.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingPtrOutput

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponse 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponse struct {
	// Optional. The cpu utilization that the Autoscaler should be trying to achieve. This number is on a scale from 0 (no utilization) to 100 (total utilization), and is limited between 10 and 80. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set or set to 0, default to 50.
	CpuUtilizationTarget int `pulumi:"cpuUtilizationTarget"`
	// The maximum number of nodes to scale up to. Must be greater than min_node_count, and less than or equal to 10 times of 'min_node_count'.
	MaxNodeCount int `pulumi:"maxNodeCount"`
	// The minimum number of nodes to scale down to. Must be greater than or equal to 1.
	MinNodeCount int `pulumi:"minNodeCount"`
}

Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling).

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput 

type GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput struct{ *pulumi.OutputState }

Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling).

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput) CpuUtilizationTarget 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput) CpuUtilizationTarget() pulumi.IntOutput

Optional. The cpu utilization that the Autoscaler should be trying to achieve. This number is on a scale from 0 (no utilization) to 100 (total utilization), and is limited between 10 and 80. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set or set to 0, default to 50.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput) MaxNodeCount 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput) MaxNodeCount() pulumi.IntOutput

The maximum number of nodes to scale up to. Must be greater than min_node_count, and less than or equal to 10 times of 'min_node_count'.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput) MinNodeCount 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput) MinNodeCount() pulumi.IntOutput

The minimum number of nodes to scale down to. Must be greater than or equal to 1.

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput

func (GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput) ToGoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigScalingResponseOutput

type GoogleCloudAiplatformV1FilterSplit 

type GoogleCloudAiplatformV1FilterSplit struct {
	// A filter on DataItems of the Dataset. DataItems that match this filter are used to test the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.
	TestFilter string `pulumi:"testFilter"`
	// A filter on DataItems of the Dataset. DataItems that match this filter are used to train the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.
	TrainingFilter string `pulumi:"trainingFilter"`
	// A filter on DataItems of the Dataset. DataItems that match this filter are used to validate the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.
	ValidationFilter string `pulumi:"validationFilter"`
}

Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign). Supported only for unstructured Datasets.

type GoogleCloudAiplatformV1FilterSplitArgs 

type GoogleCloudAiplatformV1FilterSplitArgs struct {
	// A filter on DataItems of the Dataset. DataItems that match this filter are used to test the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.
	TestFilter pulumi.StringInput `pulumi:"testFilter"`
	// A filter on DataItems of the Dataset. DataItems that match this filter are used to train the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.
	TrainingFilter pulumi.StringInput `pulumi:"trainingFilter"`
	// A filter on DataItems of the Dataset. DataItems that match this filter are used to validate the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.
	ValidationFilter pulumi.StringInput `pulumi:"validationFilter"`
}

Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign). Supported only for unstructured Datasets.

func (GoogleCloudAiplatformV1FilterSplitArgs) ElementType 

func (GoogleCloudAiplatformV1FilterSplitArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FilterSplitArgs) ToGoogleCloudAiplatformV1FilterSplitOutput 

func (i GoogleCloudAiplatformV1FilterSplitArgs) ToGoogleCloudAiplatformV1FilterSplitOutput() GoogleCloudAiplatformV1FilterSplitOutput

func (GoogleCloudAiplatformV1FilterSplitArgs) ToGoogleCloudAiplatformV1FilterSplitOutputWithContext 

func (i GoogleCloudAiplatformV1FilterSplitArgs) ToGoogleCloudAiplatformV1FilterSplitOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FilterSplitOutput

func (GoogleCloudAiplatformV1FilterSplitArgs) ToGoogleCloudAiplatformV1FilterSplitPtrOutput 

func (i GoogleCloudAiplatformV1FilterSplitArgs) ToGoogleCloudAiplatformV1FilterSplitPtrOutput() GoogleCloudAiplatformV1FilterSplitPtrOutput

func (GoogleCloudAiplatformV1FilterSplitArgs) ToGoogleCloudAiplatformV1FilterSplitPtrOutputWithContext 

func (i GoogleCloudAiplatformV1FilterSplitArgs) ToGoogleCloudAiplatformV1FilterSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FilterSplitPtrOutput

type GoogleCloudAiplatformV1FilterSplitInput 

type GoogleCloudAiplatformV1FilterSplitInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FilterSplitOutput() GoogleCloudAiplatformV1FilterSplitOutput
	ToGoogleCloudAiplatformV1FilterSplitOutputWithContext(context.Context) GoogleCloudAiplatformV1FilterSplitOutput
}

GoogleCloudAiplatformV1FilterSplitInput is an input type that accepts GoogleCloudAiplatformV1FilterSplitArgs and GoogleCloudAiplatformV1FilterSplitOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FilterSplitInput` via: 

GoogleCloudAiplatformV1FilterSplitArgs{...}

type GoogleCloudAiplatformV1FilterSplitOutput 

type GoogleCloudAiplatformV1FilterSplitOutput struct{ *pulumi.OutputState }

Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign). Supported only for unstructured Datasets.

func (GoogleCloudAiplatformV1FilterSplitOutput) ElementType 

func (GoogleCloudAiplatformV1FilterSplitOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FilterSplitOutput) TestFilter 

func (o GoogleCloudAiplatformV1FilterSplitOutput) TestFilter() pulumi.StringOutput

A filter on DataItems of the Dataset. DataItems that match this filter are used to test the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.

func (GoogleCloudAiplatformV1FilterSplitOutput) ToGoogleCloudAiplatformV1FilterSplitOutput 

func (o GoogleCloudAiplatformV1FilterSplitOutput) ToGoogleCloudAiplatformV1FilterSplitOutput() GoogleCloudAiplatformV1FilterSplitOutput

func (GoogleCloudAiplatformV1FilterSplitOutput) ToGoogleCloudAiplatformV1FilterSplitOutputWithContext 

func (o GoogleCloudAiplatformV1FilterSplitOutput) ToGoogleCloudAiplatformV1FilterSplitOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FilterSplitOutput

func (GoogleCloudAiplatformV1FilterSplitOutput) ToGoogleCloudAiplatformV1FilterSplitPtrOutput 

func (o GoogleCloudAiplatformV1FilterSplitOutput) ToGoogleCloudAiplatformV1FilterSplitPtrOutput() GoogleCloudAiplatformV1FilterSplitPtrOutput

func (GoogleCloudAiplatformV1FilterSplitOutput) ToGoogleCloudAiplatformV1FilterSplitPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FilterSplitOutput) ToGoogleCloudAiplatformV1FilterSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FilterSplitPtrOutput

func (GoogleCloudAiplatformV1FilterSplitOutput) TrainingFilter 

func (o GoogleCloudAiplatformV1FilterSplitOutput) TrainingFilter() pulumi.StringOutput

A filter on DataItems of the Dataset. DataItems that match this filter are used to train the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.

func (GoogleCloudAiplatformV1FilterSplitOutput) ValidationFilter 

func (o GoogleCloudAiplatformV1FilterSplitOutput) ValidationFilter() pulumi.StringOutput

A filter on DataItems of the Dataset. DataItems that match this filter are used to validate the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.

type GoogleCloudAiplatformV1FilterSplitPtrInput 

type GoogleCloudAiplatformV1FilterSplitPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FilterSplitPtrOutput() GoogleCloudAiplatformV1FilterSplitPtrOutput
	ToGoogleCloudAiplatformV1FilterSplitPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FilterSplitPtrOutput
}

GoogleCloudAiplatformV1FilterSplitPtrInput is an input type that accepts GoogleCloudAiplatformV1FilterSplitArgs, GoogleCloudAiplatformV1FilterSplitPtr and GoogleCloudAiplatformV1FilterSplitPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FilterSplitPtrInput` via: 

        GoogleCloudAiplatformV1FilterSplitArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FilterSplitPtr 

func GoogleCloudAiplatformV1FilterSplitPtr(v *GoogleCloudAiplatformV1FilterSplitArgs) GoogleCloudAiplatformV1FilterSplitPtrInput

type GoogleCloudAiplatformV1FilterSplitPtrOutput 

type GoogleCloudAiplatformV1FilterSplitPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FilterSplitPtrOutput) Elem 

func (o GoogleCloudAiplatformV1FilterSplitPtrOutput) Elem() GoogleCloudAiplatformV1FilterSplitOutput

func (GoogleCloudAiplatformV1FilterSplitPtrOutput) ElementType 

func (GoogleCloudAiplatformV1FilterSplitPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FilterSplitPtrOutput) TestFilter 

func (o GoogleCloudAiplatformV1FilterSplitPtrOutput) TestFilter() pulumi.StringPtrOutput

A filter on DataItems of the Dataset. DataItems that match this filter are used to test the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.

func (GoogleCloudAiplatformV1FilterSplitPtrOutput) ToGoogleCloudAiplatformV1FilterSplitPtrOutput 

func (o GoogleCloudAiplatformV1FilterSplitPtrOutput) ToGoogleCloudAiplatformV1FilterSplitPtrOutput() GoogleCloudAiplatformV1FilterSplitPtrOutput

func (GoogleCloudAiplatformV1FilterSplitPtrOutput) ToGoogleCloudAiplatformV1FilterSplitPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FilterSplitPtrOutput) ToGoogleCloudAiplatformV1FilterSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FilterSplitPtrOutput

func (GoogleCloudAiplatformV1FilterSplitPtrOutput) TrainingFilter 

func (o GoogleCloudAiplatformV1FilterSplitPtrOutput) TrainingFilter() pulumi.StringPtrOutput

A filter on DataItems of the Dataset. DataItems that match this filter are used to train the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.

func (GoogleCloudAiplatformV1FilterSplitPtrOutput) ValidationFilter 

func (o GoogleCloudAiplatformV1FilterSplitPtrOutput) ValidationFilter() pulumi.StringPtrOutput

A filter on DataItems of the Dataset. DataItems that match this filter are used to validate the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.

type GoogleCloudAiplatformV1FilterSplitResponse 

type GoogleCloudAiplatformV1FilterSplitResponse struct {
	// A filter on DataItems of the Dataset. DataItems that match this filter are used to test the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.
	TestFilter string `pulumi:"testFilter"`
	// A filter on DataItems of the Dataset. DataItems that match this filter are used to train the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.
	TrainingFilter string `pulumi:"trainingFilter"`
	// A filter on DataItems of the Dataset. DataItems that match this filter are used to validate the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.
	ValidationFilter string `pulumi:"validationFilter"`
}

Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign). Supported only for unstructured Datasets.

type GoogleCloudAiplatformV1FilterSplitResponseOutput 

type GoogleCloudAiplatformV1FilterSplitResponseOutput struct{ *pulumi.OutputState }

Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign). Supported only for unstructured Datasets.

func (GoogleCloudAiplatformV1FilterSplitResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FilterSplitResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FilterSplitResponseOutput) TestFilter 

func (o GoogleCloudAiplatformV1FilterSplitResponseOutput) TestFilter() pulumi.StringOutput

A filter on DataItems of the Dataset. DataItems that match this filter are used to test the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.

func (GoogleCloudAiplatformV1FilterSplitResponseOutput) ToGoogleCloudAiplatformV1FilterSplitResponseOutput 

func (o GoogleCloudAiplatformV1FilterSplitResponseOutput) ToGoogleCloudAiplatformV1FilterSplitResponseOutput() GoogleCloudAiplatformV1FilterSplitResponseOutput

func (GoogleCloudAiplatformV1FilterSplitResponseOutput) ToGoogleCloudAiplatformV1FilterSplitResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FilterSplitResponseOutput) ToGoogleCloudAiplatformV1FilterSplitResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FilterSplitResponseOutput

func (GoogleCloudAiplatformV1FilterSplitResponseOutput) TrainingFilter 

func (o GoogleCloudAiplatformV1FilterSplitResponseOutput) TrainingFilter() pulumi.StringOutput

A filter on DataItems of the Dataset. DataItems that match this filter are used to train the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.

func (GoogleCloudAiplatformV1FilterSplitResponseOutput) ValidationFilter 

func (o GoogleCloudAiplatformV1FilterSplitResponseOutput) ValidationFilter() pulumi.StringOutput

A filter on DataItems of the Dataset. DataItems that match this filter are used to validate the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order.

type GoogleCloudAiplatformV1FractionSplit 

type GoogleCloudAiplatformV1FractionSplit struct {
	// The fraction of the input data that is to be used to evaluate the Model.
	TestFraction *float64 `pulumi:"testFraction"`
	// The fraction of the input data that is to be used to train the Model.
	TrainingFraction *float64 `pulumi:"trainingFraction"`
	// The fraction of the input data that is to be used to validate the Model.
	ValidationFraction *float64 `pulumi:"validationFraction"`
}

Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test.

type GoogleCloudAiplatformV1FractionSplitArgs 

type GoogleCloudAiplatformV1FractionSplitArgs struct {
	// The fraction of the input data that is to be used to evaluate the Model.
	TestFraction pulumi.Float64PtrInput `pulumi:"testFraction"`
	// The fraction of the input data that is to be used to train the Model.
	TrainingFraction pulumi.Float64PtrInput `pulumi:"trainingFraction"`
	// The fraction of the input data that is to be used to validate the Model.
	ValidationFraction pulumi.Float64PtrInput `pulumi:"validationFraction"`
}

Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test.

func (GoogleCloudAiplatformV1FractionSplitArgs) ElementType 

func (GoogleCloudAiplatformV1FractionSplitArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FractionSplitArgs) ToGoogleCloudAiplatformV1FractionSplitOutput 

func (i GoogleCloudAiplatformV1FractionSplitArgs) ToGoogleCloudAiplatformV1FractionSplitOutput() GoogleCloudAiplatformV1FractionSplitOutput

func (GoogleCloudAiplatformV1FractionSplitArgs) ToGoogleCloudAiplatformV1FractionSplitOutputWithContext 

func (i GoogleCloudAiplatformV1FractionSplitArgs) ToGoogleCloudAiplatformV1FractionSplitOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FractionSplitOutput

func (GoogleCloudAiplatformV1FractionSplitArgs) ToGoogleCloudAiplatformV1FractionSplitPtrOutput 

func (i GoogleCloudAiplatformV1FractionSplitArgs) ToGoogleCloudAiplatformV1FractionSplitPtrOutput() GoogleCloudAiplatformV1FractionSplitPtrOutput

func (GoogleCloudAiplatformV1FractionSplitArgs) ToGoogleCloudAiplatformV1FractionSplitPtrOutputWithContext 

func (i GoogleCloudAiplatformV1FractionSplitArgs) ToGoogleCloudAiplatformV1FractionSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FractionSplitPtrOutput

type GoogleCloudAiplatformV1FractionSplitInput 

type GoogleCloudAiplatformV1FractionSplitInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FractionSplitOutput() GoogleCloudAiplatformV1FractionSplitOutput
	ToGoogleCloudAiplatformV1FractionSplitOutputWithContext(context.Context) GoogleCloudAiplatformV1FractionSplitOutput
}

GoogleCloudAiplatformV1FractionSplitInput is an input type that accepts GoogleCloudAiplatformV1FractionSplitArgs and GoogleCloudAiplatformV1FractionSplitOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FractionSplitInput` via: 

GoogleCloudAiplatformV1FractionSplitArgs{...}

type GoogleCloudAiplatformV1FractionSplitOutput 

type GoogleCloudAiplatformV1FractionSplitOutput struct{ *pulumi.OutputState }

Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test.

func (GoogleCloudAiplatformV1FractionSplitOutput) ElementType 

func (GoogleCloudAiplatformV1FractionSplitOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FractionSplitOutput) TestFraction 

func (o GoogleCloudAiplatformV1FractionSplitOutput) TestFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to evaluate the Model.

func (GoogleCloudAiplatformV1FractionSplitOutput) ToGoogleCloudAiplatformV1FractionSplitOutput 

func (o GoogleCloudAiplatformV1FractionSplitOutput) ToGoogleCloudAiplatformV1FractionSplitOutput() GoogleCloudAiplatformV1FractionSplitOutput

func (GoogleCloudAiplatformV1FractionSplitOutput) ToGoogleCloudAiplatformV1FractionSplitOutputWithContext 

func (o GoogleCloudAiplatformV1FractionSplitOutput) ToGoogleCloudAiplatformV1FractionSplitOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FractionSplitOutput

func (GoogleCloudAiplatformV1FractionSplitOutput) ToGoogleCloudAiplatformV1FractionSplitPtrOutput 

func (o GoogleCloudAiplatformV1FractionSplitOutput) ToGoogleCloudAiplatformV1FractionSplitPtrOutput() GoogleCloudAiplatformV1FractionSplitPtrOutput

func (GoogleCloudAiplatformV1FractionSplitOutput) ToGoogleCloudAiplatformV1FractionSplitPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FractionSplitOutput) ToGoogleCloudAiplatformV1FractionSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FractionSplitPtrOutput

func (GoogleCloudAiplatformV1FractionSplitOutput) TrainingFraction 

func (o GoogleCloudAiplatformV1FractionSplitOutput) TrainingFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to train the Model.

func (GoogleCloudAiplatformV1FractionSplitOutput) ValidationFraction 

func (o GoogleCloudAiplatformV1FractionSplitOutput) ValidationFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to validate the Model.

type GoogleCloudAiplatformV1FractionSplitPtrInput 

type GoogleCloudAiplatformV1FractionSplitPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1FractionSplitPtrOutput() GoogleCloudAiplatformV1FractionSplitPtrOutput
	ToGoogleCloudAiplatformV1FractionSplitPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1FractionSplitPtrOutput
}

GoogleCloudAiplatformV1FractionSplitPtrInput is an input type that accepts GoogleCloudAiplatformV1FractionSplitArgs, GoogleCloudAiplatformV1FractionSplitPtr and GoogleCloudAiplatformV1FractionSplitPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1FractionSplitPtrInput` via: 

        GoogleCloudAiplatformV1FractionSplitArgs{...}

or:

        nil

func GoogleCloudAiplatformV1FractionSplitPtr 

func GoogleCloudAiplatformV1FractionSplitPtr(v *GoogleCloudAiplatformV1FractionSplitArgs) GoogleCloudAiplatformV1FractionSplitPtrInput

type GoogleCloudAiplatformV1FractionSplitPtrOutput 

type GoogleCloudAiplatformV1FractionSplitPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1FractionSplitPtrOutput) Elem 

func (o GoogleCloudAiplatformV1FractionSplitPtrOutput) Elem() GoogleCloudAiplatformV1FractionSplitOutput

func (GoogleCloudAiplatformV1FractionSplitPtrOutput) ElementType 

func (GoogleCloudAiplatformV1FractionSplitPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FractionSplitPtrOutput) TestFraction 

func (o GoogleCloudAiplatformV1FractionSplitPtrOutput) TestFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to evaluate the Model.

func (GoogleCloudAiplatformV1FractionSplitPtrOutput) ToGoogleCloudAiplatformV1FractionSplitPtrOutput 

func (o GoogleCloudAiplatformV1FractionSplitPtrOutput) ToGoogleCloudAiplatformV1FractionSplitPtrOutput() GoogleCloudAiplatformV1FractionSplitPtrOutput

func (GoogleCloudAiplatformV1FractionSplitPtrOutput) ToGoogleCloudAiplatformV1FractionSplitPtrOutputWithContext 

func (o GoogleCloudAiplatformV1FractionSplitPtrOutput) ToGoogleCloudAiplatformV1FractionSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FractionSplitPtrOutput

func (GoogleCloudAiplatformV1FractionSplitPtrOutput) TrainingFraction 

func (o GoogleCloudAiplatformV1FractionSplitPtrOutput) TrainingFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to train the Model.

func (GoogleCloudAiplatformV1FractionSplitPtrOutput) ValidationFraction 

func (o GoogleCloudAiplatformV1FractionSplitPtrOutput) ValidationFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to validate the Model.

type GoogleCloudAiplatformV1FractionSplitResponse 

type GoogleCloudAiplatformV1FractionSplitResponse struct {
	// The fraction of the input data that is to be used to evaluate the Model.
	TestFraction float64 `pulumi:"testFraction"`
	// The fraction of the input data that is to be used to train the Model.
	TrainingFraction float64 `pulumi:"trainingFraction"`
	// The fraction of the input data that is to be used to validate the Model.
	ValidationFraction float64 `pulumi:"validationFraction"`
}

Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test.

type GoogleCloudAiplatformV1FractionSplitResponseOutput 

type GoogleCloudAiplatformV1FractionSplitResponseOutput struct{ *pulumi.OutputState }

Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test.

func (GoogleCloudAiplatformV1FractionSplitResponseOutput) ElementType 

func (GoogleCloudAiplatformV1FractionSplitResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1FractionSplitResponseOutput) TestFraction 

func (o GoogleCloudAiplatformV1FractionSplitResponseOutput) TestFraction() pulumi.Float64Output

The fraction of the input data that is to be used to evaluate the Model.

func (GoogleCloudAiplatformV1FractionSplitResponseOutput) ToGoogleCloudAiplatformV1FractionSplitResponseOutput 

func (o GoogleCloudAiplatformV1FractionSplitResponseOutput) ToGoogleCloudAiplatformV1FractionSplitResponseOutput() GoogleCloudAiplatformV1FractionSplitResponseOutput

func (GoogleCloudAiplatformV1FractionSplitResponseOutput) ToGoogleCloudAiplatformV1FractionSplitResponseOutputWithContext 

func (o GoogleCloudAiplatformV1FractionSplitResponseOutput) ToGoogleCloudAiplatformV1FractionSplitResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1FractionSplitResponseOutput

func (GoogleCloudAiplatformV1FractionSplitResponseOutput) TrainingFraction 

func (o GoogleCloudAiplatformV1FractionSplitResponseOutput) TrainingFraction() pulumi.Float64Output

The fraction of the input data that is to be used to train the Model.

func (GoogleCloudAiplatformV1FractionSplitResponseOutput) ValidationFraction 

func (o GoogleCloudAiplatformV1FractionSplitResponseOutput) ValidationFraction() pulumi.Float64Output

The fraction of the input data that is to be used to validate the Model.

type GoogleCloudAiplatformV1GcsDestination 

type GoogleCloudAiplatformV1GcsDestination struct {
	// Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
	OutputUriPrefix string `pulumi:"outputUriPrefix"`
}

The Google Cloud Storage location where the output is to be written to.

type GoogleCloudAiplatformV1GcsDestinationArgs 

type GoogleCloudAiplatformV1GcsDestinationArgs struct {
	// Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
	OutputUriPrefix pulumi.StringInput `pulumi:"outputUriPrefix"`
}

The Google Cloud Storage location where the output is to be written to.

func (GoogleCloudAiplatformV1GcsDestinationArgs) ElementType 

func (GoogleCloudAiplatformV1GcsDestinationArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1GcsDestinationArgs) ToGoogleCloudAiplatformV1GcsDestinationOutput 

func (i GoogleCloudAiplatformV1GcsDestinationArgs) ToGoogleCloudAiplatformV1GcsDestinationOutput() GoogleCloudAiplatformV1GcsDestinationOutput

func (GoogleCloudAiplatformV1GcsDestinationArgs) ToGoogleCloudAiplatformV1GcsDestinationOutputWithContext 

func (i GoogleCloudAiplatformV1GcsDestinationArgs) ToGoogleCloudAiplatformV1GcsDestinationOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1GcsDestinationOutput

func (GoogleCloudAiplatformV1GcsDestinationArgs) ToGoogleCloudAiplatformV1GcsDestinationPtrOutput 

func (i GoogleCloudAiplatformV1GcsDestinationArgs) ToGoogleCloudAiplatformV1GcsDestinationPtrOutput() GoogleCloudAiplatformV1GcsDestinationPtrOutput

func (GoogleCloudAiplatformV1GcsDestinationArgs) ToGoogleCloudAiplatformV1GcsDestinationPtrOutputWithContext 

func (i GoogleCloudAiplatformV1GcsDestinationArgs) ToGoogleCloudAiplatformV1GcsDestinationPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1GcsDestinationPtrOutput

type GoogleCloudAiplatformV1GcsDestinationInput 

type GoogleCloudAiplatformV1GcsDestinationInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1GcsDestinationOutput() GoogleCloudAiplatformV1GcsDestinationOutput
	ToGoogleCloudAiplatformV1GcsDestinationOutputWithContext(context.Context) GoogleCloudAiplatformV1GcsDestinationOutput
}

GoogleCloudAiplatformV1GcsDestinationInput is an input type that accepts GoogleCloudAiplatformV1GcsDestinationArgs and GoogleCloudAiplatformV1GcsDestinationOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1GcsDestinationInput` via: 

GoogleCloudAiplatformV1GcsDestinationArgs{...}

type GoogleCloudAiplatformV1GcsDestinationOutput 

type GoogleCloudAiplatformV1GcsDestinationOutput struct{ *pulumi.OutputState }

The Google Cloud Storage location where the output is to be written to.

func (GoogleCloudAiplatformV1GcsDestinationOutput) ElementType 

func (GoogleCloudAiplatformV1GcsDestinationOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1GcsDestinationOutput) OutputUriPrefix 

func (o GoogleCloudAiplatformV1GcsDestinationOutput) OutputUriPrefix() pulumi.StringOutput

Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.

func (GoogleCloudAiplatformV1GcsDestinationOutput) ToGoogleCloudAiplatformV1GcsDestinationOutput 

func (o GoogleCloudAiplatformV1GcsDestinationOutput) ToGoogleCloudAiplatformV1GcsDestinationOutput() GoogleCloudAiplatformV1GcsDestinationOutput

func (GoogleCloudAiplatformV1GcsDestinationOutput) ToGoogleCloudAiplatformV1GcsDestinationOutputWithContext 

func (o GoogleCloudAiplatformV1GcsDestinationOutput) ToGoogleCloudAiplatformV1GcsDestinationOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1GcsDestinationOutput

func (GoogleCloudAiplatformV1GcsDestinationOutput) ToGoogleCloudAiplatformV1GcsDestinationPtrOutput 

func (o GoogleCloudAiplatformV1GcsDestinationOutput) ToGoogleCloudAiplatformV1GcsDestinationPtrOutput() GoogleCloudAiplatformV1GcsDestinationPtrOutput

func (GoogleCloudAiplatformV1GcsDestinationOutput) ToGoogleCloudAiplatformV1GcsDestinationPtrOutputWithContext 

func (o GoogleCloudAiplatformV1GcsDestinationOutput) ToGoogleCloudAiplatformV1GcsDestinationPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1GcsDestinationPtrOutput

type GoogleCloudAiplatformV1GcsDestinationPtrInput 

type GoogleCloudAiplatformV1GcsDestinationPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1GcsDestinationPtrOutput() GoogleCloudAiplatformV1GcsDestinationPtrOutput
	ToGoogleCloudAiplatformV1GcsDestinationPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1GcsDestinationPtrOutput
}

GoogleCloudAiplatformV1GcsDestinationPtrInput is an input type that accepts GoogleCloudAiplatformV1GcsDestinationArgs, GoogleCloudAiplatformV1GcsDestinationPtr and GoogleCloudAiplatformV1GcsDestinationPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1GcsDestinationPtrInput` via: 

        GoogleCloudAiplatformV1GcsDestinationArgs{...}

or:

        nil

func GoogleCloudAiplatformV1GcsDestinationPtr 

func GoogleCloudAiplatformV1GcsDestinationPtr(v *GoogleCloudAiplatformV1GcsDestinationArgs) GoogleCloudAiplatformV1GcsDestinationPtrInput

type GoogleCloudAiplatformV1GcsDestinationPtrOutput 

type GoogleCloudAiplatformV1GcsDestinationPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1GcsDestinationPtrOutput) Elem 

func (o GoogleCloudAiplatformV1GcsDestinationPtrOutput) Elem() GoogleCloudAiplatformV1GcsDestinationOutput

func (GoogleCloudAiplatformV1GcsDestinationPtrOutput) ElementType 

func (GoogleCloudAiplatformV1GcsDestinationPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1GcsDestinationPtrOutput) OutputUriPrefix 

func (o GoogleCloudAiplatformV1GcsDestinationPtrOutput) OutputUriPrefix() pulumi.StringPtrOutput

Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.

func (GoogleCloudAiplatformV1GcsDestinationPtrOutput) ToGoogleCloudAiplatformV1GcsDestinationPtrOutput 

func (o GoogleCloudAiplatformV1GcsDestinationPtrOutput) ToGoogleCloudAiplatformV1GcsDestinationPtrOutput() GoogleCloudAiplatformV1GcsDestinationPtrOutput

func (GoogleCloudAiplatformV1GcsDestinationPtrOutput) ToGoogleCloudAiplatformV1GcsDestinationPtrOutputWithContext 

func (o GoogleCloudAiplatformV1GcsDestinationPtrOutput) ToGoogleCloudAiplatformV1GcsDestinationPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1GcsDestinationPtrOutput

type GoogleCloudAiplatformV1GcsDestinationResponse 

type GoogleCloudAiplatformV1GcsDestinationResponse struct {
	// Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.
	OutputUriPrefix string `pulumi:"outputUriPrefix"`
}

The Google Cloud Storage location where the output is to be written to.

type GoogleCloudAiplatformV1GcsDestinationResponseOutput 

type GoogleCloudAiplatformV1GcsDestinationResponseOutput struct{ *pulumi.OutputState }

The Google Cloud Storage location where the output is to be written to.

func (GoogleCloudAiplatformV1GcsDestinationResponseOutput) ElementType 

func (GoogleCloudAiplatformV1GcsDestinationResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1GcsDestinationResponseOutput) OutputUriPrefix 

func (o GoogleCloudAiplatformV1GcsDestinationResponseOutput) OutputUriPrefix() pulumi.StringOutput

Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist.

func (GoogleCloudAiplatformV1GcsDestinationResponseOutput) ToGoogleCloudAiplatformV1GcsDestinationResponseOutput 

func (o GoogleCloudAiplatformV1GcsDestinationResponseOutput) ToGoogleCloudAiplatformV1GcsDestinationResponseOutput() GoogleCloudAiplatformV1GcsDestinationResponseOutput

func (GoogleCloudAiplatformV1GcsDestinationResponseOutput) ToGoogleCloudAiplatformV1GcsDestinationResponseOutputWithContext 

func (o GoogleCloudAiplatformV1GcsDestinationResponseOutput) ToGoogleCloudAiplatformV1GcsDestinationResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1GcsDestinationResponseOutput

type GoogleCloudAiplatformV1GcsSource 

type GoogleCloudAiplatformV1GcsSource struct {
	// Google Cloud Storage URI(-s) to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames.
	Uris []string `pulumi:"uris"`
}

The Google Cloud Storage location for the input content.

type GoogleCloudAiplatformV1GcsSourceArgs 

type GoogleCloudAiplatformV1GcsSourceArgs struct {
	// Google Cloud Storage URI(-s) to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames.
	Uris pulumi.StringArrayInput `pulumi:"uris"`
}

The Google Cloud Storage location for the input content.

func (GoogleCloudAiplatformV1GcsSourceArgs) ElementType 

func (GoogleCloudAiplatformV1GcsSourceArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1GcsSourceArgs) ToGoogleCloudAiplatformV1GcsSourceOutput 

func (i GoogleCloudAiplatformV1GcsSourceArgs) ToGoogleCloudAiplatformV1GcsSourceOutput() GoogleCloudAiplatformV1GcsSourceOutput

func (GoogleCloudAiplatformV1GcsSourceArgs) ToGoogleCloudAiplatformV1GcsSourceOutputWithContext 

func (i GoogleCloudAiplatformV1GcsSourceArgs) ToGoogleCloudAiplatformV1GcsSourceOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1GcsSourceOutput

func (GoogleCloudAiplatformV1GcsSourceArgs) ToGoogleCloudAiplatformV1GcsSourcePtrOutput 

func (i GoogleCloudAiplatformV1GcsSourceArgs) ToGoogleCloudAiplatformV1GcsSourcePtrOutput() GoogleCloudAiplatformV1GcsSourcePtrOutput

func (GoogleCloudAiplatformV1GcsSourceArgs) ToGoogleCloudAiplatformV1GcsSourcePtrOutputWithContext 

func (i GoogleCloudAiplatformV1GcsSourceArgs) ToGoogleCloudAiplatformV1GcsSourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1GcsSourcePtrOutput

type GoogleCloudAiplatformV1GcsSourceInput 

type GoogleCloudAiplatformV1GcsSourceInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1GcsSourceOutput() GoogleCloudAiplatformV1GcsSourceOutput
	ToGoogleCloudAiplatformV1GcsSourceOutputWithContext(context.Context) GoogleCloudAiplatformV1GcsSourceOutput
}

GoogleCloudAiplatformV1GcsSourceInput is an input type that accepts GoogleCloudAiplatformV1GcsSourceArgs and GoogleCloudAiplatformV1GcsSourceOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1GcsSourceInput` via: 

GoogleCloudAiplatformV1GcsSourceArgs{...}

type GoogleCloudAiplatformV1GcsSourceOutput 

type GoogleCloudAiplatformV1GcsSourceOutput struct{ *pulumi.OutputState }

The Google Cloud Storage location for the input content.

func (GoogleCloudAiplatformV1GcsSourceOutput) ElementType 

func (GoogleCloudAiplatformV1GcsSourceOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1GcsSourceOutput) ToGoogleCloudAiplatformV1GcsSourceOutput 

func (o GoogleCloudAiplatformV1GcsSourceOutput) ToGoogleCloudAiplatformV1GcsSourceOutput() GoogleCloudAiplatformV1GcsSourceOutput

func (GoogleCloudAiplatformV1GcsSourceOutput) ToGoogleCloudAiplatformV1GcsSourceOutputWithContext 

func (o GoogleCloudAiplatformV1GcsSourceOutput) ToGoogleCloudAiplatformV1GcsSourceOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1GcsSourceOutput

func (GoogleCloudAiplatformV1GcsSourceOutput) ToGoogleCloudAiplatformV1GcsSourcePtrOutput 

func (o GoogleCloudAiplatformV1GcsSourceOutput) ToGoogleCloudAiplatformV1GcsSourcePtrOutput() GoogleCloudAiplatformV1GcsSourcePtrOutput

func (GoogleCloudAiplatformV1GcsSourceOutput) ToGoogleCloudAiplatformV1GcsSourcePtrOutputWithContext 

func (o GoogleCloudAiplatformV1GcsSourceOutput) ToGoogleCloudAiplatformV1GcsSourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1GcsSourcePtrOutput

func (GoogleCloudAiplatformV1GcsSourceOutput) Uris 

func (o GoogleCloudAiplatformV1GcsSourceOutput) Uris() pulumi.StringArrayOutput

Google Cloud Storage URI(-s) to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames.

type GoogleCloudAiplatformV1GcsSourcePtrInput 

type GoogleCloudAiplatformV1GcsSourcePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1GcsSourcePtrOutput() GoogleCloudAiplatformV1GcsSourcePtrOutput
	ToGoogleCloudAiplatformV1GcsSourcePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1GcsSourcePtrOutput
}

GoogleCloudAiplatformV1GcsSourcePtrInput is an input type that accepts GoogleCloudAiplatformV1GcsSourceArgs, GoogleCloudAiplatformV1GcsSourcePtr and GoogleCloudAiplatformV1GcsSourcePtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1GcsSourcePtrInput` via: 

        GoogleCloudAiplatformV1GcsSourceArgs{...}

or:

        nil

func GoogleCloudAiplatformV1GcsSourcePtr 

func GoogleCloudAiplatformV1GcsSourcePtr(v *GoogleCloudAiplatformV1GcsSourceArgs) GoogleCloudAiplatformV1GcsSourcePtrInput

type GoogleCloudAiplatformV1GcsSourcePtrOutput 

type GoogleCloudAiplatformV1GcsSourcePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1GcsSourcePtrOutput) Elem 

func (o GoogleCloudAiplatformV1GcsSourcePtrOutput) Elem() GoogleCloudAiplatformV1GcsSourceOutput

func (GoogleCloudAiplatformV1GcsSourcePtrOutput) ElementType 

func (GoogleCloudAiplatformV1GcsSourcePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1GcsSourcePtrOutput) ToGoogleCloudAiplatformV1GcsSourcePtrOutput 

func (o GoogleCloudAiplatformV1GcsSourcePtrOutput) ToGoogleCloudAiplatformV1GcsSourcePtrOutput() GoogleCloudAiplatformV1GcsSourcePtrOutput

func (GoogleCloudAiplatformV1GcsSourcePtrOutput) ToGoogleCloudAiplatformV1GcsSourcePtrOutputWithContext 

func (o GoogleCloudAiplatformV1GcsSourcePtrOutput) ToGoogleCloudAiplatformV1GcsSourcePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1GcsSourcePtrOutput

func (GoogleCloudAiplatformV1GcsSourcePtrOutput) Uris 

func (o GoogleCloudAiplatformV1GcsSourcePtrOutput) Uris() pulumi.StringArrayOutput

Google Cloud Storage URI(-s) to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames.

type GoogleCloudAiplatformV1GcsSourceResponse 

type GoogleCloudAiplatformV1GcsSourceResponse struct {
	// Google Cloud Storage URI(-s) to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames.
	Uris []string `pulumi:"uris"`
}

The Google Cloud Storage location for the input content.

type GoogleCloudAiplatformV1GcsSourceResponseOutput 

type GoogleCloudAiplatformV1GcsSourceResponseOutput struct{ *pulumi.OutputState }

The Google Cloud Storage location for the input content.

func (GoogleCloudAiplatformV1GcsSourceResponseOutput) ElementType 

func (GoogleCloudAiplatformV1GcsSourceResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1GcsSourceResponseOutput) ToGoogleCloudAiplatformV1GcsSourceResponseOutput 

func (o GoogleCloudAiplatformV1GcsSourceResponseOutput) ToGoogleCloudAiplatformV1GcsSourceResponseOutput() GoogleCloudAiplatformV1GcsSourceResponseOutput

func (GoogleCloudAiplatformV1GcsSourceResponseOutput) ToGoogleCloudAiplatformV1GcsSourceResponseOutputWithContext 

func (o GoogleCloudAiplatformV1GcsSourceResponseOutput) ToGoogleCloudAiplatformV1GcsSourceResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1GcsSourceResponseOutput

func (GoogleCloudAiplatformV1GcsSourceResponseOutput) Uris 

func (o GoogleCloudAiplatformV1GcsSourceResponseOutput) Uris() pulumi.StringArrayOutput

Google Cloud Storage URI(-s) to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/gsutil/addlhelp/WildcardNames.

type GoogleCloudAiplatformV1IndexPrivateEndpointsResponse 

type GoogleCloudAiplatformV1IndexPrivateEndpointsResponse struct {
	// The ip address used to send match gRPC requests.
	MatchGrpcAddress string `pulumi:"matchGrpcAddress"`
	// The name of the service attachment resource. Populated if private service connect is enabled.
	ServiceAttachment string `pulumi:"serviceAttachment"`
}

IndexPrivateEndpoints proto is used to provide paths for users to send requests via private endpoints (e.g. private service access, private service connect). To send request via private service access, use match_grpc_address. To send request via private service connect, use service_attachment.

type GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput 

type GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput struct{ *pulumi.OutputState }

IndexPrivateEndpoints proto is used to provide paths for users to send requests via private endpoints (e.g. private service access, private service connect). To send request via private service access, use match_grpc_address. To send request via private service connect, use service_attachment.

func (GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput) ElementType 

func (GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput) MatchGrpcAddress 

func (o GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput) MatchGrpcAddress() pulumi.StringOutput

The ip address used to send match gRPC requests.

func (GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput) ServiceAttachment 

func (o GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput) ServiceAttachment() pulumi.StringOutput

The name of the service attachment resource. Populated if private service connect is enabled.

func (GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput) ToGoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput 

func (o GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput) ToGoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput() GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput

func (GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput) ToGoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutputWithContext 

func (o GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput) ToGoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1IndexPrivateEndpointsResponseOutput

type GoogleCloudAiplatformV1IndexStatsResponse 

type GoogleCloudAiplatformV1IndexStatsResponse struct {
	// The number of shards in the Index.
	ShardsCount int `pulumi:"shardsCount"`
	// The number of vectors in the Index.
	VectorsCount string `pulumi:"vectorsCount"`
}

Stats of the Index.

type GoogleCloudAiplatformV1IndexStatsResponseOutput 

type GoogleCloudAiplatformV1IndexStatsResponseOutput struct{ *pulumi.OutputState }

Stats of the Index.

func (GoogleCloudAiplatformV1IndexStatsResponseOutput) ElementType 

func (GoogleCloudAiplatformV1IndexStatsResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1IndexStatsResponseOutput) ShardsCount 

func (o GoogleCloudAiplatformV1IndexStatsResponseOutput) ShardsCount() pulumi.IntOutput

The number of shards in the Index.

func (GoogleCloudAiplatformV1IndexStatsResponseOutput) ToGoogleCloudAiplatformV1IndexStatsResponseOutput 

func (o GoogleCloudAiplatformV1IndexStatsResponseOutput) ToGoogleCloudAiplatformV1IndexStatsResponseOutput() GoogleCloudAiplatformV1IndexStatsResponseOutput

func (GoogleCloudAiplatformV1IndexStatsResponseOutput) ToGoogleCloudAiplatformV1IndexStatsResponseOutputWithContext 

func (o GoogleCloudAiplatformV1IndexStatsResponseOutput) ToGoogleCloudAiplatformV1IndexStatsResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1IndexStatsResponseOutput

func (GoogleCloudAiplatformV1IndexStatsResponseOutput) VectorsCount 

func (o GoogleCloudAiplatformV1IndexStatsResponseOutput) VectorsCount() pulumi.StringOutput

The number of vectors in the Index.

type GoogleCloudAiplatformV1InputDataConfig 

type GoogleCloudAiplatformV1InputDataConfig struct {
	// Applicable only to custom training with Datasets that have DataItems and Annotations. Cloud Storage URI that points to a YAML file describing the annotation schema. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/ , note that the chosen schema must be consistent with metadata of the Dataset specified by dataset_id. Only Annotations that both match this schema and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri.
	AnnotationSchemaUri *string `pulumi:"annotationSchemaUri"`
	// Applicable only to Datasets that have DataItems and Annotations. A filter on Annotations of the Dataset. Only Annotations that both match this filter and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on (for the auto-assigned that role is decided by Vertex AI). A filter with same syntax as the one used in ListAnnotations may be used, but note here it filters across all Annotations of the Dataset, and not just within a single DataItem.
	AnnotationsFilter *string `pulumi:"annotationsFilter"`
	// Only applicable to custom training with tabular Dataset with BigQuery source. The BigQuery project location where the training data is to be written to. In the given project a new dataset is created with name `dataset___` where timestamp is in YYYY_MM_DDThh_mm_ss_sssZ format. All training input data is written into that dataset. In the dataset three tables are created, `training`, `validation` and `test`. * AIP_DATA_FORMAT = "bigquery". * AIP_TRAINING_DATA_URI = "bigquery_destination.dataset___.training" * AIP_VALIDATION_DATA_URI = "bigquery_destination.dataset___.validation" * AIP_TEST_DATA_URI = "bigquery_destination.dataset___.test"
	BigqueryDestination *GoogleCloudAiplatformV1BigQueryDestination `pulumi:"bigqueryDestination"`
	// The ID of the Dataset in the same Project and Location which data will be used to train the Model. The Dataset must use schema compatible with Model being trained, and what is compatible should be described in the used TrainingPipeline's training_task_definition. For tabular Datasets, all their data is exported to training, to pick and choose from.
	DatasetId string `pulumi:"datasetId"`
	// Split based on the provided filters for each set.
	FilterSplit *GoogleCloudAiplatformV1FilterSplit `pulumi:"filterSplit"`
	// Split based on fractions defining the size of each set.
	FractionSplit *GoogleCloudAiplatformV1FractionSplit `pulumi:"fractionSplit"`
	// The Cloud Storage location where the training data is to be written to. In the given directory a new directory is created with name: `dataset---` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All training input data is written into that directory. The Vertex AI environment variables representing Cloud Storage data URIs are represented in the Cloud Storage wildcard format to support sharded data. e.g.: "gs://.../training-*.jsonl" * AIP_DATA_FORMAT = "jsonl" for non-tabular data, "csv" for tabular data * AIP_TRAINING_DATA_URI = "gcs_destination/dataset---/training-*.${AIP_DATA_FORMAT}" * AIP_VALIDATION_DATA_URI = "gcs_destination/dataset---/validation-*.${AIP_DATA_FORMAT}" * AIP_TEST_DATA_URI = "gcs_destination/dataset---/test-*.${AIP_DATA_FORMAT}"
	GcsDestination *GoogleCloudAiplatformV1GcsDestination `pulumi:"gcsDestination"`
	// Whether to persist the ML use assignment to data item system labels.
	PersistMlUseAssignment *bool `pulumi:"persistMlUseAssignment"`
	// Supported only for tabular Datasets. Split based on a predefined key.
	PredefinedSplit *GoogleCloudAiplatformV1PredefinedSplit `pulumi:"predefinedSplit"`
	// Only applicable to Datasets that have SavedQueries. The ID of a SavedQuery (annotation set) under the Dataset specified by dataset_id used for filtering Annotations for training. Only Annotations that are associated with this SavedQuery are used in respectively training. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both saved_query_id and annotations_filter. Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.
	SavedQueryId *string `pulumi:"savedQueryId"`
	// Supported only for tabular Datasets. Split based on the distribution of the specified column.
	StratifiedSplit *GoogleCloudAiplatformV1StratifiedSplit `pulumi:"stratifiedSplit"`
	// Supported only for tabular Datasets. Split based on the timestamp of the input data pieces.
	TimestampSplit *GoogleCloudAiplatformV1TimestampSplit `pulumi:"timestampSplit"`
}

Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.

type GoogleCloudAiplatformV1InputDataConfigArgs 

type GoogleCloudAiplatformV1InputDataConfigArgs struct {
	// Applicable only to custom training with Datasets that have DataItems and Annotations. Cloud Storage URI that points to a YAML file describing the annotation schema. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/ , note that the chosen schema must be consistent with metadata of the Dataset specified by dataset_id. Only Annotations that both match this schema and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri.
	AnnotationSchemaUri pulumi.StringPtrInput `pulumi:"annotationSchemaUri"`
	// Applicable only to Datasets that have DataItems and Annotations. A filter on Annotations of the Dataset. Only Annotations that both match this filter and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on (for the auto-assigned that role is decided by Vertex AI). A filter with same syntax as the one used in ListAnnotations may be used, but note here it filters across all Annotations of the Dataset, and not just within a single DataItem.
	AnnotationsFilter pulumi.StringPtrInput `pulumi:"annotationsFilter"`
	// Only applicable to custom training with tabular Dataset with BigQuery source. The BigQuery project location where the training data is to be written to. In the given project a new dataset is created with name `dataset___` where timestamp is in YYYY_MM_DDThh_mm_ss_sssZ format. All training input data is written into that dataset. In the dataset three tables are created, `training`, `validation` and `test`. * AIP_DATA_FORMAT = "bigquery". * AIP_TRAINING_DATA_URI = "bigquery_destination.dataset___.training" * AIP_VALIDATION_DATA_URI = "bigquery_destination.dataset___.validation" * AIP_TEST_DATA_URI = "bigquery_destination.dataset___.test"
	BigqueryDestination GoogleCloudAiplatformV1BigQueryDestinationPtrInput `pulumi:"bigqueryDestination"`
	// The ID of the Dataset in the same Project and Location which data will be used to train the Model. The Dataset must use schema compatible with Model being trained, and what is compatible should be described in the used TrainingPipeline's training_task_definition. For tabular Datasets, all their data is exported to training, to pick and choose from.
	DatasetId pulumi.StringInput `pulumi:"datasetId"`
	// Split based on the provided filters for each set.
	FilterSplit GoogleCloudAiplatformV1FilterSplitPtrInput `pulumi:"filterSplit"`
	// Split based on fractions defining the size of each set.
	FractionSplit GoogleCloudAiplatformV1FractionSplitPtrInput `pulumi:"fractionSplit"`
	// The Cloud Storage location where the training data is to be written to. In the given directory a new directory is created with name: `dataset---` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All training input data is written into that directory. The Vertex AI environment variables representing Cloud Storage data URIs are represented in the Cloud Storage wildcard format to support sharded data. e.g.: "gs://.../training-*.jsonl" * AIP_DATA_FORMAT = "jsonl" for non-tabular data, "csv" for tabular data * AIP_TRAINING_DATA_URI = "gcs_destination/dataset---/training-*.${AIP_DATA_FORMAT}" * AIP_VALIDATION_DATA_URI = "gcs_destination/dataset---/validation-*.${AIP_DATA_FORMAT}" * AIP_TEST_DATA_URI = "gcs_destination/dataset---/test-*.${AIP_DATA_FORMAT}"
	GcsDestination GoogleCloudAiplatformV1GcsDestinationPtrInput `pulumi:"gcsDestination"`
	// Whether to persist the ML use assignment to data item system labels.
	PersistMlUseAssignment pulumi.BoolPtrInput `pulumi:"persistMlUseAssignment"`
	// Supported only for tabular Datasets. Split based on a predefined key.
	PredefinedSplit GoogleCloudAiplatformV1PredefinedSplitPtrInput `pulumi:"predefinedSplit"`
	// Only applicable to Datasets that have SavedQueries. The ID of a SavedQuery (annotation set) under the Dataset specified by dataset_id used for filtering Annotations for training. Only Annotations that are associated with this SavedQuery are used in respectively training. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both saved_query_id and annotations_filter. Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.
	SavedQueryId pulumi.StringPtrInput `pulumi:"savedQueryId"`
	// Supported only for tabular Datasets. Split based on the distribution of the specified column.
	StratifiedSplit GoogleCloudAiplatformV1StratifiedSplitPtrInput `pulumi:"stratifiedSplit"`
	// Supported only for tabular Datasets. Split based on the timestamp of the input data pieces.
	TimestampSplit GoogleCloudAiplatformV1TimestampSplitPtrInput `pulumi:"timestampSplit"`
}

Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.

func (GoogleCloudAiplatformV1InputDataConfigArgs) ElementType 

func (GoogleCloudAiplatformV1InputDataConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1InputDataConfigArgs) ToGoogleCloudAiplatformV1InputDataConfigOutput 

func (i GoogleCloudAiplatformV1InputDataConfigArgs) ToGoogleCloudAiplatformV1InputDataConfigOutput() GoogleCloudAiplatformV1InputDataConfigOutput

func (GoogleCloudAiplatformV1InputDataConfigArgs) ToGoogleCloudAiplatformV1InputDataConfigOutputWithContext 

func (i GoogleCloudAiplatformV1InputDataConfigArgs) ToGoogleCloudAiplatformV1InputDataConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1InputDataConfigOutput

func (GoogleCloudAiplatformV1InputDataConfigArgs) ToGoogleCloudAiplatformV1InputDataConfigPtrOutput 

func (i GoogleCloudAiplatformV1InputDataConfigArgs) ToGoogleCloudAiplatformV1InputDataConfigPtrOutput() GoogleCloudAiplatformV1InputDataConfigPtrOutput

func (GoogleCloudAiplatformV1InputDataConfigArgs) ToGoogleCloudAiplatformV1InputDataConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1InputDataConfigArgs) ToGoogleCloudAiplatformV1InputDataConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1InputDataConfigPtrOutput

type GoogleCloudAiplatformV1InputDataConfigInput 

type GoogleCloudAiplatformV1InputDataConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1InputDataConfigOutput() GoogleCloudAiplatformV1InputDataConfigOutput
	ToGoogleCloudAiplatformV1InputDataConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1InputDataConfigOutput
}

GoogleCloudAiplatformV1InputDataConfigInput is an input type that accepts GoogleCloudAiplatformV1InputDataConfigArgs and GoogleCloudAiplatformV1InputDataConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1InputDataConfigInput` via: 

GoogleCloudAiplatformV1InputDataConfigArgs{...}

type GoogleCloudAiplatformV1InputDataConfigOutput 

type GoogleCloudAiplatformV1InputDataConfigOutput struct{ *pulumi.OutputState }

Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.

func (GoogleCloudAiplatformV1InputDataConfigOutput) AnnotationSchemaUri 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) AnnotationSchemaUri() pulumi.StringPtrOutput

Applicable only to custom training with Datasets that have DataItems and Annotations. Cloud Storage URI that points to a YAML file describing the annotation schema. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/ , note that the chosen schema must be consistent with metadata of the Dataset specified by dataset_id. Only Annotations that both match this schema and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri.

func (GoogleCloudAiplatformV1InputDataConfigOutput) AnnotationsFilter 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) AnnotationsFilter() pulumi.StringPtrOutput

Applicable only to Datasets that have DataItems and Annotations. A filter on Annotations of the Dataset. Only Annotations that both match this filter and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on (for the auto-assigned that role is decided by Vertex AI). A filter with same syntax as the one used in ListAnnotations may be used, but note here it filters across all Annotations of the Dataset, and not just within a single DataItem.

func (GoogleCloudAiplatformV1InputDataConfigOutput) BigqueryDestination 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) BigqueryDestination() GoogleCloudAiplatformV1BigQueryDestinationPtrOutput

Only applicable to custom training with tabular Dataset with BigQuery source. The BigQuery project location where the training data is to be written to. In the given project a new dataset is created with name `dataset___` where timestamp is in YYYY_MM_DDThh_mm_ss_sssZ format. All training input data is written into that dataset. In the dataset three tables are created, `training`, `validation` and `test`. * AIP_DATA_FORMAT = "bigquery". * AIP_TRAINING_DATA_URI = "bigquery_destination.dataset___.training" * AIP_VALIDATION_DATA_URI = "bigquery_destination.dataset___.validation" * AIP_TEST_DATA_URI = "bigquery_destination.dataset___.test"

func (GoogleCloudAiplatformV1InputDataConfigOutput) DatasetId 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) DatasetId() pulumi.StringOutput

The ID of the Dataset in the same Project and Location which data will be used to train the Model. The Dataset must use schema compatible with Model being trained, and what is compatible should be described in the used TrainingPipeline's training_task_definition. For tabular Datasets, all their data is exported to training, to pick and choose from.

func (GoogleCloudAiplatformV1InputDataConfigOutput) ElementType 

func (GoogleCloudAiplatformV1InputDataConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1InputDataConfigOutput) FilterSplit 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) FilterSplit() GoogleCloudAiplatformV1FilterSplitPtrOutput

Split based on the provided filters for each set.

func (GoogleCloudAiplatformV1InputDataConfigOutput) FractionSplit 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) FractionSplit() GoogleCloudAiplatformV1FractionSplitPtrOutput

Split based on fractions defining the size of each set.

func (GoogleCloudAiplatformV1InputDataConfigOutput) GcsDestination 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) GcsDestination() GoogleCloudAiplatformV1GcsDestinationPtrOutput

The Cloud Storage location where the training data is to be written to. In the given directory a new directory is created with name: `dataset---` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All training input data is written into that directory. The Vertex AI environment variables representing Cloud Storage data URIs are represented in the Cloud Storage wildcard format to support sharded data. e.g.: "gs://.../training-*.jsonl" * AIP_DATA_FORMAT = "jsonl" for non-tabular data, "csv" for tabular data * AIP_TRAINING_DATA_URI = "gcs_destination/dataset---/training-*.${AIP_DATA_FORMAT}" * AIP_VALIDATION_DATA_URI = "gcs_destination/dataset---/validation-*.${AIP_DATA_FORMAT}" * AIP_TEST_DATA_URI = "gcs_destination/dataset---/test-*.${AIP_DATA_FORMAT}"

func (GoogleCloudAiplatformV1InputDataConfigOutput) PersistMlUseAssignment 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) PersistMlUseAssignment() pulumi.BoolPtrOutput

Whether to persist the ML use assignment to data item system labels.

func (GoogleCloudAiplatformV1InputDataConfigOutput) PredefinedSplit 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) PredefinedSplit() GoogleCloudAiplatformV1PredefinedSplitPtrOutput

Supported only for tabular Datasets. Split based on a predefined key.

func (GoogleCloudAiplatformV1InputDataConfigOutput) SavedQueryId 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) SavedQueryId() pulumi.StringPtrOutput

Only applicable to Datasets that have SavedQueries. The ID of a SavedQuery (annotation set) under the Dataset specified by dataset_id used for filtering Annotations for training. Only Annotations that are associated with this SavedQuery are used in respectively training. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both saved_query_id and annotations_filter. Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.

func (GoogleCloudAiplatformV1InputDataConfigOutput) StratifiedSplit 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) StratifiedSplit() GoogleCloudAiplatformV1StratifiedSplitPtrOutput

Supported only for tabular Datasets. Split based on the distribution of the specified column.

func (GoogleCloudAiplatformV1InputDataConfigOutput) TimestampSplit 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) TimestampSplit() GoogleCloudAiplatformV1TimestampSplitPtrOutput

Supported only for tabular Datasets. Split based on the timestamp of the input data pieces.

func (GoogleCloudAiplatformV1InputDataConfigOutput) ToGoogleCloudAiplatformV1InputDataConfigOutput 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) ToGoogleCloudAiplatformV1InputDataConfigOutput() GoogleCloudAiplatformV1InputDataConfigOutput

func (GoogleCloudAiplatformV1InputDataConfigOutput) ToGoogleCloudAiplatformV1InputDataConfigOutputWithContext 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) ToGoogleCloudAiplatformV1InputDataConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1InputDataConfigOutput

func (GoogleCloudAiplatformV1InputDataConfigOutput) ToGoogleCloudAiplatformV1InputDataConfigPtrOutput 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) ToGoogleCloudAiplatformV1InputDataConfigPtrOutput() GoogleCloudAiplatformV1InputDataConfigPtrOutput

func (GoogleCloudAiplatformV1InputDataConfigOutput) ToGoogleCloudAiplatformV1InputDataConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1InputDataConfigOutput) ToGoogleCloudAiplatformV1InputDataConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1InputDataConfigPtrOutput

type GoogleCloudAiplatformV1InputDataConfigPtrInput 

type GoogleCloudAiplatformV1InputDataConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1InputDataConfigPtrOutput() GoogleCloudAiplatformV1InputDataConfigPtrOutput
	ToGoogleCloudAiplatformV1InputDataConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1InputDataConfigPtrOutput
}

GoogleCloudAiplatformV1InputDataConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1InputDataConfigArgs, GoogleCloudAiplatformV1InputDataConfigPtr and GoogleCloudAiplatformV1InputDataConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1InputDataConfigPtrInput` via: 

        GoogleCloudAiplatformV1InputDataConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1InputDataConfigPtr 

func GoogleCloudAiplatformV1InputDataConfigPtr(v *GoogleCloudAiplatformV1InputDataConfigArgs) GoogleCloudAiplatformV1InputDataConfigPtrInput

type GoogleCloudAiplatformV1InputDataConfigPtrOutput 

type GoogleCloudAiplatformV1InputDataConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) AnnotationSchemaUri 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) AnnotationSchemaUri() pulumi.StringPtrOutput

Applicable only to custom training with Datasets that have DataItems and Annotations. Cloud Storage URI that points to a YAML file describing the annotation schema. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/ , note that the chosen schema must be consistent with metadata of the Dataset specified by dataset_id. Only Annotations that both match this schema and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri.

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) AnnotationsFilter 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) AnnotationsFilter() pulumi.StringPtrOutput

Applicable only to Datasets that have DataItems and Annotations. A filter on Annotations of the Dataset. Only Annotations that both match this filter and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on (for the auto-assigned that role is decided by Vertex AI). A filter with same syntax as the one used in ListAnnotations may be used, but note here it filters across all Annotations of the Dataset, and not just within a single DataItem.

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) BigqueryDestination 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) BigqueryDestination() GoogleCloudAiplatformV1BigQueryDestinationPtrOutput

Only applicable to custom training with tabular Dataset with BigQuery source. The BigQuery project location where the training data is to be written to. In the given project a new dataset is created with name `dataset___` where timestamp is in YYYY_MM_DDThh_mm_ss_sssZ format. All training input data is written into that dataset. In the dataset three tables are created, `training`, `validation` and `test`. * AIP_DATA_FORMAT = "bigquery". * AIP_TRAINING_DATA_URI = "bigquery_destination.dataset___.training" * AIP_VALIDATION_DATA_URI = "bigquery_destination.dataset___.validation" * AIP_TEST_DATA_URI = "bigquery_destination.dataset___.test"

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) DatasetId 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) DatasetId() pulumi.StringPtrOutput

The ID of the Dataset in the same Project and Location which data will be used to train the Model. The Dataset must use schema compatible with Model being trained, and what is compatible should be described in the used TrainingPipeline's training_task_definition. For tabular Datasets, all their data is exported to training, to pick and choose from.

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) Elem() GoogleCloudAiplatformV1InputDataConfigOutput

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) FilterSplit 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) FilterSplit() GoogleCloudAiplatformV1FilterSplitPtrOutput

Split based on the provided filters for each set.

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) FractionSplit 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) FractionSplit() GoogleCloudAiplatformV1FractionSplitPtrOutput

Split based on fractions defining the size of each set.

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) GcsDestination 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) GcsDestination() GoogleCloudAiplatformV1GcsDestinationPtrOutput

The Cloud Storage location where the training data is to be written to. In the given directory a new directory is created with name: `dataset---` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All training input data is written into that directory. The Vertex AI environment variables representing Cloud Storage data URIs are represented in the Cloud Storage wildcard format to support sharded data. e.g.: "gs://.../training-*.jsonl" * AIP_DATA_FORMAT = "jsonl" for non-tabular data, "csv" for tabular data * AIP_TRAINING_DATA_URI = "gcs_destination/dataset---/training-*.${AIP_DATA_FORMAT}" * AIP_VALIDATION_DATA_URI = "gcs_destination/dataset---/validation-*.${AIP_DATA_FORMAT}" * AIP_TEST_DATA_URI = "gcs_destination/dataset---/test-*.${AIP_DATA_FORMAT}"

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) PersistMlUseAssignment 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) PersistMlUseAssignment() pulumi.BoolPtrOutput

Whether to persist the ML use assignment to data item system labels.

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) PredefinedSplit 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) PredefinedSplit() GoogleCloudAiplatformV1PredefinedSplitPtrOutput

Supported only for tabular Datasets. Split based on a predefined key.

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) SavedQueryId 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) SavedQueryId() pulumi.StringPtrOutput

Only applicable to Datasets that have SavedQueries. The ID of a SavedQuery (annotation set) under the Dataset specified by dataset_id used for filtering Annotations for training. Only Annotations that are associated with this SavedQuery are used in respectively training. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both saved_query_id and annotations_filter. Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) StratifiedSplit 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) StratifiedSplit() GoogleCloudAiplatformV1StratifiedSplitPtrOutput

Supported only for tabular Datasets. Split based on the distribution of the specified column.

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) TimestampSplit 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) TimestampSplit() GoogleCloudAiplatformV1TimestampSplitPtrOutput

Supported only for tabular Datasets. Split based on the timestamp of the input data pieces.

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) ToGoogleCloudAiplatformV1InputDataConfigPtrOutput 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) ToGoogleCloudAiplatformV1InputDataConfigPtrOutput() GoogleCloudAiplatformV1InputDataConfigPtrOutput

func (GoogleCloudAiplatformV1InputDataConfigPtrOutput) ToGoogleCloudAiplatformV1InputDataConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1InputDataConfigPtrOutput) ToGoogleCloudAiplatformV1InputDataConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1InputDataConfigPtrOutput

type GoogleCloudAiplatformV1InputDataConfigResponse 

type GoogleCloudAiplatformV1InputDataConfigResponse struct {
	// Applicable only to custom training with Datasets that have DataItems and Annotations. Cloud Storage URI that points to a YAML file describing the annotation schema. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/ , note that the chosen schema must be consistent with metadata of the Dataset specified by dataset_id. Only Annotations that both match this schema and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri.
	AnnotationSchemaUri string `pulumi:"annotationSchemaUri"`
	// Applicable only to Datasets that have DataItems and Annotations. A filter on Annotations of the Dataset. Only Annotations that both match this filter and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on (for the auto-assigned that role is decided by Vertex AI). A filter with same syntax as the one used in ListAnnotations may be used, but note here it filters across all Annotations of the Dataset, and not just within a single DataItem.
	AnnotationsFilter string `pulumi:"annotationsFilter"`
	// Only applicable to custom training with tabular Dataset with BigQuery source. The BigQuery project location where the training data is to be written to. In the given project a new dataset is created with name `dataset___` where timestamp is in YYYY_MM_DDThh_mm_ss_sssZ format. All training input data is written into that dataset. In the dataset three tables are created, `training`, `validation` and `test`. * AIP_DATA_FORMAT = "bigquery". * AIP_TRAINING_DATA_URI = "bigquery_destination.dataset___.training" * AIP_VALIDATION_DATA_URI = "bigquery_destination.dataset___.validation" * AIP_TEST_DATA_URI = "bigquery_destination.dataset___.test"
	BigqueryDestination GoogleCloudAiplatformV1BigQueryDestinationResponse `pulumi:"bigqueryDestination"`
	// The ID of the Dataset in the same Project and Location which data will be used to train the Model. The Dataset must use schema compatible with Model being trained, and what is compatible should be described in the used TrainingPipeline's training_task_definition. For tabular Datasets, all their data is exported to training, to pick and choose from.
	DatasetId string `pulumi:"datasetId"`
	// Split based on the provided filters for each set.
	FilterSplit GoogleCloudAiplatformV1FilterSplitResponse `pulumi:"filterSplit"`
	// Split based on fractions defining the size of each set.
	FractionSplit GoogleCloudAiplatformV1FractionSplitResponse `pulumi:"fractionSplit"`
	// The Cloud Storage location where the training data is to be written to. In the given directory a new directory is created with name: `dataset---` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All training input data is written into that directory. The Vertex AI environment variables representing Cloud Storage data URIs are represented in the Cloud Storage wildcard format to support sharded data. e.g.: "gs://.../training-*.jsonl" * AIP_DATA_FORMAT = "jsonl" for non-tabular data, "csv" for tabular data * AIP_TRAINING_DATA_URI = "gcs_destination/dataset---/training-*.${AIP_DATA_FORMAT}" * AIP_VALIDATION_DATA_URI = "gcs_destination/dataset---/validation-*.${AIP_DATA_FORMAT}" * AIP_TEST_DATA_URI = "gcs_destination/dataset---/test-*.${AIP_DATA_FORMAT}"
	GcsDestination GoogleCloudAiplatformV1GcsDestinationResponse `pulumi:"gcsDestination"`
	// Whether to persist the ML use assignment to data item system labels.
	PersistMlUseAssignment bool `pulumi:"persistMlUseAssignment"`
	// Supported only for tabular Datasets. Split based on a predefined key.
	PredefinedSplit GoogleCloudAiplatformV1PredefinedSplitResponse `pulumi:"predefinedSplit"`
	// Only applicable to Datasets that have SavedQueries. The ID of a SavedQuery (annotation set) under the Dataset specified by dataset_id used for filtering Annotations for training. Only Annotations that are associated with this SavedQuery are used in respectively training. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both saved_query_id and annotations_filter. Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.
	SavedQueryId string `pulumi:"savedQueryId"`
	// Supported only for tabular Datasets. Split based on the distribution of the specified column.
	StratifiedSplit GoogleCloudAiplatformV1StratifiedSplitResponse `pulumi:"stratifiedSplit"`
	// Supported only for tabular Datasets. Split based on the timestamp of the input data pieces.
	TimestampSplit GoogleCloudAiplatformV1TimestampSplitResponse `pulumi:"timestampSplit"`
}

Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.

type GoogleCloudAiplatformV1InputDataConfigResponseOutput 

type GoogleCloudAiplatformV1InputDataConfigResponseOutput struct{ *pulumi.OutputState }

Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) AnnotationSchemaUri 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) AnnotationSchemaUri() pulumi.StringOutput

Applicable only to custom training with Datasets that have DataItems and Annotations. Cloud Storage URI that points to a YAML file describing the annotation schema. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/ , note that the chosen schema must be consistent with metadata of the Dataset specified by dataset_id. Only Annotations that both match this schema and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri.

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) AnnotationsFilter 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) AnnotationsFilter() pulumi.StringOutput

Applicable only to Datasets that have DataItems and Annotations. A filter on Annotations of the Dataset. Only Annotations that both match this filter and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on (for the auto-assigned that role is decided by Vertex AI). A filter with same syntax as the one used in ListAnnotations may be used, but note here it filters across all Annotations of the Dataset, and not just within a single DataItem.

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) BigqueryDestination 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) BigqueryDestination() GoogleCloudAiplatformV1BigQueryDestinationResponseOutput

Only applicable to custom training with tabular Dataset with BigQuery source. The BigQuery project location where the training data is to be written to. In the given project a new dataset is created with name `dataset___` where timestamp is in YYYY_MM_DDThh_mm_ss_sssZ format. All training input data is written into that dataset. In the dataset three tables are created, `training`, `validation` and `test`. * AIP_DATA_FORMAT = "bigquery". * AIP_TRAINING_DATA_URI = "bigquery_destination.dataset___.training" * AIP_VALIDATION_DATA_URI = "bigquery_destination.dataset___.validation" * AIP_TEST_DATA_URI = "bigquery_destination.dataset___.test"

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) DatasetId 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) DatasetId() pulumi.StringOutput

The ID of the Dataset in the same Project and Location which data will be used to train the Model. The Dataset must use schema compatible with Model being trained, and what is compatible should be described in the used TrainingPipeline's training_task_definition. For tabular Datasets, all their data is exported to training, to pick and choose from.

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) FilterSplit 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) FilterSplit() GoogleCloudAiplatformV1FilterSplitResponseOutput

Split based on the provided filters for each set.

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) FractionSplit 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) FractionSplit() GoogleCloudAiplatformV1FractionSplitResponseOutput

Split based on fractions defining the size of each set.

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) GcsDestination 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) GcsDestination() GoogleCloudAiplatformV1GcsDestinationResponseOutput

The Cloud Storage location where the training data is to be written to. In the given directory a new directory is created with name: `dataset---` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All training input data is written into that directory. The Vertex AI environment variables representing Cloud Storage data URIs are represented in the Cloud Storage wildcard format to support sharded data. e.g.: "gs://.../training-*.jsonl" * AIP_DATA_FORMAT = "jsonl" for non-tabular data, "csv" for tabular data * AIP_TRAINING_DATA_URI = "gcs_destination/dataset---/training-*.${AIP_DATA_FORMAT}" * AIP_VALIDATION_DATA_URI = "gcs_destination/dataset---/validation-*.${AIP_DATA_FORMAT}" * AIP_TEST_DATA_URI = "gcs_destination/dataset---/test-*.${AIP_DATA_FORMAT}"

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) PersistMlUseAssignment 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) PersistMlUseAssignment() pulumi.BoolOutput

Whether to persist the ML use assignment to data item system labels.

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) PredefinedSplit 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) PredefinedSplit() GoogleCloudAiplatformV1PredefinedSplitResponseOutput

Supported only for tabular Datasets. Split based on a predefined key.

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) SavedQueryId 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) SavedQueryId() pulumi.StringOutput

Only applicable to Datasets that have SavedQueries. The ID of a SavedQuery (annotation set) under the Dataset specified by dataset_id used for filtering Annotations for training. Only Annotations that are associated with this SavedQuery are used in respectively training. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both saved_query_id and annotations_filter. Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type.

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) StratifiedSplit 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) StratifiedSplit() GoogleCloudAiplatformV1StratifiedSplitResponseOutput

Supported only for tabular Datasets. Split based on the distribution of the specified column.

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) TimestampSplit 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) TimestampSplit() GoogleCloudAiplatformV1TimestampSplitResponseOutput

Supported only for tabular Datasets. Split based on the timestamp of the input data pieces.

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) ToGoogleCloudAiplatformV1InputDataConfigResponseOutput 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) ToGoogleCloudAiplatformV1InputDataConfigResponseOutput() GoogleCloudAiplatformV1InputDataConfigResponseOutput

func (GoogleCloudAiplatformV1InputDataConfigResponseOutput) ToGoogleCloudAiplatformV1InputDataConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1InputDataConfigResponseOutput) ToGoogleCloudAiplatformV1InputDataConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1InputDataConfigResponseOutput

type GoogleCloudAiplatformV1IntegratedGradientsAttribution 

type GoogleCloudAiplatformV1IntegratedGradientsAttribution struct {
	// Config for IG with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383
	BlurBaselineConfig *GoogleCloudAiplatformV1BlurBaselineConfig `pulumi:"blurBaselineConfig"`
	// Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf
	SmoothGradConfig *GoogleCloudAiplatformV1SmoothGradConfig `pulumi:"smoothGradConfig"`
	// The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is within the desired error range. Valid range of its value is [1, 100], inclusively.
	StepCount int `pulumi:"stepCount"`
}

An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

type GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs 

type GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs struct {
	// Config for IG with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383
	BlurBaselineConfig GoogleCloudAiplatformV1BlurBaselineConfigPtrInput `pulumi:"blurBaselineConfig"`
	// Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf
	SmoothGradConfig GoogleCloudAiplatformV1SmoothGradConfigPtrInput `pulumi:"smoothGradConfig"`
	// The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is within the desired error range. Valid range of its value is [1, 100], inclusively.
	StepCount pulumi.IntInput `pulumi:"stepCount"`
}

An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs) ElementType 

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionOutput 

func (i GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionOutput() GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionOutputWithContext 

func (i GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput 

func (i GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput() GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutputWithContext 

func (i GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput

type GoogleCloudAiplatformV1IntegratedGradientsAttributionInput 

type GoogleCloudAiplatformV1IntegratedGradientsAttributionInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1IntegratedGradientsAttributionOutput() GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput
	ToGoogleCloudAiplatformV1IntegratedGradientsAttributionOutputWithContext(context.Context) GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput
}

GoogleCloudAiplatformV1IntegratedGradientsAttributionInput is an input type that accepts GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs and GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1IntegratedGradientsAttributionInput` via: 

GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs{...}

type GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput 

type GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput struct{ *pulumi.OutputState }

An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) BlurBaselineConfig 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) BlurBaselineConfig() GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput

Config for IG with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) ElementType 

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) SmoothGradConfig 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) SmoothGradConfig() GoogleCloudAiplatformV1SmoothGradConfigPtrOutput

Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) StepCount 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) StepCount() pulumi.IntOutput

The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is within the desired error range. Valid range of its value is [1, 100], inclusively.

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionOutput 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionOutput() GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionOutputWithContext 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput() GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput

type GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrInput 

type GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput() GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput
	ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput
}

GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrInput is an input type that accepts GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs, GoogleCloudAiplatformV1IntegratedGradientsAttributionPtr and GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrInput` via: 

        GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs{...}

or:

        nil

func GoogleCloudAiplatformV1IntegratedGradientsAttributionPtr 

func GoogleCloudAiplatformV1IntegratedGradientsAttributionPtr(v *GoogleCloudAiplatformV1IntegratedGradientsAttributionArgs) GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrInput

type GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput 

type GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) BlurBaselineConfig 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) BlurBaselineConfig() GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput

Config for IG with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) Elem 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) Elem() GoogleCloudAiplatformV1IntegratedGradientsAttributionOutput

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) ElementType 

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) SmoothGradConfig 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) SmoothGradConfig() GoogleCloudAiplatformV1SmoothGradConfigPtrOutput

Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) StepCount 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) StepCount() pulumi.IntPtrOutput

The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is within the desired error range. Valid range of its value is [1, 100], inclusively.

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput() GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1IntegratedGradientsAttributionPtrOutput

type GoogleCloudAiplatformV1IntegratedGradientsAttributionResponse 

type GoogleCloudAiplatformV1IntegratedGradientsAttributionResponse struct {
	// Config for IG with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383
	BlurBaselineConfig GoogleCloudAiplatformV1BlurBaselineConfigResponse `pulumi:"blurBaselineConfig"`
	// Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf
	SmoothGradConfig GoogleCloudAiplatformV1SmoothGradConfigResponse `pulumi:"smoothGradConfig"`
	// The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is within the desired error range. Valid range of its value is [1, 100], inclusively.
	StepCount int `pulumi:"stepCount"`
}

An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

type GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput 

type GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput struct{ *pulumi.OutputState }

An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput) BlurBaselineConfig 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput) BlurBaselineConfig() GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput

Config for IG with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput) ElementType 

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput) SmoothGradConfig 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput) SmoothGradConfig() GoogleCloudAiplatformV1SmoothGradConfigResponseOutput

Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput) StepCount 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput) StepCount() pulumi.IntOutput

The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is within the desired error range. Valid range of its value is [1, 100], inclusively.

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput() GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput

func (GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutputWithContext 

func (o GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput) ToGoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1IntegratedGradientsAttributionResponseOutput

type GoogleCloudAiplatformV1MachineSpec 

type GoogleCloudAiplatformV1MachineSpec struct {
	// The number of accelerators to attach to the machine.
	AcceleratorCount *int `pulumi:"acceleratorCount"`
	// Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
	AcceleratorType *GoogleCloudAiplatformV1MachineSpecAcceleratorType `pulumi:"acceleratorType"`
	// Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
	MachineType *string `pulumi:"machineType"`
	// Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
	TpuTopology *string `pulumi:"tpuTopology"`
}

Specification of a single machine.

type GoogleCloudAiplatformV1MachineSpecAcceleratorType 

type GoogleCloudAiplatformV1MachineSpecAcceleratorType string

Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.

func (GoogleCloudAiplatformV1MachineSpecAcceleratorType) ElementType 

func (GoogleCloudAiplatformV1MachineSpecAcceleratorType) ElementType() reflect.Type

func (GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput 

func (e GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput() GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutputWithContext 

func (e GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput 

func (e GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput() GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutputWithContext 

func (e GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToStringOutput 

func (e GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1MachineSpecAcceleratorType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1MachineSpecAcceleratorTypeInput 

type GoogleCloudAiplatformV1MachineSpecAcceleratorTypeInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput() GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput
	ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutputWithContext(context.Context) GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput
}

GoogleCloudAiplatformV1MachineSpecAcceleratorTypeInput is an input type that accepts GoogleCloudAiplatformV1MachineSpecAcceleratorTypeArgs and GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1MachineSpecAcceleratorTypeInput` via: 

GoogleCloudAiplatformV1MachineSpecAcceleratorTypeArgs{...}

type GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput 

type GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ElementType 

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput 

func (o GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput() GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutputWithContext 

func (o GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput 

func (o GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput() GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutputWithContext 

func (o GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrInput 

type GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput() GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput
	ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput
}

func GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtr 

func GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtr(v string) GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrInput

type GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput 

type GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput) Elem 

func (o GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput) Elem() GoogleCloudAiplatformV1MachineSpecAcceleratorTypeOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput) ElementType 

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput 

func (o GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput() GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutputWithContext 

func (o GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput) ToGoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1MachineSpecArgs 

type GoogleCloudAiplatformV1MachineSpecArgs struct {
	// The number of accelerators to attach to the machine.
	AcceleratorCount pulumi.IntPtrInput `pulumi:"acceleratorCount"`
	// Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
	AcceleratorType GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrInput `pulumi:"acceleratorType"`
	// Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
	MachineType pulumi.StringPtrInput `pulumi:"machineType"`
	// Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
	TpuTopology pulumi.StringPtrInput `pulumi:"tpuTopology"`
}

Specification of a single machine.

func (GoogleCloudAiplatformV1MachineSpecArgs) ElementType 

func (GoogleCloudAiplatformV1MachineSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1MachineSpecArgs) ToGoogleCloudAiplatformV1MachineSpecOutput 

func (i GoogleCloudAiplatformV1MachineSpecArgs) ToGoogleCloudAiplatformV1MachineSpecOutput() GoogleCloudAiplatformV1MachineSpecOutput

func (GoogleCloudAiplatformV1MachineSpecArgs) ToGoogleCloudAiplatformV1MachineSpecOutputWithContext 

func (i GoogleCloudAiplatformV1MachineSpecArgs) ToGoogleCloudAiplatformV1MachineSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MachineSpecOutput

func (GoogleCloudAiplatformV1MachineSpecArgs) ToGoogleCloudAiplatformV1MachineSpecPtrOutput 

func (i GoogleCloudAiplatformV1MachineSpecArgs) ToGoogleCloudAiplatformV1MachineSpecPtrOutput() GoogleCloudAiplatformV1MachineSpecPtrOutput

func (GoogleCloudAiplatformV1MachineSpecArgs) ToGoogleCloudAiplatformV1MachineSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1MachineSpecArgs) ToGoogleCloudAiplatformV1MachineSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MachineSpecPtrOutput

type GoogleCloudAiplatformV1MachineSpecInput 

type GoogleCloudAiplatformV1MachineSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1MachineSpecOutput() GoogleCloudAiplatformV1MachineSpecOutput
	ToGoogleCloudAiplatformV1MachineSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1MachineSpecOutput
}

GoogleCloudAiplatformV1MachineSpecInput is an input type that accepts GoogleCloudAiplatformV1MachineSpecArgs and GoogleCloudAiplatformV1MachineSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1MachineSpecInput` via: 

GoogleCloudAiplatformV1MachineSpecArgs{...}

type GoogleCloudAiplatformV1MachineSpecOutput 

type GoogleCloudAiplatformV1MachineSpecOutput struct{ *pulumi.OutputState }

Specification of a single machine.

func (GoogleCloudAiplatformV1MachineSpecOutput) AcceleratorCount 

func (o GoogleCloudAiplatformV1MachineSpecOutput) AcceleratorCount() pulumi.IntPtrOutput

The number of accelerators to attach to the machine.

func (GoogleCloudAiplatformV1MachineSpecOutput) AcceleratorType 

func (o GoogleCloudAiplatformV1MachineSpecOutput) AcceleratorType() GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput

Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.

func (GoogleCloudAiplatformV1MachineSpecOutput) ElementType 

func (GoogleCloudAiplatformV1MachineSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1MachineSpecOutput) MachineType 

func (o GoogleCloudAiplatformV1MachineSpecOutput) MachineType() pulumi.StringPtrOutput

Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.

func (GoogleCloudAiplatformV1MachineSpecOutput) ToGoogleCloudAiplatformV1MachineSpecOutput 

func (o GoogleCloudAiplatformV1MachineSpecOutput) ToGoogleCloudAiplatformV1MachineSpecOutput() GoogleCloudAiplatformV1MachineSpecOutput

func (GoogleCloudAiplatformV1MachineSpecOutput) ToGoogleCloudAiplatformV1MachineSpecOutputWithContext 

func (o GoogleCloudAiplatformV1MachineSpecOutput) ToGoogleCloudAiplatformV1MachineSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MachineSpecOutput

func (GoogleCloudAiplatformV1MachineSpecOutput) ToGoogleCloudAiplatformV1MachineSpecPtrOutput 

func (o GoogleCloudAiplatformV1MachineSpecOutput) ToGoogleCloudAiplatformV1MachineSpecPtrOutput() GoogleCloudAiplatformV1MachineSpecPtrOutput

func (GoogleCloudAiplatformV1MachineSpecOutput) ToGoogleCloudAiplatformV1MachineSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1MachineSpecOutput) ToGoogleCloudAiplatformV1MachineSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MachineSpecPtrOutput

func (GoogleCloudAiplatformV1MachineSpecOutput) TpuTopology 

func (o GoogleCloudAiplatformV1MachineSpecOutput) TpuTopology() pulumi.StringPtrOutput

Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").

type GoogleCloudAiplatformV1MachineSpecPtrInput 

type GoogleCloudAiplatformV1MachineSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1MachineSpecPtrOutput() GoogleCloudAiplatformV1MachineSpecPtrOutput
	ToGoogleCloudAiplatformV1MachineSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1MachineSpecPtrOutput
}

GoogleCloudAiplatformV1MachineSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1MachineSpecArgs, GoogleCloudAiplatformV1MachineSpecPtr and GoogleCloudAiplatformV1MachineSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1MachineSpecPtrInput` via: 

        GoogleCloudAiplatformV1MachineSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1MachineSpecPtr 

func GoogleCloudAiplatformV1MachineSpecPtr(v *GoogleCloudAiplatformV1MachineSpecArgs) GoogleCloudAiplatformV1MachineSpecPtrInput

type GoogleCloudAiplatformV1MachineSpecPtrOutput 

type GoogleCloudAiplatformV1MachineSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1MachineSpecPtrOutput) AcceleratorCount 

func (o GoogleCloudAiplatformV1MachineSpecPtrOutput) AcceleratorCount() pulumi.IntPtrOutput

The number of accelerators to attach to the machine.

func (GoogleCloudAiplatformV1MachineSpecPtrOutput) AcceleratorType 

func (o GoogleCloudAiplatformV1MachineSpecPtrOutput) AcceleratorType() GoogleCloudAiplatformV1MachineSpecAcceleratorTypePtrOutput

Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.

func (GoogleCloudAiplatformV1MachineSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1MachineSpecPtrOutput) Elem() GoogleCloudAiplatformV1MachineSpecOutput

func (GoogleCloudAiplatformV1MachineSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1MachineSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1MachineSpecPtrOutput) MachineType 

func (o GoogleCloudAiplatformV1MachineSpecPtrOutput) MachineType() pulumi.StringPtrOutput

Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.

func (GoogleCloudAiplatformV1MachineSpecPtrOutput) ToGoogleCloudAiplatformV1MachineSpecPtrOutput 

func (o GoogleCloudAiplatformV1MachineSpecPtrOutput) ToGoogleCloudAiplatformV1MachineSpecPtrOutput() GoogleCloudAiplatformV1MachineSpecPtrOutput

func (GoogleCloudAiplatformV1MachineSpecPtrOutput) ToGoogleCloudAiplatformV1MachineSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1MachineSpecPtrOutput) ToGoogleCloudAiplatformV1MachineSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MachineSpecPtrOutput

func (GoogleCloudAiplatformV1MachineSpecPtrOutput) TpuTopology 

func (o GoogleCloudAiplatformV1MachineSpecPtrOutput) TpuTopology() pulumi.StringPtrOutput

Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").

type GoogleCloudAiplatformV1MachineSpecResponse 

type GoogleCloudAiplatformV1MachineSpecResponse struct {
	// The number of accelerators to attach to the machine.
	AcceleratorCount int `pulumi:"acceleratorCount"`
	// Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
	AcceleratorType string `pulumi:"acceleratorType"`
	// Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
	MachineType string `pulumi:"machineType"`
	// Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
	TpuTopology string `pulumi:"tpuTopology"`
}

Specification of a single machine.

type GoogleCloudAiplatformV1MachineSpecResponseOutput 

type GoogleCloudAiplatformV1MachineSpecResponseOutput struct{ *pulumi.OutputState }

Specification of a single machine.

func (GoogleCloudAiplatformV1MachineSpecResponseOutput) AcceleratorCount 

func (o GoogleCloudAiplatformV1MachineSpecResponseOutput) AcceleratorCount() pulumi.IntOutput

The number of accelerators to attach to the machine.

func (GoogleCloudAiplatformV1MachineSpecResponseOutput) AcceleratorType 

func (o GoogleCloudAiplatformV1MachineSpecResponseOutput) AcceleratorType() pulumi.StringOutput

Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.

func (GoogleCloudAiplatformV1MachineSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1MachineSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1MachineSpecResponseOutput) MachineType 

func (o GoogleCloudAiplatformV1MachineSpecResponseOutput) MachineType() pulumi.StringOutput

Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.

func (GoogleCloudAiplatformV1MachineSpecResponseOutput) ToGoogleCloudAiplatformV1MachineSpecResponseOutput 

func (o GoogleCloudAiplatformV1MachineSpecResponseOutput) ToGoogleCloudAiplatformV1MachineSpecResponseOutput() GoogleCloudAiplatformV1MachineSpecResponseOutput

func (GoogleCloudAiplatformV1MachineSpecResponseOutput) ToGoogleCloudAiplatformV1MachineSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1MachineSpecResponseOutput) ToGoogleCloudAiplatformV1MachineSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MachineSpecResponseOutput

func (GoogleCloudAiplatformV1MachineSpecResponseOutput) TpuTopology 

func (o GoogleCloudAiplatformV1MachineSpecResponseOutput) TpuTopology() pulumi.StringOutput

Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").

type GoogleCloudAiplatformV1ManualBatchTuningParameters 

type GoogleCloudAiplatformV1ManualBatchTuningParameters struct {
	// Immutable. The number of the records (e.g. instances) of the operation given in each batch to a machine replica. Machine type, and size of a single record should be considered when setting this parameter, higher value speeds up the batch operation's execution, but too high value will result in a whole batch not fitting in a machine's memory, and the whole operation will fail. The default value is 64.
	BatchSize *int `pulumi:"batchSize"`
}

Manual batch tuning parameters.

type GoogleCloudAiplatformV1ManualBatchTuningParametersArgs 

type GoogleCloudAiplatformV1ManualBatchTuningParametersArgs struct {
	// Immutable. The number of the records (e.g. instances) of the operation given in each batch to a machine replica. Machine type, and size of a single record should be considered when setting this parameter, higher value speeds up the batch operation's execution, but too high value will result in a whole batch not fitting in a machine's memory, and the whole operation will fail. The default value is 64.
	BatchSize pulumi.IntPtrInput `pulumi:"batchSize"`
}

Manual batch tuning parameters.

func (GoogleCloudAiplatformV1ManualBatchTuningParametersArgs) ElementType 

func (GoogleCloudAiplatformV1ManualBatchTuningParametersArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ManualBatchTuningParametersArgs) ToGoogleCloudAiplatformV1ManualBatchTuningParametersOutput 

func (i GoogleCloudAiplatformV1ManualBatchTuningParametersArgs) ToGoogleCloudAiplatformV1ManualBatchTuningParametersOutput() GoogleCloudAiplatformV1ManualBatchTuningParametersOutput

func (GoogleCloudAiplatformV1ManualBatchTuningParametersArgs) ToGoogleCloudAiplatformV1ManualBatchTuningParametersOutputWithContext 

func (i GoogleCloudAiplatformV1ManualBatchTuningParametersArgs) ToGoogleCloudAiplatformV1ManualBatchTuningParametersOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ManualBatchTuningParametersOutput

func (GoogleCloudAiplatformV1ManualBatchTuningParametersArgs) ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput 

func (i GoogleCloudAiplatformV1ManualBatchTuningParametersArgs) ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput() GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput

func (GoogleCloudAiplatformV1ManualBatchTuningParametersArgs) ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ManualBatchTuningParametersArgs) ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput

type GoogleCloudAiplatformV1ManualBatchTuningParametersInput 

type GoogleCloudAiplatformV1ManualBatchTuningParametersInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ManualBatchTuningParametersOutput() GoogleCloudAiplatformV1ManualBatchTuningParametersOutput
	ToGoogleCloudAiplatformV1ManualBatchTuningParametersOutputWithContext(context.Context) GoogleCloudAiplatformV1ManualBatchTuningParametersOutput
}

GoogleCloudAiplatformV1ManualBatchTuningParametersInput is an input type that accepts GoogleCloudAiplatformV1ManualBatchTuningParametersArgs and GoogleCloudAiplatformV1ManualBatchTuningParametersOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ManualBatchTuningParametersInput` via: 

GoogleCloudAiplatformV1ManualBatchTuningParametersArgs{...}

type GoogleCloudAiplatformV1ManualBatchTuningParametersOutput 

type GoogleCloudAiplatformV1ManualBatchTuningParametersOutput struct{ *pulumi.OutputState }

Manual batch tuning parameters.

func (GoogleCloudAiplatformV1ManualBatchTuningParametersOutput) BatchSize 

func (o GoogleCloudAiplatformV1ManualBatchTuningParametersOutput) BatchSize() pulumi.IntPtrOutput

Immutable. The number of the records (e.g. instances) of the operation given in each batch to a machine replica. Machine type, and size of a single record should be considered when setting this parameter, higher value speeds up the batch operation's execution, but too high value will result in a whole batch not fitting in a machine's memory, and the whole operation will fail. The default value is 64.

func (GoogleCloudAiplatformV1ManualBatchTuningParametersOutput) ElementType 

func (GoogleCloudAiplatformV1ManualBatchTuningParametersOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ManualBatchTuningParametersOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersOutput 

func (o GoogleCloudAiplatformV1ManualBatchTuningParametersOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersOutput() GoogleCloudAiplatformV1ManualBatchTuningParametersOutput

func (GoogleCloudAiplatformV1ManualBatchTuningParametersOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersOutputWithContext 

func (o GoogleCloudAiplatformV1ManualBatchTuningParametersOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ManualBatchTuningParametersOutput

func (GoogleCloudAiplatformV1ManualBatchTuningParametersOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput 

func (o GoogleCloudAiplatformV1ManualBatchTuningParametersOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput() GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput

func (GoogleCloudAiplatformV1ManualBatchTuningParametersOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ManualBatchTuningParametersOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput

type GoogleCloudAiplatformV1ManualBatchTuningParametersPtrInput 

type GoogleCloudAiplatformV1ManualBatchTuningParametersPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput() GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput
	ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput
}

GoogleCloudAiplatformV1ManualBatchTuningParametersPtrInput is an input type that accepts GoogleCloudAiplatformV1ManualBatchTuningParametersArgs, GoogleCloudAiplatformV1ManualBatchTuningParametersPtr and GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ManualBatchTuningParametersPtrInput` via: 

        GoogleCloudAiplatformV1ManualBatchTuningParametersArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ManualBatchTuningParametersPtr 

func GoogleCloudAiplatformV1ManualBatchTuningParametersPtr(v *GoogleCloudAiplatformV1ManualBatchTuningParametersArgs) GoogleCloudAiplatformV1ManualBatchTuningParametersPtrInput

type GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput 

type GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput) BatchSize 

func (o GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput) BatchSize() pulumi.IntPtrOutput

Immutable. The number of the records (e.g. instances) of the operation given in each batch to a machine replica. Machine type, and size of a single record should be considered when setting this parameter, higher value speeds up the batch operation's execution, but too high value will result in a whole batch not fitting in a machine's memory, and the whole operation will fail. The default value is 64.

func (GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput) Elem() GoogleCloudAiplatformV1ManualBatchTuningParametersOutput

func (GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput 

func (o GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput() GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput

func (GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ManualBatchTuningParametersPtrOutput

type GoogleCloudAiplatformV1ManualBatchTuningParametersResponse 

type GoogleCloudAiplatformV1ManualBatchTuningParametersResponse struct {
	// Immutable. The number of the records (e.g. instances) of the operation given in each batch to a machine replica. Machine type, and size of a single record should be considered when setting this parameter, higher value speeds up the batch operation's execution, but too high value will result in a whole batch not fitting in a machine's memory, and the whole operation will fail. The default value is 64.
	BatchSize int `pulumi:"batchSize"`
}

Manual batch tuning parameters.

type GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput 

type GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput struct{ *pulumi.OutputState }

Manual batch tuning parameters.

func (GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput) BatchSize 

func (o GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput) BatchSize() pulumi.IntOutput

Immutable. The number of the records (e.g. instances) of the operation given in each batch to a machine replica. Machine type, and size of a single record should be considered when setting this parameter, higher value speeds up the batch operation's execution, but too high value will result in a whole batch not fitting in a machine's memory, and the whole operation will fail. The default value is 64.

func (GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput 

func (o GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput() GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput

func (GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput) ToGoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput

type GoogleCloudAiplatformV1MeasurementMetricResponse 

type GoogleCloudAiplatformV1MeasurementMetricResponse struct {
	// The ID of the Metric. The Metric should be defined in StudySpec's Metrics.
	MetricId string `pulumi:"metricId"`
	// The value for this metric.
	Value float64 `pulumi:"value"`
}

A message representing a metric in the measurement.

type GoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput 

type GoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1MeasurementMetricResponseOutput

func (GoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput) ToGoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput 

func (o GoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput) ToGoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput() GoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput

func (GoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput) ToGoogleCloudAiplatformV1MeasurementMetricResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput) ToGoogleCloudAiplatformV1MeasurementMetricResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput

type GoogleCloudAiplatformV1MeasurementMetricResponseOutput 

type GoogleCloudAiplatformV1MeasurementMetricResponseOutput struct{ *pulumi.OutputState }

A message representing a metric in the measurement.

func (GoogleCloudAiplatformV1MeasurementMetricResponseOutput) ElementType 

func (GoogleCloudAiplatformV1MeasurementMetricResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1MeasurementMetricResponseOutput) MetricId 

func (o GoogleCloudAiplatformV1MeasurementMetricResponseOutput) MetricId() pulumi.StringOutput

The ID of the Metric. The Metric should be defined in StudySpec's Metrics.

func (GoogleCloudAiplatformV1MeasurementMetricResponseOutput) ToGoogleCloudAiplatformV1MeasurementMetricResponseOutput 

func (o GoogleCloudAiplatformV1MeasurementMetricResponseOutput) ToGoogleCloudAiplatformV1MeasurementMetricResponseOutput() GoogleCloudAiplatformV1MeasurementMetricResponseOutput

func (GoogleCloudAiplatformV1MeasurementMetricResponseOutput) ToGoogleCloudAiplatformV1MeasurementMetricResponseOutputWithContext 

func (o GoogleCloudAiplatformV1MeasurementMetricResponseOutput) ToGoogleCloudAiplatformV1MeasurementMetricResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MeasurementMetricResponseOutput

func (GoogleCloudAiplatformV1MeasurementMetricResponseOutput) Value 

func (o GoogleCloudAiplatformV1MeasurementMetricResponseOutput) Value() pulumi.Float64Output

The value for this metric.

type GoogleCloudAiplatformV1MeasurementResponse 

type GoogleCloudAiplatformV1MeasurementResponse struct {
	// Time that the Trial has been running at the point of this Measurement.
	ElapsedDuration string `pulumi:"elapsedDuration"`
	// A list of metrics got by evaluating the objective functions using suggested Parameter values.
	Metrics []GoogleCloudAiplatformV1MeasurementMetricResponse `pulumi:"metrics"`
	// The number of steps the machine learning model has been trained for. Must be non-negative.
	StepCount string `pulumi:"stepCount"`
}

A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values.

type GoogleCloudAiplatformV1MeasurementResponseArrayOutput 

type GoogleCloudAiplatformV1MeasurementResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1MeasurementResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1MeasurementResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1MeasurementResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1MeasurementResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1MeasurementResponseOutput

func (GoogleCloudAiplatformV1MeasurementResponseArrayOutput) ToGoogleCloudAiplatformV1MeasurementResponseArrayOutput 

func (o GoogleCloudAiplatformV1MeasurementResponseArrayOutput) ToGoogleCloudAiplatformV1MeasurementResponseArrayOutput() GoogleCloudAiplatformV1MeasurementResponseArrayOutput

func (GoogleCloudAiplatformV1MeasurementResponseArrayOutput) ToGoogleCloudAiplatformV1MeasurementResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1MeasurementResponseArrayOutput) ToGoogleCloudAiplatformV1MeasurementResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MeasurementResponseArrayOutput

type GoogleCloudAiplatformV1MeasurementResponseOutput 

type GoogleCloudAiplatformV1MeasurementResponseOutput struct{ *pulumi.OutputState }

A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values.

func (GoogleCloudAiplatformV1MeasurementResponseOutput) ElapsedDuration 

func (o GoogleCloudAiplatformV1MeasurementResponseOutput) ElapsedDuration() pulumi.StringOutput

Time that the Trial has been running at the point of this Measurement.

func (GoogleCloudAiplatformV1MeasurementResponseOutput) ElementType 

func (GoogleCloudAiplatformV1MeasurementResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1MeasurementResponseOutput) Metrics 

func (o GoogleCloudAiplatformV1MeasurementResponseOutput) Metrics() GoogleCloudAiplatformV1MeasurementMetricResponseArrayOutput

A list of metrics got by evaluating the objective functions using suggested Parameter values.

func (GoogleCloudAiplatformV1MeasurementResponseOutput) StepCount 

func (o GoogleCloudAiplatformV1MeasurementResponseOutput) StepCount() pulumi.StringOutput

The number of steps the machine learning model has been trained for. Must be non-negative.

func (GoogleCloudAiplatformV1MeasurementResponseOutput) ToGoogleCloudAiplatformV1MeasurementResponseOutput 

func (o GoogleCloudAiplatformV1MeasurementResponseOutput) ToGoogleCloudAiplatformV1MeasurementResponseOutput() GoogleCloudAiplatformV1MeasurementResponseOutput

func (GoogleCloudAiplatformV1MeasurementResponseOutput) ToGoogleCloudAiplatformV1MeasurementResponseOutputWithContext 

func (o GoogleCloudAiplatformV1MeasurementResponseOutput) ToGoogleCloudAiplatformV1MeasurementResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MeasurementResponseOutput

type GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponse 

type GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponse struct {
	// The disk utilization of the MetadataStore in bytes.
	DiskUtilizationBytes string `pulumi:"diskUtilizationBytes"`
}

Represents state information for a MetadataStore.

type GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput 

type GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput struct{ *pulumi.OutputState }

Represents state information for a MetadataStore.

func (GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput) DiskUtilizationBytes 

func (o GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput) DiskUtilizationBytes() pulumi.StringOutput

The disk utilization of the MetadataStore in bytes.

func (GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput) ElementType 

func (GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput) ToGoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput 

func (o GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput) ToGoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput() GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput

func (GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput) ToGoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutputWithContext 

func (o GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput) ToGoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput

type GoogleCloudAiplatformV1Model 

type GoogleCloudAiplatformV1Model struct {
	// Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models or Large Models.
	ArtifactUri *string `pulumi:"artifactUri"`
	// Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models or Large Models.
	ContainerSpec *GoogleCloudAiplatformV1ModelContainerSpec `pulumi:"containerSpec"`
	// The description of the Model.
	Description *string `pulumi:"description"`
	// The display name of the Model. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.
	EncryptionSpec *GoogleCloudAiplatformV1EncryptionSpec `pulumi:"encryptionSpec"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag *string `pulumi:"etag"`
	// The default explanation specification for this Model. The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated. All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob. If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.
	ExplanationSpec *GoogleCloudAiplatformV1ExplanationSpec `pulumi:"explanationSpec"`
	// The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels map[string]string `pulumi:"labels"`
	// Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
	Metadata interface{} `pulumi:"metadata"`
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	MetadataSchemaUri *string `pulumi:"metadataSchemaUri"`
	// The resource name of the Model.
	Name *string `pulumi:"name"`
	// Optional. This field is populated if the model is produced by a pipeline job.
	PipelineJob *string `pulumi:"pipelineJob"`
	// The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.
	PredictSchemata *GoogleCloudAiplatformV1PredictSchemata `pulumi:"predictSchemata"`
	// User provided version aliases so that a model version can be referenced via alias (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_alias}` instead of auto-generated version id (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_id})`. The format is a-z{0,126}[a-z0-9] to distinguish from version_id. A default version alias will be created for the first version of the model, and there must be exactly one default version alias for a model.
	VersionAliases []string `pulumi:"versionAliases"`
	// The description of this version.
	VersionDescription *string `pulumi:"versionDescription"`
}

A trained machine learning Model.

type GoogleCloudAiplatformV1ModelArgs 

type GoogleCloudAiplatformV1ModelArgs struct {
	// Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models or Large Models.
	ArtifactUri pulumi.StringPtrInput `pulumi:"artifactUri"`
	// Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models or Large Models.
	ContainerSpec GoogleCloudAiplatformV1ModelContainerSpecPtrInput `pulumi:"containerSpec"`
	// The description of the Model.
	Description pulumi.StringPtrInput `pulumi:"description"`
	// The display name of the Model. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringInput `pulumi:"displayName"`
	// Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput `pulumi:"encryptionSpec"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput `pulumi:"etag"`
	// The default explanation specification for this Model. The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated. All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob. If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.
	ExplanationSpec GoogleCloudAiplatformV1ExplanationSpecPtrInput `pulumi:"explanationSpec"`
	// The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels pulumi.StringMapInput `pulumi:"labels"`
	// Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
	Metadata pulumi.Input `pulumi:"metadata"`
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	MetadataSchemaUri pulumi.StringPtrInput `pulumi:"metadataSchemaUri"`
	// The resource name of the Model.
	Name pulumi.StringPtrInput `pulumi:"name"`
	// Optional. This field is populated if the model is produced by a pipeline job.
	PipelineJob pulumi.StringPtrInput `pulumi:"pipelineJob"`
	// The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.
	PredictSchemata GoogleCloudAiplatformV1PredictSchemataPtrInput `pulumi:"predictSchemata"`
	// User provided version aliases so that a model version can be referenced via alias (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_alias}` instead of auto-generated version id (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_id})`. The format is a-z{0,126}[a-z0-9] to distinguish from version_id. A default version alias will be created for the first version of the model, and there must be exactly one default version alias for a model.
	VersionAliases pulumi.StringArrayInput `pulumi:"versionAliases"`
	// The description of this version.
	VersionDescription pulumi.StringPtrInput `pulumi:"versionDescription"`
}

A trained machine learning Model.

func (GoogleCloudAiplatformV1ModelArgs) ElementType 

func (GoogleCloudAiplatformV1ModelArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelArgs) ToGoogleCloudAiplatformV1ModelOutput 

func (i GoogleCloudAiplatformV1ModelArgs) ToGoogleCloudAiplatformV1ModelOutput() GoogleCloudAiplatformV1ModelOutput

func (GoogleCloudAiplatformV1ModelArgs) ToGoogleCloudAiplatformV1ModelOutputWithContext 

func (i GoogleCloudAiplatformV1ModelArgs) ToGoogleCloudAiplatformV1ModelOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelOutput

func (GoogleCloudAiplatformV1ModelArgs) ToGoogleCloudAiplatformV1ModelPtrOutput 

func (i GoogleCloudAiplatformV1ModelArgs) ToGoogleCloudAiplatformV1ModelPtrOutput() GoogleCloudAiplatformV1ModelPtrOutput

func (GoogleCloudAiplatformV1ModelArgs) ToGoogleCloudAiplatformV1ModelPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ModelArgs) ToGoogleCloudAiplatformV1ModelPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelPtrOutput

type GoogleCloudAiplatformV1ModelContainerSpec 

type GoogleCloudAiplatformV1ModelContainerSpec struct {
	// Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
	Args []string `pulumi:"args"`
	// Immutable. Specifies the command that runs when the container starts. This overrides the container's [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
	Command []string `pulumi:"command"`
	// Immutable. Deployment timeout. TODO (b/306244185): Revise documentation before exposing.
	DeploymentTimeout *string `pulumi:"deploymentTimeout"`
	// Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: “` json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ]  “` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
	Env []GoogleCloudAiplatformV1EnvVar `pulumi:"env"`
	// Immutable. Specification for Kubernetes readiness probe. TODO (b/306244185): Revise documentation before exposing.
	HealthProbe *GoogleCloudAiplatformV1Probe `pulumi:"healthProbe"`
	// Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#health). For example, if you set this field to `/bar`, then Vertex AI intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/ DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
	HealthRoute *string `pulumi:"healthRoute"`
	// Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon ModelService.UploadModel, stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.
	ImageUri string `pulumi:"imageUri"`
	// Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to the first port on this list. Vertex AI also sends [liveness and health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness) to this port. If you do not specify this field, it defaults to following value: “` json [ { "containerPort": 8080 } ]  “` Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
	Ports []GoogleCloudAiplatformV1Port `pulumi:"ports"`
	// Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using projects.locations.endpoints.predict to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
	PredictRoute *string `pulumi:"predictRoute"`
	// Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes. TODO (b/306244185): Revise documentation before exposing.
	SharedMemorySizeMb *string `pulumi:"sharedMemorySizeMb"`
	// Immutable. Specification for Kubernetes startup probe. TODO (b/306244185): Revise documentation before exposing.
	StartupProbe *GoogleCloudAiplatformV1Probe `pulumi:"startupProbe"`
}

Specification of a container for serving predictions. Some fields in this message correspond to fields in the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

type GoogleCloudAiplatformV1ModelContainerSpecArgs 

type GoogleCloudAiplatformV1ModelContainerSpecArgs struct {
	// Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
	Args pulumi.StringArrayInput `pulumi:"args"`
	// Immutable. Specifies the command that runs when the container starts. This overrides the container's [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
	Command pulumi.StringArrayInput `pulumi:"command"`
	// Immutable. Deployment timeout. TODO (b/306244185): Revise documentation before exposing.
	DeploymentTimeout pulumi.StringPtrInput `pulumi:"deploymentTimeout"`
	// Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: “` json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ]  “` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
	Env GoogleCloudAiplatformV1EnvVarArrayInput `pulumi:"env"`
	// Immutable. Specification for Kubernetes readiness probe. TODO (b/306244185): Revise documentation before exposing.
	HealthProbe GoogleCloudAiplatformV1ProbePtrInput `pulumi:"healthProbe"`
	// Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#health). For example, if you set this field to `/bar`, then Vertex AI intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/ DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
	HealthRoute pulumi.StringPtrInput `pulumi:"healthRoute"`
	// Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon ModelService.UploadModel, stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.
	ImageUri pulumi.StringInput `pulumi:"imageUri"`
	// Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to the first port on this list. Vertex AI also sends [liveness and health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness) to this port. If you do not specify this field, it defaults to following value: “` json [ { "containerPort": 8080 } ]  “` Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
	Ports GoogleCloudAiplatformV1PortArrayInput `pulumi:"ports"`
	// Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using projects.locations.endpoints.predict to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
	PredictRoute pulumi.StringPtrInput `pulumi:"predictRoute"`
	// Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes. TODO (b/306244185): Revise documentation before exposing.
	SharedMemorySizeMb pulumi.StringPtrInput `pulumi:"sharedMemorySizeMb"`
	// Immutable. Specification for Kubernetes startup probe. TODO (b/306244185): Revise documentation before exposing.
	StartupProbe GoogleCloudAiplatformV1ProbePtrInput `pulumi:"startupProbe"`
}

Specification of a container for serving predictions. Some fields in this message correspond to fields in the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecArgs) ElementType 

func (GoogleCloudAiplatformV1ModelContainerSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelContainerSpecArgs) ToGoogleCloudAiplatformV1ModelContainerSpecOutput 

func (i GoogleCloudAiplatformV1ModelContainerSpecArgs) ToGoogleCloudAiplatformV1ModelContainerSpecOutput() GoogleCloudAiplatformV1ModelContainerSpecOutput

func (GoogleCloudAiplatformV1ModelContainerSpecArgs) ToGoogleCloudAiplatformV1ModelContainerSpecOutputWithContext 

func (i GoogleCloudAiplatformV1ModelContainerSpecArgs) ToGoogleCloudAiplatformV1ModelContainerSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelContainerSpecOutput

func (GoogleCloudAiplatformV1ModelContainerSpecArgs) ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutput 

func (i GoogleCloudAiplatformV1ModelContainerSpecArgs) ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutput() GoogleCloudAiplatformV1ModelContainerSpecPtrOutput

func (GoogleCloudAiplatformV1ModelContainerSpecArgs) ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ModelContainerSpecArgs) ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelContainerSpecPtrOutput

type GoogleCloudAiplatformV1ModelContainerSpecInput 

type GoogleCloudAiplatformV1ModelContainerSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelContainerSpecOutput() GoogleCloudAiplatformV1ModelContainerSpecOutput
	ToGoogleCloudAiplatformV1ModelContainerSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelContainerSpecOutput
}

GoogleCloudAiplatformV1ModelContainerSpecInput is an input type that accepts GoogleCloudAiplatformV1ModelContainerSpecArgs and GoogleCloudAiplatformV1ModelContainerSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelContainerSpecInput` via: 

GoogleCloudAiplatformV1ModelContainerSpecArgs{...}

type GoogleCloudAiplatformV1ModelContainerSpecOutput 

type GoogleCloudAiplatformV1ModelContainerSpecOutput struct{ *pulumi.OutputState }

Specification of a container for serving predictions. Some fields in this message correspond to fields in the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) Args 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) Args() pulumi.StringArrayOutput

Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) Command 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) Command() pulumi.StringArrayOutput

Immutable. Specifies the command that runs when the container starts. This overrides the container's [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) DeploymentTimeout 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) DeploymentTimeout() pulumi.StringPtrOutput

Immutable. Deployment timeout. TODO (b/306244185): Revise documentation before exposing.

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) ElementType 

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) Env 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) Env() GoogleCloudAiplatformV1EnvVarArrayOutput

Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: ``` json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ] ``` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) HealthProbe 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) HealthProbe() GoogleCloudAiplatformV1ProbePtrOutput

Immutable. Specification for Kubernetes readiness probe. TODO (b/306244185): Revise documentation before exposing.

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) HealthRoute 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) HealthRoute() pulumi.StringPtrOutput

Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#health). For example, if you set this field to `/bar`, then Vertex AI intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/ DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) ImageUri 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) ImageUri() pulumi.StringOutput

Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon ModelService.UploadModel, stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) Ports 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) Ports() GoogleCloudAiplatformV1PortArrayOutput

Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to the first port on this list. Vertex AI also sends [liveness and health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness) to this port. If you do not specify this field, it defaults to following value: ``` json [ { "containerPort": 8080 } ] ``` Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) PredictRoute 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) PredictRoute() pulumi.StringPtrOutput

Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using projects.locations.endpoints.predict to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) SharedMemorySizeMb 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) SharedMemorySizeMb() pulumi.StringPtrOutput

Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes. TODO (b/306244185): Revise documentation before exposing.

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) StartupProbe 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) StartupProbe() GoogleCloudAiplatformV1ProbePtrOutput

Immutable. Specification for Kubernetes startup probe. TODO (b/306244185): Revise documentation before exposing.

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) ToGoogleCloudAiplatformV1ModelContainerSpecOutput 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) ToGoogleCloudAiplatformV1ModelContainerSpecOutput() GoogleCloudAiplatformV1ModelContainerSpecOutput

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) ToGoogleCloudAiplatformV1ModelContainerSpecOutputWithContext 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) ToGoogleCloudAiplatformV1ModelContainerSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelContainerSpecOutput

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutput 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutput() GoogleCloudAiplatformV1ModelContainerSpecPtrOutput

func (GoogleCloudAiplatformV1ModelContainerSpecOutput) ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelContainerSpecOutput) ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelContainerSpecPtrOutput

type GoogleCloudAiplatformV1ModelContainerSpecPtrInput 

type GoogleCloudAiplatformV1ModelContainerSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutput() GoogleCloudAiplatformV1ModelContainerSpecPtrOutput
	ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelContainerSpecPtrOutput
}

GoogleCloudAiplatformV1ModelContainerSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1ModelContainerSpecArgs, GoogleCloudAiplatformV1ModelContainerSpecPtr and GoogleCloudAiplatformV1ModelContainerSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelContainerSpecPtrInput` via: 

        GoogleCloudAiplatformV1ModelContainerSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ModelContainerSpecPtr 

func GoogleCloudAiplatformV1ModelContainerSpecPtr(v *GoogleCloudAiplatformV1ModelContainerSpecArgs) GoogleCloudAiplatformV1ModelContainerSpecPtrInput

type GoogleCloudAiplatformV1ModelContainerSpecPtrOutput 

type GoogleCloudAiplatformV1ModelContainerSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) Args 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) Args() pulumi.StringArrayOutput

Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) Command 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) Command() pulumi.StringArrayOutput

Immutable. Specifies the command that runs when the container starts. This overrides the container's [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) DeploymentTimeout 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) DeploymentTimeout() pulumi.StringPtrOutput

Immutable. Deployment timeout. TODO (b/306244185): Revise documentation before exposing.

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) Elem() GoogleCloudAiplatformV1ModelContainerSpecOutput

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) Env 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) Env() GoogleCloudAiplatformV1EnvVarArrayOutput

Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: ``` json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ] ``` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) HealthProbe 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) HealthProbe() GoogleCloudAiplatformV1ProbePtrOutput

Immutable. Specification for Kubernetes readiness probe. TODO (b/306244185): Revise documentation before exposing.

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) HealthRoute 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) HealthRoute() pulumi.StringPtrOutput

Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#health). For example, if you set this field to `/bar`, then Vertex AI intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/ DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) ImageUri 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) ImageUri() pulumi.StringPtrOutput

Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon ModelService.UploadModel, stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) Ports 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) Ports() GoogleCloudAiplatformV1PortArrayOutput

Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to the first port on this list. Vertex AI also sends [liveness and health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness) to this port. If you do not specify this field, it defaults to following value: ``` json [ { "containerPort": 8080 } ] ``` Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) PredictRoute 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) PredictRoute() pulumi.StringPtrOutput

Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using projects.locations.endpoints.predict to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) SharedMemorySizeMb 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) SharedMemorySizeMb() pulumi.StringPtrOutput

Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes. TODO (b/306244185): Revise documentation before exposing.

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) StartupProbe 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) StartupProbe() GoogleCloudAiplatformV1ProbePtrOutput

Immutable. Specification for Kubernetes startup probe. TODO (b/306244185): Revise documentation before exposing.

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutput 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutput() GoogleCloudAiplatformV1ModelContainerSpecPtrOutput

func (GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelContainerSpecPtrOutput) ToGoogleCloudAiplatformV1ModelContainerSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelContainerSpecPtrOutput

type GoogleCloudAiplatformV1ModelContainerSpecResponse 

type GoogleCloudAiplatformV1ModelContainerSpecResponse struct {
	// Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
	Args []string `pulumi:"args"`
	// Immutable. Specifies the command that runs when the container starts. This overrides the container's [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
	Command []string `pulumi:"command"`
	// Immutable. Deployment timeout. TODO (b/306244185): Revise documentation before exposing.
	DeploymentTimeout string `pulumi:"deploymentTimeout"`
	// Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: “` json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ]  “` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
	Env []GoogleCloudAiplatformV1EnvVarResponse `pulumi:"env"`
	// Immutable. Specification for Kubernetes readiness probe. TODO (b/306244185): Revise documentation before exposing.
	HealthProbe GoogleCloudAiplatformV1ProbeResponse `pulumi:"healthProbe"`
	// Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#health). For example, if you set this field to `/bar`, then Vertex AI intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/ DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
	HealthRoute string `pulumi:"healthRoute"`
	// Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon ModelService.UploadModel, stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.
	ImageUri string `pulumi:"imageUri"`
	// Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to the first port on this list. Vertex AI also sends [liveness and health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness) to this port. If you do not specify this field, it defaults to following value: “` json [ { "containerPort": 8080 } ]  “` Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).
	Ports []GoogleCloudAiplatformV1PortResponse `pulumi:"ports"`
	// Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using projects.locations.endpoints.predict to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)
	PredictRoute string `pulumi:"predictRoute"`
	// Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes. TODO (b/306244185): Revise documentation before exposing.
	SharedMemorySizeMb string `pulumi:"sharedMemorySizeMb"`
	// Immutable. Specification for Kubernetes startup probe. TODO (b/306244185): Revise documentation before exposing.
	StartupProbe GoogleCloudAiplatformV1ProbeResponse `pulumi:"startupProbe"`
}

Specification of a container for serving predictions. Some fields in this message correspond to fields in the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

type GoogleCloudAiplatformV1ModelContainerSpecResponseOutput 

type GoogleCloudAiplatformV1ModelContainerSpecResponseOutput struct{ *pulumi.OutputState }

Specification of a container for serving predictions. Some fields in this message correspond to fields in the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) Args 

func (o GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) Args() pulumi.StringArrayOutput

Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) Command 

func (o GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) Command() pulumi.StringArrayOutput

Immutable. Specifies the command that runs when the container starts. This overrides the container's [ENTRYPOINT](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) DeploymentTimeout 

func (o GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) DeploymentTimeout() pulumi.StringOutput

Immutable. Deployment timeout. TODO (b/306244185): Revise documentation before exposing.

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) Env 

func (o GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) Env() GoogleCloudAiplatformV1EnvVarResponseArrayOutput

Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: ``` json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ] ``` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) HealthProbe 

func (o GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) HealthProbe() GoogleCloudAiplatformV1ProbeResponseOutput

Immutable. Specification for Kubernetes readiness probe. TODO (b/306244185): Revise documentation before exposing.

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) HealthRoute 

func (o GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) HealthRoute() pulumi.StringOutput

Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#health). For example, if you set this field to `/bar`, then Vertex AI intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/ DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) ImageUri 

func (o GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) ImageUri() pulumi.StringOutput

Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon ModelService.UploadModel, stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre-built-containers) in this field.

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) Ports 

func (o GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) Ports() GoogleCloudAiplatformV1PortResponseArrayOutput

Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to the first port on this list. Vertex AI also sends [liveness and health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#liveness) to this port. If you do not specify this field, it defaults to following value: ``` json [ { "containerPort": 8080 } ] ``` Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core).

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) PredictRoute 

func (o GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) PredictRoute() pulumi.StringOutput

Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using projects.locations.endpoints.predict to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom-container-requirements#aip-variables).)

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) SharedMemorySizeMb 

func (o GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) SharedMemorySizeMb() pulumi.StringOutput

Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes. TODO (b/306244185): Revise documentation before exposing.

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) StartupProbe 

func (o GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) StartupProbe() GoogleCloudAiplatformV1ProbeResponseOutput

Immutable. Specification for Kubernetes startup probe. TODO (b/306244185): Revise documentation before exposing.

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) ToGoogleCloudAiplatformV1ModelContainerSpecResponseOutput 

func (o GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) ToGoogleCloudAiplatformV1ModelContainerSpecResponseOutput() GoogleCloudAiplatformV1ModelContainerSpecResponseOutput

func (GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) ToGoogleCloudAiplatformV1ModelContainerSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelContainerSpecResponseOutput) ToGoogleCloudAiplatformV1ModelContainerSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelContainerSpecResponseOutput

type GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponse 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponse struct {
	// The created BigQuery table to store logs. Customer could do their own query & analysis. Format: `bq://.model_deployment_monitoring_._`
	BigqueryTablePath string `pulumi:"bigqueryTablePath"`
	// The source of log.
	LogSource string `pulumi:"logSource"`
	// The type of log.
	LogType string `pulumi:"logType"`
}

ModelDeploymentMonitoringBigQueryTable specifies the BigQuery table name as well as some information of the logs stored in this table.

type GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput

type GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput struct{ *pulumi.OutputState }

ModelDeploymentMonitoringBigQueryTable specifies the BigQuery table name as well as some information of the logs stored in this table.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput) BigqueryTablePath 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput) BigqueryTablePath() pulumi.StringOutput

The created BigQuery table to store logs. Customer could do their own query & analysis. Format: `bq://.model_deployment_monitoring_._`

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput) LogSource 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput) LogSource() pulumi.StringOutput

The source of log.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput) LogType 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput) LogType() pulumi.StringOutput

The type of log.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseOutput

type GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponse 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponse struct {
	// The time that most recent monitoring pipelines that is related to this run.
	RunTime string `pulumi:"runTime"`
	// The status of the most recent monitoring pipeline.
	Status GoogleRpcStatusResponse `pulumi:"status"`
}

All metadata of most recent monitoring pipelines.

type GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput struct{ *pulumi.OutputState }

All metadata of most recent monitoring pipelines.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput) RunTime 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput) RunTime() pulumi.StringOutput

The time that most recent monitoring pipelines that is related to this run.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput) Status 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput) Status() GoogleRpcStatusResponseOutput

The status of the most recent monitoring pipeline.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfig 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfig struct {
	// The DeployedModel ID of the objective config.
	DeployedModelId *string `pulumi:"deployedModelId"`
	// The objective config of for the modelmonitoring job of this deployed model.
	ObjectiveConfig *GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig `pulumi:"objectiveConfig"`
}

ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig.

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArgs 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArgs struct {
	// The DeployedModel ID of the objective config.
	DeployedModelId pulumi.StringPtrInput `pulumi:"deployedModelId"`
	// The objective config of for the modelmonitoring job of this deployed model.
	ObjectiveConfig GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrInput `pulumi:"objectiveConfig"`
}

ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArgs) ElementType 

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArgs) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput 

func (i GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArgs) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArgs) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutputWithContext 

func (i GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArgs) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArray 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArray []GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigInput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArray) ElementType 

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArray) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArray) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput 

func (i GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArray) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArray) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutputWithContext 

func (i GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArray) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayInput 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput
	ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput
}

GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayInput is an input type that accepts GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArray and GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayInput` via: 

GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArray{ GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArgs{...} }

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput) ElementType 

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput) Index 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutputWithContext 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayOutput

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigInput 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput
	ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput
}

GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigInput is an input type that accepts GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArgs and GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigInput` via: 

GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArgs{...}

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput struct{ *pulumi.OutputState }

ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput) DeployedModelId 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput) DeployedModelId() pulumi.StringPtrOutput

The DeployedModel ID of the objective config.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput) ElementType 

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput) ObjectiveConfig 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput) ObjectiveConfig() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput

The objective config of for the modelmonitoring job of this deployed model.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutputWithContext 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigOutput

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponse 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponse struct {
	// The DeployedModel ID of the objective config.
	DeployedModelId string `pulumi:"deployedModelId"`
	// The objective config of for the modelmonitoring job of this deployed model.
	ObjectiveConfig GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponse `pulumi:"objectiveConfig"`
}

ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig.

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput struct{ *pulumi.OutputState }

ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput) DeployedModelId 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput) DeployedModelId() pulumi.StringOutput

The DeployedModel ID of the objective config.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput) ObjectiveConfig 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput) ObjectiveConfig() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput

The objective config of for the modelmonitoring job of this deployed model.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseOutput

type GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfig 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfig struct {
	// The model monitoring job scheduling interval. It will be rounded up to next full hour. This defines how often the monitoring jobs are triggered.
	MonitorInterval string `pulumi:"monitorInterval"`
	// The time window of the prediction data being included in each prediction dataset. This window specifies how long the data should be collected from historical model results for each run. If not set, ModelDeploymentMonitoringScheduleConfig.monitor_interval will be used. e.g. If currently the cutoff time is 2022-01-08 14:30:00 and the monitor_window is set to be 3600, then data from 2022-01-08 13:30:00 to 2022-01-08 14:30:00 will be retrieved and aggregated to calculate the monitoring statistics.
	MonitorWindow *string `pulumi:"monitorWindow"`
}

The config for scheduling monitoring job.

type GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigArgs 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigArgs struct {
	// The model monitoring job scheduling interval. It will be rounded up to next full hour. This defines how often the monitoring jobs are triggered.
	MonitorInterval pulumi.StringInput `pulumi:"monitorInterval"`
	// The time window of the prediction data being included in each prediction dataset. This window specifies how long the data should be collected from historical model results for each run. If not set, ModelDeploymentMonitoringScheduleConfig.monitor_interval will be used. e.g. If currently the cutoff time is 2022-01-08 14:30:00 and the monitor_window is set to be 3600, then data from 2022-01-08 13:30:00 to 2022-01-08 14:30:00 will be retrieved and aggregated to calculate the monitoring statistics.
	MonitorWindow pulumi.StringPtrInput `pulumi:"monitorWindow"`
}

The config for scheduling monitoring job.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigArgs) ElementType 

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigArgs) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput 

func (i GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigArgs) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigArgs) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutputWithContext 

func (i GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigArgs) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput

type GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigInput 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput
	ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput
}

GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigInput is an input type that accepts GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigArgs and GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigInput` via: 

GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigArgs{...}

type GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput struct{ *pulumi.OutputState }

The config for scheduling monitoring job.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput) ElementType 

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput) MonitorInterval 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput) MonitorInterval() pulumi.StringOutput

The model monitoring job scheduling interval. It will be rounded up to next full hour. This defines how often the monitoring jobs are triggered.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput) MonitorWindow 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput) MonitorWindow() pulumi.StringPtrOutput

The time window of the prediction data being included in each prediction dataset. This window specifies how long the data should be collected from historical model results for each run. If not set, ModelDeploymentMonitoringScheduleConfig.monitor_interval will be used. e.g. If currently the cutoff time is 2022-01-08 14:30:00 and the monitor_window is set to be 3600, then data from 2022-01-08 13:30:00 to 2022-01-08 14:30:00 will be retrieved and aggregated to calculate the monitoring statistics.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutputWithContext 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigOutput

type GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponse 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponse struct {
	// The model monitoring job scheduling interval. It will be rounded up to next full hour. This defines how often the monitoring jobs are triggered.
	MonitorInterval string `pulumi:"monitorInterval"`
	// The time window of the prediction data being included in each prediction dataset. This window specifies how long the data should be collected from historical model results for each run. If not set, ModelDeploymentMonitoringScheduleConfig.monitor_interval will be used. e.g. If currently the cutoff time is 2022-01-08 14:30:00 and the monitor_window is set to be 3600, then data from 2022-01-08 13:30:00 to 2022-01-08 14:30:00 will be retrieved and aggregated to calculate the monitoring statistics.
	MonitorWindow string `pulumi:"monitorWindow"`
}

The config for scheduling monitoring job.

type GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput 

type GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput struct{ *pulumi.OutputState }

The config for scheduling monitoring job.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput) MonitorInterval 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput) MonitorInterval() pulumi.StringOutput

The model monitoring job scheduling interval. It will be rounded up to next full hour. This defines how often the monitoring jobs are triggered.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput) MonitorWindow 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput) MonitorWindow() pulumi.StringOutput

The time window of the prediction data being included in each prediction dataset. This window specifies how long the data should be collected from historical model results for each run. If not set, ModelDeploymentMonitoringScheduleConfig.monitor_interval will be used. e.g. If currently the cutoff time is 2022-01-08 14:30:00 and the monitor_window is set to be 3600, then data from 2022-01-08 13:30:00 to 2022-01-08 14:30:00 will be retrieved and aggregated to calculate the monitoring statistics.

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput() GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput

func (GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput) ToGoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput

type GoogleCloudAiplatformV1ModelExportFormatResponse 

type GoogleCloudAiplatformV1ModelExportFormatResponse struct {
	// The content of this Model that may be exported.
	ExportableContents []string `pulumi:"exportableContents"`
}

Represents export format supported by the Model. All formats export to Google Cloud Storage.

type GoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput 

type GoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1ModelExportFormatResponseOutput

func (GoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput) ToGoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput 

func (o GoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput) ToGoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput() GoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput

func (GoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput) ToGoogleCloudAiplatformV1ModelExportFormatResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput) ToGoogleCloudAiplatformV1ModelExportFormatResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput

type GoogleCloudAiplatformV1ModelExportFormatResponseOutput 

type GoogleCloudAiplatformV1ModelExportFormatResponseOutput struct{ *pulumi.OutputState }

Represents export format supported by the Model. All formats export to Google Cloud Storage.

func (GoogleCloudAiplatformV1ModelExportFormatResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelExportFormatResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelExportFormatResponseOutput) ExportableContents 

func (o GoogleCloudAiplatformV1ModelExportFormatResponseOutput) ExportableContents() pulumi.StringArrayOutput

The content of this Model that may be exported.

func (GoogleCloudAiplatformV1ModelExportFormatResponseOutput) ToGoogleCloudAiplatformV1ModelExportFormatResponseOutput 

func (o GoogleCloudAiplatformV1ModelExportFormatResponseOutput) ToGoogleCloudAiplatformV1ModelExportFormatResponseOutput() GoogleCloudAiplatformV1ModelExportFormatResponseOutput

func (GoogleCloudAiplatformV1ModelExportFormatResponseOutput) ToGoogleCloudAiplatformV1ModelExportFormatResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelExportFormatResponseOutput) ToGoogleCloudAiplatformV1ModelExportFormatResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelExportFormatResponseOutput

type GoogleCloudAiplatformV1ModelInput 

type GoogleCloudAiplatformV1ModelInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelOutput() GoogleCloudAiplatformV1ModelOutput
	ToGoogleCloudAiplatformV1ModelOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelOutput
}

GoogleCloudAiplatformV1ModelInput is an input type that accepts GoogleCloudAiplatformV1ModelArgs and GoogleCloudAiplatformV1ModelOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelInput` via: 

GoogleCloudAiplatformV1ModelArgs{...}

type GoogleCloudAiplatformV1ModelMonitoringAlertConfig 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfig struct {
	// Email alert config.
	EmailAlertConfig *GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfig `pulumi:"emailAlertConfig"`
	// Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.
	EnableLogging *bool `pulumi:"enableLogging"`
	// Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`
	NotificationChannels []string `pulumi:"notificationChannels"`
}

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs struct {
	// Email alert config.
	EmailAlertConfig GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrInput `pulumi:"emailAlertConfig"`
	// Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.
	EnableLogging pulumi.BoolPtrInput `pulumi:"enableLogging"`
	// Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`
	NotificationChannels pulumi.StringArrayInput `pulumi:"notificationChannels"`
}

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfig 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfig struct {
	// The email addresses to send the alert.
	UserEmails []string `pulumi:"userEmails"`
}

The config for email alert.

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs struct {
	// The email addresses to send the alert.
	UserEmails pulumi.StringArrayInput `pulumi:"userEmails"`
}

The config for email alert.

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigInput 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput
	ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput
}

GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs and GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigInput` via: 

GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs{...}

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput struct{ *pulumi.OutputState }

The config for email alert.

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput) UserEmails 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput) UserEmails() pulumi.StringArrayOutput

The email addresses to send the alert.

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrInput 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput
	ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput
}

GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs, GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtr and GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrInput` via: 

        GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtr 

func GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtr(v *GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigArgs) GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrInput

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput) Elem() GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput) UserEmails 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput) UserEmails() pulumi.StringArrayOutput

The email addresses to send the alert.

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponse 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponse struct {
	// The email addresses to send the alert.
	UserEmails []string `pulumi:"userEmails"`
}

The config for email alert.

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput struct{ *pulumi.OutputState }

The config for email alert.

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput) UserEmails 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput) UserEmails() pulumi.StringArrayOutput

The email addresses to send the alert.

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigInput 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput
	ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput
}

GoogleCloudAiplatformV1ModelMonitoringAlertConfigInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs and GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringAlertConfigInput` via: 

GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs{...}

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) EmailAlertConfig 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) EmailAlertConfig() GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput

Email alert config.

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) EnableLogging 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) EnableLogging() pulumi.BoolPtrOutput

Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) NotificationChannels 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) NotificationChannels() pulumi.StringArrayOutput

Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrInput 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput
	ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput
}

GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs, GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtr and GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrInput` via: 

        GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtr 

func GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtr(v *GoogleCloudAiplatformV1ModelMonitoringAlertConfigArgs) GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrInput

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) Elem() GoogleCloudAiplatformV1ModelMonitoringAlertConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) EmailAlertConfig 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) EmailAlertConfig() GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigPtrOutput

Email alert config.

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) EnableLogging 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) EnableLogging() pulumi.BoolPtrOutput

Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) NotificationChannels 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) NotificationChannels() pulumi.StringArrayOutput

Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponse 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponse struct {
	// Email alert config.
	EmailAlertConfig GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponse `pulumi:"emailAlertConfig"`
	// Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.
	EnableLogging bool `pulumi:"enableLogging"`
	// Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`
	NotificationChannels []string `pulumi:"notificationChannels"`
}

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput 

type GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput) EmailAlertConfig 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput) EmailAlertConfig() GoogleCloudAiplatformV1ModelMonitoringAlertConfigEmailAlertConfigResponseOutput

Email alert config.

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput) EnableLogging 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput) EnableLogging() pulumi.BoolOutput

Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging.

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput) NotificationChannels 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput) NotificationChannels() pulumi.StringArrayOutput

Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/`

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput() GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput

func (GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfig struct {
	// The config for integrating with Vertex Explainable AI.
	ExplanationConfig *GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfig `pulumi:"explanationConfig"`
	// The config for drift of prediction data.
	PredictionDriftDetectionConfig *GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig `pulumi:"predictionDriftDetectionConfig"`
	// Training dataset for models. This field has to be set only if TrainingPredictionSkewDetectionConfig is specified.
	TrainingDataset *GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDataset `pulumi:"trainingDataset"`
	// The config for skew between training data and prediction data.
	TrainingPredictionSkewDetectionConfig *GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig `pulumi:"trainingPredictionSkewDetectionConfig"`
}

The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs struct {
	// The config for integrating with Vertex Explainable AI.
	ExplanationConfig GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrInput `pulumi:"explanationConfig"`
	// The config for drift of prediction data.
	PredictionDriftDetectionConfig GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrInput `pulumi:"predictionDriftDetectionConfig"`
	// Training dataset for models. This field has to be set only if TrainingPredictionSkewDetectionConfig is specified.
	TrainingDataset GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrInput `pulumi:"trainingDataset"`
	// The config for skew between training data and prediction data.
	TrainingPredictionSkewDetectionConfig GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrInput `pulumi:"trainingPredictionSkewDetectionConfig"`
}

The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfig 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfig struct {
	// If want to analyze the Vertex Explainable AI feature attribute scores or not. If set to true, Vertex AI will log the feature attributions from explain response and do the skew/drift detection for them.
	EnableFeatureAttributes *bool `pulumi:"enableFeatureAttributes"`
	// Predictions generated by the BatchPredictionJob using baseline dataset.
	ExplanationBaseline *GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline `pulumi:"explanationBaseline"`
}

The config for integrating with Vertex Explainable AI. Only applicable if the Model has explanation_spec populated.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs struct {
	// If want to analyze the Vertex Explainable AI feature attribute scores or not. If set to true, Vertex AI will log the feature attributions from explain response and do the skew/drift detection for them.
	EnableFeatureAttributes pulumi.BoolPtrInput `pulumi:"enableFeatureAttributes"`
	// Predictions generated by the BatchPredictionJob using baseline dataset.
	ExplanationBaseline GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrInput `pulumi:"explanationBaseline"`
}

The config for integrating with Vertex Explainable AI. Only applicable if the Model has explanation_spec populated.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline struct {
	// BigQuery location for BatchExplain output.
	Bigquery *GoogleCloudAiplatformV1BigQueryDestination `pulumi:"bigquery"`
	// Cloud Storage location for BatchExplain output.
	Gcs *GoogleCloudAiplatformV1GcsDestination `pulumi:"gcs"`
	// The storage format of the predictions generated BatchPrediction job.
	PredictionFormat *GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat `pulumi:"predictionFormat"`
}

Output from BatchPredictionJob for Model Monitoring baseline dataset, which can be used to generate baseline attribution scores.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs struct {
	// BigQuery location for BatchExplain output.
	Bigquery GoogleCloudAiplatformV1BigQueryDestinationPtrInput `pulumi:"bigquery"`
	// Cloud Storage location for BatchExplain output.
	Gcs GoogleCloudAiplatformV1GcsDestinationPtrInput `pulumi:"gcs"`
	// The storage format of the predictions generated BatchPrediction job.
	PredictionFormat GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrInput `pulumi:"predictionFormat"`
}

Output from BatchPredictionJob for Model Monitoring baseline dataset, which can be used to generate baseline attribution scores.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput
}

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs and GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineInput` via: 

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs{...}

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput struct{ *pulumi.OutputState }

Output from BatchPredictionJob for Model Monitoring baseline dataset, which can be used to generate baseline attribution scores.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) Bigquery 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) Bigquery() GoogleCloudAiplatformV1BigQueryDestinationPtrOutput

BigQuery location for BatchExplain output.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) Gcs 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) Gcs() GoogleCloudAiplatformV1GcsDestinationPtrOutput

Cloud Storage location for BatchExplain output.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) PredictionFormat 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) PredictionFormat() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput

The storage format of the predictions generated BatchPrediction job.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat string

The storage format of the predictions generated BatchPrediction job.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput 

func (e GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutputWithContext 

func (e GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput 

func (e GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutputWithContext 

func (e GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToStringOutput 

func (e GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormat) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput
}

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatArgs and GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatInput` via: 

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatArgs{...}

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput
}

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtr 

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtr(v string) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrInput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput) Elem() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput
}

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs, GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtr and GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrInput` via: 

        GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtr 

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtr(v *GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineArgs) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrInput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) Bigquery 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) Bigquery() GoogleCloudAiplatformV1BigQueryDestinationPtrOutput

BigQuery location for BatchExplain output.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) Elem 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) Elem() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) Gcs 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) Gcs() GoogleCloudAiplatformV1GcsDestinationPtrOutput

Cloud Storage location for BatchExplain output.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) PredictionFormat 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) PredictionFormat() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePredictionFormatPtrOutput

The storage format of the predictions generated BatchPrediction job.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponse 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponse struct {
	// BigQuery location for BatchExplain output.
	Bigquery GoogleCloudAiplatformV1BigQueryDestinationResponse `pulumi:"bigquery"`
	// Cloud Storage location for BatchExplain output.
	Gcs GoogleCloudAiplatformV1GcsDestinationResponse `pulumi:"gcs"`
	// The storage format of the predictions generated BatchPrediction job.
	PredictionFormat string `pulumi:"predictionFormat"`
}

Output from BatchPredictionJob for Model Monitoring baseline dataset, which can be used to generate baseline attribution scores.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput struct{ *pulumi.OutputState }

Output from BatchPredictionJob for Model Monitoring baseline dataset, which can be used to generate baseline attribution scores.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput) Bigquery 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput) Bigquery() GoogleCloudAiplatformV1BigQueryDestinationResponseOutput

BigQuery location for BatchExplain output.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput) Gcs 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput) Gcs() GoogleCloudAiplatformV1GcsDestinationResponseOutput

Cloud Storage location for BatchExplain output.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput) PredictionFormat 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput) PredictionFormat() pulumi.StringOutput

The storage format of the predictions generated BatchPrediction job.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput
}

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs and GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigInput` via: 

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs{...}

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput struct{ *pulumi.OutputState }

The config for integrating with Vertex Explainable AI. Only applicable if the Model has explanation_spec populated.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) EnableFeatureAttributes 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) EnableFeatureAttributes() pulumi.BoolPtrOutput

If want to analyze the Vertex Explainable AI feature attribute scores or not. If set to true, Vertex AI will log the feature attributions from explain response and do the skew/drift detection for them.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) ExplanationBaseline 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) ExplanationBaseline() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput

Predictions generated by the BatchPredictionJob using baseline dataset.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput
}

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs, GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtr and GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrInput` via: 

        GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtr 

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtr(v *GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigArgs) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrInput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput) Elem() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput) EnableFeatureAttributes 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput) EnableFeatureAttributes() pulumi.BoolPtrOutput

If want to analyze the Vertex Explainable AI feature attribute scores or not. If set to true, Vertex AI will log the feature attributions from explain response and do the skew/drift detection for them.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput) ExplanationBaseline 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput) ExplanationBaseline() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselinePtrOutput

Predictions generated by the BatchPredictionJob using baseline dataset.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponse 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponse struct {
	// If want to analyze the Vertex Explainable AI feature attribute scores or not. If set to true, Vertex AI will log the feature attributions from explain response and do the skew/drift detection for them.
	EnableFeatureAttributes bool `pulumi:"enableFeatureAttributes"`
	// Predictions generated by the BatchPredictionJob using baseline dataset.
	ExplanationBaseline GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponse `pulumi:"explanationBaseline"`
}

The config for integrating with Vertex Explainable AI. Only applicable if the Model has explanation_spec populated.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput struct{ *pulumi.OutputState }

The config for integrating with Vertex Explainable AI. Only applicable if the Model has explanation_spec populated.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput) EnableFeatureAttributes 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput) EnableFeatureAttributes() pulumi.BoolOutput

If want to analyze the Vertex Explainable AI feature attribute scores or not. If set to true, Vertex AI will log the feature attributions from explain response and do the skew/drift detection for them.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput) ExplanationBaseline 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput) ExplanationBaseline() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaselineResponseOutput

Predictions generated by the BatchPredictionJob using baseline dataset.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput
}

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs and GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigInput` via: 

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs{...}

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput struct{ *pulumi.OutputState }

The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) ExplanationConfig 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) ExplanationConfig() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput

The config for integrating with Vertex Explainable AI.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) PredictionDriftDetectionConfig 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) PredictionDriftDetectionConfig() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput

The config for drift of prediction data.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) TrainingDataset 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) TrainingDataset() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput

Training dataset for models. This field has to be set only if TrainingPredictionSkewDetectionConfig is specified.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) TrainingPredictionSkewDetectionConfig 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput) TrainingPredictionSkewDetectionConfig() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput

The config for skew between training data and prediction data.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig struct {
	// Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows.
	AttributionScoreDriftThresholds map[string]string `pulumi:"attributionScoreDriftThresholds"`
	// Drift anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
	DefaultDriftThreshold *GoogleCloudAiplatformV1ThresholdConfig `pulumi:"defaultDriftThreshold"`
	// Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws.
	DriftThresholds map[string]string `pulumi:"driftThresholds"`
}

The config for Prediction data drift detection.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs struct {
	// Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows.
	AttributionScoreDriftThresholds pulumi.StringMapInput `pulumi:"attributionScoreDriftThresholds"`
	// Drift anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
	DefaultDriftThreshold GoogleCloudAiplatformV1ThresholdConfigPtrInput `pulumi:"defaultDriftThreshold"`
	// Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws.
	DriftThresholds pulumi.StringMapInput `pulumi:"driftThresholds"`
}

The config for Prediction data drift detection.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput
}

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs and GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigInput` via: 

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs{...}

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput struct{ *pulumi.OutputState }

The config for Prediction data drift detection.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) AttributionScoreDriftThresholds 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) AttributionScoreDriftThresholds() pulumi.StringMapOutput

Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) DefaultDriftThreshold 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) DefaultDriftThreshold() GoogleCloudAiplatformV1ThresholdConfigPtrOutput

Drift anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) DriftThresholds 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) DriftThresholds() pulumi.StringMapOutput

Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput
}

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs, GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtr and GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrInput` via: 

        GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtr 

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtr(v *GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigArgs) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrInput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) AttributionScoreDriftThresholds 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) AttributionScoreDriftThresholds() pulumi.StringMapOutput

Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) DefaultDriftThreshold 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) DefaultDriftThreshold() GoogleCloudAiplatformV1ThresholdConfigPtrOutput

Drift anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) DriftThresholds 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) DriftThresholds() pulumi.StringMapOutput

Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) Elem() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponse 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponse struct {
	// Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows.
	AttributionScoreDriftThresholds map[string]string `pulumi:"attributionScoreDriftThresholds"`
	// Drift anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
	DefaultDriftThreshold GoogleCloudAiplatformV1ThresholdConfigResponse `pulumi:"defaultDriftThreshold"`
	// Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws.
	DriftThresholds map[string]string `pulumi:"driftThresholds"`
}

The config for Prediction data drift detection.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput struct{ *pulumi.OutputState }

The config for Prediction data drift detection.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput) AttributionScoreDriftThresholds 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput) AttributionScoreDriftThresholds() pulumi.StringMapOutput

Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput) DefaultDriftThreshold 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput) DefaultDriftThreshold() GoogleCloudAiplatformV1ThresholdConfigResponseOutput

Drift anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput) DriftThresholds 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput) DriftThresholds() pulumi.StringMapOutput

Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput
}

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs, GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtr and GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrInput` via: 

        GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtr 

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtr(v *GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigArgs) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrInput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) Elem() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) ExplanationConfig 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) ExplanationConfig() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigPtrOutput

The config for integrating with Vertex Explainable AI.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) PredictionDriftDetectionConfig 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) PredictionDriftDetectionConfig() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigPtrOutput

The config for drift of prediction data.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) TrainingDataset 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) TrainingDataset() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput

Training dataset for models. This field has to be set only if TrainingPredictionSkewDetectionConfig is specified.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) TrainingPredictionSkewDetectionConfig 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPtrOutput) TrainingPredictionSkewDetectionConfig() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput

The config for skew between training data and prediction data.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponse 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponse struct {
	// The config for integrating with Vertex Explainable AI.
	ExplanationConfig GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponse `pulumi:"explanationConfig"`
	// The config for drift of prediction data.
	PredictionDriftDetectionConfig GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponse `pulumi:"predictionDriftDetectionConfig"`
	// Training dataset for models. This field has to be set only if TrainingPredictionSkewDetectionConfig is specified.
	TrainingDataset GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponse `pulumi:"trainingDataset"`
	// The config for skew between training data and prediction data.
	TrainingPredictionSkewDetectionConfig GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponse `pulumi:"trainingPredictionSkewDetectionConfig"`
}

The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput struct{ *pulumi.OutputState }

The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) ExplanationConfig 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) ExplanationConfig() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigExplanationConfigResponseOutput

The config for integrating with Vertex Explainable AI.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) PredictionDriftDetectionConfig 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) PredictionDriftDetectionConfig() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfigResponseOutput

The config for drift of prediction data.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) TrainingDataset 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) TrainingDataset() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput

Training dataset for models. This field has to be set only if TrainingPredictionSkewDetectionConfig is specified.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) TrainingPredictionSkewDetectionConfig 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigResponseOutput) TrainingPredictionSkewDetectionConfig() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput

The config for skew between training data and prediction data.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDataset 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDataset struct {
	// The BigQuery table of the unmanaged Dataset used to train this Model.
	BigquerySource *GoogleCloudAiplatformV1BigQuerySource `pulumi:"bigquerySource"`
	// Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: "tf-record" The source file is a TFRecord file. "csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.
	DataFormat *string `pulumi:"dataFormat"`
	// The resource name of the Dataset used to train this Model.
	Dataset *string `pulumi:"dataset"`
	// The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.
	GcsSource *GoogleCloudAiplatformV1GcsSource `pulumi:"gcsSource"`
	// Strategy to sample data from Training Dataset. If not set, we process the whole dataset.
	LoggingSamplingStrategy *GoogleCloudAiplatformV1SamplingStrategy `pulumi:"loggingSamplingStrategy"`
	// The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.
	TargetField *string `pulumi:"targetField"`
}

Training Dataset information.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs struct {
	// The BigQuery table of the unmanaged Dataset used to train this Model.
	BigquerySource GoogleCloudAiplatformV1BigQuerySourcePtrInput `pulumi:"bigquerySource"`
	// Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: "tf-record" The source file is a TFRecord file. "csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.
	DataFormat pulumi.StringPtrInput `pulumi:"dataFormat"`
	// The resource name of the Dataset used to train this Model.
	Dataset pulumi.StringPtrInput `pulumi:"dataset"`
	// The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.
	GcsSource GoogleCloudAiplatformV1GcsSourcePtrInput `pulumi:"gcsSource"`
	// Strategy to sample data from Training Dataset. If not set, we process the whole dataset.
	LoggingSamplingStrategy GoogleCloudAiplatformV1SamplingStrategyPtrInput `pulumi:"loggingSamplingStrategy"`
	// The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.
	TargetField pulumi.StringPtrInput `pulumi:"targetField"`
}

Training Dataset information.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput
}

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs and GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetInput` via: 

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs{...}

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput struct{ *pulumi.OutputState }

Training Dataset information.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) BigquerySource 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) BigquerySource() GoogleCloudAiplatformV1BigQuerySourcePtrOutput

The BigQuery table of the unmanaged Dataset used to train this Model.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) DataFormat 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) DataFormat() pulumi.StringPtrOutput

Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: "tf-record" The source file is a TFRecord file. "csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) Dataset 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) Dataset() pulumi.StringPtrOutput

The resource name of the Dataset used to train this Model.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) GcsSource 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) GcsSource() GoogleCloudAiplatformV1GcsSourcePtrOutput

The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) LoggingSamplingStrategy 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) LoggingSamplingStrategy() GoogleCloudAiplatformV1SamplingStrategyPtrOutput

Strategy to sample data from Training Dataset. If not set, we process the whole dataset.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) TargetField 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) TargetField() pulumi.StringPtrOutput

The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput
}

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs, GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtr and GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrInput` via: 

        GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtr 

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtr(v *GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetArgs) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrInput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) BigquerySource 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) BigquerySource() GoogleCloudAiplatformV1BigQuerySourcePtrOutput

The BigQuery table of the unmanaged Dataset used to train this Model.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) DataFormat 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) DataFormat() pulumi.StringPtrOutput

Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: "tf-record" The source file is a TFRecord file. "csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) Dataset 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) Dataset() pulumi.StringPtrOutput

The resource name of the Dataset used to train this Model.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) Elem() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) GcsSource 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) GcsSource() GoogleCloudAiplatformV1GcsSourcePtrOutput

The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) LoggingSamplingStrategy 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) LoggingSamplingStrategy() GoogleCloudAiplatformV1SamplingStrategyPtrOutput

Strategy to sample data from Training Dataset. If not set, we process the whole dataset.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) TargetField 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) TargetField() pulumi.StringPtrOutput

The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponse 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponse struct {
	// The BigQuery table of the unmanaged Dataset used to train this Model.
	BigquerySource GoogleCloudAiplatformV1BigQuerySourceResponse `pulumi:"bigquerySource"`
	// Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: "tf-record" The source file is a TFRecord file. "csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.
	DataFormat string `pulumi:"dataFormat"`
	// The resource name of the Dataset used to train this Model.
	Dataset string `pulumi:"dataset"`
	// The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.
	GcsSource GoogleCloudAiplatformV1GcsSourceResponse `pulumi:"gcsSource"`
	// Strategy to sample data from Training Dataset. If not set, we process the whole dataset.
	LoggingSamplingStrategy GoogleCloudAiplatformV1SamplingStrategyResponse `pulumi:"loggingSamplingStrategy"`
	// The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.
	TargetField string `pulumi:"targetField"`
}

Training Dataset information.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput struct{ *pulumi.OutputState }

Training Dataset information.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) BigquerySource 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) BigquerySource() GoogleCloudAiplatformV1BigQuerySourceResponseOutput

The BigQuery table of the unmanaged Dataset used to train this Model.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) DataFormat 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) DataFormat() pulumi.StringOutput

Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: "tf-record" The source file is a TFRecord file. "csv" The source file is a CSV file. "jsonl" The source file is a JSONL file.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) Dataset 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) Dataset() pulumi.StringOutput

The resource name of the Dataset used to train this Model.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) GcsSource 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) GcsSource() GoogleCloudAiplatformV1GcsSourceResponseOutput

The Google Cloud Storage uri of the unmanaged Dataset used to train this Model.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) LoggingSamplingStrategy 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) LoggingSamplingStrategy() GoogleCloudAiplatformV1SamplingStrategyResponseOutput

Strategy to sample data from Training Dataset. If not set, we process the whole dataset.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) TargetField 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) TargetField() pulumi.StringOutput

The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingDatasetResponseOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig struct {
	// Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.
	AttributionScoreSkewThresholds map[string]string `pulumi:"attributionScoreSkewThresholds"`
	// Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
	DefaultSkewThreshold *GoogleCloudAiplatformV1ThresholdConfig `pulumi:"defaultSkewThreshold"`
	// Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.
	SkewThresholds map[string]string `pulumi:"skewThresholds"`
}

The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs struct {
	// Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.
	AttributionScoreSkewThresholds pulumi.StringMapInput `pulumi:"attributionScoreSkewThresholds"`
	// Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
	DefaultSkewThreshold GoogleCloudAiplatformV1ThresholdConfigPtrInput `pulumi:"defaultSkewThreshold"`
	// Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.
	SkewThresholds pulumi.StringMapInput `pulumi:"skewThresholds"`
}

The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput
}

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs and GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigInput` via: 

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs{...}

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput struct{ *pulumi.OutputState }

The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) AttributionScoreSkewThresholds 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) AttributionScoreSkewThresholds() pulumi.StringMapOutput

Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) DefaultSkewThreshold 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) DefaultSkewThreshold() GoogleCloudAiplatformV1ThresholdConfigPtrOutput

Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) SkewThresholds 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) SkewThresholds() pulumi.StringMapOutput

Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrInput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput
	ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput
}

GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs, GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtr and GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrInput` via: 

        GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtr 

func GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtr(v *GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigArgs) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrInput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) AttributionScoreSkewThresholds 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) AttributionScoreSkewThresholds() pulumi.StringMapOutput

Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) DefaultSkewThreshold 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) DefaultSkewThreshold() GoogleCloudAiplatformV1ThresholdConfigPtrOutput

Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) Elem() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) SkewThresholds 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) SkewThresholds() pulumi.StringMapOutput

Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigPtrOutput

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponse 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponse struct {
	// Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.
	AttributionScoreSkewThresholds map[string]string `pulumi:"attributionScoreSkewThresholds"`
	// Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.
	DefaultSkewThreshold GoogleCloudAiplatformV1ThresholdConfigResponse `pulumi:"defaultSkewThreshold"`
	// Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.
	SkewThresholds map[string]string `pulumi:"skewThresholds"`
}

The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters.

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput 

type GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput struct{ *pulumi.OutputState }

The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput) AttributionScoreSkewThresholds 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput) AttributionScoreSkewThresholds() pulumi.StringMapOutput

Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput) DefaultSkewThreshold 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput) DefaultSkewThreshold() GoogleCloudAiplatformV1ThresholdConfigResponseOutput

Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput) SkewThresholds 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput) SkewThresholds() pulumi.StringMapOutput

Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature.

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput() GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput

func (GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput) ToGoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfigResponseOutput

type GoogleCloudAiplatformV1ModelOriginalModelInfoResponse 

type GoogleCloudAiplatformV1ModelOriginalModelInfoResponse struct {
	// The resource name of the Model this Model is a copy of, including the revision. Format: `projects/{project}/locations/{location}/models/{model_id}@{version_id}`
	Model string `pulumi:"model"`
}

Contains information about the original Model if this Model is a copy.

type GoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput 

type GoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput struct{ *pulumi.OutputState }

Contains information about the original Model if this Model is a copy.

func (GoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput) Model 

func (o GoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput) Model() pulumi.StringOutput

The resource name of the Model this Model is a copy of, including the revision. Format: `projects/{project}/locations/{location}/models/{model_id}@{version_id}`

func (GoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput) ToGoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput 

func (o GoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput) ToGoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput() GoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput

func (GoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput) ToGoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput) ToGoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput

type GoogleCloudAiplatformV1ModelOutput 

type GoogleCloudAiplatformV1ModelOutput struct{ *pulumi.OutputState }

A trained machine learning Model.

func (GoogleCloudAiplatformV1ModelOutput) ArtifactUri 

func (o GoogleCloudAiplatformV1ModelOutput) ArtifactUri() pulumi.StringPtrOutput

Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models or Large Models.

func (GoogleCloudAiplatformV1ModelOutput) ContainerSpec 

func (o GoogleCloudAiplatformV1ModelOutput) ContainerSpec() GoogleCloudAiplatformV1ModelContainerSpecPtrOutput

Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models or Large Models.

func (GoogleCloudAiplatformV1ModelOutput) Description 

func (o GoogleCloudAiplatformV1ModelOutput) Description() pulumi.StringPtrOutput

The description of the Model.

func (GoogleCloudAiplatformV1ModelOutput) DisplayName 

func (o GoogleCloudAiplatformV1ModelOutput) DisplayName() pulumi.StringOutput

The display name of the Model. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (GoogleCloudAiplatformV1ModelOutput) ElementType 

func (GoogleCloudAiplatformV1ModelOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelOutput) EncryptionSpec 

func (o GoogleCloudAiplatformV1ModelOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecPtrOutput

Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.

func (GoogleCloudAiplatformV1ModelOutput) Etag 

func (o GoogleCloudAiplatformV1ModelOutput) Etag() pulumi.StringPtrOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (GoogleCloudAiplatformV1ModelOutput) ExplanationSpec 

func (o GoogleCloudAiplatformV1ModelOutput) ExplanationSpec() GoogleCloudAiplatformV1ExplanationSpecPtrOutput

The default explanation specification for this Model. The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated. All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob. If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.

func (GoogleCloudAiplatformV1ModelOutput) Labels 

func (o GoogleCloudAiplatformV1ModelOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (GoogleCloudAiplatformV1ModelOutput) Metadata 

func (o GoogleCloudAiplatformV1ModelOutput) Metadata() pulumi.AnyOutput

Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.

func (GoogleCloudAiplatformV1ModelOutput) MetadataSchemaUri 

func (o GoogleCloudAiplatformV1ModelOutput) MetadataSchemaUri() pulumi.StringPtrOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1ModelOutput) Name 

func (o GoogleCloudAiplatformV1ModelOutput) Name() pulumi.StringPtrOutput

The resource name of the Model.

func (GoogleCloudAiplatformV1ModelOutput) PipelineJob 

func (o GoogleCloudAiplatformV1ModelOutput) PipelineJob() pulumi.StringPtrOutput

Optional. This field is populated if the model is produced by a pipeline job.

func (GoogleCloudAiplatformV1ModelOutput) PredictSchemata 

func (o GoogleCloudAiplatformV1ModelOutput) PredictSchemata() GoogleCloudAiplatformV1PredictSchemataPtrOutput

The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.

func (GoogleCloudAiplatformV1ModelOutput) ToGoogleCloudAiplatformV1ModelOutput 

func (o GoogleCloudAiplatformV1ModelOutput) ToGoogleCloudAiplatformV1ModelOutput() GoogleCloudAiplatformV1ModelOutput

func (GoogleCloudAiplatformV1ModelOutput) ToGoogleCloudAiplatformV1ModelOutputWithContext 

func (o GoogleCloudAiplatformV1ModelOutput) ToGoogleCloudAiplatformV1ModelOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelOutput

func (GoogleCloudAiplatformV1ModelOutput) ToGoogleCloudAiplatformV1ModelPtrOutput 

func (o GoogleCloudAiplatformV1ModelOutput) ToGoogleCloudAiplatformV1ModelPtrOutput() GoogleCloudAiplatformV1ModelPtrOutput

func (GoogleCloudAiplatformV1ModelOutput) ToGoogleCloudAiplatformV1ModelPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelOutput) ToGoogleCloudAiplatformV1ModelPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelPtrOutput

func (GoogleCloudAiplatformV1ModelOutput) VersionAliases 

func (o GoogleCloudAiplatformV1ModelOutput) VersionAliases() pulumi.StringArrayOutput

User provided version aliases so that a model version can be referenced via alias (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_alias}` instead of auto-generated version id (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_id})`. The format is a-z{0,126}[a-z0-9] to distinguish from version_id. A default version alias will be created for the first version of the model, and there must be exactly one default version alias for a model.

func (GoogleCloudAiplatformV1ModelOutput) VersionDescription 

func (o GoogleCloudAiplatformV1ModelOutput) VersionDescription() pulumi.StringPtrOutput

The description of this version.

type GoogleCloudAiplatformV1ModelPtrInput 

type GoogleCloudAiplatformV1ModelPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ModelPtrOutput() GoogleCloudAiplatformV1ModelPtrOutput
	ToGoogleCloudAiplatformV1ModelPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ModelPtrOutput
}

GoogleCloudAiplatformV1ModelPtrInput is an input type that accepts GoogleCloudAiplatformV1ModelArgs, GoogleCloudAiplatformV1ModelPtr and GoogleCloudAiplatformV1ModelPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ModelPtrInput` via: 

        GoogleCloudAiplatformV1ModelArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ModelPtr 

func GoogleCloudAiplatformV1ModelPtr(v *GoogleCloudAiplatformV1ModelArgs) GoogleCloudAiplatformV1ModelPtrInput

type GoogleCloudAiplatformV1ModelPtrOutput 

type GoogleCloudAiplatformV1ModelPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ModelPtrOutput) ArtifactUri 

func (o GoogleCloudAiplatformV1ModelPtrOutput) ArtifactUri() pulumi.StringPtrOutput

Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models or Large Models.

func (GoogleCloudAiplatformV1ModelPtrOutput) ContainerSpec 

func (o GoogleCloudAiplatformV1ModelPtrOutput) ContainerSpec() GoogleCloudAiplatformV1ModelContainerSpecPtrOutput

Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models or Large Models.

func (GoogleCloudAiplatformV1ModelPtrOutput) Description 

func (o GoogleCloudAiplatformV1ModelPtrOutput) Description() pulumi.StringPtrOutput

The description of the Model.

func (GoogleCloudAiplatformV1ModelPtrOutput) DisplayName 

func (o GoogleCloudAiplatformV1ModelPtrOutput) DisplayName() pulumi.StringPtrOutput

The display name of the Model. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (GoogleCloudAiplatformV1ModelPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ModelPtrOutput) Elem() GoogleCloudAiplatformV1ModelOutput

func (GoogleCloudAiplatformV1ModelPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ModelPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelPtrOutput) EncryptionSpec 

func (o GoogleCloudAiplatformV1ModelPtrOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecPtrOutput

Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.

func (GoogleCloudAiplatformV1ModelPtrOutput) Etag 

func (o GoogleCloudAiplatformV1ModelPtrOutput) Etag() pulumi.StringPtrOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (GoogleCloudAiplatformV1ModelPtrOutput) ExplanationSpec 

func (o GoogleCloudAiplatformV1ModelPtrOutput) ExplanationSpec() GoogleCloudAiplatformV1ExplanationSpecPtrOutput

The default explanation specification for this Model. The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated. All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob. If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.

func (GoogleCloudAiplatformV1ModelPtrOutput) Labels 

func (o GoogleCloudAiplatformV1ModelPtrOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (GoogleCloudAiplatformV1ModelPtrOutput) Metadata 

func (o GoogleCloudAiplatformV1ModelPtrOutput) Metadata() pulumi.AnyOutput

Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.

func (GoogleCloudAiplatformV1ModelPtrOutput) MetadataSchemaUri 

func (o GoogleCloudAiplatformV1ModelPtrOutput) MetadataSchemaUri() pulumi.StringPtrOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1ModelPtrOutput) Name 

func (o GoogleCloudAiplatformV1ModelPtrOutput) Name() pulumi.StringPtrOutput

The resource name of the Model.

func (GoogleCloudAiplatformV1ModelPtrOutput) PipelineJob 

func (o GoogleCloudAiplatformV1ModelPtrOutput) PipelineJob() pulumi.StringPtrOutput

Optional. This field is populated if the model is produced by a pipeline job.

func (GoogleCloudAiplatformV1ModelPtrOutput) PredictSchemata 

func (o GoogleCloudAiplatformV1ModelPtrOutput) PredictSchemata() GoogleCloudAiplatformV1PredictSchemataPtrOutput

The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.

func (GoogleCloudAiplatformV1ModelPtrOutput) ToGoogleCloudAiplatformV1ModelPtrOutput 

func (o GoogleCloudAiplatformV1ModelPtrOutput) ToGoogleCloudAiplatformV1ModelPtrOutput() GoogleCloudAiplatformV1ModelPtrOutput

func (GoogleCloudAiplatformV1ModelPtrOutput) ToGoogleCloudAiplatformV1ModelPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ModelPtrOutput) ToGoogleCloudAiplatformV1ModelPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelPtrOutput

func (GoogleCloudAiplatformV1ModelPtrOutput) VersionAliases 

func (o GoogleCloudAiplatformV1ModelPtrOutput) VersionAliases() pulumi.StringArrayOutput

User provided version aliases so that a model version can be referenced via alias (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_alias}` instead of auto-generated version id (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_id})`. The format is a-z{0,126}[a-z0-9] to distinguish from version_id. A default version alias will be created for the first version of the model, and there must be exactly one default version alias for a model.

func (GoogleCloudAiplatformV1ModelPtrOutput) VersionDescription 

func (o GoogleCloudAiplatformV1ModelPtrOutput) VersionDescription() pulumi.StringPtrOutput

The description of this version.

type GoogleCloudAiplatformV1ModelResponse 

type GoogleCloudAiplatformV1ModelResponse struct {
	// Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models or Large Models.
	ArtifactUri string `pulumi:"artifactUri"`
	// Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models or Large Models.
	ContainerSpec GoogleCloudAiplatformV1ModelContainerSpecResponse `pulumi:"containerSpec"`
	// Timestamp when this Model was uploaded into Vertex AI.
	CreateTime string `pulumi:"createTime"`
	// The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
	DeployedModels []GoogleCloudAiplatformV1DeployedModelRefResponse `pulumi:"deployedModels"`
	// The description of the Model.
	Description string `pulumi:"description"`
	// The display name of the Model. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// The default explanation specification for this Model. The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated. All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob. If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.
	ExplanationSpec GoogleCloudAiplatformV1ExplanationSpecResponse `pulumi:"explanationSpec"`
	// The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels map[string]string `pulumi:"labels"`
	// Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.
	Metadata interface{} `pulumi:"metadata"`
	// The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
	MetadataArtifact string `pulumi:"metadataArtifact"`
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	MetadataSchemaUri string `pulumi:"metadataSchemaUri"`
	// Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or existing Vertex AI Model.
	ModelSourceInfo GoogleCloudAiplatformV1ModelSourceInfoResponse `pulumi:"modelSourceInfo"`
	// The resource name of the Model.
	Name string `pulumi:"name"`
	// If this Model is a copy of another Model, this contains info about the original.
	OriginalModelInfo GoogleCloudAiplatformV1ModelOriginalModelInfoResponse `pulumi:"originalModelInfo"`
	// Optional. This field is populated if the model is produced by a pipeline job.
	PipelineJob string `pulumi:"pipelineJob"`
	// The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.
	PredictSchemata GoogleCloudAiplatformV1PredictSchemataResponse `pulumi:"predictSchemata"`
	// When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the Endpoint.deployed_models object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an Endpoint and does not support online predictions (PredictionService.Predict or PredictionService.Explain). Such a Model can serve predictions by using a BatchPredictionJob, if it has at least one entry each in supported_input_storage_formats and supported_output_storage_formats.
	SupportedDeploymentResourcesTypes []string `pulumi:"supportedDeploymentResourcesTypes"`
	// The formats in which this Model may be exported. If empty, this Model is not available for export.
	SupportedExportFormats []GoogleCloudAiplatformV1ModelExportFormatResponse `pulumi:"supportedExportFormats"`
	// The formats this Model supports in BatchPredictionJob.input_config. If PredictSchemata.instance_schema_uri exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses GcsSource. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses GcsSource. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses GcsSource. * `bigquery` Each instance is a single row in BigQuery. Uses BigQuerySource. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the InputConfig object. If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
	SupportedInputStorageFormats []string `pulumi:"supportedInputStorageFormats"`
	// The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and PredictSchemata.prediction_schema_uri exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses GcsDestination. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses GcsDestination. * `bigquery` Each prediction is a single row in a BigQuery table, uses BigQueryDestination . If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.
	SupportedOutputStorageFormats []string `pulumi:"supportedOutputStorageFormats"`
	// The resource name of the TrainingPipeline that uploaded this Model, if any.
	TrainingPipeline string `pulumi:"trainingPipeline"`
	// Timestamp when this Model was most recently updated.
	UpdateTime string `pulumi:"updateTime"`
	// User provided version aliases so that a model version can be referenced via alias (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_alias}` instead of auto-generated version id (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_id})`. The format is a-z{0,126}[a-z0-9] to distinguish from version_id. A default version alias will be created for the first version of the model, and there must be exactly one default version alias for a model.
	VersionAliases []string `pulumi:"versionAliases"`
	// Timestamp when this version was created.
	VersionCreateTime string `pulumi:"versionCreateTime"`
	// The description of this version.
	VersionDescription string `pulumi:"versionDescription"`
	// Immutable. The version ID of the model. A new version is committed when a new model version is uploaded or trained under an existing model id. It is an auto-incrementing decimal number in string representation.
	VersionId string `pulumi:"versionId"`
	// Timestamp when this version was most recently updated.
	VersionUpdateTime string `pulumi:"versionUpdateTime"`
}

A trained machine learning Model.

type GoogleCloudAiplatformV1ModelResponseOutput 

type GoogleCloudAiplatformV1ModelResponseOutput struct{ *pulumi.OutputState }

A trained machine learning Model.

func (GoogleCloudAiplatformV1ModelResponseOutput) ArtifactUri 

func (o GoogleCloudAiplatformV1ModelResponseOutput) ArtifactUri() pulumi.StringOutput

Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models or Large Models.

func (GoogleCloudAiplatformV1ModelResponseOutput) ContainerSpec 

func (o GoogleCloudAiplatformV1ModelResponseOutput) ContainerSpec() GoogleCloudAiplatformV1ModelContainerSpecResponseOutput

Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models or Large Models.

func (GoogleCloudAiplatformV1ModelResponseOutput) CreateTime 

func (o GoogleCloudAiplatformV1ModelResponseOutput) CreateTime() pulumi.StringOutput

Timestamp when this Model was uploaded into Vertex AI.

func (GoogleCloudAiplatformV1ModelResponseOutput) DeployedModels 

func (o GoogleCloudAiplatformV1ModelResponseOutput) DeployedModels() GoogleCloudAiplatformV1DeployedModelRefResponseArrayOutput

The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.

func (GoogleCloudAiplatformV1ModelResponseOutput) Description 

func (o GoogleCloudAiplatformV1ModelResponseOutput) Description() pulumi.StringOutput

The description of the Model.

func (GoogleCloudAiplatformV1ModelResponseOutput) DisplayName 

func (o GoogleCloudAiplatformV1ModelResponseOutput) DisplayName() pulumi.StringOutput

The display name of the Model. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (GoogleCloudAiplatformV1ModelResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelResponseOutput) EncryptionSpec 

func (o GoogleCloudAiplatformV1ModelResponseOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.

func (GoogleCloudAiplatformV1ModelResponseOutput) Etag 

func (o GoogleCloudAiplatformV1ModelResponseOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (GoogleCloudAiplatformV1ModelResponseOutput) ExplanationSpec 

func (o GoogleCloudAiplatformV1ModelResponseOutput) ExplanationSpec() GoogleCloudAiplatformV1ExplanationSpecResponseOutput

The default explanation specification for this Model. The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated. All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob. If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob.

func (GoogleCloudAiplatformV1ModelResponseOutput) Labels 

func (o GoogleCloudAiplatformV1ModelResponseOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (GoogleCloudAiplatformV1ModelResponseOutput) Metadata 

func (o GoogleCloudAiplatformV1ModelResponseOutput) Metadata() pulumi.AnyOutput

Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information.

func (GoogleCloudAiplatformV1ModelResponseOutput) MetadataArtifact 

func (o GoogleCloudAiplatformV1ModelResponseOutput) MetadataArtifact() pulumi.StringOutput

The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.

func (GoogleCloudAiplatformV1ModelResponseOutput) MetadataSchemaUri 

func (o GoogleCloudAiplatformV1ModelResponseOutput) MetadataSchemaUri() pulumi.StringOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1ModelResponseOutput) ModelSourceInfo 

func (o GoogleCloudAiplatformV1ModelResponseOutput) ModelSourceInfo() GoogleCloudAiplatformV1ModelSourceInfoResponseOutput

Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or existing Vertex AI Model.

func (GoogleCloudAiplatformV1ModelResponseOutput) Name 

func (o GoogleCloudAiplatformV1ModelResponseOutput) Name() pulumi.StringOutput

The resource name of the Model.

func (GoogleCloudAiplatformV1ModelResponseOutput) OriginalModelInfo 

func (o GoogleCloudAiplatformV1ModelResponseOutput) OriginalModelInfo() GoogleCloudAiplatformV1ModelOriginalModelInfoResponseOutput

If this Model is a copy of another Model, this contains info about the original.

func (GoogleCloudAiplatformV1ModelResponseOutput) PipelineJob 

func (o GoogleCloudAiplatformV1ModelResponseOutput) PipelineJob() pulumi.StringOutput

Optional. This field is populated if the model is produced by a pipeline job.

func (GoogleCloudAiplatformV1ModelResponseOutput) PredictSchemata 

func (o GoogleCloudAiplatformV1ModelResponseOutput) PredictSchemata() GoogleCloudAiplatformV1PredictSchemataResponseOutput

The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain.

func (GoogleCloudAiplatformV1ModelResponseOutput) SupportedDeploymentResourcesTypes 

func (o GoogleCloudAiplatformV1ModelResponseOutput) SupportedDeploymentResourcesTypes() pulumi.StringArrayOutput

When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the Endpoint.deployed_models object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an Endpoint and does not support online predictions (PredictionService.Predict or PredictionService.Explain). Such a Model can serve predictions by using a BatchPredictionJob, if it has at least one entry each in supported_input_storage_formats and supported_output_storage_formats.

func (GoogleCloudAiplatformV1ModelResponseOutput) SupportedExportFormats 

func (o GoogleCloudAiplatformV1ModelResponseOutput) SupportedExportFormats() GoogleCloudAiplatformV1ModelExportFormatResponseArrayOutput

The formats in which this Model may be exported. If empty, this Model is not available for export.

func (GoogleCloudAiplatformV1ModelResponseOutput) SupportedInputStorageFormats 

func (o GoogleCloudAiplatformV1ModelResponseOutput) SupportedInputStorageFormats() pulumi.StringArrayOutput

The formats this Model supports in BatchPredictionJob.input_config. If PredictSchemata.instance_schema_uri exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses GcsSource. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses GcsSource. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses GcsSource. * `bigquery` Each instance is a single row in BigQuery. Uses BigQuerySource. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the InputConfig object. If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.

func (GoogleCloudAiplatformV1ModelResponseOutput) SupportedOutputStorageFormats 

func (o GoogleCloudAiplatformV1ModelResponseOutput) SupportedOutputStorageFormats() pulumi.StringArrayOutput

The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and PredictSchemata.prediction_schema_uri exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses GcsDestination. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses GcsDestination. * `bigquery` Each prediction is a single row in a BigQuery table, uses BigQueryDestination . If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain.

func (GoogleCloudAiplatformV1ModelResponseOutput) ToGoogleCloudAiplatformV1ModelResponseOutput 

func (o GoogleCloudAiplatformV1ModelResponseOutput) ToGoogleCloudAiplatformV1ModelResponseOutput() GoogleCloudAiplatformV1ModelResponseOutput

func (GoogleCloudAiplatformV1ModelResponseOutput) ToGoogleCloudAiplatformV1ModelResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelResponseOutput) ToGoogleCloudAiplatformV1ModelResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelResponseOutput

func (GoogleCloudAiplatformV1ModelResponseOutput) TrainingPipeline 

func (o GoogleCloudAiplatformV1ModelResponseOutput) TrainingPipeline() pulumi.StringOutput

The resource name of the TrainingPipeline that uploaded this Model, if any.

func (GoogleCloudAiplatformV1ModelResponseOutput) UpdateTime 

func (o GoogleCloudAiplatformV1ModelResponseOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Model was most recently updated.

func (GoogleCloudAiplatformV1ModelResponseOutput) VersionAliases 

func (o GoogleCloudAiplatformV1ModelResponseOutput) VersionAliases() pulumi.StringArrayOutput

User provided version aliases so that a model version can be referenced via alias (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_alias}` instead of auto-generated version id (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_id})`. The format is a-z{0,126}[a-z0-9] to distinguish from version_id. A default version alias will be created for the first version of the model, and there must be exactly one default version alias for a model.

func (GoogleCloudAiplatformV1ModelResponseOutput) VersionCreateTime 

func (o GoogleCloudAiplatformV1ModelResponseOutput) VersionCreateTime() pulumi.StringOutput

Timestamp when this version was created.

func (GoogleCloudAiplatformV1ModelResponseOutput) VersionDescription 

func (o GoogleCloudAiplatformV1ModelResponseOutput) VersionDescription() pulumi.StringOutput

The description of this version.

func (GoogleCloudAiplatformV1ModelResponseOutput) VersionId 

func (o GoogleCloudAiplatformV1ModelResponseOutput) VersionId() pulumi.StringOutput

Immutable. The version ID of the model. A new version is committed when a new model version is uploaded or trained under an existing model id. It is an auto-incrementing decimal number in string representation.

func (GoogleCloudAiplatformV1ModelResponseOutput) VersionUpdateTime 

func (o GoogleCloudAiplatformV1ModelResponseOutput) VersionUpdateTime() pulumi.StringOutput

Timestamp when this version was most recently updated.

type GoogleCloudAiplatformV1ModelSourceInfoResponse 

type GoogleCloudAiplatformV1ModelSourceInfoResponse struct {
	// If this Model is copy of another Model. If true then source_type pertains to the original.
	Copy bool `pulumi:"copy"`
	// Type of the model source.
	SourceType string `pulumi:"sourceType"`
}

Detail description of the source information of the model.

type GoogleCloudAiplatformV1ModelSourceInfoResponseOutput 

type GoogleCloudAiplatformV1ModelSourceInfoResponseOutput struct{ *pulumi.OutputState }

Detail description of the source information of the model.

func (GoogleCloudAiplatformV1ModelSourceInfoResponseOutput) Copy 

func (o GoogleCloudAiplatformV1ModelSourceInfoResponseOutput) Copy() pulumi.BoolOutput

If this Model is copy of another Model. If true then source_type pertains to the original.

func (GoogleCloudAiplatformV1ModelSourceInfoResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ModelSourceInfoResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ModelSourceInfoResponseOutput) SourceType 

func (o GoogleCloudAiplatformV1ModelSourceInfoResponseOutput) SourceType() pulumi.StringOutput

Type of the model source.

func (GoogleCloudAiplatformV1ModelSourceInfoResponseOutput) ToGoogleCloudAiplatformV1ModelSourceInfoResponseOutput 

func (o GoogleCloudAiplatformV1ModelSourceInfoResponseOutput) ToGoogleCloudAiplatformV1ModelSourceInfoResponseOutput() GoogleCloudAiplatformV1ModelSourceInfoResponseOutput

func (GoogleCloudAiplatformV1ModelSourceInfoResponseOutput) ToGoogleCloudAiplatformV1ModelSourceInfoResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ModelSourceInfoResponseOutput) ToGoogleCloudAiplatformV1ModelSourceInfoResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ModelSourceInfoResponseOutput

type GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponse 

type GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponse struct {
	// List of NasTrials that were started as part of search stage.
	SearchTrials []GoogleCloudAiplatformV1NasTrialResponse `pulumi:"searchTrials"`
	// List of NasTrials that were started as part of train stage.
	TrainTrials []GoogleCloudAiplatformV1NasTrialResponse `pulumi:"trainTrials"`
}

The output of a multi-trial Neural Architecture Search (NAS) jobs.

type GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput 

type GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput struct{ *pulumi.OutputState }

The output of a multi-trial Neural Architecture Search (NAS) jobs.

func (GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput) SearchTrials 

func (o GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput) SearchTrials() GoogleCloudAiplatformV1NasTrialResponseArrayOutput

List of NasTrials that were started as part of search stage.

func (GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput) ToGoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput 

func (o GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput) ToGoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput() GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput

func (GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput) ToGoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput) ToGoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput

func (GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput) TrainTrials 

func (o GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput) TrainTrials() GoogleCloudAiplatformV1NasTrialResponseArrayOutput

List of NasTrials that were started as part of train stage.

type GoogleCloudAiplatformV1NasJobOutputResponse 

type GoogleCloudAiplatformV1NasJobOutputResponse struct {
	// The output of this multi-trial Neural Architecture Search (NAS) job.
	MultiTrialJobOutput GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponse `pulumi:"multiTrialJobOutput"`
}

Represents a uCAIP NasJob output.

type GoogleCloudAiplatformV1NasJobOutputResponseOutput 

type GoogleCloudAiplatformV1NasJobOutputResponseOutput struct{ *pulumi.OutputState }

Represents a uCAIP NasJob output.

func (GoogleCloudAiplatformV1NasJobOutputResponseOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobOutputResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobOutputResponseOutput) MultiTrialJobOutput 

func (o GoogleCloudAiplatformV1NasJobOutputResponseOutput) MultiTrialJobOutput() GoogleCloudAiplatformV1NasJobOutputMultiTrialJobOutputResponseOutput

The output of this multi-trial Neural Architecture Search (NAS) job.

func (GoogleCloudAiplatformV1NasJobOutputResponseOutput) ToGoogleCloudAiplatformV1NasJobOutputResponseOutput 

func (o GoogleCloudAiplatformV1NasJobOutputResponseOutput) ToGoogleCloudAiplatformV1NasJobOutputResponseOutput() GoogleCloudAiplatformV1NasJobOutputResponseOutput

func (GoogleCloudAiplatformV1NasJobOutputResponseOutput) ToGoogleCloudAiplatformV1NasJobOutputResponseOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobOutputResponseOutput) ToGoogleCloudAiplatformV1NasJobOutputResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobOutputResponseOutput

type GoogleCloudAiplatformV1NasJobSpec 

type GoogleCloudAiplatformV1NasJobSpec struct {
	// The spec of multi-trial algorithms.
	MultiTrialAlgorithmSpec *GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec `pulumi:"multiTrialAlgorithmSpec"`
	// The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
	ResumeNasJobId *string `pulumi:"resumeNasJobId"`
	// It defines the search space for Neural Architecture Search (NAS).
	SearchSpaceSpec *string `pulumi:"searchSpaceSpec"`
}

Represents the spec of a NasJob.

type GoogleCloudAiplatformV1NasJobSpecArgs 

type GoogleCloudAiplatformV1NasJobSpecArgs struct {
	// The spec of multi-trial algorithms.
	MultiTrialAlgorithmSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrInput `pulumi:"multiTrialAlgorithmSpec"`
	// The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
	ResumeNasJobId pulumi.StringPtrInput `pulumi:"resumeNasJobId"`
	// It defines the search space for Neural Architecture Search (NAS).
	SearchSpaceSpec pulumi.StringPtrInput `pulumi:"searchSpaceSpec"`
}

Represents the spec of a NasJob.

func (GoogleCloudAiplatformV1NasJobSpecArgs) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecOutput 

func (i GoogleCloudAiplatformV1NasJobSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecOutput() GoogleCloudAiplatformV1NasJobSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecOutputWithContext 

func (i GoogleCloudAiplatformV1NasJobSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecOutput

type GoogleCloudAiplatformV1NasJobSpecInput 

type GoogleCloudAiplatformV1NasJobSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NasJobSpecOutput() GoogleCloudAiplatformV1NasJobSpecOutput
	ToGoogleCloudAiplatformV1NasJobSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1NasJobSpecOutput
}

GoogleCloudAiplatformV1NasJobSpecInput is an input type that accepts GoogleCloudAiplatformV1NasJobSpecArgs and GoogleCloudAiplatformV1NasJobSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NasJobSpecInput` via: 

GoogleCloudAiplatformV1NasJobSpecArgs{...}

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpec struct {
	// Metric specs for the NAS job. Validation for this field is done at `multi_trial_algorithm_spec` field.
	Metric *GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec `pulumi:"metric"`
	// The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`.
	MultiTrialAlgorithm *GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm `pulumi:"multiTrialAlgorithm"`
	// Spec for search trials.
	SearchTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec `pulumi:"searchTrialSpec"`
	// Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
	TrainTrialSpec *GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec `pulumi:"trainTrialSpec"`
}

The spec of multi-trial Neural Architecture Search (NAS).

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs struct {
	// Metric specs for the NAS job. Validation for this field is done at `multi_trial_algorithm_spec` field.
	Metric GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrInput `pulumi:"metric"`
	// The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`.
	MultiTrialAlgorithm GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrInput `pulumi:"multiTrialAlgorithm"`
	// Spec for search trials.
	SearchTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecInput `pulumi:"searchTrialSpec"`
	// Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
	TrainTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrInput `pulumi:"trainTrialSpec"`
}

The spec of multi-trial Neural Architecture Search (NAS).

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutputWithContext 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecInput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput
	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput
}

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecInput is an input type that accepts GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs and GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecInput` via: 

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs{...}

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpec struct {
	// The optimization goal of the metric.
	Goal GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal `pulumi:"goal"`
	// The ID of the metric. Must not contain whitespaces.
	MetricId string `pulumi:"metricId"`
}

Represents a metric to optimize.

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs struct {
	// The optimization goal of the metric.
	Goal GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalInput `pulumi:"goal"`
	// The ID of the metric. Must not contain whitespaces.
	MetricId pulumi.StringInput `pulumi:"metricId"`
}

Represents a metric to optimize.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutputWithContext 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal string

Required. The optimization goal of the metric.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutputWithContext 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutputWithContext 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToStringOutput 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoal) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalInput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput
	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutputWithContext(context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput
}

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalInput is an input type that accepts GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalArgs and GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalInput` via: 

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalArgs{...}

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrInput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput
	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput
}

func GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtr 

func GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtr(v string) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrInput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput) Elem 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput) Elem() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecInput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput
	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput
}

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecInput is an input type that accepts GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs and GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecInput` via: 

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs{...}

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput struct{ *pulumi.OutputState }

Represents a metric to optimize.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) Goal 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) Goal() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalOutput

The optimization goal of the metric.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) MetricId 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) MetricId() pulumi.StringOutput

The ID of the metric. Must not contain whitespaces.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrInput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput
	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput
}

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtr and GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrInput` via: 

        GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtr 

func GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtr(v *GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecArgs) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrInput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput) Elem() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput) Goal 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput) Goal() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecGoalPtrOutput

The optimization goal of the metric.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput) MetricId 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput) MetricId() pulumi.StringPtrOutput

The ID of the metric. Must not contain whitespaces.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponse 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponse struct {
	// The optimization goal of the metric.
	Goal string `pulumi:"goal"`
	// The ID of the metric. Must not contain whitespaces.
	MetricId string `pulumi:"metricId"`
}

Represents a metric to optimize.

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput struct{ *pulumi.OutputState }

Represents a metric to optimize.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput) Goal 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput) Goal() pulumi.StringOutput

The optimization goal of the metric.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput) MetricId 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput) MetricId() pulumi.StringOutput

The ID of the metric. Must not contain whitespaces.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm string

The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutputWithContext 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutputWithContext 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToStringOutput 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithm) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmInput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput
	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutputWithContext(context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput
}

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmInput is an input type that accepts GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmArgs and GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmInput` via: 

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmArgs{...}

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrInput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput
	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput
}

func GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtr 

func GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtr(v string) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrInput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput) Elem 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput) Elem() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput struct{ *pulumi.OutputState }

The spec of multi-trial Neural Architecture Search (NAS).

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) Metric 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) Metric() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput

Metric specs for the NAS job. Validation for this field is done at `multi_trial_algorithm_spec` field.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) MultiTrialAlgorithm 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) MultiTrialAlgorithm() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput

The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) SearchTrialSpec 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) SearchTrialSpec() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput

Spec for search trials.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) TrainTrialSpec 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput) TrainTrialSpec() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput

Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrInput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput
	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput
}

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtr and GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrInput` via: 

        GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtr 

func GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtr(v *GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecArgs) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrInput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) Elem() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) Metric 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) Metric() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecPtrOutput

Metric specs for the NAS job. Validation for this field is done at `multi_trial_algorithm_spec` field.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) MultiTrialAlgorithm 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) MultiTrialAlgorithm() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMultiTrialAlgorithmPtrOutput

The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) SearchTrialSpec 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) SearchTrialSpec() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput

Spec for search trials.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) TrainTrialSpec 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput) TrainTrialSpec() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput

Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponse 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponse struct {
	// Metric specs for the NAS job. Validation for this field is done at `multi_trial_algorithm_spec` field.
	Metric GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponse `pulumi:"metric"`
	// The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`.
	MultiTrialAlgorithm string `pulumi:"multiTrialAlgorithm"`
	// Spec for search trials.
	SearchTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponse `pulumi:"searchTrialSpec"`
	// Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
	TrainTrialSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponse `pulumi:"trainTrialSpec"`
}

The spec of multi-trial Neural Architecture Search (NAS).

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput struct{ *pulumi.OutputState }

The spec of multi-trial Neural Architecture Search (NAS).

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) Metric 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) Metric() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecMetricSpecResponseOutput

Metric specs for the NAS job. Validation for this field is done at `multi_trial_algorithm_spec` field.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) MultiTrialAlgorithm 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) MultiTrialAlgorithm() pulumi.StringOutput

The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) SearchTrialSpec 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) SearchTrialSpec() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput

Spec for search trials.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) TrainTrialSpec 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput) TrainTrialSpec() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput

Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec struct {
	// The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
	MaxFailedTrialCount *int `pulumi:"maxFailedTrialCount"`
	// The maximum number of trials to run in parallel.
	MaxParallelTrialCount int `pulumi:"maxParallelTrialCount"`
	// The maximum number of Neural Architecture Search (NAS) trials to run.
	MaxTrialCount int `pulumi:"maxTrialCount"`
	// The spec of a search trial job. The same spec applies to all search trials.
	SearchTrialJobSpec GoogleCloudAiplatformV1CustomJobSpec `pulumi:"searchTrialJobSpec"`
}

Represent spec for search trials.

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs struct {
	// The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
	MaxFailedTrialCount pulumi.IntPtrInput `pulumi:"maxFailedTrialCount"`
	// The maximum number of trials to run in parallel.
	MaxParallelTrialCount pulumi.IntInput `pulumi:"maxParallelTrialCount"`
	// The maximum number of Neural Architecture Search (NAS) trials to run.
	MaxTrialCount pulumi.IntInput `pulumi:"maxTrialCount"`
	// The spec of a search trial job. The same spec applies to all search trials.
	SearchTrialJobSpec GoogleCloudAiplatformV1CustomJobSpecInput `pulumi:"searchTrialJobSpec"`
}

Represent spec for search trials.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutputWithContext 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecInput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput
	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput
}

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecInput is an input type that accepts GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs and GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecInput` via: 

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs{...}

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput struct{ *pulumi.OutputState }

Represent spec for search trials.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) MaxFailedTrialCount 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) MaxFailedTrialCount() pulumi.IntPtrOutput

The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) MaxParallelTrialCount 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) MaxParallelTrialCount() pulumi.IntOutput

The maximum number of trials to run in parallel.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) MaxTrialCount 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) MaxTrialCount() pulumi.IntOutput

The maximum number of Neural Architecture Search (NAS) trials to run.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) SearchTrialJobSpec 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) SearchTrialJobSpec() GoogleCloudAiplatformV1CustomJobSpecOutput

The spec of a search trial job. The same spec applies to all search trials.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrInput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput
	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput
}

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtr and GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrInput` via: 

        GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtr 

func GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtr(v *GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecArgs) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrInput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) Elem() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) MaxFailedTrialCount 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) MaxFailedTrialCount() pulumi.IntPtrOutput

The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) MaxParallelTrialCount 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) MaxParallelTrialCount() pulumi.IntPtrOutput

The maximum number of trials to run in parallel.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) MaxTrialCount 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) MaxTrialCount() pulumi.IntPtrOutput

The maximum number of Neural Architecture Search (NAS) trials to run.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) SearchTrialJobSpec 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) SearchTrialJobSpec() GoogleCloudAiplatformV1CustomJobSpecPtrOutput

The spec of a search trial job. The same spec applies to all search trials.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponse 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponse struct {
	// The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.
	MaxFailedTrialCount int `pulumi:"maxFailedTrialCount"`
	// The maximum number of trials to run in parallel.
	MaxParallelTrialCount int `pulumi:"maxParallelTrialCount"`
	// The maximum number of Neural Architecture Search (NAS) trials to run.
	MaxTrialCount int `pulumi:"maxTrialCount"`
	// The spec of a search trial job. The same spec applies to all search trials.
	SearchTrialJobSpec GoogleCloudAiplatformV1CustomJobSpecResponse `pulumi:"searchTrialJobSpec"`
}

Represent spec for search trials.

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput struct{ *pulumi.OutputState }

Represent spec for search trials.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) MaxFailedTrialCount 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) MaxFailedTrialCount() pulumi.IntOutput

The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) MaxParallelTrialCount 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) MaxParallelTrialCount() pulumi.IntOutput

The maximum number of trials to run in parallel.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) MaxTrialCount 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) MaxTrialCount() pulumi.IntOutput

The maximum number of Neural Architecture Search (NAS) trials to run.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) SearchTrialJobSpec 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) SearchTrialJobSpec() GoogleCloudAiplatformV1CustomJobSpecResponseOutput

The spec of a search trial job. The same spec applies to all search trials.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpecResponseOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec struct {
	// Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
	Frequency int `pulumi:"frequency"`
	// The maximum number of trials to run in parallel.
	MaxParallelTrialCount int `pulumi:"maxParallelTrialCount"`
	// The spec of a train trial job. The same spec applies to all train trials.
	TrainTrialJobSpec GoogleCloudAiplatformV1CustomJobSpec `pulumi:"trainTrialJobSpec"`
}

Represent spec for train trials.

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs struct {
	// Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
	Frequency pulumi.IntInput `pulumi:"frequency"`
	// The maximum number of trials to run in parallel.
	MaxParallelTrialCount pulumi.IntInput `pulumi:"maxParallelTrialCount"`
	// The spec of a train trial job. The same spec applies to all train trials.
	TrainTrialJobSpec GoogleCloudAiplatformV1CustomJobSpecInput `pulumi:"trainTrialJobSpec"`
}

Represent spec for train trials.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutputWithContext 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecInput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput
	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput
}

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecInput is an input type that accepts GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs and GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecInput` via: 

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs{...}

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput struct{ *pulumi.OutputState }

Represent spec for train trials.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) Frequency 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) Frequency() pulumi.IntOutput

Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) MaxParallelTrialCount 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) MaxParallelTrialCount() pulumi.IntOutput

The maximum number of trials to run in parallel.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) TrainTrialJobSpec 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput) TrainTrialJobSpec() GoogleCloudAiplatformV1CustomJobSpecOutput

The spec of a train trial job. The same spec applies to all train trials.

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrInput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput
	ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput
}

GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs, GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtr and GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrInput` via: 

        GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtr 

func GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtr(v *GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecArgs) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrInput

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) Elem() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) Frequency 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) Frequency() pulumi.IntPtrOutput

Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) MaxParallelTrialCount 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) MaxParallelTrialCount() pulumi.IntPtrOutput

The maximum number of trials to run in parallel.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) TrainTrialJobSpec 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecPtrOutput) TrainTrialJobSpec() GoogleCloudAiplatformV1CustomJobSpecPtrOutput

The spec of a train trial job. The same spec applies to all train trials.

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponse 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponse struct {
	// Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.
	Frequency int `pulumi:"frequency"`
	// The maximum number of trials to run in parallel.
	MaxParallelTrialCount int `pulumi:"maxParallelTrialCount"`
	// The spec of a train trial job. The same spec applies to all train trials.
	TrainTrialJobSpec GoogleCloudAiplatformV1CustomJobSpecResponse `pulumi:"trainTrialJobSpec"`
}

Represent spec for train trials.

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput 

type GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput struct{ *pulumi.OutputState }

Represent spec for train trials.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput) Frequency 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput) Frequency() pulumi.IntOutput

Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput) MaxParallelTrialCount 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput) MaxParallelTrialCount() pulumi.IntOutput

The maximum number of trials to run in parallel.

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput

func (GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput) TrainTrialJobSpec 

func (o GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpecResponseOutput) TrainTrialJobSpec() GoogleCloudAiplatformV1CustomJobSpecResponseOutput

The spec of a train trial job. The same spec applies to all train trials.

type GoogleCloudAiplatformV1NasJobSpecOutput 

type GoogleCloudAiplatformV1NasJobSpecOutput struct{ *pulumi.OutputState }

Represents the spec of a NasJob.

func (GoogleCloudAiplatformV1NasJobSpecOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecOutput) MultiTrialAlgorithmSpec 

func (o GoogleCloudAiplatformV1NasJobSpecOutput) MultiTrialAlgorithmSpec() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecPtrOutput

The spec of multi-trial algorithms.

func (GoogleCloudAiplatformV1NasJobSpecOutput) ResumeNasJobId 

func (o GoogleCloudAiplatformV1NasJobSpecOutput) ResumeNasJobId() pulumi.StringPtrOutput

The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.

func (GoogleCloudAiplatformV1NasJobSpecOutput) SearchSpaceSpec 

func (o GoogleCloudAiplatformV1NasJobSpecOutput) SearchSpaceSpec() pulumi.StringPtrOutput

It defines the search space for Neural Architecture Search (NAS).

func (GoogleCloudAiplatformV1NasJobSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecOutput 

func (o GoogleCloudAiplatformV1NasJobSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecOutput() GoogleCloudAiplatformV1NasJobSpecOutput

func (GoogleCloudAiplatformV1NasJobSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecOutput) ToGoogleCloudAiplatformV1NasJobSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecOutput

type GoogleCloudAiplatformV1NasJobSpecResponse 

type GoogleCloudAiplatformV1NasJobSpecResponse struct {
	// The spec of multi-trial algorithms.
	MultiTrialAlgorithmSpec GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponse `pulumi:"multiTrialAlgorithmSpec"`
	// The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.
	ResumeNasJobId string `pulumi:"resumeNasJobId"`
	// It defines the search space for Neural Architecture Search (NAS).
	SearchSpaceSpec string `pulumi:"searchSpaceSpec"`
}

Represents the spec of a NasJob.

type GoogleCloudAiplatformV1NasJobSpecResponseOutput 

type GoogleCloudAiplatformV1NasJobSpecResponseOutput struct{ *pulumi.OutputState }

Represents the spec of a NasJob.

func (GoogleCloudAiplatformV1NasJobSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1NasJobSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasJobSpecResponseOutput) MultiTrialAlgorithmSpec 

func (o GoogleCloudAiplatformV1NasJobSpecResponseOutput) MultiTrialAlgorithmSpec() GoogleCloudAiplatformV1NasJobSpecMultiTrialAlgorithmSpecResponseOutput

The spec of multi-trial algorithms.

func (GoogleCloudAiplatformV1NasJobSpecResponseOutput) ResumeNasJobId 

func (o GoogleCloudAiplatformV1NasJobSpecResponseOutput) ResumeNasJobId() pulumi.StringOutput

The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob.

func (GoogleCloudAiplatformV1NasJobSpecResponseOutput) SearchSpaceSpec 

func (o GoogleCloudAiplatformV1NasJobSpecResponseOutput) SearchSpaceSpec() pulumi.StringOutput

It defines the search space for Neural Architecture Search (NAS).

func (GoogleCloudAiplatformV1NasJobSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecResponseOutput 

func (o GoogleCloudAiplatformV1NasJobSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecResponseOutput() GoogleCloudAiplatformV1NasJobSpecResponseOutput

func (GoogleCloudAiplatformV1NasJobSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1NasJobSpecResponseOutput) ToGoogleCloudAiplatformV1NasJobSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasJobSpecResponseOutput

type GoogleCloudAiplatformV1NasTrialResponse 

type GoogleCloudAiplatformV1NasTrialResponse struct {
	// Time when the NasTrial's status changed to `SUCCEEDED` or `INFEASIBLE`.
	EndTime string `pulumi:"endTime"`
	// The final measurement containing the objective value.
	FinalMeasurement GoogleCloudAiplatformV1MeasurementResponse `pulumi:"finalMeasurement"`
	// Time when the NasTrial was started.
	StartTime string `pulumi:"startTime"`
	// The detailed state of the NasTrial.
	State string `pulumi:"state"`
}

Represents a uCAIP NasJob trial.

type GoogleCloudAiplatformV1NasTrialResponseArrayOutput 

type GoogleCloudAiplatformV1NasTrialResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NasTrialResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1NasTrialResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasTrialResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1NasTrialResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1NasTrialResponseOutput

func (GoogleCloudAiplatformV1NasTrialResponseArrayOutput) ToGoogleCloudAiplatformV1NasTrialResponseArrayOutput 

func (o GoogleCloudAiplatformV1NasTrialResponseArrayOutput) ToGoogleCloudAiplatformV1NasTrialResponseArrayOutput() GoogleCloudAiplatformV1NasTrialResponseArrayOutput

func (GoogleCloudAiplatformV1NasTrialResponseArrayOutput) ToGoogleCloudAiplatformV1NasTrialResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1NasTrialResponseArrayOutput) ToGoogleCloudAiplatformV1NasTrialResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasTrialResponseArrayOutput

type GoogleCloudAiplatformV1NasTrialResponseOutput 

type GoogleCloudAiplatformV1NasTrialResponseOutput struct{ *pulumi.OutputState }

Represents a uCAIP NasJob trial.

func (GoogleCloudAiplatformV1NasTrialResponseOutput) ElementType 

func (GoogleCloudAiplatformV1NasTrialResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NasTrialResponseOutput) EndTime 

func (o GoogleCloudAiplatformV1NasTrialResponseOutput) EndTime() pulumi.StringOutput

Time when the NasTrial's status changed to `SUCCEEDED` or `INFEASIBLE`.

func (GoogleCloudAiplatformV1NasTrialResponseOutput) FinalMeasurement 

func (o GoogleCloudAiplatformV1NasTrialResponseOutput) FinalMeasurement() GoogleCloudAiplatformV1MeasurementResponseOutput

The final measurement containing the objective value.

func (GoogleCloudAiplatformV1NasTrialResponseOutput) StartTime 

func (o GoogleCloudAiplatformV1NasTrialResponseOutput) StartTime() pulumi.StringOutput

Time when the NasTrial was started.

func (GoogleCloudAiplatformV1NasTrialResponseOutput) State 

func (o GoogleCloudAiplatformV1NasTrialResponseOutput) State() pulumi.StringOutput

The detailed state of the NasTrial.

func (GoogleCloudAiplatformV1NasTrialResponseOutput) ToGoogleCloudAiplatformV1NasTrialResponseOutput 

func (o GoogleCloudAiplatformV1NasTrialResponseOutput) ToGoogleCloudAiplatformV1NasTrialResponseOutput() GoogleCloudAiplatformV1NasTrialResponseOutput

func (GoogleCloudAiplatformV1NasTrialResponseOutput) ToGoogleCloudAiplatformV1NasTrialResponseOutputWithContext 

func (o GoogleCloudAiplatformV1NasTrialResponseOutput) ToGoogleCloudAiplatformV1NasTrialResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NasTrialResponseOutput

type GoogleCloudAiplatformV1NetworkSpec 

type GoogleCloudAiplatformV1NetworkSpec struct {
	// Whether to enable public internet access. Default false.
	EnableInternetAccess *bool `pulumi:"enableInternetAccess"`
	// The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
	Network *string `pulumi:"network"`
	// The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
	Subnetwork *string `pulumi:"subnetwork"`
}

Network spec.

type GoogleCloudAiplatformV1NetworkSpecArgs 

type GoogleCloudAiplatformV1NetworkSpecArgs struct {
	// Whether to enable public internet access. Default false.
	EnableInternetAccess pulumi.BoolPtrInput `pulumi:"enableInternetAccess"`
	// The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
	Network pulumi.StringPtrInput `pulumi:"network"`
	// The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
	Subnetwork pulumi.StringPtrInput `pulumi:"subnetwork"`
}

Network spec.

func (GoogleCloudAiplatformV1NetworkSpecArgs) ElementType 

func (GoogleCloudAiplatformV1NetworkSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NetworkSpecArgs) ToGoogleCloudAiplatformV1NetworkSpecOutput 

func (i GoogleCloudAiplatformV1NetworkSpecArgs) ToGoogleCloudAiplatformV1NetworkSpecOutput() GoogleCloudAiplatformV1NetworkSpecOutput

func (GoogleCloudAiplatformV1NetworkSpecArgs) ToGoogleCloudAiplatformV1NetworkSpecOutputWithContext 

func (i GoogleCloudAiplatformV1NetworkSpecArgs) ToGoogleCloudAiplatformV1NetworkSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NetworkSpecOutput

func (GoogleCloudAiplatformV1NetworkSpecArgs) ToGoogleCloudAiplatformV1NetworkSpecPtrOutput 

func (i GoogleCloudAiplatformV1NetworkSpecArgs) ToGoogleCloudAiplatformV1NetworkSpecPtrOutput() GoogleCloudAiplatformV1NetworkSpecPtrOutput

func (GoogleCloudAiplatformV1NetworkSpecArgs) ToGoogleCloudAiplatformV1NetworkSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1NetworkSpecArgs) ToGoogleCloudAiplatformV1NetworkSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NetworkSpecPtrOutput

type GoogleCloudAiplatformV1NetworkSpecInput 

type GoogleCloudAiplatformV1NetworkSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NetworkSpecOutput() GoogleCloudAiplatformV1NetworkSpecOutput
	ToGoogleCloudAiplatformV1NetworkSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1NetworkSpecOutput
}

GoogleCloudAiplatformV1NetworkSpecInput is an input type that accepts GoogleCloudAiplatformV1NetworkSpecArgs and GoogleCloudAiplatformV1NetworkSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NetworkSpecInput` via: 

GoogleCloudAiplatformV1NetworkSpecArgs{...}

type GoogleCloudAiplatformV1NetworkSpecOutput 

type GoogleCloudAiplatformV1NetworkSpecOutput struct{ *pulumi.OutputState }

Network spec.

func (GoogleCloudAiplatformV1NetworkSpecOutput) ElementType 

func (GoogleCloudAiplatformV1NetworkSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NetworkSpecOutput) EnableInternetAccess 

func (o GoogleCloudAiplatformV1NetworkSpecOutput) EnableInternetAccess() pulumi.BoolPtrOutput

Whether to enable public internet access. Default false.

func (GoogleCloudAiplatformV1NetworkSpecOutput) Network 

func (o GoogleCloudAiplatformV1NetworkSpecOutput) Network() pulumi.StringPtrOutput

The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)

func (GoogleCloudAiplatformV1NetworkSpecOutput) Subnetwork 

func (o GoogleCloudAiplatformV1NetworkSpecOutput) Subnetwork() pulumi.StringPtrOutput

The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`

func (GoogleCloudAiplatformV1NetworkSpecOutput) ToGoogleCloudAiplatformV1NetworkSpecOutput 

func (o GoogleCloudAiplatformV1NetworkSpecOutput) ToGoogleCloudAiplatformV1NetworkSpecOutput() GoogleCloudAiplatformV1NetworkSpecOutput

func (GoogleCloudAiplatformV1NetworkSpecOutput) ToGoogleCloudAiplatformV1NetworkSpecOutputWithContext 

func (o GoogleCloudAiplatformV1NetworkSpecOutput) ToGoogleCloudAiplatformV1NetworkSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NetworkSpecOutput

func (GoogleCloudAiplatformV1NetworkSpecOutput) ToGoogleCloudAiplatformV1NetworkSpecPtrOutput 

func (o GoogleCloudAiplatformV1NetworkSpecOutput) ToGoogleCloudAiplatformV1NetworkSpecPtrOutput() GoogleCloudAiplatformV1NetworkSpecPtrOutput

func (GoogleCloudAiplatformV1NetworkSpecOutput) ToGoogleCloudAiplatformV1NetworkSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NetworkSpecOutput) ToGoogleCloudAiplatformV1NetworkSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NetworkSpecPtrOutput

type GoogleCloudAiplatformV1NetworkSpecPtrInput 

type GoogleCloudAiplatformV1NetworkSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NetworkSpecPtrOutput() GoogleCloudAiplatformV1NetworkSpecPtrOutput
	ToGoogleCloudAiplatformV1NetworkSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1NetworkSpecPtrOutput
}

GoogleCloudAiplatformV1NetworkSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1NetworkSpecArgs, GoogleCloudAiplatformV1NetworkSpecPtr and GoogleCloudAiplatformV1NetworkSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NetworkSpecPtrInput` via: 

        GoogleCloudAiplatformV1NetworkSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1NetworkSpecPtr 

func GoogleCloudAiplatformV1NetworkSpecPtr(v *GoogleCloudAiplatformV1NetworkSpecArgs) GoogleCloudAiplatformV1NetworkSpecPtrInput

type GoogleCloudAiplatformV1NetworkSpecPtrOutput 

type GoogleCloudAiplatformV1NetworkSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NetworkSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1NetworkSpecPtrOutput) Elem() GoogleCloudAiplatformV1NetworkSpecOutput

func (GoogleCloudAiplatformV1NetworkSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1NetworkSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NetworkSpecPtrOutput) EnableInternetAccess 

func (o GoogleCloudAiplatformV1NetworkSpecPtrOutput) EnableInternetAccess() pulumi.BoolPtrOutput

Whether to enable public internet access. Default false.

func (GoogleCloudAiplatformV1NetworkSpecPtrOutput) Network 

func (o GoogleCloudAiplatformV1NetworkSpecPtrOutput) Network() pulumi.StringPtrOutput

The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)

func (GoogleCloudAiplatformV1NetworkSpecPtrOutput) Subnetwork 

func (o GoogleCloudAiplatformV1NetworkSpecPtrOutput) Subnetwork() pulumi.StringPtrOutput

The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`

func (GoogleCloudAiplatformV1NetworkSpecPtrOutput) ToGoogleCloudAiplatformV1NetworkSpecPtrOutput 

func (o GoogleCloudAiplatformV1NetworkSpecPtrOutput) ToGoogleCloudAiplatformV1NetworkSpecPtrOutput() GoogleCloudAiplatformV1NetworkSpecPtrOutput

func (GoogleCloudAiplatformV1NetworkSpecPtrOutput) ToGoogleCloudAiplatformV1NetworkSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NetworkSpecPtrOutput) ToGoogleCloudAiplatformV1NetworkSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NetworkSpecPtrOutput

type GoogleCloudAiplatformV1NetworkSpecResponse 

type GoogleCloudAiplatformV1NetworkSpecResponse struct {
	// Whether to enable public internet access. Default false.
	EnableInternetAccess bool `pulumi:"enableInternetAccess"`
	// The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
	Network string `pulumi:"network"`
	// The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`
	Subnetwork string `pulumi:"subnetwork"`
}

Network spec.

type GoogleCloudAiplatformV1NetworkSpecResponseOutput 

type GoogleCloudAiplatformV1NetworkSpecResponseOutput struct{ *pulumi.OutputState }

Network spec.

func (GoogleCloudAiplatformV1NetworkSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1NetworkSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NetworkSpecResponseOutput) EnableInternetAccess 

func (o GoogleCloudAiplatformV1NetworkSpecResponseOutput) EnableInternetAccess() pulumi.BoolOutput

Whether to enable public internet access. Default false.

func (GoogleCloudAiplatformV1NetworkSpecResponseOutput) Network 

func (o GoogleCloudAiplatformV1NetworkSpecResponseOutput) Network() pulumi.StringOutput

The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)

func (GoogleCloudAiplatformV1NetworkSpecResponseOutput) Subnetwork 

func (o GoogleCloudAiplatformV1NetworkSpecResponseOutput) Subnetwork() pulumi.StringOutput

The name of the subnet that this instance is in. Format: `projects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id}`

func (GoogleCloudAiplatformV1NetworkSpecResponseOutput) ToGoogleCloudAiplatformV1NetworkSpecResponseOutput 

func (o GoogleCloudAiplatformV1NetworkSpecResponseOutput) ToGoogleCloudAiplatformV1NetworkSpecResponseOutput() GoogleCloudAiplatformV1NetworkSpecResponseOutput

func (GoogleCloudAiplatformV1NetworkSpecResponseOutput) ToGoogleCloudAiplatformV1NetworkSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1NetworkSpecResponseOutput) ToGoogleCloudAiplatformV1NetworkSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NetworkSpecResponseOutput

type GoogleCloudAiplatformV1NfsMount 

type GoogleCloudAiplatformV1NfsMount struct {
	// Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
	MountPoint string `pulumi:"mountPoint"`
	// Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of `server:path`
	Path string `pulumi:"path"`
	// IP address of the NFS server.
	Server string `pulumi:"server"`
}

Represents a mount configuration for Network File System (NFS) to mount.

type GoogleCloudAiplatformV1NfsMountArgs 

type GoogleCloudAiplatformV1NfsMountArgs struct {
	// Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
	MountPoint pulumi.StringInput `pulumi:"mountPoint"`
	// Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of `server:path`
	Path pulumi.StringInput `pulumi:"path"`
	// IP address of the NFS server.
	Server pulumi.StringInput `pulumi:"server"`
}

Represents a mount configuration for Network File System (NFS) to mount.

func (GoogleCloudAiplatformV1NfsMountArgs) ElementType 

func (GoogleCloudAiplatformV1NfsMountArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NfsMountArgs) ToGoogleCloudAiplatformV1NfsMountOutput 

func (i GoogleCloudAiplatformV1NfsMountArgs) ToGoogleCloudAiplatformV1NfsMountOutput() GoogleCloudAiplatformV1NfsMountOutput

func (GoogleCloudAiplatformV1NfsMountArgs) ToGoogleCloudAiplatformV1NfsMountOutputWithContext 

func (i GoogleCloudAiplatformV1NfsMountArgs) ToGoogleCloudAiplatformV1NfsMountOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NfsMountOutput

type GoogleCloudAiplatformV1NfsMountArray 

type GoogleCloudAiplatformV1NfsMountArray []GoogleCloudAiplatformV1NfsMountInput

func (GoogleCloudAiplatformV1NfsMountArray) ElementType 

func (GoogleCloudAiplatformV1NfsMountArray) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NfsMountArray) ToGoogleCloudAiplatformV1NfsMountArrayOutput 

func (i GoogleCloudAiplatformV1NfsMountArray) ToGoogleCloudAiplatformV1NfsMountArrayOutput() GoogleCloudAiplatformV1NfsMountArrayOutput

func (GoogleCloudAiplatformV1NfsMountArray) ToGoogleCloudAiplatformV1NfsMountArrayOutputWithContext 

func (i GoogleCloudAiplatformV1NfsMountArray) ToGoogleCloudAiplatformV1NfsMountArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NfsMountArrayOutput

type GoogleCloudAiplatformV1NfsMountArrayInput 

type GoogleCloudAiplatformV1NfsMountArrayInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NfsMountArrayOutput() GoogleCloudAiplatformV1NfsMountArrayOutput
	ToGoogleCloudAiplatformV1NfsMountArrayOutputWithContext(context.Context) GoogleCloudAiplatformV1NfsMountArrayOutput
}

GoogleCloudAiplatformV1NfsMountArrayInput is an input type that accepts GoogleCloudAiplatformV1NfsMountArray and GoogleCloudAiplatformV1NfsMountArrayOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NfsMountArrayInput` via: 

GoogleCloudAiplatformV1NfsMountArray{ GoogleCloudAiplatformV1NfsMountArgs{...} }

type GoogleCloudAiplatformV1NfsMountArrayOutput 

type GoogleCloudAiplatformV1NfsMountArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NfsMountArrayOutput) ElementType 

func (GoogleCloudAiplatformV1NfsMountArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NfsMountArrayOutput) Index 

func (o GoogleCloudAiplatformV1NfsMountArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1NfsMountOutput

func (GoogleCloudAiplatformV1NfsMountArrayOutput) ToGoogleCloudAiplatformV1NfsMountArrayOutput 

func (o GoogleCloudAiplatformV1NfsMountArrayOutput) ToGoogleCloudAiplatformV1NfsMountArrayOutput() GoogleCloudAiplatformV1NfsMountArrayOutput

func (GoogleCloudAiplatformV1NfsMountArrayOutput) ToGoogleCloudAiplatformV1NfsMountArrayOutputWithContext 

func (o GoogleCloudAiplatformV1NfsMountArrayOutput) ToGoogleCloudAiplatformV1NfsMountArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NfsMountArrayOutput

type GoogleCloudAiplatformV1NfsMountInput 

type GoogleCloudAiplatformV1NfsMountInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NfsMountOutput() GoogleCloudAiplatformV1NfsMountOutput
	ToGoogleCloudAiplatformV1NfsMountOutputWithContext(context.Context) GoogleCloudAiplatformV1NfsMountOutput
}

GoogleCloudAiplatformV1NfsMountInput is an input type that accepts GoogleCloudAiplatformV1NfsMountArgs and GoogleCloudAiplatformV1NfsMountOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NfsMountInput` via: 

GoogleCloudAiplatformV1NfsMountArgs{...}

type GoogleCloudAiplatformV1NfsMountOutput 

type GoogleCloudAiplatformV1NfsMountOutput struct{ *pulumi.OutputState }

Represents a mount configuration for Network File System (NFS) to mount.

func (GoogleCloudAiplatformV1NfsMountOutput) ElementType 

func (GoogleCloudAiplatformV1NfsMountOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NfsMountOutput) MountPoint 

func (o GoogleCloudAiplatformV1NfsMountOutput) MountPoint() pulumi.StringOutput

Destination mount path. The NFS will be mounted for the user under /mnt/nfs/

func (GoogleCloudAiplatformV1NfsMountOutput) Path 

func (o GoogleCloudAiplatformV1NfsMountOutput) Path() pulumi.StringOutput

Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of `server:path`

func (GoogleCloudAiplatformV1NfsMountOutput) Server 

func (o GoogleCloudAiplatformV1NfsMountOutput) Server() pulumi.StringOutput

IP address of the NFS server.

func (GoogleCloudAiplatformV1NfsMountOutput) ToGoogleCloudAiplatformV1NfsMountOutput 

func (o GoogleCloudAiplatformV1NfsMountOutput) ToGoogleCloudAiplatformV1NfsMountOutput() GoogleCloudAiplatformV1NfsMountOutput

func (GoogleCloudAiplatformV1NfsMountOutput) ToGoogleCloudAiplatformV1NfsMountOutputWithContext 

func (o GoogleCloudAiplatformV1NfsMountOutput) ToGoogleCloudAiplatformV1NfsMountOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NfsMountOutput

type GoogleCloudAiplatformV1NfsMountResponse 

type GoogleCloudAiplatformV1NfsMountResponse struct {
	// Destination mount path. The NFS will be mounted for the user under /mnt/nfs/
	MountPoint string `pulumi:"mountPoint"`
	// Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of `server:path`
	Path string `pulumi:"path"`
	// IP address of the NFS server.
	Server string `pulumi:"server"`
}

Represents a mount configuration for Network File System (NFS) to mount.

type GoogleCloudAiplatformV1NfsMountResponseArrayOutput 

type GoogleCloudAiplatformV1NfsMountResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NfsMountResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1NfsMountResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NfsMountResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1NfsMountResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1NfsMountResponseOutput

func (GoogleCloudAiplatformV1NfsMountResponseArrayOutput) ToGoogleCloudAiplatformV1NfsMountResponseArrayOutput 

func (o GoogleCloudAiplatformV1NfsMountResponseArrayOutput) ToGoogleCloudAiplatformV1NfsMountResponseArrayOutput() GoogleCloudAiplatformV1NfsMountResponseArrayOutput

func (GoogleCloudAiplatformV1NfsMountResponseArrayOutput) ToGoogleCloudAiplatformV1NfsMountResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1NfsMountResponseArrayOutput) ToGoogleCloudAiplatformV1NfsMountResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NfsMountResponseArrayOutput

type GoogleCloudAiplatformV1NfsMountResponseOutput 

type GoogleCloudAiplatformV1NfsMountResponseOutput struct{ *pulumi.OutputState }

Represents a mount configuration for Network File System (NFS) to mount.

func (GoogleCloudAiplatformV1NfsMountResponseOutput) ElementType 

func (GoogleCloudAiplatformV1NfsMountResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NfsMountResponseOutput) MountPoint 

func (o GoogleCloudAiplatformV1NfsMountResponseOutput) MountPoint() pulumi.StringOutput

Destination mount path. The NFS will be mounted for the user under /mnt/nfs/

func (GoogleCloudAiplatformV1NfsMountResponseOutput) Path 

func (o GoogleCloudAiplatformV1NfsMountResponseOutput) Path() pulumi.StringOutput

Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of `server:path`

func (GoogleCloudAiplatformV1NfsMountResponseOutput) Server 

func (o GoogleCloudAiplatformV1NfsMountResponseOutput) Server() pulumi.StringOutput

IP address of the NFS server.

func (GoogleCloudAiplatformV1NfsMountResponseOutput) ToGoogleCloudAiplatformV1NfsMountResponseOutput 

func (o GoogleCloudAiplatformV1NfsMountResponseOutput) ToGoogleCloudAiplatformV1NfsMountResponseOutput() GoogleCloudAiplatformV1NfsMountResponseOutput

func (GoogleCloudAiplatformV1NfsMountResponseOutput) ToGoogleCloudAiplatformV1NfsMountResponseOutputWithContext 

func (o GoogleCloudAiplatformV1NfsMountResponseOutput) ToGoogleCloudAiplatformV1NfsMountResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NfsMountResponseOutput

type GoogleCloudAiplatformV1NotebookEucConfig 

type GoogleCloudAiplatformV1NotebookEucConfig struct {
	// Input only. Whether EUC is disabled in this NotebookRuntimeTemplate. In proto3, the default value of a boolean is false. In this way, by default EUC will be enabled for NotebookRuntimeTemplate.
	EucDisabled *bool `pulumi:"eucDisabled"`
}

The euc configuration of NotebookRuntimeTemplate.

type GoogleCloudAiplatformV1NotebookEucConfigArgs 

type GoogleCloudAiplatformV1NotebookEucConfigArgs struct {
	// Input only. Whether EUC is disabled in this NotebookRuntimeTemplate. In proto3, the default value of a boolean is false. In this way, by default EUC will be enabled for NotebookRuntimeTemplate.
	EucDisabled pulumi.BoolPtrInput `pulumi:"eucDisabled"`
}

The euc configuration of NotebookRuntimeTemplate.

func (GoogleCloudAiplatformV1NotebookEucConfigArgs) ElementType 

func (GoogleCloudAiplatformV1NotebookEucConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NotebookEucConfigArgs) ToGoogleCloudAiplatformV1NotebookEucConfigOutput 

func (i GoogleCloudAiplatformV1NotebookEucConfigArgs) ToGoogleCloudAiplatformV1NotebookEucConfigOutput() GoogleCloudAiplatformV1NotebookEucConfigOutput

func (GoogleCloudAiplatformV1NotebookEucConfigArgs) ToGoogleCloudAiplatformV1NotebookEucConfigOutputWithContext 

func (i GoogleCloudAiplatformV1NotebookEucConfigArgs) ToGoogleCloudAiplatformV1NotebookEucConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NotebookEucConfigOutput

func (GoogleCloudAiplatformV1NotebookEucConfigArgs) ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutput 

func (i GoogleCloudAiplatformV1NotebookEucConfigArgs) ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutput() GoogleCloudAiplatformV1NotebookEucConfigPtrOutput

func (GoogleCloudAiplatformV1NotebookEucConfigArgs) ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1NotebookEucConfigArgs) ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NotebookEucConfigPtrOutput

type GoogleCloudAiplatformV1NotebookEucConfigInput 

type GoogleCloudAiplatformV1NotebookEucConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NotebookEucConfigOutput() GoogleCloudAiplatformV1NotebookEucConfigOutput
	ToGoogleCloudAiplatformV1NotebookEucConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1NotebookEucConfigOutput
}

GoogleCloudAiplatformV1NotebookEucConfigInput is an input type that accepts GoogleCloudAiplatformV1NotebookEucConfigArgs and GoogleCloudAiplatformV1NotebookEucConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NotebookEucConfigInput` via: 

GoogleCloudAiplatformV1NotebookEucConfigArgs{...}

type GoogleCloudAiplatformV1NotebookEucConfigOutput 

type GoogleCloudAiplatformV1NotebookEucConfigOutput struct{ *pulumi.OutputState }

The euc configuration of NotebookRuntimeTemplate.

func (GoogleCloudAiplatformV1NotebookEucConfigOutput) ElementType 

func (GoogleCloudAiplatformV1NotebookEucConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NotebookEucConfigOutput) EucDisabled 

func (o GoogleCloudAiplatformV1NotebookEucConfigOutput) EucDisabled() pulumi.BoolPtrOutput

Input only. Whether EUC is disabled in this NotebookRuntimeTemplate. In proto3, the default value of a boolean is false. In this way, by default EUC will be enabled for NotebookRuntimeTemplate.

func (GoogleCloudAiplatformV1NotebookEucConfigOutput) ToGoogleCloudAiplatformV1NotebookEucConfigOutput 

func (o GoogleCloudAiplatformV1NotebookEucConfigOutput) ToGoogleCloudAiplatformV1NotebookEucConfigOutput() GoogleCloudAiplatformV1NotebookEucConfigOutput

func (GoogleCloudAiplatformV1NotebookEucConfigOutput) ToGoogleCloudAiplatformV1NotebookEucConfigOutputWithContext 

func (o GoogleCloudAiplatformV1NotebookEucConfigOutput) ToGoogleCloudAiplatformV1NotebookEucConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NotebookEucConfigOutput

func (GoogleCloudAiplatformV1NotebookEucConfigOutput) ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutput 

func (o GoogleCloudAiplatformV1NotebookEucConfigOutput) ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutput() GoogleCloudAiplatformV1NotebookEucConfigPtrOutput

func (GoogleCloudAiplatformV1NotebookEucConfigOutput) ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NotebookEucConfigOutput) ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NotebookEucConfigPtrOutput

type GoogleCloudAiplatformV1NotebookEucConfigPtrInput 

type GoogleCloudAiplatformV1NotebookEucConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutput() GoogleCloudAiplatformV1NotebookEucConfigPtrOutput
	ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1NotebookEucConfigPtrOutput
}

GoogleCloudAiplatformV1NotebookEucConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1NotebookEucConfigArgs, GoogleCloudAiplatformV1NotebookEucConfigPtr and GoogleCloudAiplatformV1NotebookEucConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NotebookEucConfigPtrInput` via: 

        GoogleCloudAiplatformV1NotebookEucConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1NotebookEucConfigPtr 

func GoogleCloudAiplatformV1NotebookEucConfigPtr(v *GoogleCloudAiplatformV1NotebookEucConfigArgs) GoogleCloudAiplatformV1NotebookEucConfigPtrInput

type GoogleCloudAiplatformV1NotebookEucConfigPtrOutput 

type GoogleCloudAiplatformV1NotebookEucConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NotebookEucConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1NotebookEucConfigPtrOutput) Elem() GoogleCloudAiplatformV1NotebookEucConfigOutput

func (GoogleCloudAiplatformV1NotebookEucConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1NotebookEucConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NotebookEucConfigPtrOutput) EucDisabled 

func (o GoogleCloudAiplatformV1NotebookEucConfigPtrOutput) EucDisabled() pulumi.BoolPtrOutput

Input only. Whether EUC is disabled in this NotebookRuntimeTemplate. In proto3, the default value of a boolean is false. In this way, by default EUC will be enabled for NotebookRuntimeTemplate.

func (GoogleCloudAiplatformV1NotebookEucConfigPtrOutput) ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutput 

func (o GoogleCloudAiplatformV1NotebookEucConfigPtrOutput) ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutput() GoogleCloudAiplatformV1NotebookEucConfigPtrOutput

func (GoogleCloudAiplatformV1NotebookEucConfigPtrOutput) ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NotebookEucConfigPtrOutput) ToGoogleCloudAiplatformV1NotebookEucConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NotebookEucConfigPtrOutput

type GoogleCloudAiplatformV1NotebookEucConfigResponse 

type GoogleCloudAiplatformV1NotebookEucConfigResponse struct {
	// Whether ActAs check is bypassed for service account attached to the VM. If false, we need ActAs check for the default Compute Engine Service account. When a Runtime is created, a VM is allocated using Default Compute Engine Service Account. Any user requesting to use this Runtime requires Service Account User (ActAs) permission over this SA. If true, Runtime owner is using EUC and does not require the above permission as VM no longer use default Compute Engine SA, but a P4SA.
	BypassActasCheck bool `pulumi:"bypassActasCheck"`
	// Input only. Whether EUC is disabled in this NotebookRuntimeTemplate. In proto3, the default value of a boolean is false. In this way, by default EUC will be enabled for NotebookRuntimeTemplate.
	EucDisabled bool `pulumi:"eucDisabled"`
}

The euc configuration of NotebookRuntimeTemplate.

type GoogleCloudAiplatformV1NotebookEucConfigResponseOutput 

type GoogleCloudAiplatformV1NotebookEucConfigResponseOutput struct{ *pulumi.OutputState }

The euc configuration of NotebookRuntimeTemplate.

func (GoogleCloudAiplatformV1NotebookEucConfigResponseOutput) BypassActasCheck 

func (o GoogleCloudAiplatformV1NotebookEucConfigResponseOutput) BypassActasCheck() pulumi.BoolOutput

Whether ActAs check is bypassed for service account attached to the VM. If false, we need ActAs check for the default Compute Engine Service account. When a Runtime is created, a VM is allocated using Default Compute Engine Service Account. Any user requesting to use this Runtime requires Service Account User (ActAs) permission over this SA. If true, Runtime owner is using EUC and does not require the above permission as VM no longer use default Compute Engine SA, but a P4SA.

func (GoogleCloudAiplatformV1NotebookEucConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1NotebookEucConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NotebookEucConfigResponseOutput) EucDisabled 

func (o GoogleCloudAiplatformV1NotebookEucConfigResponseOutput) EucDisabled() pulumi.BoolOutput

Input only. Whether EUC is disabled in this NotebookRuntimeTemplate. In proto3, the default value of a boolean is false. In this way, by default EUC will be enabled for NotebookRuntimeTemplate.

func (GoogleCloudAiplatformV1NotebookEucConfigResponseOutput) ToGoogleCloudAiplatformV1NotebookEucConfigResponseOutput 

func (o GoogleCloudAiplatformV1NotebookEucConfigResponseOutput) ToGoogleCloudAiplatformV1NotebookEucConfigResponseOutput() GoogleCloudAiplatformV1NotebookEucConfigResponseOutput

func (GoogleCloudAiplatformV1NotebookEucConfigResponseOutput) ToGoogleCloudAiplatformV1NotebookEucConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1NotebookEucConfigResponseOutput) ToGoogleCloudAiplatformV1NotebookEucConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NotebookEucConfigResponseOutput

type GoogleCloudAiplatformV1NotebookIdleShutdownConfig 

type GoogleCloudAiplatformV1NotebookIdleShutdownConfig struct {
	// Whether Idle Shutdown is disabled in this NotebookRuntimeTemplate.
	IdleShutdownDisabled *bool `pulumi:"idleShutdownDisabled"`
	// Duration is accurate to the second. In Notebook, Idle Timeout is accurate to minute so the range of idle_timeout (second) is: 10 * 60 ~ 1440 * 60.
	IdleTimeout string `pulumi:"idleTimeout"`
}

The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field.

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs 

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs struct {
	// Whether Idle Shutdown is disabled in this NotebookRuntimeTemplate.
	IdleShutdownDisabled pulumi.BoolPtrInput `pulumi:"idleShutdownDisabled"`
	// Duration is accurate to the second. In Notebook, Idle Timeout is accurate to minute so the range of idle_timeout (second) is: 10 * 60 ~ 1440 * 60.
	IdleTimeout pulumi.StringInput `pulumi:"idleTimeout"`
}

The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field.

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs) ElementType 

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput 

func (i GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput() GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigOutputWithContext 

func (i GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput 

func (i GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput() GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigInput 

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput() GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput
	ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput
}

GoogleCloudAiplatformV1NotebookIdleShutdownConfigInput is an input type that accepts GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs and GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NotebookIdleShutdownConfigInput` via: 

GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs{...}

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput 

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput struct{ *pulumi.OutputState }

The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field.

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) ElementType 

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) IdleShutdownDisabled 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) IdleShutdownDisabled() pulumi.BoolPtrOutput

Whether Idle Shutdown is disabled in this NotebookRuntimeTemplate.

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) IdleTimeout 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) IdleTimeout() pulumi.StringOutput

Duration is accurate to the second. In Notebook, Idle Timeout is accurate to minute so the range of idle_timeout (second) is: 10 * 60 ~ 1440 * 60.

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput() GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigOutputWithContext 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput() GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrInput 

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput() GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput
	ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput
}

GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs, GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtr and GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrInput` via: 

        GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtr 

func GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtr(v *GoogleCloudAiplatformV1NotebookIdleShutdownConfigArgs) GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrInput

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput 

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput) Elem() GoogleCloudAiplatformV1NotebookIdleShutdownConfigOutput

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput) IdleShutdownDisabled 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput) IdleShutdownDisabled() pulumi.BoolPtrOutput

Whether Idle Shutdown is disabled in this NotebookRuntimeTemplate.

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput) IdleTimeout 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput) IdleTimeout() pulumi.StringPtrOutput

Duration is accurate to the second. In Notebook, Idle Timeout is accurate to minute so the range of idle_timeout (second) is: 10 * 60 ~ 1440 * 60.

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput() GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrOutput

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponse 

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponse struct {
	// Whether Idle Shutdown is disabled in this NotebookRuntimeTemplate.
	IdleShutdownDisabled bool `pulumi:"idleShutdownDisabled"`
	// Duration is accurate to the second. In Notebook, Idle Timeout is accurate to minute so the range of idle_timeout (second) is: 10 * 60 ~ 1440 * 60.
	IdleTimeout string `pulumi:"idleTimeout"`
}

The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field.

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput 

type GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput struct{ *pulumi.OutputState }

The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field.

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput) IdleShutdownDisabled 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput) IdleShutdownDisabled() pulumi.BoolOutput

Whether Idle Shutdown is disabled in this NotebookRuntimeTemplate.

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput) IdleTimeout 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput) IdleTimeout() pulumi.StringOutput

Duration is accurate to the second. In Notebook, Idle Timeout is accurate to minute so the range of idle_timeout (second) is: 10 * 60 ~ 1440 * 60.

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput() GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput

func (GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput) ToGoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput

type GoogleCloudAiplatformV1PersistentDiskSpec 

type GoogleCloudAiplatformV1PersistentDiskSpec struct {
	// Size in GB of the disk (default is 100GB).
	DiskSizeGb *string `pulumi:"diskSizeGb"`
	// Type of the disk (default is "pd-standard"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) "pd-standard" (Persistent Disk Hard Disk Drive) "pd-balanced" (Balanced Persistent Disk) "pd-extreme" (Extreme Persistent Disk)
	DiskType *string `pulumi:"diskType"`
}

Represents the spec of persistent disk options.

type GoogleCloudAiplatformV1PersistentDiskSpecArgs 

type GoogleCloudAiplatformV1PersistentDiskSpecArgs struct {
	// Size in GB of the disk (default is 100GB).
	DiskSizeGb pulumi.StringPtrInput `pulumi:"diskSizeGb"`
	// Type of the disk (default is "pd-standard"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) "pd-standard" (Persistent Disk Hard Disk Drive) "pd-balanced" (Balanced Persistent Disk) "pd-extreme" (Extreme Persistent Disk)
	DiskType pulumi.StringPtrInput `pulumi:"diskType"`
}

Represents the spec of persistent disk options.

func (GoogleCloudAiplatformV1PersistentDiskSpecArgs) ElementType 

func (GoogleCloudAiplatformV1PersistentDiskSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PersistentDiskSpecArgs) ToGoogleCloudAiplatformV1PersistentDiskSpecOutput 

func (i GoogleCloudAiplatformV1PersistentDiskSpecArgs) ToGoogleCloudAiplatformV1PersistentDiskSpecOutput() GoogleCloudAiplatformV1PersistentDiskSpecOutput

func (GoogleCloudAiplatformV1PersistentDiskSpecArgs) ToGoogleCloudAiplatformV1PersistentDiskSpecOutputWithContext 

func (i GoogleCloudAiplatformV1PersistentDiskSpecArgs) ToGoogleCloudAiplatformV1PersistentDiskSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PersistentDiskSpecOutput

func (GoogleCloudAiplatformV1PersistentDiskSpecArgs) ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutput 

func (i GoogleCloudAiplatformV1PersistentDiskSpecArgs) ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutput() GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput

func (GoogleCloudAiplatformV1PersistentDiskSpecArgs) ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1PersistentDiskSpecArgs) ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput

type GoogleCloudAiplatformV1PersistentDiskSpecInput 

type GoogleCloudAiplatformV1PersistentDiskSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PersistentDiskSpecOutput() GoogleCloudAiplatformV1PersistentDiskSpecOutput
	ToGoogleCloudAiplatformV1PersistentDiskSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1PersistentDiskSpecOutput
}

GoogleCloudAiplatformV1PersistentDiskSpecInput is an input type that accepts GoogleCloudAiplatformV1PersistentDiskSpecArgs and GoogleCloudAiplatformV1PersistentDiskSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PersistentDiskSpecInput` via: 

GoogleCloudAiplatformV1PersistentDiskSpecArgs{...}

type GoogleCloudAiplatformV1PersistentDiskSpecOutput 

type GoogleCloudAiplatformV1PersistentDiskSpecOutput struct{ *pulumi.OutputState }

Represents the spec of persistent disk options.

func (GoogleCloudAiplatformV1PersistentDiskSpecOutput) DiskSizeGb 

func (o GoogleCloudAiplatformV1PersistentDiskSpecOutput) DiskSizeGb() pulumi.StringPtrOutput

Size in GB of the disk (default is 100GB).

func (GoogleCloudAiplatformV1PersistentDiskSpecOutput) DiskType 

func (o GoogleCloudAiplatformV1PersistentDiskSpecOutput) DiskType() pulumi.StringPtrOutput

Type of the disk (default is "pd-standard"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) "pd-standard" (Persistent Disk Hard Disk Drive) "pd-balanced" (Balanced Persistent Disk) "pd-extreme" (Extreme Persistent Disk)

func (GoogleCloudAiplatformV1PersistentDiskSpecOutput) ElementType 

func (GoogleCloudAiplatformV1PersistentDiskSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PersistentDiskSpecOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecOutput 

func (o GoogleCloudAiplatformV1PersistentDiskSpecOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecOutput() GoogleCloudAiplatformV1PersistentDiskSpecOutput

func (GoogleCloudAiplatformV1PersistentDiskSpecOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecOutputWithContext 

func (o GoogleCloudAiplatformV1PersistentDiskSpecOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PersistentDiskSpecOutput

func (GoogleCloudAiplatformV1PersistentDiskSpecOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutput 

func (o GoogleCloudAiplatformV1PersistentDiskSpecOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutput() GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput

func (GoogleCloudAiplatformV1PersistentDiskSpecOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PersistentDiskSpecOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput

type GoogleCloudAiplatformV1PersistentDiskSpecPtrInput 

type GoogleCloudAiplatformV1PersistentDiskSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutput() GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput
	ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput
}

GoogleCloudAiplatformV1PersistentDiskSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1PersistentDiskSpecArgs, GoogleCloudAiplatformV1PersistentDiskSpecPtr and GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PersistentDiskSpecPtrInput` via: 

        GoogleCloudAiplatformV1PersistentDiskSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1PersistentDiskSpecPtr 

func GoogleCloudAiplatformV1PersistentDiskSpecPtr(v *GoogleCloudAiplatformV1PersistentDiskSpecArgs) GoogleCloudAiplatformV1PersistentDiskSpecPtrInput

type GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput 

type GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput) DiskSizeGb 

func (o GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput) DiskSizeGb() pulumi.StringPtrOutput

Size in GB of the disk (default is 100GB).

func (GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput) DiskType 

func (o GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput) DiskType() pulumi.StringPtrOutput

Type of the disk (default is "pd-standard"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) "pd-standard" (Persistent Disk Hard Disk Drive) "pd-balanced" (Balanced Persistent Disk) "pd-extreme" (Extreme Persistent Disk)

func (GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput) Elem() GoogleCloudAiplatformV1PersistentDiskSpecOutput

func (GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutput 

func (o GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutput() GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput

func (GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PersistentDiskSpecPtrOutput

type GoogleCloudAiplatformV1PersistentDiskSpecResponse 

type GoogleCloudAiplatformV1PersistentDiskSpecResponse struct {
	// Size in GB of the disk (default is 100GB).
	DiskSizeGb string `pulumi:"diskSizeGb"`
	// Type of the disk (default is "pd-standard"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) "pd-standard" (Persistent Disk Hard Disk Drive) "pd-balanced" (Balanced Persistent Disk) "pd-extreme" (Extreme Persistent Disk)
	DiskType string `pulumi:"diskType"`
}

Represents the spec of persistent disk options.

type GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput 

type GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput struct{ *pulumi.OutputState }

Represents the spec of persistent disk options.

func (GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput) DiskSizeGb 

func (o GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput) DiskSizeGb() pulumi.StringOutput

Size in GB of the disk (default is 100GB).

func (GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput) DiskType 

func (o GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput) DiskType() pulumi.StringOutput

Type of the disk (default is "pd-standard"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) "pd-standard" (Persistent Disk Hard Disk Drive) "pd-balanced" (Balanced Persistent Disk) "pd-extreme" (Extreme Persistent Disk)

func (GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecResponseOutput 

func (o GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecResponseOutput() GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput

func (GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput) ToGoogleCloudAiplatformV1PersistentDiskSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput

type GoogleCloudAiplatformV1PipelineJob 

type GoogleCloudAiplatformV1PipelineJob struct {
	// The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName *string `pulumi:"displayName"`
	// Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
	EncryptionSpec *GoogleCloudAiplatformV1EncryptionSpec `pulumi:"encryptionSpec"`
	// The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
	Labels map[string]string `pulumi:"labels"`
	// The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
	Network *string `pulumi:"network"`
	// The spec of the pipeline.
	PipelineSpec map[string]string `pulumi:"pipelineSpec"`
	// A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
	ReservedIpRanges []string `pulumi:"reservedIpRanges"`
	// Runtime config of the pipeline.
	RuntimeConfig *GoogleCloudAiplatformV1PipelineJobRuntimeConfig `pulumi:"runtimeConfig"`
	// The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
	ServiceAccount *string `pulumi:"serviceAccount"`
	// A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
	TemplateUri *string `pulumi:"templateUri"`
}

An instance of a machine learning PipelineJob.

type GoogleCloudAiplatformV1PipelineJobArgs 

type GoogleCloudAiplatformV1PipelineJobArgs struct {
	// The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringPtrInput `pulumi:"displayName"`
	// Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput `pulumi:"encryptionSpec"`
	// The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
	Labels pulumi.StringMapInput `pulumi:"labels"`
	// The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
	Network pulumi.StringPtrInput `pulumi:"network"`
	// The spec of the pipeline.
	PipelineSpec pulumi.StringMapInput `pulumi:"pipelineSpec"`
	// A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
	ReservedIpRanges pulumi.StringArrayInput `pulumi:"reservedIpRanges"`
	// Runtime config of the pipeline.
	RuntimeConfig GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrInput `pulumi:"runtimeConfig"`
	// The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
	ServiceAccount pulumi.StringPtrInput `pulumi:"serviceAccount"`
	// A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
	TemplateUri pulumi.StringPtrInput `pulumi:"templateUri"`
}

An instance of a machine learning PipelineJob.

func (GoogleCloudAiplatformV1PipelineJobArgs) ElementType 

func (GoogleCloudAiplatformV1PipelineJobArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineJobArgs) ToGoogleCloudAiplatformV1PipelineJobOutput 

func (i GoogleCloudAiplatformV1PipelineJobArgs) ToGoogleCloudAiplatformV1PipelineJobOutput() GoogleCloudAiplatformV1PipelineJobOutput

func (GoogleCloudAiplatformV1PipelineJobArgs) ToGoogleCloudAiplatformV1PipelineJobOutputWithContext 

func (i GoogleCloudAiplatformV1PipelineJobArgs) ToGoogleCloudAiplatformV1PipelineJobOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobOutput

func (GoogleCloudAiplatformV1PipelineJobArgs) ToGoogleCloudAiplatformV1PipelineJobPtrOutput 

func (i GoogleCloudAiplatformV1PipelineJobArgs) ToGoogleCloudAiplatformV1PipelineJobPtrOutput() GoogleCloudAiplatformV1PipelineJobPtrOutput

func (GoogleCloudAiplatformV1PipelineJobArgs) ToGoogleCloudAiplatformV1PipelineJobPtrOutputWithContext 

func (i GoogleCloudAiplatformV1PipelineJobArgs) ToGoogleCloudAiplatformV1PipelineJobPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobPtrOutput

type GoogleCloudAiplatformV1PipelineJobDetailResponse 

type GoogleCloudAiplatformV1PipelineJobDetailResponse struct {
	// The context of the pipeline.
	PipelineContext GoogleCloudAiplatformV1ContextResponse `pulumi:"pipelineContext"`
	// The context of the current pipeline run.
	PipelineRunContext GoogleCloudAiplatformV1ContextResponse `pulumi:"pipelineRunContext"`
	// The runtime details of the tasks under the pipeline.
	TaskDetails []GoogleCloudAiplatformV1PipelineTaskDetailResponse `pulumi:"taskDetails"`
}

The runtime detail of PipelineJob.

type GoogleCloudAiplatformV1PipelineJobDetailResponseOutput 

type GoogleCloudAiplatformV1PipelineJobDetailResponseOutput struct{ *pulumi.OutputState }

The runtime detail of PipelineJob.

func (GoogleCloudAiplatformV1PipelineJobDetailResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineJobDetailResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineJobDetailResponseOutput) PipelineContext 

func (o GoogleCloudAiplatformV1PipelineJobDetailResponseOutput) PipelineContext() GoogleCloudAiplatformV1ContextResponseOutput

The context of the pipeline.

func (GoogleCloudAiplatformV1PipelineJobDetailResponseOutput) PipelineRunContext 

func (o GoogleCloudAiplatformV1PipelineJobDetailResponseOutput) PipelineRunContext() GoogleCloudAiplatformV1ContextResponseOutput

The context of the current pipeline run.

func (GoogleCloudAiplatformV1PipelineJobDetailResponseOutput) TaskDetails 

func (o GoogleCloudAiplatformV1PipelineJobDetailResponseOutput) TaskDetails() GoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput

The runtime details of the tasks under the pipeline.

func (GoogleCloudAiplatformV1PipelineJobDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineJobDetailResponseOutput 

func (o GoogleCloudAiplatformV1PipelineJobDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineJobDetailResponseOutput() GoogleCloudAiplatformV1PipelineJobDetailResponseOutput

func (GoogleCloudAiplatformV1PipelineJobDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineJobDetailResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineJobDetailResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobDetailResponseOutput

type GoogleCloudAiplatformV1PipelineJobInput 

type GoogleCloudAiplatformV1PipelineJobInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PipelineJobOutput() GoogleCloudAiplatformV1PipelineJobOutput
	ToGoogleCloudAiplatformV1PipelineJobOutputWithContext(context.Context) GoogleCloudAiplatformV1PipelineJobOutput
}

GoogleCloudAiplatformV1PipelineJobInput is an input type that accepts GoogleCloudAiplatformV1PipelineJobArgs and GoogleCloudAiplatformV1PipelineJobOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PipelineJobInput` via: 

GoogleCloudAiplatformV1PipelineJobArgs{...}

type GoogleCloudAiplatformV1PipelineJobOutput 

type GoogleCloudAiplatformV1PipelineJobOutput struct{ *pulumi.OutputState }

An instance of a machine learning PipelineJob.

func (GoogleCloudAiplatformV1PipelineJobOutput) DisplayName 

func (o GoogleCloudAiplatformV1PipelineJobOutput) DisplayName() pulumi.StringPtrOutput

The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (GoogleCloudAiplatformV1PipelineJobOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineJobOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineJobOutput) EncryptionSpec 

func (o GoogleCloudAiplatformV1PipelineJobOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecPtrOutput

Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.

func (GoogleCloudAiplatformV1PipelineJobOutput) Labels 

func (o GoogleCloudAiplatformV1PipelineJobOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.

func (GoogleCloudAiplatformV1PipelineJobOutput) Network 

func (o GoogleCloudAiplatformV1PipelineJobOutput) Network() pulumi.StringPtrOutput

The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.

func (GoogleCloudAiplatformV1PipelineJobOutput) PipelineSpec 

func (o GoogleCloudAiplatformV1PipelineJobOutput) PipelineSpec() pulumi.StringMapOutput

The spec of the pipeline.

func (GoogleCloudAiplatformV1PipelineJobOutput) ReservedIpRanges 

func (o GoogleCloudAiplatformV1PipelineJobOutput) ReservedIpRanges() pulumi.StringArrayOutput

A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

func (GoogleCloudAiplatformV1PipelineJobOutput) RuntimeConfig 

func (o GoogleCloudAiplatformV1PipelineJobOutput) RuntimeConfig() GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput

Runtime config of the pipeline.

func (GoogleCloudAiplatformV1PipelineJobOutput) ServiceAccount 

func (o GoogleCloudAiplatformV1PipelineJobOutput) ServiceAccount() pulumi.StringPtrOutput

The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.

func (GoogleCloudAiplatformV1PipelineJobOutput) TemplateUri 

func (o GoogleCloudAiplatformV1PipelineJobOutput) TemplateUri() pulumi.StringPtrOutput

A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.

func (GoogleCloudAiplatformV1PipelineJobOutput) ToGoogleCloudAiplatformV1PipelineJobOutput 

func (o GoogleCloudAiplatformV1PipelineJobOutput) ToGoogleCloudAiplatformV1PipelineJobOutput() GoogleCloudAiplatformV1PipelineJobOutput

func (GoogleCloudAiplatformV1PipelineJobOutput) ToGoogleCloudAiplatformV1PipelineJobOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobOutput) ToGoogleCloudAiplatformV1PipelineJobOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobOutput

func (GoogleCloudAiplatformV1PipelineJobOutput) ToGoogleCloudAiplatformV1PipelineJobPtrOutput 

func (o GoogleCloudAiplatformV1PipelineJobOutput) ToGoogleCloudAiplatformV1PipelineJobPtrOutput() GoogleCloudAiplatformV1PipelineJobPtrOutput

func (GoogleCloudAiplatformV1PipelineJobOutput) ToGoogleCloudAiplatformV1PipelineJobPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobOutput) ToGoogleCloudAiplatformV1PipelineJobPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobPtrOutput

type GoogleCloudAiplatformV1PipelineJobPtrInput 

type GoogleCloudAiplatformV1PipelineJobPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PipelineJobPtrOutput() GoogleCloudAiplatformV1PipelineJobPtrOutput
	ToGoogleCloudAiplatformV1PipelineJobPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1PipelineJobPtrOutput
}

GoogleCloudAiplatformV1PipelineJobPtrInput is an input type that accepts GoogleCloudAiplatformV1PipelineJobArgs, GoogleCloudAiplatformV1PipelineJobPtr and GoogleCloudAiplatformV1PipelineJobPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PipelineJobPtrInput` via: 

        GoogleCloudAiplatformV1PipelineJobArgs{...}

or:

        nil

func GoogleCloudAiplatformV1PipelineJobPtr 

func GoogleCloudAiplatformV1PipelineJobPtr(v *GoogleCloudAiplatformV1PipelineJobArgs) GoogleCloudAiplatformV1PipelineJobPtrInput

type GoogleCloudAiplatformV1PipelineJobPtrOutput 

type GoogleCloudAiplatformV1PipelineJobPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) DisplayName 

func (o GoogleCloudAiplatformV1PipelineJobPtrOutput) DisplayName() pulumi.StringPtrOutput

The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) Elem 

func (o GoogleCloudAiplatformV1PipelineJobPtrOutput) Elem() GoogleCloudAiplatformV1PipelineJobOutput

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) EncryptionSpec 

func (o GoogleCloudAiplatformV1PipelineJobPtrOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecPtrOutput

Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) Labels 

func (o GoogleCloudAiplatformV1PipelineJobPtrOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) Network 

func (o GoogleCloudAiplatformV1PipelineJobPtrOutput) Network() pulumi.StringPtrOutput

The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) PipelineSpec 

func (o GoogleCloudAiplatformV1PipelineJobPtrOutput) PipelineSpec() pulumi.StringMapOutput

The spec of the pipeline.

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) ReservedIpRanges 

func (o GoogleCloudAiplatformV1PipelineJobPtrOutput) ReservedIpRanges() pulumi.StringArrayOutput

A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) RuntimeConfig 

func (o GoogleCloudAiplatformV1PipelineJobPtrOutput) RuntimeConfig() GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput

Runtime config of the pipeline.

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) ServiceAccount 

func (o GoogleCloudAiplatformV1PipelineJobPtrOutput) ServiceAccount() pulumi.StringPtrOutput

The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) TemplateUri 

func (o GoogleCloudAiplatformV1PipelineJobPtrOutput) TemplateUri() pulumi.StringPtrOutput

A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) ToGoogleCloudAiplatformV1PipelineJobPtrOutput 

func (o GoogleCloudAiplatformV1PipelineJobPtrOutput) ToGoogleCloudAiplatformV1PipelineJobPtrOutput() GoogleCloudAiplatformV1PipelineJobPtrOutput

func (GoogleCloudAiplatformV1PipelineJobPtrOutput) ToGoogleCloudAiplatformV1PipelineJobPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobPtrOutput) ToGoogleCloudAiplatformV1PipelineJobPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobPtrOutput

type GoogleCloudAiplatformV1PipelineJobResponse 

type GoogleCloudAiplatformV1PipelineJobResponse struct {
	// Pipeline creation time.
	CreateTime string `pulumi:"createTime"`
	// The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Pipeline end time.
	EndTime string `pulumi:"endTime"`
	// The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
	Error GoogleRpcStatusResponse `pulumi:"error"`
	// The details of pipeline run. Not available in the list view.
	JobDetail GoogleCloudAiplatformV1PipelineJobDetailResponse `pulumi:"jobDetail"`
	// The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
	Labels map[string]string `pulumi:"labels"`
	// The resource name of the PipelineJob.
	Name string `pulumi:"name"`
	// The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
	Network string `pulumi:"network"`
	// The spec of the pipeline.
	PipelineSpec map[string]string `pulumi:"pipelineSpec"`
	// A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
	ReservedIpRanges []string `pulumi:"reservedIpRanges"`
	// Runtime config of the pipeline.
	RuntimeConfig GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse `pulumi:"runtimeConfig"`
	// The schedule resource name. Only returned if the Pipeline is created by Schedule API.
	ScheduleName string `pulumi:"scheduleName"`
	// The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
	ServiceAccount string `pulumi:"serviceAccount"`
	// Pipeline start time.
	StartTime string `pulumi:"startTime"`
	// The detailed state of the job.
	State string `pulumi:"state"`
	// Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
	TemplateMetadata GoogleCloudAiplatformV1PipelineTemplateMetadataResponse `pulumi:"templateMetadata"`
	// A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
	TemplateUri string `pulumi:"templateUri"`
	// Timestamp when this PipelineJob was most recently updated.
	UpdateTime string `pulumi:"updateTime"`
}

An instance of a machine learning PipelineJob.

type GoogleCloudAiplatformV1PipelineJobResponseOutput 

type GoogleCloudAiplatformV1PipelineJobResponseOutput struct{ *pulumi.OutputState }

An instance of a machine learning PipelineJob.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) CreateTime 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) CreateTime() pulumi.StringOutput

Pipeline creation time.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) DisplayName 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) DisplayName() pulumi.StringOutput

The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) EncryptionSpec 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) EndTime 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) EndTime() pulumi.StringOutput

Pipeline end time.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) Error 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) Error() GoogleRpcStatusResponseOutput

The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) JobDetail 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) JobDetail() GoogleCloudAiplatformV1PipelineJobDetailResponseOutput

The details of pipeline run. Not available in the list view.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) Labels 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) Name 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) Name() pulumi.StringOutput

The resource name of the PipelineJob.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) Network 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) Network() pulumi.StringOutput

The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) PipelineSpec 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) PipelineSpec() pulumi.StringMapOutput

The spec of the pipeline.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) ReservedIpRanges 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) ReservedIpRanges() pulumi.StringArrayOutput

A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) RuntimeConfig 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) RuntimeConfig() GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput

Runtime config of the pipeline.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) ScheduleName 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) ScheduleName() pulumi.StringOutput

The schedule resource name. Only returned if the Pipeline is created by Schedule API.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) ServiceAccount 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) ServiceAccount() pulumi.StringOutput

The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) StartTime 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) StartTime() pulumi.StringOutput

Pipeline start time.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) State 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) State() pulumi.StringOutput

The detailed state of the job.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) TemplateMetadata 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) TemplateMetadata() GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput

Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) TemplateUri 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) TemplateUri() pulumi.StringOutput

A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) ToGoogleCloudAiplatformV1PipelineJobResponseOutput 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) ToGoogleCloudAiplatformV1PipelineJobResponseOutput() GoogleCloudAiplatformV1PipelineJobResponseOutput

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) ToGoogleCloudAiplatformV1PipelineJobResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) ToGoogleCloudAiplatformV1PipelineJobResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobResponseOutput

func (GoogleCloudAiplatformV1PipelineJobResponseOutput) UpdateTime 

func (o GoogleCloudAiplatformV1PipelineJobResponseOutput) UpdateTime() pulumi.StringOutput

Timestamp when this PipelineJob was most recently updated.

type GoogleCloudAiplatformV1PipelineJobRuntimeConfig 

type GoogleCloudAiplatformV1PipelineJobRuntimeConfig struct {
	// Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
	FailurePolicy *GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy `pulumi:"failurePolicy"`
	// A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
	GcsOutputDirectory string `pulumi:"gcsOutputDirectory"`
	// The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
	InputArtifacts map[string]string `pulumi:"inputArtifacts"`
	// The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
	ParameterValues map[string]string `pulumi:"parameterValues"`
	// Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
	//
	// Deprecated: Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
	Parameters map[string]string `pulumi:"parameters"`
}

The runtime config of a PipelineJob.

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs 

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs struct {
	// Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
	FailurePolicy GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrInput `pulumi:"failurePolicy"`
	// A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
	GcsOutputDirectory pulumi.StringInput `pulumi:"gcsOutputDirectory"`
	// The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
	InputArtifacts pulumi.StringMapInput `pulumi:"inputArtifacts"`
	// The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
	ParameterValues pulumi.StringMapInput `pulumi:"parameterValues"`
	// Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
	//
	// Deprecated: Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
	Parameters pulumi.StringMapInput `pulumi:"parameters"`
}

The runtime config of a PipelineJob.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs) ElementType 

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput 

func (i GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigOutputWithContext 

func (i GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput 

func (i GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy 

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy string

Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ElementType 

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput 

func (e GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutputWithContext 

func (e GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput 

func (e GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutputWithContext 

func (e GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToStringOutput 

func (e GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicy) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyInput 

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput
	ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutputWithContext(context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput
}

GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyInput is an input type that accepts GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyArgs and GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyInput` via: 

GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyArgs{...}

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput 

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrInput 

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput
	ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput
}

func GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtr 

func GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtr(v string) GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrInput

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput 

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput) Elem 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput) Elem() GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigInput 

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput
	ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput
}

GoogleCloudAiplatformV1PipelineJobRuntimeConfigInput is an input type that accepts GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs and GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PipelineJobRuntimeConfigInput` via: 

GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs{...}

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput 

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput struct{ *pulumi.OutputState }

The runtime config of a PipelineJob.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) FailurePolicy 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) FailurePolicy() GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput

Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) GcsOutputDirectory 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) GcsOutputDirectory() pulumi.StringOutput

A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) InputArtifacts 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) InputArtifacts() pulumi.StringMapOutput

The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) ParameterValues 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) ParameterValues() pulumi.StringMapOutput

The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) Parameters deprecated 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) Parameters() pulumi.StringMapOutput

Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.

Deprecated: Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrInput 

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput
	ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput
}

GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs, GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtr and GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrInput` via: 

        GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtr 

func GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtr(v *GoogleCloudAiplatformV1PipelineJobRuntimeConfigArgs) GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrInput

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput 

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) Elem() GoogleCloudAiplatformV1PipelineJobRuntimeConfigOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) FailurePolicy 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) FailurePolicy() GoogleCloudAiplatformV1PipelineJobRuntimeConfigFailurePolicyPtrOutput

Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) GcsOutputDirectory 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) GcsOutputDirectory() pulumi.StringPtrOutput

A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) InputArtifacts 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) InputArtifacts() pulumi.StringMapOutput

The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) ParameterValues 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) ParameterValues() pulumi.StringMapOutput

The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) Parameters deprecated 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) Parameters() pulumi.StringMapOutput

Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.

Deprecated: Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrOutput

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse 

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse struct {
	// Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
	FailurePolicy string `pulumi:"failurePolicy"`
	// A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
	GcsOutputDirectory string `pulumi:"gcsOutputDirectory"`
	// The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
	InputArtifacts map[string]string `pulumi:"inputArtifacts"`
	// The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.
	ParameterValues map[string]string `pulumi:"parameterValues"`
	// Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
	//
	// Deprecated: Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.
	Parameters map[string]string `pulumi:"parameters"`
}

The runtime config of a PipelineJob.

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput 

type GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput struct{ *pulumi.OutputState }

The runtime config of a PipelineJob.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) FailurePolicy 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) FailurePolicy() pulumi.StringOutput

Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) GcsOutputDirectory 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) GcsOutputDirectory() pulumi.StringOutput

A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) InputArtifacts 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) InputArtifacts() pulumi.StringMapOutput

The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) ParameterValues 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) ParameterValues() pulumi.StringMapOutput

The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) Parameters deprecated 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) Parameters() pulumi.StringMapOutput

Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.

Deprecated: Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower.

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput() GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput

func (GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput) ToGoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput

type GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponse 

type GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponse struct {
	// The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.
	Error GoogleRpcStatusResponse `pulumi:"error"`
	// The state of the task.
	State string `pulumi:"state"`
	// Update time of this status.
	UpdateTime string `pulumi:"updateTime"`
}

A single record of the task status.

type GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput 

type GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput

func (GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput 

func (o GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput() GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput

func (GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput

type GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput 

type GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput struct{ *pulumi.OutputState }

A single record of the task status.

func (GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput) Error 

func (o GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput) Error() GoogleRpcStatusResponseOutput

The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried.

func (GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput) State 

func (o GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput) State() pulumi.StringOutput

The state of the task.

func (GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput 

func (o GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput() GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput

func (GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput

func (GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput) UpdateTime 

func (o GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseOutput) UpdateTime() pulumi.StringOutput

Update time of this status.

type GoogleCloudAiplatformV1PipelineTaskDetailResponse 

type GoogleCloudAiplatformV1PipelineTaskDetailResponse struct {
	// Task create time.
	CreateTime string `pulumi:"createTime"`
	// Task end time.
	EndTime string `pulumi:"endTime"`
	// The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.
	Error GoogleRpcStatusResponse `pulumi:"error"`
	// The execution metadata of the task.
	Execution GoogleCloudAiplatformV1ExecutionResponse `pulumi:"execution"`
	// The detailed execution info.
	ExecutorDetail GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponse `pulumi:"executorDetail"`
	// The runtime input artifacts of the task.
	Inputs map[string]string `pulumi:"inputs"`
	// The runtime output artifacts of the task.
	Outputs map[string]string `pulumi:"outputs"`
	// The id of the parent task if the task is within a component scope. Empty if the task is at the root level.
	ParentTaskId string `pulumi:"parentTaskId"`
	// A list of task status. This field keeps a record of task status evolving over time.
	PipelineTaskStatus []GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponse `pulumi:"pipelineTaskStatus"`
	// Task start time.
	StartTime string `pulumi:"startTime"`
	// State of the task.
	State string `pulumi:"state"`
	// The system generated ID of the task.
	TaskId string `pulumi:"taskId"`
	// The user specified name of the task that is defined in pipeline_spec.
	TaskName string `pulumi:"taskName"`
}

The runtime detail of a task execution.

type GoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput 

type GoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput() GoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineTaskDetailResponseArrayOutput

type GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput 

type GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput struct{ *pulumi.OutputState }

The runtime detail of a task execution.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) CreateTime 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) CreateTime() pulumi.StringOutput

Task create time.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) EndTime 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) EndTime() pulumi.StringOutput

Task end time.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) Error 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) Error() GoogleRpcStatusResponseOutput

The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) Execution 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) Execution() GoogleCloudAiplatformV1ExecutionResponseOutput

The execution metadata of the task.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) ExecutorDetail 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) ExecutorDetail() GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput

The detailed execution info.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) Inputs 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) Inputs() pulumi.StringMapOutput

The runtime input artifacts of the task.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) Outputs 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) Outputs() pulumi.StringMapOutput

The runtime output artifacts of the task.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) ParentTaskId 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) ParentTaskId() pulumi.StringOutput

The id of the parent task if the task is within a component scope. Empty if the task is at the root level.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) PipelineTaskStatus 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) PipelineTaskStatus() GoogleCloudAiplatformV1PipelineTaskDetailPipelineTaskStatusResponseArrayOutput

A list of task status. This field keeps a record of task status evolving over time.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) StartTime 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) StartTime() pulumi.StringOutput

Task start time.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) State 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) State() pulumi.StringOutput

State of the task.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) TaskId 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) TaskId() pulumi.StringOutput

The system generated ID of the task.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) TaskName 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) TaskName() pulumi.StringOutput

The user specified name of the task that is defined in pipeline_spec.

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailResponseOutput 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailResponseOutput() GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput

func (GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskDetailResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineTaskDetailResponseOutput

type GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponse 

type GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponse struct {
	// The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.
	FailedMainJobs []string `pulumi:"failedMainJobs"`
	// The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.
	FailedPreCachingCheckJobs []string `pulumi:"failedPreCachingCheckJobs"`
	// The name of the CustomJob for the main container execution.
	MainJob string `pulumi:"mainJob"`
	// The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.
	PreCachingCheckJob string `pulumi:"preCachingCheckJob"`
}

The detail of a container execution. It contains the job names of the lifecycle of a container execution.

type GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput 

type GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput struct{ *pulumi.OutputState }

The detail of a container execution. It contains the job names of the lifecycle of a container execution.

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) FailedMainJobs 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) FailedMainJobs() pulumi.StringArrayOutput

The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order.

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) FailedPreCachingCheckJobs 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) FailedPreCachingCheckJobs() pulumi.StringArrayOutput

The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order.

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) MainJob 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) MainJob() pulumi.StringOutput

The name of the CustomJob for the main container execution.

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) PreCachingCheckJob 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) PreCachingCheckJob() pulumi.StringOutput

The name of the CustomJob for the pre-caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events.

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput() GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput

type GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponse 

type GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponse struct {
	// The names of the previously failed CustomJob. The list includes the all attempts in chronological order.
	FailedJobs []string `pulumi:"failedJobs"`
	// The name of the CustomJob.
	Job string `pulumi:"job"`
}

The detailed info for a custom job executor.

type GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput 

type GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput struct{ *pulumi.OutputState }

The detailed info for a custom job executor.

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput) FailedJobs 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput) FailedJobs() pulumi.StringArrayOutput

The names of the previously failed CustomJob. The list includes the all attempts in chronological order.

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput) Job 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput) Job() pulumi.StringOutput

The name of the CustomJob.

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput() GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput

type GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponse 

type GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponse struct {
	// The detailed info for a container executor.
	ContainerDetail GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponse `pulumi:"containerDetail"`
	// The detailed info for a custom job executor.
	CustomJobDetail GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponse `pulumi:"customJobDetail"`
}

The runtime detail of a pipeline executor.

type GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput 

type GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput struct{ *pulumi.OutputState }

The runtime detail of a pipeline executor.

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput) ContainerDetail 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput) ContainerDetail() GoogleCloudAiplatformV1PipelineTaskExecutorDetailContainerDetailResponseOutput

The detailed info for a container executor.

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput) CustomJobDetail 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput) CustomJobDetail() GoogleCloudAiplatformV1PipelineTaskExecutorDetailCustomJobDetailResponseOutput

The detailed info for a custom job executor.

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput() GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput

func (GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput) ToGoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineTaskExecutorDetailResponseOutput

type GoogleCloudAiplatformV1PipelineTemplateMetadataResponse 

type GoogleCloudAiplatformV1PipelineTemplateMetadataResponse struct {
	// The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is "sha256:abcdef123456...".
	Version string `pulumi:"version"`
}

Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry.

type GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput 

type GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput struct{ *pulumi.OutputState }

Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry.

func (GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput) ToGoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput 

func (o GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput) ToGoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput() GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput

func (GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput) ToGoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput) ToGoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput

func (GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput) Version 

func (o GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput) Version() pulumi.StringOutput

The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is "sha256:abcdef123456...".

type GoogleCloudAiplatformV1Port 

type GoogleCloudAiplatformV1Port struct {
	// The number of the port to expose on the pod's IP address. Must be a valid port number, between 1 and 65535 inclusive.
	ContainerPort *int `pulumi:"containerPort"`
}

Represents a network port in a container.

type GoogleCloudAiplatformV1PortArgs 

type GoogleCloudAiplatformV1PortArgs struct {
	// The number of the port to expose on the pod's IP address. Must be a valid port number, between 1 and 65535 inclusive.
	ContainerPort pulumi.IntPtrInput `pulumi:"containerPort"`
}

Represents a network port in a container.

func (GoogleCloudAiplatformV1PortArgs) ElementType 

func (GoogleCloudAiplatformV1PortArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PortArgs) ToGoogleCloudAiplatformV1PortOutput 

func (i GoogleCloudAiplatformV1PortArgs) ToGoogleCloudAiplatformV1PortOutput() GoogleCloudAiplatformV1PortOutput

func (GoogleCloudAiplatformV1PortArgs) ToGoogleCloudAiplatformV1PortOutputWithContext 

func (i GoogleCloudAiplatformV1PortArgs) ToGoogleCloudAiplatformV1PortOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PortOutput

type GoogleCloudAiplatformV1PortArray 

type GoogleCloudAiplatformV1PortArray []GoogleCloudAiplatformV1PortInput

func (GoogleCloudAiplatformV1PortArray) ElementType 

func (GoogleCloudAiplatformV1PortArray) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PortArray) ToGoogleCloudAiplatformV1PortArrayOutput 

func (i GoogleCloudAiplatformV1PortArray) ToGoogleCloudAiplatformV1PortArrayOutput() GoogleCloudAiplatformV1PortArrayOutput

func (GoogleCloudAiplatformV1PortArray) ToGoogleCloudAiplatformV1PortArrayOutputWithContext 

func (i GoogleCloudAiplatformV1PortArray) ToGoogleCloudAiplatformV1PortArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PortArrayOutput

type GoogleCloudAiplatformV1PortArrayInput 

type GoogleCloudAiplatformV1PortArrayInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PortArrayOutput() GoogleCloudAiplatformV1PortArrayOutput
	ToGoogleCloudAiplatformV1PortArrayOutputWithContext(context.Context) GoogleCloudAiplatformV1PortArrayOutput
}

GoogleCloudAiplatformV1PortArrayInput is an input type that accepts GoogleCloudAiplatformV1PortArray and GoogleCloudAiplatformV1PortArrayOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PortArrayInput` via: 

GoogleCloudAiplatformV1PortArray{ GoogleCloudAiplatformV1PortArgs{...} }

type GoogleCloudAiplatformV1PortArrayOutput 

type GoogleCloudAiplatformV1PortArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PortArrayOutput) ElementType 

func (GoogleCloudAiplatformV1PortArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PortArrayOutput) Index 

func (o GoogleCloudAiplatformV1PortArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1PortOutput

func (GoogleCloudAiplatformV1PortArrayOutput) ToGoogleCloudAiplatformV1PortArrayOutput 

func (o GoogleCloudAiplatformV1PortArrayOutput) ToGoogleCloudAiplatformV1PortArrayOutput() GoogleCloudAiplatformV1PortArrayOutput

func (GoogleCloudAiplatformV1PortArrayOutput) ToGoogleCloudAiplatformV1PortArrayOutputWithContext 

func (o GoogleCloudAiplatformV1PortArrayOutput) ToGoogleCloudAiplatformV1PortArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PortArrayOutput

type GoogleCloudAiplatformV1PortInput 

type GoogleCloudAiplatformV1PortInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PortOutput() GoogleCloudAiplatformV1PortOutput
	ToGoogleCloudAiplatformV1PortOutputWithContext(context.Context) GoogleCloudAiplatformV1PortOutput
}

GoogleCloudAiplatformV1PortInput is an input type that accepts GoogleCloudAiplatformV1PortArgs and GoogleCloudAiplatformV1PortOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PortInput` via: 

GoogleCloudAiplatformV1PortArgs{...}

type GoogleCloudAiplatformV1PortOutput 

type GoogleCloudAiplatformV1PortOutput struct{ *pulumi.OutputState }

Represents a network port in a container.

func (GoogleCloudAiplatformV1PortOutput) ContainerPort 

func (o GoogleCloudAiplatformV1PortOutput) ContainerPort() pulumi.IntPtrOutput

The number of the port to expose on the pod's IP address. Must be a valid port number, between 1 and 65535 inclusive.

func (GoogleCloudAiplatformV1PortOutput) ElementType 

func (GoogleCloudAiplatformV1PortOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PortOutput) ToGoogleCloudAiplatformV1PortOutput 

func (o GoogleCloudAiplatformV1PortOutput) ToGoogleCloudAiplatformV1PortOutput() GoogleCloudAiplatformV1PortOutput

func (GoogleCloudAiplatformV1PortOutput) ToGoogleCloudAiplatformV1PortOutputWithContext 

func (o GoogleCloudAiplatformV1PortOutput) ToGoogleCloudAiplatformV1PortOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PortOutput

type GoogleCloudAiplatformV1PortResponse 

type GoogleCloudAiplatformV1PortResponse struct {
	// The number of the port to expose on the pod's IP address. Must be a valid port number, between 1 and 65535 inclusive.
	ContainerPort int `pulumi:"containerPort"`
}

Represents a network port in a container.

type GoogleCloudAiplatformV1PortResponseArrayOutput 

type GoogleCloudAiplatformV1PortResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PortResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1PortResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PortResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1PortResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1PortResponseOutput

func (GoogleCloudAiplatformV1PortResponseArrayOutput) ToGoogleCloudAiplatformV1PortResponseArrayOutput 

func (o GoogleCloudAiplatformV1PortResponseArrayOutput) ToGoogleCloudAiplatformV1PortResponseArrayOutput() GoogleCloudAiplatformV1PortResponseArrayOutput

func (GoogleCloudAiplatformV1PortResponseArrayOutput) ToGoogleCloudAiplatformV1PortResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1PortResponseArrayOutput) ToGoogleCloudAiplatformV1PortResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PortResponseArrayOutput

type GoogleCloudAiplatformV1PortResponseOutput 

type GoogleCloudAiplatformV1PortResponseOutput struct{ *pulumi.OutputState }

Represents a network port in a container.

func (GoogleCloudAiplatformV1PortResponseOutput) ContainerPort 

func (o GoogleCloudAiplatformV1PortResponseOutput) ContainerPort() pulumi.IntOutput

The number of the port to expose on the pod's IP address. Must be a valid port number, between 1 and 65535 inclusive.

func (GoogleCloudAiplatformV1PortResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PortResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PortResponseOutput) ToGoogleCloudAiplatformV1PortResponseOutput 

func (o GoogleCloudAiplatformV1PortResponseOutput) ToGoogleCloudAiplatformV1PortResponseOutput() GoogleCloudAiplatformV1PortResponseOutput

func (GoogleCloudAiplatformV1PortResponseOutput) ToGoogleCloudAiplatformV1PortResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PortResponseOutput) ToGoogleCloudAiplatformV1PortResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PortResponseOutput

type GoogleCloudAiplatformV1PredefinedSplit 

type GoogleCloudAiplatformV1PredefinedSplit struct {
	// The key is a name of one of the Dataset's data columns. The value of the key (either the label's value or value in the column) must be one of {`training`, `validation`, `test`}, and it defines to which set the given piece of data is assigned. If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.
	Key string `pulumi:"key"`
}

Assigns input data to training, validation, and test sets based on the value of a provided key. Supported only for tabular Datasets.

type GoogleCloudAiplatformV1PredefinedSplitArgs 

type GoogleCloudAiplatformV1PredefinedSplitArgs struct {
	// The key is a name of one of the Dataset's data columns. The value of the key (either the label's value or value in the column) must be one of {`training`, `validation`, `test`}, and it defines to which set the given piece of data is assigned. If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.
	Key pulumi.StringInput `pulumi:"key"`
}

Assigns input data to training, validation, and test sets based on the value of a provided key. Supported only for tabular Datasets.

func (GoogleCloudAiplatformV1PredefinedSplitArgs) ElementType 

func (GoogleCloudAiplatformV1PredefinedSplitArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PredefinedSplitArgs) ToGoogleCloudAiplatformV1PredefinedSplitOutput 

func (i GoogleCloudAiplatformV1PredefinedSplitArgs) ToGoogleCloudAiplatformV1PredefinedSplitOutput() GoogleCloudAiplatformV1PredefinedSplitOutput

func (GoogleCloudAiplatformV1PredefinedSplitArgs) ToGoogleCloudAiplatformV1PredefinedSplitOutputWithContext 

func (i GoogleCloudAiplatformV1PredefinedSplitArgs) ToGoogleCloudAiplatformV1PredefinedSplitOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredefinedSplitOutput

func (GoogleCloudAiplatformV1PredefinedSplitArgs) ToGoogleCloudAiplatformV1PredefinedSplitPtrOutput 

func (i GoogleCloudAiplatformV1PredefinedSplitArgs) ToGoogleCloudAiplatformV1PredefinedSplitPtrOutput() GoogleCloudAiplatformV1PredefinedSplitPtrOutput

func (GoogleCloudAiplatformV1PredefinedSplitArgs) ToGoogleCloudAiplatformV1PredefinedSplitPtrOutputWithContext 

func (i GoogleCloudAiplatformV1PredefinedSplitArgs) ToGoogleCloudAiplatformV1PredefinedSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredefinedSplitPtrOutput

type GoogleCloudAiplatformV1PredefinedSplitInput 

type GoogleCloudAiplatformV1PredefinedSplitInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PredefinedSplitOutput() GoogleCloudAiplatformV1PredefinedSplitOutput
	ToGoogleCloudAiplatformV1PredefinedSplitOutputWithContext(context.Context) GoogleCloudAiplatformV1PredefinedSplitOutput
}

GoogleCloudAiplatformV1PredefinedSplitInput is an input type that accepts GoogleCloudAiplatformV1PredefinedSplitArgs and GoogleCloudAiplatformV1PredefinedSplitOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PredefinedSplitInput` via: 

GoogleCloudAiplatformV1PredefinedSplitArgs{...}

type GoogleCloudAiplatformV1PredefinedSplitOutput 

type GoogleCloudAiplatformV1PredefinedSplitOutput struct{ *pulumi.OutputState }

Assigns input data to training, validation, and test sets based on the value of a provided key. Supported only for tabular Datasets.

func (GoogleCloudAiplatformV1PredefinedSplitOutput) ElementType 

func (GoogleCloudAiplatformV1PredefinedSplitOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PredefinedSplitOutput) Key 

func (o GoogleCloudAiplatformV1PredefinedSplitOutput) Key() pulumi.StringOutput

The key is a name of one of the Dataset's data columns. The value of the key (either the label's value or value in the column) must be one of {`training`, `validation`, `test`}, and it defines to which set the given piece of data is assigned. If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.

func (GoogleCloudAiplatformV1PredefinedSplitOutput) ToGoogleCloudAiplatformV1PredefinedSplitOutput 

func (o GoogleCloudAiplatformV1PredefinedSplitOutput) ToGoogleCloudAiplatformV1PredefinedSplitOutput() GoogleCloudAiplatformV1PredefinedSplitOutput

func (GoogleCloudAiplatformV1PredefinedSplitOutput) ToGoogleCloudAiplatformV1PredefinedSplitOutputWithContext 

func (o GoogleCloudAiplatformV1PredefinedSplitOutput) ToGoogleCloudAiplatformV1PredefinedSplitOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredefinedSplitOutput

func (GoogleCloudAiplatformV1PredefinedSplitOutput) ToGoogleCloudAiplatformV1PredefinedSplitPtrOutput 

func (o GoogleCloudAiplatformV1PredefinedSplitOutput) ToGoogleCloudAiplatformV1PredefinedSplitPtrOutput() GoogleCloudAiplatformV1PredefinedSplitPtrOutput

func (GoogleCloudAiplatformV1PredefinedSplitOutput) ToGoogleCloudAiplatformV1PredefinedSplitPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PredefinedSplitOutput) ToGoogleCloudAiplatformV1PredefinedSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredefinedSplitPtrOutput

type GoogleCloudAiplatformV1PredefinedSplitPtrInput 

type GoogleCloudAiplatformV1PredefinedSplitPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PredefinedSplitPtrOutput() GoogleCloudAiplatformV1PredefinedSplitPtrOutput
	ToGoogleCloudAiplatformV1PredefinedSplitPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1PredefinedSplitPtrOutput
}

GoogleCloudAiplatformV1PredefinedSplitPtrInput is an input type that accepts GoogleCloudAiplatformV1PredefinedSplitArgs, GoogleCloudAiplatformV1PredefinedSplitPtr and GoogleCloudAiplatformV1PredefinedSplitPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PredefinedSplitPtrInput` via: 

        GoogleCloudAiplatformV1PredefinedSplitArgs{...}

or:

        nil

func GoogleCloudAiplatformV1PredefinedSplitPtr 

func GoogleCloudAiplatformV1PredefinedSplitPtr(v *GoogleCloudAiplatformV1PredefinedSplitArgs) GoogleCloudAiplatformV1PredefinedSplitPtrInput

type GoogleCloudAiplatformV1PredefinedSplitPtrOutput 

type GoogleCloudAiplatformV1PredefinedSplitPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PredefinedSplitPtrOutput) Elem 

func (o GoogleCloudAiplatformV1PredefinedSplitPtrOutput) Elem() GoogleCloudAiplatformV1PredefinedSplitOutput

func (GoogleCloudAiplatformV1PredefinedSplitPtrOutput) ElementType 

func (GoogleCloudAiplatformV1PredefinedSplitPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PredefinedSplitPtrOutput) Key 

func (o GoogleCloudAiplatformV1PredefinedSplitPtrOutput) Key() pulumi.StringPtrOutput

The key is a name of one of the Dataset's data columns. The value of the key (either the label's value or value in the column) must be one of {`training`, `validation`, `test`}, and it defines to which set the given piece of data is assigned. If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.

func (GoogleCloudAiplatformV1PredefinedSplitPtrOutput) ToGoogleCloudAiplatformV1PredefinedSplitPtrOutput 

func (o GoogleCloudAiplatformV1PredefinedSplitPtrOutput) ToGoogleCloudAiplatformV1PredefinedSplitPtrOutput() GoogleCloudAiplatformV1PredefinedSplitPtrOutput

func (GoogleCloudAiplatformV1PredefinedSplitPtrOutput) ToGoogleCloudAiplatformV1PredefinedSplitPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PredefinedSplitPtrOutput) ToGoogleCloudAiplatformV1PredefinedSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredefinedSplitPtrOutput

type GoogleCloudAiplatformV1PredefinedSplitResponse 

type GoogleCloudAiplatformV1PredefinedSplitResponse struct {
	// The key is a name of one of the Dataset's data columns. The value of the key (either the label's value or value in the column) must be one of {`training`, `validation`, `test`}, and it defines to which set the given piece of data is assigned. If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.
	Key string `pulumi:"key"`
}

Assigns input data to training, validation, and test sets based on the value of a provided key. Supported only for tabular Datasets.

type GoogleCloudAiplatformV1PredefinedSplitResponseOutput 

type GoogleCloudAiplatformV1PredefinedSplitResponseOutput struct{ *pulumi.OutputState }

Assigns input data to training, validation, and test sets based on the value of a provided key. Supported only for tabular Datasets.

func (GoogleCloudAiplatformV1PredefinedSplitResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PredefinedSplitResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PredefinedSplitResponseOutput) Key 

func (o GoogleCloudAiplatformV1PredefinedSplitResponseOutput) Key() pulumi.StringOutput

The key is a name of one of the Dataset's data columns. The value of the key (either the label's value or value in the column) must be one of {`training`, `validation`, `test`}, and it defines to which set the given piece of data is assigned. If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.

func (GoogleCloudAiplatformV1PredefinedSplitResponseOutput) ToGoogleCloudAiplatformV1PredefinedSplitResponseOutput 

func (o GoogleCloudAiplatformV1PredefinedSplitResponseOutput) ToGoogleCloudAiplatformV1PredefinedSplitResponseOutput() GoogleCloudAiplatformV1PredefinedSplitResponseOutput

func (GoogleCloudAiplatformV1PredefinedSplitResponseOutput) ToGoogleCloudAiplatformV1PredefinedSplitResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PredefinedSplitResponseOutput) ToGoogleCloudAiplatformV1PredefinedSplitResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredefinedSplitResponseOutput

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfig 

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfig struct {
	// BigQuery table for logging. If only given a project, a new dataset will be created with name `logging__` where will be made BigQuery-dataset-name compatible (e.g. most special characters will become underscores). If no table name is given, a new table will be created with name `request_response_logging`
	BigqueryDestination *GoogleCloudAiplatformV1BigQueryDestination `pulumi:"bigqueryDestination"`
	// If logging is enabled or not.
	Enabled *bool `pulumi:"enabled"`
	// Percentage of requests to be logged, expressed as a fraction in range(0,1].
	SamplingRate *float64 `pulumi:"samplingRate"`
}

Configuration for logging request-response to a BigQuery table.

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs 

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs struct {
	// BigQuery table for logging. If only given a project, a new dataset will be created with name `logging__` where will be made BigQuery-dataset-name compatible (e.g. most special characters will become underscores). If no table name is given, a new table will be created with name `request_response_logging`
	BigqueryDestination GoogleCloudAiplatformV1BigQueryDestinationPtrInput `pulumi:"bigqueryDestination"`
	// If logging is enabled or not.
	Enabled pulumi.BoolPtrInput `pulumi:"enabled"`
	// Percentage of requests to be logged, expressed as a fraction in range(0,1].
	SamplingRate pulumi.Float64PtrInput `pulumi:"samplingRate"`
}

Configuration for logging request-response to a BigQuery table.

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs) ElementType 

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput 

func (i GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput() GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutputWithContext 

func (i GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput 

func (i GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput() GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigInput 

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput() GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput
	ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput
}

GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigInput is an input type that accepts GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs and GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigInput` via: 

GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs{...}

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput 

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput struct{ *pulumi.OutputState }

Configuration for logging request-response to a BigQuery table.

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) BigqueryDestination 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) BigqueryDestination() GoogleCloudAiplatformV1BigQueryDestinationPtrOutput

BigQuery table for logging. If only given a project, a new dataset will be created with name `logging__` where will be made BigQuery-dataset-name compatible (e.g. most special characters will become underscores). If no table name is given, a new table will be created with name `request_response_logging`

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) ElementType 

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) Enabled 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) Enabled() pulumi.BoolPtrOutput

If logging is enabled or not.

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) SamplingRate 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) SamplingRate() pulumi.Float64PtrOutput

Percentage of requests to be logged, expressed as a fraction in range(0,1].

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput() GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutputWithContext 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput() GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrInput 

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput() GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput
	ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput
}

GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs, GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtr and GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrInput` via: 

        GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtr 

func GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtr(v *GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigArgs) GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrInput

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput 

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) BigqueryDestination 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) BigqueryDestination() GoogleCloudAiplatformV1BigQueryDestinationPtrOutput

BigQuery table for logging. If only given a project, a new dataset will be created with name `logging__` where will be made BigQuery-dataset-name compatible (e.g. most special characters will become underscores). If no table name is given, a new table will be created with name `request_response_logging`

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) Elem() GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigOutput

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) Enabled 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) Enabled() pulumi.BoolPtrOutput

If logging is enabled or not.

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) SamplingRate 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) SamplingRate() pulumi.Float64PtrOutput

Percentage of requests to be logged, expressed as a fraction in range(0,1].

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput() GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigPtrOutput

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponse 

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponse struct {
	// BigQuery table for logging. If only given a project, a new dataset will be created with name `logging__` where will be made BigQuery-dataset-name compatible (e.g. most special characters will become underscores). If no table name is given, a new table will be created with name `request_response_logging`
	BigqueryDestination GoogleCloudAiplatformV1BigQueryDestinationResponse `pulumi:"bigqueryDestination"`
	// If logging is enabled or not.
	Enabled bool `pulumi:"enabled"`
	// Percentage of requests to be logged, expressed as a fraction in range(0,1].
	SamplingRate float64 `pulumi:"samplingRate"`
}

Configuration for logging request-response to a BigQuery table.

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput 

type GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput struct{ *pulumi.OutputState }

Configuration for logging request-response to a BigQuery table.

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput) BigqueryDestination 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput) BigqueryDestination() GoogleCloudAiplatformV1BigQueryDestinationResponseOutput

BigQuery table for logging. If only given a project, a new dataset will be created with name `logging__` where will be made BigQuery-dataset-name compatible (e.g. most special characters will become underscores). If no table name is given, a new table will be created with name `request_response_logging`

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput) Enabled 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput) Enabled() pulumi.BoolOutput

If logging is enabled or not.

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput) SamplingRate 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput) SamplingRate() pulumi.Float64Output

Percentage of requests to be logged, expressed as a fraction in range(0,1].

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput() GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput

func (GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput) ToGoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput

type GoogleCloudAiplatformV1PredictSchemata 

type GoogleCloudAiplatformV1PredictSchemata struct {
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single instance, which are used in PredictRequest.instances, ExplainRequest.instances and BatchPredictionJob.input_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	InstanceSchemaUri *string `pulumi:"instanceSchemaUri"`
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing the parameters of prediction and explanation via PredictRequest.parameters, ExplainRequest.parameters and BatchPredictionJob.model_parameters. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no parameters are supported, then it is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	ParametersSchemaUri *string `pulumi:"parametersSchemaUri"`
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single prediction produced by this Model, which are returned via PredictResponse.predictions, ExplainResponse.explanations, and BatchPredictionJob.output_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	PredictionSchemaUri *string `pulumi:"predictionSchemaUri"`
}

Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob.

type GoogleCloudAiplatformV1PredictSchemataArgs 

type GoogleCloudAiplatformV1PredictSchemataArgs struct {
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single instance, which are used in PredictRequest.instances, ExplainRequest.instances and BatchPredictionJob.input_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	InstanceSchemaUri pulumi.StringPtrInput `pulumi:"instanceSchemaUri"`
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing the parameters of prediction and explanation via PredictRequest.parameters, ExplainRequest.parameters and BatchPredictionJob.model_parameters. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no parameters are supported, then it is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	ParametersSchemaUri pulumi.StringPtrInput `pulumi:"parametersSchemaUri"`
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single prediction produced by this Model, which are returned via PredictResponse.predictions, ExplainResponse.explanations, and BatchPredictionJob.output_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	PredictionSchemaUri pulumi.StringPtrInput `pulumi:"predictionSchemaUri"`
}

Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob.

func (GoogleCloudAiplatformV1PredictSchemataArgs) ElementType 

func (GoogleCloudAiplatformV1PredictSchemataArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PredictSchemataArgs) ToGoogleCloudAiplatformV1PredictSchemataOutput 

func (i GoogleCloudAiplatformV1PredictSchemataArgs) ToGoogleCloudAiplatformV1PredictSchemataOutput() GoogleCloudAiplatformV1PredictSchemataOutput

func (GoogleCloudAiplatformV1PredictSchemataArgs) ToGoogleCloudAiplatformV1PredictSchemataOutputWithContext 

func (i GoogleCloudAiplatformV1PredictSchemataArgs) ToGoogleCloudAiplatformV1PredictSchemataOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredictSchemataOutput

func (GoogleCloudAiplatformV1PredictSchemataArgs) ToGoogleCloudAiplatformV1PredictSchemataPtrOutput 

func (i GoogleCloudAiplatformV1PredictSchemataArgs) ToGoogleCloudAiplatformV1PredictSchemataPtrOutput() GoogleCloudAiplatformV1PredictSchemataPtrOutput

func (GoogleCloudAiplatformV1PredictSchemataArgs) ToGoogleCloudAiplatformV1PredictSchemataPtrOutputWithContext 

func (i GoogleCloudAiplatformV1PredictSchemataArgs) ToGoogleCloudAiplatformV1PredictSchemataPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredictSchemataPtrOutput

type GoogleCloudAiplatformV1PredictSchemataInput 

type GoogleCloudAiplatformV1PredictSchemataInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PredictSchemataOutput() GoogleCloudAiplatformV1PredictSchemataOutput
	ToGoogleCloudAiplatformV1PredictSchemataOutputWithContext(context.Context) GoogleCloudAiplatformV1PredictSchemataOutput
}

GoogleCloudAiplatformV1PredictSchemataInput is an input type that accepts GoogleCloudAiplatformV1PredictSchemataArgs and GoogleCloudAiplatformV1PredictSchemataOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PredictSchemataInput` via: 

GoogleCloudAiplatformV1PredictSchemataArgs{...}

type GoogleCloudAiplatformV1PredictSchemataOutput 

type GoogleCloudAiplatformV1PredictSchemataOutput struct{ *pulumi.OutputState }

Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob.

func (GoogleCloudAiplatformV1PredictSchemataOutput) ElementType 

func (GoogleCloudAiplatformV1PredictSchemataOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PredictSchemataOutput) InstanceSchemaUri 

func (o GoogleCloudAiplatformV1PredictSchemataOutput) InstanceSchemaUri() pulumi.StringPtrOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single instance, which are used in PredictRequest.instances, ExplainRequest.instances and BatchPredictionJob.input_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1PredictSchemataOutput) ParametersSchemaUri 

func (o GoogleCloudAiplatformV1PredictSchemataOutput) ParametersSchemaUri() pulumi.StringPtrOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing the parameters of prediction and explanation via PredictRequest.parameters, ExplainRequest.parameters and BatchPredictionJob.model_parameters. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no parameters are supported, then it is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1PredictSchemataOutput) PredictionSchemaUri 

func (o GoogleCloudAiplatformV1PredictSchemataOutput) PredictionSchemaUri() pulumi.StringPtrOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single prediction produced by this Model, which are returned via PredictResponse.predictions, ExplainResponse.explanations, and BatchPredictionJob.output_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1PredictSchemataOutput) ToGoogleCloudAiplatformV1PredictSchemataOutput 

func (o GoogleCloudAiplatformV1PredictSchemataOutput) ToGoogleCloudAiplatformV1PredictSchemataOutput() GoogleCloudAiplatformV1PredictSchemataOutput

func (GoogleCloudAiplatformV1PredictSchemataOutput) ToGoogleCloudAiplatformV1PredictSchemataOutputWithContext 

func (o GoogleCloudAiplatformV1PredictSchemataOutput) ToGoogleCloudAiplatformV1PredictSchemataOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredictSchemataOutput

func (GoogleCloudAiplatformV1PredictSchemataOutput) ToGoogleCloudAiplatformV1PredictSchemataPtrOutput 

func (o GoogleCloudAiplatformV1PredictSchemataOutput) ToGoogleCloudAiplatformV1PredictSchemataPtrOutput() GoogleCloudAiplatformV1PredictSchemataPtrOutput

func (GoogleCloudAiplatformV1PredictSchemataOutput) ToGoogleCloudAiplatformV1PredictSchemataPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PredictSchemataOutput) ToGoogleCloudAiplatformV1PredictSchemataPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredictSchemataPtrOutput

type GoogleCloudAiplatformV1PredictSchemataPtrInput 

type GoogleCloudAiplatformV1PredictSchemataPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PredictSchemataPtrOutput() GoogleCloudAiplatformV1PredictSchemataPtrOutput
	ToGoogleCloudAiplatformV1PredictSchemataPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1PredictSchemataPtrOutput
}

GoogleCloudAiplatformV1PredictSchemataPtrInput is an input type that accepts GoogleCloudAiplatformV1PredictSchemataArgs, GoogleCloudAiplatformV1PredictSchemataPtr and GoogleCloudAiplatformV1PredictSchemataPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PredictSchemataPtrInput` via: 

        GoogleCloudAiplatformV1PredictSchemataArgs{...}

or:

        nil

func GoogleCloudAiplatformV1PredictSchemataPtr 

func GoogleCloudAiplatformV1PredictSchemataPtr(v *GoogleCloudAiplatformV1PredictSchemataArgs) GoogleCloudAiplatformV1PredictSchemataPtrInput

type GoogleCloudAiplatformV1PredictSchemataPtrOutput 

type GoogleCloudAiplatformV1PredictSchemataPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PredictSchemataPtrOutput) Elem 

func (o GoogleCloudAiplatformV1PredictSchemataPtrOutput) Elem() GoogleCloudAiplatformV1PredictSchemataOutput

func (GoogleCloudAiplatformV1PredictSchemataPtrOutput) ElementType 

func (GoogleCloudAiplatformV1PredictSchemataPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PredictSchemataPtrOutput) InstanceSchemaUri 

func (o GoogleCloudAiplatformV1PredictSchemataPtrOutput) InstanceSchemaUri() pulumi.StringPtrOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single instance, which are used in PredictRequest.instances, ExplainRequest.instances and BatchPredictionJob.input_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1PredictSchemataPtrOutput) ParametersSchemaUri 

func (o GoogleCloudAiplatformV1PredictSchemataPtrOutput) ParametersSchemaUri() pulumi.StringPtrOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing the parameters of prediction and explanation via PredictRequest.parameters, ExplainRequest.parameters and BatchPredictionJob.model_parameters. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no parameters are supported, then it is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1PredictSchemataPtrOutput) PredictionSchemaUri 

func (o GoogleCloudAiplatformV1PredictSchemataPtrOutput) PredictionSchemaUri() pulumi.StringPtrOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single prediction produced by this Model, which are returned via PredictResponse.predictions, ExplainResponse.explanations, and BatchPredictionJob.output_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1PredictSchemataPtrOutput) ToGoogleCloudAiplatformV1PredictSchemataPtrOutput 

func (o GoogleCloudAiplatformV1PredictSchemataPtrOutput) ToGoogleCloudAiplatformV1PredictSchemataPtrOutput() GoogleCloudAiplatformV1PredictSchemataPtrOutput

func (GoogleCloudAiplatformV1PredictSchemataPtrOutput) ToGoogleCloudAiplatformV1PredictSchemataPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PredictSchemataPtrOutput) ToGoogleCloudAiplatformV1PredictSchemataPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredictSchemataPtrOutput

type GoogleCloudAiplatformV1PredictSchemataResponse 

type GoogleCloudAiplatformV1PredictSchemataResponse struct {
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single instance, which are used in PredictRequest.instances, ExplainRequest.instances and BatchPredictionJob.input_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	InstanceSchemaUri string `pulumi:"instanceSchemaUri"`
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing the parameters of prediction and explanation via PredictRequest.parameters, ExplainRequest.parameters and BatchPredictionJob.model_parameters. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no parameters are supported, then it is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	ParametersSchemaUri string `pulumi:"parametersSchemaUri"`
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single prediction produced by this Model, which are returned via PredictResponse.predictions, ExplainResponse.explanations, and BatchPredictionJob.output_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	PredictionSchemaUri string `pulumi:"predictionSchemaUri"`
}

Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob.

type GoogleCloudAiplatformV1PredictSchemataResponseOutput 

type GoogleCloudAiplatformV1PredictSchemataResponseOutput struct{ *pulumi.OutputState }

Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob.

func (GoogleCloudAiplatformV1PredictSchemataResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PredictSchemataResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PredictSchemataResponseOutput) InstanceSchemaUri 

func (o GoogleCloudAiplatformV1PredictSchemataResponseOutput) InstanceSchemaUri() pulumi.StringOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single instance, which are used in PredictRequest.instances, ExplainRequest.instances and BatchPredictionJob.input_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1PredictSchemataResponseOutput) ParametersSchemaUri 

func (o GoogleCloudAiplatformV1PredictSchemataResponseOutput) ParametersSchemaUri() pulumi.StringOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing the parameters of prediction and explanation via PredictRequest.parameters, ExplainRequest.parameters and BatchPredictionJob.model_parameters. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no parameters are supported, then it is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1PredictSchemataResponseOutput) PredictionSchemaUri 

func (o GoogleCloudAiplatformV1PredictSchemataResponseOutput) PredictionSchemaUri() pulumi.StringOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single prediction produced by this Model, which are returned via PredictResponse.predictions, ExplainResponse.explanations, and BatchPredictionJob.output_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (GoogleCloudAiplatformV1PredictSchemataResponseOutput) ToGoogleCloudAiplatformV1PredictSchemataResponseOutput 

func (o GoogleCloudAiplatformV1PredictSchemataResponseOutput) ToGoogleCloudAiplatformV1PredictSchemataResponseOutput() GoogleCloudAiplatformV1PredictSchemataResponseOutput

func (GoogleCloudAiplatformV1PredictSchemataResponseOutput) ToGoogleCloudAiplatformV1PredictSchemataResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PredictSchemataResponseOutput) ToGoogleCloudAiplatformV1PredictSchemataResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PredictSchemataResponseOutput

type GoogleCloudAiplatformV1Presets 

type GoogleCloudAiplatformV1Presets struct {
	// The modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. If your model does not precisely fit one of these types, it is okay to choose the closest type.
	Modality *GoogleCloudAiplatformV1PresetsModality `pulumi:"modality"`
	// Preset option controlling parameters for speed-precision trade-off when querying for examples. If omitted, defaults to `PRECISE`.
	Query *GoogleCloudAiplatformV1PresetsQuery `pulumi:"query"`
}

Preset configuration for example-based explanations

type GoogleCloudAiplatformV1PresetsArgs 

type GoogleCloudAiplatformV1PresetsArgs struct {
	// The modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. If your model does not precisely fit one of these types, it is okay to choose the closest type.
	Modality GoogleCloudAiplatformV1PresetsModalityPtrInput `pulumi:"modality"`
	// Preset option controlling parameters for speed-precision trade-off when querying for examples. If omitted, defaults to `PRECISE`.
	Query GoogleCloudAiplatformV1PresetsQueryPtrInput `pulumi:"query"`
}

Preset configuration for example-based explanations

func (GoogleCloudAiplatformV1PresetsArgs) ElementType 

func (GoogleCloudAiplatformV1PresetsArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PresetsArgs) ToGoogleCloudAiplatformV1PresetsOutput 

func (i GoogleCloudAiplatformV1PresetsArgs) ToGoogleCloudAiplatformV1PresetsOutput() GoogleCloudAiplatformV1PresetsOutput

func (GoogleCloudAiplatformV1PresetsArgs) ToGoogleCloudAiplatformV1PresetsOutputWithContext 

func (i GoogleCloudAiplatformV1PresetsArgs) ToGoogleCloudAiplatformV1PresetsOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsOutput

func (GoogleCloudAiplatformV1PresetsArgs) ToGoogleCloudAiplatformV1PresetsPtrOutput 

func (i GoogleCloudAiplatformV1PresetsArgs) ToGoogleCloudAiplatformV1PresetsPtrOutput() GoogleCloudAiplatformV1PresetsPtrOutput

func (GoogleCloudAiplatformV1PresetsArgs) ToGoogleCloudAiplatformV1PresetsPtrOutputWithContext 

func (i GoogleCloudAiplatformV1PresetsArgs) ToGoogleCloudAiplatformV1PresetsPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsPtrOutput

type GoogleCloudAiplatformV1PresetsInput 

type GoogleCloudAiplatformV1PresetsInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PresetsOutput() GoogleCloudAiplatformV1PresetsOutput
	ToGoogleCloudAiplatformV1PresetsOutputWithContext(context.Context) GoogleCloudAiplatformV1PresetsOutput
}

GoogleCloudAiplatformV1PresetsInput is an input type that accepts GoogleCloudAiplatformV1PresetsArgs and GoogleCloudAiplatformV1PresetsOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PresetsInput` via: 

GoogleCloudAiplatformV1PresetsArgs{...}

type GoogleCloudAiplatformV1PresetsModality 

type GoogleCloudAiplatformV1PresetsModality string

The modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. If your model does not precisely fit one of these types, it is okay to choose the closest type.

func (GoogleCloudAiplatformV1PresetsModality) ElementType 

func (GoogleCloudAiplatformV1PresetsModality) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PresetsModality) ToGoogleCloudAiplatformV1PresetsModalityOutput 

func (e GoogleCloudAiplatformV1PresetsModality) ToGoogleCloudAiplatformV1PresetsModalityOutput() GoogleCloudAiplatformV1PresetsModalityOutput

func (GoogleCloudAiplatformV1PresetsModality) ToGoogleCloudAiplatformV1PresetsModalityOutputWithContext 

func (e GoogleCloudAiplatformV1PresetsModality) ToGoogleCloudAiplatformV1PresetsModalityOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsModalityOutput

func (GoogleCloudAiplatformV1PresetsModality) ToGoogleCloudAiplatformV1PresetsModalityPtrOutput 

func (e GoogleCloudAiplatformV1PresetsModality) ToGoogleCloudAiplatformV1PresetsModalityPtrOutput() GoogleCloudAiplatformV1PresetsModalityPtrOutput

func (GoogleCloudAiplatformV1PresetsModality) ToGoogleCloudAiplatformV1PresetsModalityPtrOutputWithContext 

func (e GoogleCloudAiplatformV1PresetsModality) ToGoogleCloudAiplatformV1PresetsModalityPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsModalityPtrOutput

func (GoogleCloudAiplatformV1PresetsModality) ToStringOutput 

func (e GoogleCloudAiplatformV1PresetsModality) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1PresetsModality) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1PresetsModality) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1PresetsModality) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1PresetsModality) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1PresetsModality) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1PresetsModality) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1PresetsModalityInput 

type GoogleCloudAiplatformV1PresetsModalityInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PresetsModalityOutput() GoogleCloudAiplatformV1PresetsModalityOutput
	ToGoogleCloudAiplatformV1PresetsModalityOutputWithContext(context.Context) GoogleCloudAiplatformV1PresetsModalityOutput
}

GoogleCloudAiplatformV1PresetsModalityInput is an input type that accepts GoogleCloudAiplatformV1PresetsModalityArgs and GoogleCloudAiplatformV1PresetsModalityOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PresetsModalityInput` via: 

GoogleCloudAiplatformV1PresetsModalityArgs{...}

type GoogleCloudAiplatformV1PresetsModalityOutput 

type GoogleCloudAiplatformV1PresetsModalityOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PresetsModalityOutput) ElementType 

func (GoogleCloudAiplatformV1PresetsModalityOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PresetsModalityOutput) ToGoogleCloudAiplatformV1PresetsModalityOutput 

func (o GoogleCloudAiplatformV1PresetsModalityOutput) ToGoogleCloudAiplatformV1PresetsModalityOutput() GoogleCloudAiplatformV1PresetsModalityOutput

func (GoogleCloudAiplatformV1PresetsModalityOutput) ToGoogleCloudAiplatformV1PresetsModalityOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsModalityOutput) ToGoogleCloudAiplatformV1PresetsModalityOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsModalityOutput

func (GoogleCloudAiplatformV1PresetsModalityOutput) ToGoogleCloudAiplatformV1PresetsModalityPtrOutput 

func (o GoogleCloudAiplatformV1PresetsModalityOutput) ToGoogleCloudAiplatformV1PresetsModalityPtrOutput() GoogleCloudAiplatformV1PresetsModalityPtrOutput

func (GoogleCloudAiplatformV1PresetsModalityOutput) ToGoogleCloudAiplatformV1PresetsModalityPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsModalityOutput) ToGoogleCloudAiplatformV1PresetsModalityPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsModalityPtrOutput

func (GoogleCloudAiplatformV1PresetsModalityOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1PresetsModalityOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1PresetsModalityOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsModalityOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1PresetsModalityOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1PresetsModalityOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1PresetsModalityOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsModalityOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1PresetsModalityPtrInput 

type GoogleCloudAiplatformV1PresetsModalityPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PresetsModalityPtrOutput() GoogleCloudAiplatformV1PresetsModalityPtrOutput
	ToGoogleCloudAiplatformV1PresetsModalityPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1PresetsModalityPtrOutput
}

func GoogleCloudAiplatformV1PresetsModalityPtr 

func GoogleCloudAiplatformV1PresetsModalityPtr(v string) GoogleCloudAiplatformV1PresetsModalityPtrInput

type GoogleCloudAiplatformV1PresetsModalityPtrOutput 

type GoogleCloudAiplatformV1PresetsModalityPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PresetsModalityPtrOutput) Elem 

func (o GoogleCloudAiplatformV1PresetsModalityPtrOutput) Elem() GoogleCloudAiplatformV1PresetsModalityOutput

func (GoogleCloudAiplatformV1PresetsModalityPtrOutput) ElementType 

func (GoogleCloudAiplatformV1PresetsModalityPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PresetsModalityPtrOutput) ToGoogleCloudAiplatformV1PresetsModalityPtrOutput 

func (o GoogleCloudAiplatformV1PresetsModalityPtrOutput) ToGoogleCloudAiplatformV1PresetsModalityPtrOutput() GoogleCloudAiplatformV1PresetsModalityPtrOutput

func (GoogleCloudAiplatformV1PresetsModalityPtrOutput) ToGoogleCloudAiplatformV1PresetsModalityPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsModalityPtrOutput) ToGoogleCloudAiplatformV1PresetsModalityPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsModalityPtrOutput

func (GoogleCloudAiplatformV1PresetsModalityPtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1PresetsModalityPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1PresetsModalityPtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsModalityPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1PresetsOutput 

type GoogleCloudAiplatformV1PresetsOutput struct{ *pulumi.OutputState }

Preset configuration for example-based explanations

func (GoogleCloudAiplatformV1PresetsOutput) ElementType 

func (GoogleCloudAiplatformV1PresetsOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PresetsOutput) Modality 

func (o GoogleCloudAiplatformV1PresetsOutput) Modality() GoogleCloudAiplatformV1PresetsModalityPtrOutput

The modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. If your model does not precisely fit one of these types, it is okay to choose the closest type.

func (GoogleCloudAiplatformV1PresetsOutput) Query 

func (o GoogleCloudAiplatformV1PresetsOutput) Query() GoogleCloudAiplatformV1PresetsQueryPtrOutput

Preset option controlling parameters for speed-precision trade-off when querying for examples. If omitted, defaults to `PRECISE`.

func (GoogleCloudAiplatformV1PresetsOutput) ToGoogleCloudAiplatformV1PresetsOutput 

func (o GoogleCloudAiplatformV1PresetsOutput) ToGoogleCloudAiplatformV1PresetsOutput() GoogleCloudAiplatformV1PresetsOutput

func (GoogleCloudAiplatformV1PresetsOutput) ToGoogleCloudAiplatformV1PresetsOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsOutput) ToGoogleCloudAiplatformV1PresetsOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsOutput

func (GoogleCloudAiplatformV1PresetsOutput) ToGoogleCloudAiplatformV1PresetsPtrOutput 

func (o GoogleCloudAiplatformV1PresetsOutput) ToGoogleCloudAiplatformV1PresetsPtrOutput() GoogleCloudAiplatformV1PresetsPtrOutput

func (GoogleCloudAiplatformV1PresetsOutput) ToGoogleCloudAiplatformV1PresetsPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsOutput) ToGoogleCloudAiplatformV1PresetsPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsPtrOutput

type GoogleCloudAiplatformV1PresetsPtrInput 

type GoogleCloudAiplatformV1PresetsPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PresetsPtrOutput() GoogleCloudAiplatformV1PresetsPtrOutput
	ToGoogleCloudAiplatformV1PresetsPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1PresetsPtrOutput
}

GoogleCloudAiplatformV1PresetsPtrInput is an input type that accepts GoogleCloudAiplatformV1PresetsArgs, GoogleCloudAiplatformV1PresetsPtr and GoogleCloudAiplatformV1PresetsPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PresetsPtrInput` via: 

        GoogleCloudAiplatformV1PresetsArgs{...}

or:

        nil

func GoogleCloudAiplatformV1PresetsPtr 

func GoogleCloudAiplatformV1PresetsPtr(v *GoogleCloudAiplatformV1PresetsArgs) GoogleCloudAiplatformV1PresetsPtrInput

type GoogleCloudAiplatformV1PresetsPtrOutput 

type GoogleCloudAiplatformV1PresetsPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PresetsPtrOutput) Elem 

func (o GoogleCloudAiplatformV1PresetsPtrOutput) Elem() GoogleCloudAiplatformV1PresetsOutput

func (GoogleCloudAiplatformV1PresetsPtrOutput) ElementType 

func (GoogleCloudAiplatformV1PresetsPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PresetsPtrOutput) Modality 

func (o GoogleCloudAiplatformV1PresetsPtrOutput) Modality() GoogleCloudAiplatformV1PresetsModalityPtrOutput

The modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. If your model does not precisely fit one of these types, it is okay to choose the closest type.

func (GoogleCloudAiplatformV1PresetsPtrOutput) Query 

func (o GoogleCloudAiplatformV1PresetsPtrOutput) Query() GoogleCloudAiplatformV1PresetsQueryPtrOutput

Preset option controlling parameters for speed-precision trade-off when querying for examples. If omitted, defaults to `PRECISE`.

func (GoogleCloudAiplatformV1PresetsPtrOutput) ToGoogleCloudAiplatformV1PresetsPtrOutput 

func (o GoogleCloudAiplatformV1PresetsPtrOutput) ToGoogleCloudAiplatformV1PresetsPtrOutput() GoogleCloudAiplatformV1PresetsPtrOutput

func (GoogleCloudAiplatformV1PresetsPtrOutput) ToGoogleCloudAiplatformV1PresetsPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsPtrOutput) ToGoogleCloudAiplatformV1PresetsPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsPtrOutput

type GoogleCloudAiplatformV1PresetsQuery 

type GoogleCloudAiplatformV1PresetsQuery string

Preset option controlling parameters for speed-precision trade-off when querying for examples. If omitted, defaults to `PRECISE`.

func (GoogleCloudAiplatformV1PresetsQuery) ElementType 

func (GoogleCloudAiplatformV1PresetsQuery) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PresetsQuery) ToGoogleCloudAiplatformV1PresetsQueryOutput 

func (e GoogleCloudAiplatformV1PresetsQuery) ToGoogleCloudAiplatformV1PresetsQueryOutput() GoogleCloudAiplatformV1PresetsQueryOutput

func (GoogleCloudAiplatformV1PresetsQuery) ToGoogleCloudAiplatformV1PresetsQueryOutputWithContext 

func (e GoogleCloudAiplatformV1PresetsQuery) ToGoogleCloudAiplatformV1PresetsQueryOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsQueryOutput

func (GoogleCloudAiplatformV1PresetsQuery) ToGoogleCloudAiplatformV1PresetsQueryPtrOutput 

func (e GoogleCloudAiplatformV1PresetsQuery) ToGoogleCloudAiplatformV1PresetsQueryPtrOutput() GoogleCloudAiplatformV1PresetsQueryPtrOutput

func (GoogleCloudAiplatformV1PresetsQuery) ToGoogleCloudAiplatformV1PresetsQueryPtrOutputWithContext 

func (e GoogleCloudAiplatformV1PresetsQuery) ToGoogleCloudAiplatformV1PresetsQueryPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsQueryPtrOutput

func (GoogleCloudAiplatformV1PresetsQuery) ToStringOutput 

func (e GoogleCloudAiplatformV1PresetsQuery) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1PresetsQuery) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1PresetsQuery) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1PresetsQuery) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1PresetsQuery) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1PresetsQuery) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1PresetsQuery) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1PresetsQueryInput 

type GoogleCloudAiplatformV1PresetsQueryInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PresetsQueryOutput() GoogleCloudAiplatformV1PresetsQueryOutput
	ToGoogleCloudAiplatformV1PresetsQueryOutputWithContext(context.Context) GoogleCloudAiplatformV1PresetsQueryOutput
}

GoogleCloudAiplatformV1PresetsQueryInput is an input type that accepts GoogleCloudAiplatformV1PresetsQueryArgs and GoogleCloudAiplatformV1PresetsQueryOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PresetsQueryInput` via: 

GoogleCloudAiplatformV1PresetsQueryArgs{...}

type GoogleCloudAiplatformV1PresetsQueryOutput 

type GoogleCloudAiplatformV1PresetsQueryOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PresetsQueryOutput) ElementType 

func (GoogleCloudAiplatformV1PresetsQueryOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PresetsQueryOutput) ToGoogleCloudAiplatformV1PresetsQueryOutput 

func (o GoogleCloudAiplatformV1PresetsQueryOutput) ToGoogleCloudAiplatformV1PresetsQueryOutput() GoogleCloudAiplatformV1PresetsQueryOutput

func (GoogleCloudAiplatformV1PresetsQueryOutput) ToGoogleCloudAiplatformV1PresetsQueryOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsQueryOutput) ToGoogleCloudAiplatformV1PresetsQueryOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsQueryOutput

func (GoogleCloudAiplatformV1PresetsQueryOutput) ToGoogleCloudAiplatformV1PresetsQueryPtrOutput 

func (o GoogleCloudAiplatformV1PresetsQueryOutput) ToGoogleCloudAiplatformV1PresetsQueryPtrOutput() GoogleCloudAiplatformV1PresetsQueryPtrOutput

func (GoogleCloudAiplatformV1PresetsQueryOutput) ToGoogleCloudAiplatformV1PresetsQueryPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsQueryOutput) ToGoogleCloudAiplatformV1PresetsQueryPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsQueryPtrOutput

func (GoogleCloudAiplatformV1PresetsQueryOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1PresetsQueryOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1PresetsQueryOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsQueryOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1PresetsQueryOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1PresetsQueryOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1PresetsQueryOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsQueryOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1PresetsQueryPtrInput 

type GoogleCloudAiplatformV1PresetsQueryPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PresetsQueryPtrOutput() GoogleCloudAiplatformV1PresetsQueryPtrOutput
	ToGoogleCloudAiplatformV1PresetsQueryPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1PresetsQueryPtrOutput
}

func GoogleCloudAiplatformV1PresetsQueryPtr 

func GoogleCloudAiplatformV1PresetsQueryPtr(v string) GoogleCloudAiplatformV1PresetsQueryPtrInput

type GoogleCloudAiplatformV1PresetsQueryPtrOutput 

type GoogleCloudAiplatformV1PresetsQueryPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PresetsQueryPtrOutput) Elem 

func (o GoogleCloudAiplatformV1PresetsQueryPtrOutput) Elem() GoogleCloudAiplatformV1PresetsQueryOutput

func (GoogleCloudAiplatformV1PresetsQueryPtrOutput) ElementType 

func (GoogleCloudAiplatformV1PresetsQueryPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PresetsQueryPtrOutput) ToGoogleCloudAiplatformV1PresetsQueryPtrOutput 

func (o GoogleCloudAiplatformV1PresetsQueryPtrOutput) ToGoogleCloudAiplatformV1PresetsQueryPtrOutput() GoogleCloudAiplatformV1PresetsQueryPtrOutput

func (GoogleCloudAiplatformV1PresetsQueryPtrOutput) ToGoogleCloudAiplatformV1PresetsQueryPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsQueryPtrOutput) ToGoogleCloudAiplatformV1PresetsQueryPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsQueryPtrOutput

func (GoogleCloudAiplatformV1PresetsQueryPtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1PresetsQueryPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1PresetsQueryPtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsQueryPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1PresetsResponse 

type GoogleCloudAiplatformV1PresetsResponse struct {
	// The modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. If your model does not precisely fit one of these types, it is okay to choose the closest type.
	Modality string `pulumi:"modality"`
	// Preset option controlling parameters for speed-precision trade-off when querying for examples. If omitted, defaults to `PRECISE`.
	Query string `pulumi:"query"`
}

Preset configuration for example-based explanations

type GoogleCloudAiplatformV1PresetsResponseOutput 

type GoogleCloudAiplatformV1PresetsResponseOutput struct{ *pulumi.OutputState }

Preset configuration for example-based explanations

func (GoogleCloudAiplatformV1PresetsResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PresetsResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PresetsResponseOutput) Modality 

func (o GoogleCloudAiplatformV1PresetsResponseOutput) Modality() pulumi.StringOutput

The modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. If your model does not precisely fit one of these types, it is okay to choose the closest type.

func (GoogleCloudAiplatformV1PresetsResponseOutput) Query 

func (o GoogleCloudAiplatformV1PresetsResponseOutput) Query() pulumi.StringOutput

Preset option controlling parameters for speed-precision trade-off when querying for examples. If omitted, defaults to `PRECISE`.

func (GoogleCloudAiplatformV1PresetsResponseOutput) ToGoogleCloudAiplatformV1PresetsResponseOutput 

func (o GoogleCloudAiplatformV1PresetsResponseOutput) ToGoogleCloudAiplatformV1PresetsResponseOutput() GoogleCloudAiplatformV1PresetsResponseOutput

func (GoogleCloudAiplatformV1PresetsResponseOutput) ToGoogleCloudAiplatformV1PresetsResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PresetsResponseOutput) ToGoogleCloudAiplatformV1PresetsResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PresetsResponseOutput

type GoogleCloudAiplatformV1PrivateEndpointsResponse 

type GoogleCloudAiplatformV1PrivateEndpointsResponse struct {
	// Http(s) path to send explain requests.
	ExplainHttpUri string `pulumi:"explainHttpUri"`
	// Http(s) path to send health check requests.
	HealthHttpUri string `pulumi:"healthHttpUri"`
	// Http(s) path to send prediction requests.
	PredictHttpUri string `pulumi:"predictHttpUri"`
	// The name of the service attachment resource. Populated if private service connect is enabled.
	ServiceAttachment string `pulumi:"serviceAttachment"`
}

PrivateEndpoints proto is used to provide paths for users to send requests privately. To send request via private service access, use predict_http_uri, explain_http_uri or health_http_uri. To send request via private service connect, use service_attachment.

type GoogleCloudAiplatformV1PrivateEndpointsResponseOutput 

type GoogleCloudAiplatformV1PrivateEndpointsResponseOutput struct{ *pulumi.OutputState }

PrivateEndpoints proto is used to provide paths for users to send requests privately. To send request via private service access, use predict_http_uri, explain_http_uri or health_http_uri. To send request via private service connect, use service_attachment.

func (GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) ExplainHttpUri 

func (o GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) ExplainHttpUri() pulumi.StringOutput

Http(s) path to send explain requests.

func (GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) HealthHttpUri 

func (o GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) HealthHttpUri() pulumi.StringOutput

Http(s) path to send health check requests.

func (GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) PredictHttpUri 

func (o GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) PredictHttpUri() pulumi.StringOutput

Http(s) path to send prediction requests.

func (GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) ServiceAttachment 

func (o GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) ServiceAttachment() pulumi.StringOutput

The name of the service attachment resource. Populated if private service connect is enabled.

func (GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) ToGoogleCloudAiplatformV1PrivateEndpointsResponseOutput 

func (o GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) ToGoogleCloudAiplatformV1PrivateEndpointsResponseOutput() GoogleCloudAiplatformV1PrivateEndpointsResponseOutput

func (GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) ToGoogleCloudAiplatformV1PrivateEndpointsResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PrivateEndpointsResponseOutput) ToGoogleCloudAiplatformV1PrivateEndpointsResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PrivateEndpointsResponseOutput

type GoogleCloudAiplatformV1PrivateServiceConnectConfig 

type GoogleCloudAiplatformV1PrivateServiceConnectConfig struct {
	// If true, expose the IndexEndpoint via private service connect.
	EnablePrivateServiceConnect bool `pulumi:"enablePrivateServiceConnect"`
	// A list of Projects from which the forwarding rule will target the service attachment.
	ProjectAllowlist []string `pulumi:"projectAllowlist"`
}

Represents configuration for private service connect.

type GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs 

type GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs struct {
	// If true, expose the IndexEndpoint via private service connect.
	EnablePrivateServiceConnect pulumi.BoolInput `pulumi:"enablePrivateServiceConnect"`
	// A list of Projects from which the forwarding rule will target the service attachment.
	ProjectAllowlist pulumi.StringArrayInput `pulumi:"projectAllowlist"`
}

Represents configuration for private service connect.

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs) ElementType 

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigOutput 

func (i GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigOutput() GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigOutputWithContext 

func (i GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput 

func (i GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput() GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput

type GoogleCloudAiplatformV1PrivateServiceConnectConfigInput 

type GoogleCloudAiplatformV1PrivateServiceConnectConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PrivateServiceConnectConfigOutput() GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput
	ToGoogleCloudAiplatformV1PrivateServiceConnectConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput
}

GoogleCloudAiplatformV1PrivateServiceConnectConfigInput is an input type that accepts GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs and GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PrivateServiceConnectConfigInput` via: 

GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs{...}

type GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput 

type GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput struct{ *pulumi.OutputState }

Represents configuration for private service connect.

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) ElementType 

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) EnablePrivateServiceConnect 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) EnablePrivateServiceConnect() pulumi.BoolOutput

If true, expose the IndexEndpoint via private service connect.

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) ProjectAllowlist 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) ProjectAllowlist() pulumi.StringArrayOutput

A list of Projects from which the forwarding rule will target the service attachment.

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigOutput 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigOutput() GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigOutputWithContext 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput() GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput

type GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrInput 

type GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput() GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput
	ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput
}

GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs, GoogleCloudAiplatformV1PrivateServiceConnectConfigPtr and GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrInput` via: 

        GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1PrivateServiceConnectConfigPtr 

func GoogleCloudAiplatformV1PrivateServiceConnectConfigPtr(v *GoogleCloudAiplatformV1PrivateServiceConnectConfigArgs) GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrInput

type GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput 

type GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput) Elem() GoogleCloudAiplatformV1PrivateServiceConnectConfigOutput

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput) EnablePrivateServiceConnect 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput) EnablePrivateServiceConnect() pulumi.BoolPtrOutput

If true, expose the IndexEndpoint via private service connect.

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput) ProjectAllowlist 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput) ProjectAllowlist() pulumi.StringArrayOutput

A list of Projects from which the forwarding rule will target the service attachment.

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput() GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrOutput

type GoogleCloudAiplatformV1PrivateServiceConnectConfigResponse 

type GoogleCloudAiplatformV1PrivateServiceConnectConfigResponse struct {
	// If true, expose the IndexEndpoint via private service connect.
	EnablePrivateServiceConnect bool `pulumi:"enablePrivateServiceConnect"`
	// A list of Projects from which the forwarding rule will target the service attachment.
	ProjectAllowlist []string `pulumi:"projectAllowlist"`
}

Represents configuration for private service connect.

type GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput 

type GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput struct{ *pulumi.OutputState }

Represents configuration for private service connect.

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput) EnablePrivateServiceConnect 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput) EnablePrivateServiceConnect() pulumi.BoolOutput

If true, expose the IndexEndpoint via private service connect.

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput) ProjectAllowlist 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput) ProjectAllowlist() pulumi.StringArrayOutput

A list of Projects from which the forwarding rule will target the service attachment.

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput() GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput

func (GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput) ToGoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput

type GoogleCloudAiplatformV1Probe 

type GoogleCloudAiplatformV1Probe struct {
	// Exec specifies the action to take.
	Exec *GoogleCloudAiplatformV1ProbeExecAction `pulumi:"exec"`
	// How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. Must be less than timeout_seconds. Maps to Kubernetes probe argument 'periodSeconds'.
	PeriodSeconds *int `pulumi:"periodSeconds"`
	// Number of seconds after which the probe times out. Defaults to 1 second. Minimum value is 1. Must be greater or equal to period_seconds. Maps to Kubernetes probe argument 'timeoutSeconds'.
	TimeoutSeconds *int `pulumi:"timeoutSeconds"`
}

Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.

type GoogleCloudAiplatformV1ProbeArgs 

type GoogleCloudAiplatformV1ProbeArgs struct {
	// Exec specifies the action to take.
	Exec GoogleCloudAiplatformV1ProbeExecActionPtrInput `pulumi:"exec"`
	// How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. Must be less than timeout_seconds. Maps to Kubernetes probe argument 'periodSeconds'.
	PeriodSeconds pulumi.IntPtrInput `pulumi:"periodSeconds"`
	// Number of seconds after which the probe times out. Defaults to 1 second. Minimum value is 1. Must be greater or equal to period_seconds. Maps to Kubernetes probe argument 'timeoutSeconds'.
	TimeoutSeconds pulumi.IntPtrInput `pulumi:"timeoutSeconds"`
}

Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.

func (GoogleCloudAiplatformV1ProbeArgs) ElementType 

func (GoogleCloudAiplatformV1ProbeArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ProbeArgs) ToGoogleCloudAiplatformV1ProbeOutput 

func (i GoogleCloudAiplatformV1ProbeArgs) ToGoogleCloudAiplatformV1ProbeOutput() GoogleCloudAiplatformV1ProbeOutput

func (GoogleCloudAiplatformV1ProbeArgs) ToGoogleCloudAiplatformV1ProbeOutputWithContext 

func (i GoogleCloudAiplatformV1ProbeArgs) ToGoogleCloudAiplatformV1ProbeOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ProbeOutput

func (GoogleCloudAiplatformV1ProbeArgs) ToGoogleCloudAiplatformV1ProbePtrOutput 

func (i GoogleCloudAiplatformV1ProbeArgs) ToGoogleCloudAiplatformV1ProbePtrOutput() GoogleCloudAiplatformV1ProbePtrOutput

func (GoogleCloudAiplatformV1ProbeArgs) ToGoogleCloudAiplatformV1ProbePtrOutputWithContext 

func (i GoogleCloudAiplatformV1ProbeArgs) ToGoogleCloudAiplatformV1ProbePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ProbePtrOutput

type GoogleCloudAiplatformV1ProbeExecAction 

type GoogleCloudAiplatformV1ProbeExecAction struct {
	// Command is the command line to execute inside the container, the working directory for the command is root ('/') in the container's filesystem. The command is simply exec'd, it is not run inside a shell, so traditional shell instructions ('|', etc) won't work. To use a shell, you need to explicitly call out to that shell. Exit status of 0 is treated as live/healthy and non-zero is unhealthy.
	Command []string `pulumi:"command"`
}

ExecAction specifies a command to execute.

type GoogleCloudAiplatformV1ProbeExecActionArgs 

type GoogleCloudAiplatformV1ProbeExecActionArgs struct {
	// Command is the command line to execute inside the container, the working directory for the command is root ('/') in the container's filesystem. The command is simply exec'd, it is not run inside a shell, so traditional shell instructions ('|', etc) won't work. To use a shell, you need to explicitly call out to that shell. Exit status of 0 is treated as live/healthy and non-zero is unhealthy.
	Command pulumi.StringArrayInput `pulumi:"command"`
}

ExecAction specifies a command to execute.

func (GoogleCloudAiplatformV1ProbeExecActionArgs) ElementType 

func (GoogleCloudAiplatformV1ProbeExecActionArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ProbeExecActionArgs) ToGoogleCloudAiplatformV1ProbeExecActionOutput 

func (i GoogleCloudAiplatformV1ProbeExecActionArgs) ToGoogleCloudAiplatformV1ProbeExecActionOutput() GoogleCloudAiplatformV1ProbeExecActionOutput

func (GoogleCloudAiplatformV1ProbeExecActionArgs) ToGoogleCloudAiplatformV1ProbeExecActionOutputWithContext 

func (i GoogleCloudAiplatformV1ProbeExecActionArgs) ToGoogleCloudAiplatformV1ProbeExecActionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ProbeExecActionOutput

func (GoogleCloudAiplatformV1ProbeExecActionArgs) ToGoogleCloudAiplatformV1ProbeExecActionPtrOutput 

func (i GoogleCloudAiplatformV1ProbeExecActionArgs) ToGoogleCloudAiplatformV1ProbeExecActionPtrOutput() GoogleCloudAiplatformV1ProbeExecActionPtrOutput

func (GoogleCloudAiplatformV1ProbeExecActionArgs) ToGoogleCloudAiplatformV1ProbeExecActionPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ProbeExecActionArgs) ToGoogleCloudAiplatformV1ProbeExecActionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ProbeExecActionPtrOutput

type GoogleCloudAiplatformV1ProbeExecActionInput 

type GoogleCloudAiplatformV1ProbeExecActionInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ProbeExecActionOutput() GoogleCloudAiplatformV1ProbeExecActionOutput
	ToGoogleCloudAiplatformV1ProbeExecActionOutputWithContext(context.Context) GoogleCloudAiplatformV1ProbeExecActionOutput
}

GoogleCloudAiplatformV1ProbeExecActionInput is an input type that accepts GoogleCloudAiplatformV1ProbeExecActionArgs and GoogleCloudAiplatformV1ProbeExecActionOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ProbeExecActionInput` via: 

GoogleCloudAiplatformV1ProbeExecActionArgs{...}

type GoogleCloudAiplatformV1ProbeExecActionOutput 

type GoogleCloudAiplatformV1ProbeExecActionOutput struct{ *pulumi.OutputState }

ExecAction specifies a command to execute.

func (GoogleCloudAiplatformV1ProbeExecActionOutput) Command 

func (o GoogleCloudAiplatformV1ProbeExecActionOutput) Command() pulumi.StringArrayOutput

Command is the command line to execute inside the container, the working directory for the command is root ('/') in the container's filesystem. The command is simply exec'd, it is not run inside a shell, so traditional shell instructions ('|', etc) won't work. To use a shell, you need to explicitly call out to that shell. Exit status of 0 is treated as live/healthy and non-zero is unhealthy.

func (GoogleCloudAiplatformV1ProbeExecActionOutput) ElementType 

func (GoogleCloudAiplatformV1ProbeExecActionOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ProbeExecActionOutput) ToGoogleCloudAiplatformV1ProbeExecActionOutput 

func (o GoogleCloudAiplatformV1ProbeExecActionOutput) ToGoogleCloudAiplatformV1ProbeExecActionOutput() GoogleCloudAiplatformV1ProbeExecActionOutput

func (GoogleCloudAiplatformV1ProbeExecActionOutput) ToGoogleCloudAiplatformV1ProbeExecActionOutputWithContext 

func (o GoogleCloudAiplatformV1ProbeExecActionOutput) ToGoogleCloudAiplatformV1ProbeExecActionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ProbeExecActionOutput

func (GoogleCloudAiplatformV1ProbeExecActionOutput) ToGoogleCloudAiplatformV1ProbeExecActionPtrOutput 

func (o GoogleCloudAiplatformV1ProbeExecActionOutput) ToGoogleCloudAiplatformV1ProbeExecActionPtrOutput() GoogleCloudAiplatformV1ProbeExecActionPtrOutput

func (GoogleCloudAiplatformV1ProbeExecActionOutput) ToGoogleCloudAiplatformV1ProbeExecActionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ProbeExecActionOutput) ToGoogleCloudAiplatformV1ProbeExecActionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ProbeExecActionPtrOutput

type GoogleCloudAiplatformV1ProbeExecActionPtrInput 

type GoogleCloudAiplatformV1ProbeExecActionPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ProbeExecActionPtrOutput() GoogleCloudAiplatformV1ProbeExecActionPtrOutput
	ToGoogleCloudAiplatformV1ProbeExecActionPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ProbeExecActionPtrOutput
}

GoogleCloudAiplatformV1ProbeExecActionPtrInput is an input type that accepts GoogleCloudAiplatformV1ProbeExecActionArgs, GoogleCloudAiplatformV1ProbeExecActionPtr and GoogleCloudAiplatformV1ProbeExecActionPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ProbeExecActionPtrInput` via: 

        GoogleCloudAiplatformV1ProbeExecActionArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ProbeExecActionPtr 

func GoogleCloudAiplatformV1ProbeExecActionPtr(v *GoogleCloudAiplatformV1ProbeExecActionArgs) GoogleCloudAiplatformV1ProbeExecActionPtrInput

type GoogleCloudAiplatformV1ProbeExecActionPtrOutput 

type GoogleCloudAiplatformV1ProbeExecActionPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ProbeExecActionPtrOutput) Command 

func (o GoogleCloudAiplatformV1ProbeExecActionPtrOutput) Command() pulumi.StringArrayOutput

Command is the command line to execute inside the container, the working directory for the command is root ('/') in the container's filesystem. The command is simply exec'd, it is not run inside a shell, so traditional shell instructions ('|', etc) won't work. To use a shell, you need to explicitly call out to that shell. Exit status of 0 is treated as live/healthy and non-zero is unhealthy.

func (GoogleCloudAiplatformV1ProbeExecActionPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ProbeExecActionPtrOutput) Elem() GoogleCloudAiplatformV1ProbeExecActionOutput

func (GoogleCloudAiplatformV1ProbeExecActionPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ProbeExecActionPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ProbeExecActionPtrOutput) ToGoogleCloudAiplatformV1ProbeExecActionPtrOutput 

func (o GoogleCloudAiplatformV1ProbeExecActionPtrOutput) ToGoogleCloudAiplatformV1ProbeExecActionPtrOutput() GoogleCloudAiplatformV1ProbeExecActionPtrOutput

func (GoogleCloudAiplatformV1ProbeExecActionPtrOutput) ToGoogleCloudAiplatformV1ProbeExecActionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ProbeExecActionPtrOutput) ToGoogleCloudAiplatformV1ProbeExecActionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ProbeExecActionPtrOutput

type GoogleCloudAiplatformV1ProbeExecActionResponse 

type GoogleCloudAiplatformV1ProbeExecActionResponse struct {
	// Command is the command line to execute inside the container, the working directory for the command is root ('/') in the container's filesystem. The command is simply exec'd, it is not run inside a shell, so traditional shell instructions ('|', etc) won't work. To use a shell, you need to explicitly call out to that shell. Exit status of 0 is treated as live/healthy and non-zero is unhealthy.
	Command []string `pulumi:"command"`
}

ExecAction specifies a command to execute.

type GoogleCloudAiplatformV1ProbeExecActionResponseOutput 

type GoogleCloudAiplatformV1ProbeExecActionResponseOutput struct{ *pulumi.OutputState }

ExecAction specifies a command to execute.

func (GoogleCloudAiplatformV1ProbeExecActionResponseOutput) Command 

func (o GoogleCloudAiplatformV1ProbeExecActionResponseOutput) Command() pulumi.StringArrayOutput

Command is the command line to execute inside the container, the working directory for the command is root ('/') in the container's filesystem. The command is simply exec'd, it is not run inside a shell, so traditional shell instructions ('|', etc) won't work. To use a shell, you need to explicitly call out to that shell. Exit status of 0 is treated as live/healthy and non-zero is unhealthy.

func (GoogleCloudAiplatformV1ProbeExecActionResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ProbeExecActionResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ProbeExecActionResponseOutput) ToGoogleCloudAiplatformV1ProbeExecActionResponseOutput 

func (o GoogleCloudAiplatformV1ProbeExecActionResponseOutput) ToGoogleCloudAiplatformV1ProbeExecActionResponseOutput() GoogleCloudAiplatformV1ProbeExecActionResponseOutput

func (GoogleCloudAiplatformV1ProbeExecActionResponseOutput) ToGoogleCloudAiplatformV1ProbeExecActionResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ProbeExecActionResponseOutput) ToGoogleCloudAiplatformV1ProbeExecActionResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ProbeExecActionResponseOutput

type GoogleCloudAiplatformV1ProbeInput 

type GoogleCloudAiplatformV1ProbeInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ProbeOutput() GoogleCloudAiplatformV1ProbeOutput
	ToGoogleCloudAiplatformV1ProbeOutputWithContext(context.Context) GoogleCloudAiplatformV1ProbeOutput
}

GoogleCloudAiplatformV1ProbeInput is an input type that accepts GoogleCloudAiplatformV1ProbeArgs and GoogleCloudAiplatformV1ProbeOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ProbeInput` via: 

GoogleCloudAiplatformV1ProbeArgs{...}

type GoogleCloudAiplatformV1ProbeOutput 

type GoogleCloudAiplatformV1ProbeOutput struct{ *pulumi.OutputState }

Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.

func (GoogleCloudAiplatformV1ProbeOutput) ElementType 

func (GoogleCloudAiplatformV1ProbeOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ProbeOutput) Exec 

func (o GoogleCloudAiplatformV1ProbeOutput) Exec() GoogleCloudAiplatformV1ProbeExecActionPtrOutput

Exec specifies the action to take.

func (GoogleCloudAiplatformV1ProbeOutput) PeriodSeconds 

func (o GoogleCloudAiplatformV1ProbeOutput) PeriodSeconds() pulumi.IntPtrOutput

How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. Must be less than timeout_seconds. Maps to Kubernetes probe argument 'periodSeconds'.

func (GoogleCloudAiplatformV1ProbeOutput) TimeoutSeconds 

func (o GoogleCloudAiplatformV1ProbeOutput) TimeoutSeconds() pulumi.IntPtrOutput

Number of seconds after which the probe times out. Defaults to 1 second. Minimum value is 1. Must be greater or equal to period_seconds. Maps to Kubernetes probe argument 'timeoutSeconds'.

func (GoogleCloudAiplatformV1ProbeOutput) ToGoogleCloudAiplatformV1ProbeOutput 

func (o GoogleCloudAiplatformV1ProbeOutput) ToGoogleCloudAiplatformV1ProbeOutput() GoogleCloudAiplatformV1ProbeOutput

func (GoogleCloudAiplatformV1ProbeOutput) ToGoogleCloudAiplatformV1ProbeOutputWithContext 

func (o GoogleCloudAiplatformV1ProbeOutput) ToGoogleCloudAiplatformV1ProbeOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ProbeOutput

func (GoogleCloudAiplatformV1ProbeOutput) ToGoogleCloudAiplatformV1ProbePtrOutput 

func (o GoogleCloudAiplatformV1ProbeOutput) ToGoogleCloudAiplatformV1ProbePtrOutput() GoogleCloudAiplatformV1ProbePtrOutput

func (GoogleCloudAiplatformV1ProbeOutput) ToGoogleCloudAiplatformV1ProbePtrOutputWithContext 

func (o GoogleCloudAiplatformV1ProbeOutput) ToGoogleCloudAiplatformV1ProbePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ProbePtrOutput

type GoogleCloudAiplatformV1ProbePtrInput 

type GoogleCloudAiplatformV1ProbePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ProbePtrOutput() GoogleCloudAiplatformV1ProbePtrOutput
	ToGoogleCloudAiplatformV1ProbePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ProbePtrOutput
}

GoogleCloudAiplatformV1ProbePtrInput is an input type that accepts GoogleCloudAiplatformV1ProbeArgs, GoogleCloudAiplatformV1ProbePtr and GoogleCloudAiplatformV1ProbePtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ProbePtrInput` via: 

        GoogleCloudAiplatformV1ProbeArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ProbePtr 

func GoogleCloudAiplatformV1ProbePtr(v *GoogleCloudAiplatformV1ProbeArgs) GoogleCloudAiplatformV1ProbePtrInput

type GoogleCloudAiplatformV1ProbePtrOutput 

type GoogleCloudAiplatformV1ProbePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ProbePtrOutput) Elem 

func (o GoogleCloudAiplatformV1ProbePtrOutput) Elem() GoogleCloudAiplatformV1ProbeOutput

func (GoogleCloudAiplatformV1ProbePtrOutput) ElementType 

func (GoogleCloudAiplatformV1ProbePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ProbePtrOutput) Exec 

func (o GoogleCloudAiplatformV1ProbePtrOutput) Exec() GoogleCloudAiplatformV1ProbeExecActionPtrOutput

Exec specifies the action to take.

func (GoogleCloudAiplatformV1ProbePtrOutput) PeriodSeconds 

func (o GoogleCloudAiplatformV1ProbePtrOutput) PeriodSeconds() pulumi.IntPtrOutput

How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. Must be less than timeout_seconds. Maps to Kubernetes probe argument 'periodSeconds'.

func (GoogleCloudAiplatformV1ProbePtrOutput) TimeoutSeconds 

func (o GoogleCloudAiplatformV1ProbePtrOutput) TimeoutSeconds() pulumi.IntPtrOutput

Number of seconds after which the probe times out. Defaults to 1 second. Minimum value is 1. Must be greater or equal to period_seconds. Maps to Kubernetes probe argument 'timeoutSeconds'.

func (GoogleCloudAiplatformV1ProbePtrOutput) ToGoogleCloudAiplatformV1ProbePtrOutput 

func (o GoogleCloudAiplatformV1ProbePtrOutput) ToGoogleCloudAiplatformV1ProbePtrOutput() GoogleCloudAiplatformV1ProbePtrOutput

func (GoogleCloudAiplatformV1ProbePtrOutput) ToGoogleCloudAiplatformV1ProbePtrOutputWithContext 

func (o GoogleCloudAiplatformV1ProbePtrOutput) ToGoogleCloudAiplatformV1ProbePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ProbePtrOutput

type GoogleCloudAiplatformV1ProbeResponse 

type GoogleCloudAiplatformV1ProbeResponse struct {
	// Exec specifies the action to take.
	Exec GoogleCloudAiplatformV1ProbeExecActionResponse `pulumi:"exec"`
	// How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. Must be less than timeout_seconds. Maps to Kubernetes probe argument 'periodSeconds'.
	PeriodSeconds int `pulumi:"periodSeconds"`
	// Number of seconds after which the probe times out. Defaults to 1 second. Minimum value is 1. Must be greater or equal to period_seconds. Maps to Kubernetes probe argument 'timeoutSeconds'.
	TimeoutSeconds int `pulumi:"timeoutSeconds"`
}

Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.

type GoogleCloudAiplatformV1ProbeResponseOutput 

type GoogleCloudAiplatformV1ProbeResponseOutput struct{ *pulumi.OutputState }

Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.

func (GoogleCloudAiplatformV1ProbeResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ProbeResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ProbeResponseOutput) Exec 

func (o GoogleCloudAiplatformV1ProbeResponseOutput) Exec() GoogleCloudAiplatformV1ProbeExecActionResponseOutput

Exec specifies the action to take.

func (GoogleCloudAiplatformV1ProbeResponseOutput) PeriodSeconds 

func (o GoogleCloudAiplatformV1ProbeResponseOutput) PeriodSeconds() pulumi.IntOutput

How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. Must be less than timeout_seconds. Maps to Kubernetes probe argument 'periodSeconds'.

func (GoogleCloudAiplatformV1ProbeResponseOutput) TimeoutSeconds 

func (o GoogleCloudAiplatformV1ProbeResponseOutput) TimeoutSeconds() pulumi.IntOutput

Number of seconds after which the probe times out. Defaults to 1 second. Minimum value is 1. Must be greater or equal to period_seconds. Maps to Kubernetes probe argument 'timeoutSeconds'.

func (GoogleCloudAiplatformV1ProbeResponseOutput) ToGoogleCloudAiplatformV1ProbeResponseOutput 

func (o GoogleCloudAiplatformV1ProbeResponseOutput) ToGoogleCloudAiplatformV1ProbeResponseOutput() GoogleCloudAiplatformV1ProbeResponseOutput

func (GoogleCloudAiplatformV1ProbeResponseOutput) ToGoogleCloudAiplatformV1ProbeResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ProbeResponseOutput) ToGoogleCloudAiplatformV1ProbeResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ProbeResponseOutput

type GoogleCloudAiplatformV1PythonPackageSpec 

type GoogleCloudAiplatformV1PythonPackageSpec struct {
	// Command line arguments to be passed to the Python task.
	Args []string `pulumi:"args"`
	// Environment variables to be passed to the python module. Maximum limit is 100.
	Env []GoogleCloudAiplatformV1EnvVar `pulumi:"env"`
	// The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of [pre-built containers for training](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). You must use an image from this list.
	ExecutorImageUri string `pulumi:"executorImageUri"`
	// The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
	PackageUris []string `pulumi:"packageUris"`
	// The Python module name to run after installing the packages.
	PythonModule string `pulumi:"pythonModule"`
}

The spec of a Python packaged code.

type GoogleCloudAiplatformV1PythonPackageSpecArgs 

type GoogleCloudAiplatformV1PythonPackageSpecArgs struct {
	// Command line arguments to be passed to the Python task.
	Args pulumi.StringArrayInput `pulumi:"args"`
	// Environment variables to be passed to the python module. Maximum limit is 100.
	Env GoogleCloudAiplatformV1EnvVarArrayInput `pulumi:"env"`
	// The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of [pre-built containers for training](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). You must use an image from this list.
	ExecutorImageUri pulumi.StringInput `pulumi:"executorImageUri"`
	// The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
	PackageUris pulumi.StringArrayInput `pulumi:"packageUris"`
	// The Python module name to run after installing the packages.
	PythonModule pulumi.StringInput `pulumi:"pythonModule"`
}

The spec of a Python packaged code.

func (GoogleCloudAiplatformV1PythonPackageSpecArgs) ElementType 

func (GoogleCloudAiplatformV1PythonPackageSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PythonPackageSpecArgs) ToGoogleCloudAiplatformV1PythonPackageSpecOutput 

func (i GoogleCloudAiplatformV1PythonPackageSpecArgs) ToGoogleCloudAiplatformV1PythonPackageSpecOutput() GoogleCloudAiplatformV1PythonPackageSpecOutput

func (GoogleCloudAiplatformV1PythonPackageSpecArgs) ToGoogleCloudAiplatformV1PythonPackageSpecOutputWithContext 

func (i GoogleCloudAiplatformV1PythonPackageSpecArgs) ToGoogleCloudAiplatformV1PythonPackageSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PythonPackageSpecOutput

func (GoogleCloudAiplatformV1PythonPackageSpecArgs) ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutput 

func (i GoogleCloudAiplatformV1PythonPackageSpecArgs) ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutput() GoogleCloudAiplatformV1PythonPackageSpecPtrOutput

func (GoogleCloudAiplatformV1PythonPackageSpecArgs) ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1PythonPackageSpecArgs) ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PythonPackageSpecPtrOutput

type GoogleCloudAiplatformV1PythonPackageSpecInput 

type GoogleCloudAiplatformV1PythonPackageSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PythonPackageSpecOutput() GoogleCloudAiplatformV1PythonPackageSpecOutput
	ToGoogleCloudAiplatformV1PythonPackageSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1PythonPackageSpecOutput
}

GoogleCloudAiplatformV1PythonPackageSpecInput is an input type that accepts GoogleCloudAiplatformV1PythonPackageSpecArgs and GoogleCloudAiplatformV1PythonPackageSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PythonPackageSpecInput` via: 

GoogleCloudAiplatformV1PythonPackageSpecArgs{...}

type GoogleCloudAiplatformV1PythonPackageSpecOutput 

type GoogleCloudAiplatformV1PythonPackageSpecOutput struct{ *pulumi.OutputState }

The spec of a Python packaged code.

func (GoogleCloudAiplatformV1PythonPackageSpecOutput) Args 

func (o GoogleCloudAiplatformV1PythonPackageSpecOutput) Args() pulumi.StringArrayOutput

Command line arguments to be passed to the Python task.

func (GoogleCloudAiplatformV1PythonPackageSpecOutput) ElementType 

func (GoogleCloudAiplatformV1PythonPackageSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PythonPackageSpecOutput) Env 

func (o GoogleCloudAiplatformV1PythonPackageSpecOutput) Env() GoogleCloudAiplatformV1EnvVarArrayOutput

Environment variables to be passed to the python module. Maximum limit is 100.

func (GoogleCloudAiplatformV1PythonPackageSpecOutput) ExecutorImageUri 

func (o GoogleCloudAiplatformV1PythonPackageSpecOutput) ExecutorImageUri() pulumi.StringOutput

The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of [pre-built containers for training](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). You must use an image from this list.

func (GoogleCloudAiplatformV1PythonPackageSpecOutput) PackageUris 

func (o GoogleCloudAiplatformV1PythonPackageSpecOutput) PackageUris() pulumi.StringArrayOutput

The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.

func (GoogleCloudAiplatformV1PythonPackageSpecOutput) PythonModule 

func (o GoogleCloudAiplatformV1PythonPackageSpecOutput) PythonModule() pulumi.StringOutput

The Python module name to run after installing the packages.

func (GoogleCloudAiplatformV1PythonPackageSpecOutput) ToGoogleCloudAiplatformV1PythonPackageSpecOutput 

func (o GoogleCloudAiplatformV1PythonPackageSpecOutput) ToGoogleCloudAiplatformV1PythonPackageSpecOutput() GoogleCloudAiplatformV1PythonPackageSpecOutput

func (GoogleCloudAiplatformV1PythonPackageSpecOutput) ToGoogleCloudAiplatformV1PythonPackageSpecOutputWithContext 

func (o GoogleCloudAiplatformV1PythonPackageSpecOutput) ToGoogleCloudAiplatformV1PythonPackageSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PythonPackageSpecOutput

func (GoogleCloudAiplatformV1PythonPackageSpecOutput) ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutput 

func (o GoogleCloudAiplatformV1PythonPackageSpecOutput) ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutput() GoogleCloudAiplatformV1PythonPackageSpecPtrOutput

func (GoogleCloudAiplatformV1PythonPackageSpecOutput) ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PythonPackageSpecOutput) ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PythonPackageSpecPtrOutput

type GoogleCloudAiplatformV1PythonPackageSpecPtrInput 

type GoogleCloudAiplatformV1PythonPackageSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutput() GoogleCloudAiplatformV1PythonPackageSpecPtrOutput
	ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1PythonPackageSpecPtrOutput
}

GoogleCloudAiplatformV1PythonPackageSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1PythonPackageSpecArgs, GoogleCloudAiplatformV1PythonPackageSpecPtr and GoogleCloudAiplatformV1PythonPackageSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1PythonPackageSpecPtrInput` via: 

        GoogleCloudAiplatformV1PythonPackageSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1PythonPackageSpecPtr 

func GoogleCloudAiplatformV1PythonPackageSpecPtr(v *GoogleCloudAiplatformV1PythonPackageSpecArgs) GoogleCloudAiplatformV1PythonPackageSpecPtrInput

type GoogleCloudAiplatformV1PythonPackageSpecPtrOutput 

type GoogleCloudAiplatformV1PythonPackageSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) Args 

func (o GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) Args() pulumi.StringArrayOutput

Command line arguments to be passed to the Python task.

func (GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) Elem() GoogleCloudAiplatformV1PythonPackageSpecOutput

func (GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) Env 

func (o GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) Env() GoogleCloudAiplatformV1EnvVarArrayOutput

Environment variables to be passed to the python module. Maximum limit is 100.

func (GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) ExecutorImageUri 

func (o GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) ExecutorImageUri() pulumi.StringPtrOutput

The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of [pre-built containers for training](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). You must use an image from this list.

func (GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) PackageUris 

func (o GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) PackageUris() pulumi.StringArrayOutput

The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.

func (GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) PythonModule 

func (o GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) PythonModule() pulumi.StringPtrOutput

The Python module name to run after installing the packages.

func (GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutput 

func (o GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutput() GoogleCloudAiplatformV1PythonPackageSpecPtrOutput

func (GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1PythonPackageSpecPtrOutput) ToGoogleCloudAiplatformV1PythonPackageSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PythonPackageSpecPtrOutput

type GoogleCloudAiplatformV1PythonPackageSpecResponse 

type GoogleCloudAiplatformV1PythonPackageSpecResponse struct {
	// Command line arguments to be passed to the Python task.
	Args []string `pulumi:"args"`
	// Environment variables to be passed to the python module. Maximum limit is 100.
	Env []GoogleCloudAiplatformV1EnvVarResponse `pulumi:"env"`
	// The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of [pre-built containers for training](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). You must use an image from this list.
	ExecutorImageUri string `pulumi:"executorImageUri"`
	// The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.
	PackageUris []string `pulumi:"packageUris"`
	// The Python module name to run after installing the packages.
	PythonModule string `pulumi:"pythonModule"`
}

The spec of a Python packaged code.

type GoogleCloudAiplatformV1PythonPackageSpecResponseOutput 

type GoogleCloudAiplatformV1PythonPackageSpecResponseOutput struct{ *pulumi.OutputState }

The spec of a Python packaged code.

func (GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) Args 

func (o GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) Args() pulumi.StringArrayOutput

Command line arguments to be passed to the Python task.

func (GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) Env 

func (o GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) Env() GoogleCloudAiplatformV1EnvVarResponseArrayOutput

Environment variables to be passed to the python module. Maximum limit is 100.

func (GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) ExecutorImageUri 

func (o GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) ExecutorImageUri() pulumi.StringOutput

The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of [pre-built containers for training](https://cloud.google.com/vertex-ai/docs/training/pre-built-containers). You must use an image from this list.

func (GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) PackageUris 

func (o GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) PackageUris() pulumi.StringArrayOutput

The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100.

func (GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) PythonModule 

func (o GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) PythonModule() pulumi.StringOutput

The Python module name to run after installing the packages.

func (GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) ToGoogleCloudAiplatformV1PythonPackageSpecResponseOutput 

func (o GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) ToGoogleCloudAiplatformV1PythonPackageSpecResponseOutput() GoogleCloudAiplatformV1PythonPackageSpecResponseOutput

func (GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) ToGoogleCloudAiplatformV1PythonPackageSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1PythonPackageSpecResponseOutput) ToGoogleCloudAiplatformV1PythonPackageSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1PythonPackageSpecResponseOutput

type GoogleCloudAiplatformV1ResourcesConsumedResponse 

type GoogleCloudAiplatformV1ResourcesConsumedResponse struct {
	// The number of replica hours used. Note that many replicas may run in parallel, and additionally any given work may be queued for some time. Therefore this value is not strictly related to wall time.
	ReplicaHours float64 `pulumi:"replicaHours"`
}

Statistics information about resource consumption.

type GoogleCloudAiplatformV1ResourcesConsumedResponseOutput 

type GoogleCloudAiplatformV1ResourcesConsumedResponseOutput struct{ *pulumi.OutputState }

Statistics information about resource consumption.

func (GoogleCloudAiplatformV1ResourcesConsumedResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ResourcesConsumedResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ResourcesConsumedResponseOutput) ReplicaHours 

func (o GoogleCloudAiplatformV1ResourcesConsumedResponseOutput) ReplicaHours() pulumi.Float64Output

The number of replica hours used. Note that many replicas may run in parallel, and additionally any given work may be queued for some time. Therefore this value is not strictly related to wall time.

func (GoogleCloudAiplatformV1ResourcesConsumedResponseOutput) ToGoogleCloudAiplatformV1ResourcesConsumedResponseOutput 

func (o GoogleCloudAiplatformV1ResourcesConsumedResponseOutput) ToGoogleCloudAiplatformV1ResourcesConsumedResponseOutput() GoogleCloudAiplatformV1ResourcesConsumedResponseOutput

func (GoogleCloudAiplatformV1ResourcesConsumedResponseOutput) ToGoogleCloudAiplatformV1ResourcesConsumedResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ResourcesConsumedResponseOutput) ToGoogleCloudAiplatformV1ResourcesConsumedResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ResourcesConsumedResponseOutput

type GoogleCloudAiplatformV1SampleConfig 

type GoogleCloudAiplatformV1SampleConfig struct {
	// The percentage of data needed to be labeled in each following batch (except the first batch).
	FollowingBatchSamplePercentage *int `pulumi:"followingBatchSamplePercentage"`
	// The percentage of data needed to be labeled in the first batch.
	InitialBatchSamplePercentage *int `pulumi:"initialBatchSamplePercentage"`
	// Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.
	SampleStrategy *GoogleCloudAiplatformV1SampleConfigSampleStrategy `pulumi:"sampleStrategy"`
}

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

type GoogleCloudAiplatformV1SampleConfigArgs 

type GoogleCloudAiplatformV1SampleConfigArgs struct {
	// The percentage of data needed to be labeled in each following batch (except the first batch).
	FollowingBatchSamplePercentage pulumi.IntPtrInput `pulumi:"followingBatchSamplePercentage"`
	// The percentage of data needed to be labeled in the first batch.
	InitialBatchSamplePercentage pulumi.IntPtrInput `pulumi:"initialBatchSamplePercentage"`
	// Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.
	SampleStrategy GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrInput `pulumi:"sampleStrategy"`
}

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

func (GoogleCloudAiplatformV1SampleConfigArgs) ElementType 

func (GoogleCloudAiplatformV1SampleConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SampleConfigArgs) ToGoogleCloudAiplatformV1SampleConfigOutput 

func (i GoogleCloudAiplatformV1SampleConfigArgs) ToGoogleCloudAiplatformV1SampleConfigOutput() GoogleCloudAiplatformV1SampleConfigOutput

func (GoogleCloudAiplatformV1SampleConfigArgs) ToGoogleCloudAiplatformV1SampleConfigOutputWithContext 

func (i GoogleCloudAiplatformV1SampleConfigArgs) ToGoogleCloudAiplatformV1SampleConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampleConfigOutput

func (GoogleCloudAiplatformV1SampleConfigArgs) ToGoogleCloudAiplatformV1SampleConfigPtrOutput 

func (i GoogleCloudAiplatformV1SampleConfigArgs) ToGoogleCloudAiplatformV1SampleConfigPtrOutput() GoogleCloudAiplatformV1SampleConfigPtrOutput

func (GoogleCloudAiplatformV1SampleConfigArgs) ToGoogleCloudAiplatformV1SampleConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1SampleConfigArgs) ToGoogleCloudAiplatformV1SampleConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampleConfigPtrOutput

type GoogleCloudAiplatformV1SampleConfigInput 

type GoogleCloudAiplatformV1SampleConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SampleConfigOutput() GoogleCloudAiplatformV1SampleConfigOutput
	ToGoogleCloudAiplatformV1SampleConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1SampleConfigOutput
}

GoogleCloudAiplatformV1SampleConfigInput is an input type that accepts GoogleCloudAiplatformV1SampleConfigArgs and GoogleCloudAiplatformV1SampleConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SampleConfigInput` via: 

GoogleCloudAiplatformV1SampleConfigArgs{...}

type GoogleCloudAiplatformV1SampleConfigOutput 

type GoogleCloudAiplatformV1SampleConfigOutput struct{ *pulumi.OutputState }

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

func (GoogleCloudAiplatformV1SampleConfigOutput) ElementType 

func (GoogleCloudAiplatformV1SampleConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SampleConfigOutput) FollowingBatchSamplePercentage 

func (o GoogleCloudAiplatformV1SampleConfigOutput) FollowingBatchSamplePercentage() pulumi.IntPtrOutput

The percentage of data needed to be labeled in each following batch (except the first batch).

func (GoogleCloudAiplatformV1SampleConfigOutput) InitialBatchSamplePercentage 

func (o GoogleCloudAiplatformV1SampleConfigOutput) InitialBatchSamplePercentage() pulumi.IntPtrOutput

The percentage of data needed to be labeled in the first batch.

func (GoogleCloudAiplatformV1SampleConfigOutput) SampleStrategy 

func (o GoogleCloudAiplatformV1SampleConfigOutput) SampleStrategy() GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput

Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.

func (GoogleCloudAiplatformV1SampleConfigOutput) ToGoogleCloudAiplatformV1SampleConfigOutput 

func (o GoogleCloudAiplatformV1SampleConfigOutput) ToGoogleCloudAiplatformV1SampleConfigOutput() GoogleCloudAiplatformV1SampleConfigOutput

func (GoogleCloudAiplatformV1SampleConfigOutput) ToGoogleCloudAiplatformV1SampleConfigOutputWithContext 

func (o GoogleCloudAiplatformV1SampleConfigOutput) ToGoogleCloudAiplatformV1SampleConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampleConfigOutput

func (GoogleCloudAiplatformV1SampleConfigOutput) ToGoogleCloudAiplatformV1SampleConfigPtrOutput 

func (o GoogleCloudAiplatformV1SampleConfigOutput) ToGoogleCloudAiplatformV1SampleConfigPtrOutput() GoogleCloudAiplatformV1SampleConfigPtrOutput

func (GoogleCloudAiplatformV1SampleConfigOutput) ToGoogleCloudAiplatformV1SampleConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SampleConfigOutput) ToGoogleCloudAiplatformV1SampleConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampleConfigPtrOutput

type GoogleCloudAiplatformV1SampleConfigPtrInput 

type GoogleCloudAiplatformV1SampleConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SampleConfigPtrOutput() GoogleCloudAiplatformV1SampleConfigPtrOutput
	ToGoogleCloudAiplatformV1SampleConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1SampleConfigPtrOutput
}

GoogleCloudAiplatformV1SampleConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1SampleConfigArgs, GoogleCloudAiplatformV1SampleConfigPtr and GoogleCloudAiplatformV1SampleConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SampleConfigPtrInput` via: 

        GoogleCloudAiplatformV1SampleConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1SampleConfigPtr 

func GoogleCloudAiplatformV1SampleConfigPtr(v *GoogleCloudAiplatformV1SampleConfigArgs) GoogleCloudAiplatformV1SampleConfigPtrInput

type GoogleCloudAiplatformV1SampleConfigPtrOutput 

type GoogleCloudAiplatformV1SampleConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1SampleConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1SampleConfigPtrOutput) Elem() GoogleCloudAiplatformV1SampleConfigOutput

func (GoogleCloudAiplatformV1SampleConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1SampleConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SampleConfigPtrOutput) FollowingBatchSamplePercentage 

func (o GoogleCloudAiplatformV1SampleConfigPtrOutput) FollowingBatchSamplePercentage() pulumi.IntPtrOutput

The percentage of data needed to be labeled in each following batch (except the first batch).

func (GoogleCloudAiplatformV1SampleConfigPtrOutput) InitialBatchSamplePercentage 

func (o GoogleCloudAiplatformV1SampleConfigPtrOutput) InitialBatchSamplePercentage() pulumi.IntPtrOutput

The percentage of data needed to be labeled in the first batch.

func (GoogleCloudAiplatformV1SampleConfigPtrOutput) SampleStrategy 

func (o GoogleCloudAiplatformV1SampleConfigPtrOutput) SampleStrategy() GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput

Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.

func (GoogleCloudAiplatformV1SampleConfigPtrOutput) ToGoogleCloudAiplatformV1SampleConfigPtrOutput 

func (o GoogleCloudAiplatformV1SampleConfigPtrOutput) ToGoogleCloudAiplatformV1SampleConfigPtrOutput() GoogleCloudAiplatformV1SampleConfigPtrOutput

func (GoogleCloudAiplatformV1SampleConfigPtrOutput) ToGoogleCloudAiplatformV1SampleConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SampleConfigPtrOutput) ToGoogleCloudAiplatformV1SampleConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampleConfigPtrOutput

type GoogleCloudAiplatformV1SampleConfigResponse 

type GoogleCloudAiplatformV1SampleConfigResponse struct {
	// The percentage of data needed to be labeled in each following batch (except the first batch).
	FollowingBatchSamplePercentage int `pulumi:"followingBatchSamplePercentage"`
	// The percentage of data needed to be labeled in the first batch.
	InitialBatchSamplePercentage int `pulumi:"initialBatchSamplePercentage"`
	// Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.
	SampleStrategy string `pulumi:"sampleStrategy"`
}

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

type GoogleCloudAiplatformV1SampleConfigResponseOutput 

type GoogleCloudAiplatformV1SampleConfigResponseOutput struct{ *pulumi.OutputState }

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

func (GoogleCloudAiplatformV1SampleConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1SampleConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SampleConfigResponseOutput) FollowingBatchSamplePercentage 

func (o GoogleCloudAiplatformV1SampleConfigResponseOutput) FollowingBatchSamplePercentage() pulumi.IntOutput

The percentage of data needed to be labeled in each following batch (except the first batch).

func (GoogleCloudAiplatformV1SampleConfigResponseOutput) InitialBatchSamplePercentage 

func (o GoogleCloudAiplatformV1SampleConfigResponseOutput) InitialBatchSamplePercentage() pulumi.IntOutput

The percentage of data needed to be labeled in the first batch.

func (GoogleCloudAiplatformV1SampleConfigResponseOutput) SampleStrategy 

func (o GoogleCloudAiplatformV1SampleConfigResponseOutput) SampleStrategy() pulumi.StringOutput

Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.

func (GoogleCloudAiplatformV1SampleConfigResponseOutput) ToGoogleCloudAiplatformV1SampleConfigResponseOutput 

func (o GoogleCloudAiplatformV1SampleConfigResponseOutput) ToGoogleCloudAiplatformV1SampleConfigResponseOutput() GoogleCloudAiplatformV1SampleConfigResponseOutput

func (GoogleCloudAiplatformV1SampleConfigResponseOutput) ToGoogleCloudAiplatformV1SampleConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1SampleConfigResponseOutput) ToGoogleCloudAiplatformV1SampleConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampleConfigResponseOutput

type GoogleCloudAiplatformV1SampleConfigSampleStrategy 

type GoogleCloudAiplatformV1SampleConfigSampleStrategy string

Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch.

func (GoogleCloudAiplatformV1SampleConfigSampleStrategy) ElementType 

func (GoogleCloudAiplatformV1SampleConfigSampleStrategy) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyOutput 

func (e GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyOutput() GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyOutputWithContext 

func (e GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput 

func (e GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput() GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutputWithContext 

func (e GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToStringOutput 

func (e GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1SampleConfigSampleStrategy) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1SampleConfigSampleStrategyInput 

type GoogleCloudAiplatformV1SampleConfigSampleStrategyInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SampleConfigSampleStrategyOutput() GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput
	ToGoogleCloudAiplatformV1SampleConfigSampleStrategyOutputWithContext(context.Context) GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput
}

GoogleCloudAiplatformV1SampleConfigSampleStrategyInput is an input type that accepts GoogleCloudAiplatformV1SampleConfigSampleStrategyArgs and GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SampleConfigSampleStrategyInput` via: 

GoogleCloudAiplatformV1SampleConfigSampleStrategyArgs{...}

type GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput 

type GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ElementType 

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyOutput 

func (o GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyOutput() GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyOutputWithContext 

func (o GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput 

func (o GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput() GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrInput 

type GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput() GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput
	ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput
}

func GoogleCloudAiplatformV1SampleConfigSampleStrategyPtr 

func GoogleCloudAiplatformV1SampleConfigSampleStrategyPtr(v string) GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrInput

type GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput 

type GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput) Elem 

func (o GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput) Elem() GoogleCloudAiplatformV1SampleConfigSampleStrategyOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput) ElementType 

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput 

func (o GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput() GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput) ToGoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SampleConfigSampleStrategyPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1SampledShapleyAttribution 

type GoogleCloudAiplatformV1SampledShapleyAttribution struct {
	// The number of feature permutations to consider when approximating the Shapley values. Valid range of its value is [1, 50], inclusively.
	PathCount int `pulumi:"pathCount"`
}

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

type GoogleCloudAiplatformV1SampledShapleyAttributionArgs 

type GoogleCloudAiplatformV1SampledShapleyAttributionArgs struct {
	// The number of feature permutations to consider when approximating the Shapley values. Valid range of its value is [1, 50], inclusively.
	PathCount pulumi.IntInput `pulumi:"pathCount"`
}

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

func (GoogleCloudAiplatformV1SampledShapleyAttributionArgs) ElementType 

func (GoogleCloudAiplatformV1SampledShapleyAttributionArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SampledShapleyAttributionArgs) ToGoogleCloudAiplatformV1SampledShapleyAttributionOutput 

func (i GoogleCloudAiplatformV1SampledShapleyAttributionArgs) ToGoogleCloudAiplatformV1SampledShapleyAttributionOutput() GoogleCloudAiplatformV1SampledShapleyAttributionOutput

func (GoogleCloudAiplatformV1SampledShapleyAttributionArgs) ToGoogleCloudAiplatformV1SampledShapleyAttributionOutputWithContext 

func (i GoogleCloudAiplatformV1SampledShapleyAttributionArgs) ToGoogleCloudAiplatformV1SampledShapleyAttributionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampledShapleyAttributionOutput

func (GoogleCloudAiplatformV1SampledShapleyAttributionArgs) ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput 

func (i GoogleCloudAiplatformV1SampledShapleyAttributionArgs) ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput() GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput

func (GoogleCloudAiplatformV1SampledShapleyAttributionArgs) ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutputWithContext 

func (i GoogleCloudAiplatformV1SampledShapleyAttributionArgs) ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput

type GoogleCloudAiplatformV1SampledShapleyAttributionInput 

type GoogleCloudAiplatformV1SampledShapleyAttributionInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SampledShapleyAttributionOutput() GoogleCloudAiplatformV1SampledShapleyAttributionOutput
	ToGoogleCloudAiplatformV1SampledShapleyAttributionOutputWithContext(context.Context) GoogleCloudAiplatformV1SampledShapleyAttributionOutput
}

GoogleCloudAiplatformV1SampledShapleyAttributionInput is an input type that accepts GoogleCloudAiplatformV1SampledShapleyAttributionArgs and GoogleCloudAiplatformV1SampledShapleyAttributionOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SampledShapleyAttributionInput` via: 

GoogleCloudAiplatformV1SampledShapleyAttributionArgs{...}

type GoogleCloudAiplatformV1SampledShapleyAttributionOutput 

type GoogleCloudAiplatformV1SampledShapleyAttributionOutput struct{ *pulumi.OutputState }

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

func (GoogleCloudAiplatformV1SampledShapleyAttributionOutput) ElementType 

func (GoogleCloudAiplatformV1SampledShapleyAttributionOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SampledShapleyAttributionOutput) PathCount 

func (o GoogleCloudAiplatformV1SampledShapleyAttributionOutput) PathCount() pulumi.IntOutput

The number of feature permutations to consider when approximating the Shapley values. Valid range of its value is [1, 50], inclusively.

func (GoogleCloudAiplatformV1SampledShapleyAttributionOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionOutput 

func (o GoogleCloudAiplatformV1SampledShapleyAttributionOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionOutput() GoogleCloudAiplatformV1SampledShapleyAttributionOutput

func (GoogleCloudAiplatformV1SampledShapleyAttributionOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionOutputWithContext 

func (o GoogleCloudAiplatformV1SampledShapleyAttributionOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampledShapleyAttributionOutput

func (GoogleCloudAiplatformV1SampledShapleyAttributionOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput 

func (o GoogleCloudAiplatformV1SampledShapleyAttributionOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput() GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput

func (GoogleCloudAiplatformV1SampledShapleyAttributionOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SampledShapleyAttributionOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput

type GoogleCloudAiplatformV1SampledShapleyAttributionPtrInput 

type GoogleCloudAiplatformV1SampledShapleyAttributionPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput() GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput
	ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput
}

GoogleCloudAiplatformV1SampledShapleyAttributionPtrInput is an input type that accepts GoogleCloudAiplatformV1SampledShapleyAttributionArgs, GoogleCloudAiplatformV1SampledShapleyAttributionPtr and GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SampledShapleyAttributionPtrInput` via: 

        GoogleCloudAiplatformV1SampledShapleyAttributionArgs{...}

or:

        nil

func GoogleCloudAiplatformV1SampledShapleyAttributionPtr 

func GoogleCloudAiplatformV1SampledShapleyAttributionPtr(v *GoogleCloudAiplatformV1SampledShapleyAttributionArgs) GoogleCloudAiplatformV1SampledShapleyAttributionPtrInput

type GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput 

type GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput) Elem 

func (o GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput) Elem() GoogleCloudAiplatformV1SampledShapleyAttributionOutput

func (GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput) ElementType 

func (GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput) PathCount 

func (o GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput) PathCount() pulumi.IntPtrOutput

The number of feature permutations to consider when approximating the Shapley values. Valid range of its value is [1, 50], inclusively.

func (GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput 

func (o GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput() GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput

func (GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampledShapleyAttributionPtrOutput

type GoogleCloudAiplatformV1SampledShapleyAttributionResponse 

type GoogleCloudAiplatformV1SampledShapleyAttributionResponse struct {
	// The number of feature permutations to consider when approximating the Shapley values. Valid range of its value is [1, 50], inclusively.
	PathCount int `pulumi:"pathCount"`
}

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

type GoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput 

type GoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput struct{ *pulumi.OutputState }

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

func (GoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput) ElementType 

func (GoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput) PathCount 

func (o GoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput) PathCount() pulumi.IntOutput

The number of feature permutations to consider when approximating the Shapley values. Valid range of its value is [1, 50], inclusively.

func (GoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput 

func (o GoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput() GoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput

func (GoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionResponseOutputWithContext 

func (o GoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput) ToGoogleCloudAiplatformV1SampledShapleyAttributionResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SampledShapleyAttributionResponseOutput

type GoogleCloudAiplatformV1SamplingStrategy 

type GoogleCloudAiplatformV1SamplingStrategy struct {
	// Random sample config. Will support more sampling strategies later.
	RandomSampleConfig *GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfig `pulumi:"randomSampleConfig"`
}

Sampling Strategy for logging, can be for both training and prediction dataset.

type GoogleCloudAiplatformV1SamplingStrategyArgs 

type GoogleCloudAiplatformV1SamplingStrategyArgs struct {
	// Random sample config. Will support more sampling strategies later.
	RandomSampleConfig GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrInput `pulumi:"randomSampleConfig"`
}

Sampling Strategy for logging, can be for both training and prediction dataset.

func (GoogleCloudAiplatformV1SamplingStrategyArgs) ElementType 

func (GoogleCloudAiplatformV1SamplingStrategyArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SamplingStrategyArgs) ToGoogleCloudAiplatformV1SamplingStrategyOutput 

func (i GoogleCloudAiplatformV1SamplingStrategyArgs) ToGoogleCloudAiplatformV1SamplingStrategyOutput() GoogleCloudAiplatformV1SamplingStrategyOutput

func (GoogleCloudAiplatformV1SamplingStrategyArgs) ToGoogleCloudAiplatformV1SamplingStrategyOutputWithContext 

func (i GoogleCloudAiplatformV1SamplingStrategyArgs) ToGoogleCloudAiplatformV1SamplingStrategyOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SamplingStrategyOutput

func (GoogleCloudAiplatformV1SamplingStrategyArgs) ToGoogleCloudAiplatformV1SamplingStrategyPtrOutput 

func (i GoogleCloudAiplatformV1SamplingStrategyArgs) ToGoogleCloudAiplatformV1SamplingStrategyPtrOutput() GoogleCloudAiplatformV1SamplingStrategyPtrOutput

func (GoogleCloudAiplatformV1SamplingStrategyArgs) ToGoogleCloudAiplatformV1SamplingStrategyPtrOutputWithContext 

func (i GoogleCloudAiplatformV1SamplingStrategyArgs) ToGoogleCloudAiplatformV1SamplingStrategyPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SamplingStrategyPtrOutput

type GoogleCloudAiplatformV1SamplingStrategyInput 

type GoogleCloudAiplatformV1SamplingStrategyInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SamplingStrategyOutput() GoogleCloudAiplatformV1SamplingStrategyOutput
	ToGoogleCloudAiplatformV1SamplingStrategyOutputWithContext(context.Context) GoogleCloudAiplatformV1SamplingStrategyOutput
}

GoogleCloudAiplatformV1SamplingStrategyInput is an input type that accepts GoogleCloudAiplatformV1SamplingStrategyArgs and GoogleCloudAiplatformV1SamplingStrategyOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SamplingStrategyInput` via: 

GoogleCloudAiplatformV1SamplingStrategyArgs{...}

type GoogleCloudAiplatformV1SamplingStrategyOutput 

type GoogleCloudAiplatformV1SamplingStrategyOutput struct{ *pulumi.OutputState }

Sampling Strategy for logging, can be for both training and prediction dataset.

func (GoogleCloudAiplatformV1SamplingStrategyOutput) ElementType 

func (GoogleCloudAiplatformV1SamplingStrategyOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SamplingStrategyOutput) RandomSampleConfig 

func (o GoogleCloudAiplatformV1SamplingStrategyOutput) RandomSampleConfig() GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput

Random sample config. Will support more sampling strategies later.

func (GoogleCloudAiplatformV1SamplingStrategyOutput) ToGoogleCloudAiplatformV1SamplingStrategyOutput 

func (o GoogleCloudAiplatformV1SamplingStrategyOutput) ToGoogleCloudAiplatformV1SamplingStrategyOutput() GoogleCloudAiplatformV1SamplingStrategyOutput

func (GoogleCloudAiplatformV1SamplingStrategyOutput) ToGoogleCloudAiplatformV1SamplingStrategyOutputWithContext 

func (o GoogleCloudAiplatformV1SamplingStrategyOutput) ToGoogleCloudAiplatformV1SamplingStrategyOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SamplingStrategyOutput

func (GoogleCloudAiplatformV1SamplingStrategyOutput) ToGoogleCloudAiplatformV1SamplingStrategyPtrOutput 

func (o GoogleCloudAiplatformV1SamplingStrategyOutput) ToGoogleCloudAiplatformV1SamplingStrategyPtrOutput() GoogleCloudAiplatformV1SamplingStrategyPtrOutput

func (GoogleCloudAiplatformV1SamplingStrategyOutput) ToGoogleCloudAiplatformV1SamplingStrategyPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SamplingStrategyOutput) ToGoogleCloudAiplatformV1SamplingStrategyPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SamplingStrategyPtrOutput

type GoogleCloudAiplatformV1SamplingStrategyPtrInput 

type GoogleCloudAiplatformV1SamplingStrategyPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SamplingStrategyPtrOutput() GoogleCloudAiplatformV1SamplingStrategyPtrOutput
	ToGoogleCloudAiplatformV1SamplingStrategyPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1SamplingStrategyPtrOutput
}

GoogleCloudAiplatformV1SamplingStrategyPtrInput is an input type that accepts GoogleCloudAiplatformV1SamplingStrategyArgs, GoogleCloudAiplatformV1SamplingStrategyPtr and GoogleCloudAiplatformV1SamplingStrategyPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SamplingStrategyPtrInput` via: 

        GoogleCloudAiplatformV1SamplingStrategyArgs{...}

or:

        nil

func GoogleCloudAiplatformV1SamplingStrategyPtr 

func GoogleCloudAiplatformV1SamplingStrategyPtr(v *GoogleCloudAiplatformV1SamplingStrategyArgs) GoogleCloudAiplatformV1SamplingStrategyPtrInput

type GoogleCloudAiplatformV1SamplingStrategyPtrOutput 

type GoogleCloudAiplatformV1SamplingStrategyPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1SamplingStrategyPtrOutput) Elem 

func (o GoogleCloudAiplatformV1SamplingStrategyPtrOutput) Elem() GoogleCloudAiplatformV1SamplingStrategyOutput

func (GoogleCloudAiplatformV1SamplingStrategyPtrOutput) ElementType 

func (GoogleCloudAiplatformV1SamplingStrategyPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SamplingStrategyPtrOutput) RandomSampleConfig 

func (o GoogleCloudAiplatformV1SamplingStrategyPtrOutput) RandomSampleConfig() GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput

Random sample config. Will support more sampling strategies later.

func (GoogleCloudAiplatformV1SamplingStrategyPtrOutput) ToGoogleCloudAiplatformV1SamplingStrategyPtrOutput 

func (o GoogleCloudAiplatformV1SamplingStrategyPtrOutput) ToGoogleCloudAiplatformV1SamplingStrategyPtrOutput() GoogleCloudAiplatformV1SamplingStrategyPtrOutput

func (GoogleCloudAiplatformV1SamplingStrategyPtrOutput) ToGoogleCloudAiplatformV1SamplingStrategyPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SamplingStrategyPtrOutput) ToGoogleCloudAiplatformV1SamplingStrategyPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SamplingStrategyPtrOutput

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfig 

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfig struct {
	// Sample rate (0, 1]
	SampleRate *float64 `pulumi:"sampleRate"`
}

Requests are randomly selected.

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs 

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs struct {
	// Sample rate (0, 1]
	SampleRate pulumi.Float64PtrInput `pulumi:"sampleRate"`
}

Requests are randomly selected.

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs) ElementType 

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput 

func (i GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput() GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutputWithContext 

func (i GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput 

func (i GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput() GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigInput 

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput() GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput
	ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput
}

GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigInput is an input type that accepts GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs and GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigInput` via: 

GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs{...}

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput 

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput struct{ *pulumi.OutputState }

Requests are randomly selected.

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput) ElementType 

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput) SampleRate 

func (o GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput) SampleRate() pulumi.Float64PtrOutput

Sample rate (0, 1]

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput 

func (o GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput() GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutputWithContext 

func (o GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput 

func (o GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput() GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrInput 

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput() GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput
	ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput
}

GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs, GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtr and GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrInput` via: 

        GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtr 

func GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtr(v *GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigArgs) GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrInput

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput 

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput) Elem() GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigOutput

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput) SampleRate 

func (o GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput) SampleRate() pulumi.Float64PtrOutput

Sample rate (0, 1]

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput 

func (o GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput() GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigPtrOutput

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponse 

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponse struct {
	// Sample rate (0, 1]
	SampleRate float64 `pulumi:"sampleRate"`
}

Requests are randomly selected.

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput 

type GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput struct{ *pulumi.OutputState }

Requests are randomly selected.

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput) SampleRate 

func (o GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput) SampleRate() pulumi.Float64Output

Sample rate (0, 1]

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput 

func (o GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput() GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput

func (GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput) ToGoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput

type GoogleCloudAiplatformV1SamplingStrategyResponse 

type GoogleCloudAiplatformV1SamplingStrategyResponse struct {
	// Random sample config. Will support more sampling strategies later.
	RandomSampleConfig GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponse `pulumi:"randomSampleConfig"`
}

Sampling Strategy for logging, can be for both training and prediction dataset.

type GoogleCloudAiplatformV1SamplingStrategyResponseOutput 

type GoogleCloudAiplatformV1SamplingStrategyResponseOutput struct{ *pulumi.OutputState }

Sampling Strategy for logging, can be for both training and prediction dataset.

func (GoogleCloudAiplatformV1SamplingStrategyResponseOutput) ElementType 

func (GoogleCloudAiplatformV1SamplingStrategyResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SamplingStrategyResponseOutput) RandomSampleConfig 

func (o GoogleCloudAiplatformV1SamplingStrategyResponseOutput) RandomSampleConfig() GoogleCloudAiplatformV1SamplingStrategyRandomSampleConfigResponseOutput

Random sample config. Will support more sampling strategies later.

func (GoogleCloudAiplatformV1SamplingStrategyResponseOutput) ToGoogleCloudAiplatformV1SamplingStrategyResponseOutput 

func (o GoogleCloudAiplatformV1SamplingStrategyResponseOutput) ToGoogleCloudAiplatformV1SamplingStrategyResponseOutput() GoogleCloudAiplatformV1SamplingStrategyResponseOutput

func (GoogleCloudAiplatformV1SamplingStrategyResponseOutput) ToGoogleCloudAiplatformV1SamplingStrategyResponseOutputWithContext 

func (o GoogleCloudAiplatformV1SamplingStrategyResponseOutput) ToGoogleCloudAiplatformV1SamplingStrategyResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SamplingStrategyResponseOutput

type GoogleCloudAiplatformV1SavedQuery 

type GoogleCloudAiplatformV1SavedQuery struct {
	// The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Used to perform a consistent read-modify-write update. If not set, a blind "overwrite" update happens.
	Etag *string `pulumi:"etag"`
	// Some additional information about the SavedQuery.
	Metadata interface{} `pulumi:"metadata"`
	// Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING
	ProblemType string `pulumi:"problemType"`
}

A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.

type GoogleCloudAiplatformV1SavedQueryArgs 

type GoogleCloudAiplatformV1SavedQueryArgs struct {
	// The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringInput `pulumi:"displayName"`
	// Used to perform a consistent read-modify-write update. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput `pulumi:"etag"`
	// Some additional information about the SavedQuery.
	Metadata pulumi.Input `pulumi:"metadata"`
	// Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING
	ProblemType pulumi.StringInput `pulumi:"problemType"`
}

A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.

func (GoogleCloudAiplatformV1SavedQueryArgs) ElementType 

func (GoogleCloudAiplatformV1SavedQueryArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SavedQueryArgs) ToGoogleCloudAiplatformV1SavedQueryOutput 

func (i GoogleCloudAiplatformV1SavedQueryArgs) ToGoogleCloudAiplatformV1SavedQueryOutput() GoogleCloudAiplatformV1SavedQueryOutput

func (GoogleCloudAiplatformV1SavedQueryArgs) ToGoogleCloudAiplatformV1SavedQueryOutputWithContext 

func (i GoogleCloudAiplatformV1SavedQueryArgs) ToGoogleCloudAiplatformV1SavedQueryOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SavedQueryOutput

type GoogleCloudAiplatformV1SavedQueryArray 

type GoogleCloudAiplatformV1SavedQueryArray []GoogleCloudAiplatformV1SavedQueryInput

func (GoogleCloudAiplatformV1SavedQueryArray) ElementType 

func (GoogleCloudAiplatformV1SavedQueryArray) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SavedQueryArray) ToGoogleCloudAiplatformV1SavedQueryArrayOutput 

func (i GoogleCloudAiplatformV1SavedQueryArray) ToGoogleCloudAiplatformV1SavedQueryArrayOutput() GoogleCloudAiplatformV1SavedQueryArrayOutput

func (GoogleCloudAiplatformV1SavedQueryArray) ToGoogleCloudAiplatformV1SavedQueryArrayOutputWithContext 

func (i GoogleCloudAiplatformV1SavedQueryArray) ToGoogleCloudAiplatformV1SavedQueryArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SavedQueryArrayOutput

type GoogleCloudAiplatformV1SavedQueryArrayInput 

type GoogleCloudAiplatformV1SavedQueryArrayInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SavedQueryArrayOutput() GoogleCloudAiplatformV1SavedQueryArrayOutput
	ToGoogleCloudAiplatformV1SavedQueryArrayOutputWithContext(context.Context) GoogleCloudAiplatformV1SavedQueryArrayOutput
}

GoogleCloudAiplatformV1SavedQueryArrayInput is an input type that accepts GoogleCloudAiplatformV1SavedQueryArray and GoogleCloudAiplatformV1SavedQueryArrayOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SavedQueryArrayInput` via: 

GoogleCloudAiplatformV1SavedQueryArray{ GoogleCloudAiplatformV1SavedQueryArgs{...} }

type GoogleCloudAiplatformV1SavedQueryArrayOutput 

type GoogleCloudAiplatformV1SavedQueryArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1SavedQueryArrayOutput) ElementType 

func (GoogleCloudAiplatformV1SavedQueryArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SavedQueryArrayOutput) Index 

func (o GoogleCloudAiplatformV1SavedQueryArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1SavedQueryOutput

func (GoogleCloudAiplatformV1SavedQueryArrayOutput) ToGoogleCloudAiplatformV1SavedQueryArrayOutput 

func (o GoogleCloudAiplatformV1SavedQueryArrayOutput) ToGoogleCloudAiplatformV1SavedQueryArrayOutput() GoogleCloudAiplatformV1SavedQueryArrayOutput

func (GoogleCloudAiplatformV1SavedQueryArrayOutput) ToGoogleCloudAiplatformV1SavedQueryArrayOutputWithContext 

func (o GoogleCloudAiplatformV1SavedQueryArrayOutput) ToGoogleCloudAiplatformV1SavedQueryArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SavedQueryArrayOutput

type GoogleCloudAiplatformV1SavedQueryInput 

type GoogleCloudAiplatformV1SavedQueryInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SavedQueryOutput() GoogleCloudAiplatformV1SavedQueryOutput
	ToGoogleCloudAiplatformV1SavedQueryOutputWithContext(context.Context) GoogleCloudAiplatformV1SavedQueryOutput
}

GoogleCloudAiplatformV1SavedQueryInput is an input type that accepts GoogleCloudAiplatformV1SavedQueryArgs and GoogleCloudAiplatformV1SavedQueryOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SavedQueryInput` via: 

GoogleCloudAiplatformV1SavedQueryArgs{...}

type GoogleCloudAiplatformV1SavedQueryOutput 

type GoogleCloudAiplatformV1SavedQueryOutput struct{ *pulumi.OutputState }

A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.

func (GoogleCloudAiplatformV1SavedQueryOutput) DisplayName 

func (o GoogleCloudAiplatformV1SavedQueryOutput) DisplayName() pulumi.StringOutput

The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (GoogleCloudAiplatformV1SavedQueryOutput) ElementType 

func (GoogleCloudAiplatformV1SavedQueryOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SavedQueryOutput) Etag 

func (o GoogleCloudAiplatformV1SavedQueryOutput) Etag() pulumi.StringPtrOutput

Used to perform a consistent read-modify-write update. If not set, a blind "overwrite" update happens.

func (GoogleCloudAiplatformV1SavedQueryOutput) Metadata 

func (o GoogleCloudAiplatformV1SavedQueryOutput) Metadata() pulumi.AnyOutput

Some additional information about the SavedQuery.

func (GoogleCloudAiplatformV1SavedQueryOutput) ProblemType 

func (o GoogleCloudAiplatformV1SavedQueryOutput) ProblemType() pulumi.StringOutput

Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING

func (GoogleCloudAiplatformV1SavedQueryOutput) ToGoogleCloudAiplatformV1SavedQueryOutput 

func (o GoogleCloudAiplatformV1SavedQueryOutput) ToGoogleCloudAiplatformV1SavedQueryOutput() GoogleCloudAiplatformV1SavedQueryOutput

func (GoogleCloudAiplatformV1SavedQueryOutput) ToGoogleCloudAiplatformV1SavedQueryOutputWithContext 

func (o GoogleCloudAiplatformV1SavedQueryOutput) ToGoogleCloudAiplatformV1SavedQueryOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SavedQueryOutput

type GoogleCloudAiplatformV1SavedQueryResponse 

type GoogleCloudAiplatformV1SavedQueryResponse struct {
	// Filters on the Annotations in the dataset.
	AnnotationFilter string `pulumi:"annotationFilter"`
	// Number of AnnotationSpecs in the context of the SavedQuery.
	AnnotationSpecCount int `pulumi:"annotationSpecCount"`
	// Timestamp when this SavedQuery was created.
	CreateTime string `pulumi:"createTime"`
	// The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Used to perform a consistent read-modify-write update. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// Some additional information about the SavedQuery.
	Metadata interface{} `pulumi:"metadata"`
	// Resource name of the SavedQuery.
	Name string `pulumi:"name"`
	// Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING
	ProblemType string `pulumi:"problemType"`
	// If the Annotations belonging to the SavedQuery can be used for AutoML training.
	SupportAutomlTraining bool `pulumi:"supportAutomlTraining"`
	// Timestamp when SavedQuery was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.

type GoogleCloudAiplatformV1SavedQueryResponseArrayOutput 

type GoogleCloudAiplatformV1SavedQueryResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1SavedQueryResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1SavedQueryResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SavedQueryResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1SavedQueryResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1SavedQueryResponseOutput

func (GoogleCloudAiplatformV1SavedQueryResponseArrayOutput) ToGoogleCloudAiplatformV1SavedQueryResponseArrayOutput 

func (o GoogleCloudAiplatformV1SavedQueryResponseArrayOutput) ToGoogleCloudAiplatformV1SavedQueryResponseArrayOutput() GoogleCloudAiplatformV1SavedQueryResponseArrayOutput

func (GoogleCloudAiplatformV1SavedQueryResponseArrayOutput) ToGoogleCloudAiplatformV1SavedQueryResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1SavedQueryResponseArrayOutput) ToGoogleCloudAiplatformV1SavedQueryResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SavedQueryResponseArrayOutput

type GoogleCloudAiplatformV1SavedQueryResponseOutput 

type GoogleCloudAiplatformV1SavedQueryResponseOutput struct{ *pulumi.OutputState }

A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) AnnotationFilter 

func (o GoogleCloudAiplatformV1SavedQueryResponseOutput) AnnotationFilter() pulumi.StringOutput

Filters on the Annotations in the dataset.

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) AnnotationSpecCount 

func (o GoogleCloudAiplatformV1SavedQueryResponseOutput) AnnotationSpecCount() pulumi.IntOutput

Number of AnnotationSpecs in the context of the SavedQuery.

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) CreateTime 

func (o GoogleCloudAiplatformV1SavedQueryResponseOutput) CreateTime() pulumi.StringOutput

Timestamp when this SavedQuery was created.

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) DisplayName 

func (o GoogleCloudAiplatformV1SavedQueryResponseOutput) DisplayName() pulumi.StringOutput

The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) ElementType 

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) Etag 

func (o GoogleCloudAiplatformV1SavedQueryResponseOutput) Etag() pulumi.StringOutput

Used to perform a consistent read-modify-write update. If not set, a blind "overwrite" update happens.

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) Metadata 

func (o GoogleCloudAiplatformV1SavedQueryResponseOutput) Metadata() pulumi.AnyOutput

Some additional information about the SavedQuery.

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) Name 

func (o GoogleCloudAiplatformV1SavedQueryResponseOutput) Name() pulumi.StringOutput

Resource name of the SavedQuery.

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) ProblemType 

func (o GoogleCloudAiplatformV1SavedQueryResponseOutput) ProblemType() pulumi.StringOutput

Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) SupportAutomlTraining 

func (o GoogleCloudAiplatformV1SavedQueryResponseOutput) SupportAutomlTraining() pulumi.BoolOutput

If the Annotations belonging to the SavedQuery can be used for AutoML training.

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) ToGoogleCloudAiplatformV1SavedQueryResponseOutput 

func (o GoogleCloudAiplatformV1SavedQueryResponseOutput) ToGoogleCloudAiplatformV1SavedQueryResponseOutput() GoogleCloudAiplatformV1SavedQueryResponseOutput

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) ToGoogleCloudAiplatformV1SavedQueryResponseOutputWithContext 

func (o GoogleCloudAiplatformV1SavedQueryResponseOutput) ToGoogleCloudAiplatformV1SavedQueryResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SavedQueryResponseOutput

func (GoogleCloudAiplatformV1SavedQueryResponseOutput) UpdateTime 

func (o GoogleCloudAiplatformV1SavedQueryResponseOutput) UpdateTime() pulumi.StringOutput

Timestamp when SavedQuery was last updated.

type GoogleCloudAiplatformV1ScheduleRunResponseResponse 

type GoogleCloudAiplatformV1ScheduleRunResponseResponse struct {
	// The response of the scheduled run.
	RunResponse string `pulumi:"runResponse"`
	// The scheduled run time based on the user-specified schedule.
	ScheduledRunTime string `pulumi:"scheduledRunTime"`
}

Status of a scheduled run.

type GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput 

type GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput struct{ *pulumi.OutputState }

Status of a scheduled run.

func (GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput) RunResponse 

func (o GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput) RunResponse() pulumi.StringOutput

The response of the scheduled run.

func (GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput) ScheduledRunTime 

func (o GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput) ScheduledRunTime() pulumi.StringOutput

The scheduled run time based on the user-specified schedule.

func (GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput) ToGoogleCloudAiplatformV1ScheduleRunResponseResponseOutput 

func (o GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput) ToGoogleCloudAiplatformV1ScheduleRunResponseResponseOutput() GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput

func (GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput) ToGoogleCloudAiplatformV1ScheduleRunResponseResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput) ToGoogleCloudAiplatformV1ScheduleRunResponseResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput

type GoogleCloudAiplatformV1Scheduling 

type GoogleCloudAiplatformV1Scheduling struct {
	// Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false.
	DisableRetries *bool `pulumi:"disableRetries"`
	// Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
	RestartJobOnWorkerRestart *bool `pulumi:"restartJobOnWorkerRestart"`
	// The maximum job running time. The default is 7 days.
	Timeout *string `pulumi:"timeout"`
}

All parameters related to queuing and scheduling of custom jobs.

type GoogleCloudAiplatformV1SchedulingArgs 

type GoogleCloudAiplatformV1SchedulingArgs struct {
	// Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false.
	DisableRetries pulumi.BoolPtrInput `pulumi:"disableRetries"`
	// Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
	RestartJobOnWorkerRestart pulumi.BoolPtrInput `pulumi:"restartJobOnWorkerRestart"`
	// The maximum job running time. The default is 7 days.
	Timeout pulumi.StringPtrInput `pulumi:"timeout"`
}

All parameters related to queuing and scheduling of custom jobs.

func (GoogleCloudAiplatformV1SchedulingArgs) ElementType 

func (GoogleCloudAiplatformV1SchedulingArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SchedulingArgs) ToGoogleCloudAiplatformV1SchedulingOutput 

func (i GoogleCloudAiplatformV1SchedulingArgs) ToGoogleCloudAiplatformV1SchedulingOutput() GoogleCloudAiplatformV1SchedulingOutput

func (GoogleCloudAiplatformV1SchedulingArgs) ToGoogleCloudAiplatformV1SchedulingOutputWithContext 

func (i GoogleCloudAiplatformV1SchedulingArgs) ToGoogleCloudAiplatformV1SchedulingOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SchedulingOutput

func (GoogleCloudAiplatformV1SchedulingArgs) ToGoogleCloudAiplatformV1SchedulingPtrOutput 

func (i GoogleCloudAiplatformV1SchedulingArgs) ToGoogleCloudAiplatformV1SchedulingPtrOutput() GoogleCloudAiplatformV1SchedulingPtrOutput

func (GoogleCloudAiplatformV1SchedulingArgs) ToGoogleCloudAiplatformV1SchedulingPtrOutputWithContext 

func (i GoogleCloudAiplatformV1SchedulingArgs) ToGoogleCloudAiplatformV1SchedulingPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SchedulingPtrOutput

type GoogleCloudAiplatformV1SchedulingInput 

type GoogleCloudAiplatformV1SchedulingInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SchedulingOutput() GoogleCloudAiplatformV1SchedulingOutput
	ToGoogleCloudAiplatformV1SchedulingOutputWithContext(context.Context) GoogleCloudAiplatformV1SchedulingOutput
}

GoogleCloudAiplatformV1SchedulingInput is an input type that accepts GoogleCloudAiplatformV1SchedulingArgs and GoogleCloudAiplatformV1SchedulingOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SchedulingInput` via: 

GoogleCloudAiplatformV1SchedulingArgs{...}

type GoogleCloudAiplatformV1SchedulingOutput 

type GoogleCloudAiplatformV1SchedulingOutput struct{ *pulumi.OutputState }

All parameters related to queuing and scheduling of custom jobs.

func (GoogleCloudAiplatformV1SchedulingOutput) DisableRetries 

func (o GoogleCloudAiplatformV1SchedulingOutput) DisableRetries() pulumi.BoolPtrOutput

Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false.

func (GoogleCloudAiplatformV1SchedulingOutput) ElementType 

func (GoogleCloudAiplatformV1SchedulingOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SchedulingOutput) RestartJobOnWorkerRestart 

func (o GoogleCloudAiplatformV1SchedulingOutput) RestartJobOnWorkerRestart() pulumi.BoolPtrOutput

Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.

func (GoogleCloudAiplatformV1SchedulingOutput) Timeout 

func (o GoogleCloudAiplatformV1SchedulingOutput) Timeout() pulumi.StringPtrOutput

The maximum job running time. The default is 7 days.

func (GoogleCloudAiplatformV1SchedulingOutput) ToGoogleCloudAiplatformV1SchedulingOutput 

func (o GoogleCloudAiplatformV1SchedulingOutput) ToGoogleCloudAiplatformV1SchedulingOutput() GoogleCloudAiplatformV1SchedulingOutput

func (GoogleCloudAiplatformV1SchedulingOutput) ToGoogleCloudAiplatformV1SchedulingOutputWithContext 

func (o GoogleCloudAiplatformV1SchedulingOutput) ToGoogleCloudAiplatformV1SchedulingOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SchedulingOutput

func (GoogleCloudAiplatformV1SchedulingOutput) ToGoogleCloudAiplatformV1SchedulingPtrOutput 

func (o GoogleCloudAiplatformV1SchedulingOutput) ToGoogleCloudAiplatformV1SchedulingPtrOutput() GoogleCloudAiplatformV1SchedulingPtrOutput

func (GoogleCloudAiplatformV1SchedulingOutput) ToGoogleCloudAiplatformV1SchedulingPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SchedulingOutput) ToGoogleCloudAiplatformV1SchedulingPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SchedulingPtrOutput

type GoogleCloudAiplatformV1SchedulingPtrInput 

type GoogleCloudAiplatformV1SchedulingPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SchedulingPtrOutput() GoogleCloudAiplatformV1SchedulingPtrOutput
	ToGoogleCloudAiplatformV1SchedulingPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1SchedulingPtrOutput
}

GoogleCloudAiplatformV1SchedulingPtrInput is an input type that accepts GoogleCloudAiplatformV1SchedulingArgs, GoogleCloudAiplatformV1SchedulingPtr and GoogleCloudAiplatformV1SchedulingPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SchedulingPtrInput` via: 

        GoogleCloudAiplatformV1SchedulingArgs{...}

or:

        nil

func GoogleCloudAiplatformV1SchedulingPtr 

func GoogleCloudAiplatformV1SchedulingPtr(v *GoogleCloudAiplatformV1SchedulingArgs) GoogleCloudAiplatformV1SchedulingPtrInput

type GoogleCloudAiplatformV1SchedulingPtrOutput 

type GoogleCloudAiplatformV1SchedulingPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1SchedulingPtrOutput) DisableRetries 

func (o GoogleCloudAiplatformV1SchedulingPtrOutput) DisableRetries() pulumi.BoolPtrOutput

Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false.

func (GoogleCloudAiplatformV1SchedulingPtrOutput) Elem 

func (o GoogleCloudAiplatformV1SchedulingPtrOutput) Elem() GoogleCloudAiplatformV1SchedulingOutput

func (GoogleCloudAiplatformV1SchedulingPtrOutput) ElementType 

func (GoogleCloudAiplatformV1SchedulingPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SchedulingPtrOutput) RestartJobOnWorkerRestart 

func (o GoogleCloudAiplatformV1SchedulingPtrOutput) RestartJobOnWorkerRestart() pulumi.BoolPtrOutput

Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.

func (GoogleCloudAiplatformV1SchedulingPtrOutput) Timeout 

func (o GoogleCloudAiplatformV1SchedulingPtrOutput) Timeout() pulumi.StringPtrOutput

The maximum job running time. The default is 7 days.

func (GoogleCloudAiplatformV1SchedulingPtrOutput) ToGoogleCloudAiplatformV1SchedulingPtrOutput 

func (o GoogleCloudAiplatformV1SchedulingPtrOutput) ToGoogleCloudAiplatformV1SchedulingPtrOutput() GoogleCloudAiplatformV1SchedulingPtrOutput

func (GoogleCloudAiplatformV1SchedulingPtrOutput) ToGoogleCloudAiplatformV1SchedulingPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SchedulingPtrOutput) ToGoogleCloudAiplatformV1SchedulingPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SchedulingPtrOutput

type GoogleCloudAiplatformV1SchedulingResponse 

type GoogleCloudAiplatformV1SchedulingResponse struct {
	// Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false.
	DisableRetries bool `pulumi:"disableRetries"`
	// Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
	RestartJobOnWorkerRestart bool `pulumi:"restartJobOnWorkerRestart"`
	// The maximum job running time. The default is 7 days.
	Timeout string `pulumi:"timeout"`
}

All parameters related to queuing and scheduling of custom jobs.

type GoogleCloudAiplatformV1SchedulingResponseOutput 

type GoogleCloudAiplatformV1SchedulingResponseOutput struct{ *pulumi.OutputState }

All parameters related to queuing and scheduling of custom jobs.

func (GoogleCloudAiplatformV1SchedulingResponseOutput) DisableRetries 

func (o GoogleCloudAiplatformV1SchedulingResponseOutput) DisableRetries() pulumi.BoolOutput

Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false.

func (GoogleCloudAiplatformV1SchedulingResponseOutput) ElementType 

func (GoogleCloudAiplatformV1SchedulingResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SchedulingResponseOutput) RestartJobOnWorkerRestart 

func (o GoogleCloudAiplatformV1SchedulingResponseOutput) RestartJobOnWorkerRestart() pulumi.BoolOutput

Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.

func (GoogleCloudAiplatformV1SchedulingResponseOutput) Timeout 

func (o GoogleCloudAiplatformV1SchedulingResponseOutput) Timeout() pulumi.StringOutput

The maximum job running time. The default is 7 days.

func (GoogleCloudAiplatformV1SchedulingResponseOutput) ToGoogleCloudAiplatformV1SchedulingResponseOutput 

func (o GoogleCloudAiplatformV1SchedulingResponseOutput) ToGoogleCloudAiplatformV1SchedulingResponseOutput() GoogleCloudAiplatformV1SchedulingResponseOutput

func (GoogleCloudAiplatformV1SchedulingResponseOutput) ToGoogleCloudAiplatformV1SchedulingResponseOutputWithContext 

func (o GoogleCloudAiplatformV1SchedulingResponseOutput) ToGoogleCloudAiplatformV1SchedulingResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SchedulingResponseOutput

type GoogleCloudAiplatformV1SmoothGradConfig 

type GoogleCloudAiplatformV1SmoothGradConfig struct {
	// This is similar to noise_sigma, but provides additional flexibility. A separate noise sigma can be provided for each feature, which is useful if their distributions are different. No noise is added to features that are not set. If this field is unset, noise_sigma will be used for all features.
	FeatureNoiseSigma *GoogleCloudAiplatformV1FeatureNoiseSigma `pulumi:"featureNoiseSigma"`
	// This is a single float value and will be used to add noise to all the features. Use this field when all features are normalized to have the same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where features are normalized to have 0-mean and 1-variance. Learn more about [normalization](https://developers.google.com/machine-learning/data-prep/transform/normalization). For best results the recommended value is about 10% - 20% of the standard deviation of the input feature. Refer to section 3.2 of the SmoothGrad paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1. If the distribution is different per feature, set feature_noise_sigma instead for each feature.
	NoiseSigma *float64 `pulumi:"noiseSigma"`
	// The number of gradient samples to use for approximation. The higher this number, the more accurate the gradient is, but the runtime complexity increases by this factor as well. Valid range of its value is [1, 50]. Defaults to 3.
	NoisySampleCount *int `pulumi:"noisySampleCount"`
}

Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf

type GoogleCloudAiplatformV1SmoothGradConfigArgs 

type GoogleCloudAiplatformV1SmoothGradConfigArgs struct {
	// This is similar to noise_sigma, but provides additional flexibility. A separate noise sigma can be provided for each feature, which is useful if their distributions are different. No noise is added to features that are not set. If this field is unset, noise_sigma will be used for all features.
	FeatureNoiseSigma GoogleCloudAiplatformV1FeatureNoiseSigmaPtrInput `pulumi:"featureNoiseSigma"`
	// This is a single float value and will be used to add noise to all the features. Use this field when all features are normalized to have the same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where features are normalized to have 0-mean and 1-variance. Learn more about [normalization](https://developers.google.com/machine-learning/data-prep/transform/normalization). For best results the recommended value is about 10% - 20% of the standard deviation of the input feature. Refer to section 3.2 of the SmoothGrad paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1. If the distribution is different per feature, set feature_noise_sigma instead for each feature.
	NoiseSigma pulumi.Float64PtrInput `pulumi:"noiseSigma"`
	// The number of gradient samples to use for approximation. The higher this number, the more accurate the gradient is, but the runtime complexity increases by this factor as well. Valid range of its value is [1, 50]. Defaults to 3.
	NoisySampleCount pulumi.IntPtrInput `pulumi:"noisySampleCount"`
}

Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf

func (GoogleCloudAiplatformV1SmoothGradConfigArgs) ElementType 

func (GoogleCloudAiplatformV1SmoothGradConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SmoothGradConfigArgs) ToGoogleCloudAiplatformV1SmoothGradConfigOutput 

func (i GoogleCloudAiplatformV1SmoothGradConfigArgs) ToGoogleCloudAiplatformV1SmoothGradConfigOutput() GoogleCloudAiplatformV1SmoothGradConfigOutput

func (GoogleCloudAiplatformV1SmoothGradConfigArgs) ToGoogleCloudAiplatformV1SmoothGradConfigOutputWithContext 

func (i GoogleCloudAiplatformV1SmoothGradConfigArgs) ToGoogleCloudAiplatformV1SmoothGradConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SmoothGradConfigOutput

func (GoogleCloudAiplatformV1SmoothGradConfigArgs) ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutput 

func (i GoogleCloudAiplatformV1SmoothGradConfigArgs) ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutput() GoogleCloudAiplatformV1SmoothGradConfigPtrOutput

func (GoogleCloudAiplatformV1SmoothGradConfigArgs) ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1SmoothGradConfigArgs) ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SmoothGradConfigPtrOutput

type GoogleCloudAiplatformV1SmoothGradConfigInput 

type GoogleCloudAiplatformV1SmoothGradConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SmoothGradConfigOutput() GoogleCloudAiplatformV1SmoothGradConfigOutput
	ToGoogleCloudAiplatformV1SmoothGradConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1SmoothGradConfigOutput
}

GoogleCloudAiplatformV1SmoothGradConfigInput is an input type that accepts GoogleCloudAiplatformV1SmoothGradConfigArgs and GoogleCloudAiplatformV1SmoothGradConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SmoothGradConfigInput` via: 

GoogleCloudAiplatformV1SmoothGradConfigArgs{...}

type GoogleCloudAiplatformV1SmoothGradConfigOutput 

type GoogleCloudAiplatformV1SmoothGradConfigOutput struct{ *pulumi.OutputState }

Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf

func (GoogleCloudAiplatformV1SmoothGradConfigOutput) ElementType 

func (GoogleCloudAiplatformV1SmoothGradConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SmoothGradConfigOutput) FeatureNoiseSigma 

func (o GoogleCloudAiplatformV1SmoothGradConfigOutput) FeatureNoiseSigma() GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput

This is similar to noise_sigma, but provides additional flexibility. A separate noise sigma can be provided for each feature, which is useful if their distributions are different. No noise is added to features that are not set. If this field is unset, noise_sigma will be used for all features.

func (GoogleCloudAiplatformV1SmoothGradConfigOutput) NoiseSigma 

func (o GoogleCloudAiplatformV1SmoothGradConfigOutput) NoiseSigma() pulumi.Float64PtrOutput

This is a single float value and will be used to add noise to all the features. Use this field when all features are normalized to have the same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where features are normalized to have 0-mean and 1-variance. Learn more about [normalization](https://developers.google.com/machine-learning/data-prep/transform/normalization). For best results the recommended value is about 10% - 20% of the standard deviation of the input feature. Refer to section 3.2 of the SmoothGrad paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1. If the distribution is different per feature, set feature_noise_sigma instead for each feature.

func (GoogleCloudAiplatformV1SmoothGradConfigOutput) NoisySampleCount 

func (o GoogleCloudAiplatformV1SmoothGradConfigOutput) NoisySampleCount() pulumi.IntPtrOutput

The number of gradient samples to use for approximation. The higher this number, the more accurate the gradient is, but the runtime complexity increases by this factor as well. Valid range of its value is [1, 50]. Defaults to 3.

func (GoogleCloudAiplatformV1SmoothGradConfigOutput) ToGoogleCloudAiplatformV1SmoothGradConfigOutput 

func (o GoogleCloudAiplatformV1SmoothGradConfigOutput) ToGoogleCloudAiplatformV1SmoothGradConfigOutput() GoogleCloudAiplatformV1SmoothGradConfigOutput

func (GoogleCloudAiplatformV1SmoothGradConfigOutput) ToGoogleCloudAiplatformV1SmoothGradConfigOutputWithContext 

func (o GoogleCloudAiplatformV1SmoothGradConfigOutput) ToGoogleCloudAiplatformV1SmoothGradConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SmoothGradConfigOutput

func (GoogleCloudAiplatformV1SmoothGradConfigOutput) ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutput 

func (o GoogleCloudAiplatformV1SmoothGradConfigOutput) ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutput() GoogleCloudAiplatformV1SmoothGradConfigPtrOutput

func (GoogleCloudAiplatformV1SmoothGradConfigOutput) ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SmoothGradConfigOutput) ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SmoothGradConfigPtrOutput

type GoogleCloudAiplatformV1SmoothGradConfigPtrInput 

type GoogleCloudAiplatformV1SmoothGradConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutput() GoogleCloudAiplatformV1SmoothGradConfigPtrOutput
	ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1SmoothGradConfigPtrOutput
}

GoogleCloudAiplatformV1SmoothGradConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1SmoothGradConfigArgs, GoogleCloudAiplatformV1SmoothGradConfigPtr and GoogleCloudAiplatformV1SmoothGradConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1SmoothGradConfigPtrInput` via: 

        GoogleCloudAiplatformV1SmoothGradConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1SmoothGradConfigPtr 

func GoogleCloudAiplatformV1SmoothGradConfigPtr(v *GoogleCloudAiplatformV1SmoothGradConfigArgs) GoogleCloudAiplatformV1SmoothGradConfigPtrInput

type GoogleCloudAiplatformV1SmoothGradConfigPtrOutput 

type GoogleCloudAiplatformV1SmoothGradConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) Elem() GoogleCloudAiplatformV1SmoothGradConfigOutput

func (GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) FeatureNoiseSigma 

func (o GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) FeatureNoiseSigma() GoogleCloudAiplatformV1FeatureNoiseSigmaPtrOutput

This is similar to noise_sigma, but provides additional flexibility. A separate noise sigma can be provided for each feature, which is useful if their distributions are different. No noise is added to features that are not set. If this field is unset, noise_sigma will be used for all features.

func (GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) NoiseSigma 

func (o GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) NoiseSigma() pulumi.Float64PtrOutput

This is a single float value and will be used to add noise to all the features. Use this field when all features are normalized to have the same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where features are normalized to have 0-mean and 1-variance. Learn more about [normalization](https://developers.google.com/machine-learning/data-prep/transform/normalization). For best results the recommended value is about 10% - 20% of the standard deviation of the input feature. Refer to section 3.2 of the SmoothGrad paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1. If the distribution is different per feature, set feature_noise_sigma instead for each feature.

func (GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) NoisySampleCount 

func (o GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) NoisySampleCount() pulumi.IntPtrOutput

The number of gradient samples to use for approximation. The higher this number, the more accurate the gradient is, but the runtime complexity increases by this factor as well. Valid range of its value is [1, 50]. Defaults to 3.

func (GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutput 

func (o GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutput() GoogleCloudAiplatformV1SmoothGradConfigPtrOutput

func (GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1SmoothGradConfigPtrOutput) ToGoogleCloudAiplatformV1SmoothGradConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SmoothGradConfigPtrOutput

type GoogleCloudAiplatformV1SmoothGradConfigResponse 

type GoogleCloudAiplatformV1SmoothGradConfigResponse struct {
	// This is similar to noise_sigma, but provides additional flexibility. A separate noise sigma can be provided for each feature, which is useful if their distributions are different. No noise is added to features that are not set. If this field is unset, noise_sigma will be used for all features.
	FeatureNoiseSigma GoogleCloudAiplatformV1FeatureNoiseSigmaResponse `pulumi:"featureNoiseSigma"`
	// This is a single float value and will be used to add noise to all the features. Use this field when all features are normalized to have the same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where features are normalized to have 0-mean and 1-variance. Learn more about [normalization](https://developers.google.com/machine-learning/data-prep/transform/normalization). For best results the recommended value is about 10% - 20% of the standard deviation of the input feature. Refer to section 3.2 of the SmoothGrad paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1. If the distribution is different per feature, set feature_noise_sigma instead for each feature.
	NoiseSigma float64 `pulumi:"noiseSigma"`
	// The number of gradient samples to use for approximation. The higher this number, the more accurate the gradient is, but the runtime complexity increases by this factor as well. Valid range of its value is [1, 50]. Defaults to 3.
	NoisySampleCount int `pulumi:"noisySampleCount"`
}

Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf

type GoogleCloudAiplatformV1SmoothGradConfigResponseOutput 

type GoogleCloudAiplatformV1SmoothGradConfigResponseOutput struct{ *pulumi.OutputState }

Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf

func (GoogleCloudAiplatformV1SmoothGradConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1SmoothGradConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1SmoothGradConfigResponseOutput) FeatureNoiseSigma 

func (o GoogleCloudAiplatformV1SmoothGradConfigResponseOutput) FeatureNoiseSigma() GoogleCloudAiplatformV1FeatureNoiseSigmaResponseOutput

This is similar to noise_sigma, but provides additional flexibility. A separate noise sigma can be provided for each feature, which is useful if their distributions are different. No noise is added to features that are not set. If this field is unset, noise_sigma will be used for all features.

func (GoogleCloudAiplatformV1SmoothGradConfigResponseOutput) NoiseSigma 

func (o GoogleCloudAiplatformV1SmoothGradConfigResponseOutput) NoiseSigma() pulumi.Float64Output

This is a single float value and will be used to add noise to all the features. Use this field when all features are normalized to have the same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where features are normalized to have 0-mean and 1-variance. Learn more about [normalization](https://developers.google.com/machine-learning/data-prep/transform/normalization). For best results the recommended value is about 10% - 20% of the standard deviation of the input feature. Refer to section 3.2 of the SmoothGrad paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1. If the distribution is different per feature, set feature_noise_sigma instead for each feature.

func (GoogleCloudAiplatformV1SmoothGradConfigResponseOutput) NoisySampleCount 

func (o GoogleCloudAiplatformV1SmoothGradConfigResponseOutput) NoisySampleCount() pulumi.IntOutput

The number of gradient samples to use for approximation. The higher this number, the more accurate the gradient is, but the runtime complexity increases by this factor as well. Valid range of its value is [1, 50]. Defaults to 3.

func (GoogleCloudAiplatformV1SmoothGradConfigResponseOutput) ToGoogleCloudAiplatformV1SmoothGradConfigResponseOutput 

func (o GoogleCloudAiplatformV1SmoothGradConfigResponseOutput) ToGoogleCloudAiplatformV1SmoothGradConfigResponseOutput() GoogleCloudAiplatformV1SmoothGradConfigResponseOutput

func (GoogleCloudAiplatformV1SmoothGradConfigResponseOutput) ToGoogleCloudAiplatformV1SmoothGradConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1SmoothGradConfigResponseOutput) ToGoogleCloudAiplatformV1SmoothGradConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1SmoothGradConfigResponseOutput

type GoogleCloudAiplatformV1StratifiedSplit 

type GoogleCloudAiplatformV1StratifiedSplit struct {
	// The key is a name of one of the Dataset's data columns. The key provided must be for a categorical column.
	Key string `pulumi:"key"`
	// The fraction of the input data that is to be used to evaluate the Model.
	TestFraction *float64 `pulumi:"testFraction"`
	// The fraction of the input data that is to be used to train the Model.
	TrainingFraction *float64 `pulumi:"trainingFraction"`
	// The fraction of the input data that is to be used to validate the Model.
	ValidationFraction *float64 `pulumi:"validationFraction"`
}

Assigns input data to the training, validation, and test sets so that the distribution of values found in the categorical column (as specified by the `key` field) is mirrored within each split. The fraction values determine the relative sizes of the splits. For example, if the specified column has three values, with 50% of the rows having value "A", 25% value "B", and 25% value "C", and the split fractions are specified as 80/10/10, then the training set will constitute 80% of the training data, with about 50% of the training set rows having the value "A" for the specified column, about 25% having the value "B", and about 25% having the value "C". Only the top 500 occurring values are used; any values not in the top 500 values are randomly assigned to a split. If less than three rows contain a specific value, those rows are randomly assigned. Supported only for tabular Datasets.

type GoogleCloudAiplatformV1StratifiedSplitArgs 

type GoogleCloudAiplatformV1StratifiedSplitArgs struct {
	// The key is a name of one of the Dataset's data columns. The key provided must be for a categorical column.
	Key pulumi.StringInput `pulumi:"key"`
	// The fraction of the input data that is to be used to evaluate the Model.
	TestFraction pulumi.Float64PtrInput `pulumi:"testFraction"`
	// The fraction of the input data that is to be used to train the Model.
	TrainingFraction pulumi.Float64PtrInput `pulumi:"trainingFraction"`
	// The fraction of the input data that is to be used to validate the Model.
	ValidationFraction pulumi.Float64PtrInput `pulumi:"validationFraction"`
}

Assigns input data to the training, validation, and test sets so that the distribution of values found in the categorical column (as specified by the `key` field) is mirrored within each split. The fraction values determine the relative sizes of the splits. For example, if the specified column has three values, with 50% of the rows having value "A", 25% value "B", and 25% value "C", and the split fractions are specified as 80/10/10, then the training set will constitute 80% of the training data, with about 50% of the training set rows having the value "A" for the specified column, about 25% having the value "B", and about 25% having the value "C". Only the top 500 occurring values are used; any values not in the top 500 values are randomly assigned to a split. If less than three rows contain a specific value, those rows are randomly assigned. Supported only for tabular Datasets.

func (GoogleCloudAiplatformV1StratifiedSplitArgs) ElementType 

func (GoogleCloudAiplatformV1StratifiedSplitArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StratifiedSplitArgs) ToGoogleCloudAiplatformV1StratifiedSplitOutput 

func (i GoogleCloudAiplatformV1StratifiedSplitArgs) ToGoogleCloudAiplatformV1StratifiedSplitOutput() GoogleCloudAiplatformV1StratifiedSplitOutput

func (GoogleCloudAiplatformV1StratifiedSplitArgs) ToGoogleCloudAiplatformV1StratifiedSplitOutputWithContext 

func (i GoogleCloudAiplatformV1StratifiedSplitArgs) ToGoogleCloudAiplatformV1StratifiedSplitOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StratifiedSplitOutput

func (GoogleCloudAiplatformV1StratifiedSplitArgs) ToGoogleCloudAiplatformV1StratifiedSplitPtrOutput 

func (i GoogleCloudAiplatformV1StratifiedSplitArgs) ToGoogleCloudAiplatformV1StratifiedSplitPtrOutput() GoogleCloudAiplatformV1StratifiedSplitPtrOutput

func (GoogleCloudAiplatformV1StratifiedSplitArgs) ToGoogleCloudAiplatformV1StratifiedSplitPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StratifiedSplitArgs) ToGoogleCloudAiplatformV1StratifiedSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StratifiedSplitPtrOutput

type GoogleCloudAiplatformV1StratifiedSplitInput 

type GoogleCloudAiplatformV1StratifiedSplitInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StratifiedSplitOutput() GoogleCloudAiplatformV1StratifiedSplitOutput
	ToGoogleCloudAiplatformV1StratifiedSplitOutputWithContext(context.Context) GoogleCloudAiplatformV1StratifiedSplitOutput
}

GoogleCloudAiplatformV1StratifiedSplitInput is an input type that accepts GoogleCloudAiplatformV1StratifiedSplitArgs and GoogleCloudAiplatformV1StratifiedSplitOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StratifiedSplitInput` via: 

GoogleCloudAiplatformV1StratifiedSplitArgs{...}

type GoogleCloudAiplatformV1StratifiedSplitOutput 

type GoogleCloudAiplatformV1StratifiedSplitOutput struct{ *pulumi.OutputState }

Assigns input data to the training, validation, and test sets so that the distribution of values found in the categorical column (as specified by the `key` field) is mirrored within each split. The fraction values determine the relative sizes of the splits. For example, if the specified column has three values, with 50% of the rows having value "A", 25% value "B", and 25% value "C", and the split fractions are specified as 80/10/10, then the training set will constitute 80% of the training data, with about 50% of the training set rows having the value "A" for the specified column, about 25% having the value "B", and about 25% having the value "C". Only the top 500 occurring values are used; any values not in the top 500 values are randomly assigned to a split. If less than three rows contain a specific value, those rows are randomly assigned. Supported only for tabular Datasets.

func (GoogleCloudAiplatformV1StratifiedSplitOutput) ElementType 

func (GoogleCloudAiplatformV1StratifiedSplitOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StratifiedSplitOutput) Key 

func (o GoogleCloudAiplatformV1StratifiedSplitOutput) Key() pulumi.StringOutput

The key is a name of one of the Dataset's data columns. The key provided must be for a categorical column.

func (GoogleCloudAiplatformV1StratifiedSplitOutput) TestFraction 

func (o GoogleCloudAiplatformV1StratifiedSplitOutput) TestFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to evaluate the Model.

func (GoogleCloudAiplatformV1StratifiedSplitOutput) ToGoogleCloudAiplatformV1StratifiedSplitOutput 

func (o GoogleCloudAiplatformV1StratifiedSplitOutput) ToGoogleCloudAiplatformV1StratifiedSplitOutput() GoogleCloudAiplatformV1StratifiedSplitOutput

func (GoogleCloudAiplatformV1StratifiedSplitOutput) ToGoogleCloudAiplatformV1StratifiedSplitOutputWithContext 

func (o GoogleCloudAiplatformV1StratifiedSplitOutput) ToGoogleCloudAiplatformV1StratifiedSplitOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StratifiedSplitOutput

func (GoogleCloudAiplatformV1StratifiedSplitOutput) ToGoogleCloudAiplatformV1StratifiedSplitPtrOutput 

func (o GoogleCloudAiplatformV1StratifiedSplitOutput) ToGoogleCloudAiplatformV1StratifiedSplitPtrOutput() GoogleCloudAiplatformV1StratifiedSplitPtrOutput

func (GoogleCloudAiplatformV1StratifiedSplitOutput) ToGoogleCloudAiplatformV1StratifiedSplitPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StratifiedSplitOutput) ToGoogleCloudAiplatformV1StratifiedSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StratifiedSplitPtrOutput

func (GoogleCloudAiplatformV1StratifiedSplitOutput) TrainingFraction 

func (o GoogleCloudAiplatformV1StratifiedSplitOutput) TrainingFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to train the Model.

func (GoogleCloudAiplatformV1StratifiedSplitOutput) ValidationFraction 

func (o GoogleCloudAiplatformV1StratifiedSplitOutput) ValidationFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to validate the Model.

type GoogleCloudAiplatformV1StratifiedSplitPtrInput 

type GoogleCloudAiplatformV1StratifiedSplitPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StratifiedSplitPtrOutput() GoogleCloudAiplatformV1StratifiedSplitPtrOutput
	ToGoogleCloudAiplatformV1StratifiedSplitPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StratifiedSplitPtrOutput
}

GoogleCloudAiplatformV1StratifiedSplitPtrInput is an input type that accepts GoogleCloudAiplatformV1StratifiedSplitArgs, GoogleCloudAiplatformV1StratifiedSplitPtr and GoogleCloudAiplatformV1StratifiedSplitPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StratifiedSplitPtrInput` via: 

        GoogleCloudAiplatformV1StratifiedSplitArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StratifiedSplitPtr 

func GoogleCloudAiplatformV1StratifiedSplitPtr(v *GoogleCloudAiplatformV1StratifiedSplitArgs) GoogleCloudAiplatformV1StratifiedSplitPtrInput

type GoogleCloudAiplatformV1StratifiedSplitPtrOutput 

type GoogleCloudAiplatformV1StratifiedSplitPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StratifiedSplitPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StratifiedSplitPtrOutput) Elem() GoogleCloudAiplatformV1StratifiedSplitOutput

func (GoogleCloudAiplatformV1StratifiedSplitPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StratifiedSplitPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StratifiedSplitPtrOutput) Key 

func (o GoogleCloudAiplatformV1StratifiedSplitPtrOutput) Key() pulumi.StringPtrOutput

The key is a name of one of the Dataset's data columns. The key provided must be for a categorical column.

func (GoogleCloudAiplatformV1StratifiedSplitPtrOutput) TestFraction 

func (o GoogleCloudAiplatformV1StratifiedSplitPtrOutput) TestFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to evaluate the Model.

func (GoogleCloudAiplatformV1StratifiedSplitPtrOutput) ToGoogleCloudAiplatformV1StratifiedSplitPtrOutput 

func (o GoogleCloudAiplatformV1StratifiedSplitPtrOutput) ToGoogleCloudAiplatformV1StratifiedSplitPtrOutput() GoogleCloudAiplatformV1StratifiedSplitPtrOutput

func (GoogleCloudAiplatformV1StratifiedSplitPtrOutput) ToGoogleCloudAiplatformV1StratifiedSplitPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StratifiedSplitPtrOutput) ToGoogleCloudAiplatformV1StratifiedSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StratifiedSplitPtrOutput

func (GoogleCloudAiplatformV1StratifiedSplitPtrOutput) TrainingFraction 

func (o GoogleCloudAiplatformV1StratifiedSplitPtrOutput) TrainingFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to train the Model.

func (GoogleCloudAiplatformV1StratifiedSplitPtrOutput) ValidationFraction 

func (o GoogleCloudAiplatformV1StratifiedSplitPtrOutput) ValidationFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to validate the Model.

type GoogleCloudAiplatformV1StratifiedSplitResponse 

type GoogleCloudAiplatformV1StratifiedSplitResponse struct {
	// The key is a name of one of the Dataset's data columns. The key provided must be for a categorical column.
	Key string `pulumi:"key"`
	// The fraction of the input data that is to be used to evaluate the Model.
	TestFraction float64 `pulumi:"testFraction"`
	// The fraction of the input data that is to be used to train the Model.
	TrainingFraction float64 `pulumi:"trainingFraction"`
	// The fraction of the input data that is to be used to validate the Model.
	ValidationFraction float64 `pulumi:"validationFraction"`
}

Assigns input data to the training, validation, and test sets so that the distribution of values found in the categorical column (as specified by the `key` field) is mirrored within each split. The fraction values determine the relative sizes of the splits. For example, if the specified column has three values, with 50% of the rows having value "A", 25% value "B", and 25% value "C", and the split fractions are specified as 80/10/10, then the training set will constitute 80% of the training data, with about 50% of the training set rows having the value "A" for the specified column, about 25% having the value "B", and about 25% having the value "C". Only the top 500 occurring values are used; any values not in the top 500 values are randomly assigned to a split. If less than three rows contain a specific value, those rows are randomly assigned. Supported only for tabular Datasets.

type GoogleCloudAiplatformV1StratifiedSplitResponseOutput 

type GoogleCloudAiplatformV1StratifiedSplitResponseOutput struct{ *pulumi.OutputState }

Assigns input data to the training, validation, and test sets so that the distribution of values found in the categorical column (as specified by the `key` field) is mirrored within each split. The fraction values determine the relative sizes of the splits. For example, if the specified column has three values, with 50% of the rows having value "A", 25% value "B", and 25% value "C", and the split fractions are specified as 80/10/10, then the training set will constitute 80% of the training data, with about 50% of the training set rows having the value "A" for the specified column, about 25% having the value "B", and about 25% having the value "C". Only the top 500 occurring values are used; any values not in the top 500 values are randomly assigned to a split. If less than three rows contain a specific value, those rows are randomly assigned. Supported only for tabular Datasets.

func (GoogleCloudAiplatformV1StratifiedSplitResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StratifiedSplitResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StratifiedSplitResponseOutput) Key 

func (o GoogleCloudAiplatformV1StratifiedSplitResponseOutput) Key() pulumi.StringOutput

The key is a name of one of the Dataset's data columns. The key provided must be for a categorical column.

func (GoogleCloudAiplatformV1StratifiedSplitResponseOutput) TestFraction 

func (o GoogleCloudAiplatformV1StratifiedSplitResponseOutput) TestFraction() pulumi.Float64Output

The fraction of the input data that is to be used to evaluate the Model.

func (GoogleCloudAiplatformV1StratifiedSplitResponseOutput) ToGoogleCloudAiplatformV1StratifiedSplitResponseOutput 

func (o GoogleCloudAiplatformV1StratifiedSplitResponseOutput) ToGoogleCloudAiplatformV1StratifiedSplitResponseOutput() GoogleCloudAiplatformV1StratifiedSplitResponseOutput

func (GoogleCloudAiplatformV1StratifiedSplitResponseOutput) ToGoogleCloudAiplatformV1StratifiedSplitResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StratifiedSplitResponseOutput) ToGoogleCloudAiplatformV1StratifiedSplitResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StratifiedSplitResponseOutput

func (GoogleCloudAiplatformV1StratifiedSplitResponseOutput) TrainingFraction 

func (o GoogleCloudAiplatformV1StratifiedSplitResponseOutput) TrainingFraction() pulumi.Float64Output

The fraction of the input data that is to be used to train the Model.

func (GoogleCloudAiplatformV1StratifiedSplitResponseOutput) ValidationFraction 

func (o GoogleCloudAiplatformV1StratifiedSplitResponseOutput) ValidationFraction() pulumi.Float64Output

The fraction of the input data that is to be used to validate the Model.

type GoogleCloudAiplatformV1StudySpec 

type GoogleCloudAiplatformV1StudySpec struct {
	// The search algorithm specified for the Study.
	Algorithm *GoogleCloudAiplatformV1StudySpecAlgorithm `pulumi:"algorithm"`
	// The automated early stopping spec using convex stopping rule.
	ConvexAutomatedStoppingSpec *GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpec `pulumi:"convexAutomatedStoppingSpec"`
	// The automated early stopping spec using decay curve rule.
	DecayCurveStoppingSpec *GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpec `pulumi:"decayCurveStoppingSpec"`
	// Describe which measurement selection type will be used
	MeasurementSelectionType *GoogleCloudAiplatformV1StudySpecMeasurementSelectionType `pulumi:"measurementSelectionType"`
	// The automated early stopping spec using median rule.
	MedianAutomatedStoppingSpec *GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpec `pulumi:"medianAutomatedStoppingSpec"`
	// Metric specs for the Study.
	Metrics []GoogleCloudAiplatformV1StudySpecMetricSpec `pulumi:"metrics"`
	// The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	ObservationNoise *GoogleCloudAiplatformV1StudySpecObservationNoise `pulumi:"observationNoise"`
	// The set of parameters to tune.
	Parameters []GoogleCloudAiplatformV1StudySpecParameterSpec `pulumi:"parameters"`
	// Conditions for automated stopping of a Study. Enable automated stopping by configuring at least one condition.
	StudyStoppingConfig *GoogleCloudAiplatformV1StudySpecStudyStoppingConfig `pulumi:"studyStoppingConfig"`
}

Represents specification of a Study.

type GoogleCloudAiplatformV1StudySpecAlgorithm 

type GoogleCloudAiplatformV1StudySpecAlgorithm string

The search algorithm specified for the Study.

func (GoogleCloudAiplatformV1StudySpecAlgorithm) ElementType 

func (GoogleCloudAiplatformV1StudySpecAlgorithm) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecAlgorithm) ToGoogleCloudAiplatformV1StudySpecAlgorithmOutput 

func (e GoogleCloudAiplatformV1StudySpecAlgorithm) ToGoogleCloudAiplatformV1StudySpecAlgorithmOutput() GoogleCloudAiplatformV1StudySpecAlgorithmOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithm) ToGoogleCloudAiplatformV1StudySpecAlgorithmOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecAlgorithm) ToGoogleCloudAiplatformV1StudySpecAlgorithmOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecAlgorithmOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithm) ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput 

func (e GoogleCloudAiplatformV1StudySpecAlgorithm) ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput() GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithm) ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecAlgorithm) ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithm) ToStringOutput 

func (e GoogleCloudAiplatformV1StudySpecAlgorithm) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithm) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecAlgorithm) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithm) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1StudySpecAlgorithm) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithm) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecAlgorithm) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecAlgorithmInput 

type GoogleCloudAiplatformV1StudySpecAlgorithmInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecAlgorithmOutput() GoogleCloudAiplatformV1StudySpecAlgorithmOutput
	ToGoogleCloudAiplatformV1StudySpecAlgorithmOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecAlgorithmOutput
}

GoogleCloudAiplatformV1StudySpecAlgorithmInput is an input type that accepts GoogleCloudAiplatformV1StudySpecAlgorithmArgs and GoogleCloudAiplatformV1StudySpecAlgorithmOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecAlgorithmInput` via: 

GoogleCloudAiplatformV1StudySpecAlgorithmArgs{...}

type GoogleCloudAiplatformV1StudySpecAlgorithmOutput 

type GoogleCloudAiplatformV1StudySpecAlgorithmOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToGoogleCloudAiplatformV1StudySpecAlgorithmOutput 

func (o GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToGoogleCloudAiplatformV1StudySpecAlgorithmOutput() GoogleCloudAiplatformV1StudySpecAlgorithmOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToGoogleCloudAiplatformV1StudySpecAlgorithmOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToGoogleCloudAiplatformV1StudySpecAlgorithmOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecAlgorithmOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput() GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecAlgorithmOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecAlgorithmPtrInput 

type GoogleCloudAiplatformV1StudySpecAlgorithmPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput() GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput
	ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput
}

func GoogleCloudAiplatformV1StudySpecAlgorithmPtr 

func GoogleCloudAiplatformV1StudySpecAlgorithmPtr(v string) GoogleCloudAiplatformV1StudySpecAlgorithmPtrInput

type GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput 

type GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecAlgorithmOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput) ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput) ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput() GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput) ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput) ToGoogleCloudAiplatformV1StudySpecAlgorithmPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecArgs 

type GoogleCloudAiplatformV1StudySpecArgs struct {
	// The search algorithm specified for the Study.
	Algorithm GoogleCloudAiplatformV1StudySpecAlgorithmPtrInput `pulumi:"algorithm"`
	// The automated early stopping spec using convex stopping rule.
	ConvexAutomatedStoppingSpec GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrInput `pulumi:"convexAutomatedStoppingSpec"`
	// The automated early stopping spec using decay curve rule.
	DecayCurveStoppingSpec GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrInput `pulumi:"decayCurveStoppingSpec"`
	// Describe which measurement selection type will be used
	MeasurementSelectionType GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrInput `pulumi:"measurementSelectionType"`
	// The automated early stopping spec using median rule.
	MedianAutomatedStoppingSpec GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrInput `pulumi:"medianAutomatedStoppingSpec"`
	// Metric specs for the Study.
	Metrics GoogleCloudAiplatformV1StudySpecMetricSpecArrayInput `pulumi:"metrics"`
	// The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	ObservationNoise GoogleCloudAiplatformV1StudySpecObservationNoisePtrInput `pulumi:"observationNoise"`
	// The set of parameters to tune.
	Parameters GoogleCloudAiplatformV1StudySpecParameterSpecArrayInput `pulumi:"parameters"`
	// Conditions for automated stopping of a Study. Enable automated stopping by configuring at least one condition.
	StudyStoppingConfig GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrInput `pulumi:"studyStoppingConfig"`
}

Represents specification of a Study.

func (GoogleCloudAiplatformV1StudySpecArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecArgs) ToGoogleCloudAiplatformV1StudySpecOutput 

func (i GoogleCloudAiplatformV1StudySpecArgs) ToGoogleCloudAiplatformV1StudySpecOutput() GoogleCloudAiplatformV1StudySpecOutput

func (GoogleCloudAiplatformV1StudySpecArgs) ToGoogleCloudAiplatformV1StudySpecOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecArgs) ToGoogleCloudAiplatformV1StudySpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecOutput

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpec 

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpec struct {
	// The hyper-parameter name used in the tuning job that stands for learning rate. Leave it blank if learning rate is not in a parameter in tuning. The learning_rate is used to estimate the objective value of the ongoing trial.
	LearningRateParameterName *string `pulumi:"learningRateParameterName"`
	// Steps used in predicting the final objective for early stopped trials. In general, it's set to be the same as the defined steps in training / tuning. If not defined, it will learn it from the completed trials. When use_steps is false, this field is set to the maximum elapsed seconds.
	MaxStepCount *string `pulumi:"maxStepCount"`
	// The minimal number of measurements in a Trial. Early-stopping checks will not trigger if less than min_measurement_count+1 completed trials or pending trials with less than min_measurement_count measurements. If not defined, the default value is 5.
	MinMeasurementCount *string `pulumi:"minMeasurementCount"`
	// Minimum number of steps for a trial to complete. Trials which do not have a measurement with step_count > min_step_count won't be considered for early stopping. It's ok to set it to 0, and a trial can be early stopped at any stage. By default, min_step_count is set to be one-tenth of the max_step_count. When use_elapsed_duration is true, this field is set to the minimum elapsed seconds.
	MinStepCount *string `pulumi:"minStepCount"`
	// ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model. When this flag is set to True, all stopped trials from the beginning are potentially updated in terms of their `final_measurement`. Also, note that the training logic of autoregressive models is different in this case. Enabling this option has shown better results and this may be the default option in the future.
	UpdateAllStoppedTrials *bool `pulumi:"updateAllStoppedTrials"`
	// This bool determines whether or not the rule is applied based on elapsed_secs or steps. If use_elapsed_duration==false, the early stopping decision is made according to the predicted objective values according to the target steps. If use_elapsed_duration==true, elapsed_secs is used instead of steps. Also, in this case, the parameters max_num_steps and min_num_steps are overloaded to contain max_elapsed_seconds and min_elapsed_seconds.
	UseElapsedDuration *bool `pulumi:"useElapsedDuration"`
}

Configuration for ConvexAutomatedStoppingSpec. When there are enough completed trials (configured by min_measurement_count), for pending trials with enough measurements and steps, the policy first computes an overestimate of the objective value at max_num_steps according to the slope of the incomplete objective value curve. No prediction can be made if the curve is completely flat. If the overestimation is worse than the best objective value of the completed trials, this pending trial will be early-stopped, but a last measurement will be added to the pending trial with max_num_steps and predicted objective value from the autoregression model.

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs 

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs struct {
	// The hyper-parameter name used in the tuning job that stands for learning rate. Leave it blank if learning rate is not in a parameter in tuning. The learning_rate is used to estimate the objective value of the ongoing trial.
	LearningRateParameterName pulumi.StringPtrInput `pulumi:"learningRateParameterName"`
	// Steps used in predicting the final objective for early stopped trials. In general, it's set to be the same as the defined steps in training / tuning. If not defined, it will learn it from the completed trials. When use_steps is false, this field is set to the maximum elapsed seconds.
	MaxStepCount pulumi.StringPtrInput `pulumi:"maxStepCount"`
	// The minimal number of measurements in a Trial. Early-stopping checks will not trigger if less than min_measurement_count+1 completed trials or pending trials with less than min_measurement_count measurements. If not defined, the default value is 5.
	MinMeasurementCount pulumi.StringPtrInput `pulumi:"minMeasurementCount"`
	// Minimum number of steps for a trial to complete. Trials which do not have a measurement with step_count > min_step_count won't be considered for early stopping. It's ok to set it to 0, and a trial can be early stopped at any stage. By default, min_step_count is set to be one-tenth of the max_step_count. When use_elapsed_duration is true, this field is set to the minimum elapsed seconds.
	MinStepCount pulumi.StringPtrInput `pulumi:"minStepCount"`
	// ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model. When this flag is set to True, all stopped trials from the beginning are potentially updated in terms of their `final_measurement`. Also, note that the training logic of autoregressive models is different in this case. Enabling this option has shown better results and this may be the default option in the future.
	UpdateAllStoppedTrials pulumi.BoolPtrInput `pulumi:"updateAllStoppedTrials"`
	// This bool determines whether or not the rule is applied based on elapsed_secs or steps. If use_elapsed_duration==false, the early stopping decision is made according to the predicted objective values according to the target steps. If use_elapsed_duration==true, elapsed_secs is used instead of steps. Also, in this case, the parameters max_num_steps and min_num_steps are overloaded to contain max_elapsed_seconds and min_elapsed_seconds.
	UseElapsedDuration pulumi.BoolPtrInput `pulumi:"useElapsedDuration"`
}

Configuration for ConvexAutomatedStoppingSpec. When there are enough completed trials (configured by min_measurement_count), for pending trials with enough measurements and steps, the policy first computes an overestimate of the objective value at max_num_steps according to the slope of the incomplete objective value curve. No prediction can be made if the curve is completely flat. If the overestimation is worse than the best objective value of the completed trials, this pending trial will be early-stopped, but a last measurement will be added to the pending trial with max_num_steps and predicted objective value from the autoregression model.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput 

func (i GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput() GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput 

func (i GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput() GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecInput 

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput() GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput
	ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput
}

GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecInput is an input type that accepts GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs and GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecInput` via: 

GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs{...}

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput 

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput struct{ *pulumi.OutputState }

Configuration for ConvexAutomatedStoppingSpec. When there are enough completed trials (configured by min_measurement_count), for pending trials with enough measurements and steps, the policy first computes an overestimate of the objective value at max_num_steps according to the slope of the incomplete objective value curve. No prediction can be made if the curve is completely flat. If the overestimation is worse than the best objective value of the completed trials, this pending trial will be early-stopped, but a last measurement will be added to the pending trial with max_num_steps and predicted objective value from the autoregression model.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) LearningRateParameterName 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) LearningRateParameterName() pulumi.StringPtrOutput

The hyper-parameter name used in the tuning job that stands for learning rate. Leave it blank if learning rate is not in a parameter in tuning. The learning_rate is used to estimate the objective value of the ongoing trial.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) MaxStepCount 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) MaxStepCount() pulumi.StringPtrOutput

Steps used in predicting the final objective for early stopped trials. In general, it's set to be the same as the defined steps in training / tuning. If not defined, it will learn it from the completed trials. When use_steps is false, this field is set to the maximum elapsed seconds.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) MinMeasurementCount 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) MinMeasurementCount() pulumi.StringPtrOutput

The minimal number of measurements in a Trial. Early-stopping checks will not trigger if less than min_measurement_count+1 completed trials or pending trials with less than min_measurement_count measurements. If not defined, the default value is 5.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) MinStepCount 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) MinStepCount() pulumi.StringPtrOutput

Minimum number of steps for a trial to complete. Trials which do not have a measurement with step_count > min_step_count won't be considered for early stopping. It's ok to set it to 0, and a trial can be early stopped at any stage. By default, min_step_count is set to be one-tenth of the max_step_count. When use_elapsed_duration is true, this field is set to the minimum elapsed seconds.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput() GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput() GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) UpdateAllStoppedTrials 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) UpdateAllStoppedTrials() pulumi.BoolPtrOutput

ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model. When this flag is set to True, all stopped trials from the beginning are potentially updated in terms of their `final_measurement`. Also, note that the training logic of autoregressive models is different in this case. Enabling this option has shown better results and this may be the default option in the future.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) UseElapsedDuration 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput) UseElapsedDuration() pulumi.BoolPtrOutput

This bool determines whether or not the rule is applied based on elapsed_secs or steps. If use_elapsed_duration==false, the early stopping decision is made according to the predicted objective values according to the target steps. If use_elapsed_duration==true, elapsed_secs is used instead of steps. Also, in this case, the parameters max_num_steps and min_num_steps are overloaded to contain max_elapsed_seconds and min_elapsed_seconds.

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrInput 

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput() GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput
	ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput
}

GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs, GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtr and GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrInput` via: 

        GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtr 

func GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtr(v *GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecArgs) GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrInput

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput 

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) LearningRateParameterName 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) LearningRateParameterName() pulumi.StringPtrOutput

The hyper-parameter name used in the tuning job that stands for learning rate. Leave it blank if learning rate is not in a parameter in tuning. The learning_rate is used to estimate the objective value of the ongoing trial.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) MaxStepCount 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) MaxStepCount() pulumi.StringPtrOutput

Steps used in predicting the final objective for early stopped trials. In general, it's set to be the same as the defined steps in training / tuning. If not defined, it will learn it from the completed trials. When use_steps is false, this field is set to the maximum elapsed seconds.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) MinMeasurementCount 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) MinMeasurementCount() pulumi.StringPtrOutput

The minimal number of measurements in a Trial. Early-stopping checks will not trigger if less than min_measurement_count+1 completed trials or pending trials with less than min_measurement_count measurements. If not defined, the default value is 5.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) MinStepCount 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) MinStepCount() pulumi.StringPtrOutput

Minimum number of steps for a trial to complete. Trials which do not have a measurement with step_count > min_step_count won't be considered for early stopping. It's ok to set it to 0, and a trial can be early stopped at any stage. By default, min_step_count is set to be one-tenth of the max_step_count. When use_elapsed_duration is true, this field is set to the minimum elapsed seconds.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput() GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) UpdateAllStoppedTrials 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) UpdateAllStoppedTrials() pulumi.BoolPtrOutput

ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model. When this flag is set to True, all stopped trials from the beginning are potentially updated in terms of their `final_measurement`. Also, note that the training logic of autoregressive models is different in this case. Enabling this option has shown better results and this may be the default option in the future.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) UseElapsedDuration 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput) UseElapsedDuration() pulumi.BoolPtrOutput

This bool determines whether or not the rule is applied based on elapsed_secs or steps. If use_elapsed_duration==false, the early stopping decision is made according to the predicted objective values according to the target steps. If use_elapsed_duration==true, elapsed_secs is used instead of steps. Also, in this case, the parameters max_num_steps and min_num_steps are overloaded to contain max_elapsed_seconds and min_elapsed_seconds.

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponse 

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponse struct {
	// The hyper-parameter name used in the tuning job that stands for learning rate. Leave it blank if learning rate is not in a parameter in tuning. The learning_rate is used to estimate the objective value of the ongoing trial.
	LearningRateParameterName string `pulumi:"learningRateParameterName"`
	// Steps used in predicting the final objective for early stopped trials. In general, it's set to be the same as the defined steps in training / tuning. If not defined, it will learn it from the completed trials. When use_steps is false, this field is set to the maximum elapsed seconds.
	MaxStepCount string `pulumi:"maxStepCount"`
	// The minimal number of measurements in a Trial. Early-stopping checks will not trigger if less than min_measurement_count+1 completed trials or pending trials with less than min_measurement_count measurements. If not defined, the default value is 5.
	MinMeasurementCount string `pulumi:"minMeasurementCount"`
	// Minimum number of steps for a trial to complete. Trials which do not have a measurement with step_count > min_step_count won't be considered for early stopping. It's ok to set it to 0, and a trial can be early stopped at any stage. By default, min_step_count is set to be one-tenth of the max_step_count. When use_elapsed_duration is true, this field is set to the minimum elapsed seconds.
	MinStepCount string `pulumi:"minStepCount"`
	// ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model. When this flag is set to True, all stopped trials from the beginning are potentially updated in terms of their `final_measurement`. Also, note that the training logic of autoregressive models is different in this case. Enabling this option has shown better results and this may be the default option in the future.
	UpdateAllStoppedTrials bool `pulumi:"updateAllStoppedTrials"`
	// This bool determines whether or not the rule is applied based on elapsed_secs or steps. If use_elapsed_duration==false, the early stopping decision is made according to the predicted objective values according to the target steps. If use_elapsed_duration==true, elapsed_secs is used instead of steps. Also, in this case, the parameters max_num_steps and min_num_steps are overloaded to contain max_elapsed_seconds and min_elapsed_seconds.
	UseElapsedDuration bool `pulumi:"useElapsedDuration"`
}

Configuration for ConvexAutomatedStoppingSpec. When there are enough completed trials (configured by min_measurement_count), for pending trials with enough measurements and steps, the policy first computes an overestimate of the objective value at max_num_steps according to the slope of the incomplete objective value curve. No prediction can be made if the curve is completely flat. If the overestimation is worse than the best objective value of the completed trials, this pending trial will be early-stopped, but a last measurement will be added to the pending trial with max_num_steps and predicted objective value from the autoregression model.

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput 

type GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput struct{ *pulumi.OutputState }

Configuration for ConvexAutomatedStoppingSpec. When there are enough completed trials (configured by min_measurement_count), for pending trials with enough measurements and steps, the policy first computes an overestimate of the objective value at max_num_steps according to the slope of the incomplete objective value curve. No prediction can be made if the curve is completely flat. If the overestimation is worse than the best objective value of the completed trials, this pending trial will be early-stopped, but a last measurement will be added to the pending trial with max_num_steps and predicted objective value from the autoregression model.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) LearningRateParameterName 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) LearningRateParameterName() pulumi.StringOutput

The hyper-parameter name used in the tuning job that stands for learning rate. Leave it blank if learning rate is not in a parameter in tuning. The learning_rate is used to estimate the objective value of the ongoing trial.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) MaxStepCount 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) MaxStepCount() pulumi.StringOutput

Steps used in predicting the final objective for early stopped trials. In general, it's set to be the same as the defined steps in training / tuning. If not defined, it will learn it from the completed trials. When use_steps is false, this field is set to the maximum elapsed seconds.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) MinMeasurementCount 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) MinMeasurementCount() pulumi.StringOutput

The minimal number of measurements in a Trial. Early-stopping checks will not trigger if less than min_measurement_count+1 completed trials or pending trials with less than min_measurement_count measurements. If not defined, the default value is 5.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) MinStepCount 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) MinStepCount() pulumi.StringOutput

Minimum number of steps for a trial to complete. Trials which do not have a measurement with step_count > min_step_count won't be considered for early stopping. It's ok to set it to 0, and a trial can be early stopped at any stage. By default, min_step_count is set to be one-tenth of the max_step_count. When use_elapsed_duration is true, this field is set to the minimum elapsed seconds.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput() GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) UpdateAllStoppedTrials 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) UpdateAllStoppedTrials() pulumi.BoolOutput

ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model. When this flag is set to True, all stopped trials from the beginning are potentially updated in terms of their `final_measurement`. Also, note that the training logic of autoregressive models is different in this case. Enabling this option has shown better results and this may be the default option in the future.

func (GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) UseElapsedDuration 

func (o GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput) UseElapsedDuration() pulumi.BoolOutput

This bool determines whether or not the rule is applied based on elapsed_secs or steps. If use_elapsed_duration==false, the early stopping decision is made according to the predicted objective values according to the target steps. If use_elapsed_duration==true, elapsed_secs is used instead of steps. Also, in this case, the parameters max_num_steps and min_num_steps are overloaded to contain max_elapsed_seconds and min_elapsed_seconds.

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpec 

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpec struct {
	// True if Measurement.elapsed_duration is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.step_count will be used as the x-axis.
	UseElapsedDuration *bool `pulumi:"useElapsedDuration"`
}

The decay curve automated stopping rule builds a Gaussian Process Regressor to predict the final objective value of a Trial based on the already completed Trials and the intermediate measurements of the current Trial. Early stopping is requested for the current Trial if there is very low probability to exceed the optimal value found so far.

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs 

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs struct {
	// True if Measurement.elapsed_duration is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.step_count will be used as the x-axis.
	UseElapsedDuration pulumi.BoolPtrInput `pulumi:"useElapsedDuration"`
}

The decay curve automated stopping rule builds a Gaussian Process Regressor to predict the final objective value of a Trial based on the already completed Trials and the intermediate measurements of the current Trial. Early stopping is requested for the current Trial if there is very low probability to exceed the optimal value found so far.

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput 

func (i GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput() GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput 

func (i GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput() GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecInput 

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput() GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput
	ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput
}

GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecInput is an input type that accepts GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs and GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecInput` via: 

GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs{...}

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput 

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput struct{ *pulumi.OutputState }

The decay curve automated stopping rule builds a Gaussian Process Regressor to predict the final objective value of a Trial based on the already completed Trials and the intermediate measurements of the current Trial. Early stopping is requested for the current Trial if there is very low probability to exceed the optimal value found so far.

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput 

func (o GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput() GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput() GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput) UseElapsedDuration 

func (o GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput) UseElapsedDuration() pulumi.BoolPtrOutput

True if Measurement.elapsed_duration is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.step_count will be used as the x-axis.

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrInput 

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput() GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput
	ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput
}

GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs, GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtr and GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrInput` via: 

        GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtr 

func GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtr(v *GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecArgs) GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrInput

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput 

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput() GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput) UseElapsedDuration 

func (o GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput) UseElapsedDuration() pulumi.BoolPtrOutput

True if Measurement.elapsed_duration is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.step_count will be used as the x-axis.

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponse 

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponse struct {
	// True if Measurement.elapsed_duration is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.step_count will be used as the x-axis.
	UseElapsedDuration bool `pulumi:"useElapsedDuration"`
}

The decay curve automated stopping rule builds a Gaussian Process Regressor to predict the final objective value of a Trial based on the already completed Trials and the intermediate measurements of the current Trial. Early stopping is requested for the current Trial if there is very low probability to exceed the optimal value found so far.

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput 

type GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput struct{ *pulumi.OutputState }

The decay curve automated stopping rule builds a Gaussian Process Regressor to predict the final objective value of a Trial based on the already completed Trials and the intermediate measurements of the current Trial. Early stopping is requested for the current Trial if there is very low probability to exceed the optimal value found so far.

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput() GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput) UseElapsedDuration 

func (o GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput) UseElapsedDuration() pulumi.BoolOutput

True if Measurement.elapsed_duration is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.step_count will be used as the x-axis.

type GoogleCloudAiplatformV1StudySpecInput 

type GoogleCloudAiplatformV1StudySpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecOutput() GoogleCloudAiplatformV1StudySpecOutput
	ToGoogleCloudAiplatformV1StudySpecOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecOutput
}

GoogleCloudAiplatformV1StudySpecInput is an input type that accepts GoogleCloudAiplatformV1StudySpecArgs and GoogleCloudAiplatformV1StudySpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecInput` via: 

GoogleCloudAiplatformV1StudySpecArgs{...}

type GoogleCloudAiplatformV1StudySpecMeasurementSelectionType 

type GoogleCloudAiplatformV1StudySpecMeasurementSelectionType string

Describe which measurement selection type will be used

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ElementType 

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput 

func (e GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput() GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput 

func (e GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput() GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToStringOutput 

func (e GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecMeasurementSelectionType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeInput 

type GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput() GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput
	ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput
}

GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeInput is an input type that accepts GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeArgs and GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeInput` via: 

GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeArgs{...}

type GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput 

type GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput 

func (o GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput() GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput 

func (o GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput() GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrInput 

type GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput() GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput
	ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput
}

func GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtr 

func GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtr(v string) GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrInput

type GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput 

type GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput) Elem() GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypeOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput 

func (o GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput() GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput) ToGoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpec 

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpec struct {
	// True if median automated stopping rule applies on Measurement.elapsed_duration. It means that elapsed_duration field of latest measurement of current Trial is used to compute median objective value for each completed Trials.
	UseElapsedDuration *bool `pulumi:"useElapsedDuration"`
}

The median automated stopping rule stops a pending Trial if the Trial's best objective_value is strictly below the median 'performance' of all completed Trials reported up to the Trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the Trial in each measurement.

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs 

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs struct {
	// True if median automated stopping rule applies on Measurement.elapsed_duration. It means that elapsed_duration field of latest measurement of current Trial is used to compute median objective value for each completed Trials.
	UseElapsedDuration pulumi.BoolPtrInput `pulumi:"useElapsedDuration"`
}

The median automated stopping rule stops a pending Trial if the Trial's best objective_value is strictly below the median 'performance' of all completed Trials reported up to the Trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the Trial in each measurement.

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput 

func (i GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput() GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput 

func (i GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput() GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecInput 

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput() GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput
	ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput
}

GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecInput is an input type that accepts GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs and GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecInput` via: 

GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs{...}

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput 

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput struct{ *pulumi.OutputState }

The median automated stopping rule stops a pending Trial if the Trial's best objective_value is strictly below the median 'performance' of all completed Trials reported up to the Trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the Trial in each measurement.

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput 

func (o GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput() GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput() GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput) UseElapsedDuration 

func (o GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput) UseElapsedDuration() pulumi.BoolPtrOutput

True if median automated stopping rule applies on Measurement.elapsed_duration. It means that elapsed_duration field of latest measurement of current Trial is used to compute median objective value for each completed Trials.

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrInput 

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput() GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput
	ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput
}

GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs, GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtr and GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrInput` via: 

        GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtr 

func GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtr(v *GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecArgs) GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrInput

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput 

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecOutput

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput() GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput) UseElapsedDuration 

func (o GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput) UseElapsedDuration() pulumi.BoolPtrOutput

True if median automated stopping rule applies on Measurement.elapsed_duration. It means that elapsed_duration field of latest measurement of current Trial is used to compute median objective value for each completed Trials.

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponse 

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponse struct {
	// True if median automated stopping rule applies on Measurement.elapsed_duration. It means that elapsed_duration field of latest measurement of current Trial is used to compute median objective value for each completed Trials.
	UseElapsedDuration bool `pulumi:"useElapsedDuration"`
}

The median automated stopping rule stops a pending Trial if the Trial's best objective_value is strictly below the median 'performance' of all completed Trials reported up to the Trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the Trial in each measurement.

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput 

type GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput struct{ *pulumi.OutputState }

The median automated stopping rule stops a pending Trial if the Trial's best objective_value is strictly below the median 'performance' of all completed Trials reported up to the Trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the Trial in each measurement.

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput() GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput) UseElapsedDuration 

func (o GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput) UseElapsedDuration() pulumi.BoolOutput

True if median automated stopping rule applies on Measurement.elapsed_duration. It means that elapsed_duration field of latest measurement of current Trial is used to compute median objective value for each completed Trials.

type GoogleCloudAiplatformV1StudySpecMetricSpec 

type GoogleCloudAiplatformV1StudySpecMetricSpec struct {
	// The optimization goal of the metric.
	Goal GoogleCloudAiplatformV1StudySpecMetricSpecGoal `pulumi:"goal"`
	// The ID of the metric. Must not contain whitespaces and must be unique amongst all MetricSpecs.
	MetricId string `pulumi:"metricId"`
	// Used for safe search. In the case, the metric will be a safety metric. You must provide a separate metric for objective metric.
	SafetyConfig *GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfig `pulumi:"safetyConfig"`
}

Represents a metric to optimize.

type GoogleCloudAiplatformV1StudySpecMetricSpecArgs 

type GoogleCloudAiplatformV1StudySpecMetricSpecArgs struct {
	// The optimization goal of the metric.
	Goal GoogleCloudAiplatformV1StudySpecMetricSpecGoalInput `pulumi:"goal"`
	// The ID of the metric. Must not contain whitespaces and must be unique amongst all MetricSpecs.
	MetricId pulumi.StringInput `pulumi:"metricId"`
	// Used for safe search. In the case, the metric will be a safety metric. You must provide a separate metric for objective metric.
	SafetyConfig GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrInput `pulumi:"safetyConfig"`
}

Represents a metric to optimize.

func (GoogleCloudAiplatformV1StudySpecMetricSpecArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecMetricSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMetricSpecArgs) ToGoogleCloudAiplatformV1StudySpecMetricSpecOutput 

func (i GoogleCloudAiplatformV1StudySpecMetricSpecArgs) ToGoogleCloudAiplatformV1StudySpecMetricSpecOutput() GoogleCloudAiplatformV1StudySpecMetricSpecOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecArgs) ToGoogleCloudAiplatformV1StudySpecMetricSpecOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecMetricSpecArgs) ToGoogleCloudAiplatformV1StudySpecMetricSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecOutput

type GoogleCloudAiplatformV1StudySpecMetricSpecArray 

type GoogleCloudAiplatformV1StudySpecMetricSpecArray []GoogleCloudAiplatformV1StudySpecMetricSpecInput

func (GoogleCloudAiplatformV1StudySpecMetricSpecArray) ElementType 

func (GoogleCloudAiplatformV1StudySpecMetricSpecArray) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMetricSpecArray) ToGoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput 

func (i GoogleCloudAiplatformV1StudySpecMetricSpecArray) ToGoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput() GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecArray) ToGoogleCloudAiplatformV1StudySpecMetricSpecArrayOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecMetricSpecArray) ToGoogleCloudAiplatformV1StudySpecMetricSpecArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput

type GoogleCloudAiplatformV1StudySpecMetricSpecArrayInput 

type GoogleCloudAiplatformV1StudySpecMetricSpecArrayInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput() GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput
	ToGoogleCloudAiplatformV1StudySpecMetricSpecArrayOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput
}

GoogleCloudAiplatformV1StudySpecMetricSpecArrayInput is an input type that accepts GoogleCloudAiplatformV1StudySpecMetricSpecArray and GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecMetricSpecArrayInput` via: 

GoogleCloudAiplatformV1StudySpecMetricSpecArray{ GoogleCloudAiplatformV1StudySpecMetricSpecArgs{...} }

type GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput 

type GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput) Index 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1StudySpecMetricSpecOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput() GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecArrayOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput

type GoogleCloudAiplatformV1StudySpecMetricSpecGoal 

type GoogleCloudAiplatformV1StudySpecMetricSpecGoal string

Required. The optimization goal of the metric.

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ElementType 

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput 

func (e GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput() GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput 

func (e GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput() GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToStringOutput 

func (e GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecMetricSpecGoal) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecMetricSpecGoalInput 

type GoogleCloudAiplatformV1StudySpecMetricSpecGoalInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput() GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput
	ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput
}

GoogleCloudAiplatformV1StudySpecMetricSpecGoalInput is an input type that accepts GoogleCloudAiplatformV1StudySpecMetricSpecGoalArgs and GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecMetricSpecGoalInput` via: 

GoogleCloudAiplatformV1StudySpecMetricSpecGoalArgs{...}

type GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput 

type GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput() GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput() GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrInput 

type GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput() GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput
	ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput
}

func GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtr 

func GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtr(v string) GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrInput

type GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput 

type GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput() GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecGoalPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecMetricSpecInput 

type GoogleCloudAiplatformV1StudySpecMetricSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecMetricSpecOutput() GoogleCloudAiplatformV1StudySpecMetricSpecOutput
	ToGoogleCloudAiplatformV1StudySpecMetricSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecOutput
}

GoogleCloudAiplatformV1StudySpecMetricSpecInput is an input type that accepts GoogleCloudAiplatformV1StudySpecMetricSpecArgs and GoogleCloudAiplatformV1StudySpecMetricSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecMetricSpecInput` via: 

GoogleCloudAiplatformV1StudySpecMetricSpecArgs{...}

type GoogleCloudAiplatformV1StudySpecMetricSpecOutput 

type GoogleCloudAiplatformV1StudySpecMetricSpecOutput struct{ *pulumi.OutputState }

Represents a metric to optimize.

func (GoogleCloudAiplatformV1StudySpecMetricSpecOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMetricSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMetricSpecOutput) Goal 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecOutput) Goal() GoogleCloudAiplatformV1StudySpecMetricSpecGoalOutput

The optimization goal of the metric.

func (GoogleCloudAiplatformV1StudySpecMetricSpecOutput) MetricId 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecOutput) MetricId() pulumi.StringOutput

The ID of the metric. Must not contain whitespaces and must be unique amongst all MetricSpecs.

func (GoogleCloudAiplatformV1StudySpecMetricSpecOutput) SafetyConfig 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecOutput) SafetyConfig() GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput

Used for safe search. In the case, the metric will be a safety metric. You must provide a separate metric for objective metric.

func (GoogleCloudAiplatformV1StudySpecMetricSpecOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecOutput() GoogleCloudAiplatformV1StudySpecMetricSpecOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecOutput

type GoogleCloudAiplatformV1StudySpecMetricSpecResponse 

type GoogleCloudAiplatformV1StudySpecMetricSpecResponse struct {
	// The optimization goal of the metric.
	Goal string `pulumi:"goal"`
	// The ID of the metric. Must not contain whitespaces and must be unique amongst all MetricSpecs.
	MetricId string `pulumi:"metricId"`
	// Used for safe search. In the case, the metric will be a safety metric. You must provide a separate metric for objective metric.
	SafetyConfig GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponse `pulumi:"safetyConfig"`
}

Represents a metric to optimize.

type GoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput 

type GoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput() GoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput

type GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput 

type GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput struct{ *pulumi.OutputState }

Represents a metric to optimize.

func (GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput) Goal 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput) Goal() pulumi.StringOutput

The optimization goal of the metric.

func (GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput) MetricId 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput) MetricId() pulumi.StringOutput

The ID of the metric. Must not contain whitespaces and must be unique amongst all MetricSpecs.

func (GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput) SafetyConfig 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput) SafetyConfig() GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput

Used for safe search. In the case, the metric will be a safety metric. You must provide a separate metric for objective metric.

func (GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput() GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecResponseOutput

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfig 

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfig struct {
	// Desired minimum fraction of safe trials (over total number of trials) that should be targeted by the algorithm at any time during the study (best effort). This should be between 0.0 and 1.0 and a value of 0.0 means that there is no minimum and an algorithm proceeds without targeting any specific fraction. A value of 1.0 means that the algorithm attempts to only Suggest safe Trials.
	DesiredMinSafeTrialsFraction *float64 `pulumi:"desiredMinSafeTrialsFraction"`
	// Safety threshold (boundary value between safe and unsafe). NOTE that if you leave SafetyMetricConfig unset, a default value of 0 will be used.
	SafetyThreshold *float64 `pulumi:"safetyThreshold"`
}

Used in safe optimization to specify threshold levels and risk tolerance.

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs 

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs struct {
	// Desired minimum fraction of safe trials (over total number of trials) that should be targeted by the algorithm at any time during the study (best effort). This should be between 0.0 and 1.0 and a value of 0.0 means that there is no minimum and an algorithm proceeds without targeting any specific fraction. A value of 1.0 means that the algorithm attempts to only Suggest safe Trials.
	DesiredMinSafeTrialsFraction pulumi.Float64PtrInput `pulumi:"desiredMinSafeTrialsFraction"`
	// Safety threshold (boundary value between safe and unsafe). NOTE that if you leave SafetyMetricConfig unset, a default value of 0 will be used.
	SafetyThreshold pulumi.Float64PtrInput `pulumi:"safetyThreshold"`
}

Used in safe optimization to specify threshold levels and risk tolerance.

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput 

func (i GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput() GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput 

func (i GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput() GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigInput 

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput() GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput
	ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput
}

GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigInput is an input type that accepts GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs and GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigInput` via: 

GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs{...}

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput 

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput struct{ *pulumi.OutputState }

Used in safe optimization to specify threshold levels and risk tolerance.

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) DesiredMinSafeTrialsFraction 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) DesiredMinSafeTrialsFraction() pulumi.Float64PtrOutput

Desired minimum fraction of safe trials (over total number of trials) that should be targeted by the algorithm at any time during the study (best effort). This should be between 0.0 and 1.0 and a value of 0.0 means that there is no minimum and an algorithm proceeds without targeting any specific fraction. A value of 1.0 means that the algorithm attempts to only Suggest safe Trials.

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) SafetyThreshold 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) SafetyThreshold() pulumi.Float64PtrOutput

Safety threshold (boundary value between safe and unsafe). NOTE that if you leave SafetyMetricConfig unset, a default value of 0 will be used.

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput() GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput() GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrInput 

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput() GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput
	ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput
}

GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs, GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtr and GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrInput` via: 

        GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtr 

func GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtr(v *GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigArgs) GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrInput

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput 

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput) DesiredMinSafeTrialsFraction 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput) DesiredMinSafeTrialsFraction() pulumi.Float64PtrOutput

Desired minimum fraction of safe trials (over total number of trials) that should be targeted by the algorithm at any time during the study (best effort). This should be between 0.0 and 1.0 and a value of 0.0 means that there is no minimum and an algorithm proceeds without targeting any specific fraction. A value of 1.0 means that the algorithm attempts to only Suggest safe Trials.

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput) SafetyThreshold 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput) SafetyThreshold() pulumi.Float64PtrOutput

Safety threshold (boundary value between safe and unsafe). NOTE that if you leave SafetyMetricConfig unset, a default value of 0 will be used.

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput() GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigPtrOutput

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponse 

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponse struct {
	// Desired minimum fraction of safe trials (over total number of trials) that should be targeted by the algorithm at any time during the study (best effort). This should be between 0.0 and 1.0 and a value of 0.0 means that there is no minimum and an algorithm proceeds without targeting any specific fraction. A value of 1.0 means that the algorithm attempts to only Suggest safe Trials.
	DesiredMinSafeTrialsFraction float64 `pulumi:"desiredMinSafeTrialsFraction"`
	// Safety threshold (boundary value between safe and unsafe). NOTE that if you leave SafetyMetricConfig unset, a default value of 0 will be used.
	SafetyThreshold float64 `pulumi:"safetyThreshold"`
}

Used in safe optimization to specify threshold levels and risk tolerance.

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput 

type GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput struct{ *pulumi.OutputState }

Used in safe optimization to specify threshold levels and risk tolerance.

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput) DesiredMinSafeTrialsFraction 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput) DesiredMinSafeTrialsFraction() pulumi.Float64Output

Desired minimum fraction of safe trials (over total number of trials) that should be targeted by the algorithm at any time during the study (best effort). This should be between 0.0 and 1.0 and a value of 0.0 means that there is no minimum and an algorithm proceeds without targeting any specific fraction. A value of 1.0 means that the algorithm attempts to only Suggest safe Trials.

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput) SafetyThreshold 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput) SafetyThreshold() pulumi.Float64Output

Safety threshold (boundary value between safe and unsafe). NOTE that if you leave SafetyMetricConfig unset, a default value of 0 will be used.

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput() GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput

func (GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput) ToGoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecMetricSpecSafetyMetricConfigResponseOutput

type GoogleCloudAiplatformV1StudySpecObservationNoise 

type GoogleCloudAiplatformV1StudySpecObservationNoise string

The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecObservationNoise) ElementType 

func (GoogleCloudAiplatformV1StudySpecObservationNoise) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecObservationNoise) ToGoogleCloudAiplatformV1StudySpecObservationNoiseOutput 

func (e GoogleCloudAiplatformV1StudySpecObservationNoise) ToGoogleCloudAiplatformV1StudySpecObservationNoiseOutput() GoogleCloudAiplatformV1StudySpecObservationNoiseOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoise) ToGoogleCloudAiplatformV1StudySpecObservationNoiseOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecObservationNoise) ToGoogleCloudAiplatformV1StudySpecObservationNoiseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecObservationNoiseOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoise) ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput 

func (e GoogleCloudAiplatformV1StudySpecObservationNoise) ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput() GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoise) ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecObservationNoise) ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoise) ToStringOutput 

func (e GoogleCloudAiplatformV1StudySpecObservationNoise) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoise) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecObservationNoise) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoise) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1StudySpecObservationNoise) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoise) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecObservationNoise) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecObservationNoiseInput 

type GoogleCloudAiplatformV1StudySpecObservationNoiseInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecObservationNoiseOutput() GoogleCloudAiplatformV1StudySpecObservationNoiseOutput
	ToGoogleCloudAiplatformV1StudySpecObservationNoiseOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecObservationNoiseOutput
}

GoogleCloudAiplatformV1StudySpecObservationNoiseInput is an input type that accepts GoogleCloudAiplatformV1StudySpecObservationNoiseArgs and GoogleCloudAiplatformV1StudySpecObservationNoiseOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecObservationNoiseInput` via: 

GoogleCloudAiplatformV1StudySpecObservationNoiseArgs{...}

type GoogleCloudAiplatformV1StudySpecObservationNoiseOutput 

type GoogleCloudAiplatformV1StudySpecObservationNoiseOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToGoogleCloudAiplatformV1StudySpecObservationNoiseOutput 

func (o GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToGoogleCloudAiplatformV1StudySpecObservationNoiseOutput() GoogleCloudAiplatformV1StudySpecObservationNoiseOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToGoogleCloudAiplatformV1StudySpecObservationNoiseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToGoogleCloudAiplatformV1StudySpecObservationNoiseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecObservationNoiseOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput 

func (o GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput() GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecObservationNoiseOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecObservationNoisePtrInput 

type GoogleCloudAiplatformV1StudySpecObservationNoisePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput() GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput
	ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput
}

func GoogleCloudAiplatformV1StudySpecObservationNoisePtr 

func GoogleCloudAiplatformV1StudySpecObservationNoisePtr(v string) GoogleCloudAiplatformV1StudySpecObservationNoisePtrInput

type GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput 

type GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput) Elem() GoogleCloudAiplatformV1StudySpecObservationNoiseOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput) ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput 

func (o GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput) ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput() GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput) ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput) ToGoogleCloudAiplatformV1StudySpecObservationNoisePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecOutput 

type GoogleCloudAiplatformV1StudySpecOutput struct{ *pulumi.OutputState }

Represents specification of a Study.

func (GoogleCloudAiplatformV1StudySpecOutput) Algorithm 

func (o GoogleCloudAiplatformV1StudySpecOutput) Algorithm() GoogleCloudAiplatformV1StudySpecAlgorithmPtrOutput

The search algorithm specified for the Study.

func (GoogleCloudAiplatformV1StudySpecOutput) ConvexAutomatedStoppingSpec 

func (o GoogleCloudAiplatformV1StudySpecOutput) ConvexAutomatedStoppingSpec() GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecPtrOutput

The automated early stopping spec using convex stopping rule.

func (GoogleCloudAiplatformV1StudySpecOutput) DecayCurveStoppingSpec 

func (o GoogleCloudAiplatformV1StudySpecOutput) DecayCurveStoppingSpec() GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecPtrOutput

The automated early stopping spec using decay curve rule.

func (GoogleCloudAiplatformV1StudySpecOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecOutput) MeasurementSelectionType 

func (o GoogleCloudAiplatformV1StudySpecOutput) MeasurementSelectionType() GoogleCloudAiplatformV1StudySpecMeasurementSelectionTypePtrOutput

Describe which measurement selection type will be used

func (GoogleCloudAiplatformV1StudySpecOutput) MedianAutomatedStoppingSpec 

func (o GoogleCloudAiplatformV1StudySpecOutput) MedianAutomatedStoppingSpec() GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecPtrOutput

The automated early stopping spec using median rule.

func (GoogleCloudAiplatformV1StudySpecOutput) Metrics 

func (o GoogleCloudAiplatformV1StudySpecOutput) Metrics() GoogleCloudAiplatformV1StudySpecMetricSpecArrayOutput

Metric specs for the Study.

func (GoogleCloudAiplatformV1StudySpecOutput) ObservationNoise 

func (o GoogleCloudAiplatformV1StudySpecOutput) ObservationNoise() GoogleCloudAiplatformV1StudySpecObservationNoisePtrOutput

The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecOutput) Parameters 

func (o GoogleCloudAiplatformV1StudySpecOutput) Parameters() GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput

The set of parameters to tune.

func (GoogleCloudAiplatformV1StudySpecOutput) StudyStoppingConfig 

func (o GoogleCloudAiplatformV1StudySpecOutput) StudyStoppingConfig() GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput

Conditions for automated stopping of a Study. Enable automated stopping by configuring at least one condition.

func (GoogleCloudAiplatformV1StudySpecOutput) ToGoogleCloudAiplatformV1StudySpecOutput 

func (o GoogleCloudAiplatformV1StudySpecOutput) ToGoogleCloudAiplatformV1StudySpecOutput() GoogleCloudAiplatformV1StudySpecOutput

func (GoogleCloudAiplatformV1StudySpecOutput) ToGoogleCloudAiplatformV1StudySpecOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecOutput) ToGoogleCloudAiplatformV1StudySpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecOutput

type GoogleCloudAiplatformV1StudySpecParameterSpec 

type GoogleCloudAiplatformV1StudySpecParameterSpec struct {
	// The value spec for a 'CATEGORICAL' parameter.
	CategoricalValueSpec *GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpec `pulumi:"categoricalValueSpec"`
	// A conditional parameter node is active if the parameter's value matches the conditional node's parent_value_condition. If two items in conditional_parameter_specs have the same name, they must have disjoint parent_value_condition.
	ConditionalParameterSpecs []GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpec `pulumi:"conditionalParameterSpecs"`
	// The value spec for a 'DISCRETE' parameter.
	DiscreteValueSpec *GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpec `pulumi:"discreteValueSpec"`
	// The value spec for a 'DOUBLE' parameter.
	DoubleValueSpec *GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpec `pulumi:"doubleValueSpec"`
	// The value spec for an 'INTEGER' parameter.
	IntegerValueSpec *GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpec `pulumi:"integerValueSpec"`
	// The ID of the parameter. Must not contain whitespaces and must be unique amongst all ParameterSpecs.
	ParameterId string `pulumi:"parameterId"`
	// How the parameter should be scaled. Leave unset for `CATEGORICAL` parameters.
	ScaleType *GoogleCloudAiplatformV1StudySpecParameterSpecScaleType `pulumi:"scaleType"`
}

Represents a single parameter to optimize.

type GoogleCloudAiplatformV1StudySpecParameterSpecArgs 

type GoogleCloudAiplatformV1StudySpecParameterSpecArgs struct {
	// The value spec for a 'CATEGORICAL' parameter.
	CategoricalValueSpec GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrInput `pulumi:"categoricalValueSpec"`
	// A conditional parameter node is active if the parameter's value matches the conditional node's parent_value_condition. If two items in conditional_parameter_specs have the same name, they must have disjoint parent_value_condition.
	ConditionalParameterSpecs GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayInput `pulumi:"conditionalParameterSpecs"`
	// The value spec for a 'DISCRETE' parameter.
	DiscreteValueSpec GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrInput `pulumi:"discreteValueSpec"`
	// The value spec for a 'DOUBLE' parameter.
	DoubleValueSpec GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrInput `pulumi:"doubleValueSpec"`
	// The value spec for an 'INTEGER' parameter.
	IntegerValueSpec GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrInput `pulumi:"integerValueSpec"`
	// The ID of the parameter. Must not contain whitespaces and must be unique amongst all ParameterSpecs.
	ParameterId pulumi.StringInput `pulumi:"parameterId"`
	// How the parameter should be scaled. Leave unset for `CATEGORICAL` parameters.
	ScaleType GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrInput `pulumi:"scaleType"`
}

Represents a single parameter to optimize.

func (GoogleCloudAiplatformV1StudySpecParameterSpecArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecArray 

type GoogleCloudAiplatformV1StudySpecParameterSpecArray []GoogleCloudAiplatformV1StudySpecParameterSpecInput

func (GoogleCloudAiplatformV1StudySpecParameterSpecArray) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecArray) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecArray) ToGoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecArray) ToGoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput() GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecArray) ToGoogleCloudAiplatformV1StudySpecParameterSpecArrayOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecArray) ToGoogleCloudAiplatformV1StudySpecParameterSpecArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecArrayInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecArrayInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput() GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecArrayOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecArrayInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecArray and GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecArrayInput` via: 

GoogleCloudAiplatformV1StudySpecParameterSpecArray{ GoogleCloudAiplatformV1StudySpecParameterSpecArgs{...} }

type GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput) Index 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1StudySpecParameterSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput() GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecArrayOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecArrayOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpec 

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpec struct {
	// A default value for a `CATEGORICAL` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	DefaultValue *string `pulumi:"defaultValue"`
	// The list of possible categories.
	Values []string `pulumi:"values"`
}

Value specification for a parameter in `CATEGORICAL` type.

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs 

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs struct {
	// A default value for a `CATEGORICAL` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	DefaultValue pulumi.StringPtrInput `pulumi:"defaultValue"`
	// The list of possible categories.
	Values pulumi.StringArrayInput `pulumi:"values"`
}

Value specification for a parameter in `CATEGORICAL` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs and GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecInput` via: 

GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs{...}

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput struct{ *pulumi.OutputState }

Value specification for a parameter in `CATEGORICAL` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) DefaultValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) DefaultValue() pulumi.StringPtrOutput

A default value for a `CATEGORICAL` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput) Values() pulumi.StringArrayOutput

The list of possible categories.

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs, GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtr and GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrInput` via: 

        GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtr 

func GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtr(v *GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecArgs) GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrInput

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput) DefaultValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput) DefaultValue() pulumi.StringPtrOutput

A default value for a `CATEGORICAL` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput) Values() pulumi.StringArrayOutput

The list of possible categories.

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponse 

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponse struct {
	// A default value for a `CATEGORICAL` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	DefaultValue string `pulumi:"defaultValue"`
	// The list of possible categories.
	Values []string `pulumi:"values"`
}

Value specification for a parameter in `CATEGORICAL` type.

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput struct{ *pulumi.OutputState }

Value specification for a parameter in `CATEGORICAL` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput) DefaultValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput) DefaultValue() pulumi.StringOutput

A default value for a `CATEGORICAL` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput() GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput) Values() pulumi.StringArrayOutput

The list of possible categories.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpec 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpec struct {
	// The spec for a conditional parameter.
	ParameterSpec GoogleCloudAiplatformV1StudySpecParameterSpec `pulumi:"parameterSpec"`
	// The spec for matching values from a parent parameter of `CATEGORICAL` type.
	ParentCategoricalValues *GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition `pulumi:"parentCategoricalValues"`
	// The spec for matching values from a parent parameter of `DISCRETE` type.
	ParentDiscreteValues *GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition `pulumi:"parentDiscreteValues"`
	// The spec for matching values from a parent parameter of `INTEGER` type.
	ParentIntValues *GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueCondition `pulumi:"parentIntValues"`
}

Represents a parameter spec with condition from its parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArgs 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArgs struct {
	// The spec for a conditional parameter.
	ParameterSpec GoogleCloudAiplatformV1StudySpecParameterSpecInput `pulumi:"parameterSpec"`
	// The spec for matching values from a parent parameter of `CATEGORICAL` type.
	ParentCategoricalValues GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrInput `pulumi:"parentCategoricalValues"`
	// The spec for matching values from a parent parameter of `DISCRETE` type.
	ParentDiscreteValues GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrInput `pulumi:"parentDiscreteValues"`
	// The spec for matching values from a parent parameter of `INTEGER` type.
	ParentIntValues GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrInput `pulumi:"parentIntValues"`
}

Represents a parameter spec with condition from its parent parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArray 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArray []GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecInput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArray) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArray) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArray) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArray) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArray) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArray) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArray and GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayInput` via: 

GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArray{ GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArgs{...} }

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput) Index 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition struct {
	// Matches values of the parent parameter of 'CATEGORICAL' type. All values must exist in `categorical_value_spec` of parent parameter.
	Values []string `pulumi:"values"`
}

Represents the spec to match categorical values from parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs struct {
	// Matches values of the parent parameter of 'CATEGORICAL' type. All values must exist in `categorical_value_spec` of parent parameter.
	Values pulumi.StringArrayInput `pulumi:"values"`
}

Represents the spec to match categorical values from parent parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs and GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionInput` via: 

GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs{...}

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput struct{ *pulumi.OutputState }

Represents the spec to match categorical values from parent parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput) Values() pulumi.StringArrayOutput

Matches values of the parent parameter of 'CATEGORICAL' type. All values must exist in `categorical_value_spec` of parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs, GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtr and GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrInput` via: 

        GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtr 

func GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtr(v *GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionArgs) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrInput

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput) Values() pulumi.StringArrayOutput

Matches values of the parent parameter of 'CATEGORICAL' type. All values must exist in `categorical_value_spec` of parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponse 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponse struct {
	// Matches values of the parent parameter of 'CATEGORICAL' type. All values must exist in `categorical_value_spec` of parent parameter.
	Values []string `pulumi:"values"`
}

Represents the spec to match categorical values from parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput struct{ *pulumi.OutputState }

Represents the spec to match categorical values from parent parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput) Values() pulumi.StringArrayOutput

Matches values of the parent parameter of 'CATEGORICAL' type. All values must exist in `categorical_value_spec` of parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition struct {
	// Matches values of the parent parameter of 'DISCRETE' type. All values must exist in `discrete_value_spec` of parent parameter. The Epsilon of the value matching is 1e-10.
	Values []float64 `pulumi:"values"`
}

Represents the spec to match discrete values from parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs struct {
	// Matches values of the parent parameter of 'DISCRETE' type. All values must exist in `discrete_value_spec` of parent parameter. The Epsilon of the value matching is 1e-10.
	Values pulumi.Float64ArrayInput `pulumi:"values"`
}

Represents the spec to match discrete values from parent parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs and GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionInput` via: 

GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs{...}

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput struct{ *pulumi.OutputState }

Represents the spec to match discrete values from parent parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput) Values() pulumi.Float64ArrayOutput

Matches values of the parent parameter of 'DISCRETE' type. All values must exist in `discrete_value_spec` of parent parameter. The Epsilon of the value matching is 1e-10.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs, GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtr and GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrInput` via: 

        GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtr 

func GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtr(v *GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionArgs) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrInput

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput) Values() pulumi.Float64ArrayOutput

Matches values of the parent parameter of 'DISCRETE' type. All values must exist in `discrete_value_spec` of parent parameter. The Epsilon of the value matching is 1e-10.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponse 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponse struct {
	// Matches values of the parent parameter of 'DISCRETE' type. All values must exist in `discrete_value_spec` of parent parameter. The Epsilon of the value matching is 1e-10.
	Values []float64 `pulumi:"values"`
}

Represents the spec to match discrete values from parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput struct{ *pulumi.OutputState }

Represents the spec to match discrete values from parent parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput) Values() pulumi.Float64ArrayOutput

Matches values of the parent parameter of 'DISCRETE' type. All values must exist in `discrete_value_spec` of parent parameter. The Epsilon of the value matching is 1e-10.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArgs and GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecInput` via: 

GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArgs{...}

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueCondition 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueCondition struct {
	// Matches values of the parent parameter of 'INTEGER' type. All values must lie in `integer_value_spec` of parent parameter.
	Values []string `pulumi:"values"`
}

Represents the spec to match integer values from parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs struct {
	// Matches values of the parent parameter of 'INTEGER' type. All values must lie in `integer_value_spec` of parent parameter.
	Values pulumi.StringArrayInput `pulumi:"values"`
}

Represents the spec to match integer values from parent parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs and GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionInput` via: 

GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs{...}

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput struct{ *pulumi.OutputState }

Represents the spec to match integer values from parent parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput) Values() pulumi.StringArrayOutput

Matches values of the parent parameter of 'INTEGER' type. All values must lie in `integer_value_spec` of parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs, GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtr and GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrInput` via: 

        GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtr 

func GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtr(v *GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionArgs) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrInput

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput) Values() pulumi.StringArrayOutput

Matches values of the parent parameter of 'INTEGER' type. All values must lie in `integer_value_spec` of parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponse 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponse struct {
	// Matches values of the parent parameter of 'INTEGER' type. All values must lie in `integer_value_spec` of parent parameter.
	Values []string `pulumi:"values"`
}

Represents the spec to match integer values from parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput struct{ *pulumi.OutputState }

Represents the spec to match integer values from parent parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput) Values() pulumi.StringArrayOutput

Matches values of the parent parameter of 'INTEGER' type. All values must lie in `integer_value_spec` of parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput struct{ *pulumi.OutputState }

Represents a parameter spec with condition from its parent parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ParameterSpec 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ParameterSpec() GoogleCloudAiplatformV1StudySpecParameterSpecOutput

The spec for a conditional parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ParentCategoricalValues 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ParentCategoricalValues() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionPtrOutput

The spec for matching values from a parent parameter of `CATEGORICAL` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ParentDiscreteValues 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ParentDiscreteValues() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionPtrOutput

The spec for matching values from a parent parameter of `DISCRETE` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ParentIntValues 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ParentIntValues() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionPtrOutput

The spec for matching values from a parent parameter of `INTEGER` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponse 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponse struct {
	// The spec for a conditional parameter.
	ParameterSpec GoogleCloudAiplatformV1StudySpecParameterSpecResponse `pulumi:"parameterSpec"`
	// The spec for matching values from a parent parameter of `CATEGORICAL` type.
	ParentCategoricalValues GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponse `pulumi:"parentCategoricalValues"`
	// The spec for matching values from a parent parameter of `DISCRETE` type.
	ParentDiscreteValues GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponse `pulumi:"parentDiscreteValues"`
	// The spec for matching values from a parent parameter of `INTEGER` type.
	ParentIntValues GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponse `pulumi:"parentIntValues"`
}

Represents a parameter spec with condition from its parent parameter.

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput struct{ *pulumi.OutputState }

Represents a parameter spec with condition from its parent parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ParameterSpec 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ParameterSpec() GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput

The spec for a conditional parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ParentCategoricalValues 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ParentCategoricalValues() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecCategoricalValueConditionResponseOutput

The spec for matching values from a parent parameter of `CATEGORICAL` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ParentDiscreteValues 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ParentDiscreteValues() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecDiscreteValueConditionResponseOutput

The spec for matching values from a parent parameter of `DISCRETE` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ParentIntValues 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ParentIntValues() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecIntValueConditionResponseOutput

The spec for matching values from a parent parameter of `INTEGER` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpec 

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpec struct {
	// A default value for a `DISCRETE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. It automatically rounds to the nearest feasible discrete point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	DefaultValue *float64 `pulumi:"defaultValue"`
	// A list of possible values. The list should be in increasing order and at least 1e-10 apart. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
	Values []float64 `pulumi:"values"`
}

Value specification for a parameter in `DISCRETE` type.

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs 

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs struct {
	// A default value for a `DISCRETE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. It automatically rounds to the nearest feasible discrete point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	DefaultValue pulumi.Float64PtrInput `pulumi:"defaultValue"`
	// A list of possible values. The list should be in increasing order and at least 1e-10 apart. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
	Values pulumi.Float64ArrayInput `pulumi:"values"`
}

Value specification for a parameter in `DISCRETE` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs and GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecInput` via: 

GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs{...}

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput struct{ *pulumi.OutputState }

Value specification for a parameter in `DISCRETE` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) DefaultValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) DefaultValue() pulumi.Float64PtrOutput

A default value for a `DISCRETE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. It automatically rounds to the nearest feasible discrete point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput) Values() pulumi.Float64ArrayOutput

A list of possible values. The list should be in increasing order and at least 1e-10 apart. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs, GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtr and GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrInput` via: 

        GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtr 

func GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtr(v *GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecArgs) GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrInput

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput) DefaultValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput) DefaultValue() pulumi.Float64PtrOutput

A default value for a `DISCRETE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. It automatically rounds to the nearest feasible discrete point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput) Values() pulumi.Float64ArrayOutput

A list of possible values. The list should be in increasing order and at least 1e-10 apart. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponse 

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponse struct {
	// A default value for a `DISCRETE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. It automatically rounds to the nearest feasible discrete point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	DefaultValue float64 `pulumi:"defaultValue"`
	// A list of possible values. The list should be in increasing order and at least 1e-10 apart. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
	Values []float64 `pulumi:"values"`
}

Value specification for a parameter in `DISCRETE` type.

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput struct{ *pulumi.OutputState }

Value specification for a parameter in `DISCRETE` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput) DefaultValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput) DefaultValue() pulumi.Float64Output

A default value for a `DISCRETE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. It automatically rounds to the nearest feasible discrete point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput) Values 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput) Values() pulumi.Float64ArrayOutput

A list of possible values. The list should be in increasing order and at least 1e-10 apart. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpec 

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpec struct {
	// A default value for a `DOUBLE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	DefaultValue *float64 `pulumi:"defaultValue"`
	// Inclusive maximum value of the parameter.
	MaxValue float64 `pulumi:"maxValue"`
	// Inclusive minimum value of the parameter.
	MinValue float64 `pulumi:"minValue"`
}

Value specification for a parameter in `DOUBLE` type.

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs 

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs struct {
	// A default value for a `DOUBLE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	DefaultValue pulumi.Float64PtrInput `pulumi:"defaultValue"`
	// Inclusive maximum value of the parameter.
	MaxValue pulumi.Float64Input `pulumi:"maxValue"`
	// Inclusive minimum value of the parameter.
	MinValue pulumi.Float64Input `pulumi:"minValue"`
}

Value specification for a parameter in `DOUBLE` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs and GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecInput` via: 

GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs{...}

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput struct{ *pulumi.OutputState }

Value specification for a parameter in `DOUBLE` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) DefaultValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) DefaultValue() pulumi.Float64PtrOutput

A default value for a `DOUBLE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) MaxValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) MaxValue() pulumi.Float64Output

Inclusive maximum value of the parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) MinValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) MinValue() pulumi.Float64Output

Inclusive minimum value of the parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs, GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtr and GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrInput` via: 

        GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtr 

func GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtr(v *GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecArgs) GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrInput

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) DefaultValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) DefaultValue() pulumi.Float64PtrOutput

A default value for a `DOUBLE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) MaxValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) MaxValue() pulumi.Float64PtrOutput

Inclusive maximum value of the parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) MinValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) MinValue() pulumi.Float64PtrOutput

Inclusive minimum value of the parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponse 

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponse struct {
	// A default value for a `DOUBLE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	DefaultValue float64 `pulumi:"defaultValue"`
	// Inclusive maximum value of the parameter.
	MaxValue float64 `pulumi:"maxValue"`
	// Inclusive minimum value of the parameter.
	MinValue float64 `pulumi:"minValue"`
}

Value specification for a parameter in `DOUBLE` type.

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput struct{ *pulumi.OutputState }

Value specification for a parameter in `DOUBLE` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput) DefaultValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput) DefaultValue() pulumi.Float64Output

A default value for a `DOUBLE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput) MaxValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput) MaxValue() pulumi.Float64Output

Inclusive maximum value of the parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput) MinValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput) MinValue() pulumi.Float64Output

Inclusive minimum value of the parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput() GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecArgs and GoogleCloudAiplatformV1StudySpecParameterSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecInput` via: 

GoogleCloudAiplatformV1StudySpecParameterSpecArgs{...}

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpec 

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpec struct {
	// A default value for an `INTEGER` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	DefaultValue *string `pulumi:"defaultValue"`
	// Inclusive maximum value of the parameter.
	MaxValue string `pulumi:"maxValue"`
	// Inclusive minimum value of the parameter.
	MinValue string `pulumi:"minValue"`
}

Value specification for a parameter in `INTEGER` type.

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs 

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs struct {
	// A default value for an `INTEGER` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	DefaultValue pulumi.StringPtrInput `pulumi:"defaultValue"`
	// Inclusive maximum value of the parameter.
	MaxValue pulumi.StringInput `pulumi:"maxValue"`
	// Inclusive minimum value of the parameter.
	MinValue pulumi.StringInput `pulumi:"minValue"`
}

Value specification for a parameter in `INTEGER` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs and GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecInput` via: 

GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs{...}

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput struct{ *pulumi.OutputState }

Value specification for a parameter in `INTEGER` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) DefaultValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) DefaultValue() pulumi.StringPtrOutput

A default value for an `INTEGER` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) MaxValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) MaxValue() pulumi.StringOutput

Inclusive maximum value of the parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) MinValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) MinValue() pulumi.StringOutput

Inclusive minimum value of the parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs, GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtr and GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrInput` via: 

        GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtr 

func GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtr(v *GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecArgs) GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrInput

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) DefaultValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) DefaultValue() pulumi.StringPtrOutput

A default value for an `INTEGER` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) MaxValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) MaxValue() pulumi.StringPtrOutput

Inclusive maximum value of the parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) MinValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) MinValue() pulumi.StringPtrOutput

Inclusive minimum value of the parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponse 

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponse struct {
	// A default value for an `INTEGER` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	DefaultValue string `pulumi:"defaultValue"`
	// Inclusive maximum value of the parameter.
	MaxValue string `pulumi:"maxValue"`
	// Inclusive minimum value of the parameter.
	MinValue string `pulumi:"minValue"`
}

Value specification for a parameter in `INTEGER` type.

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput struct{ *pulumi.OutputState }

Value specification for a parameter in `INTEGER` type.

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput) DefaultValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput) DefaultValue() pulumi.StringOutput

A default value for an `INTEGER` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput) MaxValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput) MaxValue() pulumi.StringOutput

Inclusive maximum value of the parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput) MinValue 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput) MinValue() pulumi.StringOutput

Inclusive minimum value of the parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput() GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecOutput struct{ *pulumi.OutputState }

Represents a single parameter to optimize.

func (GoogleCloudAiplatformV1StudySpecParameterSpecOutput) CategoricalValueSpec 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecOutput) CategoricalValueSpec() GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecPtrOutput

The value spec for a 'CATEGORICAL' parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecOutput) ConditionalParameterSpecs 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecOutput) ConditionalParameterSpecs() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecArrayOutput

A conditional parameter node is active if the parameter's value matches the conditional node's parent_value_condition. If two items in conditional_parameter_specs have the same name, they must have disjoint parent_value_condition.

func (GoogleCloudAiplatformV1StudySpecParameterSpecOutput) DiscreteValueSpec 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecOutput) DiscreteValueSpec() GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecPtrOutput

The value spec for a 'DISCRETE' parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecOutput) DoubleValueSpec 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecOutput) DoubleValueSpec() GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecPtrOutput

The value spec for a 'DOUBLE' parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecOutput) IntegerValueSpec 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecOutput) IntegerValueSpec() GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecPtrOutput

The value spec for an 'INTEGER' parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecOutput) ParameterId 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecOutput) ParameterId() pulumi.StringOutput

The ID of the parameter. Must not contain whitespaces and must be unique amongst all ParameterSpecs.

func (GoogleCloudAiplatformV1StudySpecParameterSpecOutput) ScaleType 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecOutput) ScaleType() GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput

How the parameter should be scaled. Leave unset for `CATEGORICAL` parameters.

func (GoogleCloudAiplatformV1StudySpecParameterSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecOutput() GoogleCloudAiplatformV1StudySpecParameterSpecOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecResponse 

type GoogleCloudAiplatformV1StudySpecParameterSpecResponse struct {
	// The value spec for a 'CATEGORICAL' parameter.
	CategoricalValueSpec GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponse `pulumi:"categoricalValueSpec"`
	// A conditional parameter node is active if the parameter's value matches the conditional node's parent_value_condition. If two items in conditional_parameter_specs have the same name, they must have disjoint parent_value_condition.
	ConditionalParameterSpecs []GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponse `pulumi:"conditionalParameterSpecs"`
	// The value spec for a 'DISCRETE' parameter.
	DiscreteValueSpec GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponse `pulumi:"discreteValueSpec"`
	// The value spec for a 'DOUBLE' parameter.
	DoubleValueSpec GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponse `pulumi:"doubleValueSpec"`
	// The value spec for an 'INTEGER' parameter.
	IntegerValueSpec GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponse `pulumi:"integerValueSpec"`
	// The ID of the parameter. Must not contain whitespaces and must be unique amongst all ParameterSpecs.
	ParameterId string `pulumi:"parameterId"`
	// How the parameter should be scaled. Leave unset for `CATEGORICAL` parameters.
	ScaleType string `pulumi:"scaleType"`
}

Represents a single parameter to optimize.

type GoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput() GoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput struct{ *pulumi.OutputState }

Represents a single parameter to optimize.

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) CategoricalValueSpec 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) CategoricalValueSpec() GoogleCloudAiplatformV1StudySpecParameterSpecCategoricalValueSpecResponseOutput

The value spec for a 'CATEGORICAL' parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) ConditionalParameterSpecs 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) ConditionalParameterSpecs() GoogleCloudAiplatformV1StudySpecParameterSpecConditionalParameterSpecResponseArrayOutput

A conditional parameter node is active if the parameter's value matches the conditional node's parent_value_condition. If two items in conditional_parameter_specs have the same name, they must have disjoint parent_value_condition.

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) DiscreteValueSpec 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) DiscreteValueSpec() GoogleCloudAiplatformV1StudySpecParameterSpecDiscreteValueSpecResponseOutput

The value spec for a 'DISCRETE' parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) DoubleValueSpec 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) DoubleValueSpec() GoogleCloudAiplatformV1StudySpecParameterSpecDoubleValueSpecResponseOutput

The value spec for a 'DOUBLE' parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) IntegerValueSpec 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) IntegerValueSpec() GoogleCloudAiplatformV1StudySpecParameterSpecIntegerValueSpecResponseOutput

The value spec for an 'INTEGER' parameter.

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) ParameterId 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) ParameterId() pulumi.StringOutput

The ID of the parameter. Must not contain whitespaces and must be unique amongst all ParameterSpecs.

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) ScaleType 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) ScaleType() pulumi.StringOutput

How the parameter should be scaled. Leave unset for `CATEGORICAL` parameters.

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput() GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecResponseOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecScaleType 

type GoogleCloudAiplatformV1StudySpecParameterSpecScaleType string

How the parameter should be scaled. Leave unset for `CATEGORICAL` parameters.

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput 

func (e GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput() GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput 

func (e GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToStringOutput 

func (e GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToStringOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToStringPtrOutput 

func (e GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToStringPtrOutputWithContext 

func (e GoogleCloudAiplatformV1StudySpecParameterSpecScaleType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput() GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput
}

GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeInput is an input type that accepts GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeArgs and GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeInput` via: 

GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeArgs{...}

type GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput() GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToStringOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToStringOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrInput 

type GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput
	ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput
}

func GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtr 

func GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtr(v string) GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrInput

type GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput 

type GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput) Elem() GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypeOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput() GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput) ToGoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput) ToStringPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput) ToStringPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecParameterSpecScaleTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudAiplatformV1StudySpecResponse 

type GoogleCloudAiplatformV1StudySpecResponse struct {
	// The search algorithm specified for the Study.
	Algorithm string `pulumi:"algorithm"`
	// The automated early stopping spec using convex stopping rule.
	ConvexAutomatedStoppingSpec GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponse `pulumi:"convexAutomatedStoppingSpec"`
	// The automated early stopping spec using decay curve rule.
	DecayCurveStoppingSpec GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponse `pulumi:"decayCurveStoppingSpec"`
	// Describe which measurement selection type will be used
	MeasurementSelectionType string `pulumi:"measurementSelectionType"`
	// The automated early stopping spec using median rule.
	MedianAutomatedStoppingSpec GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponse `pulumi:"medianAutomatedStoppingSpec"`
	// Metric specs for the Study.
	Metrics []GoogleCloudAiplatformV1StudySpecMetricSpecResponse `pulumi:"metrics"`
	// The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.
	ObservationNoise string `pulumi:"observationNoise"`
	// The set of parameters to tune.
	Parameters []GoogleCloudAiplatformV1StudySpecParameterSpecResponse `pulumi:"parameters"`
	// Conditions for automated stopping of a Study. Enable automated stopping by configuring at least one condition.
	StudyStoppingConfig GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponse `pulumi:"studyStoppingConfig"`
}

Represents specification of a Study.

type GoogleCloudAiplatformV1StudySpecResponseOutput 

type GoogleCloudAiplatformV1StudySpecResponseOutput struct{ *pulumi.OutputState }

Represents specification of a Study.

func (GoogleCloudAiplatformV1StudySpecResponseOutput) Algorithm 

func (o GoogleCloudAiplatformV1StudySpecResponseOutput) Algorithm() pulumi.StringOutput

The search algorithm specified for the Study.

func (GoogleCloudAiplatformV1StudySpecResponseOutput) ConvexAutomatedStoppingSpec 

func (o GoogleCloudAiplatformV1StudySpecResponseOutput) ConvexAutomatedStoppingSpec() GoogleCloudAiplatformV1StudySpecConvexAutomatedStoppingSpecResponseOutput

The automated early stopping spec using convex stopping rule.

func (GoogleCloudAiplatformV1StudySpecResponseOutput) DecayCurveStoppingSpec 

func (o GoogleCloudAiplatformV1StudySpecResponseOutput) DecayCurveStoppingSpec() GoogleCloudAiplatformV1StudySpecDecayCurveAutomatedStoppingSpecResponseOutput

The automated early stopping spec using decay curve rule.

func (GoogleCloudAiplatformV1StudySpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecResponseOutput) MeasurementSelectionType 

func (o GoogleCloudAiplatformV1StudySpecResponseOutput) MeasurementSelectionType() pulumi.StringOutput

Describe which measurement selection type will be used

func (GoogleCloudAiplatformV1StudySpecResponseOutput) MedianAutomatedStoppingSpec 

func (o GoogleCloudAiplatformV1StudySpecResponseOutput) MedianAutomatedStoppingSpec() GoogleCloudAiplatformV1StudySpecMedianAutomatedStoppingSpecResponseOutput

The automated early stopping spec using median rule.

func (GoogleCloudAiplatformV1StudySpecResponseOutput) Metrics 

func (o GoogleCloudAiplatformV1StudySpecResponseOutput) Metrics() GoogleCloudAiplatformV1StudySpecMetricSpecResponseArrayOutput

Metric specs for the Study.

func (GoogleCloudAiplatformV1StudySpecResponseOutput) ObservationNoise 

func (o GoogleCloudAiplatformV1StudySpecResponseOutput) ObservationNoise() pulumi.StringOutput

The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline.

func (GoogleCloudAiplatformV1StudySpecResponseOutput) Parameters 

func (o GoogleCloudAiplatformV1StudySpecResponseOutput) Parameters() GoogleCloudAiplatformV1StudySpecParameterSpecResponseArrayOutput

The set of parameters to tune.

func (GoogleCloudAiplatformV1StudySpecResponseOutput) StudyStoppingConfig 

func (o GoogleCloudAiplatformV1StudySpecResponseOutput) StudyStoppingConfig() GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput

Conditions for automated stopping of a Study. Enable automated stopping by configuring at least one condition.

func (GoogleCloudAiplatformV1StudySpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecResponseOutput() GoogleCloudAiplatformV1StudySpecResponseOutput

func (GoogleCloudAiplatformV1StudySpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecResponseOutput) ToGoogleCloudAiplatformV1StudySpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecResponseOutput

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfig 

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfig struct {
	// If the objective value has not improved for this much time, stop the study. WARNING: Effective only for single-objective studies.
	MaxDurationNoProgress *string `pulumi:"maxDurationNoProgress"`
	// If there are more than this many trials, stop the study.
	MaxNumTrials *int `pulumi:"maxNumTrials"`
	// If the objective value has not improved for this many consecutive trials, stop the study. WARNING: Effective only for single-objective studies.
	MaxNumTrialsNoProgress *int `pulumi:"maxNumTrialsNoProgress"`
	// If the specified time or duration has passed, stop the study.
	MaximumRuntimeConstraint *GoogleCloudAiplatformV1StudyTimeConstraint `pulumi:"maximumRuntimeConstraint"`
	// If there are fewer than this many COMPLETED trials, do not stop the study.
	MinNumTrials *int `pulumi:"minNumTrials"`
	// Each "stopping rule" in this proto specifies an "if" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting `min_num_trials=5` and `always_stop_after= 1 hour` means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose "if" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to _resume_ a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study.
	MinimumRuntimeConstraint *GoogleCloudAiplatformV1StudyTimeConstraint `pulumi:"minimumRuntimeConstraint"`
	// If true, a Study enters STOPPING_ASAP whenever it would normally enters STOPPING state. The bottom line is: set to true if you want to interrupt on-going evaluations of Trials as soon as the study stopping condition is met. (Please see Study.State documentation for the source of truth).
	ShouldStopAsap *bool `pulumi:"shouldStopAsap"`
}

The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection.

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs 

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs struct {
	// If the objective value has not improved for this much time, stop the study. WARNING: Effective only for single-objective studies.
	MaxDurationNoProgress pulumi.StringPtrInput `pulumi:"maxDurationNoProgress"`
	// If there are more than this many trials, stop the study.
	MaxNumTrials pulumi.IntPtrInput `pulumi:"maxNumTrials"`
	// If the objective value has not improved for this many consecutive trials, stop the study. WARNING: Effective only for single-objective studies.
	MaxNumTrialsNoProgress pulumi.IntPtrInput `pulumi:"maxNumTrialsNoProgress"`
	// If the specified time or duration has passed, stop the study.
	MaximumRuntimeConstraint GoogleCloudAiplatformV1StudyTimeConstraintPtrInput `pulumi:"maximumRuntimeConstraint"`
	// If there are fewer than this many COMPLETED trials, do not stop the study.
	MinNumTrials pulumi.IntPtrInput `pulumi:"minNumTrials"`
	// Each "stopping rule" in this proto specifies an "if" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting `min_num_trials=5` and `always_stop_after= 1 hour` means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose "if" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to _resume_ a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study.
	MinimumRuntimeConstraint GoogleCloudAiplatformV1StudyTimeConstraintPtrInput `pulumi:"minimumRuntimeConstraint"`
	// If true, a Study enters STOPPING_ASAP whenever it would normally enters STOPPING state. The bottom line is: set to true if you want to interrupt on-going evaluations of Trials as soon as the study stopping condition is met. (Please see Study.State documentation for the source of truth).
	ShouldStopAsap pulumi.BoolPtrInput `pulumi:"shouldStopAsap"`
}

The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs) ElementType 

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput 

func (i GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput() GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput 

func (i GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput() GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigInput 

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput() GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput
	ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput
}

GoogleCloudAiplatformV1StudySpecStudyStoppingConfigInput is an input type that accepts GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs and GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecStudyStoppingConfigInput` via: 

GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs{...}

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput 

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput struct{ *pulumi.OutputState }

The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) MaxDurationNoProgress 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) MaxDurationNoProgress() pulumi.StringPtrOutput

If the objective value has not improved for this much time, stop the study. WARNING: Effective only for single-objective studies.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) MaxNumTrials 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) MaxNumTrials() pulumi.IntPtrOutput

If there are more than this many trials, stop the study.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) MaxNumTrialsNoProgress 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) MaxNumTrialsNoProgress() pulumi.IntPtrOutput

If the objective value has not improved for this many consecutive trials, stop the study. WARNING: Effective only for single-objective studies.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) MaximumRuntimeConstraint 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) MaximumRuntimeConstraint() GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput

If the specified time or duration has passed, stop the study.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) MinNumTrials 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) MinNumTrials() pulumi.IntPtrOutput

If there are fewer than this many COMPLETED trials, do not stop the study.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) MinimumRuntimeConstraint 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) MinimumRuntimeConstraint() GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput

Each "stopping rule" in this proto specifies an "if" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting `min_num_trials=5` and `always_stop_after= 1 hour` means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose "if" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to _resume_ a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) ShouldStopAsap 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) ShouldStopAsap() pulumi.BoolPtrOutput

If true, a Study enters STOPPING_ASAP whenever it would normally enters STOPPING state. The bottom line is: set to true if you want to interrupt on-going evaluations of Trials as soon as the study stopping condition is met. (Please see Study.State documentation for the source of truth).

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput() GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput() GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrInput 

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput() GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput
	ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput
}

GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs, GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtr and GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrInput` via: 

        GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtr 

func GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtr(v *GoogleCloudAiplatformV1StudySpecStudyStoppingConfigArgs) GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrInput

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput 

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) Elem() GoogleCloudAiplatformV1StudySpecStudyStoppingConfigOutput

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) MaxDurationNoProgress 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) MaxDurationNoProgress() pulumi.StringPtrOutput

If the objective value has not improved for this much time, stop the study. WARNING: Effective only for single-objective studies.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) MaxNumTrials 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) MaxNumTrials() pulumi.IntPtrOutput

If there are more than this many trials, stop the study.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) MaxNumTrialsNoProgress 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) MaxNumTrialsNoProgress() pulumi.IntPtrOutput

If the objective value has not improved for this many consecutive trials, stop the study. WARNING: Effective only for single-objective studies.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) MaximumRuntimeConstraint 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) MaximumRuntimeConstraint() GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput

If the specified time or duration has passed, stop the study.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) MinNumTrials 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) MinNumTrials() pulumi.IntPtrOutput

If there are fewer than this many COMPLETED trials, do not stop the study.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) MinimumRuntimeConstraint 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) MinimumRuntimeConstraint() GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput

Each "stopping rule" in this proto specifies an "if" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting `min_num_trials=5` and `always_stop_after= 1 hour` means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose "if" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to _resume_ a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) ShouldStopAsap 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) ShouldStopAsap() pulumi.BoolPtrOutput

If true, a Study enters STOPPING_ASAP whenever it would normally enters STOPPING state. The bottom line is: set to true if you want to interrupt on-going evaluations of Trials as soon as the study stopping condition is met. (Please see Study.State documentation for the source of truth).

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput() GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecStudyStoppingConfigPtrOutput

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponse 

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponse struct {
	// If the objective value has not improved for this much time, stop the study. WARNING: Effective only for single-objective studies.
	MaxDurationNoProgress string `pulumi:"maxDurationNoProgress"`
	// If there are more than this many trials, stop the study.
	MaxNumTrials int `pulumi:"maxNumTrials"`
	// If the objective value has not improved for this many consecutive trials, stop the study. WARNING: Effective only for single-objective studies.
	MaxNumTrialsNoProgress int `pulumi:"maxNumTrialsNoProgress"`
	// If the specified time or duration has passed, stop the study.
	MaximumRuntimeConstraint GoogleCloudAiplatformV1StudyTimeConstraintResponse `pulumi:"maximumRuntimeConstraint"`
	// If there are fewer than this many COMPLETED trials, do not stop the study.
	MinNumTrials int `pulumi:"minNumTrials"`
	// Each "stopping rule" in this proto specifies an "if" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting `min_num_trials=5` and `always_stop_after= 1 hour` means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose "if" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to _resume_ a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study.
	MinimumRuntimeConstraint GoogleCloudAiplatformV1StudyTimeConstraintResponse `pulumi:"minimumRuntimeConstraint"`
	// If true, a Study enters STOPPING_ASAP whenever it would normally enters STOPPING state. The bottom line is: set to true if you want to interrupt on-going evaluations of Trials as soon as the study stopping condition is met. (Please see Study.State documentation for the source of truth).
	ShouldStopAsap bool `pulumi:"shouldStopAsap"`
}

The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection.

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput 

type GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput struct{ *pulumi.OutputState }

The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) MaxDurationNoProgress 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) MaxDurationNoProgress() pulumi.StringOutput

If the objective value has not improved for this much time, stop the study. WARNING: Effective only for single-objective studies.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) MaxNumTrials 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) MaxNumTrials() pulumi.IntOutput

If there are more than this many trials, stop the study.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) MaxNumTrialsNoProgress 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) MaxNumTrialsNoProgress() pulumi.IntOutput

If the objective value has not improved for this many consecutive trials, stop the study. WARNING: Effective only for single-objective studies.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) MaximumRuntimeConstraint 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) MaximumRuntimeConstraint() GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput

If the specified time or duration has passed, stop the study.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) MinNumTrials 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) MinNumTrials() pulumi.IntOutput

If there are fewer than this many COMPLETED trials, do not stop the study.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) MinimumRuntimeConstraint 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) MinimumRuntimeConstraint() GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput

Each "stopping rule" in this proto specifies an "if" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting `min_num_trials=5` and `always_stop_after= 1 hour` means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose "if" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to _resume_ a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study.

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) ShouldStopAsap 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) ShouldStopAsap() pulumi.BoolOutput

If true, a Study enters STOPPING_ASAP whenever it would normally enters STOPPING state. The bottom line is: set to true if you want to interrupt on-going evaluations of Trials as soon as the study stopping condition is met. (Please see Study.State documentation for the source of truth).

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput() GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput

func (GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput) ToGoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudySpecStudyStoppingConfigResponseOutput

type GoogleCloudAiplatformV1StudyTimeConstraint 

type GoogleCloudAiplatformV1StudyTimeConstraint struct {
	// Compares the wallclock time to this time. Must use UTC timezone.
	EndTime *string `pulumi:"endTime"`
	// Counts the wallclock time passed since the creation of this Study.
	MaxDuration *string `pulumi:"maxDuration"`
}

Time-based Constraint for Study

type GoogleCloudAiplatformV1StudyTimeConstraintArgs 

type GoogleCloudAiplatformV1StudyTimeConstraintArgs struct {
	// Compares the wallclock time to this time. Must use UTC timezone.
	EndTime pulumi.StringPtrInput `pulumi:"endTime"`
	// Counts the wallclock time passed since the creation of this Study.
	MaxDuration pulumi.StringPtrInput `pulumi:"maxDuration"`
}

Time-based Constraint for Study

func (GoogleCloudAiplatformV1StudyTimeConstraintArgs) ElementType 

func (GoogleCloudAiplatformV1StudyTimeConstraintArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudyTimeConstraintArgs) ToGoogleCloudAiplatformV1StudyTimeConstraintOutput 

func (i GoogleCloudAiplatformV1StudyTimeConstraintArgs) ToGoogleCloudAiplatformV1StudyTimeConstraintOutput() GoogleCloudAiplatformV1StudyTimeConstraintOutput

func (GoogleCloudAiplatformV1StudyTimeConstraintArgs) ToGoogleCloudAiplatformV1StudyTimeConstraintOutputWithContext 

func (i GoogleCloudAiplatformV1StudyTimeConstraintArgs) ToGoogleCloudAiplatformV1StudyTimeConstraintOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudyTimeConstraintOutput

func (GoogleCloudAiplatformV1StudyTimeConstraintArgs) ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutput 

func (i GoogleCloudAiplatformV1StudyTimeConstraintArgs) ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutput() GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput

func (GoogleCloudAiplatformV1StudyTimeConstraintArgs) ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutputWithContext 

func (i GoogleCloudAiplatformV1StudyTimeConstraintArgs) ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput

type GoogleCloudAiplatformV1StudyTimeConstraintInput 

type GoogleCloudAiplatformV1StudyTimeConstraintInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudyTimeConstraintOutput() GoogleCloudAiplatformV1StudyTimeConstraintOutput
	ToGoogleCloudAiplatformV1StudyTimeConstraintOutputWithContext(context.Context) GoogleCloudAiplatformV1StudyTimeConstraintOutput
}

GoogleCloudAiplatformV1StudyTimeConstraintInput is an input type that accepts GoogleCloudAiplatformV1StudyTimeConstraintArgs and GoogleCloudAiplatformV1StudyTimeConstraintOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudyTimeConstraintInput` via: 

GoogleCloudAiplatformV1StudyTimeConstraintArgs{...}

type GoogleCloudAiplatformV1StudyTimeConstraintOutput 

type GoogleCloudAiplatformV1StudyTimeConstraintOutput struct{ *pulumi.OutputState }

Time-based Constraint for Study

func (GoogleCloudAiplatformV1StudyTimeConstraintOutput) ElementType 

func (GoogleCloudAiplatformV1StudyTimeConstraintOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudyTimeConstraintOutput) EndTime 

func (o GoogleCloudAiplatformV1StudyTimeConstraintOutput) EndTime() pulumi.StringPtrOutput

Compares the wallclock time to this time. Must use UTC timezone.

func (GoogleCloudAiplatformV1StudyTimeConstraintOutput) MaxDuration 

func (o GoogleCloudAiplatformV1StudyTimeConstraintOutput) MaxDuration() pulumi.StringPtrOutput

Counts the wallclock time passed since the creation of this Study.

func (GoogleCloudAiplatformV1StudyTimeConstraintOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintOutput 

func (o GoogleCloudAiplatformV1StudyTimeConstraintOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintOutput() GoogleCloudAiplatformV1StudyTimeConstraintOutput

func (GoogleCloudAiplatformV1StudyTimeConstraintOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintOutputWithContext 

func (o GoogleCloudAiplatformV1StudyTimeConstraintOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudyTimeConstraintOutput

func (GoogleCloudAiplatformV1StudyTimeConstraintOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutput 

func (o GoogleCloudAiplatformV1StudyTimeConstraintOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutput() GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput

func (GoogleCloudAiplatformV1StudyTimeConstraintOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudyTimeConstraintOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput

type GoogleCloudAiplatformV1StudyTimeConstraintPtrInput 

type GoogleCloudAiplatformV1StudyTimeConstraintPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutput() GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput
	ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput
}

GoogleCloudAiplatformV1StudyTimeConstraintPtrInput is an input type that accepts GoogleCloudAiplatformV1StudyTimeConstraintArgs, GoogleCloudAiplatformV1StudyTimeConstraintPtr and GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1StudyTimeConstraintPtrInput` via: 

        GoogleCloudAiplatformV1StudyTimeConstraintArgs{...}

or:

        nil

func GoogleCloudAiplatformV1StudyTimeConstraintPtr 

func GoogleCloudAiplatformV1StudyTimeConstraintPtr(v *GoogleCloudAiplatformV1StudyTimeConstraintArgs) GoogleCloudAiplatformV1StudyTimeConstraintPtrInput

type GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput 

type GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput) Elem 

func (o GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput) Elem() GoogleCloudAiplatformV1StudyTimeConstraintOutput

func (GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput) ElementType 

func (GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput) EndTime 

func (o GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput) EndTime() pulumi.StringPtrOutput

Compares the wallclock time to this time. Must use UTC timezone.

func (GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput) MaxDuration 

func (o GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput) MaxDuration() pulumi.StringPtrOutput

Counts the wallclock time passed since the creation of this Study.

func (GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutput 

func (o GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutput() GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput

func (GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutputWithContext 

func (o GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudyTimeConstraintPtrOutput

type GoogleCloudAiplatformV1StudyTimeConstraintResponse 

type GoogleCloudAiplatformV1StudyTimeConstraintResponse struct {
	// Compares the wallclock time to this time. Must use UTC timezone.
	EndTime string `pulumi:"endTime"`
	// Counts the wallclock time passed since the creation of this Study.
	MaxDuration string `pulumi:"maxDuration"`
}

Time-based Constraint for Study

type GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput 

type GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput struct{ *pulumi.OutputState }

Time-based Constraint for Study

func (GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput) ElementType 

func (GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput) EndTime 

func (o GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput) EndTime() pulumi.StringOutput

Compares the wallclock time to this time. Must use UTC timezone.

func (GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput) MaxDuration 

func (o GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput) MaxDuration() pulumi.StringOutput

Counts the wallclock time passed since the creation of this Study.

func (GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintResponseOutput 

func (o GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintResponseOutput() GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput

func (GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintResponseOutputWithContext 

func (o GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput) ToGoogleCloudAiplatformV1StudyTimeConstraintResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1StudyTimeConstraintResponseOutput

type GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponse 

type GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponse struct {
	// The largest blob sequence length (number of blobs) of all data points in this time series, if its ValueType is BLOB_SEQUENCE.
	MaxBlobSequenceLength string `pulumi:"maxBlobSequenceLength"`
	// Max step index of all data points within a TensorboardTimeSeries.
	MaxStep string `pulumi:"maxStep"`
	// Max wall clock timestamp of all data points within a TensorboardTimeSeries.
	MaxWallTime string `pulumi:"maxWallTime"`
}

Describes metadata for a TensorboardTimeSeries.

type GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput 

type GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput struct{ *pulumi.OutputState }

Describes metadata for a TensorboardTimeSeries.

func (GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput) ElementType 

func (GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput) MaxBlobSequenceLength 

func (o GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput) MaxBlobSequenceLength() pulumi.StringOutput

The largest blob sequence length (number of blobs) of all data points in this time series, if its ValueType is BLOB_SEQUENCE.

func (GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput) MaxStep 

func (o GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput) MaxStep() pulumi.StringOutput

Max step index of all data points within a TensorboardTimeSeries.

func (GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput) MaxWallTime 

func (o GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput) MaxWallTime() pulumi.StringOutput

Max wall clock timestamp of all data points within a TensorboardTimeSeries.

func (GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput) ToGoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput 

func (o GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput) ToGoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput() GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput

func (GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput) ToGoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutputWithContext 

func (o GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput) ToGoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput

type GoogleCloudAiplatformV1ThresholdConfig 

type GoogleCloudAiplatformV1ThresholdConfig struct {
	// Specify a threshold value that can trigger the alert. If this threshold config is for feature distribution distance: 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
	Value *float64 `pulumi:"value"`
}

The config for feature monitoring threshold.

type GoogleCloudAiplatformV1ThresholdConfigArgs 

type GoogleCloudAiplatformV1ThresholdConfigArgs struct {
	// Specify a threshold value that can trigger the alert. If this threshold config is for feature distribution distance: 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
	Value pulumi.Float64PtrInput `pulumi:"value"`
}

The config for feature monitoring threshold.

func (GoogleCloudAiplatformV1ThresholdConfigArgs) ElementType 

func (GoogleCloudAiplatformV1ThresholdConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ThresholdConfigArgs) ToGoogleCloudAiplatformV1ThresholdConfigOutput 

func (i GoogleCloudAiplatformV1ThresholdConfigArgs) ToGoogleCloudAiplatformV1ThresholdConfigOutput() GoogleCloudAiplatformV1ThresholdConfigOutput

func (GoogleCloudAiplatformV1ThresholdConfigArgs) ToGoogleCloudAiplatformV1ThresholdConfigOutputWithContext 

func (i GoogleCloudAiplatformV1ThresholdConfigArgs) ToGoogleCloudAiplatformV1ThresholdConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ThresholdConfigOutput

func (GoogleCloudAiplatformV1ThresholdConfigArgs) ToGoogleCloudAiplatformV1ThresholdConfigPtrOutput 

func (i GoogleCloudAiplatformV1ThresholdConfigArgs) ToGoogleCloudAiplatformV1ThresholdConfigPtrOutput() GoogleCloudAiplatformV1ThresholdConfigPtrOutput

func (GoogleCloudAiplatformV1ThresholdConfigArgs) ToGoogleCloudAiplatformV1ThresholdConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1ThresholdConfigArgs) ToGoogleCloudAiplatformV1ThresholdConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ThresholdConfigPtrOutput

type GoogleCloudAiplatformV1ThresholdConfigInput 

type GoogleCloudAiplatformV1ThresholdConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ThresholdConfigOutput() GoogleCloudAiplatformV1ThresholdConfigOutput
	ToGoogleCloudAiplatformV1ThresholdConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1ThresholdConfigOutput
}

GoogleCloudAiplatformV1ThresholdConfigInput is an input type that accepts GoogleCloudAiplatformV1ThresholdConfigArgs and GoogleCloudAiplatformV1ThresholdConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ThresholdConfigInput` via: 

GoogleCloudAiplatformV1ThresholdConfigArgs{...}

type GoogleCloudAiplatformV1ThresholdConfigOutput 

type GoogleCloudAiplatformV1ThresholdConfigOutput struct{ *pulumi.OutputState }

The config for feature monitoring threshold.

func (GoogleCloudAiplatformV1ThresholdConfigOutput) ElementType 

func (GoogleCloudAiplatformV1ThresholdConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ThresholdConfigOutput) ToGoogleCloudAiplatformV1ThresholdConfigOutput 

func (o GoogleCloudAiplatformV1ThresholdConfigOutput) ToGoogleCloudAiplatformV1ThresholdConfigOutput() GoogleCloudAiplatformV1ThresholdConfigOutput

func (GoogleCloudAiplatformV1ThresholdConfigOutput) ToGoogleCloudAiplatformV1ThresholdConfigOutputWithContext 

func (o GoogleCloudAiplatformV1ThresholdConfigOutput) ToGoogleCloudAiplatformV1ThresholdConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ThresholdConfigOutput

func (GoogleCloudAiplatformV1ThresholdConfigOutput) ToGoogleCloudAiplatformV1ThresholdConfigPtrOutput 

func (o GoogleCloudAiplatformV1ThresholdConfigOutput) ToGoogleCloudAiplatformV1ThresholdConfigPtrOutput() GoogleCloudAiplatformV1ThresholdConfigPtrOutput

func (GoogleCloudAiplatformV1ThresholdConfigOutput) ToGoogleCloudAiplatformV1ThresholdConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ThresholdConfigOutput) ToGoogleCloudAiplatformV1ThresholdConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ThresholdConfigPtrOutput

func (GoogleCloudAiplatformV1ThresholdConfigOutput) Value 

func (o GoogleCloudAiplatformV1ThresholdConfigOutput) Value() pulumi.Float64PtrOutput

Specify a threshold value that can trigger the alert. If this threshold config is for feature distribution distance: 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.

type GoogleCloudAiplatformV1ThresholdConfigPtrInput 

type GoogleCloudAiplatformV1ThresholdConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1ThresholdConfigPtrOutput() GoogleCloudAiplatformV1ThresholdConfigPtrOutput
	ToGoogleCloudAiplatformV1ThresholdConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1ThresholdConfigPtrOutput
}

GoogleCloudAiplatformV1ThresholdConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1ThresholdConfigArgs, GoogleCloudAiplatformV1ThresholdConfigPtr and GoogleCloudAiplatformV1ThresholdConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1ThresholdConfigPtrInput` via: 

        GoogleCloudAiplatformV1ThresholdConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1ThresholdConfigPtr 

func GoogleCloudAiplatformV1ThresholdConfigPtr(v *GoogleCloudAiplatformV1ThresholdConfigArgs) GoogleCloudAiplatformV1ThresholdConfigPtrInput

type GoogleCloudAiplatformV1ThresholdConfigPtrOutput 

type GoogleCloudAiplatformV1ThresholdConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1ThresholdConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1ThresholdConfigPtrOutput) Elem() GoogleCloudAiplatformV1ThresholdConfigOutput

func (GoogleCloudAiplatformV1ThresholdConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1ThresholdConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ThresholdConfigPtrOutput) ToGoogleCloudAiplatformV1ThresholdConfigPtrOutput 

func (o GoogleCloudAiplatformV1ThresholdConfigPtrOutput) ToGoogleCloudAiplatformV1ThresholdConfigPtrOutput() GoogleCloudAiplatformV1ThresholdConfigPtrOutput

func (GoogleCloudAiplatformV1ThresholdConfigPtrOutput) ToGoogleCloudAiplatformV1ThresholdConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1ThresholdConfigPtrOutput) ToGoogleCloudAiplatformV1ThresholdConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ThresholdConfigPtrOutput

func (GoogleCloudAiplatformV1ThresholdConfigPtrOutput) Value 

func (o GoogleCloudAiplatformV1ThresholdConfigPtrOutput) Value() pulumi.Float64PtrOutput

Specify a threshold value that can trigger the alert. If this threshold config is for feature distribution distance: 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.

type GoogleCloudAiplatformV1ThresholdConfigResponse 

type GoogleCloudAiplatformV1ThresholdConfigResponse struct {
	// Specify a threshold value that can trigger the alert. If this threshold config is for feature distribution distance: 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
	Value float64 `pulumi:"value"`
}

The config for feature monitoring threshold.

type GoogleCloudAiplatformV1ThresholdConfigResponseOutput 

type GoogleCloudAiplatformV1ThresholdConfigResponseOutput struct{ *pulumi.OutputState }

The config for feature monitoring threshold.

func (GoogleCloudAiplatformV1ThresholdConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1ThresholdConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1ThresholdConfigResponseOutput) ToGoogleCloudAiplatformV1ThresholdConfigResponseOutput 

func (o GoogleCloudAiplatformV1ThresholdConfigResponseOutput) ToGoogleCloudAiplatformV1ThresholdConfigResponseOutput() GoogleCloudAiplatformV1ThresholdConfigResponseOutput

func (GoogleCloudAiplatformV1ThresholdConfigResponseOutput) ToGoogleCloudAiplatformV1ThresholdConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1ThresholdConfigResponseOutput) ToGoogleCloudAiplatformV1ThresholdConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1ThresholdConfigResponseOutput

func (GoogleCloudAiplatformV1ThresholdConfigResponseOutput) Value 

func (o GoogleCloudAiplatformV1ThresholdConfigResponseOutput) Value() pulumi.Float64Output

Specify a threshold value that can trigger the alert. If this threshold config is for feature distribution distance: 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.

type GoogleCloudAiplatformV1TimestampSplit 

type GoogleCloudAiplatformV1TimestampSplit struct {
	// The key is a name of one of the Dataset's data columns. The values of the key (the values in the column) must be in RFC 3339 `date-time` format, where `time-offset` = `"Z"` (e.g. 1985-04-12T23:20:50.52Z). If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.
	Key string `pulumi:"key"`
	// The fraction of the input data that is to be used to evaluate the Model.
	TestFraction *float64 `pulumi:"testFraction"`
	// The fraction of the input data that is to be used to train the Model.
	TrainingFraction *float64 `pulumi:"trainingFraction"`
	// The fraction of the input data that is to be used to validate the Model.
	ValidationFraction *float64 `pulumi:"validationFraction"`
}

Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set. Supported only for tabular Datasets.

type GoogleCloudAiplatformV1TimestampSplitArgs 

type GoogleCloudAiplatformV1TimestampSplitArgs struct {
	// The key is a name of one of the Dataset's data columns. The values of the key (the values in the column) must be in RFC 3339 `date-time` format, where `time-offset` = `"Z"` (e.g. 1985-04-12T23:20:50.52Z). If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.
	Key pulumi.StringInput `pulumi:"key"`
	// The fraction of the input data that is to be used to evaluate the Model.
	TestFraction pulumi.Float64PtrInput `pulumi:"testFraction"`
	// The fraction of the input data that is to be used to train the Model.
	TrainingFraction pulumi.Float64PtrInput `pulumi:"trainingFraction"`
	// The fraction of the input data that is to be used to validate the Model.
	ValidationFraction pulumi.Float64PtrInput `pulumi:"validationFraction"`
}

Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set. Supported only for tabular Datasets.

func (GoogleCloudAiplatformV1TimestampSplitArgs) ElementType 

func (GoogleCloudAiplatformV1TimestampSplitArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1TimestampSplitArgs) ToGoogleCloudAiplatformV1TimestampSplitOutput 

func (i GoogleCloudAiplatformV1TimestampSplitArgs) ToGoogleCloudAiplatformV1TimestampSplitOutput() GoogleCloudAiplatformV1TimestampSplitOutput

func (GoogleCloudAiplatformV1TimestampSplitArgs) ToGoogleCloudAiplatformV1TimestampSplitOutputWithContext 

func (i GoogleCloudAiplatformV1TimestampSplitArgs) ToGoogleCloudAiplatformV1TimestampSplitOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TimestampSplitOutput

func (GoogleCloudAiplatformV1TimestampSplitArgs) ToGoogleCloudAiplatformV1TimestampSplitPtrOutput 

func (i GoogleCloudAiplatformV1TimestampSplitArgs) ToGoogleCloudAiplatformV1TimestampSplitPtrOutput() GoogleCloudAiplatformV1TimestampSplitPtrOutput

func (GoogleCloudAiplatformV1TimestampSplitArgs) ToGoogleCloudAiplatformV1TimestampSplitPtrOutputWithContext 

func (i GoogleCloudAiplatformV1TimestampSplitArgs) ToGoogleCloudAiplatformV1TimestampSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TimestampSplitPtrOutput

type GoogleCloudAiplatformV1TimestampSplitInput 

type GoogleCloudAiplatformV1TimestampSplitInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1TimestampSplitOutput() GoogleCloudAiplatformV1TimestampSplitOutput
	ToGoogleCloudAiplatformV1TimestampSplitOutputWithContext(context.Context) GoogleCloudAiplatformV1TimestampSplitOutput
}

GoogleCloudAiplatformV1TimestampSplitInput is an input type that accepts GoogleCloudAiplatformV1TimestampSplitArgs and GoogleCloudAiplatformV1TimestampSplitOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1TimestampSplitInput` via: 

GoogleCloudAiplatformV1TimestampSplitArgs{...}

type GoogleCloudAiplatformV1TimestampSplitOutput 

type GoogleCloudAiplatformV1TimestampSplitOutput struct{ *pulumi.OutputState }

Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set. Supported only for tabular Datasets.

func (GoogleCloudAiplatformV1TimestampSplitOutput) ElementType 

func (GoogleCloudAiplatformV1TimestampSplitOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1TimestampSplitOutput) Key 

func (o GoogleCloudAiplatformV1TimestampSplitOutput) Key() pulumi.StringOutput

The key is a name of one of the Dataset's data columns. The values of the key (the values in the column) must be in RFC 3339 `date-time` format, where `time-offset` = `"Z"` (e.g. 1985-04-12T23:20:50.52Z). If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.

func (GoogleCloudAiplatformV1TimestampSplitOutput) TestFraction 

func (o GoogleCloudAiplatformV1TimestampSplitOutput) TestFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to evaluate the Model.

func (GoogleCloudAiplatformV1TimestampSplitOutput) ToGoogleCloudAiplatformV1TimestampSplitOutput 

func (o GoogleCloudAiplatformV1TimestampSplitOutput) ToGoogleCloudAiplatformV1TimestampSplitOutput() GoogleCloudAiplatformV1TimestampSplitOutput

func (GoogleCloudAiplatformV1TimestampSplitOutput) ToGoogleCloudAiplatformV1TimestampSplitOutputWithContext 

func (o GoogleCloudAiplatformV1TimestampSplitOutput) ToGoogleCloudAiplatformV1TimestampSplitOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TimestampSplitOutput

func (GoogleCloudAiplatformV1TimestampSplitOutput) ToGoogleCloudAiplatformV1TimestampSplitPtrOutput 

func (o GoogleCloudAiplatformV1TimestampSplitOutput) ToGoogleCloudAiplatformV1TimestampSplitPtrOutput() GoogleCloudAiplatformV1TimestampSplitPtrOutput

func (GoogleCloudAiplatformV1TimestampSplitOutput) ToGoogleCloudAiplatformV1TimestampSplitPtrOutputWithContext 

func (o GoogleCloudAiplatformV1TimestampSplitOutput) ToGoogleCloudAiplatformV1TimestampSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TimestampSplitPtrOutput

func (GoogleCloudAiplatformV1TimestampSplitOutput) TrainingFraction 

func (o GoogleCloudAiplatformV1TimestampSplitOutput) TrainingFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to train the Model.

func (GoogleCloudAiplatformV1TimestampSplitOutput) ValidationFraction 

func (o GoogleCloudAiplatformV1TimestampSplitOutput) ValidationFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to validate the Model.

type GoogleCloudAiplatformV1TimestampSplitPtrInput 

type GoogleCloudAiplatformV1TimestampSplitPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1TimestampSplitPtrOutput() GoogleCloudAiplatformV1TimestampSplitPtrOutput
	ToGoogleCloudAiplatformV1TimestampSplitPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1TimestampSplitPtrOutput
}

GoogleCloudAiplatformV1TimestampSplitPtrInput is an input type that accepts GoogleCloudAiplatformV1TimestampSplitArgs, GoogleCloudAiplatformV1TimestampSplitPtr and GoogleCloudAiplatformV1TimestampSplitPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1TimestampSplitPtrInput` via: 

        GoogleCloudAiplatformV1TimestampSplitArgs{...}

or:

        nil

func GoogleCloudAiplatformV1TimestampSplitPtr 

func GoogleCloudAiplatformV1TimestampSplitPtr(v *GoogleCloudAiplatformV1TimestampSplitArgs) GoogleCloudAiplatformV1TimestampSplitPtrInput

type GoogleCloudAiplatformV1TimestampSplitPtrOutput 

type GoogleCloudAiplatformV1TimestampSplitPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1TimestampSplitPtrOutput) Elem 

func (o GoogleCloudAiplatformV1TimestampSplitPtrOutput) Elem() GoogleCloudAiplatformV1TimestampSplitOutput

func (GoogleCloudAiplatformV1TimestampSplitPtrOutput) ElementType 

func (GoogleCloudAiplatformV1TimestampSplitPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1TimestampSplitPtrOutput) Key 

func (o GoogleCloudAiplatformV1TimestampSplitPtrOutput) Key() pulumi.StringPtrOutput

The key is a name of one of the Dataset's data columns. The values of the key (the values in the column) must be in RFC 3339 `date-time` format, where `time-offset` = `"Z"` (e.g. 1985-04-12T23:20:50.52Z). If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.

func (GoogleCloudAiplatformV1TimestampSplitPtrOutput) TestFraction 

func (o GoogleCloudAiplatformV1TimestampSplitPtrOutput) TestFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to evaluate the Model.

func (GoogleCloudAiplatformV1TimestampSplitPtrOutput) ToGoogleCloudAiplatformV1TimestampSplitPtrOutput 

func (o GoogleCloudAiplatformV1TimestampSplitPtrOutput) ToGoogleCloudAiplatformV1TimestampSplitPtrOutput() GoogleCloudAiplatformV1TimestampSplitPtrOutput

func (GoogleCloudAiplatformV1TimestampSplitPtrOutput) ToGoogleCloudAiplatformV1TimestampSplitPtrOutputWithContext 

func (o GoogleCloudAiplatformV1TimestampSplitPtrOutput) ToGoogleCloudAiplatformV1TimestampSplitPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TimestampSplitPtrOutput

func (GoogleCloudAiplatformV1TimestampSplitPtrOutput) TrainingFraction 

func (o GoogleCloudAiplatformV1TimestampSplitPtrOutput) TrainingFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to train the Model.

func (GoogleCloudAiplatformV1TimestampSplitPtrOutput) ValidationFraction 

func (o GoogleCloudAiplatformV1TimestampSplitPtrOutput) ValidationFraction() pulumi.Float64PtrOutput

The fraction of the input data that is to be used to validate the Model.

type GoogleCloudAiplatformV1TimestampSplitResponse 

type GoogleCloudAiplatformV1TimestampSplitResponse struct {
	// The key is a name of one of the Dataset's data columns. The values of the key (the values in the column) must be in RFC 3339 `date-time` format, where `time-offset` = `"Z"` (e.g. 1985-04-12T23:20:50.52Z). If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.
	Key string `pulumi:"key"`
	// The fraction of the input data that is to be used to evaluate the Model.
	TestFraction float64 `pulumi:"testFraction"`
	// The fraction of the input data that is to be used to train the Model.
	TrainingFraction float64 `pulumi:"trainingFraction"`
	// The fraction of the input data that is to be used to validate the Model.
	ValidationFraction float64 `pulumi:"validationFraction"`
}

Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set. Supported only for tabular Datasets.

type GoogleCloudAiplatformV1TimestampSplitResponseOutput 

type GoogleCloudAiplatformV1TimestampSplitResponseOutput struct{ *pulumi.OutputState }

Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set. Supported only for tabular Datasets.

func (GoogleCloudAiplatformV1TimestampSplitResponseOutput) ElementType 

func (GoogleCloudAiplatformV1TimestampSplitResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1TimestampSplitResponseOutput) Key 

func (o GoogleCloudAiplatformV1TimestampSplitResponseOutput) Key() pulumi.StringOutput

The key is a name of one of the Dataset's data columns. The values of the key (the values in the column) must be in RFC 3339 `date-time` format, where `time-offset` = `"Z"` (e.g. 1985-04-12T23:20:50.52Z). If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline.

func (GoogleCloudAiplatformV1TimestampSplitResponseOutput) TestFraction 

func (o GoogleCloudAiplatformV1TimestampSplitResponseOutput) TestFraction() pulumi.Float64Output

The fraction of the input data that is to be used to evaluate the Model.

func (GoogleCloudAiplatformV1TimestampSplitResponseOutput) ToGoogleCloudAiplatformV1TimestampSplitResponseOutput 

func (o GoogleCloudAiplatformV1TimestampSplitResponseOutput) ToGoogleCloudAiplatformV1TimestampSplitResponseOutput() GoogleCloudAiplatformV1TimestampSplitResponseOutput

func (GoogleCloudAiplatformV1TimestampSplitResponseOutput) ToGoogleCloudAiplatformV1TimestampSplitResponseOutputWithContext 

func (o GoogleCloudAiplatformV1TimestampSplitResponseOutput) ToGoogleCloudAiplatformV1TimestampSplitResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TimestampSplitResponseOutput

func (GoogleCloudAiplatformV1TimestampSplitResponseOutput) TrainingFraction 

func (o GoogleCloudAiplatformV1TimestampSplitResponseOutput) TrainingFraction() pulumi.Float64Output

The fraction of the input data that is to be used to train the Model.

func (GoogleCloudAiplatformV1TimestampSplitResponseOutput) ValidationFraction 

func (o GoogleCloudAiplatformV1TimestampSplitResponseOutput) ValidationFraction() pulumi.Float64Output

The fraction of the input data that is to be used to validate the Model.

type GoogleCloudAiplatformV1TrainingConfig 

type GoogleCloudAiplatformV1TrainingConfig struct {
	// The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.
	TimeoutTrainingMilliHours *string `pulumi:"timeoutTrainingMilliHours"`
}

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

type GoogleCloudAiplatformV1TrainingConfigArgs 

type GoogleCloudAiplatformV1TrainingConfigArgs struct {
	// The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.
	TimeoutTrainingMilliHours pulumi.StringPtrInput `pulumi:"timeoutTrainingMilliHours"`
}

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

func (GoogleCloudAiplatformV1TrainingConfigArgs) ElementType 

func (GoogleCloudAiplatformV1TrainingConfigArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1TrainingConfigArgs) ToGoogleCloudAiplatformV1TrainingConfigOutput 

func (i GoogleCloudAiplatformV1TrainingConfigArgs) ToGoogleCloudAiplatformV1TrainingConfigOutput() GoogleCloudAiplatformV1TrainingConfigOutput

func (GoogleCloudAiplatformV1TrainingConfigArgs) ToGoogleCloudAiplatformV1TrainingConfigOutputWithContext 

func (i GoogleCloudAiplatformV1TrainingConfigArgs) ToGoogleCloudAiplatformV1TrainingConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TrainingConfigOutput

func (GoogleCloudAiplatformV1TrainingConfigArgs) ToGoogleCloudAiplatformV1TrainingConfigPtrOutput 

func (i GoogleCloudAiplatformV1TrainingConfigArgs) ToGoogleCloudAiplatformV1TrainingConfigPtrOutput() GoogleCloudAiplatformV1TrainingConfigPtrOutput

func (GoogleCloudAiplatformV1TrainingConfigArgs) ToGoogleCloudAiplatformV1TrainingConfigPtrOutputWithContext 

func (i GoogleCloudAiplatformV1TrainingConfigArgs) ToGoogleCloudAiplatformV1TrainingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TrainingConfigPtrOutput

type GoogleCloudAiplatformV1TrainingConfigInput 

type GoogleCloudAiplatformV1TrainingConfigInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1TrainingConfigOutput() GoogleCloudAiplatformV1TrainingConfigOutput
	ToGoogleCloudAiplatformV1TrainingConfigOutputWithContext(context.Context) GoogleCloudAiplatformV1TrainingConfigOutput
}

GoogleCloudAiplatformV1TrainingConfigInput is an input type that accepts GoogleCloudAiplatformV1TrainingConfigArgs and GoogleCloudAiplatformV1TrainingConfigOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1TrainingConfigInput` via: 

GoogleCloudAiplatformV1TrainingConfigArgs{...}

type GoogleCloudAiplatformV1TrainingConfigOutput 

type GoogleCloudAiplatformV1TrainingConfigOutput struct{ *pulumi.OutputState }

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

func (GoogleCloudAiplatformV1TrainingConfigOutput) ElementType 

func (GoogleCloudAiplatformV1TrainingConfigOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1TrainingConfigOutput) TimeoutTrainingMilliHours 

func (o GoogleCloudAiplatformV1TrainingConfigOutput) TimeoutTrainingMilliHours() pulumi.StringPtrOutput

The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.

func (GoogleCloudAiplatformV1TrainingConfigOutput) ToGoogleCloudAiplatformV1TrainingConfigOutput 

func (o GoogleCloudAiplatformV1TrainingConfigOutput) ToGoogleCloudAiplatformV1TrainingConfigOutput() GoogleCloudAiplatformV1TrainingConfigOutput

func (GoogleCloudAiplatformV1TrainingConfigOutput) ToGoogleCloudAiplatformV1TrainingConfigOutputWithContext 

func (o GoogleCloudAiplatformV1TrainingConfigOutput) ToGoogleCloudAiplatformV1TrainingConfigOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TrainingConfigOutput

func (GoogleCloudAiplatformV1TrainingConfigOutput) ToGoogleCloudAiplatformV1TrainingConfigPtrOutput 

func (o GoogleCloudAiplatformV1TrainingConfigOutput) ToGoogleCloudAiplatformV1TrainingConfigPtrOutput() GoogleCloudAiplatformV1TrainingConfigPtrOutput

func (GoogleCloudAiplatformV1TrainingConfigOutput) ToGoogleCloudAiplatformV1TrainingConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1TrainingConfigOutput) ToGoogleCloudAiplatformV1TrainingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TrainingConfigPtrOutput

type GoogleCloudAiplatformV1TrainingConfigPtrInput 

type GoogleCloudAiplatformV1TrainingConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1TrainingConfigPtrOutput() GoogleCloudAiplatformV1TrainingConfigPtrOutput
	ToGoogleCloudAiplatformV1TrainingConfigPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1TrainingConfigPtrOutput
}

GoogleCloudAiplatformV1TrainingConfigPtrInput is an input type that accepts GoogleCloudAiplatformV1TrainingConfigArgs, GoogleCloudAiplatformV1TrainingConfigPtr and GoogleCloudAiplatformV1TrainingConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1TrainingConfigPtrInput` via: 

        GoogleCloudAiplatformV1TrainingConfigArgs{...}

or:

        nil

func GoogleCloudAiplatformV1TrainingConfigPtr 

func GoogleCloudAiplatformV1TrainingConfigPtr(v *GoogleCloudAiplatformV1TrainingConfigArgs) GoogleCloudAiplatformV1TrainingConfigPtrInput

type GoogleCloudAiplatformV1TrainingConfigPtrOutput 

type GoogleCloudAiplatformV1TrainingConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1TrainingConfigPtrOutput) Elem 

func (o GoogleCloudAiplatformV1TrainingConfigPtrOutput) Elem() GoogleCloudAiplatformV1TrainingConfigOutput

func (GoogleCloudAiplatformV1TrainingConfigPtrOutput) ElementType 

func (GoogleCloudAiplatformV1TrainingConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1TrainingConfigPtrOutput) TimeoutTrainingMilliHours 

func (o GoogleCloudAiplatformV1TrainingConfigPtrOutput) TimeoutTrainingMilliHours() pulumi.StringPtrOutput

The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.

func (GoogleCloudAiplatformV1TrainingConfigPtrOutput) ToGoogleCloudAiplatformV1TrainingConfigPtrOutput 

func (o GoogleCloudAiplatformV1TrainingConfigPtrOutput) ToGoogleCloudAiplatformV1TrainingConfigPtrOutput() GoogleCloudAiplatformV1TrainingConfigPtrOutput

func (GoogleCloudAiplatformV1TrainingConfigPtrOutput) ToGoogleCloudAiplatformV1TrainingConfigPtrOutputWithContext 

func (o GoogleCloudAiplatformV1TrainingConfigPtrOutput) ToGoogleCloudAiplatformV1TrainingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TrainingConfigPtrOutput

type GoogleCloudAiplatformV1TrainingConfigResponse 

type GoogleCloudAiplatformV1TrainingConfigResponse struct {
	// The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.
	TimeoutTrainingMilliHours string `pulumi:"timeoutTrainingMilliHours"`
}

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

type GoogleCloudAiplatformV1TrainingConfigResponseOutput 

type GoogleCloudAiplatformV1TrainingConfigResponseOutput struct{ *pulumi.OutputState }

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

func (GoogleCloudAiplatformV1TrainingConfigResponseOutput) ElementType 

func (GoogleCloudAiplatformV1TrainingConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1TrainingConfigResponseOutput) TimeoutTrainingMilliHours 

func (o GoogleCloudAiplatformV1TrainingConfigResponseOutput) TimeoutTrainingMilliHours() pulumi.StringOutput

The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour.

func (GoogleCloudAiplatformV1TrainingConfigResponseOutput) ToGoogleCloudAiplatformV1TrainingConfigResponseOutput 

func (o GoogleCloudAiplatformV1TrainingConfigResponseOutput) ToGoogleCloudAiplatformV1TrainingConfigResponseOutput() GoogleCloudAiplatformV1TrainingConfigResponseOutput

func (GoogleCloudAiplatformV1TrainingConfigResponseOutput) ToGoogleCloudAiplatformV1TrainingConfigResponseOutputWithContext 

func (o GoogleCloudAiplatformV1TrainingConfigResponseOutput) ToGoogleCloudAiplatformV1TrainingConfigResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TrainingConfigResponseOutput

type GoogleCloudAiplatformV1TrialParameterResponse 

type GoogleCloudAiplatformV1TrialParameterResponse struct {
	// The ID of the parameter. The parameter should be defined in StudySpec's Parameters.
	ParameterId string `pulumi:"parameterId"`
	// The value of the parameter. `number_value` will be set if a parameter defined in StudySpec is in type 'INTEGER', 'DOUBLE' or 'DISCRETE'. `string_value` will be set if a parameter defined in StudySpec is in type 'CATEGORICAL'.
	Value interface{} `pulumi:"value"`
}

A message representing a parameter to be tuned.

type GoogleCloudAiplatformV1TrialParameterResponseArrayOutput 

type GoogleCloudAiplatformV1TrialParameterResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1TrialParameterResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1TrialParameterResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1TrialParameterResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1TrialParameterResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1TrialParameterResponseOutput

func (GoogleCloudAiplatformV1TrialParameterResponseArrayOutput) ToGoogleCloudAiplatformV1TrialParameterResponseArrayOutput 

func (o GoogleCloudAiplatformV1TrialParameterResponseArrayOutput) ToGoogleCloudAiplatformV1TrialParameterResponseArrayOutput() GoogleCloudAiplatformV1TrialParameterResponseArrayOutput

func (GoogleCloudAiplatformV1TrialParameterResponseArrayOutput) ToGoogleCloudAiplatformV1TrialParameterResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1TrialParameterResponseArrayOutput) ToGoogleCloudAiplatformV1TrialParameterResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TrialParameterResponseArrayOutput

type GoogleCloudAiplatformV1TrialParameterResponseOutput 

type GoogleCloudAiplatformV1TrialParameterResponseOutput struct{ *pulumi.OutputState }

A message representing a parameter to be tuned.

func (GoogleCloudAiplatformV1TrialParameterResponseOutput) ElementType 

func (GoogleCloudAiplatformV1TrialParameterResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1TrialParameterResponseOutput) ParameterId 

func (o GoogleCloudAiplatformV1TrialParameterResponseOutput) ParameterId() pulumi.StringOutput

The ID of the parameter. The parameter should be defined in StudySpec's Parameters.

func (GoogleCloudAiplatformV1TrialParameterResponseOutput) ToGoogleCloudAiplatformV1TrialParameterResponseOutput 

func (o GoogleCloudAiplatformV1TrialParameterResponseOutput) ToGoogleCloudAiplatformV1TrialParameterResponseOutput() GoogleCloudAiplatformV1TrialParameterResponseOutput

func (GoogleCloudAiplatformV1TrialParameterResponseOutput) ToGoogleCloudAiplatformV1TrialParameterResponseOutputWithContext 

func (o GoogleCloudAiplatformV1TrialParameterResponseOutput) ToGoogleCloudAiplatformV1TrialParameterResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TrialParameterResponseOutput

func (GoogleCloudAiplatformV1TrialParameterResponseOutput) Value 

func (o GoogleCloudAiplatformV1TrialParameterResponseOutput) Value() pulumi.AnyOutput

The value of the parameter. `number_value` will be set if a parameter defined in StudySpec is in type 'INTEGER', 'DOUBLE' or 'DISCRETE'. `string_value` will be set if a parameter defined in StudySpec is in type 'CATEGORICAL'.

type GoogleCloudAiplatformV1TrialResponse 

type GoogleCloudAiplatformV1TrialResponse struct {
	// The identifier of the client that originally requested this Trial. Each client is identified by a unique client_id. When a client asks for a suggestion, Vertex AI Vizier will assign it a Trial. The client should evaluate the Trial, complete it, and report back to Vertex AI Vizier. If suggestion is asked again by same client_id before the Trial is completed, the same Trial will be returned. Multiple clients with different client_ids can ask for suggestions simultaneously, each of them will get their own Trial.
	ClientId string `pulumi:"clientId"`
	// The CustomJob name linked to the Trial. It's set for a HyperparameterTuningJob's Trial.
	CustomJob string `pulumi:"customJob"`
	// Time when the Trial's status changed to `SUCCEEDED` or `INFEASIBLE`.
	EndTime string `pulumi:"endTime"`
	// The final measurement containing the objective value.
	FinalMeasurement GoogleCloudAiplatformV1MeasurementResponse `pulumi:"finalMeasurement"`
	// A human readable string describing why the Trial is infeasible. This is set only if Trial state is `INFEASIBLE`.
	InfeasibleReason string `pulumi:"infeasibleReason"`
	// A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_duration). These are used for early stopping computations.
	Measurements []GoogleCloudAiplatformV1MeasurementResponse `pulumi:"measurements"`
	// Resource name of the Trial assigned by the service.
	Name string `pulumi:"name"`
	// The parameters of the Trial.
	Parameters []GoogleCloudAiplatformV1TrialParameterResponse `pulumi:"parameters"`
	// Time when the Trial was started.
	StartTime string `pulumi:"startTime"`
	// The detailed state of the Trial.
	State string `pulumi:"state"`
	// URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a HyperparameterTuningJob and the job's trial_job_spec.enable_web_access field is `true`. The keys are names of each node used for the trial; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.
	WebAccessUris map[string]string `pulumi:"webAccessUris"`
}

A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial.

type GoogleCloudAiplatformV1TrialResponseArrayOutput 

type GoogleCloudAiplatformV1TrialResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1TrialResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1TrialResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1TrialResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1TrialResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1TrialResponseOutput

func (GoogleCloudAiplatformV1TrialResponseArrayOutput) ToGoogleCloudAiplatformV1TrialResponseArrayOutput 

func (o GoogleCloudAiplatformV1TrialResponseArrayOutput) ToGoogleCloudAiplatformV1TrialResponseArrayOutput() GoogleCloudAiplatformV1TrialResponseArrayOutput

func (GoogleCloudAiplatformV1TrialResponseArrayOutput) ToGoogleCloudAiplatformV1TrialResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1TrialResponseArrayOutput) ToGoogleCloudAiplatformV1TrialResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TrialResponseArrayOutput

type GoogleCloudAiplatformV1TrialResponseOutput 

type GoogleCloudAiplatformV1TrialResponseOutput struct{ *pulumi.OutputState }

A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial.

func (GoogleCloudAiplatformV1TrialResponseOutput) ClientId 

func (o GoogleCloudAiplatformV1TrialResponseOutput) ClientId() pulumi.StringOutput

The identifier of the client that originally requested this Trial. Each client is identified by a unique client_id. When a client asks for a suggestion, Vertex AI Vizier will assign it a Trial. The client should evaluate the Trial, complete it, and report back to Vertex AI Vizier. If suggestion is asked again by same client_id before the Trial is completed, the same Trial will be returned. Multiple clients with different client_ids can ask for suggestions simultaneously, each of them will get their own Trial.

func (GoogleCloudAiplatformV1TrialResponseOutput) CustomJob 

func (o GoogleCloudAiplatformV1TrialResponseOutput) CustomJob() pulumi.StringOutput

The CustomJob name linked to the Trial. It's set for a HyperparameterTuningJob's Trial.

func (GoogleCloudAiplatformV1TrialResponseOutput) ElementType 

func (GoogleCloudAiplatformV1TrialResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1TrialResponseOutput) EndTime 

func (o GoogleCloudAiplatformV1TrialResponseOutput) EndTime() pulumi.StringOutput

Time when the Trial's status changed to `SUCCEEDED` or `INFEASIBLE`.

func (GoogleCloudAiplatformV1TrialResponseOutput) FinalMeasurement 

func (o GoogleCloudAiplatformV1TrialResponseOutput) FinalMeasurement() GoogleCloudAiplatformV1MeasurementResponseOutput

The final measurement containing the objective value.

func (GoogleCloudAiplatformV1TrialResponseOutput) InfeasibleReason 

func (o GoogleCloudAiplatformV1TrialResponseOutput) InfeasibleReason() pulumi.StringOutput

A human readable string describing why the Trial is infeasible. This is set only if Trial state is `INFEASIBLE`.

func (GoogleCloudAiplatformV1TrialResponseOutput) Measurements 

func (o GoogleCloudAiplatformV1TrialResponseOutput) Measurements() GoogleCloudAiplatformV1MeasurementResponseArrayOutput

A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_duration). These are used for early stopping computations.

func (GoogleCloudAiplatformV1TrialResponseOutput) Name 

func (o GoogleCloudAiplatformV1TrialResponseOutput) Name() pulumi.StringOutput

Resource name of the Trial assigned by the service.

func (GoogleCloudAiplatformV1TrialResponseOutput) Parameters 

func (o GoogleCloudAiplatformV1TrialResponseOutput) Parameters() GoogleCloudAiplatformV1TrialParameterResponseArrayOutput

The parameters of the Trial.

func (GoogleCloudAiplatformV1TrialResponseOutput) StartTime 

func (o GoogleCloudAiplatformV1TrialResponseOutput) StartTime() pulumi.StringOutput

Time when the Trial was started.

func (GoogleCloudAiplatformV1TrialResponseOutput) State 

func (o GoogleCloudAiplatformV1TrialResponseOutput) State() pulumi.StringOutput

The detailed state of the Trial.

func (GoogleCloudAiplatformV1TrialResponseOutput) ToGoogleCloudAiplatformV1TrialResponseOutput 

func (o GoogleCloudAiplatformV1TrialResponseOutput) ToGoogleCloudAiplatformV1TrialResponseOutput() GoogleCloudAiplatformV1TrialResponseOutput

func (GoogleCloudAiplatformV1TrialResponseOutput) ToGoogleCloudAiplatformV1TrialResponseOutputWithContext 

func (o GoogleCloudAiplatformV1TrialResponseOutput) ToGoogleCloudAiplatformV1TrialResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1TrialResponseOutput

func (GoogleCloudAiplatformV1TrialResponseOutput) WebAccessUris 

func (o GoogleCloudAiplatformV1TrialResponseOutput) WebAccessUris() pulumi.StringMapOutput

URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a HyperparameterTuningJob and the job's trial_job_spec.enable_web_access field is `true`. The keys are names of each node used for the trial; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.

type GoogleCloudAiplatformV1UnmanagedContainerModel 

type GoogleCloudAiplatformV1UnmanagedContainerModel struct {
	// The path to the directory containing the Model artifact and any of its supporting files.
	ArtifactUri *string `pulumi:"artifactUri"`
	// Input only. The specification of the container that is to be used when deploying this Model.
	ContainerSpec *GoogleCloudAiplatformV1ModelContainerSpec `pulumi:"containerSpec"`
	// Contains the schemata used in Model's predictions and explanations
	PredictSchemata *GoogleCloudAiplatformV1PredictSchemata `pulumi:"predictSchemata"`
}

Contains model information necessary to perform batch prediction without requiring a full model import.

type GoogleCloudAiplatformV1UnmanagedContainerModelArgs 

type GoogleCloudAiplatformV1UnmanagedContainerModelArgs struct {
	// The path to the directory containing the Model artifact and any of its supporting files.
	ArtifactUri pulumi.StringPtrInput `pulumi:"artifactUri"`
	// Input only. The specification of the container that is to be used when deploying this Model.
	ContainerSpec GoogleCloudAiplatformV1ModelContainerSpecPtrInput `pulumi:"containerSpec"`
	// Contains the schemata used in Model's predictions and explanations
	PredictSchemata GoogleCloudAiplatformV1PredictSchemataPtrInput `pulumi:"predictSchemata"`
}

Contains model information necessary to perform batch prediction without requiring a full model import.

func (GoogleCloudAiplatformV1UnmanagedContainerModelArgs) ElementType 

func (GoogleCloudAiplatformV1UnmanagedContainerModelArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1UnmanagedContainerModelArgs) ToGoogleCloudAiplatformV1UnmanagedContainerModelOutput 

func (i GoogleCloudAiplatformV1UnmanagedContainerModelArgs) ToGoogleCloudAiplatformV1UnmanagedContainerModelOutput() GoogleCloudAiplatformV1UnmanagedContainerModelOutput

func (GoogleCloudAiplatformV1UnmanagedContainerModelArgs) ToGoogleCloudAiplatformV1UnmanagedContainerModelOutputWithContext 

func (i GoogleCloudAiplatformV1UnmanagedContainerModelArgs) ToGoogleCloudAiplatformV1UnmanagedContainerModelOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1UnmanagedContainerModelOutput

func (GoogleCloudAiplatformV1UnmanagedContainerModelArgs) ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput 

func (i GoogleCloudAiplatformV1UnmanagedContainerModelArgs) ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput() GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput

func (GoogleCloudAiplatformV1UnmanagedContainerModelArgs) ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutputWithContext 

func (i GoogleCloudAiplatformV1UnmanagedContainerModelArgs) ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput

type GoogleCloudAiplatformV1UnmanagedContainerModelInput 

type GoogleCloudAiplatformV1UnmanagedContainerModelInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1UnmanagedContainerModelOutput() GoogleCloudAiplatformV1UnmanagedContainerModelOutput
	ToGoogleCloudAiplatformV1UnmanagedContainerModelOutputWithContext(context.Context) GoogleCloudAiplatformV1UnmanagedContainerModelOutput
}

GoogleCloudAiplatformV1UnmanagedContainerModelInput is an input type that accepts GoogleCloudAiplatformV1UnmanagedContainerModelArgs and GoogleCloudAiplatformV1UnmanagedContainerModelOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1UnmanagedContainerModelInput` via: 

GoogleCloudAiplatformV1UnmanagedContainerModelArgs{...}

type GoogleCloudAiplatformV1UnmanagedContainerModelOutput 

type GoogleCloudAiplatformV1UnmanagedContainerModelOutput struct{ *pulumi.OutputState }

Contains model information necessary to perform batch prediction without requiring a full model import.

func (GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ArtifactUri 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ArtifactUri() pulumi.StringPtrOutput

The path to the directory containing the Model artifact and any of its supporting files.

func (GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ContainerSpec 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ContainerSpec() GoogleCloudAiplatformV1ModelContainerSpecPtrOutput

Input only. The specification of the container that is to be used when deploying this Model.

func (GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ElementType 

func (GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1UnmanagedContainerModelOutput) PredictSchemata 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelOutput) PredictSchemata() GoogleCloudAiplatformV1PredictSchemataPtrOutput

Contains the schemata used in Model's predictions and explanations

func (GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelOutput 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelOutput() GoogleCloudAiplatformV1UnmanagedContainerModelOutput

func (GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelOutputWithContext 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1UnmanagedContainerModelOutput

func (GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput() GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput

func (GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutputWithContext 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput

type GoogleCloudAiplatformV1UnmanagedContainerModelPtrInput 

type GoogleCloudAiplatformV1UnmanagedContainerModelPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput() GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput
	ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput
}

GoogleCloudAiplatformV1UnmanagedContainerModelPtrInput is an input type that accepts GoogleCloudAiplatformV1UnmanagedContainerModelArgs, GoogleCloudAiplatformV1UnmanagedContainerModelPtr and GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1UnmanagedContainerModelPtrInput` via: 

        GoogleCloudAiplatformV1UnmanagedContainerModelArgs{...}

or:

        nil

func GoogleCloudAiplatformV1UnmanagedContainerModelPtr 

func GoogleCloudAiplatformV1UnmanagedContainerModelPtr(v *GoogleCloudAiplatformV1UnmanagedContainerModelArgs) GoogleCloudAiplatformV1UnmanagedContainerModelPtrInput

type GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput 

type GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) ArtifactUri 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) ArtifactUri() pulumi.StringPtrOutput

The path to the directory containing the Model artifact and any of its supporting files.

func (GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) ContainerSpec 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) ContainerSpec() GoogleCloudAiplatformV1ModelContainerSpecPtrOutput

Input only. The specification of the container that is to be used when deploying this Model.

func (GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) Elem 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) Elem() GoogleCloudAiplatformV1UnmanagedContainerModelOutput

func (GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) ElementType 

func (GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) PredictSchemata 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) PredictSchemata() GoogleCloudAiplatformV1PredictSchemataPtrOutput

Contains the schemata used in Model's predictions and explanations

func (GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput() GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput

func (GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutputWithContext 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1UnmanagedContainerModelPtrOutput

type GoogleCloudAiplatformV1UnmanagedContainerModelResponse 

type GoogleCloudAiplatformV1UnmanagedContainerModelResponse struct {
	// The path to the directory containing the Model artifact and any of its supporting files.
	ArtifactUri string `pulumi:"artifactUri"`
	// Input only. The specification of the container that is to be used when deploying this Model.
	ContainerSpec GoogleCloudAiplatformV1ModelContainerSpecResponse `pulumi:"containerSpec"`
	// Contains the schemata used in Model's predictions and explanations
	PredictSchemata GoogleCloudAiplatformV1PredictSchemataResponse `pulumi:"predictSchemata"`
}

Contains model information necessary to perform batch prediction without requiring a full model import.

type GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput 

type GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput struct{ *pulumi.OutputState }

Contains model information necessary to perform batch prediction without requiring a full model import.

func (GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput) ArtifactUri 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput) ArtifactUri() pulumi.StringOutput

The path to the directory containing the Model artifact and any of its supporting files.

func (GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput) ContainerSpec 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput) ContainerSpec() GoogleCloudAiplatformV1ModelContainerSpecResponseOutput

Input only. The specification of the container that is to be used when deploying this Model.

func (GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput) ElementType 

func (GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput) PredictSchemata 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput) PredictSchemata() GoogleCloudAiplatformV1PredictSchemataResponseOutput

Contains the schemata used in Model's predictions and explanations

func (GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput() GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput

func (GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelResponseOutputWithContext 

func (o GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput) ToGoogleCloudAiplatformV1UnmanagedContainerModelResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput

type GoogleCloudAiplatformV1WorkerPoolSpec 

type GoogleCloudAiplatformV1WorkerPoolSpec struct {
	// The custom container task.
	ContainerSpec *GoogleCloudAiplatformV1ContainerSpec `pulumi:"containerSpec"`
	// Disk spec.
	DiskSpec *GoogleCloudAiplatformV1DiskSpec `pulumi:"diskSpec"`
	// Optional. Immutable. The specification of a single machine.
	MachineSpec *GoogleCloudAiplatformV1MachineSpec `pulumi:"machineSpec"`
	// Optional. List of NFS mount spec.
	NfsMounts []GoogleCloudAiplatformV1NfsMount `pulumi:"nfsMounts"`
	// The Python packaged task.
	PythonPackageSpec *GoogleCloudAiplatformV1PythonPackageSpec `pulumi:"pythonPackageSpec"`
	// Optional. The number of worker replicas to use for this worker pool.
	ReplicaCount *string `pulumi:"replicaCount"`
}

Represents the spec of a worker pool in a job.

type GoogleCloudAiplatformV1WorkerPoolSpecArgs 

type GoogleCloudAiplatformV1WorkerPoolSpecArgs struct {
	// The custom container task.
	ContainerSpec GoogleCloudAiplatformV1ContainerSpecPtrInput `pulumi:"containerSpec"`
	// Disk spec.
	DiskSpec GoogleCloudAiplatformV1DiskSpecPtrInput `pulumi:"diskSpec"`
	// Optional. Immutable. The specification of a single machine.
	MachineSpec GoogleCloudAiplatformV1MachineSpecPtrInput `pulumi:"machineSpec"`
	// Optional. List of NFS mount spec.
	NfsMounts GoogleCloudAiplatformV1NfsMountArrayInput `pulumi:"nfsMounts"`
	// The Python packaged task.
	PythonPackageSpec GoogleCloudAiplatformV1PythonPackageSpecPtrInput `pulumi:"pythonPackageSpec"`
	// Optional. The number of worker replicas to use for this worker pool.
	ReplicaCount pulumi.StringPtrInput `pulumi:"replicaCount"`
}

Represents the spec of a worker pool in a job.

func (GoogleCloudAiplatformV1WorkerPoolSpecArgs) ElementType 

func (GoogleCloudAiplatformV1WorkerPoolSpecArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1WorkerPoolSpecArgs) ToGoogleCloudAiplatformV1WorkerPoolSpecOutput 

func (i GoogleCloudAiplatformV1WorkerPoolSpecArgs) ToGoogleCloudAiplatformV1WorkerPoolSpecOutput() GoogleCloudAiplatformV1WorkerPoolSpecOutput

func (GoogleCloudAiplatformV1WorkerPoolSpecArgs) ToGoogleCloudAiplatformV1WorkerPoolSpecOutputWithContext 

func (i GoogleCloudAiplatformV1WorkerPoolSpecArgs) ToGoogleCloudAiplatformV1WorkerPoolSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1WorkerPoolSpecOutput

type GoogleCloudAiplatformV1WorkerPoolSpecArray 

type GoogleCloudAiplatformV1WorkerPoolSpecArray []GoogleCloudAiplatformV1WorkerPoolSpecInput

func (GoogleCloudAiplatformV1WorkerPoolSpecArray) ElementType 

func (GoogleCloudAiplatformV1WorkerPoolSpecArray) ElementType() reflect.Type

func (GoogleCloudAiplatformV1WorkerPoolSpecArray) ToGoogleCloudAiplatformV1WorkerPoolSpecArrayOutput 

func (i GoogleCloudAiplatformV1WorkerPoolSpecArray) ToGoogleCloudAiplatformV1WorkerPoolSpecArrayOutput() GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput

func (GoogleCloudAiplatformV1WorkerPoolSpecArray) ToGoogleCloudAiplatformV1WorkerPoolSpecArrayOutputWithContext 

func (i GoogleCloudAiplatformV1WorkerPoolSpecArray) ToGoogleCloudAiplatformV1WorkerPoolSpecArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput

type GoogleCloudAiplatformV1WorkerPoolSpecArrayInput 

type GoogleCloudAiplatformV1WorkerPoolSpecArrayInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1WorkerPoolSpecArrayOutput() GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput
	ToGoogleCloudAiplatformV1WorkerPoolSpecArrayOutputWithContext(context.Context) GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput
}

GoogleCloudAiplatformV1WorkerPoolSpecArrayInput is an input type that accepts GoogleCloudAiplatformV1WorkerPoolSpecArray and GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1WorkerPoolSpecArrayInput` via: 

GoogleCloudAiplatformV1WorkerPoolSpecArray{ GoogleCloudAiplatformV1WorkerPoolSpecArgs{...} }

type GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput 

type GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput) ElementType 

func (GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput) Index 

func (o GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1WorkerPoolSpecOutput

func (GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecArrayOutput 

func (o GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecArrayOutput() GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput

func (GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecArrayOutputWithContext 

func (o GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1WorkerPoolSpecArrayOutput

type GoogleCloudAiplatformV1WorkerPoolSpecInput 

type GoogleCloudAiplatformV1WorkerPoolSpecInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1WorkerPoolSpecOutput() GoogleCloudAiplatformV1WorkerPoolSpecOutput
	ToGoogleCloudAiplatformV1WorkerPoolSpecOutputWithContext(context.Context) GoogleCloudAiplatformV1WorkerPoolSpecOutput
}

GoogleCloudAiplatformV1WorkerPoolSpecInput is an input type that accepts GoogleCloudAiplatformV1WorkerPoolSpecArgs and GoogleCloudAiplatformV1WorkerPoolSpecOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1WorkerPoolSpecInput` via: 

GoogleCloudAiplatformV1WorkerPoolSpecArgs{...}

type GoogleCloudAiplatformV1WorkerPoolSpecOutput 

type GoogleCloudAiplatformV1WorkerPoolSpecOutput struct{ *pulumi.OutputState }

Represents the spec of a worker pool in a job.

func (GoogleCloudAiplatformV1WorkerPoolSpecOutput) ContainerSpec 

func (o GoogleCloudAiplatformV1WorkerPoolSpecOutput) ContainerSpec() GoogleCloudAiplatformV1ContainerSpecPtrOutput

The custom container task.

func (GoogleCloudAiplatformV1WorkerPoolSpecOutput) DiskSpec 

func (o GoogleCloudAiplatformV1WorkerPoolSpecOutput) DiskSpec() GoogleCloudAiplatformV1DiskSpecPtrOutput

Disk spec.

func (GoogleCloudAiplatformV1WorkerPoolSpecOutput) ElementType 

func (GoogleCloudAiplatformV1WorkerPoolSpecOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1WorkerPoolSpecOutput) MachineSpec 

func (o GoogleCloudAiplatformV1WorkerPoolSpecOutput) MachineSpec() GoogleCloudAiplatformV1MachineSpecPtrOutput

Optional. Immutable. The specification of a single machine.

func (GoogleCloudAiplatformV1WorkerPoolSpecOutput) NfsMounts 

func (o GoogleCloudAiplatformV1WorkerPoolSpecOutput) NfsMounts() GoogleCloudAiplatformV1NfsMountArrayOutput

Optional. List of NFS mount spec.

func (GoogleCloudAiplatformV1WorkerPoolSpecOutput) PythonPackageSpec 

func (o GoogleCloudAiplatformV1WorkerPoolSpecOutput) PythonPackageSpec() GoogleCloudAiplatformV1PythonPackageSpecPtrOutput

The Python packaged task.

func (GoogleCloudAiplatformV1WorkerPoolSpecOutput) ReplicaCount 

func (o GoogleCloudAiplatformV1WorkerPoolSpecOutput) ReplicaCount() pulumi.StringPtrOutput

Optional. The number of worker replicas to use for this worker pool.

func (GoogleCloudAiplatformV1WorkerPoolSpecOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecOutput 

func (o GoogleCloudAiplatformV1WorkerPoolSpecOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecOutput() GoogleCloudAiplatformV1WorkerPoolSpecOutput

func (GoogleCloudAiplatformV1WorkerPoolSpecOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecOutputWithContext 

func (o GoogleCloudAiplatformV1WorkerPoolSpecOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1WorkerPoolSpecOutput

type GoogleCloudAiplatformV1WorkerPoolSpecResponse 

type GoogleCloudAiplatformV1WorkerPoolSpecResponse struct {
	// The custom container task.
	ContainerSpec GoogleCloudAiplatformV1ContainerSpecResponse `pulumi:"containerSpec"`
	// Disk spec.
	DiskSpec GoogleCloudAiplatformV1DiskSpecResponse `pulumi:"diskSpec"`
	// Optional. Immutable. The specification of a single machine.
	MachineSpec GoogleCloudAiplatformV1MachineSpecResponse `pulumi:"machineSpec"`
	// Optional. List of NFS mount spec.
	NfsMounts []GoogleCloudAiplatformV1NfsMountResponse `pulumi:"nfsMounts"`
	// The Python packaged task.
	PythonPackageSpec GoogleCloudAiplatformV1PythonPackageSpecResponse `pulumi:"pythonPackageSpec"`
	// Optional. The number of worker replicas to use for this worker pool.
	ReplicaCount string `pulumi:"replicaCount"`
}

Represents the spec of a worker pool in a job.

type GoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput 

type GoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput) ElementType 

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput) Index 

func (o GoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput 

func (o GoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput() GoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutputWithContext 

func (o GoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1WorkerPoolSpecResponseArrayOutput

type GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput 

type GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput struct{ *pulumi.OutputState }

Represents the spec of a worker pool in a job.

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) ContainerSpec 

func (o GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) ContainerSpec() GoogleCloudAiplatformV1ContainerSpecResponseOutput

The custom container task.

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) DiskSpec 

func (o GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) DiskSpec() GoogleCloudAiplatformV1DiskSpecResponseOutput

Disk spec.

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) ElementType 

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) MachineSpec 

func (o GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) MachineSpec() GoogleCloudAiplatformV1MachineSpecResponseOutput

Optional. Immutable. The specification of a single machine.

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) NfsMounts 

func (o GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) NfsMounts() GoogleCloudAiplatformV1NfsMountResponseArrayOutput

Optional. List of NFS mount spec.

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) PythonPackageSpec 

func (o GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) PythonPackageSpec() GoogleCloudAiplatformV1PythonPackageSpecResponseOutput

The Python packaged task.

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) ReplicaCount 

func (o GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) ReplicaCount() pulumi.StringOutput

Optional. The number of worker replicas to use for this worker pool.

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecResponseOutput 

func (o GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecResponseOutput() GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput

func (GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecResponseOutputWithContext 

func (o GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput) ToGoogleCloudAiplatformV1WorkerPoolSpecResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1WorkerPoolSpecResponseOutput

type GoogleCloudAiplatformV1XraiAttribution 

type GoogleCloudAiplatformV1XraiAttribution struct {
	// Config for XRAI with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383
	BlurBaselineConfig *GoogleCloudAiplatformV1BlurBaselineConfig `pulumi:"blurBaselineConfig"`
	// Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf
	SmoothGradConfig *GoogleCloudAiplatformV1SmoothGradConfig `pulumi:"smoothGradConfig"`
	// The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range. Valid range of its value is [1, 100], inclusively.
	StepCount int `pulumi:"stepCount"`
}

An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Supported only by image Models.

type GoogleCloudAiplatformV1XraiAttributionArgs 

type GoogleCloudAiplatformV1XraiAttributionArgs struct {
	// Config for XRAI with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383
	BlurBaselineConfig GoogleCloudAiplatformV1BlurBaselineConfigPtrInput `pulumi:"blurBaselineConfig"`
	// Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf
	SmoothGradConfig GoogleCloudAiplatformV1SmoothGradConfigPtrInput `pulumi:"smoothGradConfig"`
	// The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range. Valid range of its value is [1, 100], inclusively.
	StepCount pulumi.IntInput `pulumi:"stepCount"`
}

An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Supported only by image Models.

func (GoogleCloudAiplatformV1XraiAttributionArgs) ElementType 

func (GoogleCloudAiplatformV1XraiAttributionArgs) ElementType() reflect.Type

func (GoogleCloudAiplatformV1XraiAttributionArgs) ToGoogleCloudAiplatformV1XraiAttributionOutput 

func (i GoogleCloudAiplatformV1XraiAttributionArgs) ToGoogleCloudAiplatformV1XraiAttributionOutput() GoogleCloudAiplatformV1XraiAttributionOutput

func (GoogleCloudAiplatformV1XraiAttributionArgs) ToGoogleCloudAiplatformV1XraiAttributionOutputWithContext 

func (i GoogleCloudAiplatformV1XraiAttributionArgs) ToGoogleCloudAiplatformV1XraiAttributionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1XraiAttributionOutput

func (GoogleCloudAiplatformV1XraiAttributionArgs) ToGoogleCloudAiplatformV1XraiAttributionPtrOutput 

func (i GoogleCloudAiplatformV1XraiAttributionArgs) ToGoogleCloudAiplatformV1XraiAttributionPtrOutput() GoogleCloudAiplatformV1XraiAttributionPtrOutput

func (GoogleCloudAiplatformV1XraiAttributionArgs) ToGoogleCloudAiplatformV1XraiAttributionPtrOutputWithContext 

func (i GoogleCloudAiplatformV1XraiAttributionArgs) ToGoogleCloudAiplatformV1XraiAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1XraiAttributionPtrOutput

type GoogleCloudAiplatformV1XraiAttributionInput 

type GoogleCloudAiplatformV1XraiAttributionInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1XraiAttributionOutput() GoogleCloudAiplatformV1XraiAttributionOutput
	ToGoogleCloudAiplatformV1XraiAttributionOutputWithContext(context.Context) GoogleCloudAiplatformV1XraiAttributionOutput
}

GoogleCloudAiplatformV1XraiAttributionInput is an input type that accepts GoogleCloudAiplatformV1XraiAttributionArgs and GoogleCloudAiplatformV1XraiAttributionOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1XraiAttributionInput` via: 

GoogleCloudAiplatformV1XraiAttributionArgs{...}

type GoogleCloudAiplatformV1XraiAttributionOutput 

type GoogleCloudAiplatformV1XraiAttributionOutput struct{ *pulumi.OutputState }

An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Supported only by image Models.

func (GoogleCloudAiplatformV1XraiAttributionOutput) BlurBaselineConfig 

func (o GoogleCloudAiplatformV1XraiAttributionOutput) BlurBaselineConfig() GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput

Config for XRAI with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383

func (GoogleCloudAiplatformV1XraiAttributionOutput) ElementType 

func (GoogleCloudAiplatformV1XraiAttributionOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1XraiAttributionOutput) SmoothGradConfig 

func (o GoogleCloudAiplatformV1XraiAttributionOutput) SmoothGradConfig() GoogleCloudAiplatformV1SmoothGradConfigPtrOutput

Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf

func (GoogleCloudAiplatformV1XraiAttributionOutput) StepCount 

func (o GoogleCloudAiplatformV1XraiAttributionOutput) StepCount() pulumi.IntOutput

The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range. Valid range of its value is [1, 100], inclusively.

func (GoogleCloudAiplatformV1XraiAttributionOutput) ToGoogleCloudAiplatformV1XraiAttributionOutput 

func (o GoogleCloudAiplatformV1XraiAttributionOutput) ToGoogleCloudAiplatformV1XraiAttributionOutput() GoogleCloudAiplatformV1XraiAttributionOutput

func (GoogleCloudAiplatformV1XraiAttributionOutput) ToGoogleCloudAiplatformV1XraiAttributionOutputWithContext 

func (o GoogleCloudAiplatformV1XraiAttributionOutput) ToGoogleCloudAiplatformV1XraiAttributionOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1XraiAttributionOutput

func (GoogleCloudAiplatformV1XraiAttributionOutput) ToGoogleCloudAiplatformV1XraiAttributionPtrOutput 

func (o GoogleCloudAiplatformV1XraiAttributionOutput) ToGoogleCloudAiplatformV1XraiAttributionPtrOutput() GoogleCloudAiplatformV1XraiAttributionPtrOutput

func (GoogleCloudAiplatformV1XraiAttributionOutput) ToGoogleCloudAiplatformV1XraiAttributionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1XraiAttributionOutput) ToGoogleCloudAiplatformV1XraiAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1XraiAttributionPtrOutput

type GoogleCloudAiplatformV1XraiAttributionPtrInput 

type GoogleCloudAiplatformV1XraiAttributionPtrInput interface {
	pulumi.Input

	ToGoogleCloudAiplatformV1XraiAttributionPtrOutput() GoogleCloudAiplatformV1XraiAttributionPtrOutput
	ToGoogleCloudAiplatformV1XraiAttributionPtrOutputWithContext(context.Context) GoogleCloudAiplatformV1XraiAttributionPtrOutput
}

GoogleCloudAiplatformV1XraiAttributionPtrInput is an input type that accepts GoogleCloudAiplatformV1XraiAttributionArgs, GoogleCloudAiplatformV1XraiAttributionPtr and GoogleCloudAiplatformV1XraiAttributionPtrOutput values. You can construct a concrete instance of `GoogleCloudAiplatformV1XraiAttributionPtrInput` via: 

        GoogleCloudAiplatformV1XraiAttributionArgs{...}

or:

        nil

func GoogleCloudAiplatformV1XraiAttributionPtr 

func GoogleCloudAiplatformV1XraiAttributionPtr(v *GoogleCloudAiplatformV1XraiAttributionArgs) GoogleCloudAiplatformV1XraiAttributionPtrInput

type GoogleCloudAiplatformV1XraiAttributionPtrOutput 

type GoogleCloudAiplatformV1XraiAttributionPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudAiplatformV1XraiAttributionPtrOutput) BlurBaselineConfig 

func (o GoogleCloudAiplatformV1XraiAttributionPtrOutput) BlurBaselineConfig() GoogleCloudAiplatformV1BlurBaselineConfigPtrOutput

Config for XRAI with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383

func (GoogleCloudAiplatformV1XraiAttributionPtrOutput) Elem 

func (o GoogleCloudAiplatformV1XraiAttributionPtrOutput) Elem() GoogleCloudAiplatformV1XraiAttributionOutput

func (GoogleCloudAiplatformV1XraiAttributionPtrOutput) ElementType 

func (GoogleCloudAiplatformV1XraiAttributionPtrOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1XraiAttributionPtrOutput) SmoothGradConfig 

func (o GoogleCloudAiplatformV1XraiAttributionPtrOutput) SmoothGradConfig() GoogleCloudAiplatformV1SmoothGradConfigPtrOutput

Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf

func (GoogleCloudAiplatformV1XraiAttributionPtrOutput) StepCount 

func (o GoogleCloudAiplatformV1XraiAttributionPtrOutput) StepCount() pulumi.IntPtrOutput

The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range. Valid range of its value is [1, 100], inclusively.

func (GoogleCloudAiplatformV1XraiAttributionPtrOutput) ToGoogleCloudAiplatformV1XraiAttributionPtrOutput 

func (o GoogleCloudAiplatformV1XraiAttributionPtrOutput) ToGoogleCloudAiplatformV1XraiAttributionPtrOutput() GoogleCloudAiplatformV1XraiAttributionPtrOutput

func (GoogleCloudAiplatformV1XraiAttributionPtrOutput) ToGoogleCloudAiplatformV1XraiAttributionPtrOutputWithContext 

func (o GoogleCloudAiplatformV1XraiAttributionPtrOutput) ToGoogleCloudAiplatformV1XraiAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1XraiAttributionPtrOutput

type GoogleCloudAiplatformV1XraiAttributionResponse 

type GoogleCloudAiplatformV1XraiAttributionResponse struct {
	// Config for XRAI with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383
	BlurBaselineConfig GoogleCloudAiplatformV1BlurBaselineConfigResponse `pulumi:"blurBaselineConfig"`
	// Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf
	SmoothGradConfig GoogleCloudAiplatformV1SmoothGradConfigResponse `pulumi:"smoothGradConfig"`
	// The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range. Valid range of its value is [1, 100], inclusively.
	StepCount int `pulumi:"stepCount"`
}

An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Supported only by image Models.

type GoogleCloudAiplatformV1XraiAttributionResponseOutput 

type GoogleCloudAiplatformV1XraiAttributionResponseOutput struct{ *pulumi.OutputState }

An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Supported only by image Models.

func (GoogleCloudAiplatformV1XraiAttributionResponseOutput) BlurBaselineConfig 

func (o GoogleCloudAiplatformV1XraiAttributionResponseOutput) BlurBaselineConfig() GoogleCloudAiplatformV1BlurBaselineConfigResponseOutput

Config for XRAI with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383

func (GoogleCloudAiplatformV1XraiAttributionResponseOutput) ElementType 

func (GoogleCloudAiplatformV1XraiAttributionResponseOutput) ElementType() reflect.Type

func (GoogleCloudAiplatformV1XraiAttributionResponseOutput) SmoothGradConfig 

func (o GoogleCloudAiplatformV1XraiAttributionResponseOutput) SmoothGradConfig() GoogleCloudAiplatformV1SmoothGradConfigResponseOutput

Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf

func (GoogleCloudAiplatformV1XraiAttributionResponseOutput) StepCount 

func (o GoogleCloudAiplatformV1XraiAttributionResponseOutput) StepCount() pulumi.IntOutput

The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range. Valid range of its value is [1, 100], inclusively.

func (GoogleCloudAiplatformV1XraiAttributionResponseOutput) ToGoogleCloudAiplatformV1XraiAttributionResponseOutput 

func (o GoogleCloudAiplatformV1XraiAttributionResponseOutput) ToGoogleCloudAiplatformV1XraiAttributionResponseOutput() GoogleCloudAiplatformV1XraiAttributionResponseOutput

func (GoogleCloudAiplatformV1XraiAttributionResponseOutput) ToGoogleCloudAiplatformV1XraiAttributionResponseOutputWithContext 

func (o GoogleCloudAiplatformV1XraiAttributionResponseOutput) ToGoogleCloudAiplatformV1XraiAttributionResponseOutputWithContext(ctx context.Context) GoogleCloudAiplatformV1XraiAttributionResponseOutput

type GoogleIamV1Binding 

type GoogleIamV1Binding struct {
	// The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Condition *GoogleTypeExpr `pulumi:"condition"`
	// Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a Google service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid}.svc.id.goog[{namespace}/{kubernetes-sa}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how-to/kubernetes-service-accounts). For example, `my-project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding.
	Members []string `pulumi:"members"`
	// Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
	Role *string `pulumi:"role"`
}

Associates `members`, or principals, with a `role`.

type GoogleIamV1BindingArgs 

type GoogleIamV1BindingArgs struct {
	// The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Condition GoogleTypeExprPtrInput `pulumi:"condition"`
	// Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a Google service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid}.svc.id.goog[{namespace}/{kubernetes-sa}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how-to/kubernetes-service-accounts). For example, `my-project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding.
	Members pulumi.StringArrayInput `pulumi:"members"`
	// Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
	Role pulumi.StringPtrInput `pulumi:"role"`
}

Associates `members`, or principals, with a `role`.

func (GoogleIamV1BindingArgs) ElementType 

func (GoogleIamV1BindingArgs) ElementType() reflect.Type

func (GoogleIamV1BindingArgs) ToGoogleIamV1BindingOutput 

func (i GoogleIamV1BindingArgs) ToGoogleIamV1BindingOutput() GoogleIamV1BindingOutput

func (GoogleIamV1BindingArgs) ToGoogleIamV1BindingOutputWithContext 

func (i GoogleIamV1BindingArgs) ToGoogleIamV1BindingOutputWithContext(ctx context.Context) GoogleIamV1BindingOutput

type GoogleIamV1BindingArray 

type GoogleIamV1BindingArray []GoogleIamV1BindingInput

func (GoogleIamV1BindingArray) ElementType 

func (GoogleIamV1BindingArray) ElementType() reflect.Type

func (GoogleIamV1BindingArray) ToGoogleIamV1BindingArrayOutput 

func (i GoogleIamV1BindingArray) ToGoogleIamV1BindingArrayOutput() GoogleIamV1BindingArrayOutput

func (GoogleIamV1BindingArray) ToGoogleIamV1BindingArrayOutputWithContext 

func (i GoogleIamV1BindingArray) ToGoogleIamV1BindingArrayOutputWithContext(ctx context.Context) GoogleIamV1BindingArrayOutput

type GoogleIamV1BindingArrayInput 

type GoogleIamV1BindingArrayInput interface {
	pulumi.Input

	ToGoogleIamV1BindingArrayOutput() GoogleIamV1BindingArrayOutput
	ToGoogleIamV1BindingArrayOutputWithContext(context.Context) GoogleIamV1BindingArrayOutput
}

GoogleIamV1BindingArrayInput is an input type that accepts GoogleIamV1BindingArray and GoogleIamV1BindingArrayOutput values. You can construct a concrete instance of `GoogleIamV1BindingArrayInput` via: 

GoogleIamV1BindingArray{ GoogleIamV1BindingArgs{...} }

type GoogleIamV1BindingArrayOutput 

type GoogleIamV1BindingArrayOutput struct{ *pulumi.OutputState }

func (GoogleIamV1BindingArrayOutput) ElementType 

func (GoogleIamV1BindingArrayOutput) ElementType() reflect.Type

func (GoogleIamV1BindingArrayOutput) Index 

func (o GoogleIamV1BindingArrayOutput) Index(i pulumi.IntInput) GoogleIamV1BindingOutput

func (GoogleIamV1BindingArrayOutput) ToGoogleIamV1BindingArrayOutput 

func (o GoogleIamV1BindingArrayOutput) ToGoogleIamV1BindingArrayOutput() GoogleIamV1BindingArrayOutput

func (GoogleIamV1BindingArrayOutput) ToGoogleIamV1BindingArrayOutputWithContext 

func (o GoogleIamV1BindingArrayOutput) ToGoogleIamV1BindingArrayOutputWithContext(ctx context.Context) GoogleIamV1BindingArrayOutput

type GoogleIamV1BindingInput 

type GoogleIamV1BindingInput interface {
	pulumi.Input

	ToGoogleIamV1BindingOutput() GoogleIamV1BindingOutput
	ToGoogleIamV1BindingOutputWithContext(context.Context) GoogleIamV1BindingOutput
}

GoogleIamV1BindingInput is an input type that accepts GoogleIamV1BindingArgs and GoogleIamV1BindingOutput values. You can construct a concrete instance of `GoogleIamV1BindingInput` via: 

GoogleIamV1BindingArgs{...}

type GoogleIamV1BindingOutput 

type GoogleIamV1BindingOutput struct{ *pulumi.OutputState }

Associates `members`, or principals, with a `role`.

func (GoogleIamV1BindingOutput) Condition 

func (o GoogleIamV1BindingOutput) Condition() GoogleTypeExprPtrOutput

The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).

func (GoogleIamV1BindingOutput) ElementType 

func (GoogleIamV1BindingOutput) ElementType() reflect.Type

func (GoogleIamV1BindingOutput) Members 

func (o GoogleIamV1BindingOutput) Members() pulumi.StringArrayOutput

Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a Google service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid}.svc.id.goog[{namespace}/{kubernetes-sa}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how-to/kubernetes-service-accounts). For example, `my-project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding.

func (GoogleIamV1BindingOutput) Role 

func (o GoogleIamV1BindingOutput) Role() pulumi.StringPtrOutput

Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.

func (GoogleIamV1BindingOutput) ToGoogleIamV1BindingOutput 

func (o GoogleIamV1BindingOutput) ToGoogleIamV1BindingOutput() GoogleIamV1BindingOutput

func (GoogleIamV1BindingOutput) ToGoogleIamV1BindingOutputWithContext 

func (o GoogleIamV1BindingOutput) ToGoogleIamV1BindingOutputWithContext(ctx context.Context) GoogleIamV1BindingOutput

type GoogleIamV1BindingResponse 

type GoogleIamV1BindingResponse struct {
	// The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Condition GoogleTypeExprResponse `pulumi:"condition"`
	// Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a Google service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid}.svc.id.goog[{namespace}/{kubernetes-sa}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how-to/kubernetes-service-accounts). For example, `my-project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding.
	Members []string `pulumi:"members"`
	// Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
	Role string `pulumi:"role"`
}

Associates `members`, or principals, with a `role`.

type GoogleIamV1BindingResponseArrayOutput 

type GoogleIamV1BindingResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleIamV1BindingResponseArrayOutput) ElementType 

func (GoogleIamV1BindingResponseArrayOutput) ElementType() reflect.Type

func (GoogleIamV1BindingResponseArrayOutput) Index 

func (o GoogleIamV1BindingResponseArrayOutput) Index(i pulumi.IntInput) GoogleIamV1BindingResponseOutput

func (GoogleIamV1BindingResponseArrayOutput) ToGoogleIamV1BindingResponseArrayOutput 

func (o GoogleIamV1BindingResponseArrayOutput) ToGoogleIamV1BindingResponseArrayOutput() GoogleIamV1BindingResponseArrayOutput

func (GoogleIamV1BindingResponseArrayOutput) ToGoogleIamV1BindingResponseArrayOutputWithContext 

func (o GoogleIamV1BindingResponseArrayOutput) ToGoogleIamV1BindingResponseArrayOutputWithContext(ctx context.Context) GoogleIamV1BindingResponseArrayOutput

type GoogleIamV1BindingResponseOutput 

type GoogleIamV1BindingResponseOutput struct{ *pulumi.OutputState }

Associates `members`, or principals, with a `role`.

func (GoogleIamV1BindingResponseOutput) Condition 

func (o GoogleIamV1BindingResponseOutput) Condition() GoogleTypeExprResponseOutput

The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).

func (GoogleIamV1BindingResponseOutput) ElementType 

func (GoogleIamV1BindingResponseOutput) ElementType() reflect.Type

func (GoogleIamV1BindingResponseOutput) Members 

func (o GoogleIamV1BindingResponseOutput) Members() pulumi.StringArrayOutput

Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a Google service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid}.svc.id.goog[{namespace}/{kubernetes-sa}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how-to/kubernetes-service-accounts). For example, `my-project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding.

func (GoogleIamV1BindingResponseOutput) Role 

func (o GoogleIamV1BindingResponseOutput) Role() pulumi.StringOutput

Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.

func (GoogleIamV1BindingResponseOutput) ToGoogleIamV1BindingResponseOutput 

func (o GoogleIamV1BindingResponseOutput) ToGoogleIamV1BindingResponseOutput() GoogleIamV1BindingResponseOutput

func (GoogleIamV1BindingResponseOutput) ToGoogleIamV1BindingResponseOutputWithContext 

func (o GoogleIamV1BindingResponseOutput) ToGoogleIamV1BindingResponseOutputWithContext(ctx context.Context) GoogleIamV1BindingResponseOutput

type GoogleRpcStatusResponse 

type GoogleRpcStatusResponse struct {
	// The status code, which should be an enum value of google.rpc.Code.
	Code int `pulumi:"code"`
	// A list of messages that carry the error details. There is a common set of message types for APIs to use.
	Details []map[string]string `pulumi:"details"`
	// A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
	Message string `pulumi:"message"`
}

The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors).

type GoogleRpcStatusResponseArrayOutput 

type GoogleRpcStatusResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleRpcStatusResponseArrayOutput) ElementType 

func (GoogleRpcStatusResponseArrayOutput) ElementType() reflect.Type

func (GoogleRpcStatusResponseArrayOutput) Index 

func (o GoogleRpcStatusResponseArrayOutput) Index(i pulumi.IntInput) GoogleRpcStatusResponseOutput

func (GoogleRpcStatusResponseArrayOutput) ToGoogleRpcStatusResponseArrayOutput 

func (o GoogleRpcStatusResponseArrayOutput) ToGoogleRpcStatusResponseArrayOutput() GoogleRpcStatusResponseArrayOutput

func (GoogleRpcStatusResponseArrayOutput) ToGoogleRpcStatusResponseArrayOutputWithContext 

func (o GoogleRpcStatusResponseArrayOutput) ToGoogleRpcStatusResponseArrayOutputWithContext(ctx context.Context) GoogleRpcStatusResponseArrayOutput

type GoogleRpcStatusResponseOutput 

type GoogleRpcStatusResponseOutput struct{ *pulumi.OutputState }

The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors).

func (GoogleRpcStatusResponseOutput) Code 

func (o GoogleRpcStatusResponseOutput) Code() pulumi.IntOutput

The status code, which should be an enum value of google.rpc.Code.

func (GoogleRpcStatusResponseOutput) Details 

func (o GoogleRpcStatusResponseOutput) Details() pulumi.StringMapArrayOutput

A list of messages that carry the error details. There is a common set of message types for APIs to use.

func (GoogleRpcStatusResponseOutput) ElementType 

func (GoogleRpcStatusResponseOutput) ElementType() reflect.Type

func (GoogleRpcStatusResponseOutput) Message 

func (o GoogleRpcStatusResponseOutput) Message() pulumi.StringOutput

A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.

func (GoogleRpcStatusResponseOutput) ToGoogleRpcStatusResponseOutput 

func (o GoogleRpcStatusResponseOutput) ToGoogleRpcStatusResponseOutput() GoogleRpcStatusResponseOutput

func (GoogleRpcStatusResponseOutput) ToGoogleRpcStatusResponseOutputWithContext 

func (o GoogleRpcStatusResponseOutput) ToGoogleRpcStatusResponseOutputWithContext(ctx context.Context) GoogleRpcStatusResponseOutput

type GoogleTypeExpr 

type GoogleTypeExpr struct {
	// Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
	Description *string `pulumi:"description"`
	// Textual representation of an expression in Common Expression Language syntax.
	Expression *string `pulumi:"expression"`
	// Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.
	Location *string `pulumi:"location"`
	// Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.
	Title *string `pulumi:"title"`
}

Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.

type GoogleTypeExprArgs 

type GoogleTypeExprArgs struct {
	// Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
	Description pulumi.StringPtrInput `pulumi:"description"`
	// Textual representation of an expression in Common Expression Language syntax.
	Expression pulumi.StringPtrInput `pulumi:"expression"`
	// Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.
	Location pulumi.StringPtrInput `pulumi:"location"`
	// Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.
	Title pulumi.StringPtrInput `pulumi:"title"`
}

Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.

func (GoogleTypeExprArgs) ElementType 

func (GoogleTypeExprArgs) ElementType() reflect.Type

func (GoogleTypeExprArgs) ToGoogleTypeExprOutput 

func (i GoogleTypeExprArgs) ToGoogleTypeExprOutput() GoogleTypeExprOutput

func (GoogleTypeExprArgs) ToGoogleTypeExprOutputWithContext 

func (i GoogleTypeExprArgs) ToGoogleTypeExprOutputWithContext(ctx context.Context) GoogleTypeExprOutput

func (GoogleTypeExprArgs) ToGoogleTypeExprPtrOutput 

func (i GoogleTypeExprArgs) ToGoogleTypeExprPtrOutput() GoogleTypeExprPtrOutput

func (GoogleTypeExprArgs) ToGoogleTypeExprPtrOutputWithContext 

func (i GoogleTypeExprArgs) ToGoogleTypeExprPtrOutputWithContext(ctx context.Context) GoogleTypeExprPtrOutput

type GoogleTypeExprInput 

type GoogleTypeExprInput interface {
	pulumi.Input

	ToGoogleTypeExprOutput() GoogleTypeExprOutput
	ToGoogleTypeExprOutputWithContext(context.Context) GoogleTypeExprOutput
}

GoogleTypeExprInput is an input type that accepts GoogleTypeExprArgs and GoogleTypeExprOutput values. You can construct a concrete instance of `GoogleTypeExprInput` via: 

GoogleTypeExprArgs{...}

type GoogleTypeExprOutput 

type GoogleTypeExprOutput struct{ *pulumi.OutputState }

Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.

func (GoogleTypeExprOutput) Description 

func (o GoogleTypeExprOutput) Description() pulumi.StringPtrOutput

Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.

func (GoogleTypeExprOutput) ElementType 

func (GoogleTypeExprOutput) ElementType() reflect.Type

func (GoogleTypeExprOutput) Expression 

func (o GoogleTypeExprOutput) Expression() pulumi.StringPtrOutput

Textual representation of an expression in Common Expression Language syntax.

func (GoogleTypeExprOutput) Location 

func (o GoogleTypeExprOutput) Location() pulumi.StringPtrOutput

Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.

func (GoogleTypeExprOutput) Title 

func (o GoogleTypeExprOutput) Title() pulumi.StringPtrOutput

Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.

func (GoogleTypeExprOutput) ToGoogleTypeExprOutput 

func (o GoogleTypeExprOutput) ToGoogleTypeExprOutput() GoogleTypeExprOutput

func (GoogleTypeExprOutput) ToGoogleTypeExprOutputWithContext 

func (o GoogleTypeExprOutput) ToGoogleTypeExprOutputWithContext(ctx context.Context) GoogleTypeExprOutput

func (GoogleTypeExprOutput) ToGoogleTypeExprPtrOutput 

func (o GoogleTypeExprOutput) ToGoogleTypeExprPtrOutput() GoogleTypeExprPtrOutput

func (GoogleTypeExprOutput) ToGoogleTypeExprPtrOutputWithContext 

func (o GoogleTypeExprOutput) ToGoogleTypeExprPtrOutputWithContext(ctx context.Context) GoogleTypeExprPtrOutput

type GoogleTypeExprPtrInput 

type GoogleTypeExprPtrInput interface {
	pulumi.Input

	ToGoogleTypeExprPtrOutput() GoogleTypeExprPtrOutput
	ToGoogleTypeExprPtrOutputWithContext(context.Context) GoogleTypeExprPtrOutput
}

GoogleTypeExprPtrInput is an input type that accepts GoogleTypeExprArgs, GoogleTypeExprPtr and GoogleTypeExprPtrOutput values. You can construct a concrete instance of `GoogleTypeExprPtrInput` via: 

        GoogleTypeExprArgs{...}

or:

        nil

func GoogleTypeExprPtr 

func GoogleTypeExprPtr(v *GoogleTypeExprArgs) GoogleTypeExprPtrInput

type GoogleTypeExprPtrOutput 

type GoogleTypeExprPtrOutput struct{ *pulumi.OutputState }

func (GoogleTypeExprPtrOutput) Description 

func (o GoogleTypeExprPtrOutput) Description() pulumi.StringPtrOutput

Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.

func (GoogleTypeExprPtrOutput) Elem 

func (o GoogleTypeExprPtrOutput) Elem() GoogleTypeExprOutput

func (GoogleTypeExprPtrOutput) ElementType 

func (GoogleTypeExprPtrOutput) ElementType() reflect.Type

func (GoogleTypeExprPtrOutput) Expression 

func (o GoogleTypeExprPtrOutput) Expression() pulumi.StringPtrOutput

Textual representation of an expression in Common Expression Language syntax.

func (GoogleTypeExprPtrOutput) Location 

func (o GoogleTypeExprPtrOutput) Location() pulumi.StringPtrOutput

Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.

func (GoogleTypeExprPtrOutput) Title 

func (o GoogleTypeExprPtrOutput) Title() pulumi.StringPtrOutput

Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.

func (GoogleTypeExprPtrOutput) ToGoogleTypeExprPtrOutput 

func (o GoogleTypeExprPtrOutput) ToGoogleTypeExprPtrOutput() GoogleTypeExprPtrOutput

func (GoogleTypeExprPtrOutput) ToGoogleTypeExprPtrOutputWithContext 

func (o GoogleTypeExprPtrOutput) ToGoogleTypeExprPtrOutputWithContext(ctx context.Context) GoogleTypeExprPtrOutput

type GoogleTypeExprResponse 

type GoogleTypeExprResponse struct {
	// Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
	Description string `pulumi:"description"`
	// Textual representation of an expression in Common Expression Language syntax.
	Expression string `pulumi:"expression"`
	// Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.
	Location string `pulumi:"location"`
	// Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.
	Title string `pulumi:"title"`
}

Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.

type GoogleTypeExprResponseOutput 

type GoogleTypeExprResponseOutput struct{ *pulumi.OutputState }

Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.

func (GoogleTypeExprResponseOutput) Description 

func (o GoogleTypeExprResponseOutput) Description() pulumi.StringOutput

Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.

func (GoogleTypeExprResponseOutput) ElementType 

func (GoogleTypeExprResponseOutput) ElementType() reflect.Type

func (GoogleTypeExprResponseOutput) Expression 

func (o GoogleTypeExprResponseOutput) Expression() pulumi.StringOutput

Textual representation of an expression in Common Expression Language syntax.

func (GoogleTypeExprResponseOutput) Location 

func (o GoogleTypeExprResponseOutput) Location() pulumi.StringOutput

Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.

func (GoogleTypeExprResponseOutput) Title 

func (o GoogleTypeExprResponseOutput) Title() pulumi.StringOutput

Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.

func (GoogleTypeExprResponseOutput) ToGoogleTypeExprResponseOutput 

func (o GoogleTypeExprResponseOutput) ToGoogleTypeExprResponseOutput() GoogleTypeExprResponseOutput

func (GoogleTypeExprResponseOutput) ToGoogleTypeExprResponseOutputWithContext 

func (o GoogleTypeExprResponseOutput) ToGoogleTypeExprResponseOutputWithContext(ctx context.Context) GoogleTypeExprResponseOutput

type GoogleTypeMoneyResponse 

type GoogleTypeMoneyResponse struct {
	// The three-letter currency code defined in ISO 4217.
	CurrencyCode string `pulumi:"currencyCode"`
	// Number of nano (10^-9) units of the amount. The value must be between -999,999,999 and +999,999,999 inclusive. If `units` is positive, `nanos` must be positive or zero. If `units` is zero, `nanos` can be positive, zero, or negative. If `units` is negative, `nanos` must be negative or zero. For example $-1.75 is represented as `units`=-1 and `nanos`=-750,000,000.
	Nanos int `pulumi:"nanos"`
	// The whole units of the amount. For example if `currencyCode` is `"USD"`, then 1 unit is one US dollar.
	Units string `pulumi:"units"`
}

Represents an amount of money with its currency type.

type GoogleTypeMoneyResponseOutput 

type GoogleTypeMoneyResponseOutput struct{ *pulumi.OutputState }

Represents an amount of money with its currency type.

func (GoogleTypeMoneyResponseOutput) CurrencyCode 

func (o GoogleTypeMoneyResponseOutput) CurrencyCode() pulumi.StringOutput

The three-letter currency code defined in ISO 4217.

func (GoogleTypeMoneyResponseOutput) ElementType 

func (GoogleTypeMoneyResponseOutput) ElementType() reflect.Type

func (GoogleTypeMoneyResponseOutput) Nanos 

func (o GoogleTypeMoneyResponseOutput) Nanos() pulumi.IntOutput

Number of nano (10^-9) units of the amount. The value must be between -999,999,999 and +999,999,999 inclusive. If `units` is positive, `nanos` must be positive or zero. If `units` is zero, `nanos` can be positive, zero, or negative. If `units` is negative, `nanos` must be negative or zero. For example $-1.75 is represented as `units`=-1 and `nanos`=-750,000,000.

func (GoogleTypeMoneyResponseOutput) ToGoogleTypeMoneyResponseOutput 

func (o GoogleTypeMoneyResponseOutput) ToGoogleTypeMoneyResponseOutput() GoogleTypeMoneyResponseOutput

func (GoogleTypeMoneyResponseOutput) ToGoogleTypeMoneyResponseOutputWithContext 

func (o GoogleTypeMoneyResponseOutput) ToGoogleTypeMoneyResponseOutputWithContext(ctx context.Context) GoogleTypeMoneyResponseOutput

func (GoogleTypeMoneyResponseOutput) Units 

func (o GoogleTypeMoneyResponseOutput) Units() pulumi.StringOutput

The whole units of the amount. For example if `currencyCode` is `"USD"`, then 1 unit is one US dollar.

type HyperparameterTuningJob 

type HyperparameterTuningJob struct {
	pulumi.CustomResourceState

	// Time when the HyperparameterTuningJob was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// Time when the HyperparameterTuningJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
	EndTime pulumi.StringOutput `pulumi:"endTime"`
	// Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
	Error GoogleRpcStatusResponseOutput `pulumi:"error"`
	// The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.
	MaxFailedTrialCount pulumi.IntOutput `pulumi:"maxFailedTrialCount"`
	// The desired total number of Trials.
	MaxTrialCount pulumi.IntOutput `pulumi:"maxTrialCount"`
	// Resource name of the HyperparameterTuningJob.
	Name pulumi.StringOutput `pulumi:"name"`
	// The desired number of Trials to run in parallel.
	ParallelTrialCount pulumi.IntOutput    `pulumi:"parallelTrialCount"`
	Project            pulumi.StringOutput `pulumi:"project"`
	// Time when the HyperparameterTuningJob for the first time entered the `JOB_STATE_RUNNING` state.
	StartTime pulumi.StringOutput `pulumi:"startTime"`
	// The detailed state of the job.
	State pulumi.StringOutput `pulumi:"state"`
	// Study configuration of the HyperparameterTuningJob.
	StudySpec GoogleCloudAiplatformV1StudySpecResponseOutput `pulumi:"studySpec"`
	// The spec of a trial job. The same spec applies to the CustomJobs created in all the trials.
	TrialJobSpec GoogleCloudAiplatformV1CustomJobSpecResponseOutput `pulumi:"trialJobSpec"`
	// Trials of the HyperparameterTuningJob.
	Trials GoogleCloudAiplatformV1TrialResponseArrayOutput `pulumi:"trials"`
	// Time when the HyperparameterTuningJob was most recently updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a HyperparameterTuningJob Auto-naming is currently not supported for this resource.

func GetHyperparameterTuningJob 

func GetHyperparameterTuningJob(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *HyperparameterTuningJobState, opts ...pulumi.ResourceOption) (*HyperparameterTuningJob, error)

GetHyperparameterTuningJob gets an existing HyperparameterTuningJob resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewHyperparameterTuningJob 

func NewHyperparameterTuningJob(ctx *pulumi.Context,
	name string, args *HyperparameterTuningJobArgs, opts ...pulumi.ResourceOption) (*HyperparameterTuningJob, error)

NewHyperparameterTuningJob registers a new resource with the given unique name, arguments, and options.

func (*HyperparameterTuningJob) ElementType 

func (*HyperparameterTuningJob) ElementType() reflect.Type

func (*HyperparameterTuningJob) ToHyperparameterTuningJobOutput 

func (i *HyperparameterTuningJob) ToHyperparameterTuningJobOutput() HyperparameterTuningJobOutput

func (*HyperparameterTuningJob) ToHyperparameterTuningJobOutputWithContext 

func (i *HyperparameterTuningJob) ToHyperparameterTuningJobOutputWithContext(ctx context.Context) HyperparameterTuningJobOutput

type HyperparameterTuningJobArgs 

type HyperparameterTuningJobArgs struct {
	// The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringInput
	// Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.
	MaxFailedTrialCount pulumi.IntPtrInput
	// The desired total number of Trials.
	MaxTrialCount pulumi.IntInput
	// The desired number of Trials to run in parallel.
	ParallelTrialCount pulumi.IntInput
	Project            pulumi.StringPtrInput
	// Study configuration of the HyperparameterTuningJob.
	StudySpec GoogleCloudAiplatformV1StudySpecInput
	// The spec of a trial job. The same spec applies to the CustomJobs created in all the trials.
	TrialJobSpec GoogleCloudAiplatformV1CustomJobSpecInput
}

The set of arguments for constructing a HyperparameterTuningJob resource.

func (HyperparameterTuningJobArgs) ElementType 

func (HyperparameterTuningJobArgs) ElementType() reflect.Type

type HyperparameterTuningJobInput 

type HyperparameterTuningJobInput interface {
	pulumi.Input

	ToHyperparameterTuningJobOutput() HyperparameterTuningJobOutput
	ToHyperparameterTuningJobOutputWithContext(ctx context.Context) HyperparameterTuningJobOutput
}

type HyperparameterTuningJobOutput 

type HyperparameterTuningJobOutput struct{ *pulumi.OutputState }

func (HyperparameterTuningJobOutput) CreateTime 

func (o HyperparameterTuningJobOutput) CreateTime() pulumi.StringOutput

Time when the HyperparameterTuningJob was created.

func (HyperparameterTuningJobOutput) DisplayName 

func (o HyperparameterTuningJobOutput) DisplayName() pulumi.StringOutput

The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (HyperparameterTuningJobOutput) ElementType 

func (HyperparameterTuningJobOutput) ElementType() reflect.Type

func (HyperparameterTuningJobOutput) EncryptionSpec 

func (o HyperparameterTuningJobOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key.

func (HyperparameterTuningJobOutput) EndTime 

func (o HyperparameterTuningJobOutput) EndTime() pulumi.StringOutput

Time when the HyperparameterTuningJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.

func (HyperparameterTuningJobOutput) Error 

func (o HyperparameterTuningJobOutput) Error() GoogleRpcStatusResponseOutput

Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

func (HyperparameterTuningJobOutput) Labels 

func (o HyperparameterTuningJobOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (HyperparameterTuningJobOutput) Location 

func (o HyperparameterTuningJobOutput) Location() pulumi.StringOutput

func (HyperparameterTuningJobOutput) MaxFailedTrialCount 

func (o HyperparameterTuningJobOutput) MaxFailedTrialCount() pulumi.IntOutput

The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.

func (HyperparameterTuningJobOutput) MaxTrialCount 

func (o HyperparameterTuningJobOutput) MaxTrialCount() pulumi.IntOutput

The desired total number of Trials.

func (HyperparameterTuningJobOutput) Name 

func (o HyperparameterTuningJobOutput) Name() pulumi.StringOutput

Resource name of the HyperparameterTuningJob.

func (HyperparameterTuningJobOutput) ParallelTrialCount 

func (o HyperparameterTuningJobOutput) ParallelTrialCount() pulumi.IntOutput

The desired number of Trials to run in parallel.

func (HyperparameterTuningJobOutput) Project 

func (o HyperparameterTuningJobOutput) Project() pulumi.StringOutput

func (HyperparameterTuningJobOutput) StartTime 

func (o HyperparameterTuningJobOutput) StartTime() pulumi.StringOutput

Time when the HyperparameterTuningJob for the first time entered the `JOB_STATE_RUNNING` state.

func (HyperparameterTuningJobOutput) State 

func (o HyperparameterTuningJobOutput) State() pulumi.StringOutput

The detailed state of the job.

func (HyperparameterTuningJobOutput) StudySpec 

func (o HyperparameterTuningJobOutput) StudySpec() GoogleCloudAiplatformV1StudySpecResponseOutput

Study configuration of the HyperparameterTuningJob.

func (HyperparameterTuningJobOutput) ToHyperparameterTuningJobOutput 

func (o HyperparameterTuningJobOutput) ToHyperparameterTuningJobOutput() HyperparameterTuningJobOutput

func (HyperparameterTuningJobOutput) ToHyperparameterTuningJobOutputWithContext 

func (o HyperparameterTuningJobOutput) ToHyperparameterTuningJobOutputWithContext(ctx context.Context) HyperparameterTuningJobOutput

func (HyperparameterTuningJobOutput) TrialJobSpec 

func (o HyperparameterTuningJobOutput) TrialJobSpec() GoogleCloudAiplatformV1CustomJobSpecResponseOutput

The spec of a trial job. The same spec applies to the CustomJobs created in all the trials.

func (HyperparameterTuningJobOutput) Trials 

func (o HyperparameterTuningJobOutput) Trials() GoogleCloudAiplatformV1TrialResponseArrayOutput

Trials of the HyperparameterTuningJob.

func (HyperparameterTuningJobOutput) UpdateTime 

func (o HyperparameterTuningJobOutput) UpdateTime() pulumi.StringOutput

Time when the HyperparameterTuningJob was most recently updated.

type HyperparameterTuningJobState 

type HyperparameterTuningJobState struct {
}

func (HyperparameterTuningJobState) ElementType 

func (HyperparameterTuningJobState) ElementType() reflect.Type

type Index 

type Index struct {
	pulumi.CustomResourceState

	// Timestamp when this Index was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// The pointers to DeployedIndexes created from this Index. An Index can be only deleted if all its DeployedIndexes had been undeployed first.
	DeployedIndexes GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput `pulumi:"deployedIndexes"`
	// The description of the Index.
	Description pulumi.StringOutput `pulumi:"description"`
	// The display name of the Index. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Immutable. Customer-managed encryption key spec for an Index. If set, this Index and all sub-resources of this Index will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Stats of the index resource.
	IndexStats GoogleCloudAiplatformV1IndexStatsResponseOutput `pulumi:"indexStats"`
	// Immutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default.
	IndexUpdateMethod pulumi.StringOutput `pulumi:"indexUpdateMethod"`
	// The labels with user-defined metadata to organize your Indexes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// An additional information about the Index; the schema of the metadata can be found in metadata_schema.
	Metadata pulumi.AnyOutput `pulumi:"metadata"`
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Index, that is specific to it. Unset if the Index does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	MetadataSchemaUri pulumi.StringOutput `pulumi:"metadataSchemaUri"`
	// The resource name of the Index.
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// Timestamp when this Index was most recently updated. This also includes any update to the contents of the Index. Note that Operations working on this Index may have their Operations.metadata.generic_metadata.update_time a little after the value of this timestamp, yet that does not mean their results are not already reflected in the Index. Result of any successfully completed Operation on the Index is reflected in it.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates an Index. Auto-naming is currently not supported for this resource.

func GetIndex 

func GetIndex(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *IndexState, opts ...pulumi.ResourceOption) (*Index, error)

GetIndex gets an existing Index resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewIndex 

func NewIndex(ctx *pulumi.Context,
	name string, args *IndexArgs, opts ...pulumi.ResourceOption) (*Index, error)

NewIndex registers a new resource with the given unique name, arguments, and options.

func (*Index) ElementType 

func (*Index) ElementType() reflect.Type

func (*Index) ToIndexOutput 

func (i *Index) ToIndexOutput() IndexOutput

func (*Index) ToIndexOutputWithContext 

func (i *Index) ToIndexOutputWithContext(ctx context.Context) IndexOutput

type IndexArgs 

type IndexArgs struct {
	// The description of the Index.
	Description pulumi.StringPtrInput
	// The display name of the Index. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringInput
	// Immutable. Customer-managed encryption key spec for an Index. If set, this Index and all sub-resources of this Index will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// Immutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default.
	IndexUpdateMethod IndexIndexUpdateMethodPtrInput
	// The labels with user-defined metadata to organize your Indexes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// An additional information about the Index; the schema of the metadata can be found in metadata_schema.
	Metadata pulumi.Input
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Index, that is specific to it. Unset if the Index does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	MetadataSchemaUri pulumi.StringPtrInput
	Project           pulumi.StringPtrInput
}

The set of arguments for constructing a Index resource.

func (IndexArgs) ElementType 

func (IndexArgs) ElementType() reflect.Type

type IndexEndpoint 

type IndexEndpoint struct {
	pulumi.CustomResourceState

	// Timestamp when this IndexEndpoint was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// The indexes deployed in this endpoint.
	DeployedIndexes GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput `pulumi:"deployedIndexes"`
	// The description of the IndexEndpoint.
	Description pulumi.StringOutput `pulumi:"description"`
	// The display name of the IndexEndpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.
	//
	// Deprecated: Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.
	EnablePrivateServiceConnect pulumi.BoolOutput `pulumi:"enablePrivateServiceConnect"`
	// Immutable. Customer-managed encryption key spec for an IndexEndpoint. If set, this IndexEndpoint and all sub-resources of this IndexEndpoint will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// The labels with user-defined metadata to organize your IndexEndpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// The resource name of the IndexEndpoint.
	Name pulumi.StringOutput `pulumi:"name"`
	// Optional. The full name of the Google Compute Engine [network](https://cloud.google.com/compute/docs/networks-and-firewalls#networks) to which the IndexEndpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. network and private_service_connect_config are mutually exclusive. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in '12345', and {network} is network name.
	Network pulumi.StringOutput `pulumi:"network"`
	// Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive.
	PrivateServiceConnectConfig GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput `pulumi:"privateServiceConnectConfig"`
	Project                     pulumi.StringOutput                                              `pulumi:"project"`
	// If public_endpoint_enabled is true, this field will be populated with the domain name to use for this index endpoint.
	PublicEndpointDomainName pulumi.StringOutput `pulumi:"publicEndpointDomainName"`
	// Optional. If true, the deployed index will be accessible through public endpoint.
	PublicEndpointEnabled pulumi.BoolOutput `pulumi:"publicEndpointEnabled"`
	// Timestamp when this IndexEndpoint was last updated. This timestamp is not updated when the endpoint's DeployedIndexes are updated, e.g. due to updates of the original Indexes they are the deployments of.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates an IndexEndpoint. Auto-naming is currently not supported for this resource.

func GetIndexEndpoint 

func GetIndexEndpoint(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *IndexEndpointState, opts ...pulumi.ResourceOption) (*IndexEndpoint, error)

GetIndexEndpoint gets an existing IndexEndpoint resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewIndexEndpoint 

func NewIndexEndpoint(ctx *pulumi.Context,
	name string, args *IndexEndpointArgs, opts ...pulumi.ResourceOption) (*IndexEndpoint, error)

NewIndexEndpoint registers a new resource with the given unique name, arguments, and options.

func (*IndexEndpoint) ElementType 

func (*IndexEndpoint) ElementType() reflect.Type

func (*IndexEndpoint) ToIndexEndpointOutput 

func (i *IndexEndpoint) ToIndexEndpointOutput() IndexEndpointOutput

func (*IndexEndpoint) ToIndexEndpointOutputWithContext 

func (i *IndexEndpoint) ToIndexEndpointOutputWithContext(ctx context.Context) IndexEndpointOutput

type IndexEndpointArgs 

type IndexEndpointArgs struct {
	// The description of the IndexEndpoint.
	Description pulumi.StringPtrInput
	// The display name of the IndexEndpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringInput
	// Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.
	//
	// Deprecated: Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.
	EnablePrivateServiceConnect pulumi.BoolPtrInput
	// Immutable. Customer-managed encryption key spec for an IndexEndpoint. If set, this IndexEndpoint and all sub-resources of this IndexEndpoint will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// The labels with user-defined metadata to organize your IndexEndpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// Optional. The full name of the Google Compute Engine [network](https://cloud.google.com/compute/docs/networks-and-firewalls#networks) to which the IndexEndpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. network and private_service_connect_config are mutually exclusive. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in '12345', and {network} is network name.
	Network pulumi.StringPtrInput
	// Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive.
	PrivateServiceConnectConfig GoogleCloudAiplatformV1PrivateServiceConnectConfigPtrInput
	Project                     pulumi.StringPtrInput
	// Optional. If true, the deployed index will be accessible through public endpoint.
	PublicEndpointEnabled pulumi.BoolPtrInput
}

The set of arguments for constructing a IndexEndpoint resource.

func (IndexEndpointArgs) ElementType 

func (IndexEndpointArgs) ElementType() reflect.Type

type IndexEndpointInput 

type IndexEndpointInput interface {
	pulumi.Input

	ToIndexEndpointOutput() IndexEndpointOutput
	ToIndexEndpointOutputWithContext(ctx context.Context) IndexEndpointOutput
}

type IndexEndpointOutput 

type IndexEndpointOutput struct{ *pulumi.OutputState }

func (IndexEndpointOutput) CreateTime 

func (o IndexEndpointOutput) CreateTime() pulumi.StringOutput

Timestamp when this IndexEndpoint was created.

func (IndexEndpointOutput) DeployedIndexes 

func (o IndexEndpointOutput) DeployedIndexes() GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput

The indexes deployed in this endpoint.

func (IndexEndpointOutput) Description 

func (o IndexEndpointOutput) Description() pulumi.StringOutput

The description of the IndexEndpoint.

func (IndexEndpointOutput) DisplayName 

func (o IndexEndpointOutput) DisplayName() pulumi.StringOutput

The display name of the IndexEndpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (IndexEndpointOutput) ElementType 

func (IndexEndpointOutput) ElementType() reflect.Type

func (IndexEndpointOutput) EnablePrivateServiceConnect deprecated 

func (o IndexEndpointOutput) EnablePrivateServiceConnect() pulumi.BoolOutput

Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.

Deprecated: Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.

func (IndexEndpointOutput) EncryptionSpec 

func (o IndexEndpointOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Immutable. Customer-managed encryption key spec for an IndexEndpoint. If set, this IndexEndpoint and all sub-resources of this IndexEndpoint will be secured by this key.

func (IndexEndpointOutput) Etag 

func (o IndexEndpointOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (IndexEndpointOutput) Labels 

func (o IndexEndpointOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your IndexEndpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (IndexEndpointOutput) Location 

func (o IndexEndpointOutput) Location() pulumi.StringOutput

func (IndexEndpointOutput) Name 

func (o IndexEndpointOutput) Name() pulumi.StringOutput

The resource name of the IndexEndpoint.

func (IndexEndpointOutput) Network 

func (o IndexEndpointOutput) Network() pulumi.StringOutput

Optional. The full name of the Google Compute Engine [network](https://cloud.google.com/compute/docs/networks-and-firewalls#networks) to which the IndexEndpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. network and private_service_connect_config are mutually exclusive. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in '12345', and {network} is network name.

func (IndexEndpointOutput) PrivateServiceConnectConfig 

func (o IndexEndpointOutput) PrivateServiceConnectConfig() GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput

Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive.

func (IndexEndpointOutput) Project 

func (o IndexEndpointOutput) Project() pulumi.StringOutput

func (IndexEndpointOutput) PublicEndpointDomainName 

func (o IndexEndpointOutput) PublicEndpointDomainName() pulumi.StringOutput

If public_endpoint_enabled is true, this field will be populated with the domain name to use for this index endpoint.

func (IndexEndpointOutput) PublicEndpointEnabled 

func (o IndexEndpointOutput) PublicEndpointEnabled() pulumi.BoolOutput

Optional. If true, the deployed index will be accessible through public endpoint.

func (IndexEndpointOutput) ToIndexEndpointOutput 

func (o IndexEndpointOutput) ToIndexEndpointOutput() IndexEndpointOutput

func (IndexEndpointOutput) ToIndexEndpointOutputWithContext 

func (o IndexEndpointOutput) ToIndexEndpointOutputWithContext(ctx context.Context) IndexEndpointOutput

func (IndexEndpointOutput) UpdateTime 

func (o IndexEndpointOutput) UpdateTime() pulumi.StringOutput

Timestamp when this IndexEndpoint was last updated. This timestamp is not updated when the endpoint's DeployedIndexes are updated, e.g. due to updates of the original Indexes they are the deployments of.

type IndexEndpointState 

type IndexEndpointState struct {
}

func (IndexEndpointState) ElementType 

func (IndexEndpointState) ElementType() reflect.Type

type IndexIndexUpdateMethod 

type IndexIndexUpdateMethod string

Immutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default.

func (IndexIndexUpdateMethod) ElementType 

func (IndexIndexUpdateMethod) ElementType() reflect.Type

func (IndexIndexUpdateMethod) ToIndexIndexUpdateMethodOutput 

func (e IndexIndexUpdateMethod) ToIndexIndexUpdateMethodOutput() IndexIndexUpdateMethodOutput

func (IndexIndexUpdateMethod) ToIndexIndexUpdateMethodOutputWithContext 

func (e IndexIndexUpdateMethod) ToIndexIndexUpdateMethodOutputWithContext(ctx context.Context) IndexIndexUpdateMethodOutput

func (IndexIndexUpdateMethod) ToIndexIndexUpdateMethodPtrOutput 

func (e IndexIndexUpdateMethod) ToIndexIndexUpdateMethodPtrOutput() IndexIndexUpdateMethodPtrOutput

func (IndexIndexUpdateMethod) ToIndexIndexUpdateMethodPtrOutputWithContext 

func (e IndexIndexUpdateMethod) ToIndexIndexUpdateMethodPtrOutputWithContext(ctx context.Context) IndexIndexUpdateMethodPtrOutput

func (IndexIndexUpdateMethod) ToStringOutput 

func (e IndexIndexUpdateMethod) ToStringOutput() pulumi.StringOutput

func (IndexIndexUpdateMethod) ToStringOutputWithContext 

func (e IndexIndexUpdateMethod) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (IndexIndexUpdateMethod) ToStringPtrOutput 

func (e IndexIndexUpdateMethod) ToStringPtrOutput() pulumi.StringPtrOutput

func (IndexIndexUpdateMethod) ToStringPtrOutputWithContext 

func (e IndexIndexUpdateMethod) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type IndexIndexUpdateMethodInput 

type IndexIndexUpdateMethodInput interface {
	pulumi.Input

	ToIndexIndexUpdateMethodOutput() IndexIndexUpdateMethodOutput
	ToIndexIndexUpdateMethodOutputWithContext(context.Context) IndexIndexUpdateMethodOutput
}

IndexIndexUpdateMethodInput is an input type that accepts IndexIndexUpdateMethodArgs and IndexIndexUpdateMethodOutput values. You can construct a concrete instance of `IndexIndexUpdateMethodInput` via: 

IndexIndexUpdateMethodArgs{...}

type IndexIndexUpdateMethodOutput 

type IndexIndexUpdateMethodOutput struct{ *pulumi.OutputState }

func (IndexIndexUpdateMethodOutput) ElementType 

func (IndexIndexUpdateMethodOutput) ElementType() reflect.Type

func (IndexIndexUpdateMethodOutput) ToIndexIndexUpdateMethodOutput 

func (o IndexIndexUpdateMethodOutput) ToIndexIndexUpdateMethodOutput() IndexIndexUpdateMethodOutput

func (IndexIndexUpdateMethodOutput) ToIndexIndexUpdateMethodOutputWithContext 

func (o IndexIndexUpdateMethodOutput) ToIndexIndexUpdateMethodOutputWithContext(ctx context.Context) IndexIndexUpdateMethodOutput

func (IndexIndexUpdateMethodOutput) ToIndexIndexUpdateMethodPtrOutput 

func (o IndexIndexUpdateMethodOutput) ToIndexIndexUpdateMethodPtrOutput() IndexIndexUpdateMethodPtrOutput

func (IndexIndexUpdateMethodOutput) ToIndexIndexUpdateMethodPtrOutputWithContext 

func (o IndexIndexUpdateMethodOutput) ToIndexIndexUpdateMethodPtrOutputWithContext(ctx context.Context) IndexIndexUpdateMethodPtrOutput

func (IndexIndexUpdateMethodOutput) ToStringOutput 

func (o IndexIndexUpdateMethodOutput) ToStringOutput() pulumi.StringOutput

func (IndexIndexUpdateMethodOutput) ToStringOutputWithContext 

func (o IndexIndexUpdateMethodOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (IndexIndexUpdateMethodOutput) ToStringPtrOutput 

func (o IndexIndexUpdateMethodOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (IndexIndexUpdateMethodOutput) ToStringPtrOutputWithContext 

func (o IndexIndexUpdateMethodOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type IndexIndexUpdateMethodPtrInput 

type IndexIndexUpdateMethodPtrInput interface {
	pulumi.Input

	ToIndexIndexUpdateMethodPtrOutput() IndexIndexUpdateMethodPtrOutput
	ToIndexIndexUpdateMethodPtrOutputWithContext(context.Context) IndexIndexUpdateMethodPtrOutput
}

func IndexIndexUpdateMethodPtr 

func IndexIndexUpdateMethodPtr(v string) IndexIndexUpdateMethodPtrInput

type IndexIndexUpdateMethodPtrOutput 

type IndexIndexUpdateMethodPtrOutput struct{ *pulumi.OutputState }

func (IndexIndexUpdateMethodPtrOutput) Elem 

func (o IndexIndexUpdateMethodPtrOutput) Elem() IndexIndexUpdateMethodOutput

func (IndexIndexUpdateMethodPtrOutput) ElementType 

func (IndexIndexUpdateMethodPtrOutput) ElementType() reflect.Type

func (IndexIndexUpdateMethodPtrOutput) ToIndexIndexUpdateMethodPtrOutput 

func (o IndexIndexUpdateMethodPtrOutput) ToIndexIndexUpdateMethodPtrOutput() IndexIndexUpdateMethodPtrOutput

func (IndexIndexUpdateMethodPtrOutput) ToIndexIndexUpdateMethodPtrOutputWithContext 

func (o IndexIndexUpdateMethodPtrOutput) ToIndexIndexUpdateMethodPtrOutputWithContext(ctx context.Context) IndexIndexUpdateMethodPtrOutput

func (IndexIndexUpdateMethodPtrOutput) ToStringPtrOutput 

func (o IndexIndexUpdateMethodPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (IndexIndexUpdateMethodPtrOutput) ToStringPtrOutputWithContext 

func (o IndexIndexUpdateMethodPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type IndexInput 

type IndexInput interface {
	pulumi.Input

	ToIndexOutput() IndexOutput
	ToIndexOutputWithContext(ctx context.Context) IndexOutput
}

type IndexOutput 

type IndexOutput struct{ *pulumi.OutputState }

func (IndexOutput) CreateTime 

func (o IndexOutput) CreateTime() pulumi.StringOutput

Timestamp when this Index was created.

func (IndexOutput) DeployedIndexes 

func (o IndexOutput) DeployedIndexes() GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput

The pointers to DeployedIndexes created from this Index. An Index can be only deleted if all its DeployedIndexes had been undeployed first.

func (IndexOutput) Description 

func (o IndexOutput) Description() pulumi.StringOutput

The description of the Index.

func (IndexOutput) DisplayName 

func (o IndexOutput) DisplayName() pulumi.StringOutput

The display name of the Index. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (IndexOutput) ElementType 

func (IndexOutput) ElementType() reflect.Type

func (IndexOutput) EncryptionSpec 

func (o IndexOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Immutable. Customer-managed encryption key spec for an Index. If set, this Index and all sub-resources of this Index will be secured by this key.

func (IndexOutput) Etag 

func (o IndexOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (IndexOutput) IndexStats 

func (o IndexOutput) IndexStats() GoogleCloudAiplatformV1IndexStatsResponseOutput

Stats of the index resource.

func (IndexOutput) IndexUpdateMethod 

func (o IndexOutput) IndexUpdateMethod() pulumi.StringOutput

Immutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default.

func (IndexOutput) Labels 

func (o IndexOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Indexes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (IndexOutput) Location 

func (o IndexOutput) Location() pulumi.StringOutput

func (IndexOutput) Metadata 

func (o IndexOutput) Metadata() pulumi.AnyOutput

An additional information about the Index; the schema of the metadata can be found in metadata_schema.

func (IndexOutput) MetadataSchemaUri 

func (o IndexOutput) MetadataSchemaUri() pulumi.StringOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Index, that is specific to it. Unset if the Index does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (IndexOutput) Name 

func (o IndexOutput) Name() pulumi.StringOutput

The resource name of the Index.

func (IndexOutput) Project 

func (o IndexOutput) Project() pulumi.StringOutput

func (IndexOutput) ToIndexOutput 

func (o IndexOutput) ToIndexOutput() IndexOutput

func (IndexOutput) ToIndexOutputWithContext 

func (o IndexOutput) ToIndexOutputWithContext(ctx context.Context) IndexOutput

func (IndexOutput) UpdateTime 

func (o IndexOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Index was most recently updated. This also includes any update to the contents of the Index. Note that Operations working on this Index may have their Operations.metadata.generic_metadata.update_time a little after the value of this timestamp, yet that does not mean their results are not already reflected in the Index. Result of any successfully completed Operation on the Index is reflected in it.

type IndexState 

type IndexState struct {
}

func (IndexState) ElementType 

func (IndexState) ElementType() reflect.Type

type LookupArtifactArgs 

type LookupArtifactArgs struct {
	ArtifactId      string  `pulumi:"artifactId"`
	Location        string  `pulumi:"location"`
	MetadataStoreId string  `pulumi:"metadataStoreId"`
	Project         *string `pulumi:"project"`
}

type LookupArtifactOutputArgs 

type LookupArtifactOutputArgs struct {
	ArtifactId      pulumi.StringInput    `pulumi:"artifactId"`
	Location        pulumi.StringInput    `pulumi:"location"`
	MetadataStoreId pulumi.StringInput    `pulumi:"metadataStoreId"`
	Project         pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupArtifactOutputArgs) ElementType 

func (LookupArtifactOutputArgs) ElementType() reflect.Type

type LookupArtifactResult 

type LookupArtifactResult struct {
	// Timestamp when this Artifact was created.
	CreateTime string `pulumi:"createTime"`
	// Description of the Artifact
	Description string `pulumi:"description"`
	// User provided display name of the Artifact. May be up to 128 Unicode characters.
	DisplayName string `pulumi:"displayName"`
	// An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).
	Labels map[string]string `pulumi:"labels"`
	// Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
	Metadata map[string]string `pulumi:"metadata"`
	// The resource name of the Artifact.
	Name string `pulumi:"name"`
	// The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaTitle string `pulumi:"schemaTitle"`
	// The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaVersion string `pulumi:"schemaVersion"`
	// The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.
	State string `pulumi:"state"`
	// Timestamp when this Artifact was last updated.
	UpdateTime string `pulumi:"updateTime"`
	// The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
	Uri string `pulumi:"uri"`
}

func LookupArtifact 

func LookupArtifact(ctx *pulumi.Context, args *LookupArtifactArgs, opts ...pulumi.InvokeOption) (*LookupArtifactResult, error)

Retrieves a specific Artifact.

type LookupArtifactResultOutput 

type LookupArtifactResultOutput struct{ *pulumi.OutputState }

func LookupArtifactOutput 

func LookupArtifactOutput(ctx *pulumi.Context, args LookupArtifactOutputArgs, opts ...pulumi.InvokeOption) LookupArtifactResultOutput

func (LookupArtifactResultOutput) CreateTime 

func (o LookupArtifactResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this Artifact was created.

func (LookupArtifactResultOutput) Description 

func (o LookupArtifactResultOutput) Description() pulumi.StringOutput

Description of the Artifact

func (LookupArtifactResultOutput) DisplayName 

func (o LookupArtifactResultOutput) DisplayName() pulumi.StringOutput

User provided display name of the Artifact. May be up to 128 Unicode characters.

func (LookupArtifactResultOutput) ElementType 

func (LookupArtifactResultOutput) ElementType() reflect.Type

func (LookupArtifactResultOutput) Etag 

func (o LookupArtifactResultOutput) Etag() pulumi.StringOutput

An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupArtifactResultOutput) Labels 

func (o LookupArtifactResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).

func (LookupArtifactResultOutput) Metadata 

func (o LookupArtifactResultOutput) Metadata() pulumi.StringMapOutput

Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.

func (LookupArtifactResultOutput) Name 

func (o LookupArtifactResultOutput) Name() pulumi.StringOutput

The resource name of the Artifact.

func (LookupArtifactResultOutput) SchemaTitle 

func (o LookupArtifactResultOutput) SchemaTitle() pulumi.StringOutput

The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (LookupArtifactResultOutput) SchemaVersion 

func (o LookupArtifactResultOutput) SchemaVersion() pulumi.StringOutput

The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (LookupArtifactResultOutput) State 

func (o LookupArtifactResultOutput) State() pulumi.StringOutput

The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions.

func (LookupArtifactResultOutput) ToLookupArtifactResultOutput 

func (o LookupArtifactResultOutput) ToLookupArtifactResultOutput() LookupArtifactResultOutput

func (LookupArtifactResultOutput) ToLookupArtifactResultOutputWithContext 

func (o LookupArtifactResultOutput) ToLookupArtifactResultOutputWithContext(ctx context.Context) LookupArtifactResultOutput

func (LookupArtifactResultOutput) UpdateTime 

func (o LookupArtifactResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Artifact was last updated.

func (LookupArtifactResultOutput) Uri 

func (o LookupArtifactResultOutput) Uri() pulumi.StringOutput

The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.

type LookupBatchPredictionJobArgs 

type LookupBatchPredictionJobArgs struct {
	BatchPredictionJobId string  `pulumi:"batchPredictionJobId"`
	Location             string  `pulumi:"location"`
	Project              *string `pulumi:"project"`
}

type LookupBatchPredictionJobOutputArgs 

type LookupBatchPredictionJobOutputArgs struct {
	BatchPredictionJobId pulumi.StringInput    `pulumi:"batchPredictionJobId"`
	Location             pulumi.StringInput    `pulumi:"location"`
	Project              pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupBatchPredictionJobOutputArgs) ElementType 

func (LookupBatchPredictionJobOutputArgs) ElementType() reflect.Type

type LookupBatchPredictionJobResult 

type LookupBatchPredictionJobResult struct {
	// Statistics on completed and failed prediction instances.
	CompletionStats GoogleCloudAiplatformV1CompletionStatsResponse `pulumi:"completionStats"`
	// Time when the BatchPredictionJob was created.
	CreateTime string `pulumi:"createTime"`
	// The config of resources used by the Model during the batch prediction. If the Model supports DEDICATED_RESOURCES this config may be provided (and the job will use these resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config must be provided.
	DedicatedResources GoogleCloudAiplatformV1BatchDedicatedResourcesResponse `pulumi:"dedicatedResources"`
	// For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.
	DisableContainerLogging bool `pulumi:"disableContainerLogging"`
	// The user-defined name of this BatchPredictionJob.
	DisplayName string `pulumi:"displayName"`
	// Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Time when the BatchPredictionJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
	EndTime string `pulumi:"endTime"`
	// Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
	Error GoogleRpcStatusResponse `pulumi:"error"`
	// Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to `true`. This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited.
	ExplanationSpec GoogleCloudAiplatformV1ExplanationSpecResponse `pulumi:"explanationSpec"`
	// Generate explanation with the batch prediction results. When set to `true`, the batch prediction output changes based on the `predictions_format` field of the BatchPredictionJob.output_config object: * `bigquery`: output includes a column named `explanation`. The value is a struct that conforms to the Explanation object. * `jsonl`: The JSON objects on each line include an additional entry keyed `explanation`. The value of the entry is a JSON object that conforms to the Explanation object. * `csv`: Generating explanations for CSV format is not supported. If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated.
	GenerateExplanation bool `pulumi:"generateExplanation"`
	// Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri.
	InputConfig GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponse `pulumi:"inputConfig"`
	// Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.
	InstanceConfig GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponse `pulumi:"instanceConfig"`
	// The labels with user-defined metadata to organize BatchPredictionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels map[string]string `pulumi:"labels"`
	// Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself).
	ManualBatchTuningParameters GoogleCloudAiplatformV1ManualBatchTuningParametersResponse `pulumi:"manualBatchTuningParameters"`
	// The name of the Model resource that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources. Exactly one of model and unmanaged_container_model must be set. The model resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed. The model resource could also be a publisher model. Example: `publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`
	Model string `pulumi:"model"`
	// The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.
	ModelParameters interface{} `pulumi:"modelParameters"`
	// The version ID of the Model that produces the predictions via this job.
	ModelVersionId string `pulumi:"modelVersionId"`
	// Resource name of the BatchPredictionJob.
	Name string `pulumi:"name"`
	// The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of Model's PredictSchemata's instance_schema_uri and prediction_schema_uri.
	OutputConfig GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponse `pulumi:"outputConfig"`
	// Information further describing the output of this job.
	OutputInfo GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponse `pulumi:"outputInfo"`
	// Partial failures encountered. For example, single files that can't be read. This field never exceeds 20 entries. Status details fields contain standard Google Cloud error details.
	PartialFailures []GoogleRpcStatusResponse `pulumi:"partialFailures"`
	// Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes. Note: This field currently may be not populated for batch predictions that use AutoML Models.
	ResourcesConsumed GoogleCloudAiplatformV1ResourcesConsumedResponse `pulumi:"resourcesConsumed"`
	// The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.
	ServiceAccount string `pulumi:"serviceAccount"`
	// Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state.
	StartTime string `pulumi:"startTime"`
	// The detailed state of the job.
	State string `pulumi:"state"`
	// Contains model information necessary to perform batch prediction without requiring uploading to model registry. Exactly one of model and unmanaged_container_model must be set.
	UnmanagedContainerModel GoogleCloudAiplatformV1UnmanagedContainerModelResponse `pulumi:"unmanagedContainerModel"`
	// Time when the BatchPredictionJob was most recently updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupBatchPredictionJob 

func LookupBatchPredictionJob(ctx *pulumi.Context, args *LookupBatchPredictionJobArgs, opts ...pulumi.InvokeOption) (*LookupBatchPredictionJobResult, error)

Gets a BatchPredictionJob

type LookupBatchPredictionJobResultOutput 

type LookupBatchPredictionJobResultOutput struct{ *pulumi.OutputState }

func LookupBatchPredictionJobOutput 

func LookupBatchPredictionJobOutput(ctx *pulumi.Context, args LookupBatchPredictionJobOutputArgs, opts ...pulumi.InvokeOption) LookupBatchPredictionJobResultOutput

func (LookupBatchPredictionJobResultOutput) CompletionStats 

func (o LookupBatchPredictionJobResultOutput) CompletionStats() GoogleCloudAiplatformV1CompletionStatsResponseOutput

Statistics on completed and failed prediction instances.

func (LookupBatchPredictionJobResultOutput) CreateTime 

func (o LookupBatchPredictionJobResultOutput) CreateTime() pulumi.StringOutput

Time when the BatchPredictionJob was created.

func (LookupBatchPredictionJobResultOutput) DedicatedResources 

func (o LookupBatchPredictionJobResultOutput) DedicatedResources() GoogleCloudAiplatformV1BatchDedicatedResourcesResponseOutput

The config of resources used by the Model during the batch prediction. If the Model supports DEDICATED_RESOURCES this config may be provided (and the job will use these resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config must be provided.

func (LookupBatchPredictionJobResultOutput) DisableContainerLogging 

func (o LookupBatchPredictionJobResultOutput) DisableContainerLogging() pulumi.BoolOutput

For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.

func (LookupBatchPredictionJobResultOutput) DisplayName 

func (o LookupBatchPredictionJobResultOutput) DisplayName() pulumi.StringOutput

The user-defined name of this BatchPredictionJob.

func (LookupBatchPredictionJobResultOutput) ElementType 

func (LookupBatchPredictionJobResultOutput) ElementType() reflect.Type

func (LookupBatchPredictionJobResultOutput) EncryptionSpec 

func (o LookupBatchPredictionJobResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key.

func (LookupBatchPredictionJobResultOutput) EndTime 

func (o LookupBatchPredictionJobResultOutput) EndTime() pulumi.StringOutput

Time when the BatchPredictionJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.

func (LookupBatchPredictionJobResultOutput) Error 

func (o LookupBatchPredictionJobResultOutput) Error() GoogleRpcStatusResponseOutput

Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

func (LookupBatchPredictionJobResultOutput) ExplanationSpec 

func (o LookupBatchPredictionJobResultOutput) ExplanationSpec() GoogleCloudAiplatformV1ExplanationSpecResponseOutput

Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to `true`. This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited.

func (LookupBatchPredictionJobResultOutput) GenerateExplanation 

func (o LookupBatchPredictionJobResultOutput) GenerateExplanation() pulumi.BoolOutput

Generate explanation with the batch prediction results. When set to `true`, the batch prediction output changes based on the `predictions_format` field of the BatchPredictionJob.output_config object: * `bigquery`: output includes a column named `explanation`. The value is a struct that conforms to the Explanation object. * `jsonl`: The JSON objects on each line include an additional entry keyed `explanation`. The value of the entry is a JSON object that conforms to the Explanation object. * `csv`: Generating explanations for CSV format is not supported. If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated.

func (LookupBatchPredictionJobResultOutput) InputConfig 

func (o LookupBatchPredictionJobResultOutput) InputConfig() GoogleCloudAiplatformV1BatchPredictionJobInputConfigResponseOutput

Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri.

func (LookupBatchPredictionJobResultOutput) InstanceConfig 

func (o LookupBatchPredictionJobResultOutput) InstanceConfig() GoogleCloudAiplatformV1BatchPredictionJobInstanceConfigResponseOutput

Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model.

func (LookupBatchPredictionJobResultOutput) Labels 

func (o LookupBatchPredictionJobResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize BatchPredictionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (LookupBatchPredictionJobResultOutput) ManualBatchTuningParameters 

func (o LookupBatchPredictionJobResultOutput) ManualBatchTuningParameters() GoogleCloudAiplatformV1ManualBatchTuningParametersResponseOutput

Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself).

func (LookupBatchPredictionJobResultOutput) Model 

func (o LookupBatchPredictionJobResultOutput) Model() pulumi.StringOutput

The name of the Model resource that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources. Exactly one of model and unmanaged_container_model must be set. The model resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed. The model resource could also be a publisher model. Example: `publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`

func (LookupBatchPredictionJobResultOutput) ModelParameters 

func (o LookupBatchPredictionJobResultOutput) ModelParameters() pulumi.AnyOutput

The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.

func (LookupBatchPredictionJobResultOutput) ModelVersionId 

func (o LookupBatchPredictionJobResultOutput) ModelVersionId() pulumi.StringOutput

The version ID of the Model that produces the predictions via this job.

func (LookupBatchPredictionJobResultOutput) Name 

func (o LookupBatchPredictionJobResultOutput) Name() pulumi.StringOutput

Resource name of the BatchPredictionJob.

func (LookupBatchPredictionJobResultOutput) OutputConfig 

func (o LookupBatchPredictionJobResultOutput) OutputConfig() GoogleCloudAiplatformV1BatchPredictionJobOutputConfigResponseOutput

The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of Model's PredictSchemata's instance_schema_uri and prediction_schema_uri.

func (LookupBatchPredictionJobResultOutput) OutputInfo 

func (o LookupBatchPredictionJobResultOutput) OutputInfo() GoogleCloudAiplatformV1BatchPredictionJobOutputInfoResponseOutput

Information further describing the output of this job.

func (LookupBatchPredictionJobResultOutput) PartialFailures 

func (o LookupBatchPredictionJobResultOutput) PartialFailures() GoogleRpcStatusResponseArrayOutput

Partial failures encountered. For example, single files that can't be read. This field never exceeds 20 entries. Status details fields contain standard Google Cloud error details.

func (LookupBatchPredictionJobResultOutput) ResourcesConsumed 

func (o LookupBatchPredictionJobResultOutput) ResourcesConsumed() GoogleCloudAiplatformV1ResourcesConsumedResponseOutput

Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes. Note: This field currently may be not populated for batch predictions that use AutoML Models.

func (LookupBatchPredictionJobResultOutput) ServiceAccount 

func (o LookupBatchPredictionJobResultOutput) ServiceAccount() pulumi.StringOutput

The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account.

func (LookupBatchPredictionJobResultOutput) StartTime 

func (o LookupBatchPredictionJobResultOutput) StartTime() pulumi.StringOutput

Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state.

func (LookupBatchPredictionJobResultOutput) State 

func (o LookupBatchPredictionJobResultOutput) State() pulumi.StringOutput

The detailed state of the job.

func (LookupBatchPredictionJobResultOutput) ToLookupBatchPredictionJobResultOutput 

func (o LookupBatchPredictionJobResultOutput) ToLookupBatchPredictionJobResultOutput() LookupBatchPredictionJobResultOutput

func (LookupBatchPredictionJobResultOutput) ToLookupBatchPredictionJobResultOutputWithContext 

func (o LookupBatchPredictionJobResultOutput) ToLookupBatchPredictionJobResultOutputWithContext(ctx context.Context) LookupBatchPredictionJobResultOutput

func (LookupBatchPredictionJobResultOutput) UnmanagedContainerModel 

func (o LookupBatchPredictionJobResultOutput) UnmanagedContainerModel() GoogleCloudAiplatformV1UnmanagedContainerModelResponseOutput

Contains model information necessary to perform batch prediction without requiring uploading to model registry. Exactly one of model and unmanaged_container_model must be set.

func (LookupBatchPredictionJobResultOutput) UpdateTime 

func (o LookupBatchPredictionJobResultOutput) UpdateTime() pulumi.StringOutput

Time when the BatchPredictionJob was most recently updated.

type LookupContextArgs 

type LookupContextArgs struct {
	ContextId       string  `pulumi:"contextId"`
	Location        string  `pulumi:"location"`
	MetadataStoreId string  `pulumi:"metadataStoreId"`
	Project         *string `pulumi:"project"`
}

type LookupContextOutputArgs 

type LookupContextOutputArgs struct {
	ContextId       pulumi.StringInput    `pulumi:"contextId"`
	Location        pulumi.StringInput    `pulumi:"location"`
	MetadataStoreId pulumi.StringInput    `pulumi:"metadataStoreId"`
	Project         pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupContextOutputArgs) ElementType 

func (LookupContextOutputArgs) ElementType() reflect.Type

type LookupContextResult 

type LookupContextResult struct {
	// Timestamp when this Context was created.
	CreateTime string `pulumi:"createTime"`
	// Description of the Context
	Description string `pulumi:"description"`
	// User provided display name of the Context. May be up to 128 Unicode characters.
	DisplayName string `pulumi:"displayName"`
	// An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).
	Labels map[string]string `pulumi:"labels"`
	// Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
	Metadata map[string]string `pulumi:"metadata"`
	// Immutable. The resource name of the Context.
	Name string `pulumi:"name"`
	// A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.
	ParentContexts []string `pulumi:"parentContexts"`
	// The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaTitle string `pulumi:"schemaTitle"`
	// The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaVersion string `pulumi:"schemaVersion"`
	// Timestamp when this Context was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupContext 

func LookupContext(ctx *pulumi.Context, args *LookupContextArgs, opts ...pulumi.InvokeOption) (*LookupContextResult, error)

Retrieves a specific Context.

type LookupContextResultOutput 

type LookupContextResultOutput struct{ *pulumi.OutputState }

func LookupContextOutput 

func LookupContextOutput(ctx *pulumi.Context, args LookupContextOutputArgs, opts ...pulumi.InvokeOption) LookupContextResultOutput

func (LookupContextResultOutput) CreateTime 

func (o LookupContextResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this Context was created.

func (LookupContextResultOutput) Description 

func (o LookupContextResultOutput) Description() pulumi.StringOutput

Description of the Context

func (LookupContextResultOutput) DisplayName 

func (o LookupContextResultOutput) DisplayName() pulumi.StringOutput

User provided display name of the Context. May be up to 128 Unicode characters.

func (LookupContextResultOutput) ElementType 

func (LookupContextResultOutput) ElementType() reflect.Type

func (LookupContextResultOutput) Etag 

func (o LookupContextResultOutput) Etag() pulumi.StringOutput

An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupContextResultOutput) Labels 

func (o LookupContextResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).

func (LookupContextResultOutput) Metadata 

func (o LookupContextResultOutput) Metadata() pulumi.StringMapOutput

Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.

func (LookupContextResultOutput) Name 

func (o LookupContextResultOutput) Name() pulumi.StringOutput

Immutable. The resource name of the Context.

func (LookupContextResultOutput) ParentContexts 

func (o LookupContextResultOutput) ParentContexts() pulumi.StringArrayOutput

A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.

func (LookupContextResultOutput) SchemaTitle 

func (o LookupContextResultOutput) SchemaTitle() pulumi.StringOutput

The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (LookupContextResultOutput) SchemaVersion 

func (o LookupContextResultOutput) SchemaVersion() pulumi.StringOutput

The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (LookupContextResultOutput) ToLookupContextResultOutput 

func (o LookupContextResultOutput) ToLookupContextResultOutput() LookupContextResultOutput

func (LookupContextResultOutput) ToLookupContextResultOutputWithContext 

func (o LookupContextResultOutput) ToLookupContextResultOutputWithContext(ctx context.Context) LookupContextResultOutput

func (LookupContextResultOutput) UpdateTime 

func (o LookupContextResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Context was last updated.

type LookupCustomJobArgs 

type LookupCustomJobArgs struct {
	CustomJobId string  `pulumi:"customJobId"`
	Location    string  `pulumi:"location"`
	Project     *string `pulumi:"project"`
}

type LookupCustomJobOutputArgs 

type LookupCustomJobOutputArgs struct {
	CustomJobId pulumi.StringInput    `pulumi:"customJobId"`
	Location    pulumi.StringInput    `pulumi:"location"`
	Project     pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupCustomJobOutputArgs) ElementType 

func (LookupCustomJobOutputArgs) ElementType() reflect.Type

type LookupCustomJobResult 

type LookupCustomJobResult struct {
	// Time when the CustomJob was created.
	CreateTime string `pulumi:"createTime"`
	// The display name of the CustomJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Customer-managed encryption key options for a CustomJob. If this is set, then all resources created by the CustomJob will be encrypted with the provided encryption key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Time when the CustomJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
	EndTime string `pulumi:"endTime"`
	// Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.
	Error GoogleRpcStatusResponse `pulumi:"error"`
	// Job spec.
	JobSpec GoogleCloudAiplatformV1CustomJobSpecResponse `pulumi:"jobSpec"`
	// The labels with user-defined metadata to organize CustomJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels map[string]string `pulumi:"labels"`
	// Resource name of a CustomJob.
	Name string `pulumi:"name"`
	// Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.
	StartTime string `pulumi:"startTime"`
	// The detailed state of the job.
	State string `pulumi:"state"`
	// Time when the CustomJob was most recently updated.
	UpdateTime string `pulumi:"updateTime"`
	// URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if job_spec.enable_web_access is `true`. The keys are names of each node in the training job; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.
	WebAccessUris map[string]string `pulumi:"webAccessUris"`
}

func LookupCustomJob 

func LookupCustomJob(ctx *pulumi.Context, args *LookupCustomJobArgs, opts ...pulumi.InvokeOption) (*LookupCustomJobResult, error)

Gets a CustomJob.

type LookupCustomJobResultOutput 

type LookupCustomJobResultOutput struct{ *pulumi.OutputState }

func LookupCustomJobOutput 

func LookupCustomJobOutput(ctx *pulumi.Context, args LookupCustomJobOutputArgs, opts ...pulumi.InvokeOption) LookupCustomJobResultOutput

func (LookupCustomJobResultOutput) CreateTime 

func (o LookupCustomJobResultOutput) CreateTime() pulumi.StringOutput

Time when the CustomJob was created.

func (LookupCustomJobResultOutput) DisplayName 

func (o LookupCustomJobResultOutput) DisplayName() pulumi.StringOutput

The display name of the CustomJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (LookupCustomJobResultOutput) ElementType 

func (LookupCustomJobResultOutput) ElementType() reflect.Type

func (LookupCustomJobResultOutput) EncryptionSpec 

func (o LookupCustomJobResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key options for a CustomJob. If this is set, then all resources created by the CustomJob will be encrypted with the provided encryption key.

func (LookupCustomJobResultOutput) EndTime 

func (o LookupCustomJobResultOutput) EndTime() pulumi.StringOutput

Time when the CustomJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.

func (LookupCustomJobResultOutput) Error 

func (o LookupCustomJobResultOutput) Error() GoogleRpcStatusResponseOutput

Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.

func (LookupCustomJobResultOutput) JobSpec 

func (o LookupCustomJobResultOutput) JobSpec() GoogleCloudAiplatformV1CustomJobSpecResponseOutput

Job spec.

func (LookupCustomJobResultOutput) Labels 

func (o LookupCustomJobResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize CustomJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (LookupCustomJobResultOutput) Name 

func (o LookupCustomJobResultOutput) Name() pulumi.StringOutput

Resource name of a CustomJob.

func (LookupCustomJobResultOutput) StartTime 

func (o LookupCustomJobResultOutput) StartTime() pulumi.StringOutput

Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.

func (LookupCustomJobResultOutput) State 

func (o LookupCustomJobResultOutput) State() pulumi.StringOutput

The detailed state of the job.

func (LookupCustomJobResultOutput) ToLookupCustomJobResultOutput 

func (o LookupCustomJobResultOutput) ToLookupCustomJobResultOutput() LookupCustomJobResultOutput

func (LookupCustomJobResultOutput) ToLookupCustomJobResultOutputWithContext 

func (o LookupCustomJobResultOutput) ToLookupCustomJobResultOutputWithContext(ctx context.Context) LookupCustomJobResultOutput

func (LookupCustomJobResultOutput) UpdateTime 

func (o LookupCustomJobResultOutput) UpdateTime() pulumi.StringOutput

Time when the CustomJob was most recently updated.

func (LookupCustomJobResultOutput) WebAccessUris 

func (o LookupCustomJobResultOutput) WebAccessUris() pulumi.StringMapOutput

URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if job_spec.enable_web_access is `true`. The keys are names of each node in the training job; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.

type LookupDataLabelingJobArgs 

type LookupDataLabelingJobArgs struct {
	DataLabelingJobId string  `pulumi:"dataLabelingJobId"`
	Location          string  `pulumi:"location"`
	Project           *string `pulumi:"project"`
}

type LookupDataLabelingJobOutputArgs 

type LookupDataLabelingJobOutputArgs struct {
	DataLabelingJobId pulumi.StringInput    `pulumi:"dataLabelingJobId"`
	Location          pulumi.StringInput    `pulumi:"location"`
	Project           pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupDataLabelingJobOutputArgs) ElementType 

func (LookupDataLabelingJobOutputArgs) ElementType() reflect.Type

type LookupDataLabelingJobResult 

type LookupDataLabelingJobResult struct {
	// Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy.
	ActiveLearningConfig GoogleCloudAiplatformV1ActiveLearningConfigResponse `pulumi:"activeLearningConfig"`
	// Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	AnnotationLabels map[string]string `pulumi:"annotationLabels"`
	// Timestamp when this DataLabelingJob was created.
	CreateTime string `pulumi:"createTime"`
	// Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.
	CurrentSpend GoogleTypeMoneyResponse `pulumi:"currentSpend"`
	// Dataset resource names. Right now we only support labeling from a single Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`
	Datasets []string `pulumi:"datasets"`
	// The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.
	DisplayName string `pulumi:"displayName"`
	// Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// DataLabelingJob errors. It is only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.
	Error GoogleRpcStatusResponse `pulumi:"error"`
	// Input config parameters for the DataLabelingJob.
	Inputs interface{} `pulumi:"inputs"`
	// Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder.
	InputsSchemaUri string `pulumi:"inputsSchemaUri"`
	// The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.
	InstructionUri string `pulumi:"instructionUri"`
	// Number of labelers to work on each DataItem.
	LabelerCount int `pulumi:"labelerCount"`
	// Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.
	LabelingProgress int `pulumi:"labelingProgress"`
	// The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title.
	Labels map[string]string `pulumi:"labels"`
	// Resource name of the DataLabelingJob.
	Name string `pulumi:"name"`
	// The SpecialistPools' resource names associated with this job.
	SpecialistPools []string `pulumi:"specialistPools"`
	// The detailed state of the job.
	State string `pulumi:"state"`
	// Timestamp when this DataLabelingJob was updated most recently.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupDataLabelingJob 

func LookupDataLabelingJob(ctx *pulumi.Context, args *LookupDataLabelingJobArgs, opts ...pulumi.InvokeOption) (*LookupDataLabelingJobResult, error)

Gets a DataLabelingJob.

type LookupDataLabelingJobResultOutput 

type LookupDataLabelingJobResultOutput struct{ *pulumi.OutputState }

func LookupDataLabelingJobOutput 

func LookupDataLabelingJobOutput(ctx *pulumi.Context, args LookupDataLabelingJobOutputArgs, opts ...pulumi.InvokeOption) LookupDataLabelingJobResultOutput

func (LookupDataLabelingJobResultOutput) ActiveLearningConfig 

func (o LookupDataLabelingJobResultOutput) ActiveLearningConfig() GoogleCloudAiplatformV1ActiveLearningConfigResponseOutput

Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy.

func (LookupDataLabelingJobResultOutput) AnnotationLabels 

func (o LookupDataLabelingJobResultOutput) AnnotationLabels() pulumi.StringMapOutput

Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (LookupDataLabelingJobResultOutput) CreateTime 

func (o LookupDataLabelingJobResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this DataLabelingJob was created.

func (LookupDataLabelingJobResultOutput) CurrentSpend 

func (o LookupDataLabelingJobResultOutput) CurrentSpend() GoogleTypeMoneyResponseOutput

Estimated cost(in US dollars) that the DataLabelingJob has incurred to date.

func (LookupDataLabelingJobResultOutput) Datasets 

func (o LookupDataLabelingJobResultOutput) Datasets() pulumi.StringArrayOutput

Dataset resource names. Right now we only support labeling from a single Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`

func (LookupDataLabelingJobResultOutput) DisplayName 

func (o LookupDataLabelingJobResultOutput) DisplayName() pulumi.StringOutput

The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob.

func (LookupDataLabelingJobResultOutput) ElementType 

func (LookupDataLabelingJobResultOutput) ElementType() reflect.Type

func (LookupDataLabelingJobResultOutput) EncryptionSpec 

func (o LookupDataLabelingJobResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to.

func (LookupDataLabelingJobResultOutput) Error 

func (o LookupDataLabelingJobResultOutput) Error() GoogleRpcStatusResponseOutput

DataLabelingJob errors. It is only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.

func (LookupDataLabelingJobResultOutput) Inputs 

func (o LookupDataLabelingJobResultOutput) Inputs() pulumi.AnyOutput

Input config parameters for the DataLabelingJob.

func (LookupDataLabelingJobResultOutput) InputsSchemaUri 

func (o LookupDataLabelingJobResultOutput) InputsSchemaUri() pulumi.StringOutput

Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder.

func (LookupDataLabelingJobResultOutput) InstructionUri 

func (o LookupDataLabelingJobResultOutput) InstructionUri() pulumi.StringOutput

The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets.

func (LookupDataLabelingJobResultOutput) LabelerCount 

func (o LookupDataLabelingJobResultOutput) LabelerCount() pulumi.IntOutput

Number of labelers to work on each DataItem.

func (LookupDataLabelingJobResultOutput) LabelingProgress 

func (o LookupDataLabelingJobResultOutput) LabelingProgress() pulumi.IntOutput

Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished.

func (LookupDataLabelingJobResultOutput) Labels 

func (o LookupDataLabelingJobResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title.

func (LookupDataLabelingJobResultOutput) Name 

func (o LookupDataLabelingJobResultOutput) Name() pulumi.StringOutput

Resource name of the DataLabelingJob.

func (LookupDataLabelingJobResultOutput) SpecialistPools 

func (o LookupDataLabelingJobResultOutput) SpecialistPools() pulumi.StringArrayOutput

The SpecialistPools' resource names associated with this job.

func (LookupDataLabelingJobResultOutput) State 

func (o LookupDataLabelingJobResultOutput) State() pulumi.StringOutput

The detailed state of the job.

func (LookupDataLabelingJobResultOutput) ToLookupDataLabelingJobResultOutput 

func (o LookupDataLabelingJobResultOutput) ToLookupDataLabelingJobResultOutput() LookupDataLabelingJobResultOutput

func (LookupDataLabelingJobResultOutput) ToLookupDataLabelingJobResultOutputWithContext 

func (o LookupDataLabelingJobResultOutput) ToLookupDataLabelingJobResultOutputWithContext(ctx context.Context) LookupDataLabelingJobResultOutput

func (LookupDataLabelingJobResultOutput) UpdateTime 

func (o LookupDataLabelingJobResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this DataLabelingJob was updated most recently.

type LookupDatasetArgs 

type LookupDatasetArgs struct {
	DatasetId string  `pulumi:"datasetId"`
	Location  string  `pulumi:"location"`
	Project   *string `pulumi:"project"`
	ReadMask  *string `pulumi:"readMask"`
}

type LookupDatasetOutputArgs 

type LookupDatasetOutputArgs struct {
	DatasetId pulumi.StringInput    `pulumi:"datasetId"`
	Location  pulumi.StringInput    `pulumi:"location"`
	Project   pulumi.StringPtrInput `pulumi:"project"`
	ReadMask  pulumi.StringPtrInput `pulumi:"readMask"`
}

func (LookupDatasetOutputArgs) ElementType 

func (LookupDatasetOutputArgs) ElementType() reflect.Type

type LookupDatasetResult 

type LookupDatasetResult struct {
	// Timestamp when this Dataset was created.
	CreateTime string `pulumi:"createTime"`
	// The number of DataItems in this Dataset. Only apply for non-structured Dataset.
	DataItemCount string `pulumi:"dataItemCount"`
	// The description of the Dataset.
	Description string `pulumi:"description"`
	// The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Dataset: * "aiplatform.googleapis.com/dataset_metadata_schema": output only, its value is the metadata_schema's title.
	Labels map[string]string `pulumi:"labels"`
	// Additional information about the Dataset.
	Metadata interface{} `pulumi:"metadata"`
	// The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
	MetadataArtifact string `pulumi:"metadataArtifact"`
	// Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
	MetadataSchemaUri string `pulumi:"metadataSchemaUri"`
	// The resource name of the Dataset.
	Name string `pulumi:"name"`
	// All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
	SavedQueries []GoogleCloudAiplatformV1SavedQueryResponse `pulumi:"savedQueries"`
	// Timestamp when this Dataset was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupDataset 

func LookupDataset(ctx *pulumi.Context, args *LookupDatasetArgs, opts ...pulumi.InvokeOption) (*LookupDatasetResult, error)

Gets a Dataset.

type LookupDatasetResultOutput 

type LookupDatasetResultOutput struct{ *pulumi.OutputState }

func LookupDatasetOutput 

func LookupDatasetOutput(ctx *pulumi.Context, args LookupDatasetOutputArgs, opts ...pulumi.InvokeOption) LookupDatasetResultOutput

func (LookupDatasetResultOutput) CreateTime 

func (o LookupDatasetResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this Dataset was created.

func (LookupDatasetResultOutput) DataItemCount 

func (o LookupDatasetResultOutput) DataItemCount() pulumi.StringOutput

The number of DataItems in this Dataset. Only apply for non-structured Dataset.

func (LookupDatasetResultOutput) Description 

func (o LookupDatasetResultOutput) Description() pulumi.StringOutput

The description of the Dataset.

func (LookupDatasetResultOutput) DisplayName 

func (o LookupDatasetResultOutput) DisplayName() pulumi.StringOutput

The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (LookupDatasetResultOutput) ElementType 

func (LookupDatasetResultOutput) ElementType() reflect.Type

func (LookupDatasetResultOutput) EncryptionSpec 

func (o LookupDatasetResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key.

func (LookupDatasetResultOutput) Etag 

func (o LookupDatasetResultOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupDatasetResultOutput) Labels 

func (o LookupDatasetResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Dataset: * "aiplatform.googleapis.com/dataset_metadata_schema": output only, its value is the metadata_schema's title.

func (LookupDatasetResultOutput) Metadata 

func (o LookupDatasetResultOutput) Metadata() pulumi.AnyOutput

Additional information about the Dataset.

func (LookupDatasetResultOutput) MetadataArtifact 

func (o LookupDatasetResultOutput) MetadataArtifact() pulumi.StringOutput

The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.

func (LookupDatasetResultOutput) MetadataSchemaUri 

func (o LookupDatasetResultOutput) MetadataSchemaUri() pulumi.StringOutput

Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.

func (LookupDatasetResultOutput) Name 

func (o LookupDatasetResultOutput) Name() pulumi.StringOutput

The resource name of the Dataset.

func (LookupDatasetResultOutput) SavedQueries 

func (o LookupDatasetResultOutput) SavedQueries() GoogleCloudAiplatformV1SavedQueryResponseArrayOutput

All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.

func (LookupDatasetResultOutput) ToLookupDatasetResultOutput 

func (o LookupDatasetResultOutput) ToLookupDatasetResultOutput() LookupDatasetResultOutput

func (LookupDatasetResultOutput) ToLookupDatasetResultOutputWithContext 

func (o LookupDatasetResultOutput) ToLookupDatasetResultOutputWithContext(ctx context.Context) LookupDatasetResultOutput

func (LookupDatasetResultOutput) UpdateTime 

func (o LookupDatasetResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Dataset was last updated.

type LookupDatasetVersionArgs 

type LookupDatasetVersionArgs struct {
	DatasetId        string  `pulumi:"datasetId"`
	DatasetVersionId string  `pulumi:"datasetVersionId"`
	Location         string  `pulumi:"location"`
	Project          *string `pulumi:"project"`
	ReadMask         *string `pulumi:"readMask"`
}

type LookupDatasetVersionOutputArgs 

type LookupDatasetVersionOutputArgs struct {
	DatasetId        pulumi.StringInput    `pulumi:"datasetId"`
	DatasetVersionId pulumi.StringInput    `pulumi:"datasetVersionId"`
	Location         pulumi.StringInput    `pulumi:"location"`
	Project          pulumi.StringPtrInput `pulumi:"project"`
	ReadMask         pulumi.StringPtrInput `pulumi:"readMask"`
}

func (LookupDatasetVersionOutputArgs) ElementType 

func (LookupDatasetVersionOutputArgs) ElementType() reflect.Type

type LookupDatasetVersionResult 

type LookupDatasetVersionResult struct {
	// Name of the associated BigQuery dataset.
	BigQueryDatasetName string `pulumi:"bigQueryDatasetName"`
	// Timestamp when this DatasetVersion was created.
	CreateTime string `pulumi:"createTime"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// The resource name of the DatasetVersion.
	Name string `pulumi:"name"`
	// Timestamp when this DatasetVersion was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupDatasetVersion 

func LookupDatasetVersion(ctx *pulumi.Context, args *LookupDatasetVersionArgs, opts ...pulumi.InvokeOption) (*LookupDatasetVersionResult, error)

Gets a Dataset version.

type LookupDatasetVersionResultOutput 

type LookupDatasetVersionResultOutput struct{ *pulumi.OutputState }

func LookupDatasetVersionOutput 

func LookupDatasetVersionOutput(ctx *pulumi.Context, args LookupDatasetVersionOutputArgs, opts ...pulumi.InvokeOption) LookupDatasetVersionResultOutput

func (LookupDatasetVersionResultOutput) BigQueryDatasetName 

func (o LookupDatasetVersionResultOutput) BigQueryDatasetName() pulumi.StringOutput

Name of the associated BigQuery dataset.

func (LookupDatasetVersionResultOutput) CreateTime 

func (o LookupDatasetVersionResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this DatasetVersion was created.

func (LookupDatasetVersionResultOutput) ElementType 

func (LookupDatasetVersionResultOutput) ElementType() reflect.Type

func (LookupDatasetVersionResultOutput) Etag 

func (o LookupDatasetVersionResultOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupDatasetVersionResultOutput) Name 

func (o LookupDatasetVersionResultOutput) Name() pulumi.StringOutput

The resource name of the DatasetVersion.

func (LookupDatasetVersionResultOutput) ToLookupDatasetVersionResultOutput 

func (o LookupDatasetVersionResultOutput) ToLookupDatasetVersionResultOutput() LookupDatasetVersionResultOutput

func (LookupDatasetVersionResultOutput) ToLookupDatasetVersionResultOutputWithContext 

func (o LookupDatasetVersionResultOutput) ToLookupDatasetVersionResultOutputWithContext(ctx context.Context) LookupDatasetVersionResultOutput

func (LookupDatasetVersionResultOutput) UpdateTime 

func (o LookupDatasetVersionResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this DatasetVersion was last updated.

type LookupDeploymentResourcePoolArgs 

type LookupDeploymentResourcePoolArgs struct {
	DeploymentResourcePoolId string  `pulumi:"deploymentResourcePoolId"`
	Location                 string  `pulumi:"location"`
	Project                  *string `pulumi:"project"`
}

type LookupDeploymentResourcePoolOutputArgs 

type LookupDeploymentResourcePoolOutputArgs struct {
	DeploymentResourcePoolId pulumi.StringInput    `pulumi:"deploymentResourcePoolId"`
	Location                 pulumi.StringInput    `pulumi:"location"`
	Project                  pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupDeploymentResourcePoolOutputArgs) ElementType 

func (LookupDeploymentResourcePoolOutputArgs) ElementType() reflect.Type

type LookupDeploymentResourcePoolResult 

type LookupDeploymentResourcePoolResult struct {
	// Timestamp when this DeploymentResourcePool was created.
	CreateTime string `pulumi:"createTime"`
	// The underlying DedicatedResources that the DeploymentResourcePool uses.
	DedicatedResources GoogleCloudAiplatformV1DedicatedResourcesResponse `pulumi:"dedicatedResources"`
	// Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`
	Name string `pulumi:"name"`
}

func LookupDeploymentResourcePool 

func LookupDeploymentResourcePool(ctx *pulumi.Context, args *LookupDeploymentResourcePoolArgs, opts ...pulumi.InvokeOption) (*LookupDeploymentResourcePoolResult, error)

Get a DeploymentResourcePool.

type LookupDeploymentResourcePoolResultOutput 

type LookupDeploymentResourcePoolResultOutput struct{ *pulumi.OutputState }

func LookupDeploymentResourcePoolOutput 

func LookupDeploymentResourcePoolOutput(ctx *pulumi.Context, args LookupDeploymentResourcePoolOutputArgs, opts ...pulumi.InvokeOption) LookupDeploymentResourcePoolResultOutput

func (LookupDeploymentResourcePoolResultOutput) CreateTime 

func (o LookupDeploymentResourcePoolResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this DeploymentResourcePool was created.

func (LookupDeploymentResourcePoolResultOutput) DedicatedResources 

func (o LookupDeploymentResourcePoolResultOutput) DedicatedResources() GoogleCloudAiplatformV1DedicatedResourcesResponseOutput

The underlying DedicatedResources that the DeploymentResourcePool uses.

func (LookupDeploymentResourcePoolResultOutput) ElementType 

func (LookupDeploymentResourcePoolResultOutput) ElementType() reflect.Type

func (LookupDeploymentResourcePoolResultOutput) Name 

func (o LookupDeploymentResourcePoolResultOutput) Name() pulumi.StringOutput

Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`

func (LookupDeploymentResourcePoolResultOutput) ToLookupDeploymentResourcePoolResultOutput 

func (o LookupDeploymentResourcePoolResultOutput) ToLookupDeploymentResourcePoolResultOutput() LookupDeploymentResourcePoolResultOutput

func (LookupDeploymentResourcePoolResultOutput) ToLookupDeploymentResourcePoolResultOutputWithContext 

func (o LookupDeploymentResourcePoolResultOutput) ToLookupDeploymentResourcePoolResultOutputWithContext(ctx context.Context) LookupDeploymentResourcePoolResultOutput

type LookupEndpointArgs 

type LookupEndpointArgs struct {
	EndpointId string  `pulumi:"endpointId"`
	Location   string  `pulumi:"location"`
	Project    *string `pulumi:"project"`
}

type LookupEndpointOutputArgs 

type LookupEndpointOutputArgs struct {
	EndpointId pulumi.StringInput    `pulumi:"endpointId"`
	Location   pulumi.StringInput    `pulumi:"location"`
	Project    pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupEndpointOutputArgs) ElementType 

func (LookupEndpointOutputArgs) ElementType() reflect.Type

type LookupEndpointResult 

type LookupEndpointResult struct {
	// Timestamp when this Endpoint was created.
	CreateTime string `pulumi:"createTime"`
	// The models deployed in this Endpoint. To add or remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel respectively.
	DeployedModels []GoogleCloudAiplatformV1DeployedModelResponse `pulumi:"deployedModels"`
	// The description of the Endpoint.
	Description string `pulumi:"description"`
	// The display name of the Endpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.
	//
	// Deprecated: Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.
	EnablePrivateServiceConnect bool `pulumi:"enablePrivateServiceConnect"`
	// Customer-managed encryption key spec for an Endpoint. If set, this Endpoint and all sub-resources of this Endpoint will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels map[string]string `pulumi:"labels"`
	// Resource name of the Model Monitoring job associated with this Endpoint if monitoring is enabled by JobService.CreateModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`
	ModelDeploymentMonitoringJob string `pulumi:"modelDeploymentMonitoringJob"`
	// The resource name of the Endpoint.
	Name string `pulumi:"name"`
	// Optional. The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks) to which the Endpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. Only one of the fields, network or enable_private_service_connect, can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where `{project}` is a project number, as in `12345`, and `{network}` is network name.
	Network string `pulumi:"network"`
	// Configures the request-response logging for online prediction.
	PredictRequestResponseLoggingConfig GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponse `pulumi:"predictRequestResponseLoggingConfig"`
	// A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If a DeployedModel's ID is not listed in this map, then it receives no traffic. The traffic percentage values must add up to 100, or map must be empty if the Endpoint is to not accept any traffic at a moment.
	TrafficSplit map[string]string `pulumi:"trafficSplit"`
	// Timestamp when this Endpoint was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupEndpoint 

func LookupEndpoint(ctx *pulumi.Context, args *LookupEndpointArgs, opts ...pulumi.InvokeOption) (*LookupEndpointResult, error)

Gets an Endpoint.

type LookupEndpointResultOutput 

type LookupEndpointResultOutput struct{ *pulumi.OutputState }

func LookupEndpointOutput 

func LookupEndpointOutput(ctx *pulumi.Context, args LookupEndpointOutputArgs, opts ...pulumi.InvokeOption) LookupEndpointResultOutput

func (LookupEndpointResultOutput) CreateTime 

func (o LookupEndpointResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this Endpoint was created.

func (LookupEndpointResultOutput) DeployedModels 

func (o LookupEndpointResultOutput) DeployedModels() GoogleCloudAiplatformV1DeployedModelResponseArrayOutput

The models deployed in this Endpoint. To add or remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel respectively.

func (LookupEndpointResultOutput) Description 

func (o LookupEndpointResultOutput) Description() pulumi.StringOutput

The description of the Endpoint.

func (LookupEndpointResultOutput) DisplayName 

func (o LookupEndpointResultOutput) DisplayName() pulumi.StringOutput

The display name of the Endpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (LookupEndpointResultOutput) ElementType 

func (LookupEndpointResultOutput) ElementType() reflect.Type

func (LookupEndpointResultOutput) EnablePrivateServiceConnect deprecated 

func (o LookupEndpointResultOutput) EnablePrivateServiceConnect() pulumi.BoolOutput

Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.

Deprecated: Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.

func (LookupEndpointResultOutput) EncryptionSpec 

func (o LookupEndpointResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for an Endpoint. If set, this Endpoint and all sub-resources of this Endpoint will be secured by this key.

func (LookupEndpointResultOutput) Etag 

func (o LookupEndpointResultOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupEndpointResultOutput) Labels 

func (o LookupEndpointResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (LookupEndpointResultOutput) ModelDeploymentMonitoringJob 

func (o LookupEndpointResultOutput) ModelDeploymentMonitoringJob() pulumi.StringOutput

Resource name of the Model Monitoring job associated with this Endpoint if monitoring is enabled by JobService.CreateModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`

func (LookupEndpointResultOutput) Name 

func (o LookupEndpointResultOutput) Name() pulumi.StringOutput

The resource name of the Endpoint.

func (LookupEndpointResultOutput) Network 

func (o LookupEndpointResultOutput) Network() pulumi.StringOutput

Optional. The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks) to which the Endpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. Only one of the fields, network or enable_private_service_connect, can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where `{project}` is a project number, as in `12345`, and `{network}` is network name.

func (LookupEndpointResultOutput) PredictRequestResponseLoggingConfig 

func (o LookupEndpointResultOutput) PredictRequestResponseLoggingConfig() GoogleCloudAiplatformV1PredictRequestResponseLoggingConfigResponseOutput

Configures the request-response logging for online prediction.

func (LookupEndpointResultOutput) ToLookupEndpointResultOutput 

func (o LookupEndpointResultOutput) ToLookupEndpointResultOutput() LookupEndpointResultOutput

func (LookupEndpointResultOutput) ToLookupEndpointResultOutputWithContext 

func (o LookupEndpointResultOutput) ToLookupEndpointResultOutputWithContext(ctx context.Context) LookupEndpointResultOutput

func (LookupEndpointResultOutput) TrafficSplit 

func (o LookupEndpointResultOutput) TrafficSplit() pulumi.StringMapOutput

A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If a DeployedModel's ID is not listed in this map, then it receives no traffic. The traffic percentage values must add up to 100, or map must be empty if the Endpoint is to not accept any traffic at a moment.

func (LookupEndpointResultOutput) UpdateTime 

func (o LookupEndpointResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Endpoint was last updated.

type LookupEntityTypeArgs 

type LookupEntityTypeArgs struct {
	EntityTypeId   string  `pulumi:"entityTypeId"`
	FeaturestoreId string  `pulumi:"featurestoreId"`
	Location       string  `pulumi:"location"`
	Project        *string `pulumi:"project"`
}

type LookupEntityTypeOutputArgs 

type LookupEntityTypeOutputArgs struct {
	EntityTypeId   pulumi.StringInput    `pulumi:"entityTypeId"`
	FeaturestoreId pulumi.StringInput    `pulumi:"featurestoreId"`
	Location       pulumi.StringInput    `pulumi:"location"`
	Project        pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupEntityTypeOutputArgs) ElementType 

func (LookupEntityTypeOutputArgs) ElementType() reflect.Type

type LookupEntityTypeResult 

type LookupEntityTypeResult struct {
	// Timestamp when this EntityType was created.
	CreateTime string `pulumi:"createTime"`
	// Optional. Description of the EntityType.
	Description string `pulumi:"description"`
	// Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels map[string]string `pulumi:"labels"`
	// Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
	MonitoringConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponse `pulumi:"monitoringConfig"`
	// Immutable. Name of the EntityType. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
	Name string `pulumi:"name"`
	// Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than `offline_storage_ttl_days` since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
	OfflineStorageTtlDays int `pulumi:"offlineStorageTtlDays"`
	// Timestamp when this EntityType was most recently updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupEntityType 

func LookupEntityType(ctx *pulumi.Context, args *LookupEntityTypeArgs, opts ...pulumi.InvokeOption) (*LookupEntityTypeResult, error)

Gets details of a single EntityType.

type LookupEntityTypeResultOutput 

type LookupEntityTypeResultOutput struct{ *pulumi.OutputState }

func LookupEntityTypeOutput 

func LookupEntityTypeOutput(ctx *pulumi.Context, args LookupEntityTypeOutputArgs, opts ...pulumi.InvokeOption) LookupEntityTypeResultOutput

func (LookupEntityTypeResultOutput) CreateTime 

func (o LookupEntityTypeResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this EntityType was created.

func (LookupEntityTypeResultOutput) Description 

func (o LookupEntityTypeResultOutput) Description() pulumi.StringOutput

Optional. Description of the EntityType.

func (LookupEntityTypeResultOutput) ElementType 

func (LookupEntityTypeResultOutput) ElementType() reflect.Type

func (LookupEntityTypeResultOutput) Etag 

func (o LookupEntityTypeResultOutput) Etag() pulumi.StringOutput

Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupEntityTypeResultOutput) Labels 

func (o LookupEntityTypeResultOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (LookupEntityTypeResultOutput) MonitoringConfig 

func (o LookupEntityTypeResultOutput) MonitoringConfig() GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseOutput

Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.

func (LookupEntityTypeResultOutput) Name 

func (o LookupEntityTypeResultOutput) Name() pulumi.StringOutput

Immutable. Name of the EntityType. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.

func (LookupEntityTypeResultOutput) OfflineStorageTtlDays 

func (o LookupEntityTypeResultOutput) OfflineStorageTtlDays() pulumi.IntOutput

Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than `offline_storage_ttl_days` since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.

func (LookupEntityTypeResultOutput) ToLookupEntityTypeResultOutput 

func (o LookupEntityTypeResultOutput) ToLookupEntityTypeResultOutput() LookupEntityTypeResultOutput

func (LookupEntityTypeResultOutput) ToLookupEntityTypeResultOutputWithContext 

func (o LookupEntityTypeResultOutput) ToLookupEntityTypeResultOutputWithContext(ctx context.Context) LookupEntityTypeResultOutput

func (LookupEntityTypeResultOutput) UpdateTime 

func (o LookupEntityTypeResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this EntityType was most recently updated.

type LookupExecutionArgs 

type LookupExecutionArgs struct {
	ExecutionId     string  `pulumi:"executionId"`
	Location        string  `pulumi:"location"`
	MetadataStoreId string  `pulumi:"metadataStoreId"`
	Project         *string `pulumi:"project"`
}

type LookupExecutionOutputArgs 

type LookupExecutionOutputArgs struct {
	ExecutionId     pulumi.StringInput    `pulumi:"executionId"`
	Location        pulumi.StringInput    `pulumi:"location"`
	MetadataStoreId pulumi.StringInput    `pulumi:"metadataStoreId"`
	Project         pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupExecutionOutputArgs) ElementType 

func (LookupExecutionOutputArgs) ElementType() reflect.Type

type LookupExecutionResult 

type LookupExecutionResult struct {
	// Timestamp when this Execution was created.
	CreateTime string `pulumi:"createTime"`
	// Description of the Execution
	Description string `pulumi:"description"`
	// User provided display name of the Execution. May be up to 128 Unicode characters.
	DisplayName string `pulumi:"displayName"`
	// An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).
	Labels map[string]string `pulumi:"labels"`
	// Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
	Metadata map[string]string `pulumi:"metadata"`
	// The resource name of the Execution.
	Name string `pulumi:"name"`
	// The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaTitle string `pulumi:"schemaTitle"`
	// The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.
	SchemaVersion string `pulumi:"schemaVersion"`
	// The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.
	State string `pulumi:"state"`
	// Timestamp when this Execution was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupExecution 

func LookupExecution(ctx *pulumi.Context, args *LookupExecutionArgs, opts ...pulumi.InvokeOption) (*LookupExecutionResult, error)

Retrieves a specific Execution.

type LookupExecutionResultOutput 

type LookupExecutionResultOutput struct{ *pulumi.OutputState }

func LookupExecutionOutput 

func LookupExecutionOutput(ctx *pulumi.Context, args LookupExecutionOutputArgs, opts ...pulumi.InvokeOption) LookupExecutionResultOutput

func (LookupExecutionResultOutput) CreateTime 

func (o LookupExecutionResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this Execution was created.

func (LookupExecutionResultOutput) Description 

func (o LookupExecutionResultOutput) Description() pulumi.StringOutput

Description of the Execution

func (LookupExecutionResultOutput) DisplayName 

func (o LookupExecutionResultOutput) DisplayName() pulumi.StringOutput

User provided display name of the Execution. May be up to 128 Unicode characters.

func (LookupExecutionResultOutput) ElementType 

func (LookupExecutionResultOutput) ElementType() reflect.Type

func (LookupExecutionResultOutput) Etag 

func (o LookupExecutionResultOutput) Etag() pulumi.StringOutput

An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupExecutionResultOutput) Labels 

func (o LookupExecutionResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded).

func (LookupExecutionResultOutput) Metadata 

func (o LookupExecutionResultOutput) Metadata() pulumi.StringMapOutput

Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.

func (LookupExecutionResultOutput) Name 

func (o LookupExecutionResultOutput) Name() pulumi.StringOutput

The resource name of the Execution.

func (LookupExecutionResultOutput) SchemaTitle 

func (o LookupExecutionResultOutput) SchemaTitle() pulumi.StringOutput

The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (LookupExecutionResultOutput) SchemaVersion 

func (o LookupExecutionResultOutput) SchemaVersion() pulumi.StringOutput

The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store.

func (LookupExecutionResultOutput) State 

func (o LookupExecutionResultOutput) State() pulumi.StringOutput

The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions.

func (LookupExecutionResultOutput) ToLookupExecutionResultOutput 

func (o LookupExecutionResultOutput) ToLookupExecutionResultOutput() LookupExecutionResultOutput

func (LookupExecutionResultOutput) ToLookupExecutionResultOutputWithContext 

func (o LookupExecutionResultOutput) ToLookupExecutionResultOutputWithContext(ctx context.Context) LookupExecutionResultOutput

func (LookupExecutionResultOutput) UpdateTime 

func (o LookupExecutionResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Execution was last updated.

type LookupExperimentArgs 

type LookupExperimentArgs struct {
	ExperimentId  string  `pulumi:"experimentId"`
	Location      string  `pulumi:"location"`
	Project       *string `pulumi:"project"`
	TensorboardId string  `pulumi:"tensorboardId"`
}

type LookupExperimentOutputArgs 

type LookupExperimentOutputArgs struct {
	ExperimentId  pulumi.StringInput    `pulumi:"experimentId"`
	Location      pulumi.StringInput    `pulumi:"location"`
	Project       pulumi.StringPtrInput `pulumi:"project"`
	TensorboardId pulumi.StringInput    `pulumi:"tensorboardId"`
}

func (LookupExperimentOutputArgs) ElementType 

func (LookupExperimentOutputArgs) ElementType() reflect.Type

type LookupExperimentResult 

type LookupExperimentResult struct {
	// Timestamp when this TensorboardExperiment was created.
	CreateTime string `pulumi:"createTime"`
	// Description of this TensorboardExperiment.
	Description string `pulumi:"description"`
	// User provided name of this TensorboardExperiment.
	DisplayName string `pulumi:"displayName"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// The labels with user-defined metadata to organize your TensorboardExperiment. Label keys and values cannot be longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with `aiplatform.googleapis.com/` and are immutable. The following system labels exist for each Dataset: * `aiplatform.googleapis.com/dataset_metadata_schema`: output only. Its value is the metadata_schema's title.
	Labels map[string]string `pulumi:"labels"`
	// Name of the TensorboardExperiment. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`
	Name string `pulumi:"name"`
	// Immutable. Source of the TensorboardExperiment. Example: a custom training job.
	Source string `pulumi:"source"`
	// Timestamp when this TensorboardExperiment was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupExperiment 

func LookupExperiment(ctx *pulumi.Context, args *LookupExperimentArgs, opts ...pulumi.InvokeOption) (*LookupExperimentResult, error)

Gets a TensorboardExperiment.

type LookupExperimentResultOutput 

type LookupExperimentResultOutput struct{ *pulumi.OutputState }

func LookupExperimentOutput 

func LookupExperimentOutput(ctx *pulumi.Context, args LookupExperimentOutputArgs, opts ...pulumi.InvokeOption) LookupExperimentResultOutput

func (LookupExperimentResultOutput) CreateTime 

func (o LookupExperimentResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this TensorboardExperiment was created.

func (LookupExperimentResultOutput) Description 

func (o LookupExperimentResultOutput) Description() pulumi.StringOutput

Description of this TensorboardExperiment.

func (LookupExperimentResultOutput) DisplayName 

func (o LookupExperimentResultOutput) DisplayName() pulumi.StringOutput

User provided name of this TensorboardExperiment.

func (LookupExperimentResultOutput) ElementType 

func (LookupExperimentResultOutput) ElementType() reflect.Type

func (LookupExperimentResultOutput) Etag 

func (o LookupExperimentResultOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupExperimentResultOutput) Labels 

func (o LookupExperimentResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your TensorboardExperiment. Label keys and values cannot be longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with `aiplatform.googleapis.com/` and are immutable. The following system labels exist for each Dataset: * `aiplatform.googleapis.com/dataset_metadata_schema`: output only. Its value is the metadata_schema's title.

func (LookupExperimentResultOutput) Name 

func (o LookupExperimentResultOutput) Name() pulumi.StringOutput

Name of the TensorboardExperiment. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`

func (LookupExperimentResultOutput) Source 

func (o LookupExperimentResultOutput) Source() pulumi.StringOutput

Immutable. Source of the TensorboardExperiment. Example: a custom training job.

func (LookupExperimentResultOutput) ToLookupExperimentResultOutput 

func (o LookupExperimentResultOutput) ToLookupExperimentResultOutput() LookupExperimentResultOutput

func (LookupExperimentResultOutput) ToLookupExperimentResultOutputWithContext 

func (o LookupExperimentResultOutput) ToLookupExperimentResultOutputWithContext(ctx context.Context) LookupExperimentResultOutput

func (LookupExperimentResultOutput) UpdateTime 

func (o LookupExperimentResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this TensorboardExperiment was last updated.

type LookupFeatureGroupArgs 

type LookupFeatureGroupArgs struct {
	FeatureGroupId string  `pulumi:"featureGroupId"`
	Location       string  `pulumi:"location"`
	Project        *string `pulumi:"project"`
}

type LookupFeatureGroupFeatureArgs 

type LookupFeatureGroupFeatureArgs struct {
	FeatureGroupId string  `pulumi:"featureGroupId"`
	FeatureId      string  `pulumi:"featureId"`
	Location       string  `pulumi:"location"`
	Project        *string `pulumi:"project"`
}

type LookupFeatureGroupFeatureOutputArgs 

type LookupFeatureGroupFeatureOutputArgs struct {
	FeatureGroupId pulumi.StringInput    `pulumi:"featureGroupId"`
	FeatureId      pulumi.StringInput    `pulumi:"featureId"`
	Location       pulumi.StringInput    `pulumi:"location"`
	Project        pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupFeatureGroupFeatureOutputArgs) ElementType 

func (LookupFeatureGroupFeatureOutputArgs) ElementType() reflect.Type

type LookupFeatureGroupFeatureResult 

type LookupFeatureGroupFeatureResult struct {
	// Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
	CreateTime string `pulumi:"createTime"`
	// Description of the Feature.
	Description string `pulumi:"description"`
	// Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
	DisableMonitoring bool `pulumi:"disableMonitoring"`
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels map[string]string `pulumi:"labels"`
	// Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
	MonitoringStatsAnomalies []GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponse `pulumi:"monitoringStatsAnomalies"`
	// Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.
	Name string `pulumi:"name"`
	// Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
	UpdateTime string `pulumi:"updateTime"`
	// Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
	ValueType string `pulumi:"valueType"`
	// Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
	VersionColumnName string `pulumi:"versionColumnName"`
}

func LookupFeatureGroupFeature 

func LookupFeatureGroupFeature(ctx *pulumi.Context, args *LookupFeatureGroupFeatureArgs, opts ...pulumi.InvokeOption) (*LookupFeatureGroupFeatureResult, error)

Gets details of a single Feature.

type LookupFeatureGroupFeatureResultOutput 

type LookupFeatureGroupFeatureResultOutput struct{ *pulumi.OutputState }

func LookupFeatureGroupFeatureOutput 

func LookupFeatureGroupFeatureOutput(ctx *pulumi.Context, args LookupFeatureGroupFeatureOutputArgs, opts ...pulumi.InvokeOption) LookupFeatureGroupFeatureResultOutput

func (LookupFeatureGroupFeatureResultOutput) CreateTime 

func (o LookupFeatureGroupFeatureResultOutput) CreateTime() pulumi.StringOutput

Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.

func (LookupFeatureGroupFeatureResultOutput) Description 

func (o LookupFeatureGroupFeatureResultOutput) Description() pulumi.StringOutput

Description of the Feature.

func (LookupFeatureGroupFeatureResultOutput) DisableMonitoring 

func (o LookupFeatureGroupFeatureResultOutput) DisableMonitoring() pulumi.BoolOutput

Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.

func (LookupFeatureGroupFeatureResultOutput) ElementType 

func (LookupFeatureGroupFeatureResultOutput) ElementType() reflect.Type

func (LookupFeatureGroupFeatureResultOutput) Etag 

func (o LookupFeatureGroupFeatureResultOutput) Etag() pulumi.StringOutput

Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupFeatureGroupFeatureResultOutput) Labels 

func (o LookupFeatureGroupFeatureResultOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (LookupFeatureGroupFeatureResultOutput) MonitoringStatsAnomalies 

func (o LookupFeatureGroupFeatureResultOutput) MonitoringStatsAnomalies() GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput

Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.

func (LookupFeatureGroupFeatureResultOutput) Name 

func (o LookupFeatureGroupFeatureResultOutput) Name() pulumi.StringOutput

Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.

func (LookupFeatureGroupFeatureResultOutput) ToLookupFeatureGroupFeatureResultOutput 

func (o LookupFeatureGroupFeatureResultOutput) ToLookupFeatureGroupFeatureResultOutput() LookupFeatureGroupFeatureResultOutput

func (LookupFeatureGroupFeatureResultOutput) ToLookupFeatureGroupFeatureResultOutputWithContext 

func (o LookupFeatureGroupFeatureResultOutput) ToLookupFeatureGroupFeatureResultOutputWithContext(ctx context.Context) LookupFeatureGroupFeatureResultOutput

func (LookupFeatureGroupFeatureResultOutput) UpdateTime 

func (o LookupFeatureGroupFeatureResultOutput) UpdateTime() pulumi.StringOutput

Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.

func (LookupFeatureGroupFeatureResultOutput) ValueType 

func (o LookupFeatureGroupFeatureResultOutput) ValueType() pulumi.StringOutput

Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.

func (LookupFeatureGroupFeatureResultOutput) VersionColumnName 

func (o LookupFeatureGroupFeatureResultOutput) VersionColumnName() pulumi.StringOutput

Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.

type LookupFeatureGroupOutputArgs 

type LookupFeatureGroupOutputArgs struct {
	FeatureGroupId pulumi.StringInput    `pulumi:"featureGroupId"`
	Location       pulumi.StringInput    `pulumi:"location"`
	Project        pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupFeatureGroupOutputArgs) ElementType 

func (LookupFeatureGroupOutputArgs) ElementType() reflect.Type

type LookupFeatureGroupResult 

type LookupFeatureGroupResult struct {
	// Indicates that features for this group come from BigQuery Table/View. By default treats the source as a sparse time series source, which is required to have an entity_id and a feature_timestamp column in the source.
	BigQuery GoogleCloudAiplatformV1FeatureGroupBigQueryResponse `pulumi:"bigQuery"`
	// Timestamp when this FeatureGroup was created.
	CreateTime string `pulumi:"createTime"`
	// Optional. Description of the FeatureGroup.
	Description string `pulumi:"description"`
	// Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// Optional. The labels with user-defined metadata to organize your FeatureGroup. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureGroup(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels map[string]string `pulumi:"labels"`
	// Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`
	Name string `pulumi:"name"`
	// Timestamp when this FeatureGroup was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupFeatureGroup 

func LookupFeatureGroup(ctx *pulumi.Context, args *LookupFeatureGroupArgs, opts ...pulumi.InvokeOption) (*LookupFeatureGroupResult, error)

Gets details of a single FeatureGroup.

type LookupFeatureGroupResultOutput 

type LookupFeatureGroupResultOutput struct{ *pulumi.OutputState }

func LookupFeatureGroupOutput 

func LookupFeatureGroupOutput(ctx *pulumi.Context, args LookupFeatureGroupOutputArgs, opts ...pulumi.InvokeOption) LookupFeatureGroupResultOutput

func (LookupFeatureGroupResultOutput) BigQuery 

func (o LookupFeatureGroupResultOutput) BigQuery() GoogleCloudAiplatformV1FeatureGroupBigQueryResponseOutput

Indicates that features for this group come from BigQuery Table/View. By default treats the source as a sparse time series source, which is required to have an entity_id and a feature_timestamp column in the source.

func (LookupFeatureGroupResultOutput) CreateTime 

func (o LookupFeatureGroupResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this FeatureGroup was created.

func (LookupFeatureGroupResultOutput) Description 

func (o LookupFeatureGroupResultOutput) Description() pulumi.StringOutput

Optional. Description of the FeatureGroup.

func (LookupFeatureGroupResultOutput) ElementType 

func (LookupFeatureGroupResultOutput) ElementType() reflect.Type

func (LookupFeatureGroupResultOutput) Etag 

func (o LookupFeatureGroupResultOutput) Etag() pulumi.StringOutput

Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupFeatureGroupResultOutput) Labels 

func (o LookupFeatureGroupResultOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your FeatureGroup. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureGroup(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (LookupFeatureGroupResultOutput) Name 

func (o LookupFeatureGroupResultOutput) Name() pulumi.StringOutput

Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`

func (LookupFeatureGroupResultOutput) ToLookupFeatureGroupResultOutput 

func (o LookupFeatureGroupResultOutput) ToLookupFeatureGroupResultOutput() LookupFeatureGroupResultOutput

func (LookupFeatureGroupResultOutput) ToLookupFeatureGroupResultOutputWithContext 

func (o LookupFeatureGroupResultOutput) ToLookupFeatureGroupResultOutputWithContext(ctx context.Context) LookupFeatureGroupResultOutput

func (LookupFeatureGroupResultOutput) UpdateTime 

func (o LookupFeatureGroupResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this FeatureGroup was last updated.

type LookupFeatureOnlineStoreArgs 

type LookupFeatureOnlineStoreArgs struct {
	FeatureOnlineStoreId string  `pulumi:"featureOnlineStoreId"`
	Location             string  `pulumi:"location"`
	Project              *string `pulumi:"project"`
}

type LookupFeatureOnlineStoreOutputArgs 

type LookupFeatureOnlineStoreOutputArgs struct {
	FeatureOnlineStoreId pulumi.StringInput    `pulumi:"featureOnlineStoreId"`
	Location             pulumi.StringInput    `pulumi:"location"`
	Project              pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupFeatureOnlineStoreOutputArgs) ElementType 

func (LookupFeatureOnlineStoreOutputArgs) ElementType() reflect.Type

type LookupFeatureOnlineStoreResult 

type LookupFeatureOnlineStoreResult struct {
	// Contains settings for the Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore.
	Bigtable GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponse `pulumi:"bigtable"`
	// Timestamp when this FeatureOnlineStore was created.
	CreateTime string `pulumi:"createTime"`
	// Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// Optional. The labels with user-defined metadata to organize your FeatureOnlineStore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels map[string]string `pulumi:"labels"`
	// Name of the FeatureOnlineStore. Format: `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}`
	Name string `pulumi:"name"`
	// State of the featureOnlineStore.
	State string `pulumi:"state"`
	// Timestamp when this FeatureOnlineStore was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupFeatureOnlineStore 

func LookupFeatureOnlineStore(ctx *pulumi.Context, args *LookupFeatureOnlineStoreArgs, opts ...pulumi.InvokeOption) (*LookupFeatureOnlineStoreResult, error)

Gets details of a single FeatureOnlineStore.

type LookupFeatureOnlineStoreResultOutput 

type LookupFeatureOnlineStoreResultOutput struct{ *pulumi.OutputState }

func LookupFeatureOnlineStoreOutput 

func LookupFeatureOnlineStoreOutput(ctx *pulumi.Context, args LookupFeatureOnlineStoreOutputArgs, opts ...pulumi.InvokeOption) LookupFeatureOnlineStoreResultOutput

func (LookupFeatureOnlineStoreResultOutput) Bigtable 

func (o LookupFeatureOnlineStoreResultOutput) Bigtable() GoogleCloudAiplatformV1FeatureOnlineStoreBigtableResponseOutput

Contains settings for the Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore.

func (LookupFeatureOnlineStoreResultOutput) CreateTime 

func (o LookupFeatureOnlineStoreResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this FeatureOnlineStore was created.

func (LookupFeatureOnlineStoreResultOutput) ElementType 

func (LookupFeatureOnlineStoreResultOutput) ElementType() reflect.Type

func (LookupFeatureOnlineStoreResultOutput) Etag 

func (o LookupFeatureOnlineStoreResultOutput) Etag() pulumi.StringOutput

Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupFeatureOnlineStoreResultOutput) Labels 

func (o LookupFeatureOnlineStoreResultOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your FeatureOnlineStore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (LookupFeatureOnlineStoreResultOutput) Name 

func (o LookupFeatureOnlineStoreResultOutput) Name() pulumi.StringOutput

Name of the FeatureOnlineStore. Format: `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}`

func (LookupFeatureOnlineStoreResultOutput) State 

func (o LookupFeatureOnlineStoreResultOutput) State() pulumi.StringOutput

State of the featureOnlineStore.

func (LookupFeatureOnlineStoreResultOutput) ToLookupFeatureOnlineStoreResultOutput 

func (o LookupFeatureOnlineStoreResultOutput) ToLookupFeatureOnlineStoreResultOutput() LookupFeatureOnlineStoreResultOutput

func (LookupFeatureOnlineStoreResultOutput) ToLookupFeatureOnlineStoreResultOutputWithContext 

func (o LookupFeatureOnlineStoreResultOutput) ToLookupFeatureOnlineStoreResultOutputWithContext(ctx context.Context) LookupFeatureOnlineStoreResultOutput

func (LookupFeatureOnlineStoreResultOutput) UpdateTime 

func (o LookupFeatureOnlineStoreResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this FeatureOnlineStore was last updated.

type LookupFeatureStoreFeatureArgs 

type LookupFeatureStoreFeatureArgs struct {
	EntityTypeId   string  `pulumi:"entityTypeId"`
	FeatureId      string  `pulumi:"featureId"`
	FeaturestoreId string  `pulumi:"featurestoreId"`
	Location       string  `pulumi:"location"`
	Project        *string `pulumi:"project"`
}

type LookupFeatureStoreFeatureOutputArgs 

type LookupFeatureStoreFeatureOutputArgs struct {
	EntityTypeId   pulumi.StringInput    `pulumi:"entityTypeId"`
	FeatureId      pulumi.StringInput    `pulumi:"featureId"`
	FeaturestoreId pulumi.StringInput    `pulumi:"featurestoreId"`
	Location       pulumi.StringInput    `pulumi:"location"`
	Project        pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupFeatureStoreFeatureOutputArgs) ElementType 

func (LookupFeatureStoreFeatureOutputArgs) ElementType() reflect.Type

type LookupFeatureStoreFeatureResult 

type LookupFeatureStoreFeatureResult struct {
	// Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
	CreateTime string `pulumi:"createTime"`
	// Description of the Feature.
	Description string `pulumi:"description"`
	// Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
	DisableMonitoring bool `pulumi:"disableMonitoring"`
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels map[string]string `pulumi:"labels"`
	// Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
	MonitoringStatsAnomalies []GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponse `pulumi:"monitoringStatsAnomalies"`
	// Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.
	Name string `pulumi:"name"`
	// Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
	UpdateTime string `pulumi:"updateTime"`
	// Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
	ValueType string `pulumi:"valueType"`
	// Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
	VersionColumnName string `pulumi:"versionColumnName"`
}

func LookupFeatureStoreFeature 

func LookupFeatureStoreFeature(ctx *pulumi.Context, args *LookupFeatureStoreFeatureArgs, opts ...pulumi.InvokeOption) (*LookupFeatureStoreFeatureResult, error)

Gets details of a single Feature.

type LookupFeatureStoreFeatureResultOutput 

type LookupFeatureStoreFeatureResultOutput struct{ *pulumi.OutputState }

func LookupFeatureStoreFeatureOutput 

func LookupFeatureStoreFeatureOutput(ctx *pulumi.Context, args LookupFeatureStoreFeatureOutputArgs, opts ...pulumi.InvokeOption) LookupFeatureStoreFeatureResultOutput

func (LookupFeatureStoreFeatureResultOutput) CreateTime 

func (o LookupFeatureStoreFeatureResultOutput) CreateTime() pulumi.StringOutput

Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.

func (LookupFeatureStoreFeatureResultOutput) Description 

func (o LookupFeatureStoreFeatureResultOutput) Description() pulumi.StringOutput

Description of the Feature.

func (LookupFeatureStoreFeatureResultOutput) DisableMonitoring 

func (o LookupFeatureStoreFeatureResultOutput) DisableMonitoring() pulumi.BoolOutput

Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.

func (LookupFeatureStoreFeatureResultOutput) ElementType 

func (LookupFeatureStoreFeatureResultOutput) ElementType() reflect.Type

func (LookupFeatureStoreFeatureResultOutput) Etag 

func (o LookupFeatureStoreFeatureResultOutput) Etag() pulumi.StringOutput

Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupFeatureStoreFeatureResultOutput) Labels 

func (o LookupFeatureStoreFeatureResultOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (LookupFeatureStoreFeatureResultOutput) MonitoringStatsAnomalies 

func (o LookupFeatureStoreFeatureResultOutput) MonitoringStatsAnomalies() GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArrayOutput

Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.

func (LookupFeatureStoreFeatureResultOutput) Name 

func (o LookupFeatureStoreFeatureResultOutput) Name() pulumi.StringOutput

Immutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}` `projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.

func (LookupFeatureStoreFeatureResultOutput) ToLookupFeatureStoreFeatureResultOutput 

func (o LookupFeatureStoreFeatureResultOutput) ToLookupFeatureStoreFeatureResultOutput() LookupFeatureStoreFeatureResultOutput

func (LookupFeatureStoreFeatureResultOutput) ToLookupFeatureStoreFeatureResultOutputWithContext 

func (o LookupFeatureStoreFeatureResultOutput) ToLookupFeatureStoreFeatureResultOutputWithContext(ctx context.Context) LookupFeatureStoreFeatureResultOutput

func (LookupFeatureStoreFeatureResultOutput) UpdateTime 

func (o LookupFeatureStoreFeatureResultOutput) UpdateTime() pulumi.StringOutput

Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.

func (LookupFeatureStoreFeatureResultOutput) ValueType 

func (o LookupFeatureStoreFeatureResultOutput) ValueType() pulumi.StringOutput

Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.

func (LookupFeatureStoreFeatureResultOutput) VersionColumnName 

func (o LookupFeatureStoreFeatureResultOutput) VersionColumnName() pulumi.StringOutput

Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.

type LookupFeatureViewArgs 

type LookupFeatureViewArgs struct {
	FeatureOnlineStoreId string  `pulumi:"featureOnlineStoreId"`
	FeatureViewId        string  `pulumi:"featureViewId"`
	Location             string  `pulumi:"location"`
	Project              *string `pulumi:"project"`
}

type LookupFeatureViewOutputArgs 

type LookupFeatureViewOutputArgs struct {
	FeatureOnlineStoreId pulumi.StringInput    `pulumi:"featureOnlineStoreId"`
	FeatureViewId        pulumi.StringInput    `pulumi:"featureViewId"`
	Location             pulumi.StringInput    `pulumi:"location"`
	Project              pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupFeatureViewOutputArgs) ElementType 

func (LookupFeatureViewOutputArgs) ElementType() reflect.Type

type LookupFeatureViewResult 

type LookupFeatureViewResult struct {
	// Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore.
	BigQuerySource GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponse `pulumi:"bigQuerySource"`
	// Timestamp when this FeatureView was created.
	CreateTime string `pulumi:"createTime"`
	// Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore.
	FeatureRegistrySource GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponse `pulumi:"featureRegistrySource"`
	// Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels map[string]string `pulumi:"labels"`
	// Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`
	Name string `pulumi:"name"`
	// Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving.
	SyncConfig GoogleCloudAiplatformV1FeatureViewSyncConfigResponse `pulumi:"syncConfig"`
	// Timestamp when this FeatureView was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupFeatureView 

func LookupFeatureView(ctx *pulumi.Context, args *LookupFeatureViewArgs, opts ...pulumi.InvokeOption) (*LookupFeatureViewResult, error)

Gets details of a single FeatureView.

type LookupFeatureViewResultOutput 

type LookupFeatureViewResultOutput struct{ *pulumi.OutputState }

func LookupFeatureViewOutput 

func LookupFeatureViewOutput(ctx *pulumi.Context, args LookupFeatureViewOutputArgs, opts ...pulumi.InvokeOption) LookupFeatureViewResultOutput

func (LookupFeatureViewResultOutput) BigQuerySource 

func (o LookupFeatureViewResultOutput) BigQuerySource() GoogleCloudAiplatformV1FeatureViewBigQuerySourceResponseOutput

Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore.

func (LookupFeatureViewResultOutput) CreateTime 

func (o LookupFeatureViewResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this FeatureView was created.

func (LookupFeatureViewResultOutput) ElementType 

func (LookupFeatureViewResultOutput) ElementType() reflect.Type

func (LookupFeatureViewResultOutput) Etag 

func (o LookupFeatureViewResultOutput) Etag() pulumi.StringOutput

Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupFeatureViewResultOutput) FeatureRegistrySource 

func (o LookupFeatureViewResultOutput) FeatureRegistrySource() GoogleCloudAiplatformV1FeatureViewFeatureRegistrySourceResponseOutput

Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore.

func (LookupFeatureViewResultOutput) Labels 

func (o LookupFeatureViewResultOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (LookupFeatureViewResultOutput) Name 

func (o LookupFeatureViewResultOutput) Name() pulumi.StringOutput

Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`

func (LookupFeatureViewResultOutput) SyncConfig 

func (o LookupFeatureViewResultOutput) SyncConfig() GoogleCloudAiplatformV1FeatureViewSyncConfigResponseOutput

Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving.

func (LookupFeatureViewResultOutput) ToLookupFeatureViewResultOutput 

func (o LookupFeatureViewResultOutput) ToLookupFeatureViewResultOutput() LookupFeatureViewResultOutput

func (LookupFeatureViewResultOutput) ToLookupFeatureViewResultOutputWithContext 

func (o LookupFeatureViewResultOutput) ToLookupFeatureViewResultOutputWithContext(ctx context.Context) LookupFeatureViewResultOutput

func (LookupFeatureViewResultOutput) UpdateTime 

func (o LookupFeatureViewResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this FeatureView was last updated.

type LookupFeaturestoreArgs 

type LookupFeaturestoreArgs struct {
	FeaturestoreId string  `pulumi:"featurestoreId"`
	Location       string  `pulumi:"location"`
	Project        *string `pulumi:"project"`
}

type LookupFeaturestoreEntityTypeIamPolicyArgs 

type LookupFeaturestoreEntityTypeIamPolicyArgs struct {
	EntityTypeId                  string  `pulumi:"entityTypeId"`
	FeaturestoreId                string  `pulumi:"featurestoreId"`
	Location                      string  `pulumi:"location"`
	OptionsRequestedPolicyVersion *int    `pulumi:"optionsRequestedPolicyVersion"`
	Project                       *string `pulumi:"project"`
}

type LookupFeaturestoreEntityTypeIamPolicyOutputArgs 

type LookupFeaturestoreEntityTypeIamPolicyOutputArgs struct {
	EntityTypeId                  pulumi.StringInput    `pulumi:"entityTypeId"`
	FeaturestoreId                pulumi.StringInput    `pulumi:"featurestoreId"`
	Location                      pulumi.StringInput    `pulumi:"location"`
	OptionsRequestedPolicyVersion pulumi.IntPtrInput    `pulumi:"optionsRequestedPolicyVersion"`
	Project                       pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupFeaturestoreEntityTypeIamPolicyOutputArgs) ElementType 

func (LookupFeaturestoreEntityTypeIamPolicyOutputArgs) ElementType() reflect.Type

type LookupFeaturestoreEntityTypeIamPolicyResult 

type LookupFeaturestoreEntityTypeIamPolicyResult struct {
	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings []GoogleIamV1BindingResponse `pulumi:"bindings"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag string `pulumi:"etag"`
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version int `pulumi:"version"`
}

func LookupFeaturestoreEntityTypeIamPolicy 

func LookupFeaturestoreEntityTypeIamPolicy(ctx *pulumi.Context, args *LookupFeaturestoreEntityTypeIamPolicyArgs, opts ...pulumi.InvokeOption) (*LookupFeaturestoreEntityTypeIamPolicyResult, error)

Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.

type LookupFeaturestoreEntityTypeIamPolicyResultOutput 

type LookupFeaturestoreEntityTypeIamPolicyResultOutput struct{ *pulumi.OutputState }

func LookupFeaturestoreEntityTypeIamPolicyOutput 

func LookupFeaturestoreEntityTypeIamPolicyOutput(ctx *pulumi.Context, args LookupFeaturestoreEntityTypeIamPolicyOutputArgs, opts ...pulumi.InvokeOption) LookupFeaturestoreEntityTypeIamPolicyResultOutput

func (LookupFeaturestoreEntityTypeIamPolicyResultOutput) Bindings 

func (o LookupFeaturestoreEntityTypeIamPolicyResultOutput) Bindings() GoogleIamV1BindingResponseArrayOutput

Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.

func (LookupFeaturestoreEntityTypeIamPolicyResultOutput) ElementType 

func (LookupFeaturestoreEntityTypeIamPolicyResultOutput) ElementType() reflect.Type

func (LookupFeaturestoreEntityTypeIamPolicyResultOutput) Etag 

func (o LookupFeaturestoreEntityTypeIamPolicyResultOutput) Etag() pulumi.StringOutput

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.

func (LookupFeaturestoreEntityTypeIamPolicyResultOutput) ToLookupFeaturestoreEntityTypeIamPolicyResultOutput 

func (o LookupFeaturestoreEntityTypeIamPolicyResultOutput) ToLookupFeaturestoreEntityTypeIamPolicyResultOutput() LookupFeaturestoreEntityTypeIamPolicyResultOutput

func (LookupFeaturestoreEntityTypeIamPolicyResultOutput) ToLookupFeaturestoreEntityTypeIamPolicyResultOutputWithContext 

func (o LookupFeaturestoreEntityTypeIamPolicyResultOutput) ToLookupFeaturestoreEntityTypeIamPolicyResultOutputWithContext(ctx context.Context) LookupFeaturestoreEntityTypeIamPolicyResultOutput

func (LookupFeaturestoreEntityTypeIamPolicyResultOutput) Version 

func (o LookupFeaturestoreEntityTypeIamPolicyResultOutput) Version() pulumi.IntOutput

Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).

type LookupFeaturestoreIamPolicyArgs 

type LookupFeaturestoreIamPolicyArgs struct {
	FeaturestoreId                string  `pulumi:"featurestoreId"`
	Location                      string  `pulumi:"location"`
	OptionsRequestedPolicyVersion *int    `pulumi:"optionsRequestedPolicyVersion"`
	Project                       *string `pulumi:"project"`
}

type LookupFeaturestoreIamPolicyOutputArgs 

type LookupFeaturestoreIamPolicyOutputArgs struct {
	FeaturestoreId                pulumi.StringInput    `pulumi:"featurestoreId"`
	Location                      pulumi.StringInput    `pulumi:"location"`
	OptionsRequestedPolicyVersion pulumi.IntPtrInput    `pulumi:"optionsRequestedPolicyVersion"`
	Project                       pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupFeaturestoreIamPolicyOutputArgs) ElementType 

func (LookupFeaturestoreIamPolicyOutputArgs) ElementType() reflect.Type

type LookupFeaturestoreIamPolicyResult 

type LookupFeaturestoreIamPolicyResult struct {
	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings []GoogleIamV1BindingResponse `pulumi:"bindings"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag string `pulumi:"etag"`
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version int `pulumi:"version"`
}

func LookupFeaturestoreIamPolicy 

func LookupFeaturestoreIamPolicy(ctx *pulumi.Context, args *LookupFeaturestoreIamPolicyArgs, opts ...pulumi.InvokeOption) (*LookupFeaturestoreIamPolicyResult, error)

Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.

type LookupFeaturestoreIamPolicyResultOutput 

type LookupFeaturestoreIamPolicyResultOutput struct{ *pulumi.OutputState }

func LookupFeaturestoreIamPolicyOutput 

func LookupFeaturestoreIamPolicyOutput(ctx *pulumi.Context, args LookupFeaturestoreIamPolicyOutputArgs, opts ...pulumi.InvokeOption) LookupFeaturestoreIamPolicyResultOutput

func (LookupFeaturestoreIamPolicyResultOutput) Bindings 

func (o LookupFeaturestoreIamPolicyResultOutput) Bindings() GoogleIamV1BindingResponseArrayOutput

Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.

func (LookupFeaturestoreIamPolicyResultOutput) ElementType 

func (LookupFeaturestoreIamPolicyResultOutput) ElementType() reflect.Type

func (LookupFeaturestoreIamPolicyResultOutput) Etag 

func (o LookupFeaturestoreIamPolicyResultOutput) Etag() pulumi.StringOutput

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.

func (LookupFeaturestoreIamPolicyResultOutput) ToLookupFeaturestoreIamPolicyResultOutput 

func (o LookupFeaturestoreIamPolicyResultOutput) ToLookupFeaturestoreIamPolicyResultOutput() LookupFeaturestoreIamPolicyResultOutput

func (LookupFeaturestoreIamPolicyResultOutput) ToLookupFeaturestoreIamPolicyResultOutputWithContext 

func (o LookupFeaturestoreIamPolicyResultOutput) ToLookupFeaturestoreIamPolicyResultOutputWithContext(ctx context.Context) LookupFeaturestoreIamPolicyResultOutput

func (LookupFeaturestoreIamPolicyResultOutput) Version 

func (o LookupFeaturestoreIamPolicyResultOutput) Version() pulumi.IntOutput

Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).

type LookupFeaturestoreOutputArgs 

type LookupFeaturestoreOutputArgs struct {
	FeaturestoreId pulumi.StringInput    `pulumi:"featurestoreId"`
	Location       pulumi.StringInput    `pulumi:"location"`
	Project        pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupFeaturestoreOutputArgs) ElementType 

func (LookupFeaturestoreOutputArgs) ElementType() reflect.Type

type LookupFeaturestoreResult 

type LookupFeaturestoreResult struct {
	// Timestamp when this Featurestore was created.
	CreateTime string `pulumi:"createTime"`
	// Optional. Customer-managed encryption key spec for data storage. If set, both of the online and offline data storage will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// Optional. The labels with user-defined metadata to organize your Featurestore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Featurestore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels map[string]string `pulumi:"labels"`
	// Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`
	Name string `pulumi:"name"`
	// Optional. Config for online storage resources. The field should not co-exist with the field of `OnlineStoreReplicationConfig`. If both of it and OnlineStoreReplicationConfig are unset, the feature store will not have an online store and cannot be used for online serving.
	OnlineServingConfig GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponse `pulumi:"onlineServingConfig"`
	// Optional. TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than `online_storage_ttl_days` since the feature generation time. Note that `online_storage_ttl_days` should be less than or equal to `offline_storage_ttl_days` for each EntityType under a featurestore. If not set, default to 4000 days
	OnlineStorageTtlDays int `pulumi:"onlineStorageTtlDays"`
	// State of the featurestore.
	State string `pulumi:"state"`
	// Timestamp when this Featurestore was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupFeaturestore 

func LookupFeaturestore(ctx *pulumi.Context, args *LookupFeaturestoreArgs, opts ...pulumi.InvokeOption) (*LookupFeaturestoreResult, error)

Gets details of a single Featurestore.

type LookupFeaturestoreResultOutput 

type LookupFeaturestoreResultOutput struct{ *pulumi.OutputState }

func LookupFeaturestoreOutput 

func LookupFeaturestoreOutput(ctx *pulumi.Context, args LookupFeaturestoreOutputArgs, opts ...pulumi.InvokeOption) LookupFeaturestoreResultOutput

func (LookupFeaturestoreResultOutput) CreateTime 

func (o LookupFeaturestoreResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this Featurestore was created.

func (LookupFeaturestoreResultOutput) ElementType 

func (LookupFeaturestoreResultOutput) ElementType() reflect.Type

func (LookupFeaturestoreResultOutput) EncryptionSpec 

func (o LookupFeaturestoreResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Optional. Customer-managed encryption key spec for data storage. If set, both of the online and offline data storage will be secured by this key.

func (LookupFeaturestoreResultOutput) Etag 

func (o LookupFeaturestoreResultOutput) Etag() pulumi.StringOutput

Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupFeaturestoreResultOutput) Labels 

func (o LookupFeaturestoreResultOutput) Labels() pulumi.StringMapOutput

Optional. The labels with user-defined metadata to organize your Featurestore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Featurestore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (LookupFeaturestoreResultOutput) Name 

func (o LookupFeaturestoreResultOutput) Name() pulumi.StringOutput

Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}`

func (LookupFeaturestoreResultOutput) OnlineServingConfig 

func (o LookupFeaturestoreResultOutput) OnlineServingConfig() GoogleCloudAiplatformV1FeaturestoreOnlineServingConfigResponseOutput

Optional. Config for online storage resources. The field should not co-exist with the field of `OnlineStoreReplicationConfig`. If both of it and OnlineStoreReplicationConfig are unset, the feature store will not have an online store and cannot be used for online serving.

func (LookupFeaturestoreResultOutput) OnlineStorageTtlDays 

func (o LookupFeaturestoreResultOutput) OnlineStorageTtlDays() pulumi.IntOutput

Optional. TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than `online_storage_ttl_days` since the feature generation time. Note that `online_storage_ttl_days` should be less than or equal to `offline_storage_ttl_days` for each EntityType under a featurestore. If not set, default to 4000 days

func (LookupFeaturestoreResultOutput) State 

func (o LookupFeaturestoreResultOutput) State() pulumi.StringOutput

State of the featurestore.

func (LookupFeaturestoreResultOutput) ToLookupFeaturestoreResultOutput 

func (o LookupFeaturestoreResultOutput) ToLookupFeaturestoreResultOutput() LookupFeaturestoreResultOutput

func (LookupFeaturestoreResultOutput) ToLookupFeaturestoreResultOutputWithContext 

func (o LookupFeaturestoreResultOutput) ToLookupFeaturestoreResultOutputWithContext(ctx context.Context) LookupFeaturestoreResultOutput

func (LookupFeaturestoreResultOutput) UpdateTime 

func (o LookupFeaturestoreResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Featurestore was last updated.

type LookupHyperparameterTuningJobArgs 

type LookupHyperparameterTuningJobArgs struct {
	HyperparameterTuningJobId string  `pulumi:"hyperparameterTuningJobId"`
	Location                  string  `pulumi:"location"`
	Project                   *string `pulumi:"project"`
}

type LookupHyperparameterTuningJobOutputArgs 

type LookupHyperparameterTuningJobOutputArgs struct {
	HyperparameterTuningJobId pulumi.StringInput    `pulumi:"hyperparameterTuningJobId"`
	Location                  pulumi.StringInput    `pulumi:"location"`
	Project                   pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupHyperparameterTuningJobOutputArgs) ElementType 

func (LookupHyperparameterTuningJobOutputArgs) ElementType() reflect.Type

type LookupHyperparameterTuningJobResult 

type LookupHyperparameterTuningJobResult struct {
	// Time when the HyperparameterTuningJob was created.
	CreateTime string `pulumi:"createTime"`
	// The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Time when the HyperparameterTuningJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
	EndTime string `pulumi:"endTime"`
	// Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
	Error GoogleRpcStatusResponse `pulumi:"error"`
	// The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels map[string]string `pulumi:"labels"`
	// The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.
	MaxFailedTrialCount int `pulumi:"maxFailedTrialCount"`
	// The desired total number of Trials.
	MaxTrialCount int `pulumi:"maxTrialCount"`
	// Resource name of the HyperparameterTuningJob.
	Name string `pulumi:"name"`
	// The desired number of Trials to run in parallel.
	ParallelTrialCount int `pulumi:"parallelTrialCount"`
	// Time when the HyperparameterTuningJob for the first time entered the `JOB_STATE_RUNNING` state.
	StartTime string `pulumi:"startTime"`
	// The detailed state of the job.
	State string `pulumi:"state"`
	// Study configuration of the HyperparameterTuningJob.
	StudySpec GoogleCloudAiplatformV1StudySpecResponse `pulumi:"studySpec"`
	// The spec of a trial job. The same spec applies to the CustomJobs created in all the trials.
	TrialJobSpec GoogleCloudAiplatformV1CustomJobSpecResponse `pulumi:"trialJobSpec"`
	// Trials of the HyperparameterTuningJob.
	Trials []GoogleCloudAiplatformV1TrialResponse `pulumi:"trials"`
	// Time when the HyperparameterTuningJob was most recently updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupHyperparameterTuningJob 

func LookupHyperparameterTuningJob(ctx *pulumi.Context, args *LookupHyperparameterTuningJobArgs, opts ...pulumi.InvokeOption) (*LookupHyperparameterTuningJobResult, error)

Gets a HyperparameterTuningJob

type LookupHyperparameterTuningJobResultOutput 

type LookupHyperparameterTuningJobResultOutput struct{ *pulumi.OutputState }

func LookupHyperparameterTuningJobOutput 

func LookupHyperparameterTuningJobOutput(ctx *pulumi.Context, args LookupHyperparameterTuningJobOutputArgs, opts ...pulumi.InvokeOption) LookupHyperparameterTuningJobResultOutput

func (LookupHyperparameterTuningJobResultOutput) CreateTime 

func (o LookupHyperparameterTuningJobResultOutput) CreateTime() pulumi.StringOutput

Time when the HyperparameterTuningJob was created.

func (LookupHyperparameterTuningJobResultOutput) DisplayName 

func (o LookupHyperparameterTuningJobResultOutput) DisplayName() pulumi.StringOutput

The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (LookupHyperparameterTuningJobResultOutput) ElementType 

func (LookupHyperparameterTuningJobResultOutput) ElementType() reflect.Type

func (LookupHyperparameterTuningJobResultOutput) EncryptionSpec 

func (o LookupHyperparameterTuningJobResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key.

func (LookupHyperparameterTuningJobResultOutput) EndTime 

func (o LookupHyperparameterTuningJobResultOutput) EndTime() pulumi.StringOutput

Time when the HyperparameterTuningJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.

func (LookupHyperparameterTuningJobResultOutput) Error 

func (o LookupHyperparameterTuningJobResultOutput) Error() GoogleRpcStatusResponseOutput

Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

func (LookupHyperparameterTuningJobResultOutput) Labels 

func (o LookupHyperparameterTuningJobResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (LookupHyperparameterTuningJobResultOutput) MaxFailedTrialCount 

func (o LookupHyperparameterTuningJobResultOutput) MaxFailedTrialCount() pulumi.IntOutput

The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.

func (LookupHyperparameterTuningJobResultOutput) MaxTrialCount 

func (o LookupHyperparameterTuningJobResultOutput) MaxTrialCount() pulumi.IntOutput

The desired total number of Trials.

func (LookupHyperparameterTuningJobResultOutput) Name 

func (o LookupHyperparameterTuningJobResultOutput) Name() pulumi.StringOutput

Resource name of the HyperparameterTuningJob.

func (LookupHyperparameterTuningJobResultOutput) ParallelTrialCount 

func (o LookupHyperparameterTuningJobResultOutput) ParallelTrialCount() pulumi.IntOutput

The desired number of Trials to run in parallel.

func (LookupHyperparameterTuningJobResultOutput) StartTime 

func (o LookupHyperparameterTuningJobResultOutput) StartTime() pulumi.StringOutput

Time when the HyperparameterTuningJob for the first time entered the `JOB_STATE_RUNNING` state.

func (LookupHyperparameterTuningJobResultOutput) State 

func (o LookupHyperparameterTuningJobResultOutput) State() pulumi.StringOutput

The detailed state of the job.

func (LookupHyperparameterTuningJobResultOutput) StudySpec 

func (o LookupHyperparameterTuningJobResultOutput) StudySpec() GoogleCloudAiplatformV1StudySpecResponseOutput

Study configuration of the HyperparameterTuningJob.

func (LookupHyperparameterTuningJobResultOutput) ToLookupHyperparameterTuningJobResultOutput 

func (o LookupHyperparameterTuningJobResultOutput) ToLookupHyperparameterTuningJobResultOutput() LookupHyperparameterTuningJobResultOutput

func (LookupHyperparameterTuningJobResultOutput) ToLookupHyperparameterTuningJobResultOutputWithContext 

func (o LookupHyperparameterTuningJobResultOutput) ToLookupHyperparameterTuningJobResultOutputWithContext(ctx context.Context) LookupHyperparameterTuningJobResultOutput

func (LookupHyperparameterTuningJobResultOutput) TrialJobSpec 

func (o LookupHyperparameterTuningJobResultOutput) TrialJobSpec() GoogleCloudAiplatformV1CustomJobSpecResponseOutput

The spec of a trial job. The same spec applies to the CustomJobs created in all the trials.

func (LookupHyperparameterTuningJobResultOutput) Trials 

func (o LookupHyperparameterTuningJobResultOutput) Trials() GoogleCloudAiplatformV1TrialResponseArrayOutput

Trials of the HyperparameterTuningJob.

func (LookupHyperparameterTuningJobResultOutput) UpdateTime 

func (o LookupHyperparameterTuningJobResultOutput) UpdateTime() pulumi.StringOutput

Time when the HyperparameterTuningJob was most recently updated.

type LookupIndexArgs 

type LookupIndexArgs struct {
	IndexId  string  `pulumi:"indexId"`
	Location string  `pulumi:"location"`
	Project  *string `pulumi:"project"`
}

type LookupIndexEndpointArgs 

type LookupIndexEndpointArgs struct {
	IndexEndpointId string  `pulumi:"indexEndpointId"`
	Location        string  `pulumi:"location"`
	Project         *string `pulumi:"project"`
}

type LookupIndexEndpointOutputArgs 

type LookupIndexEndpointOutputArgs struct {
	IndexEndpointId pulumi.StringInput    `pulumi:"indexEndpointId"`
	Location        pulumi.StringInput    `pulumi:"location"`
	Project         pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupIndexEndpointOutputArgs) ElementType 

func (LookupIndexEndpointOutputArgs) ElementType() reflect.Type

type LookupIndexEndpointResult 

type LookupIndexEndpointResult struct {
	// Timestamp when this IndexEndpoint was created.
	CreateTime string `pulumi:"createTime"`
	// The indexes deployed in this endpoint.
	DeployedIndexes []GoogleCloudAiplatformV1DeployedIndexResponse `pulumi:"deployedIndexes"`
	// The description of the IndexEndpoint.
	Description string `pulumi:"description"`
	// The display name of the IndexEndpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.
	//
	// Deprecated: Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.
	EnablePrivateServiceConnect bool `pulumi:"enablePrivateServiceConnect"`
	// Immutable. Customer-managed encryption key spec for an IndexEndpoint. If set, this IndexEndpoint and all sub-resources of this IndexEndpoint will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// The labels with user-defined metadata to organize your IndexEndpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels map[string]string `pulumi:"labels"`
	// The resource name of the IndexEndpoint.
	Name string `pulumi:"name"`
	// Optional. The full name of the Google Compute Engine [network](https://cloud.google.com/compute/docs/networks-and-firewalls#networks) to which the IndexEndpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. network and private_service_connect_config are mutually exclusive. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in '12345', and {network} is network name.
	Network string `pulumi:"network"`
	// Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive.
	PrivateServiceConnectConfig GoogleCloudAiplatformV1PrivateServiceConnectConfigResponse `pulumi:"privateServiceConnectConfig"`
	// If public_endpoint_enabled is true, this field will be populated with the domain name to use for this index endpoint.
	PublicEndpointDomainName string `pulumi:"publicEndpointDomainName"`
	// Optional. If true, the deployed index will be accessible through public endpoint.
	PublicEndpointEnabled bool `pulumi:"publicEndpointEnabled"`
	// Timestamp when this IndexEndpoint was last updated. This timestamp is not updated when the endpoint's DeployedIndexes are updated, e.g. due to updates of the original Indexes they are the deployments of.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupIndexEndpoint 

func LookupIndexEndpoint(ctx *pulumi.Context, args *LookupIndexEndpointArgs, opts ...pulumi.InvokeOption) (*LookupIndexEndpointResult, error)

Gets an IndexEndpoint.

type LookupIndexEndpointResultOutput 

type LookupIndexEndpointResultOutput struct{ *pulumi.OutputState }

func LookupIndexEndpointOutput 

func LookupIndexEndpointOutput(ctx *pulumi.Context, args LookupIndexEndpointOutputArgs, opts ...pulumi.InvokeOption) LookupIndexEndpointResultOutput

func (LookupIndexEndpointResultOutput) CreateTime 

func (o LookupIndexEndpointResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this IndexEndpoint was created.

func (LookupIndexEndpointResultOutput) DeployedIndexes 

func (o LookupIndexEndpointResultOutput) DeployedIndexes() GoogleCloudAiplatformV1DeployedIndexResponseArrayOutput

The indexes deployed in this endpoint.

func (LookupIndexEndpointResultOutput) Description 

func (o LookupIndexEndpointResultOutput) Description() pulumi.StringOutput

The description of the IndexEndpoint.

func (LookupIndexEndpointResultOutput) DisplayName 

func (o LookupIndexEndpointResultOutput) DisplayName() pulumi.StringOutput

The display name of the IndexEndpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (LookupIndexEndpointResultOutput) ElementType 

func (LookupIndexEndpointResultOutput) ElementType() reflect.Type

func (LookupIndexEndpointResultOutput) EnablePrivateServiceConnect deprecated 

func (o LookupIndexEndpointResultOutput) EnablePrivateServiceConnect() pulumi.BoolOutput

Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.

Deprecated: Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.

func (LookupIndexEndpointResultOutput) EncryptionSpec 

func (o LookupIndexEndpointResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Immutable. Customer-managed encryption key spec for an IndexEndpoint. If set, this IndexEndpoint and all sub-resources of this IndexEndpoint will be secured by this key.

func (LookupIndexEndpointResultOutput) Etag 

func (o LookupIndexEndpointResultOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupIndexEndpointResultOutput) Labels 

func (o LookupIndexEndpointResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your IndexEndpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (LookupIndexEndpointResultOutput) Name 

func (o LookupIndexEndpointResultOutput) Name() pulumi.StringOutput

The resource name of the IndexEndpoint.

func (LookupIndexEndpointResultOutput) Network 

func (o LookupIndexEndpointResultOutput) Network() pulumi.StringOutput

Optional. The full name of the Google Compute Engine [network](https://cloud.google.com/compute/docs/networks-and-firewalls#networks) to which the IndexEndpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. network and private_service_connect_config are mutually exclusive. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in '12345', and {network} is network name.

func (LookupIndexEndpointResultOutput) PrivateServiceConnectConfig 

func (o LookupIndexEndpointResultOutput) PrivateServiceConnectConfig() GoogleCloudAiplatformV1PrivateServiceConnectConfigResponseOutput

Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive.

func (LookupIndexEndpointResultOutput) PublicEndpointDomainName 

func (o LookupIndexEndpointResultOutput) PublicEndpointDomainName() pulumi.StringOutput

If public_endpoint_enabled is true, this field will be populated with the domain name to use for this index endpoint.

func (LookupIndexEndpointResultOutput) PublicEndpointEnabled 

func (o LookupIndexEndpointResultOutput) PublicEndpointEnabled() pulumi.BoolOutput

Optional. If true, the deployed index will be accessible through public endpoint.

func (LookupIndexEndpointResultOutput) ToLookupIndexEndpointResultOutput 

func (o LookupIndexEndpointResultOutput) ToLookupIndexEndpointResultOutput() LookupIndexEndpointResultOutput

func (LookupIndexEndpointResultOutput) ToLookupIndexEndpointResultOutputWithContext 

func (o LookupIndexEndpointResultOutput) ToLookupIndexEndpointResultOutputWithContext(ctx context.Context) LookupIndexEndpointResultOutput

func (LookupIndexEndpointResultOutput) UpdateTime 

func (o LookupIndexEndpointResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this IndexEndpoint was last updated. This timestamp is not updated when the endpoint's DeployedIndexes are updated, e.g. due to updates of the original Indexes they are the deployments of.

type LookupIndexOutputArgs 

type LookupIndexOutputArgs struct {
	IndexId  pulumi.StringInput    `pulumi:"indexId"`
	Location pulumi.StringInput    `pulumi:"location"`
	Project  pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupIndexOutputArgs) ElementType 

func (LookupIndexOutputArgs) ElementType() reflect.Type

type LookupIndexResult 

type LookupIndexResult struct {
	// Timestamp when this Index was created.
	CreateTime string `pulumi:"createTime"`
	// The pointers to DeployedIndexes created from this Index. An Index can be only deleted if all its DeployedIndexes had been undeployed first.
	DeployedIndexes []GoogleCloudAiplatformV1DeployedIndexRefResponse `pulumi:"deployedIndexes"`
	// The description of the Index.
	Description string `pulumi:"description"`
	// The display name of the Index. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Immutable. Customer-managed encryption key spec for an Index. If set, this Index and all sub-resources of this Index will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// Stats of the index resource.
	IndexStats GoogleCloudAiplatformV1IndexStatsResponse `pulumi:"indexStats"`
	// Immutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default.
	IndexUpdateMethod string `pulumi:"indexUpdateMethod"`
	// The labels with user-defined metadata to organize your Indexes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels map[string]string `pulumi:"labels"`
	// An additional information about the Index; the schema of the metadata can be found in metadata_schema.
	Metadata interface{} `pulumi:"metadata"`
	// Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Index, that is specific to it. Unset if the Index does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	MetadataSchemaUri string `pulumi:"metadataSchemaUri"`
	// The resource name of the Index.
	Name string `pulumi:"name"`
	// Timestamp when this Index was most recently updated. This also includes any update to the contents of the Index. Note that Operations working on this Index may have their Operations.metadata.generic_metadata.update_time a little after the value of this timestamp, yet that does not mean their results are not already reflected in the Index. Result of any successfully completed Operation on the Index is reflected in it.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupIndex 

func LookupIndex(ctx *pulumi.Context, args *LookupIndexArgs, opts ...pulumi.InvokeOption) (*LookupIndexResult, error)

Gets an Index.

type LookupIndexResultOutput 

type LookupIndexResultOutput struct{ *pulumi.OutputState }

func LookupIndexOutput 

func LookupIndexOutput(ctx *pulumi.Context, args LookupIndexOutputArgs, opts ...pulumi.InvokeOption) LookupIndexResultOutput

func (LookupIndexResultOutput) CreateTime 

func (o LookupIndexResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this Index was created.

func (LookupIndexResultOutput) DeployedIndexes 

func (o LookupIndexResultOutput) DeployedIndexes() GoogleCloudAiplatformV1DeployedIndexRefResponseArrayOutput

The pointers to DeployedIndexes created from this Index. An Index can be only deleted if all its DeployedIndexes had been undeployed first.

func (LookupIndexResultOutput) Description 

func (o LookupIndexResultOutput) Description() pulumi.StringOutput

The description of the Index.

func (LookupIndexResultOutput) DisplayName 

func (o LookupIndexResultOutput) DisplayName() pulumi.StringOutput

The display name of the Index. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (LookupIndexResultOutput) ElementType 

func (LookupIndexResultOutput) ElementType() reflect.Type

func (LookupIndexResultOutput) EncryptionSpec 

func (o LookupIndexResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Immutable. Customer-managed encryption key spec for an Index. If set, this Index and all sub-resources of this Index will be secured by this key.

func (LookupIndexResultOutput) Etag 

func (o LookupIndexResultOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupIndexResultOutput) IndexStats 

func (o LookupIndexResultOutput) IndexStats() GoogleCloudAiplatformV1IndexStatsResponseOutput

Stats of the index resource.

func (LookupIndexResultOutput) IndexUpdateMethod 

func (o LookupIndexResultOutput) IndexUpdateMethod() pulumi.StringOutput

Immutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default.

func (LookupIndexResultOutput) Labels 

func (o LookupIndexResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Indexes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (LookupIndexResultOutput) Metadata 

func (o LookupIndexResultOutput) Metadata() pulumi.AnyOutput

An additional information about the Index; the schema of the metadata can be found in metadata_schema.

func (LookupIndexResultOutput) MetadataSchemaUri 

func (o LookupIndexResultOutput) MetadataSchemaUri() pulumi.StringOutput

Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Index, that is specific to it. Unset if the Index does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (LookupIndexResultOutput) Name 

func (o LookupIndexResultOutput) Name() pulumi.StringOutput

The resource name of the Index.

func (LookupIndexResultOutput) ToLookupIndexResultOutput 

func (o LookupIndexResultOutput) ToLookupIndexResultOutput() LookupIndexResultOutput

func (LookupIndexResultOutput) ToLookupIndexResultOutputWithContext 

func (o LookupIndexResultOutput) ToLookupIndexResultOutputWithContext(ctx context.Context) LookupIndexResultOutput

func (LookupIndexResultOutput) UpdateTime 

func (o LookupIndexResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Index was most recently updated. This also includes any update to the contents of the Index. Note that Operations working on this Index may have their Operations.metadata.generic_metadata.update_time a little after the value of this timestamp, yet that does not mean their results are not already reflected in the Index. Result of any successfully completed Operation on the Index is reflected in it.

type LookupMetadataSchemaArgs 

type LookupMetadataSchemaArgs struct {
	Location         string  `pulumi:"location"`
	MetadataSchemaId string  `pulumi:"metadataSchemaId"`
	MetadataStoreId  string  `pulumi:"metadataStoreId"`
	Project          *string `pulumi:"project"`
}

type LookupMetadataSchemaOutputArgs 

type LookupMetadataSchemaOutputArgs struct {
	Location         pulumi.StringInput    `pulumi:"location"`
	MetadataSchemaId pulumi.StringInput    `pulumi:"metadataSchemaId"`
	MetadataStoreId  pulumi.StringInput    `pulumi:"metadataStoreId"`
	Project          pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupMetadataSchemaOutputArgs) ElementType 

func (LookupMetadataSchemaOutputArgs) ElementType() reflect.Type

type LookupMetadataSchemaResult 

type LookupMetadataSchemaResult struct {
	// Timestamp when this MetadataSchema was created.
	CreateTime string `pulumi:"createTime"`
	// Description of the Metadata Schema
	Description string `pulumi:"description"`
	// The resource name of the MetadataSchema.
	Name string `pulumi:"name"`
	// The raw YAML string representation of the MetadataSchema. The combination of [MetadataSchema.version] and the schema name given by `title` in [MetadataSchema.schema] must be unique within a MetadataStore. The schema is defined as an OpenAPI 3.0.2 [MetadataSchema Object](https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.0.2.md#schemaObject)
	Schema string `pulumi:"schema"`
	// The type of the MetadataSchema. This is a property that identifies which metadata types will use the MetadataSchema.
	SchemaType string `pulumi:"schemaType"`
	// The version of the MetadataSchema. The version's format must match the following regular expression: `^[0-9]+.+.+$`, which would allow to order/compare different versions. Example: 1.0.0, 1.0.1, etc.
	SchemaVersion string `pulumi:"schemaVersion"`
}

func LookupMetadataSchema 

func LookupMetadataSchema(ctx *pulumi.Context, args *LookupMetadataSchemaArgs, opts ...pulumi.InvokeOption) (*LookupMetadataSchemaResult, error)

Retrieves a specific MetadataSchema.

type LookupMetadataSchemaResultOutput 

type LookupMetadataSchemaResultOutput struct{ *pulumi.OutputState }

func LookupMetadataSchemaOutput 

func LookupMetadataSchemaOutput(ctx *pulumi.Context, args LookupMetadataSchemaOutputArgs, opts ...pulumi.InvokeOption) LookupMetadataSchemaResultOutput

func (LookupMetadataSchemaResultOutput) CreateTime 

func (o LookupMetadataSchemaResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this MetadataSchema was created.

func (LookupMetadataSchemaResultOutput) Description 

func (o LookupMetadataSchemaResultOutput) Description() pulumi.StringOutput

Description of the Metadata Schema

func (LookupMetadataSchemaResultOutput) ElementType 

func (LookupMetadataSchemaResultOutput) ElementType() reflect.Type

func (LookupMetadataSchemaResultOutput) Name 

func (o LookupMetadataSchemaResultOutput) Name() pulumi.StringOutput

The resource name of the MetadataSchema.

func (LookupMetadataSchemaResultOutput) Schema 

func (o LookupMetadataSchemaResultOutput) Schema() pulumi.StringOutput

The raw YAML string representation of the MetadataSchema. The combination of [MetadataSchema.version] and the schema name given by `title` in [MetadataSchema.schema] must be unique within a MetadataStore. The schema is defined as an OpenAPI 3.0.2 [MetadataSchema Object](https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.0.2.md#schemaObject)

func (LookupMetadataSchemaResultOutput) SchemaType 

func (o LookupMetadataSchemaResultOutput) SchemaType() pulumi.StringOutput

The type of the MetadataSchema. This is a property that identifies which metadata types will use the MetadataSchema.

func (LookupMetadataSchemaResultOutput) SchemaVersion 

func (o LookupMetadataSchemaResultOutput) SchemaVersion() pulumi.StringOutput

The version of the MetadataSchema. The version's format must match the following regular expression: `^[0-9]+.+.+$`, which would allow to order/compare different versions. Example: 1.0.0, 1.0.1, etc.

func (LookupMetadataSchemaResultOutput) ToLookupMetadataSchemaResultOutput 

func (o LookupMetadataSchemaResultOutput) ToLookupMetadataSchemaResultOutput() LookupMetadataSchemaResultOutput

func (LookupMetadataSchemaResultOutput) ToLookupMetadataSchemaResultOutputWithContext 

func (o LookupMetadataSchemaResultOutput) ToLookupMetadataSchemaResultOutputWithContext(ctx context.Context) LookupMetadataSchemaResultOutput

type LookupMetadataStoreArgs 

type LookupMetadataStoreArgs struct {
	Location        string  `pulumi:"location"`
	MetadataStoreId string  `pulumi:"metadataStoreId"`
	Project         *string `pulumi:"project"`
}

type LookupMetadataStoreOutputArgs 

type LookupMetadataStoreOutputArgs struct {
	Location        pulumi.StringInput    `pulumi:"location"`
	MetadataStoreId pulumi.StringInput    `pulumi:"metadataStoreId"`
	Project         pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupMetadataStoreOutputArgs) ElementType 

func (LookupMetadataStoreOutputArgs) ElementType() reflect.Type

type LookupMetadataStoreResult 

type LookupMetadataStoreResult struct {
	// Timestamp when this MetadataStore was created.
	CreateTime string `pulumi:"createTime"`
	// Description of the MetadataStore.
	Description string `pulumi:"description"`
	// Customer-managed encryption key spec for a Metadata Store. If set, this Metadata Store and all sub-resources of this Metadata Store are secured using this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// The resource name of the MetadataStore instance.
	Name string `pulumi:"name"`
	// State information of the MetadataStore.
	State GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponse `pulumi:"state"`
	// Timestamp when this MetadataStore was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupMetadataStore 

func LookupMetadataStore(ctx *pulumi.Context, args *LookupMetadataStoreArgs, opts ...pulumi.InvokeOption) (*LookupMetadataStoreResult, error)

Retrieves a specific MetadataStore.

type LookupMetadataStoreResultOutput 

type LookupMetadataStoreResultOutput struct{ *pulumi.OutputState }

func LookupMetadataStoreOutput 

func LookupMetadataStoreOutput(ctx *pulumi.Context, args LookupMetadataStoreOutputArgs, opts ...pulumi.InvokeOption) LookupMetadataStoreResultOutput

func (LookupMetadataStoreResultOutput) CreateTime 

func (o LookupMetadataStoreResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this MetadataStore was created.

func (LookupMetadataStoreResultOutput) Description 

func (o LookupMetadataStoreResultOutput) Description() pulumi.StringOutput

Description of the MetadataStore.

func (LookupMetadataStoreResultOutput) ElementType 

func (LookupMetadataStoreResultOutput) ElementType() reflect.Type

func (LookupMetadataStoreResultOutput) EncryptionSpec 

func (o LookupMetadataStoreResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a Metadata Store. If set, this Metadata Store and all sub-resources of this Metadata Store are secured using this key.

func (LookupMetadataStoreResultOutput) Name 

func (o LookupMetadataStoreResultOutput) Name() pulumi.StringOutput

The resource name of the MetadataStore instance.

func (LookupMetadataStoreResultOutput) State 

func (o LookupMetadataStoreResultOutput) State() GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput

State information of the MetadataStore.

func (LookupMetadataStoreResultOutput) ToLookupMetadataStoreResultOutput 

func (o LookupMetadataStoreResultOutput) ToLookupMetadataStoreResultOutput() LookupMetadataStoreResultOutput

func (LookupMetadataStoreResultOutput) ToLookupMetadataStoreResultOutputWithContext 

func (o LookupMetadataStoreResultOutput) ToLookupMetadataStoreResultOutputWithContext(ctx context.Context) LookupMetadataStoreResultOutput

func (LookupMetadataStoreResultOutput) UpdateTime 

func (o LookupMetadataStoreResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this MetadataStore was last updated.

type LookupModelDeploymentMonitoringJobArgs 

type LookupModelDeploymentMonitoringJobArgs struct {
	Location                       string  `pulumi:"location"`
	ModelDeploymentMonitoringJobId string  `pulumi:"modelDeploymentMonitoringJobId"`
	Project                        *string `pulumi:"project"`
}

type LookupModelDeploymentMonitoringJobOutputArgs 

type LookupModelDeploymentMonitoringJobOutputArgs struct {
	Location                       pulumi.StringInput    `pulumi:"location"`
	ModelDeploymentMonitoringJobId pulumi.StringInput    `pulumi:"modelDeploymentMonitoringJobId"`
	Project                        pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupModelDeploymentMonitoringJobOutputArgs) ElementType 

func (LookupModelDeploymentMonitoringJobOutputArgs) ElementType() reflect.Type

type LookupModelDeploymentMonitoringJobResult 

type LookupModelDeploymentMonitoringJobResult struct {
	// YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.
	AnalysisInstanceSchemaUri string `pulumi:"analysisInstanceSchemaUri"`
	// The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum: 1. Training data logging predict request/response 2. Serving data logging predict request/response
	BigqueryTables []GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponse `pulumi:"bigqueryTables"`
	// Timestamp when this ModelDeploymentMonitoringJob was created.
	CreateTime string `pulumi:"createTime"`
	// The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.
	DisplayName string `pulumi:"displayName"`
	// If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging#pricing).
	EnableMonitoringPipelineLogs bool `pulumi:"enableMonitoringPipelineLogs"`
	// Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Endpoint resource name. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
	Endpoint string `pulumi:"endpoint"`
	// Only populated when the job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.
	Error GoogleRpcStatusResponse `pulumi:"error"`
	// The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels map[string]string `pulumi:"labels"`
	// Latest triggered monitoring pipeline metadata.
	LatestMonitoringPipelineMetadata GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponse `pulumi:"latestMonitoringPipelineMetadata"`
	// The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.
	LogTtl string `pulumi:"logTtl"`
	// Sample Strategy for logging.
	LoggingSamplingStrategy GoogleCloudAiplatformV1SamplingStrategyResponse `pulumi:"loggingSamplingStrategy"`
	// The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.
	ModelDeploymentMonitoringObjectiveConfigs []GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponse `pulumi:"modelDeploymentMonitoringObjectiveConfigs"`
	// Schedule config for running the monitoring job.
	ModelDeploymentMonitoringScheduleConfig GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponse `pulumi:"modelDeploymentMonitoringScheduleConfig"`
	// Alert config for model monitoring.
	ModelMonitoringAlertConfig GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponse `pulumi:"modelMonitoringAlertConfig"`
	// Resource name of a ModelDeploymentMonitoringJob.
	Name string `pulumi:"name"`
	// Timestamp when this monitoring pipeline will be scheduled to run for the next round.
	NextScheduleTime string `pulumi:"nextScheduleTime"`
	// YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.
	PredictInstanceSchemaUri string `pulumi:"predictInstanceSchemaUri"`
	// Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.
	SamplePredictInstance interface{} `pulumi:"samplePredictInstance"`
	// Schedule state when the monitoring job is in Running state.
	ScheduleState string `pulumi:"scheduleState"`
	// The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.
	State string `pulumi:"state"`
	// Stats anomalies base folder path.
	StatsAnomaliesBaseDirectory GoogleCloudAiplatformV1GcsDestinationResponse `pulumi:"statsAnomaliesBaseDirectory"`
	// Timestamp when this ModelDeploymentMonitoringJob was updated most recently.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupModelDeploymentMonitoringJob 

func LookupModelDeploymentMonitoringJob(ctx *pulumi.Context, args *LookupModelDeploymentMonitoringJobArgs, opts ...pulumi.InvokeOption) (*LookupModelDeploymentMonitoringJobResult, error)

Gets a ModelDeploymentMonitoringJob.

type LookupModelDeploymentMonitoringJobResultOutput 

type LookupModelDeploymentMonitoringJobResultOutput struct{ *pulumi.OutputState }

func LookupModelDeploymentMonitoringJobOutput 

func LookupModelDeploymentMonitoringJobOutput(ctx *pulumi.Context, args LookupModelDeploymentMonitoringJobOutputArgs, opts ...pulumi.InvokeOption) LookupModelDeploymentMonitoringJobResultOutput

func (LookupModelDeploymentMonitoringJobResultOutput) AnalysisInstanceSchemaUri 

func (o LookupModelDeploymentMonitoringJobResultOutput) AnalysisInstanceSchemaUri() pulumi.StringOutput

YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.

func (LookupModelDeploymentMonitoringJobResultOutput) BigqueryTables 

func (o LookupModelDeploymentMonitoringJobResultOutput) BigqueryTables() GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput

The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum: 1. Training data logging predict request/response 2. Serving data logging predict request/response

func (LookupModelDeploymentMonitoringJobResultOutput) CreateTime 

func (o LookupModelDeploymentMonitoringJobResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this ModelDeploymentMonitoringJob was created.

func (LookupModelDeploymentMonitoringJobResultOutput) DisplayName 

func (o LookupModelDeploymentMonitoringJobResultOutput) DisplayName() pulumi.StringOutput

The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.

func (LookupModelDeploymentMonitoringJobResultOutput) ElementType 

func (LookupModelDeploymentMonitoringJobResultOutput) ElementType() reflect.Type

func (LookupModelDeploymentMonitoringJobResultOutput) EnableMonitoringPipelineLogs 

func (o LookupModelDeploymentMonitoringJobResultOutput) EnableMonitoringPipelineLogs() pulumi.BoolOutput

If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging#pricing).

func (LookupModelDeploymentMonitoringJobResultOutput) EncryptionSpec 

func (o LookupModelDeploymentMonitoringJobResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.

func (LookupModelDeploymentMonitoringJobResultOutput) Endpoint 

func (o LookupModelDeploymentMonitoringJobResultOutput) Endpoint() pulumi.StringOutput

Endpoint resource name. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`

func (LookupModelDeploymentMonitoringJobResultOutput) Error 

func (o LookupModelDeploymentMonitoringJobResultOutput) Error() GoogleRpcStatusResponseOutput

Only populated when the job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.

func (LookupModelDeploymentMonitoringJobResultOutput) Labels 

func (o LookupModelDeploymentMonitoringJobResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (LookupModelDeploymentMonitoringJobResultOutput) LatestMonitoringPipelineMetadata 

func (o LookupModelDeploymentMonitoringJobResultOutput) LatestMonitoringPipelineMetadata() GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput

Latest triggered monitoring pipeline metadata.

func (LookupModelDeploymentMonitoringJobResultOutput) LogTtl 

func (o LookupModelDeploymentMonitoringJobResultOutput) LogTtl() pulumi.StringOutput

The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.

func (LookupModelDeploymentMonitoringJobResultOutput) LoggingSamplingStrategy 

func (o LookupModelDeploymentMonitoringJobResultOutput) LoggingSamplingStrategy() GoogleCloudAiplatformV1SamplingStrategyResponseOutput

Sample Strategy for logging.

func (LookupModelDeploymentMonitoringJobResultOutput) ModelDeploymentMonitoringObjectiveConfigs 

func (o LookupModelDeploymentMonitoringJobResultOutput) ModelDeploymentMonitoringObjectiveConfigs() GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput

The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

func (LookupModelDeploymentMonitoringJobResultOutput) ModelDeploymentMonitoringScheduleConfig 

func (o LookupModelDeploymentMonitoringJobResultOutput) ModelDeploymentMonitoringScheduleConfig() GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput

Schedule config for running the monitoring job.

func (LookupModelDeploymentMonitoringJobResultOutput) ModelMonitoringAlertConfig 

func (o LookupModelDeploymentMonitoringJobResultOutput) ModelMonitoringAlertConfig() GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput

Alert config for model monitoring.

func (LookupModelDeploymentMonitoringJobResultOutput) Name 

func (o LookupModelDeploymentMonitoringJobResultOutput) Name() pulumi.StringOutput

Resource name of a ModelDeploymentMonitoringJob.

func (LookupModelDeploymentMonitoringJobResultOutput) NextScheduleTime 

func (o LookupModelDeploymentMonitoringJobResultOutput) NextScheduleTime() pulumi.StringOutput

Timestamp when this monitoring pipeline will be scheduled to run for the next round.

func (LookupModelDeploymentMonitoringJobResultOutput) PredictInstanceSchemaUri 

func (o LookupModelDeploymentMonitoringJobResultOutput) PredictInstanceSchemaUri() pulumi.StringOutput

YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.

func (LookupModelDeploymentMonitoringJobResultOutput) SamplePredictInstance 

func (o LookupModelDeploymentMonitoringJobResultOutput) SamplePredictInstance() pulumi.AnyOutput

Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.

func (LookupModelDeploymentMonitoringJobResultOutput) ScheduleState 

func (o LookupModelDeploymentMonitoringJobResultOutput) ScheduleState() pulumi.StringOutput

Schedule state when the monitoring job is in Running state.

func (LookupModelDeploymentMonitoringJobResultOutput) State 

func (o LookupModelDeploymentMonitoringJobResultOutput) State() pulumi.StringOutput

The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.

func (LookupModelDeploymentMonitoringJobResultOutput) StatsAnomaliesBaseDirectory 

func (o LookupModelDeploymentMonitoringJobResultOutput) StatsAnomaliesBaseDirectory() GoogleCloudAiplatformV1GcsDestinationResponseOutput

Stats anomalies base folder path.

func (LookupModelDeploymentMonitoringJobResultOutput) ToLookupModelDeploymentMonitoringJobResultOutput 

func (o LookupModelDeploymentMonitoringJobResultOutput) ToLookupModelDeploymentMonitoringJobResultOutput() LookupModelDeploymentMonitoringJobResultOutput

func (LookupModelDeploymentMonitoringJobResultOutput) ToLookupModelDeploymentMonitoringJobResultOutputWithContext 

func (o LookupModelDeploymentMonitoringJobResultOutput) ToLookupModelDeploymentMonitoringJobResultOutputWithContext(ctx context.Context) LookupModelDeploymentMonitoringJobResultOutput

func (LookupModelDeploymentMonitoringJobResultOutput) UpdateTime 

func (o LookupModelDeploymentMonitoringJobResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this ModelDeploymentMonitoringJob was updated most recently.

type LookupNasJobArgs 

type LookupNasJobArgs struct {
	Location string  `pulumi:"location"`
	NasJobId string  `pulumi:"nasJobId"`
	Project  *string `pulumi:"project"`
}

type LookupNasJobOutputArgs 

type LookupNasJobOutputArgs struct {
	Location pulumi.StringInput    `pulumi:"location"`
	NasJobId pulumi.StringInput    `pulumi:"nasJobId"`
	Project  pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupNasJobOutputArgs) ElementType 

func (LookupNasJobOutputArgs) ElementType() reflect.Type

type LookupNasJobResult 

type LookupNasJobResult struct {
	// Time when the NasJob was created.
	CreateTime string `pulumi:"createTime"`
	// The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Optional. Enable a separation of Custom model training and restricted image training for tenant project.
	EnableRestrictedImageTraining bool `pulumi:"enableRestrictedImageTraining"`
	// Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Time when the NasJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
	EndTime string `pulumi:"endTime"`
	// Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
	Error GoogleRpcStatusResponse `pulumi:"error"`
	// The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels map[string]string `pulumi:"labels"`
	// Resource name of the NasJob.
	Name string `pulumi:"name"`
	// Output of the NasJob.
	NasJobOutput GoogleCloudAiplatformV1NasJobOutputResponse `pulumi:"nasJobOutput"`
	// The specification of a NasJob.
	NasJobSpec GoogleCloudAiplatformV1NasJobSpecResponse `pulumi:"nasJobSpec"`
	// Time when the NasJob for the first time entered the `JOB_STATE_RUNNING` state.
	StartTime string `pulumi:"startTime"`
	// The detailed state of the job.
	State string `pulumi:"state"`
	// Time when the NasJob was most recently updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupNasJob 

func LookupNasJob(ctx *pulumi.Context, args *LookupNasJobArgs, opts ...pulumi.InvokeOption) (*LookupNasJobResult, error)

Gets a NasJob

type LookupNasJobResultOutput 

type LookupNasJobResultOutput struct{ *pulumi.OutputState }

func LookupNasJobOutput 

func LookupNasJobOutput(ctx *pulumi.Context, args LookupNasJobOutputArgs, opts ...pulumi.InvokeOption) LookupNasJobResultOutput

func (LookupNasJobResultOutput) CreateTime 

func (o LookupNasJobResultOutput) CreateTime() pulumi.StringOutput

Time when the NasJob was created.

func (LookupNasJobResultOutput) DisplayName 

func (o LookupNasJobResultOutput) DisplayName() pulumi.StringOutput

The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (LookupNasJobResultOutput) ElementType 

func (LookupNasJobResultOutput) ElementType() reflect.Type

func (LookupNasJobResultOutput) EnableRestrictedImageTraining 

func (o LookupNasJobResultOutput) EnableRestrictedImageTraining() pulumi.BoolOutput

Optional. Enable a separation of Custom model training and restricted image training for tenant project.

func (LookupNasJobResultOutput) EncryptionSpec 

func (o LookupNasJobResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.

func (LookupNasJobResultOutput) EndTime 

func (o LookupNasJobResultOutput) EndTime() pulumi.StringOutput

Time when the NasJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.

func (LookupNasJobResultOutput) Error 

func (o LookupNasJobResultOutput) Error() GoogleRpcStatusResponseOutput

Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

func (LookupNasJobResultOutput) Labels 

func (o LookupNasJobResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (LookupNasJobResultOutput) Name 

func (o LookupNasJobResultOutput) Name() pulumi.StringOutput

Resource name of the NasJob.

func (LookupNasJobResultOutput) NasJobOutput 

func (o LookupNasJobResultOutput) NasJobOutput() GoogleCloudAiplatformV1NasJobOutputResponseOutput

Output of the NasJob.

func (LookupNasJobResultOutput) NasJobSpec 

func (o LookupNasJobResultOutput) NasJobSpec() GoogleCloudAiplatformV1NasJobSpecResponseOutput

The specification of a NasJob.

func (LookupNasJobResultOutput) StartTime 

func (o LookupNasJobResultOutput) StartTime() pulumi.StringOutput

Time when the NasJob for the first time entered the `JOB_STATE_RUNNING` state.

func (LookupNasJobResultOutput) State 

func (o LookupNasJobResultOutput) State() pulumi.StringOutput

The detailed state of the job.

func (LookupNasJobResultOutput) ToLookupNasJobResultOutput 

func (o LookupNasJobResultOutput) ToLookupNasJobResultOutput() LookupNasJobResultOutput

func (LookupNasJobResultOutput) ToLookupNasJobResultOutputWithContext 

func (o LookupNasJobResultOutput) ToLookupNasJobResultOutputWithContext(ctx context.Context) LookupNasJobResultOutput

func (LookupNasJobResultOutput) UpdateTime 

func (o LookupNasJobResultOutput) UpdateTime() pulumi.StringOutput

Time when the NasJob was most recently updated.

type LookupNotebookRuntimeTemplateArgs 

type LookupNotebookRuntimeTemplateArgs struct {
	Location                  string  `pulumi:"location"`
	NotebookRuntimeTemplateId string  `pulumi:"notebookRuntimeTemplateId"`
	Project                   *string `pulumi:"project"`
}

type LookupNotebookRuntimeTemplateIamPolicyArgs 

type LookupNotebookRuntimeTemplateIamPolicyArgs struct {
	Location                      string  `pulumi:"location"`
	NotebookRuntimeTemplateId     string  `pulumi:"notebookRuntimeTemplateId"`
	OptionsRequestedPolicyVersion *int    `pulumi:"optionsRequestedPolicyVersion"`
	Project                       *string `pulumi:"project"`
}

type LookupNotebookRuntimeTemplateIamPolicyOutputArgs 

type LookupNotebookRuntimeTemplateIamPolicyOutputArgs struct {
	Location                      pulumi.StringInput    `pulumi:"location"`
	NotebookRuntimeTemplateId     pulumi.StringInput    `pulumi:"notebookRuntimeTemplateId"`
	OptionsRequestedPolicyVersion pulumi.IntPtrInput    `pulumi:"optionsRequestedPolicyVersion"`
	Project                       pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupNotebookRuntimeTemplateIamPolicyOutputArgs) ElementType 

func (LookupNotebookRuntimeTemplateIamPolicyOutputArgs) ElementType() reflect.Type

type LookupNotebookRuntimeTemplateIamPolicyResult 

type LookupNotebookRuntimeTemplateIamPolicyResult struct {
	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings []GoogleIamV1BindingResponse `pulumi:"bindings"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag string `pulumi:"etag"`
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version int `pulumi:"version"`
}

func LookupNotebookRuntimeTemplateIamPolicy 

func LookupNotebookRuntimeTemplateIamPolicy(ctx *pulumi.Context, args *LookupNotebookRuntimeTemplateIamPolicyArgs, opts ...pulumi.InvokeOption) (*LookupNotebookRuntimeTemplateIamPolicyResult, error)

Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.

type LookupNotebookRuntimeTemplateIamPolicyResultOutput 

type LookupNotebookRuntimeTemplateIamPolicyResultOutput struct{ *pulumi.OutputState }

func LookupNotebookRuntimeTemplateIamPolicyOutput 

func LookupNotebookRuntimeTemplateIamPolicyOutput(ctx *pulumi.Context, args LookupNotebookRuntimeTemplateIamPolicyOutputArgs, opts ...pulumi.InvokeOption) LookupNotebookRuntimeTemplateIamPolicyResultOutput

func (LookupNotebookRuntimeTemplateIamPolicyResultOutput) Bindings 

func (o LookupNotebookRuntimeTemplateIamPolicyResultOutput) Bindings() GoogleIamV1BindingResponseArrayOutput

Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.

func (LookupNotebookRuntimeTemplateIamPolicyResultOutput) ElementType 

func (LookupNotebookRuntimeTemplateIamPolicyResultOutput) ElementType() reflect.Type

func (LookupNotebookRuntimeTemplateIamPolicyResultOutput) Etag 

func (o LookupNotebookRuntimeTemplateIamPolicyResultOutput) Etag() pulumi.StringOutput

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.

func (LookupNotebookRuntimeTemplateIamPolicyResultOutput) ToLookupNotebookRuntimeTemplateIamPolicyResultOutput 

func (o LookupNotebookRuntimeTemplateIamPolicyResultOutput) ToLookupNotebookRuntimeTemplateIamPolicyResultOutput() LookupNotebookRuntimeTemplateIamPolicyResultOutput

func (LookupNotebookRuntimeTemplateIamPolicyResultOutput) ToLookupNotebookRuntimeTemplateIamPolicyResultOutputWithContext 

func (o LookupNotebookRuntimeTemplateIamPolicyResultOutput) ToLookupNotebookRuntimeTemplateIamPolicyResultOutputWithContext(ctx context.Context) LookupNotebookRuntimeTemplateIamPolicyResultOutput

func (LookupNotebookRuntimeTemplateIamPolicyResultOutput) Version 

func (o LookupNotebookRuntimeTemplateIamPolicyResultOutput) Version() pulumi.IntOutput

Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).

type LookupNotebookRuntimeTemplateOutputArgs 

type LookupNotebookRuntimeTemplateOutputArgs struct {
	Location                  pulumi.StringInput    `pulumi:"location"`
	NotebookRuntimeTemplateId pulumi.StringInput    `pulumi:"notebookRuntimeTemplateId"`
	Project                   pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupNotebookRuntimeTemplateOutputArgs) ElementType 

func (LookupNotebookRuntimeTemplateOutputArgs) ElementType() reflect.Type

type LookupNotebookRuntimeTemplateResult 

type LookupNotebookRuntimeTemplateResult struct {
	// Timestamp when this NotebookRuntimeTemplate was created.
	CreateTime string `pulumi:"createTime"`
	// Optional. The specification of persistent disk attached to the runtime as data disk storage.
	DataPersistentDiskSpec GoogleCloudAiplatformV1PersistentDiskSpecResponse `pulumi:"dataPersistentDiskSpec"`
	// The description of the NotebookRuntimeTemplate.
	Description string `pulumi:"description"`
	// The display name of the NotebookRuntimeTemplate. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// EUC configuration of the NotebookRuntimeTemplate.
	EucConfig GoogleCloudAiplatformV1NotebookEucConfigResponse `pulumi:"eucConfig"`
	// The idle shutdown configuration of NotebookRuntimeTemplate. This config will only be set when idle shutdown is enabled.
	IdleShutdownConfig GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponse `pulumi:"idleShutdownConfig"`
	// The default template to use if not specified.
	IsDefault bool `pulumi:"isDefault"`
	// The labels with user-defined metadata to organize the NotebookRuntimeTemplates. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels map[string]string `pulumi:"labels"`
	// Optional. Immutable. The specification of a single machine for the template.
	MachineSpec GoogleCloudAiplatformV1MachineSpecResponse `pulumi:"machineSpec"`
	// The resource name of the NotebookRuntimeTemplate.
	Name string `pulumi:"name"`
	// Optional. Network spec.
	NetworkSpec GoogleCloudAiplatformV1NetworkSpecResponse `pulumi:"networkSpec"`
	// Optional. Immutable. The type of the notebook runtime template.
	NotebookRuntimeType string `pulumi:"notebookRuntimeType"`
	// The service account that the runtime workload runs as. You can use any service account within the same project, but you must have the service account user permission to use the instance. If not specified, the [Compute Engine default service account](https://cloud.google.com/compute/docs/access/service-accounts#default_service_account) is used.
	ServiceAccount string `pulumi:"serviceAccount"`
	// Timestamp when this NotebookRuntimeTemplate was most recently updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupNotebookRuntimeTemplate 

func LookupNotebookRuntimeTemplate(ctx *pulumi.Context, args *LookupNotebookRuntimeTemplateArgs, opts ...pulumi.InvokeOption) (*LookupNotebookRuntimeTemplateResult, error)

Gets a NotebookRuntimeTemplate.

type LookupNotebookRuntimeTemplateResultOutput 

type LookupNotebookRuntimeTemplateResultOutput struct{ *pulumi.OutputState }

func LookupNotebookRuntimeTemplateOutput 

func LookupNotebookRuntimeTemplateOutput(ctx *pulumi.Context, args LookupNotebookRuntimeTemplateOutputArgs, opts ...pulumi.InvokeOption) LookupNotebookRuntimeTemplateResultOutput

func (LookupNotebookRuntimeTemplateResultOutput) CreateTime 

func (o LookupNotebookRuntimeTemplateResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this NotebookRuntimeTemplate was created.

func (LookupNotebookRuntimeTemplateResultOutput) DataPersistentDiskSpec 

func (o LookupNotebookRuntimeTemplateResultOutput) DataPersistentDiskSpec() GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput

Optional. The specification of persistent disk attached to the runtime as data disk storage.

func (LookupNotebookRuntimeTemplateResultOutput) Description 

func (o LookupNotebookRuntimeTemplateResultOutput) Description() pulumi.StringOutput

The description of the NotebookRuntimeTemplate.

func (LookupNotebookRuntimeTemplateResultOutput) DisplayName 

func (o LookupNotebookRuntimeTemplateResultOutput) DisplayName() pulumi.StringOutput

The display name of the NotebookRuntimeTemplate. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (LookupNotebookRuntimeTemplateResultOutput) ElementType 

func (LookupNotebookRuntimeTemplateResultOutput) ElementType() reflect.Type

func (LookupNotebookRuntimeTemplateResultOutput) Etag 

func (o LookupNotebookRuntimeTemplateResultOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupNotebookRuntimeTemplateResultOutput) EucConfig 

func (o LookupNotebookRuntimeTemplateResultOutput) EucConfig() GoogleCloudAiplatformV1NotebookEucConfigResponseOutput

EUC configuration of the NotebookRuntimeTemplate.

func (LookupNotebookRuntimeTemplateResultOutput) IdleShutdownConfig 

func (o LookupNotebookRuntimeTemplateResultOutput) IdleShutdownConfig() GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput

The idle shutdown configuration of NotebookRuntimeTemplate. This config will only be set when idle shutdown is enabled.

func (LookupNotebookRuntimeTemplateResultOutput) IsDefault 

func (o LookupNotebookRuntimeTemplateResultOutput) IsDefault() pulumi.BoolOutput

The default template to use if not specified.

func (LookupNotebookRuntimeTemplateResultOutput) Labels 

func (o LookupNotebookRuntimeTemplateResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize the NotebookRuntimeTemplates. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (LookupNotebookRuntimeTemplateResultOutput) MachineSpec 

func (o LookupNotebookRuntimeTemplateResultOutput) MachineSpec() GoogleCloudAiplatformV1MachineSpecResponseOutput

Optional. Immutable. The specification of a single machine for the template.

func (LookupNotebookRuntimeTemplateResultOutput) Name 

func (o LookupNotebookRuntimeTemplateResultOutput) Name() pulumi.StringOutput

The resource name of the NotebookRuntimeTemplate.

func (LookupNotebookRuntimeTemplateResultOutput) NetworkSpec 

func (o LookupNotebookRuntimeTemplateResultOutput) NetworkSpec() GoogleCloudAiplatformV1NetworkSpecResponseOutput

Optional. Network spec.

func (LookupNotebookRuntimeTemplateResultOutput) NotebookRuntimeType 

func (o LookupNotebookRuntimeTemplateResultOutput) NotebookRuntimeType() pulumi.StringOutput

Optional. Immutable. The type of the notebook runtime template.

func (LookupNotebookRuntimeTemplateResultOutput) ServiceAccount 

func (o LookupNotebookRuntimeTemplateResultOutput) ServiceAccount() pulumi.StringOutput

The service account that the runtime workload runs as. You can use any service account within the same project, but you must have the service account user permission to use the instance. If not specified, the [Compute Engine default service account](https://cloud.google.com/compute/docs/access/service-accounts#default_service_account) is used.

func (LookupNotebookRuntimeTemplateResultOutput) ToLookupNotebookRuntimeTemplateResultOutput 

func (o LookupNotebookRuntimeTemplateResultOutput) ToLookupNotebookRuntimeTemplateResultOutput() LookupNotebookRuntimeTemplateResultOutput

func (LookupNotebookRuntimeTemplateResultOutput) ToLookupNotebookRuntimeTemplateResultOutputWithContext 

func (o LookupNotebookRuntimeTemplateResultOutput) ToLookupNotebookRuntimeTemplateResultOutputWithContext(ctx context.Context) LookupNotebookRuntimeTemplateResultOutput

func (LookupNotebookRuntimeTemplateResultOutput) UpdateTime 

func (o LookupNotebookRuntimeTemplateResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this NotebookRuntimeTemplate was most recently updated.

type LookupPipelineJobArgs 

type LookupPipelineJobArgs struct {
	Location      string  `pulumi:"location"`
	PipelineJobId string  `pulumi:"pipelineJobId"`
	Project       *string `pulumi:"project"`
}

type LookupPipelineJobOutputArgs 

type LookupPipelineJobOutputArgs struct {
	Location      pulumi.StringInput    `pulumi:"location"`
	PipelineJobId pulumi.StringInput    `pulumi:"pipelineJobId"`
	Project       pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupPipelineJobOutputArgs) ElementType 

func (LookupPipelineJobOutputArgs) ElementType() reflect.Type

type LookupPipelineJobResult 

type LookupPipelineJobResult struct {
	// Pipeline creation time.
	CreateTime string `pulumi:"createTime"`
	// The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Pipeline end time.
	EndTime string `pulumi:"endTime"`
	// The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
	Error GoogleRpcStatusResponse `pulumi:"error"`
	// The details of pipeline run. Not available in the list view.
	JobDetail GoogleCloudAiplatformV1PipelineJobDetailResponse `pulumi:"jobDetail"`
	// The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
	Labels map[string]string `pulumi:"labels"`
	// The resource name of the PipelineJob.
	Name string `pulumi:"name"`
	// The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
	Network string `pulumi:"network"`
	// The spec of the pipeline.
	PipelineSpec map[string]string `pulumi:"pipelineSpec"`
	// A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
	ReservedIpRanges []string `pulumi:"reservedIpRanges"`
	// Runtime config of the pipeline.
	RuntimeConfig GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponse `pulumi:"runtimeConfig"`
	// The schedule resource name. Only returned if the Pipeline is created by Schedule API.
	ScheduleName string `pulumi:"scheduleName"`
	// The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
	ServiceAccount string `pulumi:"serviceAccount"`
	// Pipeline start time.
	StartTime string `pulumi:"startTime"`
	// The detailed state of the job.
	State string `pulumi:"state"`
	// Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
	TemplateMetadata GoogleCloudAiplatformV1PipelineTemplateMetadataResponse `pulumi:"templateMetadata"`
	// A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
	TemplateUri string `pulumi:"templateUri"`
	// Timestamp when this PipelineJob was most recently updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupPipelineJob 

func LookupPipelineJob(ctx *pulumi.Context, args *LookupPipelineJobArgs, opts ...pulumi.InvokeOption) (*LookupPipelineJobResult, error)

Gets a PipelineJob.

type LookupPipelineJobResultOutput 

type LookupPipelineJobResultOutput struct{ *pulumi.OutputState }

func LookupPipelineJobOutput 

func LookupPipelineJobOutput(ctx *pulumi.Context, args LookupPipelineJobOutputArgs, opts ...pulumi.InvokeOption) LookupPipelineJobResultOutput

func (LookupPipelineJobResultOutput) CreateTime 

func (o LookupPipelineJobResultOutput) CreateTime() pulumi.StringOutput

Pipeline creation time.

func (LookupPipelineJobResultOutput) DisplayName 

func (o LookupPipelineJobResultOutput) DisplayName() pulumi.StringOutput

The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (LookupPipelineJobResultOutput) ElementType 

func (LookupPipelineJobResultOutput) ElementType() reflect.Type

func (LookupPipelineJobResultOutput) EncryptionSpec 

func (o LookupPipelineJobResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.

func (LookupPipelineJobResultOutput) EndTime 

func (o LookupPipelineJobResultOutput) EndTime() pulumi.StringOutput

Pipeline end time.

func (LookupPipelineJobResultOutput) Error 

func (o LookupPipelineJobResultOutput) Error() GoogleRpcStatusResponseOutput

The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.

func (LookupPipelineJobResultOutput) JobDetail 

func (o LookupPipelineJobResultOutput) JobDetail() GoogleCloudAiplatformV1PipelineJobDetailResponseOutput

The details of pipeline run. Not available in the list view.

func (LookupPipelineJobResultOutput) Labels 

func (o LookupPipelineJobResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.

func (LookupPipelineJobResultOutput) Name 

func (o LookupPipelineJobResultOutput) Name() pulumi.StringOutput

The resource name of the PipelineJob.

func (LookupPipelineJobResultOutput) Network 

func (o LookupPipelineJobResultOutput) Network() pulumi.StringOutput

The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.

func (LookupPipelineJobResultOutput) PipelineSpec 

func (o LookupPipelineJobResultOutput) PipelineSpec() pulumi.StringMapOutput

The spec of the pipeline.

func (LookupPipelineJobResultOutput) ReservedIpRanges 

func (o LookupPipelineJobResultOutput) ReservedIpRanges() pulumi.StringArrayOutput

A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

func (LookupPipelineJobResultOutput) RuntimeConfig 

func (o LookupPipelineJobResultOutput) RuntimeConfig() GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput

Runtime config of the pipeline.

func (LookupPipelineJobResultOutput) ScheduleName 

func (o LookupPipelineJobResultOutput) ScheduleName() pulumi.StringOutput

The schedule resource name. Only returned if the Pipeline is created by Schedule API.

func (LookupPipelineJobResultOutput) ServiceAccount 

func (o LookupPipelineJobResultOutput) ServiceAccount() pulumi.StringOutput

The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.

func (LookupPipelineJobResultOutput) StartTime 

func (o LookupPipelineJobResultOutput) StartTime() pulumi.StringOutput

Pipeline start time.

func (LookupPipelineJobResultOutput) State 

func (o LookupPipelineJobResultOutput) State() pulumi.StringOutput

The detailed state of the job.

func (LookupPipelineJobResultOutput) TemplateMetadata 

func (o LookupPipelineJobResultOutput) TemplateMetadata() GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput

Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.

func (LookupPipelineJobResultOutput) TemplateUri 

func (o LookupPipelineJobResultOutput) TemplateUri() pulumi.StringOutput

A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.

func (LookupPipelineJobResultOutput) ToLookupPipelineJobResultOutput 

func (o LookupPipelineJobResultOutput) ToLookupPipelineJobResultOutput() LookupPipelineJobResultOutput

func (LookupPipelineJobResultOutput) ToLookupPipelineJobResultOutputWithContext 

func (o LookupPipelineJobResultOutput) ToLookupPipelineJobResultOutputWithContext(ctx context.Context) LookupPipelineJobResultOutput

func (LookupPipelineJobResultOutput) UpdateTime 

func (o LookupPipelineJobResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this PipelineJob was most recently updated.

type LookupRunArgs 

type LookupRunArgs struct {
	ExperimentId  string  `pulumi:"experimentId"`
	Location      string  `pulumi:"location"`
	Project       *string `pulumi:"project"`
	RunId         string  `pulumi:"runId"`
	TensorboardId string  `pulumi:"tensorboardId"`
}

type LookupRunOutputArgs 

type LookupRunOutputArgs struct {
	ExperimentId  pulumi.StringInput    `pulumi:"experimentId"`
	Location      pulumi.StringInput    `pulumi:"location"`
	Project       pulumi.StringPtrInput `pulumi:"project"`
	RunId         pulumi.StringInput    `pulumi:"runId"`
	TensorboardId pulumi.StringInput    `pulumi:"tensorboardId"`
}

func (LookupRunOutputArgs) ElementType 

func (LookupRunOutputArgs) ElementType() reflect.Type

type LookupRunResult 

type LookupRunResult struct {
	// Timestamp when this TensorboardRun was created.
	CreateTime string `pulumi:"createTime"`
	// Description of this TensorboardRun.
	Description string `pulumi:"description"`
	// User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
	DisplayName string `pulumi:"displayName"`
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels map[string]string `pulumi:"labels"`
	// Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
	Name string `pulumi:"name"`
	// Timestamp when this TensorboardRun was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupRun 

func LookupRun(ctx *pulumi.Context, args *LookupRunArgs, opts ...pulumi.InvokeOption) (*LookupRunResult, error)

Gets a TensorboardRun.

type LookupRunResultOutput 

type LookupRunResultOutput struct{ *pulumi.OutputState }

func LookupRunOutput 

func LookupRunOutput(ctx *pulumi.Context, args LookupRunOutputArgs, opts ...pulumi.InvokeOption) LookupRunResultOutput

func (LookupRunResultOutput) CreateTime 

func (o LookupRunResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this TensorboardRun was created.

func (LookupRunResultOutput) Description 

func (o LookupRunResultOutput) Description() pulumi.StringOutput

Description of this TensorboardRun.

func (LookupRunResultOutput) DisplayName 

func (o LookupRunResultOutput) DisplayName() pulumi.StringOutput

User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.

func (LookupRunResultOutput) ElementType 

func (LookupRunResultOutput) ElementType() reflect.Type

func (LookupRunResultOutput) Etag 

func (o LookupRunResultOutput) Etag() pulumi.StringOutput

Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupRunResultOutput) Labels 

func (o LookupRunResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (LookupRunResultOutput) Name 

func (o LookupRunResultOutput) Name() pulumi.StringOutput

Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`

func (LookupRunResultOutput) ToLookupRunResultOutput 

func (o LookupRunResultOutput) ToLookupRunResultOutput() LookupRunResultOutput

func (LookupRunResultOutput) ToLookupRunResultOutputWithContext 

func (o LookupRunResultOutput) ToLookupRunResultOutputWithContext(ctx context.Context) LookupRunResultOutput

func (LookupRunResultOutput) UpdateTime 

func (o LookupRunResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this TensorboardRun was last updated.

type LookupScheduleArgs 

type LookupScheduleArgs struct {
	Location   string  `pulumi:"location"`
	Project    *string `pulumi:"project"`
	ScheduleId string  `pulumi:"scheduleId"`
}

type LookupScheduleOutputArgs 

type LookupScheduleOutputArgs struct {
	Location   pulumi.StringInput    `pulumi:"location"`
	Project    pulumi.StringPtrInput `pulumi:"project"`
	ScheduleId pulumi.StringInput    `pulumi:"scheduleId"`
}

func (LookupScheduleOutputArgs) ElementType 

func (LookupScheduleOutputArgs) ElementType() reflect.Type

type LookupScheduleResult 

type LookupScheduleResult struct {
	// Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.
	AllowQueueing bool `pulumi:"allowQueueing"`
	// Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false.
	CatchUp bool `pulumi:"catchUp"`
	// Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
	CreatePipelineJobRequest GoogleCloudAiplatformV1CreatePipelineJobRequestResponse `pulumi:"createPipelineJobRequest"`
	// Timestamp when this Schedule was created.
	CreateTime string `pulumi:"createTime"`
	// Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".
	Cron string `pulumi:"cron"`
	// User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName string `pulumi:"displayName"`
	// Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count >= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
	EndTime string `pulumi:"endTime"`
	// Timestamp when this Schedule was last paused. Unset if never paused.
	LastPauseTime string `pulumi:"lastPauseTime"`
	// Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
	LastResumeTime string `pulumi:"lastResumeTime"`
	// Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet.
	LastScheduledRunResponse GoogleCloudAiplatformV1ScheduleRunResponseResponse `pulumi:"lastScheduledRunResponse"`
	// Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable).
	MaxConcurrentRunCount string `pulumi:"maxConcurrentRunCount"`
	// Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count >= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
	MaxRunCount string `pulumi:"maxRunCount"`
	// Immutable. The resource name of the Schedule.
	Name string `pulumi:"name"`
	// Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule.
	NextRunTime string `pulumi:"nextRunTime"`
	// Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
	StartTime string `pulumi:"startTime"`
	// The number of runs started by this schedule.
	StartedRunCount string `pulumi:"startedRunCount"`
	// The state of this Schedule.
	State string `pulumi:"state"`
	// Timestamp when this Schedule was updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupSchedule 

func LookupSchedule(ctx *pulumi.Context, args *LookupScheduleArgs, opts ...pulumi.InvokeOption) (*LookupScheduleResult, error)

Gets a Schedule.

type LookupScheduleResultOutput 

type LookupScheduleResultOutput struct{ *pulumi.OutputState }

func LookupScheduleOutput 

func LookupScheduleOutput(ctx *pulumi.Context, args LookupScheduleOutputArgs, opts ...pulumi.InvokeOption) LookupScheduleResultOutput

func (LookupScheduleResultOutput) AllowQueueing 

func (o LookupScheduleResultOutput) AllowQueueing() pulumi.BoolOutput

Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.

func (LookupScheduleResultOutput) CatchUp 

func (o LookupScheduleResultOutput) CatchUp() pulumi.BoolOutput

Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false.

func (LookupScheduleResultOutput) CreatePipelineJobRequest 

func (o LookupScheduleResultOutput) CreatePipelineJobRequest() GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput

Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).

func (LookupScheduleResultOutput) CreateTime 

func (o LookupScheduleResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this Schedule was created.

func (LookupScheduleResultOutput) Cron 

func (o LookupScheduleResultOutput) Cron() pulumi.StringOutput

Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".

func (LookupScheduleResultOutput) DisplayName 

func (o LookupScheduleResultOutput) DisplayName() pulumi.StringOutput

User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (LookupScheduleResultOutput) ElementType 

func (LookupScheduleResultOutput) ElementType() reflect.Type

func (LookupScheduleResultOutput) EndTime 

func (o LookupScheduleResultOutput) EndTime() pulumi.StringOutput

Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count >= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.

func (LookupScheduleResultOutput) LastPauseTime 

func (o LookupScheduleResultOutput) LastPauseTime() pulumi.StringOutput

Timestamp when this Schedule was last paused. Unset if never paused.

func (LookupScheduleResultOutput) LastResumeTime 

func (o LookupScheduleResultOutput) LastResumeTime() pulumi.StringOutput

Timestamp when this Schedule was last resumed. Unset if never resumed from pause.

func (LookupScheduleResultOutput) LastScheduledRunResponse 

func (o LookupScheduleResultOutput) LastScheduledRunResponse() GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput

Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet.

func (LookupScheduleResultOutput) MaxConcurrentRunCount 

func (o LookupScheduleResultOutput) MaxConcurrentRunCount() pulumi.StringOutput

Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable).

func (LookupScheduleResultOutput) MaxRunCount 

func (o LookupScheduleResultOutput) MaxRunCount() pulumi.StringOutput

Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count >= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.

func (LookupScheduleResultOutput) Name 

func (o LookupScheduleResultOutput) Name() pulumi.StringOutput

Immutable. The resource name of the Schedule.

func (LookupScheduleResultOutput) NextRunTime 

func (o LookupScheduleResultOutput) NextRunTime() pulumi.StringOutput

Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule.

func (LookupScheduleResultOutput) StartTime 

func (o LookupScheduleResultOutput) StartTime() pulumi.StringOutput

Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.

func (LookupScheduleResultOutput) StartedRunCount 

func (o LookupScheduleResultOutput) StartedRunCount() pulumi.StringOutput

The number of runs started by this schedule.

func (LookupScheduleResultOutput) State 

func (o LookupScheduleResultOutput) State() pulumi.StringOutput

The state of this Schedule.

func (LookupScheduleResultOutput) ToLookupScheduleResultOutput 

func (o LookupScheduleResultOutput) ToLookupScheduleResultOutput() LookupScheduleResultOutput

func (LookupScheduleResultOutput) ToLookupScheduleResultOutputWithContext 

func (o LookupScheduleResultOutput) ToLookupScheduleResultOutputWithContext(ctx context.Context) LookupScheduleResultOutput

func (LookupScheduleResultOutput) UpdateTime 

func (o LookupScheduleResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Schedule was updated.

type LookupSpecialistPoolArgs 

type LookupSpecialistPoolArgs struct {
	Location         string  `pulumi:"location"`
	Project          *string `pulumi:"project"`
	SpecialistPoolId string  `pulumi:"specialistPoolId"`
}

type LookupSpecialistPoolOutputArgs 

type LookupSpecialistPoolOutputArgs struct {
	Location         pulumi.StringInput    `pulumi:"location"`
	Project          pulumi.StringPtrInput `pulumi:"project"`
	SpecialistPoolId pulumi.StringInput    `pulumi:"specialistPoolId"`
}

func (LookupSpecialistPoolOutputArgs) ElementType 

func (LookupSpecialistPoolOutputArgs) ElementType() reflect.Type

type LookupSpecialistPoolResult 

type LookupSpecialistPoolResult struct {
	// The user-defined name of the SpecialistPool. The name can be up to 128 characters long and can consist of any UTF-8 characters. This field should be unique on project-level.
	DisplayName string `pulumi:"displayName"`
	// The resource name of the SpecialistPool.
	Name string `pulumi:"name"`
	// The resource name of the pending data labeling jobs.
	PendingDataLabelingJobs []string `pulumi:"pendingDataLabelingJobs"`
	// The email addresses of the managers in the SpecialistPool.
	SpecialistManagerEmails []string `pulumi:"specialistManagerEmails"`
	// The number of managers in this SpecialistPool.
	SpecialistManagersCount int `pulumi:"specialistManagersCount"`
	// The email addresses of workers in the SpecialistPool.
	SpecialistWorkerEmails []string `pulumi:"specialistWorkerEmails"`
}

func LookupSpecialistPool 

func LookupSpecialistPool(ctx *pulumi.Context, args *LookupSpecialistPoolArgs, opts ...pulumi.InvokeOption) (*LookupSpecialistPoolResult, error)

Gets a SpecialistPool.

type LookupSpecialistPoolResultOutput 

type LookupSpecialistPoolResultOutput struct{ *pulumi.OutputState }

func LookupSpecialistPoolOutput 

func LookupSpecialistPoolOutput(ctx *pulumi.Context, args LookupSpecialistPoolOutputArgs, opts ...pulumi.InvokeOption) LookupSpecialistPoolResultOutput

func (LookupSpecialistPoolResultOutput) DisplayName 

func (o LookupSpecialistPoolResultOutput) DisplayName() pulumi.StringOutput

The user-defined name of the SpecialistPool. The name can be up to 128 characters long and can consist of any UTF-8 characters. This field should be unique on project-level.

func (LookupSpecialistPoolResultOutput) ElementType 

func (LookupSpecialistPoolResultOutput) ElementType() reflect.Type

func (LookupSpecialistPoolResultOutput) Name 

func (o LookupSpecialistPoolResultOutput) Name() pulumi.StringOutput

The resource name of the SpecialistPool.

func (LookupSpecialistPoolResultOutput) PendingDataLabelingJobs 

func (o LookupSpecialistPoolResultOutput) PendingDataLabelingJobs() pulumi.StringArrayOutput

The resource name of the pending data labeling jobs.

func (LookupSpecialistPoolResultOutput) SpecialistManagerEmails 

func (o LookupSpecialistPoolResultOutput) SpecialistManagerEmails() pulumi.StringArrayOutput

The email addresses of the managers in the SpecialistPool.

func (LookupSpecialistPoolResultOutput) SpecialistManagersCount 

func (o LookupSpecialistPoolResultOutput) SpecialistManagersCount() pulumi.IntOutput

The number of managers in this SpecialistPool.

func (LookupSpecialistPoolResultOutput) SpecialistWorkerEmails 

func (o LookupSpecialistPoolResultOutput) SpecialistWorkerEmails() pulumi.StringArrayOutput

The email addresses of workers in the SpecialistPool.

func (LookupSpecialistPoolResultOutput) ToLookupSpecialistPoolResultOutput 

func (o LookupSpecialistPoolResultOutput) ToLookupSpecialistPoolResultOutput() LookupSpecialistPoolResultOutput

func (LookupSpecialistPoolResultOutput) ToLookupSpecialistPoolResultOutputWithContext 

func (o LookupSpecialistPoolResultOutput) ToLookupSpecialistPoolResultOutputWithContext(ctx context.Context) LookupSpecialistPoolResultOutput

type LookupStudyArgs 

type LookupStudyArgs struct {
	Location string  `pulumi:"location"`
	Project  *string `pulumi:"project"`
	StudyId  string  `pulumi:"studyId"`
}

type LookupStudyOutputArgs 

type LookupStudyOutputArgs struct {
	Location pulumi.StringInput    `pulumi:"location"`
	Project  pulumi.StringPtrInput `pulumi:"project"`
	StudyId  pulumi.StringInput    `pulumi:"studyId"`
}

func (LookupStudyOutputArgs) ElementType 

func (LookupStudyOutputArgs) ElementType() reflect.Type

type LookupStudyResult 

type LookupStudyResult struct {
	// Time at which the study was created.
	CreateTime string `pulumi:"createTime"`
	// Describes the Study, default value is empty string.
	DisplayName string `pulumi:"displayName"`
	// A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.
	InactiveReason string `pulumi:"inactiveReason"`
	// The name of a study. The study's globally unique identifier. Format: `projects/{project}/locations/{location}/studies/{study}`
	Name string `pulumi:"name"`
	// The detailed state of a Study.
	State string `pulumi:"state"`
	// Configuration of the Study.
	StudySpec GoogleCloudAiplatformV1StudySpecResponse `pulumi:"studySpec"`
}

func LookupStudy 

func LookupStudy(ctx *pulumi.Context, args *LookupStudyArgs, opts ...pulumi.InvokeOption) (*LookupStudyResult, error)

Gets a Study by name.

type LookupStudyResultOutput 

type LookupStudyResultOutput struct{ *pulumi.OutputState }

func LookupStudyOutput 

func LookupStudyOutput(ctx *pulumi.Context, args LookupStudyOutputArgs, opts ...pulumi.InvokeOption) LookupStudyResultOutput

func (LookupStudyResultOutput) CreateTime 

func (o LookupStudyResultOutput) CreateTime() pulumi.StringOutput

Time at which the study was created.

func (LookupStudyResultOutput) DisplayName 

func (o LookupStudyResultOutput) DisplayName() pulumi.StringOutput

Describes the Study, default value is empty string.

func (LookupStudyResultOutput) ElementType 

func (LookupStudyResultOutput) ElementType() reflect.Type

func (LookupStudyResultOutput) InactiveReason 

func (o LookupStudyResultOutput) InactiveReason() pulumi.StringOutput

A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.

func (LookupStudyResultOutput) Name 

func (o LookupStudyResultOutput) Name() pulumi.StringOutput

The name of a study. The study's globally unique identifier. Format: `projects/{project}/locations/{location}/studies/{study}`

func (LookupStudyResultOutput) State 

func (o LookupStudyResultOutput) State() pulumi.StringOutput

The detailed state of a Study.

func (LookupStudyResultOutput) StudySpec 

func (o LookupStudyResultOutput) StudySpec() GoogleCloudAiplatformV1StudySpecResponseOutput

Configuration of the Study.

func (LookupStudyResultOutput) ToLookupStudyResultOutput 

func (o LookupStudyResultOutput) ToLookupStudyResultOutput() LookupStudyResultOutput

func (LookupStudyResultOutput) ToLookupStudyResultOutputWithContext 

func (o LookupStudyResultOutput) ToLookupStudyResultOutputWithContext(ctx context.Context) LookupStudyResultOutput

type LookupTensorboardArgs 

type LookupTensorboardArgs struct {
	Location      string  `pulumi:"location"`
	Project       *string `pulumi:"project"`
	TensorboardId string  `pulumi:"tensorboardId"`
}

type LookupTensorboardOutputArgs 

type LookupTensorboardOutputArgs struct {
	Location      pulumi.StringInput    `pulumi:"location"`
	Project       pulumi.StringPtrInput `pulumi:"project"`
	TensorboardId pulumi.StringInput    `pulumi:"tensorboardId"`
}

func (LookupTensorboardOutputArgs) ElementType 

func (LookupTensorboardOutputArgs) ElementType() reflect.Type

type LookupTensorboardResult 

type LookupTensorboardResult struct {
	// Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
	BlobStoragePathPrefix string `pulumi:"blobStoragePathPrefix"`
	// Timestamp when this Tensorboard was created.
	CreateTime string `pulumi:"createTime"`
	// Description of this Tensorboard.
	Description string `pulumi:"description"`
	// User provided name of this Tensorboard.
	DisplayName string `pulumi:"displayName"`
	// Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// Used to indicate if the TensorBoard instance is the default one. Each project & region can have at most one default TensorBoard instance. Creation of a default TensorBoard instance and updating an existing TensorBoard instance to be default will mark all other TensorBoard instances (if any) as non default.
	IsDefault bool `pulumi:"isDefault"`
	// The labels with user-defined metadata to organize your Tensorboards. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Tensorboard (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels map[string]string `pulumi:"labels"`
	// Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
	Name string `pulumi:"name"`
	// The number of Runs stored in this Tensorboard.
	RunCount int `pulumi:"runCount"`
	// Timestamp when this Tensorboard was last updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupTensorboard 

func LookupTensorboard(ctx *pulumi.Context, args *LookupTensorboardArgs, opts ...pulumi.InvokeOption) (*LookupTensorboardResult, error)

Gets a Tensorboard.

type LookupTensorboardResultOutput 

type LookupTensorboardResultOutput struct{ *pulumi.OutputState }

func LookupTensorboardOutput 

func LookupTensorboardOutput(ctx *pulumi.Context, args LookupTensorboardOutputArgs, opts ...pulumi.InvokeOption) LookupTensorboardResultOutput

func (LookupTensorboardResultOutput) BlobStoragePathPrefix 

func (o LookupTensorboardResultOutput) BlobStoragePathPrefix() pulumi.StringOutput

Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.

func (LookupTensorboardResultOutput) CreateTime 

func (o LookupTensorboardResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this Tensorboard was created.

func (LookupTensorboardResultOutput) Description 

func (o LookupTensorboardResultOutput) Description() pulumi.StringOutput

Description of this Tensorboard.

func (LookupTensorboardResultOutput) DisplayName 

func (o LookupTensorboardResultOutput) DisplayName() pulumi.StringOutput

User provided name of this Tensorboard.

func (LookupTensorboardResultOutput) ElementType 

func (LookupTensorboardResultOutput) ElementType() reflect.Type

func (LookupTensorboardResultOutput) EncryptionSpec 

func (o LookupTensorboardResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key.

func (LookupTensorboardResultOutput) Etag 

func (o LookupTensorboardResultOutput) Etag() pulumi.StringOutput

Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupTensorboardResultOutput) IsDefault 

func (o LookupTensorboardResultOutput) IsDefault() pulumi.BoolOutput

Used to indicate if the TensorBoard instance is the default one. Each project & region can have at most one default TensorBoard instance. Creation of a default TensorBoard instance and updating an existing TensorBoard instance to be default will mark all other TensorBoard instances (if any) as non default.

func (LookupTensorboardResultOutput) Labels 

func (o LookupTensorboardResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Tensorboards. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Tensorboard (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (LookupTensorboardResultOutput) Name 

func (o LookupTensorboardResultOutput) Name() pulumi.StringOutput

Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`

func (LookupTensorboardResultOutput) RunCount 

func (o LookupTensorboardResultOutput) RunCount() pulumi.IntOutput

The number of Runs stored in this Tensorboard.

func (LookupTensorboardResultOutput) ToLookupTensorboardResultOutput 

func (o LookupTensorboardResultOutput) ToLookupTensorboardResultOutput() LookupTensorboardResultOutput

func (LookupTensorboardResultOutput) ToLookupTensorboardResultOutputWithContext 

func (o LookupTensorboardResultOutput) ToLookupTensorboardResultOutputWithContext(ctx context.Context) LookupTensorboardResultOutput

func (LookupTensorboardResultOutput) UpdateTime 

func (o LookupTensorboardResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Tensorboard was last updated.

type LookupTimeSeriesArgs 

type LookupTimeSeriesArgs struct {
	ExperimentId  string  `pulumi:"experimentId"`
	Location      string  `pulumi:"location"`
	Project       *string `pulumi:"project"`
	RunId         string  `pulumi:"runId"`
	TensorboardId string  `pulumi:"tensorboardId"`
	TimeSeriesId  string  `pulumi:"timeSeriesId"`
}

type LookupTimeSeriesOutputArgs 

type LookupTimeSeriesOutputArgs struct {
	ExperimentId  pulumi.StringInput    `pulumi:"experimentId"`
	Location      pulumi.StringInput    `pulumi:"location"`
	Project       pulumi.StringPtrInput `pulumi:"project"`
	RunId         pulumi.StringInput    `pulumi:"runId"`
	TensorboardId pulumi.StringInput    `pulumi:"tensorboardId"`
	TimeSeriesId  pulumi.StringInput    `pulumi:"timeSeriesId"`
}

func (LookupTimeSeriesOutputArgs) ElementType 

func (LookupTimeSeriesOutputArgs) ElementType() reflect.Type

type LookupTimeSeriesResult 

type LookupTimeSeriesResult struct {
	// Timestamp when this TensorboardTimeSeries was created.
	CreateTime string `pulumi:"createTime"`
	// Description of this TensorboardTimeSeries.
	Description string `pulumi:"description"`
	// User provided name of this TensorboardTimeSeries. This value should be unique among all TensorboardTimeSeries resources belonging to the same TensorboardRun resource (parent resource).
	DisplayName string `pulumi:"displayName"`
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag string `pulumi:"etag"`
	// Scalar, Tensor, or Blob metadata for this TensorboardTimeSeries.
	Metadata GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponse `pulumi:"metadata"`
	// Name of the TensorboardTimeSeries.
	Name string `pulumi:"name"`
	// Data of the current plugin, with the size limited to 65KB.
	PluginData string `pulumi:"pluginData"`
	// Immutable. Name of the plugin this time series pertain to. Such as Scalar, Tensor, Blob
	PluginName string `pulumi:"pluginName"`
	// Timestamp when this TensorboardTimeSeries was last updated.
	UpdateTime string `pulumi:"updateTime"`
	// Immutable. Type of TensorboardTimeSeries value.
	ValueType string `pulumi:"valueType"`
}

func LookupTimeSeries 

func LookupTimeSeries(ctx *pulumi.Context, args *LookupTimeSeriesArgs, opts ...pulumi.InvokeOption) (*LookupTimeSeriesResult, error)

Gets a TensorboardTimeSeries.

type LookupTimeSeriesResultOutput 

type LookupTimeSeriesResultOutput struct{ *pulumi.OutputState }

func LookupTimeSeriesOutput 

func LookupTimeSeriesOutput(ctx *pulumi.Context, args LookupTimeSeriesOutputArgs, opts ...pulumi.InvokeOption) LookupTimeSeriesResultOutput

func (LookupTimeSeriesResultOutput) CreateTime 

func (o LookupTimeSeriesResultOutput) CreateTime() pulumi.StringOutput

Timestamp when this TensorboardTimeSeries was created.

func (LookupTimeSeriesResultOutput) Description 

func (o LookupTimeSeriesResultOutput) Description() pulumi.StringOutput

Description of this TensorboardTimeSeries.

func (LookupTimeSeriesResultOutput) DisplayName 

func (o LookupTimeSeriesResultOutput) DisplayName() pulumi.StringOutput

User provided name of this TensorboardTimeSeries. This value should be unique among all TensorboardTimeSeries resources belonging to the same TensorboardRun resource (parent resource).

func (LookupTimeSeriesResultOutput) ElementType 

func (LookupTimeSeriesResultOutput) ElementType() reflect.Type

func (LookupTimeSeriesResultOutput) Etag 

func (o LookupTimeSeriesResultOutput) Etag() pulumi.StringOutput

Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (LookupTimeSeriesResultOutput) Metadata 

func (o LookupTimeSeriesResultOutput) Metadata() GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput

Scalar, Tensor, or Blob metadata for this TensorboardTimeSeries.

func (LookupTimeSeriesResultOutput) Name 

func (o LookupTimeSeriesResultOutput) Name() pulumi.StringOutput

Name of the TensorboardTimeSeries.

func (LookupTimeSeriesResultOutput) PluginData 

func (o LookupTimeSeriesResultOutput) PluginData() pulumi.StringOutput

Data of the current plugin, with the size limited to 65KB.

func (LookupTimeSeriesResultOutput) PluginName 

func (o LookupTimeSeriesResultOutput) PluginName() pulumi.StringOutput

Immutable. Name of the plugin this time series pertain to. Such as Scalar, Tensor, Blob

func (LookupTimeSeriesResultOutput) ToLookupTimeSeriesResultOutput 

func (o LookupTimeSeriesResultOutput) ToLookupTimeSeriesResultOutput() LookupTimeSeriesResultOutput

func (LookupTimeSeriesResultOutput) ToLookupTimeSeriesResultOutputWithContext 

func (o LookupTimeSeriesResultOutput) ToLookupTimeSeriesResultOutputWithContext(ctx context.Context) LookupTimeSeriesResultOutput

func (LookupTimeSeriesResultOutput) UpdateTime 

func (o LookupTimeSeriesResultOutput) UpdateTime() pulumi.StringOutput

Timestamp when this TensorboardTimeSeries was last updated.

func (LookupTimeSeriesResultOutput) ValueType 

func (o LookupTimeSeriesResultOutput) ValueType() pulumi.StringOutput

Immutable. Type of TensorboardTimeSeries value.

type LookupTrainingPipelineArgs 

type LookupTrainingPipelineArgs struct {
	Location           string  `pulumi:"location"`
	Project            *string `pulumi:"project"`
	TrainingPipelineId string  `pulumi:"trainingPipelineId"`
}

type LookupTrainingPipelineOutputArgs 

type LookupTrainingPipelineOutputArgs struct {
	Location           pulumi.StringInput    `pulumi:"location"`
	Project            pulumi.StringPtrInput `pulumi:"project"`
	TrainingPipelineId pulumi.StringInput    `pulumi:"trainingPipelineId"`
}

func (LookupTrainingPipelineOutputArgs) ElementType 

func (LookupTrainingPipelineOutputArgs) ElementType() reflect.Type

type LookupTrainingPipelineResult 

type LookupTrainingPipelineResult struct {
	// Time when the TrainingPipeline was created.
	CreateTime string `pulumi:"createTime"`
	// The user-defined name of this TrainingPipeline.
	DisplayName string `pulumi:"displayName"`
	// Customer-managed encryption key spec for a TrainingPipeline. If set, this TrainingPipeline will be secured by this key. Note: Model trained by this TrainingPipeline is also secured by this key if model_to_upload is not set separately.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponse `pulumi:"encryptionSpec"`
	// Time when the TrainingPipeline entered any of the following states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`, `PIPELINE_STATE_CANCELLED`.
	EndTime string `pulumi:"endTime"`
	// Only populated when the pipeline's state is `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.
	Error GoogleRpcStatusResponse `pulumi:"error"`
	// Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's training_task_definition should make clear whether this config is used and if there are any special requirements on how it should be filled. If nothing about this config is mentioned in the training_task_definition, then it should be assumed that the TrainingPipeline does not depend on this configuration.
	InputDataConfig GoogleCloudAiplatformV1InputDataConfigResponse `pulumi:"inputDataConfig"`
	// The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels map[string]string `pulumi:"labels"`
	// Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen.
	ModelId string `pulumi:"modelId"`
	// Describes the Model that may be uploaded (via ModelService.UploadModel) by this TrainingPipeline. The TrainingPipeline's training_task_definition should make clear whether this Model description should be populated, and if there are any special requirements regarding how it should be filled. If nothing is mentioned in the training_task_definition, then it should be assumed that this field should not be filled and the training task either uploads the Model without a need of this information, or that training task does not support uploading a Model as part of the pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and the trained Model had been uploaded into Vertex AI, then the model_to_upload's resource name is populated. The Model is always uploaded into the Project and Location in which this pipeline is.
	ModelToUpload GoogleCloudAiplatformV1ModelResponse `pulumi:"modelToUpload"`
	// Resource name of the TrainingPipeline.
	Name string `pulumi:"name"`
	// Optional. When specify this field, the `model_to_upload` will not be uploaded as a new model, instead, it will become a new version of this `parent_model`.
	ParentModel string `pulumi:"parentModel"`
	// Time when the TrainingPipeline for the first time entered the `PIPELINE_STATE_RUNNING` state.
	StartTime string `pulumi:"startTime"`
	// The detailed state of the pipeline.
	State string `pulumi:"state"`
	// A Google Cloud Storage path to the YAML file that defines the training task which is responsible for producing the model artifact, and may also include additional auxiliary work. The definition files that can be used here are found in gs://google-cloud-aiplatform/schema/trainingjob/definition/. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	TrainingTaskDefinition string `pulumi:"trainingTaskDefinition"`
	// The training task's parameter(s), as specified in the training_task_definition's `inputs`.
	TrainingTaskInputs interface{} `pulumi:"trainingTaskInputs"`
	// The metadata information as specified in the training_task_definition's `metadata`. This metadata is an auxiliary runtime and final information about the training task. While the pipeline is running this information is populated only at a best effort basis. Only present if the pipeline's training_task_definition contains `metadata` object.
	TrainingTaskMetadata interface{} `pulumi:"trainingTaskMetadata"`
	// Time when the TrainingPipeline was most recently updated.
	UpdateTime string `pulumi:"updateTime"`
}

func LookupTrainingPipeline 

func LookupTrainingPipeline(ctx *pulumi.Context, args *LookupTrainingPipelineArgs, opts ...pulumi.InvokeOption) (*LookupTrainingPipelineResult, error)

Gets a TrainingPipeline.

type LookupTrainingPipelineResultOutput 

type LookupTrainingPipelineResultOutput struct{ *pulumi.OutputState }

func LookupTrainingPipelineOutput 

func LookupTrainingPipelineOutput(ctx *pulumi.Context, args LookupTrainingPipelineOutputArgs, opts ...pulumi.InvokeOption) LookupTrainingPipelineResultOutput

func (LookupTrainingPipelineResultOutput) CreateTime 

func (o LookupTrainingPipelineResultOutput) CreateTime() pulumi.StringOutput

Time when the TrainingPipeline was created.

func (LookupTrainingPipelineResultOutput) DisplayName 

func (o LookupTrainingPipelineResultOutput) DisplayName() pulumi.StringOutput

The user-defined name of this TrainingPipeline.

func (LookupTrainingPipelineResultOutput) ElementType 

func (LookupTrainingPipelineResultOutput) ElementType() reflect.Type

func (LookupTrainingPipelineResultOutput) EncryptionSpec 

func (o LookupTrainingPipelineResultOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a TrainingPipeline. If set, this TrainingPipeline will be secured by this key. Note: Model trained by this TrainingPipeline is also secured by this key if model_to_upload is not set separately.

func (LookupTrainingPipelineResultOutput) EndTime 

func (o LookupTrainingPipelineResultOutput) EndTime() pulumi.StringOutput

Time when the TrainingPipeline entered any of the following states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`, `PIPELINE_STATE_CANCELLED`.

func (LookupTrainingPipelineResultOutput) Error 

func (o LookupTrainingPipelineResultOutput) Error() GoogleRpcStatusResponseOutput

Only populated when the pipeline's state is `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.

func (LookupTrainingPipelineResultOutput) InputDataConfig 

func (o LookupTrainingPipelineResultOutput) InputDataConfig() GoogleCloudAiplatformV1InputDataConfigResponseOutput

Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's training_task_definition should make clear whether this config is used and if there are any special requirements on how it should be filled. If nothing about this config is mentioned in the training_task_definition, then it should be assumed that the TrainingPipeline does not depend on this configuration.

func (LookupTrainingPipelineResultOutput) Labels 

func (o LookupTrainingPipelineResultOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (LookupTrainingPipelineResultOutput) ModelId 

func (o LookupTrainingPipelineResultOutput) ModelId() pulumi.StringOutput

Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen.

func (LookupTrainingPipelineResultOutput) ModelToUpload 

func (o LookupTrainingPipelineResultOutput) ModelToUpload() GoogleCloudAiplatformV1ModelResponseOutput

Describes the Model that may be uploaded (via ModelService.UploadModel) by this TrainingPipeline. The TrainingPipeline's training_task_definition should make clear whether this Model description should be populated, and if there are any special requirements regarding how it should be filled. If nothing is mentioned in the training_task_definition, then it should be assumed that this field should not be filled and the training task either uploads the Model without a need of this information, or that training task does not support uploading a Model as part of the pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and the trained Model had been uploaded into Vertex AI, then the model_to_upload's resource name is populated. The Model is always uploaded into the Project and Location in which this pipeline is.

func (LookupTrainingPipelineResultOutput) Name 

func (o LookupTrainingPipelineResultOutput) Name() pulumi.StringOutput

Resource name of the TrainingPipeline.

func (LookupTrainingPipelineResultOutput) ParentModel 

func (o LookupTrainingPipelineResultOutput) ParentModel() pulumi.StringOutput

Optional. When specify this field, the `model_to_upload` will not be uploaded as a new model, instead, it will become a new version of this `parent_model`.

func (LookupTrainingPipelineResultOutput) StartTime 

func (o LookupTrainingPipelineResultOutput) StartTime() pulumi.StringOutput

Time when the TrainingPipeline for the first time entered the `PIPELINE_STATE_RUNNING` state.

func (LookupTrainingPipelineResultOutput) State 

func (o LookupTrainingPipelineResultOutput) State() pulumi.StringOutput

The detailed state of the pipeline.

func (LookupTrainingPipelineResultOutput) ToLookupTrainingPipelineResultOutput 

func (o LookupTrainingPipelineResultOutput) ToLookupTrainingPipelineResultOutput() LookupTrainingPipelineResultOutput

func (LookupTrainingPipelineResultOutput) ToLookupTrainingPipelineResultOutputWithContext 

func (o LookupTrainingPipelineResultOutput) ToLookupTrainingPipelineResultOutputWithContext(ctx context.Context) LookupTrainingPipelineResultOutput

func (LookupTrainingPipelineResultOutput) TrainingTaskDefinition 

func (o LookupTrainingPipelineResultOutput) TrainingTaskDefinition() pulumi.StringOutput

A Google Cloud Storage path to the YAML file that defines the training task which is responsible for producing the model artifact, and may also include additional auxiliary work. The definition files that can be used here are found in gs://google-cloud-aiplatform/schema/trainingjob/definition/. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (LookupTrainingPipelineResultOutput) TrainingTaskInputs 

func (o LookupTrainingPipelineResultOutput) TrainingTaskInputs() pulumi.AnyOutput

The training task's parameter(s), as specified in the training_task_definition's `inputs`.

func (LookupTrainingPipelineResultOutput) TrainingTaskMetadata 

func (o LookupTrainingPipelineResultOutput) TrainingTaskMetadata() pulumi.AnyOutput

The metadata information as specified in the training_task_definition's `metadata`. This metadata is an auxiliary runtime and final information about the training task. While the pipeline is running this information is populated only at a best effort basis. Only present if the pipeline's training_task_definition contains `metadata` object.

func (LookupTrainingPipelineResultOutput) UpdateTime 

func (o LookupTrainingPipelineResultOutput) UpdateTime() pulumi.StringOutput

Time when the TrainingPipeline was most recently updated.

type LookupTrialArgs 

type LookupTrialArgs struct {
	Location string  `pulumi:"location"`
	Project  *string `pulumi:"project"`
	StudyId  string  `pulumi:"studyId"`
	TrialId  string  `pulumi:"trialId"`
}

type LookupTrialOutputArgs 

type LookupTrialOutputArgs struct {
	Location pulumi.StringInput    `pulumi:"location"`
	Project  pulumi.StringPtrInput `pulumi:"project"`
	StudyId  pulumi.StringInput    `pulumi:"studyId"`
	TrialId  pulumi.StringInput    `pulumi:"trialId"`
}

func (LookupTrialOutputArgs) ElementType 

func (LookupTrialOutputArgs) ElementType() reflect.Type

type LookupTrialResult 

type LookupTrialResult struct {
	// The identifier of the client that originally requested this Trial. Each client is identified by a unique client_id. When a client asks for a suggestion, Vertex AI Vizier will assign it a Trial. The client should evaluate the Trial, complete it, and report back to Vertex AI Vizier. If suggestion is asked again by same client_id before the Trial is completed, the same Trial will be returned. Multiple clients with different client_ids can ask for suggestions simultaneously, each of them will get their own Trial.
	ClientId string `pulumi:"clientId"`
	// The CustomJob name linked to the Trial. It's set for a HyperparameterTuningJob's Trial.
	CustomJob string `pulumi:"customJob"`
	// Time when the Trial's status changed to `SUCCEEDED` or `INFEASIBLE`.
	EndTime string `pulumi:"endTime"`
	// The final measurement containing the objective value.
	FinalMeasurement GoogleCloudAiplatformV1MeasurementResponse `pulumi:"finalMeasurement"`
	// A human readable string describing why the Trial is infeasible. This is set only if Trial state is `INFEASIBLE`.
	InfeasibleReason string `pulumi:"infeasibleReason"`
	// A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_duration). These are used for early stopping computations.
	Measurements []GoogleCloudAiplatformV1MeasurementResponse `pulumi:"measurements"`
	// Resource name of the Trial assigned by the service.
	Name string `pulumi:"name"`
	// The parameters of the Trial.
	Parameters []GoogleCloudAiplatformV1TrialParameterResponse `pulumi:"parameters"`
	// Time when the Trial was started.
	StartTime string `pulumi:"startTime"`
	// The detailed state of the Trial.
	State string `pulumi:"state"`
	// URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a HyperparameterTuningJob and the job's trial_job_spec.enable_web_access field is `true`. The keys are names of each node used for the trial; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.
	WebAccessUris map[string]string `pulumi:"webAccessUris"`
}

func LookupTrial 

func LookupTrial(ctx *pulumi.Context, args *LookupTrialArgs, opts ...pulumi.InvokeOption) (*LookupTrialResult, error)

Gets a Trial.

type LookupTrialResultOutput 

type LookupTrialResultOutput struct{ *pulumi.OutputState }

func LookupTrialOutput 

func LookupTrialOutput(ctx *pulumi.Context, args LookupTrialOutputArgs, opts ...pulumi.InvokeOption) LookupTrialResultOutput

func (LookupTrialResultOutput) ClientId 

func (o LookupTrialResultOutput) ClientId() pulumi.StringOutput

The identifier of the client that originally requested this Trial. Each client is identified by a unique client_id. When a client asks for a suggestion, Vertex AI Vizier will assign it a Trial. The client should evaluate the Trial, complete it, and report back to Vertex AI Vizier. If suggestion is asked again by same client_id before the Trial is completed, the same Trial will be returned. Multiple clients with different client_ids can ask for suggestions simultaneously, each of them will get their own Trial.

func (LookupTrialResultOutput) CustomJob 

func (o LookupTrialResultOutput) CustomJob() pulumi.StringOutput

The CustomJob name linked to the Trial. It's set for a HyperparameterTuningJob's Trial.

func (LookupTrialResultOutput) ElementType 

func (LookupTrialResultOutput) ElementType() reflect.Type

func (LookupTrialResultOutput) EndTime 

func (o LookupTrialResultOutput) EndTime() pulumi.StringOutput

Time when the Trial's status changed to `SUCCEEDED` or `INFEASIBLE`.

func (LookupTrialResultOutput) FinalMeasurement 

func (o LookupTrialResultOutput) FinalMeasurement() GoogleCloudAiplatformV1MeasurementResponseOutput

The final measurement containing the objective value.

func (LookupTrialResultOutput) InfeasibleReason 

func (o LookupTrialResultOutput) InfeasibleReason() pulumi.StringOutput

A human readable string describing why the Trial is infeasible. This is set only if Trial state is `INFEASIBLE`.

func (LookupTrialResultOutput) Measurements 

func (o LookupTrialResultOutput) Measurements() GoogleCloudAiplatformV1MeasurementResponseArrayOutput

A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_duration). These are used for early stopping computations.

func (LookupTrialResultOutput) Name 

func (o LookupTrialResultOutput) Name() pulumi.StringOutput

Resource name of the Trial assigned by the service.

func (LookupTrialResultOutput) Parameters 

func (o LookupTrialResultOutput) Parameters() GoogleCloudAiplatformV1TrialParameterResponseArrayOutput

The parameters of the Trial.

func (LookupTrialResultOutput) StartTime 

func (o LookupTrialResultOutput) StartTime() pulumi.StringOutput

Time when the Trial was started.

func (LookupTrialResultOutput) State 

func (o LookupTrialResultOutput) State() pulumi.StringOutput

The detailed state of the Trial.

func (LookupTrialResultOutput) ToLookupTrialResultOutput 

func (o LookupTrialResultOutput) ToLookupTrialResultOutput() LookupTrialResultOutput

func (LookupTrialResultOutput) ToLookupTrialResultOutputWithContext 

func (o LookupTrialResultOutput) ToLookupTrialResultOutputWithContext(ctx context.Context) LookupTrialResultOutput

func (LookupTrialResultOutput) WebAccessUris 

func (o LookupTrialResultOutput) WebAccessUris() pulumi.StringMapOutput

URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a HyperparameterTuningJob and the job's trial_job_spec.enable_web_access field is `true`. The keys are names of each node used for the trial; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.

type MetadataSchema 

type MetadataSchema struct {
	pulumi.CustomResourceState

	// Timestamp when this MetadataSchema was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Description of the Metadata Schema
	Description pulumi.StringOutput `pulumi:"description"`
	Location    pulumi.StringOutput `pulumi:"location"`
	// The {metadata_schema} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataSchemas in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataSchema.)
	MetadataSchemaId pulumi.StringPtrOutput `pulumi:"metadataSchemaId"`
	MetadataStoreId  pulumi.StringOutput    `pulumi:"metadataStoreId"`
	// The resource name of the MetadataSchema.
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// The raw YAML string representation of the MetadataSchema. The combination of [MetadataSchema.version] and the schema name given by `title` in [MetadataSchema.schema] must be unique within a MetadataStore. The schema is defined as an OpenAPI 3.0.2 [MetadataSchema Object](https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.0.2.md#schemaObject)
	Schema pulumi.StringOutput `pulumi:"schema"`
	// The type of the MetadataSchema. This is a property that identifies which metadata types will use the MetadataSchema.
	SchemaType pulumi.StringOutput `pulumi:"schemaType"`
	// The version of the MetadataSchema. The version's format must match the following regular expression: `^[0-9]+.+.+$`, which would allow to order/compare different versions. Example: 1.0.0, 1.0.1, etc.
	SchemaVersion pulumi.StringOutput `pulumi:"schemaVersion"`
}

Creates a MetadataSchema. Auto-naming is currently not supported for this resource. Note - this resource's API doesn't support deletion. When deleted, the resource will persist on Google Cloud even though it will be deleted from Pulumi state.

func GetMetadataSchema 

func GetMetadataSchema(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *MetadataSchemaState, opts ...pulumi.ResourceOption) (*MetadataSchema, error)

GetMetadataSchema gets an existing MetadataSchema resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewMetadataSchema 

func NewMetadataSchema(ctx *pulumi.Context,
	name string, args *MetadataSchemaArgs, opts ...pulumi.ResourceOption) (*MetadataSchema, error)

NewMetadataSchema registers a new resource with the given unique name, arguments, and options.

func (*MetadataSchema) ElementType 

func (*MetadataSchema) ElementType() reflect.Type

func (*MetadataSchema) ToMetadataSchemaOutput 

func (i *MetadataSchema) ToMetadataSchemaOutput() MetadataSchemaOutput

func (*MetadataSchema) ToMetadataSchemaOutputWithContext 

func (i *MetadataSchema) ToMetadataSchemaOutputWithContext(ctx context.Context) MetadataSchemaOutput

type MetadataSchemaArgs 

type MetadataSchemaArgs struct {
	// Description of the Metadata Schema
	Description pulumi.StringPtrInput
	Location    pulumi.StringPtrInput
	// The {metadata_schema} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataSchemas in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataSchema.)
	MetadataSchemaId pulumi.StringPtrInput
	MetadataStoreId  pulumi.StringInput
	Project          pulumi.StringPtrInput
	// The raw YAML string representation of the MetadataSchema. The combination of [MetadataSchema.version] and the schema name given by `title` in [MetadataSchema.schema] must be unique within a MetadataStore. The schema is defined as an OpenAPI 3.0.2 [MetadataSchema Object](https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.0.2.md#schemaObject)
	Schema pulumi.StringInput
	// The type of the MetadataSchema. This is a property that identifies which metadata types will use the MetadataSchema.
	SchemaType MetadataSchemaSchemaTypePtrInput
	// The version of the MetadataSchema. The version's format must match the following regular expression: `^[0-9]+.+.+$`, which would allow to order/compare different versions. Example: 1.0.0, 1.0.1, etc.
	SchemaVersion pulumi.StringPtrInput
}

The set of arguments for constructing a MetadataSchema resource.

func (MetadataSchemaArgs) ElementType 

func (MetadataSchemaArgs) ElementType() reflect.Type

type MetadataSchemaInput 

type MetadataSchemaInput interface {
	pulumi.Input

	ToMetadataSchemaOutput() MetadataSchemaOutput
	ToMetadataSchemaOutputWithContext(ctx context.Context) MetadataSchemaOutput
}

type MetadataSchemaOutput 

type MetadataSchemaOutput struct{ *pulumi.OutputState }

func (MetadataSchemaOutput) CreateTime 

func (o MetadataSchemaOutput) CreateTime() pulumi.StringOutput

Timestamp when this MetadataSchema was created.

func (MetadataSchemaOutput) Description 

func (o MetadataSchemaOutput) Description() pulumi.StringOutput

Description of the Metadata Schema

func (MetadataSchemaOutput) ElementType 

func (MetadataSchemaOutput) ElementType() reflect.Type

func (MetadataSchemaOutput) Location 

func (o MetadataSchemaOutput) Location() pulumi.StringOutput

func (MetadataSchemaOutput) MetadataSchemaId 

func (o MetadataSchemaOutput) MetadataSchemaId() pulumi.StringPtrOutput

The {metadata_schema} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataSchemas in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataSchema.)

func (MetadataSchemaOutput) MetadataStoreId 

func (o MetadataSchemaOutput) MetadataStoreId() pulumi.StringOutput

func (MetadataSchemaOutput) Name 

func (o MetadataSchemaOutput) Name() pulumi.StringOutput

The resource name of the MetadataSchema.

func (MetadataSchemaOutput) Project 

func (o MetadataSchemaOutput) Project() pulumi.StringOutput

func (MetadataSchemaOutput) Schema 

func (o MetadataSchemaOutput) Schema() pulumi.StringOutput

The raw YAML string representation of the MetadataSchema. The combination of [MetadataSchema.version] and the schema name given by `title` in [MetadataSchema.schema] must be unique within a MetadataStore. The schema is defined as an OpenAPI 3.0.2 [MetadataSchema Object](https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.0.2.md#schemaObject)

func (MetadataSchemaOutput) SchemaType 

func (o MetadataSchemaOutput) SchemaType() pulumi.StringOutput

The type of the MetadataSchema. This is a property that identifies which metadata types will use the MetadataSchema.

func (MetadataSchemaOutput) SchemaVersion 

func (o MetadataSchemaOutput) SchemaVersion() pulumi.StringOutput

The version of the MetadataSchema. The version's format must match the following regular expression: `^[0-9]+.+.+$`, which would allow to order/compare different versions. Example: 1.0.0, 1.0.1, etc.

func (MetadataSchemaOutput) ToMetadataSchemaOutput 

func (o MetadataSchemaOutput) ToMetadataSchemaOutput() MetadataSchemaOutput

func (MetadataSchemaOutput) ToMetadataSchemaOutputWithContext 

func (o MetadataSchemaOutput) ToMetadataSchemaOutputWithContext(ctx context.Context) MetadataSchemaOutput

type MetadataSchemaSchemaType 

type MetadataSchemaSchemaType string

The type of the MetadataSchema. This is a property that identifies which metadata types will use the MetadataSchema.

func (MetadataSchemaSchemaType) ElementType 

func (MetadataSchemaSchemaType) ElementType() reflect.Type

func (MetadataSchemaSchemaType) ToMetadataSchemaSchemaTypeOutput 

func (e MetadataSchemaSchemaType) ToMetadataSchemaSchemaTypeOutput() MetadataSchemaSchemaTypeOutput

func (MetadataSchemaSchemaType) ToMetadataSchemaSchemaTypeOutputWithContext 

func (e MetadataSchemaSchemaType) ToMetadataSchemaSchemaTypeOutputWithContext(ctx context.Context) MetadataSchemaSchemaTypeOutput

func (MetadataSchemaSchemaType) ToMetadataSchemaSchemaTypePtrOutput 

func (e MetadataSchemaSchemaType) ToMetadataSchemaSchemaTypePtrOutput() MetadataSchemaSchemaTypePtrOutput

func (MetadataSchemaSchemaType) ToMetadataSchemaSchemaTypePtrOutputWithContext 

func (e MetadataSchemaSchemaType) ToMetadataSchemaSchemaTypePtrOutputWithContext(ctx context.Context) MetadataSchemaSchemaTypePtrOutput

func (MetadataSchemaSchemaType) ToStringOutput 

func (e MetadataSchemaSchemaType) ToStringOutput() pulumi.StringOutput

func (MetadataSchemaSchemaType) ToStringOutputWithContext 

func (e MetadataSchemaSchemaType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (MetadataSchemaSchemaType) ToStringPtrOutput 

func (e MetadataSchemaSchemaType) ToStringPtrOutput() pulumi.StringPtrOutput

func (MetadataSchemaSchemaType) ToStringPtrOutputWithContext 

func (e MetadataSchemaSchemaType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type MetadataSchemaSchemaTypeInput 

type MetadataSchemaSchemaTypeInput interface {
	pulumi.Input

	ToMetadataSchemaSchemaTypeOutput() MetadataSchemaSchemaTypeOutput
	ToMetadataSchemaSchemaTypeOutputWithContext(context.Context) MetadataSchemaSchemaTypeOutput
}

MetadataSchemaSchemaTypeInput is an input type that accepts MetadataSchemaSchemaTypeArgs and MetadataSchemaSchemaTypeOutput values. You can construct a concrete instance of `MetadataSchemaSchemaTypeInput` via: 

MetadataSchemaSchemaTypeArgs{...}

type MetadataSchemaSchemaTypeOutput 

type MetadataSchemaSchemaTypeOutput struct{ *pulumi.OutputState }

func (MetadataSchemaSchemaTypeOutput) ElementType 

func (MetadataSchemaSchemaTypeOutput) ElementType() reflect.Type

func (MetadataSchemaSchemaTypeOutput) ToMetadataSchemaSchemaTypeOutput 

func (o MetadataSchemaSchemaTypeOutput) ToMetadataSchemaSchemaTypeOutput() MetadataSchemaSchemaTypeOutput

func (MetadataSchemaSchemaTypeOutput) ToMetadataSchemaSchemaTypeOutputWithContext 

func (o MetadataSchemaSchemaTypeOutput) ToMetadataSchemaSchemaTypeOutputWithContext(ctx context.Context) MetadataSchemaSchemaTypeOutput

func (MetadataSchemaSchemaTypeOutput) ToMetadataSchemaSchemaTypePtrOutput 

func (o MetadataSchemaSchemaTypeOutput) ToMetadataSchemaSchemaTypePtrOutput() MetadataSchemaSchemaTypePtrOutput

func (MetadataSchemaSchemaTypeOutput) ToMetadataSchemaSchemaTypePtrOutputWithContext 

func (o MetadataSchemaSchemaTypeOutput) ToMetadataSchemaSchemaTypePtrOutputWithContext(ctx context.Context) MetadataSchemaSchemaTypePtrOutput

func (MetadataSchemaSchemaTypeOutput) ToStringOutput 

func (o MetadataSchemaSchemaTypeOutput) ToStringOutput() pulumi.StringOutput

func (MetadataSchemaSchemaTypeOutput) ToStringOutputWithContext 

func (o MetadataSchemaSchemaTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (MetadataSchemaSchemaTypeOutput) ToStringPtrOutput 

func (o MetadataSchemaSchemaTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (MetadataSchemaSchemaTypeOutput) ToStringPtrOutputWithContext 

func (o MetadataSchemaSchemaTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type MetadataSchemaSchemaTypePtrInput 

type MetadataSchemaSchemaTypePtrInput interface {
	pulumi.Input

	ToMetadataSchemaSchemaTypePtrOutput() MetadataSchemaSchemaTypePtrOutput
	ToMetadataSchemaSchemaTypePtrOutputWithContext(context.Context) MetadataSchemaSchemaTypePtrOutput
}

func MetadataSchemaSchemaTypePtr 

func MetadataSchemaSchemaTypePtr(v string) MetadataSchemaSchemaTypePtrInput

type MetadataSchemaSchemaTypePtrOutput 

type MetadataSchemaSchemaTypePtrOutput struct{ *pulumi.OutputState }

func (MetadataSchemaSchemaTypePtrOutput) Elem 

func (o MetadataSchemaSchemaTypePtrOutput) Elem() MetadataSchemaSchemaTypeOutput

func (MetadataSchemaSchemaTypePtrOutput) ElementType 

func (MetadataSchemaSchemaTypePtrOutput) ElementType() reflect.Type

func (MetadataSchemaSchemaTypePtrOutput) ToMetadataSchemaSchemaTypePtrOutput 

func (o MetadataSchemaSchemaTypePtrOutput) ToMetadataSchemaSchemaTypePtrOutput() MetadataSchemaSchemaTypePtrOutput

func (MetadataSchemaSchemaTypePtrOutput) ToMetadataSchemaSchemaTypePtrOutputWithContext 

func (o MetadataSchemaSchemaTypePtrOutput) ToMetadataSchemaSchemaTypePtrOutputWithContext(ctx context.Context) MetadataSchemaSchemaTypePtrOutput

func (MetadataSchemaSchemaTypePtrOutput) ToStringPtrOutput 

func (o MetadataSchemaSchemaTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (MetadataSchemaSchemaTypePtrOutput) ToStringPtrOutputWithContext 

func (o MetadataSchemaSchemaTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type MetadataSchemaState 

type MetadataSchemaState struct {
}

func (MetadataSchemaState) ElementType 

func (MetadataSchemaState) ElementType() reflect.Type

type MetadataStore 

type MetadataStore struct {
	pulumi.CustomResourceState

	// Timestamp when this MetadataStore was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Description of the MetadataStore.
	Description pulumi.StringOutput `pulumi:"description"`
	// Customer-managed encryption key spec for a Metadata Store. If set, this Metadata Store and all sub-resources of this Metadata Store are secured using this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	Location       pulumi.StringOutput                                 `pulumi:"location"`
	// The {metadatastore} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataStores in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataStore.)
	MetadataStoreId pulumi.StringPtrOutput `pulumi:"metadataStoreId"`
	// The resource name of the MetadataStore instance.
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// State information of the MetadataStore.
	State GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput `pulumi:"state"`
	// Timestamp when this MetadataStore was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Initializes a MetadataStore, including allocation of resources. Auto-naming is currently not supported for this resource.

func GetMetadataStore 

func GetMetadataStore(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *MetadataStoreState, opts ...pulumi.ResourceOption) (*MetadataStore, error)

GetMetadataStore gets an existing MetadataStore resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewMetadataStore 

func NewMetadataStore(ctx *pulumi.Context,
	name string, args *MetadataStoreArgs, opts ...pulumi.ResourceOption) (*MetadataStore, error)

NewMetadataStore registers a new resource with the given unique name, arguments, and options.

func (*MetadataStore) ElementType 

func (*MetadataStore) ElementType() reflect.Type

func (*MetadataStore) ToMetadataStoreOutput 

func (i *MetadataStore) ToMetadataStoreOutput() MetadataStoreOutput

func (*MetadataStore) ToMetadataStoreOutputWithContext 

func (i *MetadataStore) ToMetadataStoreOutputWithContext(ctx context.Context) MetadataStoreOutput

type MetadataStoreArgs 

type MetadataStoreArgs struct {
	// Description of the MetadataStore.
	Description pulumi.StringPtrInput
	// Customer-managed encryption key spec for a Metadata Store. If set, this Metadata Store and all sub-resources of this Metadata Store are secured using this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	Location       pulumi.StringPtrInput
	// The {metadatastore} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataStores in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataStore.)
	MetadataStoreId pulumi.StringPtrInput
	Project         pulumi.StringPtrInput
}

The set of arguments for constructing a MetadataStore resource.

func (MetadataStoreArgs) ElementType 

func (MetadataStoreArgs) ElementType() reflect.Type

type MetadataStoreInput 

type MetadataStoreInput interface {
	pulumi.Input

	ToMetadataStoreOutput() MetadataStoreOutput
	ToMetadataStoreOutputWithContext(ctx context.Context) MetadataStoreOutput
}

type MetadataStoreOutput 

type MetadataStoreOutput struct{ *pulumi.OutputState }

func (MetadataStoreOutput) CreateTime 

func (o MetadataStoreOutput) CreateTime() pulumi.StringOutput

Timestamp when this MetadataStore was created.

func (MetadataStoreOutput) Description 

func (o MetadataStoreOutput) Description() pulumi.StringOutput

Description of the MetadataStore.

func (MetadataStoreOutput) ElementType 

func (MetadataStoreOutput) ElementType() reflect.Type

func (MetadataStoreOutput) EncryptionSpec 

func (o MetadataStoreOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a Metadata Store. If set, this Metadata Store and all sub-resources of this Metadata Store are secured using this key.

func (MetadataStoreOutput) Location 

func (o MetadataStoreOutput) Location() pulumi.StringOutput

func (MetadataStoreOutput) MetadataStoreId 

func (o MetadataStoreOutput) MetadataStoreId() pulumi.StringPtrOutput

The {metadatastore} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataStores in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataStore.)

func (MetadataStoreOutput) Name 

func (o MetadataStoreOutput) Name() pulumi.StringOutput

The resource name of the MetadataStore instance.

func (MetadataStoreOutput) Project 

func (o MetadataStoreOutput) Project() pulumi.StringOutput

func (MetadataStoreOutput) State 

func (o MetadataStoreOutput) State() GoogleCloudAiplatformV1MetadataStoreMetadataStoreStateResponseOutput

State information of the MetadataStore.

func (MetadataStoreOutput) ToMetadataStoreOutput 

func (o MetadataStoreOutput) ToMetadataStoreOutput() MetadataStoreOutput

func (MetadataStoreOutput) ToMetadataStoreOutputWithContext 

func (o MetadataStoreOutput) ToMetadataStoreOutputWithContext(ctx context.Context) MetadataStoreOutput

func (MetadataStoreOutput) UpdateTime 

func (o MetadataStoreOutput) UpdateTime() pulumi.StringOutput

Timestamp when this MetadataStore was last updated.

type MetadataStoreState 

type MetadataStoreState struct {
}

func (MetadataStoreState) ElementType 

func (MetadataStoreState) ElementType() reflect.Type

type ModelDeploymentMonitoringJob 

type ModelDeploymentMonitoringJob struct {
	pulumi.CustomResourceState

	// YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.
	AnalysisInstanceSchemaUri pulumi.StringOutput `pulumi:"analysisInstanceSchemaUri"`
	// The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum: 1. Training data logging predict request/response 2. Serving data logging predict request/response
	BigqueryTables GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput `pulumi:"bigqueryTables"`
	// Timestamp when this ModelDeploymentMonitoringJob was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging#pricing).
	EnableMonitoringPipelineLogs pulumi.BoolOutput `pulumi:"enableMonitoringPipelineLogs"`
	// Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// Endpoint resource name. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
	Endpoint pulumi.StringOutput `pulumi:"endpoint"`
	// Only populated when the job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.
	Error GoogleRpcStatusResponseOutput `pulumi:"error"`
	// The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels pulumi.StringMapOutput `pulumi:"labels"`
	// Latest triggered monitoring pipeline metadata.
	LatestMonitoringPipelineMetadata GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput `pulumi:"latestMonitoringPipelineMetadata"`
	Location                         pulumi.StringOutput                                                                               `pulumi:"location"`
	// The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.
	LogTtl pulumi.StringOutput `pulumi:"logTtl"`
	// Sample Strategy for logging.
	LoggingSamplingStrategy GoogleCloudAiplatformV1SamplingStrategyResponseOutput `pulumi:"loggingSamplingStrategy"`
	// The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.
	ModelDeploymentMonitoringObjectiveConfigs GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput `pulumi:"modelDeploymentMonitoringObjectiveConfigs"`
	// Schedule config for running the monitoring job.
	ModelDeploymentMonitoringScheduleConfig GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput `pulumi:"modelDeploymentMonitoringScheduleConfig"`
	// Alert config for model monitoring.
	ModelMonitoringAlertConfig GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput `pulumi:"modelMonitoringAlertConfig"`
	// Resource name of a ModelDeploymentMonitoringJob.
	Name pulumi.StringOutput `pulumi:"name"`
	// Timestamp when this monitoring pipeline will be scheduled to run for the next round.
	NextScheduleTime pulumi.StringOutput `pulumi:"nextScheduleTime"`
	// YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.
	PredictInstanceSchemaUri pulumi.StringOutput `pulumi:"predictInstanceSchemaUri"`
	Project                  pulumi.StringOutput `pulumi:"project"`
	// Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.
	SamplePredictInstance pulumi.AnyOutput `pulumi:"samplePredictInstance"`
	// Schedule state when the monitoring job is in Running state.
	ScheduleState pulumi.StringOutput `pulumi:"scheduleState"`
	// The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.
	State pulumi.StringOutput `pulumi:"state"`
	// Stats anomalies base folder path.
	StatsAnomaliesBaseDirectory GoogleCloudAiplatformV1GcsDestinationResponseOutput `pulumi:"statsAnomaliesBaseDirectory"`
	// Timestamp when this ModelDeploymentMonitoringJob was updated most recently.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a ModelDeploymentMonitoringJob. It will run periodically on a configured interval. Auto-naming is currently not supported for this resource.

func GetModelDeploymentMonitoringJob 

func GetModelDeploymentMonitoringJob(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *ModelDeploymentMonitoringJobState, opts ...pulumi.ResourceOption) (*ModelDeploymentMonitoringJob, error)

GetModelDeploymentMonitoringJob gets an existing ModelDeploymentMonitoringJob resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewModelDeploymentMonitoringJob 

func NewModelDeploymentMonitoringJob(ctx *pulumi.Context,
	name string, args *ModelDeploymentMonitoringJobArgs, opts ...pulumi.ResourceOption) (*ModelDeploymentMonitoringJob, error)

NewModelDeploymentMonitoringJob registers a new resource with the given unique name, arguments, and options.

func (*ModelDeploymentMonitoringJob) ElementType 

func (*ModelDeploymentMonitoringJob) ElementType() reflect.Type

func (*ModelDeploymentMonitoringJob) ToModelDeploymentMonitoringJobOutput 

func (i *ModelDeploymentMonitoringJob) ToModelDeploymentMonitoringJobOutput() ModelDeploymentMonitoringJobOutput

func (*ModelDeploymentMonitoringJob) ToModelDeploymentMonitoringJobOutputWithContext 

func (i *ModelDeploymentMonitoringJob) ToModelDeploymentMonitoringJobOutputWithContext(ctx context.Context) ModelDeploymentMonitoringJobOutput

type ModelDeploymentMonitoringJobArgs 

type ModelDeploymentMonitoringJobArgs struct {
	// YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.
	AnalysisInstanceSchemaUri pulumi.StringPtrInput
	// The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.
	DisplayName pulumi.StringInput
	// If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging#pricing).
	EnableMonitoringPipelineLogs pulumi.BoolPtrInput
	// Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// Endpoint resource name. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
	Endpoint pulumi.StringInput
	// The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.
	LogTtl pulumi.StringPtrInput
	// Sample Strategy for logging.
	LoggingSamplingStrategy GoogleCloudAiplatformV1SamplingStrategyInput
	// The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.
	ModelDeploymentMonitoringObjectiveConfigs GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigArrayInput
	// Schedule config for running the monitoring job.
	ModelDeploymentMonitoringScheduleConfig GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigInput
	// Alert config for model monitoring.
	ModelMonitoringAlertConfig GoogleCloudAiplatformV1ModelMonitoringAlertConfigPtrInput
	// YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.
	PredictInstanceSchemaUri pulumi.StringPtrInput
	Project                  pulumi.StringPtrInput
	// Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.
	SamplePredictInstance pulumi.Input
	// Stats anomalies base folder path.
	StatsAnomaliesBaseDirectory GoogleCloudAiplatformV1GcsDestinationPtrInput
}

The set of arguments for constructing a ModelDeploymentMonitoringJob resource.

func (ModelDeploymentMonitoringJobArgs) ElementType 

func (ModelDeploymentMonitoringJobArgs) ElementType() reflect.Type

type ModelDeploymentMonitoringJobInput 

type ModelDeploymentMonitoringJobInput interface {
	pulumi.Input

	ToModelDeploymentMonitoringJobOutput() ModelDeploymentMonitoringJobOutput
	ToModelDeploymentMonitoringJobOutputWithContext(ctx context.Context) ModelDeploymentMonitoringJobOutput
}

type ModelDeploymentMonitoringJobOutput 

type ModelDeploymentMonitoringJobOutput struct{ *pulumi.OutputState }

func (ModelDeploymentMonitoringJobOutput) AnalysisInstanceSchemaUri 

func (o ModelDeploymentMonitoringJobOutput) AnalysisInstanceSchemaUri() pulumi.StringOutput

YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.

func (ModelDeploymentMonitoringJobOutput) BigqueryTables 

func (o ModelDeploymentMonitoringJobOutput) BigqueryTables() GoogleCloudAiplatformV1ModelDeploymentMonitoringBigQueryTableResponseArrayOutput

The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum: 1. Training data logging predict request/response 2. Serving data logging predict request/response

func (ModelDeploymentMonitoringJobOutput) CreateTime 

func (o ModelDeploymentMonitoringJobOutput) CreateTime() pulumi.StringOutput

Timestamp when this ModelDeploymentMonitoringJob was created.

func (ModelDeploymentMonitoringJobOutput) DisplayName 

func (o ModelDeploymentMonitoringJobOutput) DisplayName() pulumi.StringOutput

The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.

func (ModelDeploymentMonitoringJobOutput) ElementType 

func (ModelDeploymentMonitoringJobOutput) ElementType() reflect.Type

func (ModelDeploymentMonitoringJobOutput) EnableMonitoringPipelineLogs 

func (o ModelDeploymentMonitoringJobOutput) EnableMonitoringPipelineLogs() pulumi.BoolOutput

If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging#pricing).

func (ModelDeploymentMonitoringJobOutput) EncryptionSpec 

func (o ModelDeploymentMonitoringJobOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.

func (ModelDeploymentMonitoringJobOutput) Endpoint 

func (o ModelDeploymentMonitoringJobOutput) Endpoint() pulumi.StringOutput

Endpoint resource name. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`

func (ModelDeploymentMonitoringJobOutput) Error 

func (o ModelDeploymentMonitoringJobOutput) Error() GoogleRpcStatusResponseOutput

Only populated when the job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`.

func (ModelDeploymentMonitoringJobOutput) Labels 

func (o ModelDeploymentMonitoringJobOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (ModelDeploymentMonitoringJobOutput) LatestMonitoringPipelineMetadata 

func (o ModelDeploymentMonitoringJobOutput) LatestMonitoringPipelineMetadata() GoogleCloudAiplatformV1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadataResponseOutput

Latest triggered monitoring pipeline metadata.

func (ModelDeploymentMonitoringJobOutput) Location 

func (o ModelDeploymentMonitoringJobOutput) Location() pulumi.StringOutput

func (ModelDeploymentMonitoringJobOutput) LogTtl 

func (o ModelDeploymentMonitoringJobOutput) LogTtl() pulumi.StringOutput

The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.

func (ModelDeploymentMonitoringJobOutput) LoggingSamplingStrategy 

func (o ModelDeploymentMonitoringJobOutput) LoggingSamplingStrategy() GoogleCloudAiplatformV1SamplingStrategyResponseOutput

Sample Strategy for logging.

func (ModelDeploymentMonitoringJobOutput) ModelDeploymentMonitoringObjectiveConfigs 

func (o ModelDeploymentMonitoringJobOutput) ModelDeploymentMonitoringObjectiveConfigs() GoogleCloudAiplatformV1ModelDeploymentMonitoringObjectiveConfigResponseArrayOutput

The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

func (ModelDeploymentMonitoringJobOutput) ModelDeploymentMonitoringScheduleConfig 

func (o ModelDeploymentMonitoringJobOutput) ModelDeploymentMonitoringScheduleConfig() GoogleCloudAiplatformV1ModelDeploymentMonitoringScheduleConfigResponseOutput

Schedule config for running the monitoring job.

func (ModelDeploymentMonitoringJobOutput) ModelMonitoringAlertConfig 

func (o ModelDeploymentMonitoringJobOutput) ModelMonitoringAlertConfig() GoogleCloudAiplatformV1ModelMonitoringAlertConfigResponseOutput

Alert config for model monitoring.

func (ModelDeploymentMonitoringJobOutput) Name 

func (o ModelDeploymentMonitoringJobOutput) Name() pulumi.StringOutput

Resource name of a ModelDeploymentMonitoringJob.

func (ModelDeploymentMonitoringJobOutput) NextScheduleTime 

func (o ModelDeploymentMonitoringJobOutput) NextScheduleTime() pulumi.StringOutput

Timestamp when this monitoring pipeline will be scheduled to run for the next round.

func (ModelDeploymentMonitoringJobOutput) PredictInstanceSchemaUri 

func (o ModelDeploymentMonitoringJobOutput) PredictInstanceSchemaUri() pulumi.StringOutput

YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.

func (ModelDeploymentMonitoringJobOutput) Project 

func (o ModelDeploymentMonitoringJobOutput) Project() pulumi.StringOutput

func (ModelDeploymentMonitoringJobOutput) SamplePredictInstance 

func (o ModelDeploymentMonitoringJobOutput) SamplePredictInstance() pulumi.AnyOutput

Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.

func (ModelDeploymentMonitoringJobOutput) ScheduleState 

func (o ModelDeploymentMonitoringJobOutput) ScheduleState() pulumi.StringOutput

Schedule state when the monitoring job is in Running state.

func (ModelDeploymentMonitoringJobOutput) State 

func (o ModelDeploymentMonitoringJobOutput) State() pulumi.StringOutput

The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.

func (ModelDeploymentMonitoringJobOutput) StatsAnomaliesBaseDirectory 

func (o ModelDeploymentMonitoringJobOutput) StatsAnomaliesBaseDirectory() GoogleCloudAiplatformV1GcsDestinationResponseOutput

Stats anomalies base folder path.

func (ModelDeploymentMonitoringJobOutput) ToModelDeploymentMonitoringJobOutput 

func (o ModelDeploymentMonitoringJobOutput) ToModelDeploymentMonitoringJobOutput() ModelDeploymentMonitoringJobOutput

func (ModelDeploymentMonitoringJobOutput) ToModelDeploymentMonitoringJobOutputWithContext 

func (o ModelDeploymentMonitoringJobOutput) ToModelDeploymentMonitoringJobOutputWithContext(ctx context.Context) ModelDeploymentMonitoringJobOutput

func (ModelDeploymentMonitoringJobOutput) UpdateTime 

func (o ModelDeploymentMonitoringJobOutput) UpdateTime() pulumi.StringOutput

Timestamp when this ModelDeploymentMonitoringJob was updated most recently.

type ModelDeploymentMonitoringJobState 

type ModelDeploymentMonitoringJobState struct {
}

func (ModelDeploymentMonitoringJobState) ElementType 

func (ModelDeploymentMonitoringJobState) ElementType() reflect.Type

type NasJob 

type NasJob struct {
	pulumi.CustomResourceState

	// Time when the NasJob was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Optional. Enable a separation of Custom model training and restricted image training for tenant project.
	EnableRestrictedImageTraining pulumi.BoolOutput `pulumi:"enableRestrictedImageTraining"`
	// Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// Time when the NasJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
	EndTime pulumi.StringOutput `pulumi:"endTime"`
	// Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
	Error GoogleRpcStatusResponseOutput `pulumi:"error"`
	// The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Resource name of the NasJob.
	Name pulumi.StringOutput `pulumi:"name"`
	// Output of the NasJob.
	NasJobOutput GoogleCloudAiplatformV1NasJobOutputResponseOutput `pulumi:"nasJobOutput"`
	// The specification of a NasJob.
	NasJobSpec GoogleCloudAiplatformV1NasJobSpecResponseOutput `pulumi:"nasJobSpec"`
	Project    pulumi.StringOutput                             `pulumi:"project"`
	// Time when the NasJob for the first time entered the `JOB_STATE_RUNNING` state.
	StartTime pulumi.StringOutput `pulumi:"startTime"`
	// The detailed state of the job.
	State pulumi.StringOutput `pulumi:"state"`
	// Time when the NasJob was most recently updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a NasJob Auto-naming is currently not supported for this resource.

func GetNasJob 

func GetNasJob(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *NasJobState, opts ...pulumi.ResourceOption) (*NasJob, error)

GetNasJob gets an existing NasJob resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewNasJob 

func NewNasJob(ctx *pulumi.Context,
	name string, args *NasJobArgs, opts ...pulumi.ResourceOption) (*NasJob, error)

NewNasJob registers a new resource with the given unique name, arguments, and options.

func (*NasJob) ElementType 

func (*NasJob) ElementType() reflect.Type

func (*NasJob) ToNasJobOutput 

func (i *NasJob) ToNasJobOutput() NasJobOutput

func (*NasJob) ToNasJobOutputWithContext 

func (i *NasJob) ToNasJobOutputWithContext(ctx context.Context) NasJobOutput

type NasJobArgs 

type NasJobArgs struct {
	// The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringInput
	// Optional. Enable a separation of Custom model training and restricted image training for tenant project.
	EnableRestrictedImageTraining pulumi.BoolPtrInput
	// Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// The specification of a NasJob.
	NasJobSpec GoogleCloudAiplatformV1NasJobSpecInput
	Project    pulumi.StringPtrInput
}

The set of arguments for constructing a NasJob resource.

func (NasJobArgs) ElementType 

func (NasJobArgs) ElementType() reflect.Type

type NasJobInput 

type NasJobInput interface {
	pulumi.Input

	ToNasJobOutput() NasJobOutput
	ToNasJobOutputWithContext(ctx context.Context) NasJobOutput
}

type NasJobOutput 

type NasJobOutput struct{ *pulumi.OutputState }

func (NasJobOutput) CreateTime 

func (o NasJobOutput) CreateTime() pulumi.StringOutput

Time when the NasJob was created.

func (NasJobOutput) DisplayName 

func (o NasJobOutput) DisplayName() pulumi.StringOutput

The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (NasJobOutput) ElementType 

func (NasJobOutput) ElementType() reflect.Type

func (NasJobOutput) EnableRestrictedImageTraining 

func (o NasJobOutput) EnableRestrictedImageTraining() pulumi.BoolOutput

Optional. Enable a separation of Custom model training and restricted image training for tenant project.

func (NasJobOutput) EncryptionSpec 

func (o NasJobOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key.

func (NasJobOutput) EndTime 

func (o NasJobOutput) EndTime() pulumi.StringOutput

Time when the NasJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.

func (NasJobOutput) Error 

func (o NasJobOutput) Error() GoogleRpcStatusResponseOutput

Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

func (NasJobOutput) Labels 

func (o NasJobOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (NasJobOutput) Location 

func (o NasJobOutput) Location() pulumi.StringOutput

func (NasJobOutput) Name 

func (o NasJobOutput) Name() pulumi.StringOutput

Resource name of the NasJob.

func (NasJobOutput) NasJobOutput 

func (o NasJobOutput) NasJobOutput() GoogleCloudAiplatformV1NasJobOutputResponseOutput

Output of the NasJob.

func (NasJobOutput) NasJobSpec 

func (o NasJobOutput) NasJobSpec() GoogleCloudAiplatformV1NasJobSpecResponseOutput

The specification of a NasJob.

func (NasJobOutput) Project 

func (o NasJobOutput) Project() pulumi.StringOutput

func (NasJobOutput) StartTime 

func (o NasJobOutput) StartTime() pulumi.StringOutput

Time when the NasJob for the first time entered the `JOB_STATE_RUNNING` state.

func (NasJobOutput) State 

func (o NasJobOutput) State() pulumi.StringOutput

The detailed state of the job.

func (NasJobOutput) ToNasJobOutput 

func (o NasJobOutput) ToNasJobOutput() NasJobOutput

func (NasJobOutput) ToNasJobOutputWithContext 

func (o NasJobOutput) ToNasJobOutputWithContext(ctx context.Context) NasJobOutput

func (NasJobOutput) UpdateTime 

func (o NasJobOutput) UpdateTime() pulumi.StringOutput

Time when the NasJob was most recently updated.

type NasJobState 

type NasJobState struct {
}

func (NasJobState) ElementType 

func (NasJobState) ElementType() reflect.Type

type NotebookRuntimeTemplate 

type NotebookRuntimeTemplate struct {
	pulumi.CustomResourceState

	// Timestamp when this NotebookRuntimeTemplate was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Optional. The specification of persistent disk attached to the runtime as data disk storage.
	DataPersistentDiskSpec GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput `pulumi:"dataPersistentDiskSpec"`
	// The description of the NotebookRuntimeTemplate.
	Description pulumi.StringOutput `pulumi:"description"`
	// The display name of the NotebookRuntimeTemplate. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// EUC configuration of the NotebookRuntimeTemplate.
	EucConfig GoogleCloudAiplatformV1NotebookEucConfigResponseOutput `pulumi:"eucConfig"`
	// The idle shutdown configuration of NotebookRuntimeTemplate. This config will only be set when idle shutdown is enabled.
	IdleShutdownConfig GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput `pulumi:"idleShutdownConfig"`
	// The default template to use if not specified.
	IsDefault pulumi.BoolOutput `pulumi:"isDefault"`
	// The labels with user-defined metadata to organize the NotebookRuntimeTemplates. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Optional. Immutable. The specification of a single machine for the template.
	MachineSpec GoogleCloudAiplatformV1MachineSpecResponseOutput `pulumi:"machineSpec"`
	// The resource name of the NotebookRuntimeTemplate.
	Name pulumi.StringOutput `pulumi:"name"`
	// Optional. Network spec.
	NetworkSpec GoogleCloudAiplatformV1NetworkSpecResponseOutput `pulumi:"networkSpec"`
	// Optional. User specified ID for the notebook runtime template.
	NotebookRuntimeTemplateId pulumi.StringPtrOutput `pulumi:"notebookRuntimeTemplateId"`
	// Optional. Immutable. The type of the notebook runtime template.
	NotebookRuntimeType pulumi.StringOutput `pulumi:"notebookRuntimeType"`
	Project             pulumi.StringOutput `pulumi:"project"`
	// The service account that the runtime workload runs as. You can use any service account within the same project, but you must have the service account user permission to use the instance. If not specified, the [Compute Engine default service account](https://cloud.google.com/compute/docs/access/service-accounts#default_service_account) is used.
	ServiceAccount pulumi.StringOutput `pulumi:"serviceAccount"`
	// Timestamp when this NotebookRuntimeTemplate was most recently updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a NotebookRuntimeTemplate. Auto-naming is currently not supported for this resource.

func GetNotebookRuntimeTemplate 

func GetNotebookRuntimeTemplate(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *NotebookRuntimeTemplateState, opts ...pulumi.ResourceOption) (*NotebookRuntimeTemplate, error)

GetNotebookRuntimeTemplate gets an existing NotebookRuntimeTemplate resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewNotebookRuntimeTemplate 

func NewNotebookRuntimeTemplate(ctx *pulumi.Context,
	name string, args *NotebookRuntimeTemplateArgs, opts ...pulumi.ResourceOption) (*NotebookRuntimeTemplate, error)

NewNotebookRuntimeTemplate registers a new resource with the given unique name, arguments, and options.

func (*NotebookRuntimeTemplate) ElementType 

func (*NotebookRuntimeTemplate) ElementType() reflect.Type

func (*NotebookRuntimeTemplate) ToNotebookRuntimeTemplateOutput 

func (i *NotebookRuntimeTemplate) ToNotebookRuntimeTemplateOutput() NotebookRuntimeTemplateOutput

func (*NotebookRuntimeTemplate) ToNotebookRuntimeTemplateOutputWithContext 

func (i *NotebookRuntimeTemplate) ToNotebookRuntimeTemplateOutputWithContext(ctx context.Context) NotebookRuntimeTemplateOutput

type NotebookRuntimeTemplateArgs 

type NotebookRuntimeTemplateArgs struct {
	// Optional. The specification of persistent disk attached to the runtime as data disk storage.
	DataPersistentDiskSpec GoogleCloudAiplatformV1PersistentDiskSpecPtrInput
	// The description of the NotebookRuntimeTemplate.
	Description pulumi.StringPtrInput
	// The display name of the NotebookRuntimeTemplate. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringInput
	// Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// EUC configuration of the NotebookRuntimeTemplate.
	EucConfig GoogleCloudAiplatformV1NotebookEucConfigPtrInput
	// The idle shutdown configuration of NotebookRuntimeTemplate. This config will only be set when idle shutdown is enabled.
	IdleShutdownConfig GoogleCloudAiplatformV1NotebookIdleShutdownConfigPtrInput
	// The labels with user-defined metadata to organize the NotebookRuntimeTemplates. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// Optional. Immutable. The specification of a single machine for the template.
	MachineSpec GoogleCloudAiplatformV1MachineSpecPtrInput
	// Optional. Network spec.
	NetworkSpec GoogleCloudAiplatformV1NetworkSpecPtrInput
	// Optional. User specified ID for the notebook runtime template.
	NotebookRuntimeTemplateId pulumi.StringPtrInput
	// Optional. Immutable. The type of the notebook runtime template.
	NotebookRuntimeType NotebookRuntimeTemplateNotebookRuntimeTypePtrInput
	Project             pulumi.StringPtrInput
	// The service account that the runtime workload runs as. You can use any service account within the same project, but you must have the service account user permission to use the instance. If not specified, the [Compute Engine default service account](https://cloud.google.com/compute/docs/access/service-accounts#default_service_account) is used.
	ServiceAccount pulumi.StringPtrInput
}

The set of arguments for constructing a NotebookRuntimeTemplate resource.

func (NotebookRuntimeTemplateArgs) ElementType 

func (NotebookRuntimeTemplateArgs) ElementType() reflect.Type

type NotebookRuntimeTemplateIamBinding 

type NotebookRuntimeTemplateIamBinding struct {
	pulumi.CustomResourceState

	// An IAM Condition for a given binding. See https://cloud.google.com/iam/docs/conditions-overview for additional details.
	Condition iam.ConditionPtrOutput `pulumi:"condition"`
	// The etag of the resource's IAM policy.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Identities that will be granted the privilege in role. Each entry can have one of the following values:
	//
	//  * user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
	//  * serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
	//  * group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
	//  * domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
	Members pulumi.StringArrayOutput `pulumi:"members"`
	// The name of the resource to manage IAM policies for.
	Name pulumi.StringOutput `pulumi:"name"`
	// The project in which the resource belongs. If it is not provided, a default will be supplied.
	Project pulumi.StringOutput `pulumi:"project"`
	// The role that should be applied. Only one `IamBinding` can be used per role.
	Role pulumi.StringOutput `pulumi:"role"`
}

Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.

func GetNotebookRuntimeTemplateIamBinding 

func GetNotebookRuntimeTemplateIamBinding(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *NotebookRuntimeTemplateIamBindingState, opts ...pulumi.ResourceOption) (*NotebookRuntimeTemplateIamBinding, error)

GetNotebookRuntimeTemplateIamBinding gets an existing NotebookRuntimeTemplateIamBinding resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewNotebookRuntimeTemplateIamBinding 

func NewNotebookRuntimeTemplateIamBinding(ctx *pulumi.Context,
	name string, args *NotebookRuntimeTemplateIamBindingArgs, opts ...pulumi.ResourceOption) (*NotebookRuntimeTemplateIamBinding, error)

NewNotebookRuntimeTemplateIamBinding registers a new resource with the given unique name, arguments, and options.

func (*NotebookRuntimeTemplateIamBinding) ElementType 

func (*NotebookRuntimeTemplateIamBinding) ElementType() reflect.Type

func (*NotebookRuntimeTemplateIamBinding) ToNotebookRuntimeTemplateIamBindingOutput 

func (i *NotebookRuntimeTemplateIamBinding) ToNotebookRuntimeTemplateIamBindingOutput() NotebookRuntimeTemplateIamBindingOutput

func (*NotebookRuntimeTemplateIamBinding) ToNotebookRuntimeTemplateIamBindingOutputWithContext 

func (i *NotebookRuntimeTemplateIamBinding) ToNotebookRuntimeTemplateIamBindingOutputWithContext(ctx context.Context) NotebookRuntimeTemplateIamBindingOutput

type NotebookRuntimeTemplateIamBindingArgs 

type NotebookRuntimeTemplateIamBindingArgs struct {
	// An IAM Condition for a given binding.
	Condition iam.ConditionPtrInput
	// Identities that will be granted the privilege in role. Each entry can have one of the following values:
	//
	//  * user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
	//  * serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
	//  * group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
	//  * domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
	Members pulumi.StringArrayInput
	// The name of the resource to manage IAM policies for.
	Name pulumi.StringInput
	// The role that should be applied. Only one `IamBinding` can be used per role.
	Role pulumi.StringInput
}

The set of arguments for constructing a NotebookRuntimeTemplateIamBinding resource.

func (NotebookRuntimeTemplateIamBindingArgs) ElementType 

func (NotebookRuntimeTemplateIamBindingArgs) ElementType() reflect.Type

type NotebookRuntimeTemplateIamBindingInput 

type NotebookRuntimeTemplateIamBindingInput interface {
	pulumi.Input

	ToNotebookRuntimeTemplateIamBindingOutput() NotebookRuntimeTemplateIamBindingOutput
	ToNotebookRuntimeTemplateIamBindingOutputWithContext(ctx context.Context) NotebookRuntimeTemplateIamBindingOutput
}

type NotebookRuntimeTemplateIamBindingOutput 

type NotebookRuntimeTemplateIamBindingOutput struct{ *pulumi.OutputState }

func (NotebookRuntimeTemplateIamBindingOutput) Condition 

func (o NotebookRuntimeTemplateIamBindingOutput) Condition() iam.ConditionPtrOutput

An IAM Condition for a given binding. See https://cloud.google.com/iam/docs/conditions-overview for additional details.

func (NotebookRuntimeTemplateIamBindingOutput) ElementType 

func (NotebookRuntimeTemplateIamBindingOutput) ElementType() reflect.Type

func (NotebookRuntimeTemplateIamBindingOutput) Etag 

func (o NotebookRuntimeTemplateIamBindingOutput) Etag() pulumi.StringOutput

The etag of the resource's IAM policy.

func (NotebookRuntimeTemplateIamBindingOutput) Members 

func (o NotebookRuntimeTemplateIamBindingOutput) Members() pulumi.StringArrayOutput

Identities that will be granted the privilege in role. Each entry can have one of the following values:

  • user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
  • serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
  • group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
  • domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.

func (NotebookRuntimeTemplateIamBindingOutput) Name 

func (o NotebookRuntimeTemplateIamBindingOutput) Name() pulumi.StringOutput

The name of the resource to manage IAM policies for.

func (NotebookRuntimeTemplateIamBindingOutput) Project 

func (o NotebookRuntimeTemplateIamBindingOutput) Project() pulumi.StringOutput

The project in which the resource belongs. If it is not provided, a default will be supplied.

func (NotebookRuntimeTemplateIamBindingOutput) Role 

func (o NotebookRuntimeTemplateIamBindingOutput) Role() pulumi.StringOutput

The role that should be applied. Only one `IamBinding` can be used per role.

func (NotebookRuntimeTemplateIamBindingOutput) ToNotebookRuntimeTemplateIamBindingOutput 

func (o NotebookRuntimeTemplateIamBindingOutput) ToNotebookRuntimeTemplateIamBindingOutput() NotebookRuntimeTemplateIamBindingOutput

func (NotebookRuntimeTemplateIamBindingOutput) ToNotebookRuntimeTemplateIamBindingOutputWithContext 

func (o NotebookRuntimeTemplateIamBindingOutput) ToNotebookRuntimeTemplateIamBindingOutputWithContext(ctx context.Context) NotebookRuntimeTemplateIamBindingOutput

type NotebookRuntimeTemplateIamBindingState 

type NotebookRuntimeTemplateIamBindingState struct {
}

func (NotebookRuntimeTemplateIamBindingState) ElementType 

func (NotebookRuntimeTemplateIamBindingState) ElementType() reflect.Type

type NotebookRuntimeTemplateIamMember 

type NotebookRuntimeTemplateIamMember struct {
	pulumi.CustomResourceState

	// An IAM Condition for a given binding. See https://cloud.google.com/iam/docs/conditions-overview for additional details.
	Condition iam.ConditionPtrOutput `pulumi:"condition"`
	// The etag of the resource's IAM policy.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Identity that will be granted the privilege in role. The entry can have one of the following values:
	//
	//  * user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
	//  * serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
	//  * group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
	//  * domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
	Member pulumi.StringOutput `pulumi:"member"`
	// The name of the resource to manage IAM policies for.
	Name pulumi.StringOutput `pulumi:"name"`
	// The project in which the resource belongs. If it is not provided, a default will be supplied.
	Project pulumi.StringOutput `pulumi:"project"`
	// The role that should be applied.
	Role pulumi.StringOutput `pulumi:"role"`
}

Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.

func GetNotebookRuntimeTemplateIamMember 

func GetNotebookRuntimeTemplateIamMember(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *NotebookRuntimeTemplateIamMemberState, opts ...pulumi.ResourceOption) (*NotebookRuntimeTemplateIamMember, error)

GetNotebookRuntimeTemplateIamMember gets an existing NotebookRuntimeTemplateIamMember resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewNotebookRuntimeTemplateIamMember 

func NewNotebookRuntimeTemplateIamMember(ctx *pulumi.Context,
	name string, args *NotebookRuntimeTemplateIamMemberArgs, opts ...pulumi.ResourceOption) (*NotebookRuntimeTemplateIamMember, error)

NewNotebookRuntimeTemplateIamMember registers a new resource with the given unique name, arguments, and options.

func (*NotebookRuntimeTemplateIamMember) ElementType 

func (*NotebookRuntimeTemplateIamMember) ElementType() reflect.Type

func (*NotebookRuntimeTemplateIamMember) ToNotebookRuntimeTemplateIamMemberOutput 

func (i *NotebookRuntimeTemplateIamMember) ToNotebookRuntimeTemplateIamMemberOutput() NotebookRuntimeTemplateIamMemberOutput

func (*NotebookRuntimeTemplateIamMember) ToNotebookRuntimeTemplateIamMemberOutputWithContext 

func (i *NotebookRuntimeTemplateIamMember) ToNotebookRuntimeTemplateIamMemberOutputWithContext(ctx context.Context) NotebookRuntimeTemplateIamMemberOutput

type NotebookRuntimeTemplateIamMemberArgs 

type NotebookRuntimeTemplateIamMemberArgs struct {
	// An IAM Condition for a given binding.
	Condition iam.ConditionPtrInput
	// Identity that will be granted the privilege in role. The entry can have one of the following values:
	//
	//  * user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
	//  * serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
	//  * group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
	//  * domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
	Member pulumi.StringInput
	// The name of the resource to manage IAM policies for.
	Name pulumi.StringInput
	// The role that should be applied.
	Role pulumi.StringInput
}

The set of arguments for constructing a NotebookRuntimeTemplateIamMember resource.

func (NotebookRuntimeTemplateIamMemberArgs) ElementType 

func (NotebookRuntimeTemplateIamMemberArgs) ElementType() reflect.Type

type NotebookRuntimeTemplateIamMemberInput 

type NotebookRuntimeTemplateIamMemberInput interface {
	pulumi.Input

	ToNotebookRuntimeTemplateIamMemberOutput() NotebookRuntimeTemplateIamMemberOutput
	ToNotebookRuntimeTemplateIamMemberOutputWithContext(ctx context.Context) NotebookRuntimeTemplateIamMemberOutput
}

type NotebookRuntimeTemplateIamMemberOutput 

type NotebookRuntimeTemplateIamMemberOutput struct{ *pulumi.OutputState }

func (NotebookRuntimeTemplateIamMemberOutput) Condition 

func (o NotebookRuntimeTemplateIamMemberOutput) Condition() iam.ConditionPtrOutput

An IAM Condition for a given binding. See https://cloud.google.com/iam/docs/conditions-overview for additional details.

func (NotebookRuntimeTemplateIamMemberOutput) ElementType 

func (NotebookRuntimeTemplateIamMemberOutput) ElementType() reflect.Type

func (NotebookRuntimeTemplateIamMemberOutput) Etag 

func (o NotebookRuntimeTemplateIamMemberOutput) Etag() pulumi.StringOutput

The etag of the resource's IAM policy.

func (NotebookRuntimeTemplateIamMemberOutput) Member 

func (o NotebookRuntimeTemplateIamMemberOutput) Member() pulumi.StringOutput

Identity that will be granted the privilege in role. The entry can have one of the following values:

  • user:{emailid}: An email address that represents a specific Google account. For example, alice@gmail.com or joe@example.com.
  • serviceAccount:{emailid}: An email address that represents a service account. For example, my-other-app@appspot.gserviceaccount.com.
  • group:{emailid}: An email address that represents a Google group. For example, admins@example.com.
  • domain:{domain}: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.

func (NotebookRuntimeTemplateIamMemberOutput) Name 

func (o NotebookRuntimeTemplateIamMemberOutput) Name() pulumi.StringOutput

The name of the resource to manage IAM policies for.

func (NotebookRuntimeTemplateIamMemberOutput) Project 

func (o NotebookRuntimeTemplateIamMemberOutput) Project() pulumi.StringOutput

The project in which the resource belongs. If it is not provided, a default will be supplied.

func (NotebookRuntimeTemplateIamMemberOutput) Role 

func (o NotebookRuntimeTemplateIamMemberOutput) Role() pulumi.StringOutput

The role that should be applied.

func (NotebookRuntimeTemplateIamMemberOutput) ToNotebookRuntimeTemplateIamMemberOutput 

func (o NotebookRuntimeTemplateIamMemberOutput) ToNotebookRuntimeTemplateIamMemberOutput() NotebookRuntimeTemplateIamMemberOutput

func (NotebookRuntimeTemplateIamMemberOutput) ToNotebookRuntimeTemplateIamMemberOutputWithContext 

func (o NotebookRuntimeTemplateIamMemberOutput) ToNotebookRuntimeTemplateIamMemberOutputWithContext(ctx context.Context) NotebookRuntimeTemplateIamMemberOutput

type NotebookRuntimeTemplateIamMemberState 

type NotebookRuntimeTemplateIamMemberState struct {
}

func (NotebookRuntimeTemplateIamMemberState) ElementType 

func (NotebookRuntimeTemplateIamMemberState) ElementType() reflect.Type

type NotebookRuntimeTemplateIamPolicy 

type NotebookRuntimeTemplateIamPolicy struct {
	pulumi.CustomResourceState

	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings GoogleIamV1BindingResponseArrayOutput `pulumi:"bindings"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag                      pulumi.StringOutput `pulumi:"etag"`
	Location                  pulumi.StringOutput `pulumi:"location"`
	NotebookRuntimeTemplateId pulumi.StringOutput `pulumi:"notebookRuntimeTemplateId"`
	Project                   pulumi.StringOutput `pulumi:"project"`
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version pulumi.IntOutput `pulumi:"version"`
}

Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors. Note - this resource's API doesn't support deletion. When deleted, the resource will persist on Google Cloud even though it will be deleted from Pulumi state.

func GetNotebookRuntimeTemplateIamPolicy 

func GetNotebookRuntimeTemplateIamPolicy(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *NotebookRuntimeTemplateIamPolicyState, opts ...pulumi.ResourceOption) (*NotebookRuntimeTemplateIamPolicy, error)

GetNotebookRuntimeTemplateIamPolicy gets an existing NotebookRuntimeTemplateIamPolicy resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewNotebookRuntimeTemplateIamPolicy 

func NewNotebookRuntimeTemplateIamPolicy(ctx *pulumi.Context,
	name string, args *NotebookRuntimeTemplateIamPolicyArgs, opts ...pulumi.ResourceOption) (*NotebookRuntimeTemplateIamPolicy, error)

NewNotebookRuntimeTemplateIamPolicy registers a new resource with the given unique name, arguments, and options.

func (*NotebookRuntimeTemplateIamPolicy) ElementType 

func (*NotebookRuntimeTemplateIamPolicy) ElementType() reflect.Type

func (*NotebookRuntimeTemplateIamPolicy) ToNotebookRuntimeTemplateIamPolicyOutput 

func (i *NotebookRuntimeTemplateIamPolicy) ToNotebookRuntimeTemplateIamPolicyOutput() NotebookRuntimeTemplateIamPolicyOutput

func (*NotebookRuntimeTemplateIamPolicy) ToNotebookRuntimeTemplateIamPolicyOutputWithContext 

func (i *NotebookRuntimeTemplateIamPolicy) ToNotebookRuntimeTemplateIamPolicyOutputWithContext(ctx context.Context) NotebookRuntimeTemplateIamPolicyOutput

type NotebookRuntimeTemplateIamPolicyArgs 

type NotebookRuntimeTemplateIamPolicyArgs struct {
	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings GoogleIamV1BindingArrayInput
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag                      pulumi.StringPtrInput
	Location                  pulumi.StringPtrInput
	NotebookRuntimeTemplateId pulumi.StringInput
	Project                   pulumi.StringPtrInput
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version pulumi.IntPtrInput
}

The set of arguments for constructing a NotebookRuntimeTemplateIamPolicy resource.

func (NotebookRuntimeTemplateIamPolicyArgs) ElementType 

func (NotebookRuntimeTemplateIamPolicyArgs) ElementType() reflect.Type

type NotebookRuntimeTemplateIamPolicyInput 

type NotebookRuntimeTemplateIamPolicyInput interface {
	pulumi.Input

	ToNotebookRuntimeTemplateIamPolicyOutput() NotebookRuntimeTemplateIamPolicyOutput
	ToNotebookRuntimeTemplateIamPolicyOutputWithContext(ctx context.Context) NotebookRuntimeTemplateIamPolicyOutput
}

type NotebookRuntimeTemplateIamPolicyOutput 

type NotebookRuntimeTemplateIamPolicyOutput struct{ *pulumi.OutputState }

func (NotebookRuntimeTemplateIamPolicyOutput) Bindings 

func (o NotebookRuntimeTemplateIamPolicyOutput) Bindings() GoogleIamV1BindingResponseArrayOutput

Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.

func (NotebookRuntimeTemplateIamPolicyOutput) ElementType 

func (NotebookRuntimeTemplateIamPolicyOutput) ElementType() reflect.Type

func (NotebookRuntimeTemplateIamPolicyOutput) Etag 

func (o NotebookRuntimeTemplateIamPolicyOutput) Etag() pulumi.StringOutput

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.

func (NotebookRuntimeTemplateIamPolicyOutput) Location 

func (o NotebookRuntimeTemplateIamPolicyOutput) Location() pulumi.StringOutput

func (NotebookRuntimeTemplateIamPolicyOutput) NotebookRuntimeTemplateId 

func (o NotebookRuntimeTemplateIamPolicyOutput) NotebookRuntimeTemplateId() pulumi.StringOutput

func (NotebookRuntimeTemplateIamPolicyOutput) Project 

func (o NotebookRuntimeTemplateIamPolicyOutput) Project() pulumi.StringOutput

func (NotebookRuntimeTemplateIamPolicyOutput) ToNotebookRuntimeTemplateIamPolicyOutput 

func (o NotebookRuntimeTemplateIamPolicyOutput) ToNotebookRuntimeTemplateIamPolicyOutput() NotebookRuntimeTemplateIamPolicyOutput

func (NotebookRuntimeTemplateIamPolicyOutput) ToNotebookRuntimeTemplateIamPolicyOutputWithContext 

func (o NotebookRuntimeTemplateIamPolicyOutput) ToNotebookRuntimeTemplateIamPolicyOutputWithContext(ctx context.Context) NotebookRuntimeTemplateIamPolicyOutput

func (NotebookRuntimeTemplateIamPolicyOutput) Version 

func (o NotebookRuntimeTemplateIamPolicyOutput) Version() pulumi.IntOutput

Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).

type NotebookRuntimeTemplateIamPolicyState 

type NotebookRuntimeTemplateIamPolicyState struct {
}

func (NotebookRuntimeTemplateIamPolicyState) ElementType 

func (NotebookRuntimeTemplateIamPolicyState) ElementType() reflect.Type

type NotebookRuntimeTemplateInput 

type NotebookRuntimeTemplateInput interface {
	pulumi.Input

	ToNotebookRuntimeTemplateOutput() NotebookRuntimeTemplateOutput
	ToNotebookRuntimeTemplateOutputWithContext(ctx context.Context) NotebookRuntimeTemplateOutput
}

type NotebookRuntimeTemplateNotebookRuntimeType 

type NotebookRuntimeTemplateNotebookRuntimeType string

Optional. Immutable. The type of the notebook runtime template.

func (NotebookRuntimeTemplateNotebookRuntimeType) ElementType 

func (NotebookRuntimeTemplateNotebookRuntimeType) ElementType() reflect.Type

func (NotebookRuntimeTemplateNotebookRuntimeType) ToNotebookRuntimeTemplateNotebookRuntimeTypeOutput 

func (e NotebookRuntimeTemplateNotebookRuntimeType) ToNotebookRuntimeTemplateNotebookRuntimeTypeOutput() NotebookRuntimeTemplateNotebookRuntimeTypeOutput

func (NotebookRuntimeTemplateNotebookRuntimeType) ToNotebookRuntimeTemplateNotebookRuntimeTypeOutputWithContext 

func (e NotebookRuntimeTemplateNotebookRuntimeType) ToNotebookRuntimeTemplateNotebookRuntimeTypeOutputWithContext(ctx context.Context) NotebookRuntimeTemplateNotebookRuntimeTypeOutput

func (NotebookRuntimeTemplateNotebookRuntimeType) ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutput 

func (e NotebookRuntimeTemplateNotebookRuntimeType) ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutput() NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput

func (NotebookRuntimeTemplateNotebookRuntimeType) ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutputWithContext 

func (e NotebookRuntimeTemplateNotebookRuntimeType) ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutputWithContext(ctx context.Context) NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput

func (NotebookRuntimeTemplateNotebookRuntimeType) ToStringOutput 

func (e NotebookRuntimeTemplateNotebookRuntimeType) ToStringOutput() pulumi.StringOutput

func (NotebookRuntimeTemplateNotebookRuntimeType) ToStringOutputWithContext 

func (e NotebookRuntimeTemplateNotebookRuntimeType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (NotebookRuntimeTemplateNotebookRuntimeType) ToStringPtrOutput 

func (e NotebookRuntimeTemplateNotebookRuntimeType) ToStringPtrOutput() pulumi.StringPtrOutput

func (NotebookRuntimeTemplateNotebookRuntimeType) ToStringPtrOutputWithContext 

func (e NotebookRuntimeTemplateNotebookRuntimeType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type NotebookRuntimeTemplateNotebookRuntimeTypeInput 

type NotebookRuntimeTemplateNotebookRuntimeTypeInput interface {
	pulumi.Input

	ToNotebookRuntimeTemplateNotebookRuntimeTypeOutput() NotebookRuntimeTemplateNotebookRuntimeTypeOutput
	ToNotebookRuntimeTemplateNotebookRuntimeTypeOutputWithContext(context.Context) NotebookRuntimeTemplateNotebookRuntimeTypeOutput
}

NotebookRuntimeTemplateNotebookRuntimeTypeInput is an input type that accepts NotebookRuntimeTemplateNotebookRuntimeTypeArgs and NotebookRuntimeTemplateNotebookRuntimeTypeOutput values. You can construct a concrete instance of `NotebookRuntimeTemplateNotebookRuntimeTypeInput` via: 

NotebookRuntimeTemplateNotebookRuntimeTypeArgs{...}

type NotebookRuntimeTemplateNotebookRuntimeTypeOutput 

type NotebookRuntimeTemplateNotebookRuntimeTypeOutput struct{ *pulumi.OutputState }

func (NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ElementType 

func (NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ElementType() reflect.Type

func (NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToNotebookRuntimeTemplateNotebookRuntimeTypeOutput 

func (o NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToNotebookRuntimeTemplateNotebookRuntimeTypeOutput() NotebookRuntimeTemplateNotebookRuntimeTypeOutput

func (NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToNotebookRuntimeTemplateNotebookRuntimeTypeOutputWithContext 

func (o NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToNotebookRuntimeTemplateNotebookRuntimeTypeOutputWithContext(ctx context.Context) NotebookRuntimeTemplateNotebookRuntimeTypeOutput

func (NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutput 

func (o NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutput() NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput

func (NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutputWithContext 

func (o NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutputWithContext(ctx context.Context) NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput

func (NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToStringOutput 

func (o NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToStringOutput() pulumi.StringOutput

func (NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToStringOutputWithContext 

func (o NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToStringPtrOutput 

func (o NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToStringPtrOutputWithContext 

func (o NotebookRuntimeTemplateNotebookRuntimeTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type NotebookRuntimeTemplateNotebookRuntimeTypePtrInput 

type NotebookRuntimeTemplateNotebookRuntimeTypePtrInput interface {
	pulumi.Input

	ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutput() NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput
	ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutputWithContext(context.Context) NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput
}

func NotebookRuntimeTemplateNotebookRuntimeTypePtr 

func NotebookRuntimeTemplateNotebookRuntimeTypePtr(v string) NotebookRuntimeTemplateNotebookRuntimeTypePtrInput

type NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput 

type NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput struct{ *pulumi.OutputState }

func (NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput) Elem 

func (o NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput) Elem() NotebookRuntimeTemplateNotebookRuntimeTypeOutput

func (NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput) ElementType 

func (NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput) ElementType() reflect.Type

func (NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput) ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutput 

func (o NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput) ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutput() NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput

func (NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput) ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutputWithContext 

func (o NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput) ToNotebookRuntimeTemplateNotebookRuntimeTypePtrOutputWithContext(ctx context.Context) NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput

func (NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput) ToStringPtrOutput 

func (o NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput) ToStringPtrOutputWithContext 

func (o NotebookRuntimeTemplateNotebookRuntimeTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type NotebookRuntimeTemplateOutput 

type NotebookRuntimeTemplateOutput struct{ *pulumi.OutputState }

func (NotebookRuntimeTemplateOutput) CreateTime 

func (o NotebookRuntimeTemplateOutput) CreateTime() pulumi.StringOutput

Timestamp when this NotebookRuntimeTemplate was created.

func (NotebookRuntimeTemplateOutput) DataPersistentDiskSpec 

func (o NotebookRuntimeTemplateOutput) DataPersistentDiskSpec() GoogleCloudAiplatformV1PersistentDiskSpecResponseOutput

Optional. The specification of persistent disk attached to the runtime as data disk storage.

func (NotebookRuntimeTemplateOutput) Description 

func (o NotebookRuntimeTemplateOutput) Description() pulumi.StringOutput

The description of the NotebookRuntimeTemplate.

func (NotebookRuntimeTemplateOutput) DisplayName 

func (o NotebookRuntimeTemplateOutput) DisplayName() pulumi.StringOutput

The display name of the NotebookRuntimeTemplate. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (NotebookRuntimeTemplateOutput) ElementType 

func (NotebookRuntimeTemplateOutput) ElementType() reflect.Type

func (NotebookRuntimeTemplateOutput) Etag 

func (o NotebookRuntimeTemplateOutput) Etag() pulumi.StringOutput

Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (NotebookRuntimeTemplateOutput) EucConfig 

func (o NotebookRuntimeTemplateOutput) EucConfig() GoogleCloudAiplatformV1NotebookEucConfigResponseOutput

EUC configuration of the NotebookRuntimeTemplate.

func (NotebookRuntimeTemplateOutput) IdleShutdownConfig 

func (o NotebookRuntimeTemplateOutput) IdleShutdownConfig() GoogleCloudAiplatformV1NotebookIdleShutdownConfigResponseOutput

The idle shutdown configuration of NotebookRuntimeTemplate. This config will only be set when idle shutdown is enabled.

func (NotebookRuntimeTemplateOutput) IsDefault 

func (o NotebookRuntimeTemplateOutput) IsDefault() pulumi.BoolOutput

The default template to use if not specified.

func (NotebookRuntimeTemplateOutput) Labels 

func (o NotebookRuntimeTemplateOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize the NotebookRuntimeTemplates. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (NotebookRuntimeTemplateOutput) Location 

func (o NotebookRuntimeTemplateOutput) Location() pulumi.StringOutput

func (NotebookRuntimeTemplateOutput) MachineSpec 

func (o NotebookRuntimeTemplateOutput) MachineSpec() GoogleCloudAiplatformV1MachineSpecResponseOutput

Optional. Immutable. The specification of a single machine for the template.

func (NotebookRuntimeTemplateOutput) Name 

func (o NotebookRuntimeTemplateOutput) Name() pulumi.StringOutput

The resource name of the NotebookRuntimeTemplate.

func (NotebookRuntimeTemplateOutput) NetworkSpec 

func (o NotebookRuntimeTemplateOutput) NetworkSpec() GoogleCloudAiplatformV1NetworkSpecResponseOutput

Optional. Network spec.

func (NotebookRuntimeTemplateOutput) NotebookRuntimeTemplateId 

func (o NotebookRuntimeTemplateOutput) NotebookRuntimeTemplateId() pulumi.StringPtrOutput

Optional. User specified ID for the notebook runtime template.

func (NotebookRuntimeTemplateOutput) NotebookRuntimeType 

func (o NotebookRuntimeTemplateOutput) NotebookRuntimeType() pulumi.StringOutput

Optional. Immutable. The type of the notebook runtime template.

func (NotebookRuntimeTemplateOutput) Project 

func (o NotebookRuntimeTemplateOutput) Project() pulumi.StringOutput

func (NotebookRuntimeTemplateOutput) ServiceAccount 

func (o NotebookRuntimeTemplateOutput) ServiceAccount() pulumi.StringOutput

The service account that the runtime workload runs as. You can use any service account within the same project, but you must have the service account user permission to use the instance. If not specified, the [Compute Engine default service account](https://cloud.google.com/compute/docs/access/service-accounts#default_service_account) is used.

func (NotebookRuntimeTemplateOutput) ToNotebookRuntimeTemplateOutput 

func (o NotebookRuntimeTemplateOutput) ToNotebookRuntimeTemplateOutput() NotebookRuntimeTemplateOutput

func (NotebookRuntimeTemplateOutput) ToNotebookRuntimeTemplateOutputWithContext 

func (o NotebookRuntimeTemplateOutput) ToNotebookRuntimeTemplateOutputWithContext(ctx context.Context) NotebookRuntimeTemplateOutput

func (NotebookRuntimeTemplateOutput) UpdateTime 

func (o NotebookRuntimeTemplateOutput) UpdateTime() pulumi.StringOutput

Timestamp when this NotebookRuntimeTemplate was most recently updated.

type NotebookRuntimeTemplateState 

type NotebookRuntimeTemplateState struct {
}

func (NotebookRuntimeTemplateState) ElementType 

func (NotebookRuntimeTemplateState) ElementType() reflect.Type

type PipelineJob 

type PipelineJob struct {
	pulumi.CustomResourceState

	// Pipeline creation time.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// Pipeline end time.
	EndTime pulumi.StringOutput `pulumi:"endTime"`
	// The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.
	Error GoogleRpcStatusResponseOutput `pulumi:"error"`
	// The details of pipeline run. Not available in the list view.
	JobDetail GoogleCloudAiplatformV1PipelineJobDetailResponseOutput `pulumi:"jobDetail"`
	// The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// The resource name of the PipelineJob.
	Name pulumi.StringOutput `pulumi:"name"`
	// The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
	Network pulumi.StringOutput `pulumi:"network"`
	// The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.
	PipelineJobId pulumi.StringPtrOutput `pulumi:"pipelineJobId"`
	// The spec of the pipeline.
	PipelineSpec pulumi.StringMapOutput `pulumi:"pipelineSpec"`
	Project      pulumi.StringOutput    `pulumi:"project"`
	// A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
	ReservedIpRanges pulumi.StringArrayOutput `pulumi:"reservedIpRanges"`
	// Runtime config of the pipeline.
	RuntimeConfig GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput `pulumi:"runtimeConfig"`
	// The schedule resource name. Only returned if the Pipeline is created by Schedule API.
	ScheduleName pulumi.StringOutput `pulumi:"scheduleName"`
	// The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
	ServiceAccount pulumi.StringOutput `pulumi:"serviceAccount"`
	// Pipeline start time.
	StartTime pulumi.StringOutput `pulumi:"startTime"`
	// The detailed state of the job.
	State pulumi.StringOutput `pulumi:"state"`
	// Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.
	TemplateMetadata GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput `pulumi:"templateMetadata"`
	// A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
	TemplateUri pulumi.StringOutput `pulumi:"templateUri"`
	// Timestamp when this PipelineJob was most recently updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a PipelineJob. A PipelineJob will run immediately when created. Auto-naming is currently not supported for this resource.

func GetPipelineJob 

func GetPipelineJob(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *PipelineJobState, opts ...pulumi.ResourceOption) (*PipelineJob, error)

GetPipelineJob gets an existing PipelineJob resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewPipelineJob 

func NewPipelineJob(ctx *pulumi.Context,
	name string, args *PipelineJobArgs, opts ...pulumi.ResourceOption) (*PipelineJob, error)

NewPipelineJob registers a new resource with the given unique name, arguments, and options.

func (*PipelineJob) ElementType 

func (*PipelineJob) ElementType() reflect.Type

func (*PipelineJob) ToPipelineJobOutput 

func (i *PipelineJob) ToPipelineJobOutput() PipelineJobOutput

func (*PipelineJob) ToPipelineJobOutputWithContext 

func (i *PipelineJob) ToPipelineJobOutputWithContext(ctx context.Context) PipelineJobOutput

type PipelineJobArgs 

type PipelineJobArgs struct {
	// The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringPtrInput
	// Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.
	Network pulumi.StringPtrInput
	// The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.
	PipelineJobId pulumi.StringPtrInput
	// The spec of the pipeline.
	PipelineSpec pulumi.StringMapInput
	Project      pulumi.StringPtrInput
	// A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].
	ReservedIpRanges pulumi.StringArrayInput
	// Runtime config of the pipeline.
	RuntimeConfig GoogleCloudAiplatformV1PipelineJobRuntimeConfigPtrInput
	// The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.
	ServiceAccount pulumi.StringPtrInput
	// A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.
	TemplateUri pulumi.StringPtrInput
}

The set of arguments for constructing a PipelineJob resource.

func (PipelineJobArgs) ElementType 

func (PipelineJobArgs) ElementType() reflect.Type

type PipelineJobInput 

type PipelineJobInput interface {
	pulumi.Input

	ToPipelineJobOutput() PipelineJobOutput
	ToPipelineJobOutputWithContext(ctx context.Context) PipelineJobOutput
}

type PipelineJobOutput 

type PipelineJobOutput struct{ *pulumi.OutputState }

func (PipelineJobOutput) CreateTime 

func (o PipelineJobOutput) CreateTime() pulumi.StringOutput

Pipeline creation time.

func (PipelineJobOutput) DisplayName 

func (o PipelineJobOutput) DisplayName() pulumi.StringOutput

The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (PipelineJobOutput) ElementType 

func (PipelineJobOutput) ElementType() reflect.Type

func (PipelineJobOutput) EncryptionSpec 

func (o PipelineJobOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key.

func (PipelineJobOutput) EndTime 

func (o PipelineJobOutput) EndTime() pulumi.StringOutput

Pipeline end time.

func (PipelineJobOutput) Error 

func (o PipelineJobOutput) Error() GoogleRpcStatusResponseOutput

The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED.

func (PipelineJobOutput) JobDetail 

func (o PipelineJobOutput) JobDetail() GoogleCloudAiplatformV1PipelineJobDetailResponseOutput

The details of pipeline run. Not available in the list view.

func (PipelineJobOutput) Labels 

func (o PipelineJobOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided.

func (PipelineJobOutput) Location 

func (o PipelineJobOutput) Location() pulumi.StringOutput

func (PipelineJobOutput) Name 

func (o PipelineJobOutput) Name() pulumi.StringOutput

The resource name of the PipelineJob.

func (PipelineJobOutput) Network 

func (o PipelineJobOutput) Network() pulumi.StringOutput

The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network.

func (PipelineJobOutput) PipelineJobId 

func (o PipelineJobOutput) PipelineJobId() pulumi.StringPtrOutput

The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.

func (PipelineJobOutput) PipelineSpec 

func (o PipelineJobOutput) PipelineSpec() pulumi.StringMapOutput

The spec of the pipeline.

func (PipelineJobOutput) Project 

func (o PipelineJobOutput) Project() pulumi.StringOutput

func (PipelineJobOutput) ReservedIpRanges 

func (o PipelineJobOutput) ReservedIpRanges() pulumi.StringArrayOutput

A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

func (PipelineJobOutput) RuntimeConfig 

func (o PipelineJobOutput) RuntimeConfig() GoogleCloudAiplatformV1PipelineJobRuntimeConfigResponseOutput

Runtime config of the pipeline.

func (PipelineJobOutput) ScheduleName 

func (o PipelineJobOutput) ScheduleName() pulumi.StringOutput

The schedule resource name. Only returned if the Pipeline is created by Schedule API.

func (PipelineJobOutput) ServiceAccount 

func (o PipelineJobOutput) ServiceAccount() pulumi.StringOutput

The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service-accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account.

func (PipelineJobOutput) StartTime 

func (o PipelineJobOutput) StartTime() pulumi.StringOutput

Pipeline start time.

func (PipelineJobOutput) State 

func (o PipelineJobOutput) State() pulumi.StringOutput

The detailed state of the job.

func (PipelineJobOutput) TemplateMetadata 

func (o PipelineJobOutput) TemplateMetadata() GoogleCloudAiplatformV1PipelineTemplateMetadataResponseOutput

Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry.

func (PipelineJobOutput) TemplateUri 

func (o PipelineJobOutput) TemplateUri() pulumi.StringOutput

A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline-template.

func (PipelineJobOutput) ToPipelineJobOutput 

func (o PipelineJobOutput) ToPipelineJobOutput() PipelineJobOutput

func (PipelineJobOutput) ToPipelineJobOutputWithContext 

func (o PipelineJobOutput) ToPipelineJobOutputWithContext(ctx context.Context) PipelineJobOutput

func (PipelineJobOutput) UpdateTime 

func (o PipelineJobOutput) UpdateTime() pulumi.StringOutput

Timestamp when this PipelineJob was most recently updated.

type PipelineJobState 

type PipelineJobState struct {
}

func (PipelineJobState) ElementType 

func (PipelineJobState) ElementType() reflect.Type

type Run 

type Run struct {
	pulumi.CustomResourceState

	// Timestamp when this TensorboardRun was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Description of this TensorboardRun.
	Description pulumi.StringOutput `pulumi:"description"`
	// User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag         pulumi.StringOutput `pulumi:"etag"`
	ExperimentId pulumi.StringOutput `pulumi:"experimentId"`
	// The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
	Name          pulumi.StringOutput `pulumi:"name"`
	Project       pulumi.StringOutput `pulumi:"project"`
	TensorboardId pulumi.StringOutput `pulumi:"tensorboardId"`
	// Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.
	TensorboardRunId pulumi.StringOutput `pulumi:"tensorboardRunId"`
	// Timestamp when this TensorboardRun was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a TensorboardRun. Auto-naming is currently not supported for this resource.

func GetRun 

func GetRun(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *RunState, opts ...pulumi.ResourceOption) (*Run, error)

GetRun gets an existing Run resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewRun 

func NewRun(ctx *pulumi.Context,
	name string, args *RunArgs, opts ...pulumi.ResourceOption) (*Run, error)

NewRun registers a new resource with the given unique name, arguments, and options.

func (*Run) ElementType 

func (*Run) ElementType() reflect.Type

func (*Run) ToRunOutput 

func (i *Run) ToRunOutput() RunOutput

func (*Run) ToRunOutputWithContext 

func (i *Run) ToRunOutputWithContext(ctx context.Context) RunOutput

type RunArgs 

type RunArgs struct {
	// Description of this TensorboardRun.
	Description pulumi.StringPtrInput
	// User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
	DisplayName pulumi.StringInput
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag         pulumi.StringPtrInput
	ExperimentId pulumi.StringInput
	// The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels        pulumi.StringMapInput
	Location      pulumi.StringPtrInput
	Project       pulumi.StringPtrInput
	TensorboardId pulumi.StringInput
	// Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.
	TensorboardRunId pulumi.StringInput
}

The set of arguments for constructing a Run resource.

func (RunArgs) ElementType 

func (RunArgs) ElementType() reflect.Type

type RunInput 

type RunInput interface {
	pulumi.Input

	ToRunOutput() RunOutput
	ToRunOutputWithContext(ctx context.Context) RunOutput
}

type RunOutput 

type RunOutput struct{ *pulumi.OutputState }

func (RunOutput) CreateTime 

func (o RunOutput) CreateTime() pulumi.StringOutput

Timestamp when this TensorboardRun was created.

func (RunOutput) Description 

func (o RunOutput) Description() pulumi.StringOutput

Description of this TensorboardRun.

func (RunOutput) DisplayName 

func (o RunOutput) DisplayName() pulumi.StringOutput

User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.

func (RunOutput) ElementType 

func (RunOutput) ElementType() reflect.Type

func (RunOutput) Etag 

func (o RunOutput) Etag() pulumi.StringOutput

Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (RunOutput) ExperimentId 

func (o RunOutput) ExperimentId() pulumi.StringOutput

func (RunOutput) Labels 

func (o RunOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (RunOutput) Location 

func (o RunOutput) Location() pulumi.StringOutput

func (RunOutput) Name 

func (o RunOutput) Name() pulumi.StringOutput

Name of the TensorboardRun. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`

func (RunOutput) Project 

func (o RunOutput) Project() pulumi.StringOutput

func (RunOutput) TensorboardId 

func (o RunOutput) TensorboardId() pulumi.StringOutput

func (RunOutput) TensorboardRunId 

func (o RunOutput) TensorboardRunId() pulumi.StringOutput

Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`.

func (RunOutput) ToRunOutput 

func (o RunOutput) ToRunOutput() RunOutput

func (RunOutput) ToRunOutputWithContext 

func (o RunOutput) ToRunOutputWithContext(ctx context.Context) RunOutput

func (RunOutput) UpdateTime 

func (o RunOutput) UpdateTime() pulumi.StringOutput

Timestamp when this TensorboardRun was last updated.

type RunState 

type RunState struct {
}

func (RunState) ElementType 

func (RunState) ElementType() reflect.Type

type Schedule 

type Schedule struct {
	pulumi.CustomResourceState

	// Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.
	AllowQueueing pulumi.BoolOutput `pulumi:"allowQueueing"`
	// Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false.
	CatchUp pulumi.BoolOutput `pulumi:"catchUp"`
	// Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
	CreatePipelineJobRequest GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput `pulumi:"createPipelineJobRequest"`
	// Timestamp when this Schedule was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".
	Cron pulumi.StringOutput `pulumi:"cron"`
	// User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count >= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
	EndTime pulumi.StringOutput `pulumi:"endTime"`
	// Timestamp when this Schedule was last paused. Unset if never paused.
	LastPauseTime pulumi.StringOutput `pulumi:"lastPauseTime"`
	// Timestamp when this Schedule was last resumed. Unset if never resumed from pause.
	LastResumeTime pulumi.StringOutput `pulumi:"lastResumeTime"`
	// Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet.
	LastScheduledRunResponse GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput `pulumi:"lastScheduledRunResponse"`
	Location                 pulumi.StringOutput                                      `pulumi:"location"`
	// Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable).
	MaxConcurrentRunCount pulumi.StringOutput `pulumi:"maxConcurrentRunCount"`
	// Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count >= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
	MaxRunCount pulumi.StringOutput `pulumi:"maxRunCount"`
	// Immutable. The resource name of the Schedule.
	Name pulumi.StringOutput `pulumi:"name"`
	// Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule.
	NextRunTime pulumi.StringOutput `pulumi:"nextRunTime"`
	Project     pulumi.StringOutput `pulumi:"project"`
	// Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
	StartTime pulumi.StringOutput `pulumi:"startTime"`
	// The number of runs started by this schedule.
	StartedRunCount pulumi.StringOutput `pulumi:"startedRunCount"`
	// The state of this Schedule.
	State pulumi.StringOutput `pulumi:"state"`
	// Timestamp when this Schedule was updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a Schedule.

func GetSchedule 

func GetSchedule(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *ScheduleState, opts ...pulumi.ResourceOption) (*Schedule, error)

GetSchedule gets an existing Schedule resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewSchedule 

func NewSchedule(ctx *pulumi.Context,
	name string, args *ScheduleArgs, opts ...pulumi.ResourceOption) (*Schedule, error)

NewSchedule registers a new resource with the given unique name, arguments, and options.

func (*Schedule) ElementType 

func (*Schedule) ElementType() reflect.Type

func (*Schedule) ToScheduleOutput 

func (i *Schedule) ToScheduleOutput() ScheduleOutput

func (*Schedule) ToScheduleOutputWithContext 

func (i *Schedule) ToScheduleOutputWithContext(ctx context.Context) ScheduleOutput

type ScheduleArgs 

type ScheduleArgs struct {
	// Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.
	AllowQueueing pulumi.BoolPtrInput
	// Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).
	CreatePipelineJobRequest GoogleCloudAiplatformV1CreatePipelineJobRequestPtrInput
	// Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".
	Cron pulumi.StringPtrInput
	// User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
	DisplayName pulumi.StringInput
	// Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count >= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
	EndTime  pulumi.StringPtrInput
	Location pulumi.StringPtrInput
	// Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable).
	MaxConcurrentRunCount pulumi.StringInput
	// Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count >= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.
	MaxRunCount pulumi.StringPtrInput
	// Immutable. The resource name of the Schedule.
	Name    pulumi.StringPtrInput
	Project pulumi.StringPtrInput
	// Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
	StartTime pulumi.StringPtrInput
}

The set of arguments for constructing a Schedule resource.

func (ScheduleArgs) ElementType 

func (ScheduleArgs) ElementType() reflect.Type

type ScheduleInput 

type ScheduleInput interface {
	pulumi.Input

	ToScheduleOutput() ScheduleOutput
	ToScheduleOutputWithContext(ctx context.Context) ScheduleOutput
}

type ScheduleOutput 

type ScheduleOutput struct{ *pulumi.OutputState }

func (ScheduleOutput) AllowQueueing 

func (o ScheduleOutput) AllowQueueing() pulumi.BoolOutput

Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false.

func (ScheduleOutput) CatchUp 

func (o ScheduleOutput) CatchUp() pulumi.BoolOutput

Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false.

func (ScheduleOutput) CreatePipelineJobRequest 

func (o ScheduleOutput) CreatePipelineJobRequest() GoogleCloudAiplatformV1CreatePipelineJobRequestResponseOutput

Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}).

func (ScheduleOutput) CreateTime 

func (o ScheduleOutput) CreateTime() pulumi.StringOutput

Timestamp when this Schedule was created.

func (ScheduleOutput) Cron 

func (o ScheduleOutput) Cron() pulumi.StringOutput

Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *".

func (ScheduleOutput) DisplayName 

func (o ScheduleOutput) DisplayName() pulumi.StringOutput

User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.

func (ScheduleOutput) ElementType 

func (ScheduleOutput) ElementType() reflect.Type

func (ScheduleOutput) EndTime 

func (o ScheduleOutput) EndTime() pulumi.StringOutput

Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count >= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.

func (ScheduleOutput) LastPauseTime 

func (o ScheduleOutput) LastPauseTime() pulumi.StringOutput

Timestamp when this Schedule was last paused. Unset if never paused.

func (ScheduleOutput) LastResumeTime 

func (o ScheduleOutput) LastResumeTime() pulumi.StringOutput

Timestamp when this Schedule was last resumed. Unset if never resumed from pause.

func (ScheduleOutput) LastScheduledRunResponse 

func (o ScheduleOutput) LastScheduledRunResponse() GoogleCloudAiplatformV1ScheduleRunResponseResponseOutput

Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet.

func (ScheduleOutput) Location 

func (o ScheduleOutput) Location() pulumi.StringOutput

func (ScheduleOutput) MaxConcurrentRunCount 

func (o ScheduleOutput) MaxConcurrentRunCount() pulumi.StringOutput

Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable).

func (ScheduleOutput) MaxRunCount 

func (o ScheduleOutput) MaxRunCount() pulumi.StringOutput

Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count >= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified.

func (ScheduleOutput) Name 

func (o ScheduleOutput) Name() pulumi.StringOutput

Immutable. The resource name of the Schedule.

func (ScheduleOutput) NextRunTime 

func (o ScheduleOutput) NextRunTime() pulumi.StringOutput

Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule.

func (ScheduleOutput) Project 

func (o ScheduleOutput) Project() pulumi.StringOutput

func (ScheduleOutput) StartTime 

func (o ScheduleOutput) StartTime() pulumi.StringOutput

Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.

func (ScheduleOutput) StartedRunCount 

func (o ScheduleOutput) StartedRunCount() pulumi.StringOutput

The number of runs started by this schedule.

func (ScheduleOutput) State 

func (o ScheduleOutput) State() pulumi.StringOutput

The state of this Schedule.

func (ScheduleOutput) ToScheduleOutput 

func (o ScheduleOutput) ToScheduleOutput() ScheduleOutput

func (ScheduleOutput) ToScheduleOutputWithContext 

func (o ScheduleOutput) ToScheduleOutputWithContext(ctx context.Context) ScheduleOutput

func (ScheduleOutput) UpdateTime 

func (o ScheduleOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Schedule was updated.

type ScheduleState 

type ScheduleState struct {
}

func (ScheduleState) ElementType 

func (ScheduleState) ElementType() reflect.Type

type SpecialistPool 

type SpecialistPool struct {
	pulumi.CustomResourceState

	// The user-defined name of the SpecialistPool. The name can be up to 128 characters long and can consist of any UTF-8 characters. This field should be unique on project-level.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	Location    pulumi.StringOutput `pulumi:"location"`
	// The resource name of the SpecialistPool.
	Name pulumi.StringOutput `pulumi:"name"`
	// The resource name of the pending data labeling jobs.
	PendingDataLabelingJobs pulumi.StringArrayOutput `pulumi:"pendingDataLabelingJobs"`
	Project                 pulumi.StringOutput      `pulumi:"project"`
	// The email addresses of the managers in the SpecialistPool.
	SpecialistManagerEmails pulumi.StringArrayOutput `pulumi:"specialistManagerEmails"`
	// The number of managers in this SpecialistPool.
	SpecialistManagersCount pulumi.IntOutput `pulumi:"specialistManagersCount"`
	// The email addresses of workers in the SpecialistPool.
	SpecialistWorkerEmails pulumi.StringArrayOutput `pulumi:"specialistWorkerEmails"`
}

Creates a SpecialistPool.

func GetSpecialistPool 

func GetSpecialistPool(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *SpecialistPoolState, opts ...pulumi.ResourceOption) (*SpecialistPool, error)

GetSpecialistPool gets an existing SpecialistPool resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewSpecialistPool 

func NewSpecialistPool(ctx *pulumi.Context,
	name string, args *SpecialistPoolArgs, opts ...pulumi.ResourceOption) (*SpecialistPool, error)

NewSpecialistPool registers a new resource with the given unique name, arguments, and options.

func (*SpecialistPool) ElementType 

func (*SpecialistPool) ElementType() reflect.Type

func (*SpecialistPool) ToSpecialistPoolOutput 

func (i *SpecialistPool) ToSpecialistPoolOutput() SpecialistPoolOutput

func (*SpecialistPool) ToSpecialistPoolOutputWithContext 

func (i *SpecialistPool) ToSpecialistPoolOutputWithContext(ctx context.Context) SpecialistPoolOutput

type SpecialistPoolArgs 

type SpecialistPoolArgs struct {
	// The user-defined name of the SpecialistPool. The name can be up to 128 characters long and can consist of any UTF-8 characters. This field should be unique on project-level.
	DisplayName pulumi.StringInput
	Location    pulumi.StringPtrInput
	// The resource name of the SpecialistPool.
	Name    pulumi.StringPtrInput
	Project pulumi.StringPtrInput
	// The email addresses of the managers in the SpecialistPool.
	SpecialistManagerEmails pulumi.StringArrayInput
	// The email addresses of workers in the SpecialistPool.
	SpecialistWorkerEmails pulumi.StringArrayInput
}

The set of arguments for constructing a SpecialistPool resource.

func (SpecialistPoolArgs) ElementType 

func (SpecialistPoolArgs) ElementType() reflect.Type

type SpecialistPoolInput 

type SpecialistPoolInput interface {
	pulumi.Input

	ToSpecialistPoolOutput() SpecialistPoolOutput
	ToSpecialistPoolOutputWithContext(ctx context.Context) SpecialistPoolOutput
}

type SpecialistPoolOutput 

type SpecialistPoolOutput struct{ *pulumi.OutputState }

func (SpecialistPoolOutput) DisplayName 

func (o SpecialistPoolOutput) DisplayName() pulumi.StringOutput

The user-defined name of the SpecialistPool. The name can be up to 128 characters long and can consist of any UTF-8 characters. This field should be unique on project-level.

func (SpecialistPoolOutput) ElementType 

func (SpecialistPoolOutput) ElementType() reflect.Type

func (SpecialistPoolOutput) Location 

func (o SpecialistPoolOutput) Location() pulumi.StringOutput

func (SpecialistPoolOutput) Name 

func (o SpecialistPoolOutput) Name() pulumi.StringOutput

The resource name of the SpecialistPool.

func (SpecialistPoolOutput) PendingDataLabelingJobs 

func (o SpecialistPoolOutput) PendingDataLabelingJobs() pulumi.StringArrayOutput

The resource name of the pending data labeling jobs.

func (SpecialistPoolOutput) Project 

func (o SpecialistPoolOutput) Project() pulumi.StringOutput

func (SpecialistPoolOutput) SpecialistManagerEmails 

func (o SpecialistPoolOutput) SpecialistManagerEmails() pulumi.StringArrayOutput

The email addresses of the managers in the SpecialistPool.

func (SpecialistPoolOutput) SpecialistManagersCount 

func (o SpecialistPoolOutput) SpecialistManagersCount() pulumi.IntOutput

The number of managers in this SpecialistPool.

func (SpecialistPoolOutput) SpecialistWorkerEmails 

func (o SpecialistPoolOutput) SpecialistWorkerEmails() pulumi.StringArrayOutput

The email addresses of workers in the SpecialistPool.

func (SpecialistPoolOutput) ToSpecialistPoolOutput 

func (o SpecialistPoolOutput) ToSpecialistPoolOutput() SpecialistPoolOutput

func (SpecialistPoolOutput) ToSpecialistPoolOutputWithContext 

func (o SpecialistPoolOutput) ToSpecialistPoolOutputWithContext(ctx context.Context) SpecialistPoolOutput

type SpecialistPoolState 

type SpecialistPoolState struct {
}

func (SpecialistPoolState) ElementType 

func (SpecialistPoolState) ElementType() reflect.Type

type Study 

type Study struct {
	pulumi.CustomResourceState

	// Time at which the study was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Describes the Study, default value is empty string.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.
	InactiveReason pulumi.StringOutput `pulumi:"inactiveReason"`
	Location       pulumi.StringOutput `pulumi:"location"`
	// The name of a study. The study's globally unique identifier. Format: `projects/{project}/locations/{location}/studies/{study}`
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// The detailed state of a Study.
	State pulumi.StringOutput `pulumi:"state"`
	// Configuration of the Study.
	StudySpec GoogleCloudAiplatformV1StudySpecResponseOutput `pulumi:"studySpec"`
}

Creates a Study. A resource name will be generated after creation of the Study. Auto-naming is currently not supported for this resource.

func GetStudy 

func GetStudy(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *StudyState, opts ...pulumi.ResourceOption) (*Study, error)

GetStudy gets an existing Study resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewStudy 

func NewStudy(ctx *pulumi.Context,
	name string, args *StudyArgs, opts ...pulumi.ResourceOption) (*Study, error)

NewStudy registers a new resource with the given unique name, arguments, and options.

func (*Study) ElementType 

func (*Study) ElementType() reflect.Type

func (*Study) ToStudyOutput 

func (i *Study) ToStudyOutput() StudyOutput

func (*Study) ToStudyOutputWithContext 

func (i *Study) ToStudyOutputWithContext(ctx context.Context) StudyOutput

type StudyArgs 

type StudyArgs struct {
	// Describes the Study, default value is empty string.
	DisplayName pulumi.StringInput
	Location    pulumi.StringPtrInput
	Project     pulumi.StringPtrInput
	// Configuration of the Study.
	StudySpec GoogleCloudAiplatformV1StudySpecInput
}

The set of arguments for constructing a Study resource.

func (StudyArgs) ElementType 

func (StudyArgs) ElementType() reflect.Type

type StudyInput 

type StudyInput interface {
	pulumi.Input

	ToStudyOutput() StudyOutput
	ToStudyOutputWithContext(ctx context.Context) StudyOutput
}

type StudyOutput 

type StudyOutput struct{ *pulumi.OutputState }

func (StudyOutput) CreateTime 

func (o StudyOutput) CreateTime() pulumi.StringOutput

Time at which the study was created.

func (StudyOutput) DisplayName 

func (o StudyOutput) DisplayName() pulumi.StringOutput

Describes the Study, default value is empty string.

func (StudyOutput) ElementType 

func (StudyOutput) ElementType() reflect.Type

func (StudyOutput) InactiveReason 

func (o StudyOutput) InactiveReason() pulumi.StringOutput

A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.

func (StudyOutput) Location 

func (o StudyOutput) Location() pulumi.StringOutput

func (StudyOutput) Name 

func (o StudyOutput) Name() pulumi.StringOutput

The name of a study. The study's globally unique identifier. Format: `projects/{project}/locations/{location}/studies/{study}`

func (StudyOutput) Project 

func (o StudyOutput) Project() pulumi.StringOutput

func (StudyOutput) State 

func (o StudyOutput) State() pulumi.StringOutput

The detailed state of a Study.

func (StudyOutput) StudySpec 

func (o StudyOutput) StudySpec() GoogleCloudAiplatformV1StudySpecResponseOutput

Configuration of the Study.

func (StudyOutput) ToStudyOutput 

func (o StudyOutput) ToStudyOutput() StudyOutput

func (StudyOutput) ToStudyOutputWithContext 

func (o StudyOutput) ToStudyOutputWithContext(ctx context.Context) StudyOutput

type StudyState 

type StudyState struct {
}

func (StudyState) ElementType 

func (StudyState) ElementType() reflect.Type

type Tensorboard 

type Tensorboard struct {
	pulumi.CustomResourceState

	// Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
	BlobStoragePathPrefix pulumi.StringOutput `pulumi:"blobStoragePathPrefix"`
	// Timestamp when this Tensorboard was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Description of this Tensorboard.
	Description pulumi.StringOutput `pulumi:"description"`
	// User provided name of this Tensorboard.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Used to indicate if the TensorBoard instance is the default one. Each project & region can have at most one default TensorBoard instance. Creation of a default TensorBoard instance and updating an existing TensorBoard instance to be default will mark all other TensorBoard instances (if any) as non default.
	IsDefault pulumi.BoolOutput `pulumi:"isDefault"`
	// The labels with user-defined metadata to organize your Tensorboards. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Tensorboard (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
	Name    pulumi.StringOutput `pulumi:"name"`
	Project pulumi.StringOutput `pulumi:"project"`
	// The number of Runs stored in this Tensorboard.
	RunCount pulumi.IntOutput `pulumi:"runCount"`
	// Timestamp when this Tensorboard was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a Tensorboard. Auto-naming is currently not supported for this resource.

func GetTensorboard 

func GetTensorboard(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *TensorboardState, opts ...pulumi.ResourceOption) (*Tensorboard, error)

GetTensorboard gets an existing Tensorboard resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewTensorboard 

func NewTensorboard(ctx *pulumi.Context,
	name string, args *TensorboardArgs, opts ...pulumi.ResourceOption) (*Tensorboard, error)

NewTensorboard registers a new resource with the given unique name, arguments, and options.

func (*Tensorboard) ElementType 

func (*Tensorboard) ElementType() reflect.Type

func (*Tensorboard) ToTensorboardOutput 

func (i *Tensorboard) ToTensorboardOutput() TensorboardOutput

func (*Tensorboard) ToTensorboardOutputWithContext 

func (i *Tensorboard) ToTensorboardOutputWithContext(ctx context.Context) TensorboardOutput

type TensorboardArgs 

type TensorboardArgs struct {
	// Description of this Tensorboard.
	Description pulumi.StringPtrInput
	// User provided name of this Tensorboard.
	DisplayName pulumi.StringInput
	// Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag pulumi.StringPtrInput
	// Used to indicate if the TensorBoard instance is the default one. Each project & region can have at most one default TensorBoard instance. Creation of a default TensorBoard instance and updating an existing TensorBoard instance to be default will mark all other TensorBoard instances (if any) as non default.
	IsDefault pulumi.BoolPtrInput
	// The labels with user-defined metadata to organize your Tensorboards. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Tensorboard (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	Project  pulumi.StringPtrInput
}

The set of arguments for constructing a Tensorboard resource.

func (TensorboardArgs) ElementType 

func (TensorboardArgs) ElementType() reflect.Type

type TensorboardInput 

type TensorboardInput interface {
	pulumi.Input

	ToTensorboardOutput() TensorboardOutput
	ToTensorboardOutputWithContext(ctx context.Context) TensorboardOutput
}

type TensorboardOutput 

type TensorboardOutput struct{ *pulumi.OutputState }

func (TensorboardOutput) BlobStoragePathPrefix 

func (o TensorboardOutput) BlobStoragePathPrefix() pulumi.StringOutput

Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.

func (TensorboardOutput) CreateTime 

func (o TensorboardOutput) CreateTime() pulumi.StringOutput

Timestamp when this Tensorboard was created.

func (TensorboardOutput) Description 

func (o TensorboardOutput) Description() pulumi.StringOutput

Description of this Tensorboard.

func (TensorboardOutput) DisplayName 

func (o TensorboardOutput) DisplayName() pulumi.StringOutput

User provided name of this Tensorboard.

func (TensorboardOutput) ElementType 

func (TensorboardOutput) ElementType() reflect.Type

func (TensorboardOutput) EncryptionSpec 

func (o TensorboardOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key.

func (TensorboardOutput) Etag 

func (o TensorboardOutput) Etag() pulumi.StringOutput

Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (TensorboardOutput) IsDefault 

func (o TensorboardOutput) IsDefault() pulumi.BoolOutput

Used to indicate if the TensorBoard instance is the default one. Each project & region can have at most one default TensorBoard instance. Creation of a default TensorBoard instance and updating an existing TensorBoard instance to be default will mark all other TensorBoard instances (if any) as non default.

func (TensorboardOutput) Labels 

func (o TensorboardOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize your Tensorboards. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Tensorboard (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

func (TensorboardOutput) Location 

func (o TensorboardOutput) Location() pulumi.StringOutput

func (TensorboardOutput) Name 

func (o TensorboardOutput) Name() pulumi.StringOutput

Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`

func (TensorboardOutput) Project 

func (o TensorboardOutput) Project() pulumi.StringOutput

func (TensorboardOutput) RunCount 

func (o TensorboardOutput) RunCount() pulumi.IntOutput

The number of Runs stored in this Tensorboard.

func (TensorboardOutput) ToTensorboardOutput 

func (o TensorboardOutput) ToTensorboardOutput() TensorboardOutput

func (TensorboardOutput) ToTensorboardOutputWithContext 

func (o TensorboardOutput) ToTensorboardOutputWithContext(ctx context.Context) TensorboardOutput

func (TensorboardOutput) UpdateTime 

func (o TensorboardOutput) UpdateTime() pulumi.StringOutput

Timestamp when this Tensorboard was last updated.

type TensorboardState 

type TensorboardState struct {
}

func (TensorboardState) ElementType 

func (TensorboardState) ElementType() reflect.Type

type TimeSeries 

type TimeSeries struct {
	pulumi.CustomResourceState

	// Timestamp when this TensorboardTimeSeries was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// Description of this TensorboardTimeSeries.
	Description pulumi.StringOutput `pulumi:"description"`
	// User provided name of this TensorboardTimeSeries. This value should be unique among all TensorboardTimeSeries resources belonging to the same TensorboardRun resource (parent resource).
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag         pulumi.StringOutput `pulumi:"etag"`
	ExperimentId pulumi.StringOutput `pulumi:"experimentId"`
	Location     pulumi.StringOutput `pulumi:"location"`
	// Scalar, Tensor, or Blob metadata for this TensorboardTimeSeries.
	Metadata GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput `pulumi:"metadata"`
	// Name of the TensorboardTimeSeries.
	Name pulumi.StringOutput `pulumi:"name"`
	// Data of the current plugin, with the size limited to 65KB.
	PluginData pulumi.StringOutput `pulumi:"pluginData"`
	// Immutable. Name of the plugin this time series pertain to. Such as Scalar, Tensor, Blob
	PluginName    pulumi.StringOutput `pulumi:"pluginName"`
	Project       pulumi.StringOutput `pulumi:"project"`
	RunId         pulumi.StringOutput `pulumi:"runId"`
	TensorboardId pulumi.StringOutput `pulumi:"tensorboardId"`
	// Optional. The user specified unique ID to use for the TensorboardTimeSeries, which becomes the final component of the TensorboardTimeSeries's resource name. This value should match "a-z0-9{0, 127}"
	TensorboardTimeSeriesId pulumi.StringPtrOutput `pulumi:"tensorboardTimeSeriesId"`
	// Timestamp when this TensorboardTimeSeries was last updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
	// Immutable. Type of TensorboardTimeSeries value.
	ValueType pulumi.StringOutput `pulumi:"valueType"`
}

Creates a TensorboardTimeSeries. Auto-naming is currently not supported for this resource.

func GetTimeSeries 

func GetTimeSeries(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *TimeSeriesState, opts ...pulumi.ResourceOption) (*TimeSeries, error)

GetTimeSeries gets an existing TimeSeries resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewTimeSeries 

func NewTimeSeries(ctx *pulumi.Context,
	name string, args *TimeSeriesArgs, opts ...pulumi.ResourceOption) (*TimeSeries, error)

NewTimeSeries registers a new resource with the given unique name, arguments, and options.

func (*TimeSeries) ElementType 

func (*TimeSeries) ElementType() reflect.Type

func (*TimeSeries) ToTimeSeriesOutput 

func (i *TimeSeries) ToTimeSeriesOutput() TimeSeriesOutput

func (*TimeSeries) ToTimeSeriesOutputWithContext 

func (i *TimeSeries) ToTimeSeriesOutputWithContext(ctx context.Context) TimeSeriesOutput

type TimeSeriesArgs 

type TimeSeriesArgs struct {
	// Description of this TensorboardTimeSeries.
	Description pulumi.StringPtrInput
	// User provided name of this TensorboardTimeSeries. This value should be unique among all TensorboardTimeSeries resources belonging to the same TensorboardRun resource (parent resource).
	DisplayName pulumi.StringInput
	// Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
	Etag         pulumi.StringPtrInput
	ExperimentId pulumi.StringInput
	Location     pulumi.StringPtrInput
	// Data of the current plugin, with the size limited to 65KB.
	PluginData pulumi.StringPtrInput
	// Immutable. Name of the plugin this time series pertain to. Such as Scalar, Tensor, Blob
	PluginName    pulumi.StringPtrInput
	Project       pulumi.StringPtrInput
	RunId         pulumi.StringInput
	TensorboardId pulumi.StringInput
	// Optional. The user specified unique ID to use for the TensorboardTimeSeries, which becomes the final component of the TensorboardTimeSeries's resource name. This value should match "a-z0-9{0, 127}"
	TensorboardTimeSeriesId pulumi.StringPtrInput
	// Immutable. Type of TensorboardTimeSeries value.
	ValueType TimeSeriesValueTypeInput
}

The set of arguments for constructing a TimeSeries resource.

func (TimeSeriesArgs) ElementType 

func (TimeSeriesArgs) ElementType() reflect.Type

type TimeSeriesInput 

type TimeSeriesInput interface {
	pulumi.Input

	ToTimeSeriesOutput() TimeSeriesOutput
	ToTimeSeriesOutputWithContext(ctx context.Context) TimeSeriesOutput
}

type TimeSeriesOutput 

type TimeSeriesOutput struct{ *pulumi.OutputState }

func (TimeSeriesOutput) CreateTime 

func (o TimeSeriesOutput) CreateTime() pulumi.StringOutput

Timestamp when this TensorboardTimeSeries was created.

func (TimeSeriesOutput) Description 

func (o TimeSeriesOutput) Description() pulumi.StringOutput

Description of this TensorboardTimeSeries.

func (TimeSeriesOutput) DisplayName 

func (o TimeSeriesOutput) DisplayName() pulumi.StringOutput

User provided name of this TensorboardTimeSeries. This value should be unique among all TensorboardTimeSeries resources belonging to the same TensorboardRun resource (parent resource).

func (TimeSeriesOutput) ElementType 

func (TimeSeriesOutput) ElementType() reflect.Type

func (TimeSeriesOutput) Etag 

func (o TimeSeriesOutput) Etag() pulumi.StringOutput

Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

func (TimeSeriesOutput) ExperimentId 

func (o TimeSeriesOutput) ExperimentId() pulumi.StringOutput

func (TimeSeriesOutput) Location 

func (o TimeSeriesOutput) Location() pulumi.StringOutput

func (TimeSeriesOutput) Metadata 

func (o TimeSeriesOutput) Metadata() GoogleCloudAiplatformV1TensorboardTimeSeriesMetadataResponseOutput

Scalar, Tensor, or Blob metadata for this TensorboardTimeSeries.

func (TimeSeriesOutput) Name 

func (o TimeSeriesOutput) Name() pulumi.StringOutput

Name of the TensorboardTimeSeries.

func (TimeSeriesOutput) PluginData 

func (o TimeSeriesOutput) PluginData() pulumi.StringOutput

Data of the current plugin, with the size limited to 65KB.

func (TimeSeriesOutput) PluginName 

func (o TimeSeriesOutput) PluginName() pulumi.StringOutput

Immutable. Name of the plugin this time series pertain to. Such as Scalar, Tensor, Blob

func (TimeSeriesOutput) Project 

func (o TimeSeriesOutput) Project() pulumi.StringOutput

func (TimeSeriesOutput) RunId 

func (o TimeSeriesOutput) RunId() pulumi.StringOutput

func (TimeSeriesOutput) TensorboardId 

func (o TimeSeriesOutput) TensorboardId() pulumi.StringOutput

func (TimeSeriesOutput) TensorboardTimeSeriesId 

func (o TimeSeriesOutput) TensorboardTimeSeriesId() pulumi.StringPtrOutput

Optional. The user specified unique ID to use for the TensorboardTimeSeries, which becomes the final component of the TensorboardTimeSeries's resource name. This value should match "a-z0-9{0, 127}"

func (TimeSeriesOutput) ToTimeSeriesOutput 

func (o TimeSeriesOutput) ToTimeSeriesOutput() TimeSeriesOutput

func (TimeSeriesOutput) ToTimeSeriesOutputWithContext 

func (o TimeSeriesOutput) ToTimeSeriesOutputWithContext(ctx context.Context) TimeSeriesOutput

func (TimeSeriesOutput) UpdateTime 

func (o TimeSeriesOutput) UpdateTime() pulumi.StringOutput

Timestamp when this TensorboardTimeSeries was last updated.

func (TimeSeriesOutput) ValueType 

func (o TimeSeriesOutput) ValueType() pulumi.StringOutput

Immutable. Type of TensorboardTimeSeries value.

type TimeSeriesState 

type TimeSeriesState struct {
}

func (TimeSeriesState) ElementType 

func (TimeSeriesState) ElementType() reflect.Type

type TimeSeriesValueType 

type TimeSeriesValueType string

Required. Immutable. Type of TensorboardTimeSeries value.

func (TimeSeriesValueType) ElementType 

func (TimeSeriesValueType) ElementType() reflect.Type

func (TimeSeriesValueType) ToStringOutput 

func (e TimeSeriesValueType) ToStringOutput() pulumi.StringOutput

func (TimeSeriesValueType) ToStringOutputWithContext 

func (e TimeSeriesValueType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (TimeSeriesValueType) ToStringPtrOutput 

func (e TimeSeriesValueType) ToStringPtrOutput() pulumi.StringPtrOutput

func (TimeSeriesValueType) ToStringPtrOutputWithContext 

func (e TimeSeriesValueType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

func (TimeSeriesValueType) ToTimeSeriesValueTypeOutput 

func (e TimeSeriesValueType) ToTimeSeriesValueTypeOutput() TimeSeriesValueTypeOutput

func (TimeSeriesValueType) ToTimeSeriesValueTypeOutputWithContext 

func (e TimeSeriesValueType) ToTimeSeriesValueTypeOutputWithContext(ctx context.Context) TimeSeriesValueTypeOutput

func (TimeSeriesValueType) ToTimeSeriesValueTypePtrOutput 

func (e TimeSeriesValueType) ToTimeSeriesValueTypePtrOutput() TimeSeriesValueTypePtrOutput

func (TimeSeriesValueType) ToTimeSeriesValueTypePtrOutputWithContext 

func (e TimeSeriesValueType) ToTimeSeriesValueTypePtrOutputWithContext(ctx context.Context) TimeSeriesValueTypePtrOutput

type TimeSeriesValueTypeInput 

type TimeSeriesValueTypeInput interface {
	pulumi.Input

	ToTimeSeriesValueTypeOutput() TimeSeriesValueTypeOutput
	ToTimeSeriesValueTypeOutputWithContext(context.Context) TimeSeriesValueTypeOutput
}

TimeSeriesValueTypeInput is an input type that accepts TimeSeriesValueTypeArgs and TimeSeriesValueTypeOutput values. You can construct a concrete instance of `TimeSeriesValueTypeInput` via: 

TimeSeriesValueTypeArgs{...}

type TimeSeriesValueTypeOutput 

type TimeSeriesValueTypeOutput struct{ *pulumi.OutputState }

func (TimeSeriesValueTypeOutput) ElementType 

func (TimeSeriesValueTypeOutput) ElementType() reflect.Type

func (TimeSeriesValueTypeOutput) ToStringOutput 

func (o TimeSeriesValueTypeOutput) ToStringOutput() pulumi.StringOutput

func (TimeSeriesValueTypeOutput) ToStringOutputWithContext 

func (o TimeSeriesValueTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (TimeSeriesValueTypeOutput) ToStringPtrOutput 

func (o TimeSeriesValueTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (TimeSeriesValueTypeOutput) ToStringPtrOutputWithContext 

func (o TimeSeriesValueTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

func (TimeSeriesValueTypeOutput) ToTimeSeriesValueTypeOutput 

func (o TimeSeriesValueTypeOutput) ToTimeSeriesValueTypeOutput() TimeSeriesValueTypeOutput

func (TimeSeriesValueTypeOutput) ToTimeSeriesValueTypeOutputWithContext 

func (o TimeSeriesValueTypeOutput) ToTimeSeriesValueTypeOutputWithContext(ctx context.Context) TimeSeriesValueTypeOutput

func (TimeSeriesValueTypeOutput) ToTimeSeriesValueTypePtrOutput 

func (o TimeSeriesValueTypeOutput) ToTimeSeriesValueTypePtrOutput() TimeSeriesValueTypePtrOutput

func (TimeSeriesValueTypeOutput) ToTimeSeriesValueTypePtrOutputWithContext 

func (o TimeSeriesValueTypeOutput) ToTimeSeriesValueTypePtrOutputWithContext(ctx context.Context) TimeSeriesValueTypePtrOutput

type TimeSeriesValueTypePtrInput 

type TimeSeriesValueTypePtrInput interface {
	pulumi.Input

	ToTimeSeriesValueTypePtrOutput() TimeSeriesValueTypePtrOutput
	ToTimeSeriesValueTypePtrOutputWithContext(context.Context) TimeSeriesValueTypePtrOutput
}

func TimeSeriesValueTypePtr 

func TimeSeriesValueTypePtr(v string) TimeSeriesValueTypePtrInput

type TimeSeriesValueTypePtrOutput 

type TimeSeriesValueTypePtrOutput struct{ *pulumi.OutputState }

func (TimeSeriesValueTypePtrOutput) Elem 

func (o TimeSeriesValueTypePtrOutput) Elem() TimeSeriesValueTypeOutput

func (TimeSeriesValueTypePtrOutput) ElementType 

func (TimeSeriesValueTypePtrOutput) ElementType() reflect.Type

func (TimeSeriesValueTypePtrOutput) ToStringPtrOutput 

func (o TimeSeriesValueTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (TimeSeriesValueTypePtrOutput) ToStringPtrOutputWithContext 

func (o TimeSeriesValueTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

func (TimeSeriesValueTypePtrOutput) ToTimeSeriesValueTypePtrOutput 

func (o TimeSeriesValueTypePtrOutput) ToTimeSeriesValueTypePtrOutput() TimeSeriesValueTypePtrOutput

func (TimeSeriesValueTypePtrOutput) ToTimeSeriesValueTypePtrOutputWithContext 

func (o TimeSeriesValueTypePtrOutput) ToTimeSeriesValueTypePtrOutputWithContext(ctx context.Context) TimeSeriesValueTypePtrOutput

type TrainingPipeline 

type TrainingPipeline struct {
	pulumi.CustomResourceState

	// Time when the TrainingPipeline was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// The user-defined name of this TrainingPipeline.
	DisplayName pulumi.StringOutput `pulumi:"displayName"`
	// Customer-managed encryption key spec for a TrainingPipeline. If set, this TrainingPipeline will be secured by this key. Note: Model trained by this TrainingPipeline is also secured by this key if model_to_upload is not set separately.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecResponseOutput `pulumi:"encryptionSpec"`
	// Time when the TrainingPipeline entered any of the following states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`, `PIPELINE_STATE_CANCELLED`.
	EndTime pulumi.StringOutput `pulumi:"endTime"`
	// Only populated when the pipeline's state is `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.
	Error GoogleRpcStatusResponseOutput `pulumi:"error"`
	// Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's training_task_definition should make clear whether this config is used and if there are any special requirements on how it should be filled. If nothing about this config is mentioned in the training_task_definition, then it should be assumed that the TrainingPipeline does not depend on this configuration.
	InputDataConfig GoogleCloudAiplatformV1InputDataConfigResponseOutput `pulumi:"inputDataConfig"`
	// The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapOutput `pulumi:"labels"`
	Location pulumi.StringOutput    `pulumi:"location"`
	// Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen.
	ModelId pulumi.StringOutput `pulumi:"modelId"`
	// Describes the Model that may be uploaded (via ModelService.UploadModel) by this TrainingPipeline. The TrainingPipeline's training_task_definition should make clear whether this Model description should be populated, and if there are any special requirements regarding how it should be filled. If nothing is mentioned in the training_task_definition, then it should be assumed that this field should not be filled and the training task either uploads the Model without a need of this information, or that training task does not support uploading a Model as part of the pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and the trained Model had been uploaded into Vertex AI, then the model_to_upload's resource name is populated. The Model is always uploaded into the Project and Location in which this pipeline is.
	ModelToUpload GoogleCloudAiplatformV1ModelResponseOutput `pulumi:"modelToUpload"`
	// Resource name of the TrainingPipeline.
	Name pulumi.StringOutput `pulumi:"name"`
	// Optional. When specify this field, the `model_to_upload` will not be uploaded as a new model, instead, it will become a new version of this `parent_model`.
	ParentModel pulumi.StringOutput `pulumi:"parentModel"`
	Project     pulumi.StringOutput `pulumi:"project"`
	// Time when the TrainingPipeline for the first time entered the `PIPELINE_STATE_RUNNING` state.
	StartTime pulumi.StringOutput `pulumi:"startTime"`
	// The detailed state of the pipeline.
	State pulumi.StringOutput `pulumi:"state"`
	// A Google Cloud Storage path to the YAML file that defines the training task which is responsible for producing the model artifact, and may also include additional auxiliary work. The definition files that can be used here are found in gs://google-cloud-aiplatform/schema/trainingjob/definition/. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	TrainingTaskDefinition pulumi.StringOutput `pulumi:"trainingTaskDefinition"`
	// The training task's parameter(s), as specified in the training_task_definition's `inputs`.
	TrainingTaskInputs pulumi.AnyOutput `pulumi:"trainingTaskInputs"`
	// The metadata information as specified in the training_task_definition's `metadata`. This metadata is an auxiliary runtime and final information about the training task. While the pipeline is running this information is populated only at a best effort basis. Only present if the pipeline's training_task_definition contains `metadata` object.
	TrainingTaskMetadata pulumi.AnyOutput `pulumi:"trainingTaskMetadata"`
	// Time when the TrainingPipeline was most recently updated.
	UpdateTime pulumi.StringOutput `pulumi:"updateTime"`
}

Creates a TrainingPipeline. A created TrainingPipeline right away will be attempted to be run. Auto-naming is currently not supported for this resource.

func GetTrainingPipeline 

func GetTrainingPipeline(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *TrainingPipelineState, opts ...pulumi.ResourceOption) (*TrainingPipeline, error)

GetTrainingPipeline gets an existing TrainingPipeline resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewTrainingPipeline 

func NewTrainingPipeline(ctx *pulumi.Context,
	name string, args *TrainingPipelineArgs, opts ...pulumi.ResourceOption) (*TrainingPipeline, error)

NewTrainingPipeline registers a new resource with the given unique name, arguments, and options.

func (*TrainingPipeline) ElementType 

func (*TrainingPipeline) ElementType() reflect.Type

func (*TrainingPipeline) ToTrainingPipelineOutput 

func (i *TrainingPipeline) ToTrainingPipelineOutput() TrainingPipelineOutput

func (*TrainingPipeline) ToTrainingPipelineOutputWithContext 

func (i *TrainingPipeline) ToTrainingPipelineOutputWithContext(ctx context.Context) TrainingPipelineOutput

type TrainingPipelineArgs 

type TrainingPipelineArgs struct {
	// The user-defined name of this TrainingPipeline.
	DisplayName pulumi.StringInput
	// Customer-managed encryption key spec for a TrainingPipeline. If set, this TrainingPipeline will be secured by this key. Note: Model trained by this TrainingPipeline is also secured by this key if model_to_upload is not set separately.
	EncryptionSpec GoogleCloudAiplatformV1EncryptionSpecPtrInput
	// Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's training_task_definition should make clear whether this config is used and if there are any special requirements on how it should be filled. If nothing about this config is mentioned in the training_task_definition, then it should be assumed that the TrainingPipeline does not depend on this configuration.
	InputDataConfig GoogleCloudAiplatformV1InputDataConfigPtrInput
	// The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
	Labels   pulumi.StringMapInput
	Location pulumi.StringPtrInput
	// Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen.
	ModelId pulumi.StringPtrInput
	// Describes the Model that may be uploaded (via ModelService.UploadModel) by this TrainingPipeline. The TrainingPipeline's training_task_definition should make clear whether this Model description should be populated, and if there are any special requirements regarding how it should be filled. If nothing is mentioned in the training_task_definition, then it should be assumed that this field should not be filled and the training task either uploads the Model without a need of this information, or that training task does not support uploading a Model as part of the pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and the trained Model had been uploaded into Vertex AI, then the model_to_upload's resource name is populated. The Model is always uploaded into the Project and Location in which this pipeline is.
	ModelToUpload GoogleCloudAiplatformV1ModelPtrInput
	// Optional. When specify this field, the `model_to_upload` will not be uploaded as a new model, instead, it will become a new version of this `parent_model`.
	ParentModel pulumi.StringPtrInput
	Project     pulumi.StringPtrInput
	// A Google Cloud Storage path to the YAML file that defines the training task which is responsible for producing the model artifact, and may also include additional auxiliary work. The definition files that can be used here are found in gs://google-cloud-aiplatform/schema/trainingjob/definition/. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
	TrainingTaskDefinition pulumi.StringInput
	// The training task's parameter(s), as specified in the training_task_definition's `inputs`.
	TrainingTaskInputs pulumi.Input
}

The set of arguments for constructing a TrainingPipeline resource.

func (TrainingPipelineArgs) ElementType 

func (TrainingPipelineArgs) ElementType() reflect.Type

type TrainingPipelineInput 

type TrainingPipelineInput interface {
	pulumi.Input

	ToTrainingPipelineOutput() TrainingPipelineOutput
	ToTrainingPipelineOutputWithContext(ctx context.Context) TrainingPipelineOutput
}

type TrainingPipelineOutput 

type TrainingPipelineOutput struct{ *pulumi.OutputState }

func (TrainingPipelineOutput) CreateTime 

func (o TrainingPipelineOutput) CreateTime() pulumi.StringOutput

Time when the TrainingPipeline was created.

func (TrainingPipelineOutput) DisplayName 

func (o TrainingPipelineOutput) DisplayName() pulumi.StringOutput

The user-defined name of this TrainingPipeline.

func (TrainingPipelineOutput) ElementType 

func (TrainingPipelineOutput) ElementType() reflect.Type

func (TrainingPipelineOutput) EncryptionSpec 

func (o TrainingPipelineOutput) EncryptionSpec() GoogleCloudAiplatformV1EncryptionSpecResponseOutput

Customer-managed encryption key spec for a TrainingPipeline. If set, this TrainingPipeline will be secured by this key. Note: Model trained by this TrainingPipeline is also secured by this key if model_to_upload is not set separately.

func (TrainingPipelineOutput) EndTime 

func (o TrainingPipelineOutput) EndTime() pulumi.StringOutput

Time when the TrainingPipeline entered any of the following states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`, `PIPELINE_STATE_CANCELLED`.

func (TrainingPipelineOutput) Error 

func (o TrainingPipelineOutput) Error() GoogleRpcStatusResponseOutput

Only populated when the pipeline's state is `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`.

func (TrainingPipelineOutput) InputDataConfig 

func (o TrainingPipelineOutput) InputDataConfig() GoogleCloudAiplatformV1InputDataConfigResponseOutput

Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's training_task_definition should make clear whether this config is used and if there are any special requirements on how it should be filled. If nothing about this config is mentioned in the training_task_definition, then it should be assumed that the TrainingPipeline does not depend on this configuration.

func (TrainingPipelineOutput) Labels 

func (o TrainingPipelineOutput) Labels() pulumi.StringMapOutput

The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

func (TrainingPipelineOutput) Location 

func (o TrainingPipelineOutput) Location() pulumi.StringOutput

func (TrainingPipelineOutput) ModelId 

func (o TrainingPipelineOutput) ModelId() pulumi.StringOutput

Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen.

func (TrainingPipelineOutput) ModelToUpload 

func (o TrainingPipelineOutput) ModelToUpload() GoogleCloudAiplatformV1ModelResponseOutput

Describes the Model that may be uploaded (via ModelService.UploadModel) by this TrainingPipeline. The TrainingPipeline's training_task_definition should make clear whether this Model description should be populated, and if there are any special requirements regarding how it should be filled. If nothing is mentioned in the training_task_definition, then it should be assumed that this field should not be filled and the training task either uploads the Model without a need of this information, or that training task does not support uploading a Model as part of the pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and the trained Model had been uploaded into Vertex AI, then the model_to_upload's resource name is populated. The Model is always uploaded into the Project and Location in which this pipeline is.

func (TrainingPipelineOutput) Name 

func (o TrainingPipelineOutput) Name() pulumi.StringOutput

Resource name of the TrainingPipeline.

func (TrainingPipelineOutput) ParentModel 

func (o TrainingPipelineOutput) ParentModel() pulumi.StringOutput

Optional. When specify this field, the `model_to_upload` will not be uploaded as a new model, instead, it will become a new version of this `parent_model`.

func (TrainingPipelineOutput) Project 

func (o TrainingPipelineOutput) Project() pulumi.StringOutput

func (TrainingPipelineOutput) StartTime 

func (o TrainingPipelineOutput) StartTime() pulumi.StringOutput

Time when the TrainingPipeline for the first time entered the `PIPELINE_STATE_RUNNING` state.

func (TrainingPipelineOutput) State 

func (o TrainingPipelineOutput) State() pulumi.StringOutput

The detailed state of the pipeline.

func (TrainingPipelineOutput) ToTrainingPipelineOutput 

func (o TrainingPipelineOutput) ToTrainingPipelineOutput() TrainingPipelineOutput

func (TrainingPipelineOutput) ToTrainingPipelineOutputWithContext 

func (o TrainingPipelineOutput) ToTrainingPipelineOutputWithContext(ctx context.Context) TrainingPipelineOutput

func (TrainingPipelineOutput) TrainingTaskDefinition 

func (o TrainingPipelineOutput) TrainingTaskDefinition() pulumi.StringOutput

A Google Cloud Storage path to the YAML file that defines the training task which is responsible for producing the model artifact, and may also include additional auxiliary work. The definition files that can be used here are found in gs://google-cloud-aiplatform/schema/trainingjob/definition/. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.

func (TrainingPipelineOutput) TrainingTaskInputs 

func (o TrainingPipelineOutput) TrainingTaskInputs() pulumi.AnyOutput

The training task's parameter(s), as specified in the training_task_definition's `inputs`.

func (TrainingPipelineOutput) TrainingTaskMetadata 

func (o TrainingPipelineOutput) TrainingTaskMetadata() pulumi.AnyOutput

The metadata information as specified in the training_task_definition's `metadata`. This metadata is an auxiliary runtime and final information about the training task. While the pipeline is running this information is populated only at a best effort basis. Only present if the pipeline's training_task_definition contains `metadata` object.

func (TrainingPipelineOutput) UpdateTime 

func (o TrainingPipelineOutput) UpdateTime() pulumi.StringOutput

Time when the TrainingPipeline was most recently updated.

type TrainingPipelineState 

type TrainingPipelineState struct {
}

func (TrainingPipelineState) ElementType 

func (TrainingPipelineState) ElementType() reflect.Type

type Trial 

type Trial struct {
	pulumi.CustomResourceState

	// The identifier of the client that originally requested this Trial. Each client is identified by a unique client_id. When a client asks for a suggestion, Vertex AI Vizier will assign it a Trial. The client should evaluate the Trial, complete it, and report back to Vertex AI Vizier. If suggestion is asked again by same client_id before the Trial is completed, the same Trial will be returned. Multiple clients with different client_ids can ask for suggestions simultaneously, each of them will get their own Trial.
	ClientId pulumi.StringOutput `pulumi:"clientId"`
	// The CustomJob name linked to the Trial. It's set for a HyperparameterTuningJob's Trial.
	CustomJob pulumi.StringOutput `pulumi:"customJob"`
	// Time when the Trial's status changed to `SUCCEEDED` or `INFEASIBLE`.
	EndTime pulumi.StringOutput `pulumi:"endTime"`
	// The final measurement containing the objective value.
	FinalMeasurement GoogleCloudAiplatformV1MeasurementResponseOutput `pulumi:"finalMeasurement"`
	// A human readable string describing why the Trial is infeasible. This is set only if Trial state is `INFEASIBLE`.
	InfeasibleReason pulumi.StringOutput `pulumi:"infeasibleReason"`
	Location         pulumi.StringOutput `pulumi:"location"`
	// A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_duration). These are used for early stopping computations.
	Measurements GoogleCloudAiplatformV1MeasurementResponseArrayOutput `pulumi:"measurements"`
	// Resource name of the Trial assigned by the service.
	Name pulumi.StringOutput `pulumi:"name"`
	// The parameters of the Trial.
	Parameters GoogleCloudAiplatformV1TrialParameterResponseArrayOutput `pulumi:"parameters"`
	Project    pulumi.StringOutput                                      `pulumi:"project"`
	// Time when the Trial was started.
	StartTime pulumi.StringOutput `pulumi:"startTime"`
	// The detailed state of the Trial.
	State   pulumi.StringOutput `pulumi:"state"`
	StudyId pulumi.StringOutput `pulumi:"studyId"`
	// URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a HyperparameterTuningJob and the job's trial_job_spec.enable_web_access field is `true`. The keys are names of each node used for the trial; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.
	WebAccessUris pulumi.StringMapOutput `pulumi:"webAccessUris"`
}

Adds a user provided Trial to a Study. Auto-naming is currently not supported for this resource.

func GetTrial 

func GetTrial(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *TrialState, opts ...pulumi.ResourceOption) (*Trial, error)

GetTrial gets an existing Trial resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewTrial 

func NewTrial(ctx *pulumi.Context,
	name string, args *TrialArgs, opts ...pulumi.ResourceOption) (*Trial, error)

NewTrial registers a new resource with the given unique name, arguments, and options.

func (*Trial) ElementType 

func (*Trial) ElementType() reflect.Type

func (*Trial) ToTrialOutput 

func (i *Trial) ToTrialOutput() TrialOutput

func (*Trial) ToTrialOutputWithContext 

func (i *Trial) ToTrialOutputWithContext(ctx context.Context) TrialOutput

type TrialArgs 

type TrialArgs struct {
	Location pulumi.StringPtrInput
	Project  pulumi.StringPtrInput
	StudyId  pulumi.StringInput
}

The set of arguments for constructing a Trial resource.

func (TrialArgs) ElementType 

func (TrialArgs) ElementType() reflect.Type

type TrialInput 

type TrialInput interface {
	pulumi.Input

	ToTrialOutput() TrialOutput
	ToTrialOutputWithContext(ctx context.Context) TrialOutput
}

type TrialOutput 

type TrialOutput struct{ *pulumi.OutputState }

func (TrialOutput) ClientId 

func (o TrialOutput) ClientId() pulumi.StringOutput

The identifier of the client that originally requested this Trial. Each client is identified by a unique client_id. When a client asks for a suggestion, Vertex AI Vizier will assign it a Trial. The client should evaluate the Trial, complete it, and report back to Vertex AI Vizier. If suggestion is asked again by same client_id before the Trial is completed, the same Trial will be returned. Multiple clients with different client_ids can ask for suggestions simultaneously, each of them will get their own Trial.

func (TrialOutput) CustomJob 

func (o TrialOutput) CustomJob() pulumi.StringOutput

The CustomJob name linked to the Trial. It's set for a HyperparameterTuningJob's Trial.

func (TrialOutput) ElementType 

func (TrialOutput) ElementType() reflect.Type

func (TrialOutput) EndTime 

func (o TrialOutput) EndTime() pulumi.StringOutput

Time when the Trial's status changed to `SUCCEEDED` or `INFEASIBLE`.

func (TrialOutput) FinalMeasurement 

func (o TrialOutput) FinalMeasurement() GoogleCloudAiplatformV1MeasurementResponseOutput

The final measurement containing the objective value.

func (TrialOutput) InfeasibleReason 

func (o TrialOutput) InfeasibleReason() pulumi.StringOutput

A human readable string describing why the Trial is infeasible. This is set only if Trial state is `INFEASIBLE`.

func (TrialOutput) Location 

func (o TrialOutput) Location() pulumi.StringOutput

func (TrialOutput) Measurements 

func (o TrialOutput) Measurements() GoogleCloudAiplatformV1MeasurementResponseArrayOutput

A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_duration). These are used for early stopping computations.

func (TrialOutput) Name 

func (o TrialOutput) Name() pulumi.StringOutput

Resource name of the Trial assigned by the service.

func (TrialOutput) Parameters 

func (o TrialOutput) Parameters() GoogleCloudAiplatformV1TrialParameterResponseArrayOutput

The parameters of the Trial.

func (TrialOutput) Project 

func (o TrialOutput) Project() pulumi.StringOutput

func (TrialOutput) StartTime 

func (o TrialOutput) StartTime() pulumi.StringOutput

Time when the Trial was started.

func (TrialOutput) State 

func (o TrialOutput) State() pulumi.StringOutput

The detailed state of the Trial.

func (TrialOutput) StudyId 

func (o TrialOutput) StudyId() pulumi.StringOutput

func (TrialOutput) ToTrialOutput 

func (o TrialOutput) ToTrialOutput() TrialOutput

func (TrialOutput) ToTrialOutputWithContext 

func (o TrialOutput) ToTrialOutputWithContext(ctx context.Context) TrialOutput

func (TrialOutput) WebAccessUris 

func (o TrialOutput) WebAccessUris() pulumi.StringMapOutput

URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a HyperparameterTuningJob and the job's trial_job_spec.enable_web_access field is `true`. The keys are names of each node used for the trial; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell.

type TrialState 

type TrialState struct {
}

func (TrialState) ElementType 

func (TrialState) ElementType() reflect.Type

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