v1alpha1

package
v1.130.2 Latest Latest
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 Go to latest Published: Apr 4, 2025 License: Apache-2.0 Imports: 15 Imported by: 0

Documentation

Overview

+kcc:proto=google.cloud.aiplatform.v1

+kubebuilder:object:generate=true +groupName=aiplatform.cnrm.cloud.google.com

Index

Constants

View Source 
const (
	// Null value.
	NullValue_NULL_VALUE     int = 0
	StringValue_STRING_VALUE int = 1
	NumberValue_NUMBER_VALUE int = 2
	BoolValue_BOOL_VALUE     int = 3
	StructValue_STRUCT_VALUE int = 4
	ListValue_LIST_VALUE     int = 5
)

Variables

View Source 
var (
	// GroupVersion is group version used to register these objects
	GroupVersion = schema.GroupVersion{Group: "aiplatform.cnrm.cloud.google.com", Version: "v1alpha1"}

	// SchemeBuilder is used to add go types to the GroupVersionKind scheme
	SchemeBuilder = &scheme.Builder{GroupVersion: GroupVersion}

	// AddToScheme adds the types in this group-version to the given scheme.
	AddToScheme = SchemeBuilder.AddToScheme
)
View Source 
var AIPlatformModelGVK = GroupVersion.WithKind("AIPlatformModel")

Functions

This section is empty.

Types

type AIPlatformModel 

type AIPlatformModel struct {
	metav1.TypeMeta   `json:",inline"`
	metav1.ObjectMeta `json:"metadata,omitempty"`

	// +required
	Spec   AIPlatformModelSpec   `json:"spec,omitempty"`
	Status AIPlatformModelStatus `json:"status,omitempty"`
}

AIPlatformModel is the Schema for the AIPlatformModel API +k8s:openapi-gen=true

func (*AIPlatformModel) DeepCopy 

func (in *AIPlatformModel) DeepCopy() *AIPlatformModel

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new AIPlatformModel.

func (*AIPlatformModel) DeepCopyInto 

func (in *AIPlatformModel) DeepCopyInto(out *AIPlatformModel)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

func (*AIPlatformModel) DeepCopyObject 

func (in *AIPlatformModel) DeepCopyObject() runtime.Object

DeepCopyObject is an autogenerated deepcopy function, copying the receiver, creating a new runtime.Object.

type AIPlatformModelList 

type AIPlatformModelList struct {
	metav1.TypeMeta `json:",inline"`
	metav1.ListMeta `json:"metadata,omitempty"`
	Items           []AIPlatformModel `json:"items"`
}

+k8s:deepcopy-gen:interfaces=k8s.io/apimachinery/pkg/runtime.Object AIPlatformModelList contains a list of AIPlatformModel

func (*AIPlatformModelList) DeepCopy 

func (in *AIPlatformModelList) DeepCopy() *AIPlatformModelList

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new AIPlatformModelList.

func (*AIPlatformModelList) DeepCopyInto 

func (in *AIPlatformModelList) DeepCopyInto(out *AIPlatformModelList)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

func (*AIPlatformModelList) DeepCopyObject 

func (in *AIPlatformModelList) DeepCopyObject() runtime.Object

DeepCopyObject is an autogenerated deepcopy function, copying the receiver, creating a new runtime.Object.

type AIPlatformModelObservedState 

type AIPlatformModelObservedState struct {
	// Output only. 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.version_id
	VersionID *string `json:"versionID,omitempty"`

	// Output only. Timestamp when this version was created.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.version_create_time
	VersionCreateTime *string `json:"versionCreateTime,omitempty"`

	// Output only. Timestamp when this version was most recently updated.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.version_update_time
	VersionUpdateTime *string `json:"versionUpdateTime,omitempty"`

	// Output only. The formats in which this Model may be exported. If empty,
	//  this Model is not available for export.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.supported_export_formats
	SupportedExportFormats []Model_ExportFormat `json:"supportedExportFormats,omitempty"`

	// Output only. The resource name of the TrainingPipeline that uploaded this
	//  Model, if any.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.training_pipeline
	TrainingPipeline *string `json:"trainingPipeline,omitempty"`

	// Output only. When this Model is deployed, its prediction resources are
	//  described by the `prediction_resources` field of the
	//  [Endpoint.deployed_models][google.cloud.aiplatform.v1.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][google.cloud.aiplatform.v1.Endpoint] and does not support
	//  online predictions
	//  ([PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
	//  or
	//  [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain]).
	//  Such a Model can serve predictions by using a
	//  [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob], if it
	//  has at least one entry each in
	//  [supported_input_storage_formats][google.cloud.aiplatform.v1.Model.supported_input_storage_formats]
	//  and
	//  [supported_output_storage_formats][google.cloud.aiplatform.v1.Model.supported_output_storage_formats].
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.supported_deployment_resources_types
	SupportedDeploymentResourcesTypes []string `json:"supportedDeploymentResourcesTypes,omitempty"`

	// Output only. The formats this Model supports in
	//  [BatchPredictionJob.input_config][google.cloud.aiplatform.v1.BatchPredictionJob.input_config].
	//  If
	//  [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1.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][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].
	//
	//  * `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][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].
	//
	//  * `tf-record`
	//  The TFRecord format, where each instance is a single record in tfrecord
	//  syntax. Uses
	//  [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].
	//
	//  * `tf-record-gzip`
	//  Similar to `tf-record`, but the file is gzipped. Uses
	//  [GcsSource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.gcs_source].
	//
	//  * `bigquery`
	//  Each instance is a single row in BigQuery. Uses
	//  [BigQuerySource][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.bigquery_source].
	//
	//  * `file-list`
	//  Each line of the file is the location of an instance to process, uses
	//  `gcs_source` field of the
	//  [InputConfig][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig]
	//  object.
	//
	//
	//  If this Model doesn't support any of these formats it means it cannot be
	//  used with a
	//  [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
	//  However, if it has
	//  [supported_deployment_resources_types][google.cloud.aiplatform.v1.Model.supported_deployment_resources_types],
	//  it could serve online predictions by using
	//  [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
	//  or
	//  [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.supported_input_storage_formats
	SupportedInputStorageFormats []string `json:"supportedInputStorageFormats,omitempty"`

	// Output only. The formats this Model supports in
	//  [BatchPredictionJob.output_config][google.cloud.aiplatform.v1.BatchPredictionJob.output_config].
	//  If both
	//  [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
	//  and
	//  [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1.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][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.gcs_destination].
	//
	//  * `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][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.gcs_destination].
	//
	//  * `bigquery`
	//  Each prediction is a single row in a BigQuery table, uses
	//  [BigQueryDestination][google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.bigquery_destination]
	//  .
	//
	//
	//  If this Model doesn't support any of these formats it means it cannot be
	//  used with a
	//  [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
	//  However, if it has
	//  [supported_deployment_resources_types][google.cloud.aiplatform.v1.Model.supported_deployment_resources_types],
	//  it could serve online predictions by using
	//  [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
	//  or
	//  [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.supported_output_storage_formats
	SupportedOutputStorageFormats []string `json:"supportedOutputStorageFormats,omitempty"`

	// Output only. Timestamp when this Model was uploaded into Vertex AI.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.create_time
	CreateTime *string `json:"createTime,omitempty"`

	// Output only. Timestamp when this Model was most recently updated.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.update_time
	UpdateTime *string `json:"updateTime,omitempty"`

	// Output only. The pointers to DeployedModels created from this Model. Note
	//  that Model could have been deployed to Endpoints in different Locations.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.deployed_models
	DeployedModels []DeployedModelRef `json:"deployedModels,omitempty"`

	// Output only. Source of a model. It can either be automl training pipeline,
	//  custom training pipeline, BigQuery ML, or saved and tuned from Genie or
	//  Model Garden.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.model_source_info
	ModelSourceInfo *ModelSourceInfo `json:"modelSourceInfo,omitempty"`

	// Output only. If this Model is a copy of another Model, this contains info
	//  about the original.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.original_model_info
	OriginalModelInfo *Model_OriginalModelInfo `json:"originalModelInfo,omitempty"`

	// Output only. 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}`.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.metadata_artifact
	MetadataArtifact *string `json:"metadataArtifact,omitempty"`

	// Output only. Reserved for future use.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.satisfies_pzs
	SatisfiesPzs *bool `json:"satisfiesPzs,omitempty"`

	// Output only. Reserved for future use.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.satisfies_pzi
	SatisfiesPzi *bool `json:"satisfiesPzi,omitempty"`
}

AIPlatformModelObservedState is the state of the AIPlatformModel resource as most recently observed in GCP. +kcc:proto=google.cloud.aiplatform.v1.Model

func (*AIPlatformModelObservedState) DeepCopy 

func (in *AIPlatformModelObservedState) DeepCopy() *AIPlatformModelObservedState

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new AIPlatformModelObservedState.

func (*AIPlatformModelObservedState) DeepCopyInto 

func (in *AIPlatformModelObservedState) DeepCopyInto(out *AIPlatformModelObservedState)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type AIPlatformModelSpec 

type AIPlatformModelSpec struct {
	// 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][a-zA-Z0-9-]{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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.version_aliases
	VersionAliases []string `json:"versionAliases,omitempty"`

	// Required. The display name of the Model.
	//  The name can be up to 128 characters long and can consist of any UTF-8
	//  characters.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.display_name
	DisplayName *string `json:"displayName,omitempty"`

	// The description of the Model.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.description
	Description *string `json:"description,omitempty"`

	// The description of this version.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.version_description
	VersionDescription *string `json:"versionDescription,omitempty"`

	// The schemata that describe formats of the Model's predictions and
	//  explanations as given and returned via
	//  [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict]
	//  and
	//  [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.predict_schemata
	PredictSchemata *PredictSchemata `json:"predictSchemata,omitempty"`

	// 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.metadata_schema_uri
	MetadataSchemaURI *string `json:"metadataSchemaURI,omitempty"`

	// Immutable. An additional information about the Model; the schema of the
	//  metadata can be found in
	//  [metadata_schema][google.cloud.aiplatform.v1.Model.metadata_schema_uri].
	//  Unset if the Model does not have any additional information.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.metadata
	Metadata *Value `json:"metadata,omitempty"`

	// Optional. This field is populated if the model is produced by a pipeline
	//  job.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.pipeline_job
	PipelineJob *string `json:"pipelineJob,omitempty"`

	// Input only. The specification of the container that is to be used when
	//  deploying this Model. The specification is ingested upon
	//  [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel],
	//  and all binaries it contains are copied and stored internally by Vertex AI.
	//  Not required for AutoML Models.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.container_spec
	ContainerSpec *ModelContainerSpec `json:"containerSpec,omitempty"`

	// Immutable. The path to the directory containing the Model artifact and any
	//  of its supporting files. Not required for AutoML Models.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.artifact_uri
	ArtifactURI *string `json:"artifactURI,omitempty"`

	// The default explanation specification for this Model.
	//
	//  The Model can be used for
	//  [requesting
	//  explanation][google.cloud.aiplatform.v1.PredictionService.Explain] after
	//  being [deployed][google.cloud.aiplatform.v1.EndpointService.DeployModel] if
	//  it is populated. The Model can be used for [batch
	//  explanation][google.cloud.aiplatform.v1.BatchPredictionJob.generate_explanation]
	//  if it is populated.
	//
	//  All fields of the explanation_spec can be overridden by
	//  [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
	//  of
	//  [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1.DeployModelRequest.deployed_model],
	//  or
	//  [explanation_spec][google.cloud.aiplatform.v1.BatchPredictionJob.explanation_spec]
	//  of [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
	//
	//  If the default explanation specification is not set for this Model, this
	//  Model can still be used for
	//  [requesting
	//  explanation][google.cloud.aiplatform.v1.PredictionService.Explain] by
	//  setting
	//  [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
	//  of
	//  [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1.DeployModelRequest.deployed_model]
	//  and for [batch
	//  explanation][google.cloud.aiplatform.v1.BatchPredictionJob.generate_explanation]
	//  by setting
	//  [explanation_spec][google.cloud.aiplatform.v1.BatchPredictionJob.explanation_spec]
	//  of [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.explanation_spec
	ExplanationSpec *ExplanationSpec `json:"explanationSpec,omitempty"`

	// Used to perform consistent read-modify-write updates. If not set, a blind
	//  "overwrite" update happens.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.etag
	Etag *string `json:"etag,omitempty"`

	// 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.labels
	Labels map[string]string `json:"labels,omitempty"`

	// Stats of data used for training or evaluating the Model.
	//
	//  Only populated when the Model is trained by a TrainingPipeline with
	//  [data_input_config][google.cloud.aiplatform.v1.TrainingPipeline.input_data_config].
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.data_stats
	DataStats *Model_DataStats `json:"dataStats,omitempty"`

	// 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.encryption_spec
	EncryptionSpec *EncryptionSpec `json:"encryptionSpec,omitempty"`

	// Optional. User input field to specify the base model source. Currently it
	//  only supports specifying the Model Garden models and Genie models.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.base_model_source
	BaseModelSource *Model_BaseModelSource `json:"baseModelSource,omitempty"`

	// Required. The resource name of the Location into which to upload the Model.
	// Format: projects/{project}/locations/{location}
	*Parent `json:",inline"`

	// The AIPlatformModel name. If not given, the metadata.name will be used.
	ResourceID *string `json:"resourceID,omitempty"`
}

AIPlatformModelSpec defines the desired state of AIPlatformModel +kcc:proto=google.cloud.aiplatform.v1.Model

func (*AIPlatformModelSpec) DeepCopy 

func (in *AIPlatformModelSpec) DeepCopy() *AIPlatformModelSpec

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new AIPlatformModelSpec.

func (*AIPlatformModelSpec) DeepCopyInto 

func (in *AIPlatformModelSpec) DeepCopyInto(out *AIPlatformModelSpec)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type AIPlatformModelStatus 

type AIPlatformModelStatus struct {
	/* Conditions represent the latest available observations of the
	   object's current state. */
	Conditions []v1alpha1.Condition `json:"conditions,omitempty"`

	// ObservedGeneration is the generation of the resource that was most recently observed by the Config Connector controller. If this is equal to metadata.generation, then that means that the current reported status reflects the most recent desired state of the resource.
	ObservedGeneration *int64 `json:"observedGeneration,omitempty"`

	// A unique specifier for the AIPlatformModel resource in GCP.
	ExternalRef *string `json:"externalRef,omitempty"`

	// ObservedState is the state of the resource as most recently observed in GCP.
	ObservedState *AIPlatformModelObservedState `json:"observedState,omitempty"`
}

AIPlatformModelStatus defines the config connector machine state of AIPlatformModel

func (*AIPlatformModelStatus) DeepCopy 

func (in *AIPlatformModelStatus) DeepCopy() *AIPlatformModelStatus

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new AIPlatformModelStatus.

func (*AIPlatformModelStatus) DeepCopyInto 

func (in *AIPlatformModelStatus) DeepCopyInto(out *AIPlatformModelStatus)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type BlurBaselineConfig 

type BlurBaselineConfig 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.BlurBaselineConfig.max_blur_sigma
	MaxBlurSigma *float32 `json:"maxBlurSigma,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.BlurBaselineConfig

func (*BlurBaselineConfig) DeepCopy 

func (in *BlurBaselineConfig) DeepCopy() *BlurBaselineConfig

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new BlurBaselineConfig.

func (*BlurBaselineConfig) DeepCopyInto 

func (in *BlurBaselineConfig) DeepCopyInto(out *BlurBaselineConfig)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type DeployedModelRef 

type DeployedModelRef struct {
	// Immutable. A resource name of an Endpoint.
	// +kcc:proto:field=google.cloud.aiplatform.v1.DeployedModelRef.endpoint
	Endpoint *string `json:"endpoint,omitempty"`

	// Immutable. An ID of a DeployedModel in the above Endpoint.
	// +kcc:proto:field=google.cloud.aiplatform.v1.DeployedModelRef.deployed_model_id
	DeployedModelID *string `json:"deployedModelID,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.DeployedModelRef

func (*DeployedModelRef) DeepCopy 

func (in *DeployedModelRef) DeepCopy() *DeployedModelRef

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new DeployedModelRef.

func (*DeployedModelRef) DeepCopyInto 

func (in *DeployedModelRef) DeepCopyInto(out *DeployedModelRef)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type EncryptionSpec 

type EncryptionSpec struct {
	// Required. 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.EncryptionSpec.kms_key_name
	KMSKeyName *string `json:"kmsKeyName,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.EncryptionSpec

func (*EncryptionSpec) DeepCopy 

func (in *EncryptionSpec) DeepCopy() *EncryptionSpec

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new EncryptionSpec.

func (*EncryptionSpec) DeepCopyInto 

func (in *EncryptionSpec) DeepCopyInto(out *EncryptionSpec)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type EnvVar 

type EnvVar struct {
	// Required. Name of the environment variable. Must be a valid C identifier.
	// +kcc:proto:field=google.cloud.aiplatform.v1.EnvVar.name
	Name *string `json:"name,omitempty"`

	// Required. 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.EnvVar.value
	Value *string `json:"value,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.EnvVar

func (*EnvVar) DeepCopy 

func (in *EnvVar) DeepCopy() *EnvVar

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new EnvVar.

func (*EnvVar) DeepCopyInto 

func (in *EnvVar) DeepCopyInto(out *EnvVar)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Examples 

type Examples struct {
	// The Cloud Storage input instances.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Examples.example_gcs_source
	ExampleGCSSource *Examples_ExampleGcsSource `json:"exampleGCSSource,omitempty"`

	// The full configuration for the generated index, the semantics are the
	//  same as [metadata][google.cloud.aiplatform.v1.Index.metadata] and should
	//  match
	//  [NearestNeighborSearchConfig](https://cloud.google.com/vertex-ai/docs/explainable-ai/configuring-explanations-example-based#nearest-neighbor-search-config).
	// +kcc:proto:field=google.cloud.aiplatform.v1.Examples.nearest_neighbor_search_config
	NearestNeighborSearchConfig *Value `json:"nearestNeighborSearchConfig,omitempty"`

	// Simplified preset configuration, which automatically sets configuration
	//  values based on the desired query speed-precision trade-off and modality.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Examples.presets
	Presets *Presets `json:"presets,omitempty"`

	// The number of neighbors to return when querying for examples.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Examples.neighbor_count
	NeighborCount *int32 `json:"neighborCount,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.Examples

func (*Examples) DeepCopy 

func (in *Examples) DeepCopy() *Examples

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Examples.

func (*Examples) DeepCopyInto 

func (in *Examples) DeepCopyInto(out *Examples)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Examples_ExampleGcsSource 

type Examples_ExampleGcsSource struct {
	// The format in which instances are given, if not specified, assume it's
	//  JSONL format. Currently only JSONL format is supported.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Examples.ExampleGcsSource.data_format
	DataFormat *string `json:"dataFormat,omitempty"`

	// The Cloud Storage location for the input instances.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Examples.ExampleGcsSource.gcs_source
	GcsSource *GcsSource `json:"gcsSource,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.Examples.ExampleGcsSource

func (*Examples_ExampleGcsSource) DeepCopy 

func (in *Examples_ExampleGcsSource) DeepCopy() *Examples_ExampleGcsSource

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Examples_ExampleGcsSource.

func (*Examples_ExampleGcsSource) DeepCopyInto 

func (in *Examples_ExampleGcsSource) DeepCopyInto(out *Examples_ExampleGcsSource)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type ExplanationMetadata 

type ExplanationMetadata struct {
	// Required. 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][google.cloud.aiplatform.v1.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][google.cloud.aiplatform.v1.Attribution.feature_attributions]
	// are keyed by this key (if not grouped with another feature).
	//
	// For custom images, the key must match with the key in
	// [instance][google.cloud.aiplatform.v1.ExplainRequest.instances].
	Inputs map[string]*ExplanationMetadata_InputMetadata `json:"inputs,omitempty"`
	// Required. 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]*ExplanationMetadata_OutputMetadata `json:"outputs,omitempty"`

	// Points to a YAML file stored on Google Cloud Storage describing the format
	//  of the [feature
	//  attributions][google.cloud.aiplatform.v1.Attribution.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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.feature_attributions_schema_uri
	FeatureAttributionsSchemaURI *string `json:"featureAttributionsSchemaURI,omitempty"`

	// Name of the source to generate embeddings for example based explanations.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.latent_space_source
	LatentSpaceSource *string `json:"latentSpaceSource,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.ExplanationMetadata

func (*ExplanationMetadata) DeepCopy 

func (in *ExplanationMetadata) DeepCopy() *ExplanationMetadata

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new ExplanationMetadata.

func (*ExplanationMetadata) DeepCopyInto 

func (in *ExplanationMetadata) DeepCopyInto(out *ExplanationMetadata)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type ExplanationMetadata_InputMetadata 

type ExplanationMetadata_InputMetadata struct {
	// Baseline inputs for this feature.
	//
	//  If no baseline is specified, Vertex AI chooses the baseline for this
	//  feature. If multiple baselines are specified, Vertex AI returns the
	//  average attributions across them in
	//  [Attribution.feature_attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions].
	//
	//  For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape
	//  of each baseline must match the shape of the input tensor. If a scalar is
	//  provided, we broadcast to the same shape as the input tensor.
	//
	//  For custom images, the element of the baselines must be in the same
	//  format as the feature's input in the
	//  [instance][google.cloud.aiplatform.v1.ExplainRequest.instances][]. The
	//  schema of any single instance may be specified via Endpoint's
	//  DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
	//  [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
	//  [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.input_baselines
	InputBaselines []Value `json:"inputBaselines,omitempty"`

	// Name of the input tensor for this feature. Required and is only
	//  applicable to Vertex AI-provided images for Tensorflow.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.input_tensor_name
	InputTensorName *string `json:"inputTensorName,omitempty"`

	// Defines how the feature is encoded into the input tensor. Defaults to
	//  IDENTITY.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoding
	Encoding *string `json:"encoding,omitempty"`

	// Modality of the feature. Valid values are: numeric, image. Defaults to
	//  numeric.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.modality
	Modality *string `json:"modality,omitempty"`

	// The domain details of the input feature value. Like min/max, original
	//  mean or standard deviation if normalized.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.feature_value_domain
	FeatureValueDomain *ExplanationMetadata_InputMetadata_FeatureValueDomain `json:"featureValueDomain,omitempty"`

	// Specifies the index of the values of the input tensor.
	//  Required when the input tensor is a sparse representation. Refer to
	//  Tensorflow documentation for more details:
	//  https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.indices_tensor_name
	IndicesTensorName *string `json:"indicesTensorName,omitempty"`

	// Specifies the shape of the values of the input if the input is a sparse
	//  representation. Refer to Tensorflow documentation for more details:
	//  https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.dense_shape_tensor_name
	DenseShapeTensorName *string `json:"denseShapeTensorName,omitempty"`

	// A list of feature names for each index in the input tensor.
	//  Required when the input
	//  [InputMetadata.encoding][google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoding]
	//  is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.index_feature_mapping
	IndexFeatureMapping []string `json:"indexFeatureMapping,omitempty"`

	// Encoded tensor is a transformation of the input tensor. Must be provided
	//  if choosing
	//  [Integrated Gradients
	//  attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution]
	//  or [XRAI
	//  attribution][google.cloud.aiplatform.v1.ExplanationParameters.xrai_attribution]
	//  and the input tensor is not differentiable.
	//
	//  An encoded tensor is generated if the input tensor is encoded by a lookup
	//  table.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoded_tensor_name
	EncodedTensorName *string `json:"encodedTensorName,omitempty"`

	// A list of baselines for the encoded tensor.
	//
	//  The shape of each baseline should match the shape of the encoded tensor.
	//  If a scalar is provided, Vertex AI broadcasts to the same shape as the
	//  encoded tensor.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoded_baselines
	EncodedBaselines []Value `json:"encodedBaselines,omitempty"`

	// Visualization configurations for image explanation.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.visualization
	Visualization *ExplanationMetadata_InputMetadata_Visualization `json:"visualization,omitempty"`

	// Name of the group that the input belongs to. Features with the same group
	//  name will be treated as one feature when computing attributions. Features
	//  grouped together can have different shapes in value. If provided, there
	//  will be one single attribution generated in
	//  [Attribution.feature_attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions],
	//  keyed by the group name.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.group_name
	GroupName *string `json:"groupName,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata

func (*ExplanationMetadata_InputMetadata) DeepCopy 

func (in *ExplanationMetadata_InputMetadata) DeepCopy() *ExplanationMetadata_InputMetadata

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new ExplanationMetadata_InputMetadata.

func (*ExplanationMetadata_InputMetadata) DeepCopyInto 

func (in *ExplanationMetadata_InputMetadata) DeepCopyInto(out *ExplanationMetadata_InputMetadata)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type ExplanationMetadata_InputMetadata_FeatureValueDomain 

type ExplanationMetadata_InputMetadata_FeatureValueDomain struct {
	// The minimum permissible value for this feature.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain.min_value
	MinValue *float32 `json:"minValue,omitempty"`

	// The maximum permissible value for this feature.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain.max_value
	MaxValue *float32 `json:"maxValue,omitempty"`

	// If this input feature has been normalized to a mean value of 0,
	//  the original_mean specifies the mean value of the domain prior to
	//  normalization.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain.original_mean
	OriginalMean *float32 `json:"originalMean,omitempty"`

	// If this input feature has been normalized to a standard deviation of
	//  1.0, the original_stddev specifies the standard deviation of the domain
	//  prior to normalization.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain.original_stddev
	OriginalStddev *float32 `json:"originalStddev,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain

func (*ExplanationMetadata_InputMetadata_FeatureValueDomain) DeepCopy 

func (in *ExplanationMetadata_InputMetadata_FeatureValueDomain) DeepCopy() *ExplanationMetadata_InputMetadata_FeatureValueDomain

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new ExplanationMetadata_InputMetadata_FeatureValueDomain.

func (*ExplanationMetadata_InputMetadata_FeatureValueDomain) DeepCopyInto 

func (in *ExplanationMetadata_InputMetadata_FeatureValueDomain) DeepCopyInto(out *ExplanationMetadata_InputMetadata_FeatureValueDomain)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type ExplanationMetadata_InputMetadata_Visualization 

type ExplanationMetadata_InputMetadata_Visualization struct {
	// Type of the image visualization. Only applicable to
	//  [Integrated Gradients
	//  attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution].
	//  OUTLINES shows regions of attribution, while PIXELS shows per-pixel
	//  attribution. Defaults to OUTLINES.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.type
	Type *string `json:"type,omitempty"`

	// Whether to only highlight pixels with positive contributions, negative
	//  or both. Defaults to POSITIVE.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.polarity
	Polarity *string `json:"polarity,omitempty"`

	// The color scheme used for the highlighted areas.
	//
	//  Defaults to PINK_GREEN for
	//  [Integrated Gradients
	//  attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution],
	//  which shows positive attributions in green and negative in pink.
	//
	//  Defaults to VIRIDIS for
	//  [XRAI
	//  attribution][google.cloud.aiplatform.v1.ExplanationParameters.xrai_attribution],
	//  which highlights the most influential regions in yellow and the least
	//  influential in blue.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.color_map
	ColorMap *string `json:"colorMap,omitempty"`

	// Excludes attributions above the specified percentile from the
	//  highlighted areas. Using the clip_percent_upperbound and
	//  clip_percent_lowerbound together can be useful for filtering out noise
	//  and making it easier to see areas of strong attribution. Defaults to
	//  99.9.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.clip_percent_upperbound
	ClipPercentUpperbound *float32 `json:"clipPercentUpperbound,omitempty"`

	// Excludes attributions below the specified percentile, from the
	//  highlighted areas. Defaults to 62.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.clip_percent_lowerbound
	ClipPercentLowerbound *float32 `json:"clipPercentLowerbound,omitempty"`

	// How the original image is displayed in the visualization.
	//  Adjusting the overlay can help increase visual clarity if the original
	//  image makes it difficult to view the visualization. Defaults to NONE.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.overlay_type
	OverlayType *string `json:"overlayType,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization

func (*ExplanationMetadata_InputMetadata_Visualization) DeepCopy 

func (in *ExplanationMetadata_InputMetadata_Visualization) DeepCopy() *ExplanationMetadata_InputMetadata_Visualization

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new ExplanationMetadata_InputMetadata_Visualization.

func (*ExplanationMetadata_InputMetadata_Visualization) DeepCopyInto 

func (in *ExplanationMetadata_InputMetadata_Visualization) DeepCopyInto(out *ExplanationMetadata_InputMetadata_Visualization)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type ExplanationMetadata_OutputMetadata 

type ExplanationMetadata_OutputMetadata struct {
	// Static mapping between the index and display name.
	//
	//  Use this if the outputs are a deterministic n-dimensional array, e.g. a
	//  list of scores of all the classes in a pre-defined order for a
	//  multi-classification Model. It's not feasible if the outputs are
	//  non-deterministic, e.g. the Model produces top-k classes or sort the
	//  outputs by their values.
	//
	//  The shape of the value must be an n-dimensional array of strings. The
	//  number of dimensions must match that of the outputs to be explained.
	//  The
	//  [Attribution.output_display_name][google.cloud.aiplatform.v1.Attribution.output_display_name]
	//  is populated by locating in the mapping with
	//  [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index].
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata.index_display_name_mapping
	IndexDisplayNameMapping *Value `json:"indexDisplayNameMapping,omitempty"`

	// Specify a field name in the prediction to look for the display name.
	//
	//  Use this if the prediction contains the display names for the outputs.
	//
	//  The display names in the prediction must have the same shape of the
	//  outputs, so that it can be located by
	//  [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index]
	//  for a specific output.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata.display_name_mapping_key
	DisplayNameMappingKey *string `json:"displayNameMappingKey,omitempty"`

	// Name of the output tensor. Required and is only applicable to Vertex
	//  AI provided images for Tensorflow.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata.output_tensor_name
	OutputTensorName *string `json:"outputTensorName,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata

func (*ExplanationMetadata_OutputMetadata) DeepCopy 

func (in *ExplanationMetadata_OutputMetadata) DeepCopy() *ExplanationMetadata_OutputMetadata

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new ExplanationMetadata_OutputMetadata.

func (*ExplanationMetadata_OutputMetadata) DeepCopyInto 

func (in *ExplanationMetadata_OutputMetadata) DeepCopyInto(out *ExplanationMetadata_OutputMetadata)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type ExplanationParameters 

type ExplanationParameters struct {
	// 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationParameters.sampled_shapley_attribution
	SampledShapleyAttribution *SampledShapleyAttribution `json:"sampledShapleyAttribution,omitempty"`

	// 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
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution
	IntegratedGradientsAttribution *IntegratedGradientsAttribution `json:"integratedGradientsAttribution,omitempty"`

	// 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationParameters.xrai_attribution
	XraiAttribution *XraiAttribution `json:"xraiAttribution,omitempty"`

	// Example-based explanations that returns the nearest neighbors from the
	//  provided dataset.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationParameters.examples
	Examples *Examples `json:"examples,omitempty"`

	// 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationParameters.top_k
	TopK *int32 `json:"topK,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.ExplanationParameters

func (*ExplanationParameters) DeepCopy 

func (in *ExplanationParameters) DeepCopy() *ExplanationParameters

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new ExplanationParameters.

func (*ExplanationParameters) DeepCopyInto 

func (in *ExplanationParameters) DeepCopyInto(out *ExplanationParameters)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type ExplanationSpec 

type ExplanationSpec struct {
	// Required. Parameters that configure explaining of the Model's predictions.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationSpec.parameters
	Parameters *ExplanationParameters `json:"parameters,omitempty"`

	// Optional. Metadata describing the Model's input and output for explanation.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ExplanationSpec.metadata
	Metadata *ExplanationMetadata `json:"metadata,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.ExplanationSpec

func (*ExplanationSpec) DeepCopy 

func (in *ExplanationSpec) DeepCopy() *ExplanationSpec

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new ExplanationSpec.

func (*ExplanationSpec) DeepCopyInto 

func (in *ExplanationSpec) DeepCopyInto(out *ExplanationSpec)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type FeatureNoiseSigma 

type FeatureNoiseSigma struct {
	// Noise sigma per feature. No noise is added to features that are not set.
	// +kcc:proto:field=google.cloud.aiplatform.v1.FeatureNoiseSigma.noise_sigma
	NoiseSigma []FeatureNoiseSigma_NoiseSigmaForFeature `json:"noiseSigma,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.FeatureNoiseSigma

func (*FeatureNoiseSigma) DeepCopy 

func (in *FeatureNoiseSigma) DeepCopy() *FeatureNoiseSigma

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new FeatureNoiseSigma.

func (*FeatureNoiseSigma) DeepCopyInto 

func (in *FeatureNoiseSigma) DeepCopyInto(out *FeatureNoiseSigma)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type FeatureNoiseSigma_NoiseSigmaForFeature 

type FeatureNoiseSigma_NoiseSigmaForFeature struct {
	// The name of the input feature for which noise sigma is provided. The
	//  features are defined in
	//  [explanation metadata
	//  inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
	// +kcc:proto:field=google.cloud.aiplatform.v1.FeatureNoiseSigma.NoiseSigmaForFeature.name
	Name *string `json:"name,omitempty"`

	// 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][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma]
	//  but represents the noise added to the current feature. Defaults to 0.1.
	// +kcc:proto:field=google.cloud.aiplatform.v1.FeatureNoiseSigma.NoiseSigmaForFeature.sigma
	Sigma *float32 `json:"sigma,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.FeatureNoiseSigma.NoiseSigmaForFeature

func (*FeatureNoiseSigma_NoiseSigmaForFeature) DeepCopy 

func (in *FeatureNoiseSigma_NoiseSigmaForFeature) DeepCopy() *FeatureNoiseSigma_NoiseSigmaForFeature

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new FeatureNoiseSigma_NoiseSigmaForFeature.

func (*FeatureNoiseSigma_NoiseSigmaForFeature) DeepCopyInto 

func (in *FeatureNoiseSigma_NoiseSigmaForFeature) DeepCopyInto(out *FeatureNoiseSigma_NoiseSigmaForFeature)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type GcsSource 

type GcsSource struct {
	// Required. 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.GcsSource.uris
	Uris []string `json:"uris,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.GcsSource

func (*GcsSource) DeepCopy 

func (in *GcsSource) DeepCopy() *GcsSource

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new GcsSource.

func (*GcsSource) DeepCopyInto 

func (in *GcsSource) DeepCopyInto(out *GcsSource)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type GenieSource 

type GenieSource struct {
	// Required. The public base model URI.
	// +kcc:proto:field=google.cloud.aiplatform.v1.GenieSource.base_model_uri
	BaseModelURI *string `json:"baseModelURI,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.GenieSource

func (*GenieSource) DeepCopy 

func (in *GenieSource) DeepCopy() *GenieSource

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new GenieSource.

func (*GenieSource) DeepCopyInto 

func (in *GenieSource) DeepCopyInto(out *GenieSource)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type IntegratedGradientsAttribution 

type IntegratedGradientsAttribution struct {
	// Required. 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.IntegratedGradientsAttribution.step_count
	StepCount *int32 `json:"stepCount,omitempty"`

	// 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
	// +kcc:proto:field=google.cloud.aiplatform.v1.IntegratedGradientsAttribution.smooth_grad_config
	SmoothGradConfig *SmoothGradConfig `json:"smoothGradConfig,omitempty"`

	// 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
	// +kcc:proto:field=google.cloud.aiplatform.v1.IntegratedGradientsAttribution.blur_baseline_config
	BlurBaselineConfig *BlurBaselineConfig `json:"blurBaselineConfig,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.IntegratedGradientsAttribution

func (*IntegratedGradientsAttribution) DeepCopy 

func (in *IntegratedGradientsAttribution) DeepCopy() *IntegratedGradientsAttribution

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new IntegratedGradientsAttribution.

func (*IntegratedGradientsAttribution) DeepCopyInto 

func (in *IntegratedGradientsAttribution) DeepCopyInto(out *IntegratedGradientsAttribution)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type ModelContainerSpec 

type ModelContainerSpec struct {
	// Required. 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][google.cloud.aiplatform.v1.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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelContainerSpec.image_uri
	ImageURI *string `json:"imageURI,omitempty"`

	// 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][google.cloud.aiplatform.v1.ModelContainerSpec.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][google.cloud.aiplatform.v1.ModelContainerSpec.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: <code>$(<var>VARIABLE_NAME</var>)</code> 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 `$$`; for
	//  example: <code>$$(<var>VARIABLE_NAME</var>)</code> 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).
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelContainerSpec.command
	Command []string `json:"command,omitempty"`

	// 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][google.cloud.aiplatform.v1.ModelContainerSpec.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][google.cloud.aiplatform.v1.ModelContainerSpec.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: <code>$(<var>VARIABLE_NAME</var>)</code> 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 `$$`; for
	//  example: <code>$$(<var>VARIABLE_NAME</var>)</code> 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).
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelContainerSpec.args
	Args []string `json:"args,omitempty"`

	// 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][google.cloud.aiplatform.v1.ModelContainerSpec.command] and
	//  [args][google.cloud.aiplatform.v1.ModelContainerSpec.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).
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelContainerSpec.env
	Env []EnvVar `json:"env,omitempty"`

	// 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).
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelContainerSpec.ports
	Ports []Port `json:"ports,omitempty"`

	// Immutable. HTTP path on the container to send prediction requests to.
	//  Vertex AI forwards requests sent using
	//  [projects.locations.endpoints.predict][google.cloud.aiplatform.v1.PredictionService.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][google.cloud.aiplatform.v1.ModelContainerSpec.ports] field.
	//
	//  If you don't specify this field, it defaults to the following value when
	//  you [deploy this Model to an
	//  Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]:
	//  <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code>
	//  The placeholders in this value are replaced as follows:
	//
	//  * <var>ENDPOINT</var>: 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).)
	//
	//  * <var>DEPLOYED_MODEL</var>:
	//  [DeployedModel.id][google.cloud.aiplatform.v1.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).)
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelContainerSpec.predict_route
	PredictRoute *string `json:"predictRoute,omitempty"`

	// 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][google.cloud.aiplatform.v1.ModelContainerSpec.ports] field.
	//
	//  If you don't specify this field, it defaults to the following value when
	//  you [deploy this Model to an
	//  Endpoint][google.cloud.aiplatform.v1.EndpointService.DeployModel]:
	//  <code>/v1/endpoints/<var>ENDPOINT</var>/deployedModels/<var>DEPLOYED_MODEL</var>:predict</code>
	//  The placeholders in this value are replaced as follows:
	//
	//  * <var>ENDPOINT</var>: 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).)
	//
	//  * <var>DEPLOYED_MODEL</var>:
	//  [DeployedModel.id][google.cloud.aiplatform.v1.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).)
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelContainerSpec.health_route
	HealthRoute *string `json:"healthRoute,omitempty"`

	// Immutable. List of ports to expose from the container. Vertex AI sends gRPC
	//  prediction requests that it receives to the first port on this list. Vertex
	//  AI also sends liveness and health checks to this port.
	//
	//  If you do not specify this field, gRPC requests to the container will be
	//  disabled.
	//
	//  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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelContainerSpec.grpc_ports
	GrpcPorts []Port `json:"grpcPorts,omitempty"`

	// Immutable. Deployment timeout.
	//  Limit for deployment timeout is 2 hours.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelContainerSpec.deployment_timeout
	DeploymentTimeout *string `json:"deploymentTimeout,omitempty"`

	// Immutable. The amount of the VM memory to reserve as the shared memory for
	//  the model in megabytes.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelContainerSpec.shared_memory_size_mb
	SharedMemorySizeMb *int64 `json:"sharedMemorySizeMb,omitempty"`

	// Immutable. Specification for Kubernetes startup probe.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelContainerSpec.startup_probe
	StartupProbe *Probe `json:"startupProbe,omitempty"`

	// Immutable. Specification for Kubernetes readiness probe.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelContainerSpec.health_probe
	HealthProbe *Probe `json:"healthProbe,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.ModelContainerSpec

func (*ModelContainerSpec) DeepCopy 

func (in *ModelContainerSpec) DeepCopy() *ModelContainerSpec

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new ModelContainerSpec.

func (*ModelContainerSpec) DeepCopyInto 

func (in *ModelContainerSpec) DeepCopyInto(out *ModelContainerSpec)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type ModelGardenSource 

type ModelGardenSource struct {
	// Required. The model garden source model resource name.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelGardenSource.public_model_name
	PublicModelName *string `json:"publicModelName,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.ModelGardenSource

func (*ModelGardenSource) DeepCopy 

func (in *ModelGardenSource) DeepCopy() *ModelGardenSource

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new ModelGardenSource.

func (*ModelGardenSource) DeepCopyInto 

func (in *ModelGardenSource) DeepCopyInto(out *ModelGardenSource)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type ModelIdentity 

type ModelIdentity struct {
	// contains filtered or unexported fields
}

ModelIdentity defines the resource reference to AIPlatformModel, which "External" field holds the GCP identifier for the KRM object.

func NewModelIdentity 

func NewModelIdentity(ctx context.Context, reader client.Reader, obj *AIPlatformModel) (*ModelIdentity, error)

New builds a ModelIdentity from the Config Connector Model object.

func (*ModelIdentity) DeepCopy 

func (in *ModelIdentity) DeepCopy() *ModelIdentity

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new ModelIdentity.

func (*ModelIdentity) DeepCopyInto 

func (in *ModelIdentity) DeepCopyInto(out *ModelIdentity)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

func (*ModelIdentity) ID 

func (i *ModelIdentity) ID() string

func (*ModelIdentity) Parent 

func (i *ModelIdentity) Parent() *ModelParent

func (*ModelIdentity) String 

func (i *ModelIdentity) String() string

type ModelParent 

type ModelParent struct {
	ProjectID string
	Location  string
}

func ParseModelExternal 

func ParseModelExternal(external string) (parent *ModelParent, resourceID string, err error)

func (*ModelParent) DeepCopy 

func (in *ModelParent) DeepCopy() *ModelParent

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new ModelParent.

func (*ModelParent) DeepCopyInto 

func (in *ModelParent) DeepCopyInto(out *ModelParent)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

func (*ModelParent) String 

func (p *ModelParent) String() string

type ModelRef 

type ModelRef struct {
	// A reference to an externally managed AIPlatformModel resource.
	// Should be in the format "projects/{{projectID}}/locations/{{location}}/models/{{modelID}}".
	External string `json:"external,omitempty"`

	// The name of a AIPlatformModel resource.
	Name string `json:"name,omitempty"`

	// The namespace of a AIPlatformModel resource.
	Namespace string `json:"namespace,omitempty"`
}

ModelRef defines the resource reference to AIPlatformModel, which "External" field holds the GCP identifier for the KRM object.

func (*ModelRef) DeepCopy 

func (in *ModelRef) DeepCopy() *ModelRef

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new ModelRef.

func (*ModelRef) DeepCopyInto 

func (in *ModelRef) DeepCopyInto(out *ModelRef)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

func (*ModelRef) NormalizedExternal 

func (r *ModelRef) NormalizedExternal(ctx context.Context, reader client.Reader, otherNamespace string) (string, error)

NormalizedExternal provision the "External" value for other resource that depends on AIPlatformModel. If the "External" is given in the other resource's spec.AIPlatformModelRef, the given value will be used. Otherwise, the "Name" and "Namespace" will be used to query the actual AIPlatformModel object from the cluster.

type ModelSourceInfo 

type ModelSourceInfo struct {
	// Type of the model source.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelSourceInfo.source_type
	SourceType *string `json:"sourceType,omitempty"`

	// If this Model is copy of another Model. If true then
	//  [source_type][google.cloud.aiplatform.v1.ModelSourceInfo.source_type]
	//  pertains to the original.
	// +kcc:proto:field=google.cloud.aiplatform.v1.ModelSourceInfo.copy
	Copy *bool `json:"copy,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.ModelSourceInfo

func (*ModelSourceInfo) DeepCopy 

func (in *ModelSourceInfo) DeepCopy() *ModelSourceInfo

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new ModelSourceInfo.

func (*ModelSourceInfo) DeepCopyInto 

func (in *ModelSourceInfo) DeepCopyInto(out *ModelSourceInfo)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Model_BaseModelSource 

type Model_BaseModelSource struct {
	// Source information of Model Garden models.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.BaseModelSource.model_garden_source
	ModelGardenSource *ModelGardenSource `json:"modelGardenSource,omitempty"`

	// Information about the base model of Genie models.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.BaseModelSource.genie_source
	GenieSource *GenieSource `json:"genieSource,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.Model.BaseModelSource

func (*Model_BaseModelSource) DeepCopy 

func (in *Model_BaseModelSource) DeepCopy() *Model_BaseModelSource

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Model_BaseModelSource.

func (*Model_BaseModelSource) DeepCopyInto 

func (in *Model_BaseModelSource) DeepCopyInto(out *Model_BaseModelSource)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Model_DataStats 

type Model_DataStats struct {
	// Number of DataItems that were used for training this Model.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.DataStats.training_data_items_count
	TrainingDataItemsCount *int64 `json:"trainingDataItemsCount,omitempty"`

	// Number of DataItems that were used for validating this Model during
	//  training.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.DataStats.validation_data_items_count
	ValidationDataItemsCount *int64 `json:"validationDataItemsCount,omitempty"`

	// Number of DataItems that were used for evaluating this Model. If the
	//  Model is evaluated multiple times, this will be the number of test
	//  DataItems used by the first evaluation. If the Model is not evaluated,
	//  the number is 0.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.DataStats.test_data_items_count
	TestDataItemsCount *int64 `json:"testDataItemsCount,omitempty"`

	// Number of Annotations that are used for training this Model.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.DataStats.training_annotations_count
	TrainingAnnotationsCount *int64 `json:"trainingAnnotationsCount,omitempty"`

	// Number of Annotations that are used for validating this Model during
	//  training.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.DataStats.validation_annotations_count
	ValidationAnnotationsCount *int64 `json:"validationAnnotationsCount,omitempty"`

	// Number of Annotations that are used for evaluating this Model. If the
	//  Model is evaluated multiple times, this will be the number of test
	//  Annotations used by the first evaluation. If the Model is not evaluated,
	//  the number is 0.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.DataStats.test_annotations_count
	TestAnnotationsCount *int64 `json:"testAnnotationsCount,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.Model.DataStats

func (*Model_DataStats) DeepCopy 

func (in *Model_DataStats) DeepCopy() *Model_DataStats

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Model_DataStats.

func (*Model_DataStats) DeepCopyInto 

func (in *Model_DataStats) DeepCopyInto(out *Model_DataStats)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Model_ExportFormat 

type Model_ExportFormat struct {
}

+kcc:proto=google.cloud.aiplatform.v1.Model.ExportFormat

func (*Model_ExportFormat) DeepCopy 

func (in *Model_ExportFormat) DeepCopy() *Model_ExportFormat

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Model_ExportFormat.

func (*Model_ExportFormat) DeepCopyInto 

func (in *Model_ExportFormat) DeepCopyInto(out *Model_ExportFormat)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Model_ExportFormatObservedState 

type Model_ExportFormatObservedState struct {
	// Output only. The ID of the export format.
	//  The possible format IDs are:
	//
	//  * `tflite`
	//  Used for Android mobile devices.
	//
	//  * `edgetpu-tflite`
	//  Used for [Edge TPU](https://cloud.google.com/edge-tpu/) devices.
	//
	//  * `tf-saved-model`
	//  A tensorflow model in SavedModel format.
	//
	//  * `tf-js`
	//  A [TensorFlow.js](https://www.tensorflow.org/js) model that can be used
	//  in the browser and in Node.js using JavaScript.
	//
	//  * `core-ml`
	//  Used for iOS mobile devices.
	//
	//  * `custom-trained`
	//  A Model that was uploaded or trained by custom code.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.ExportFormat.id
	ID *string `json:"id,omitempty"`

	// Output only. The content of this Model that may be exported.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.ExportFormat.exportable_contents
	ExportableContents []string `json:"exportableContents,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.Model.ExportFormat

func (*Model_ExportFormatObservedState) DeepCopy 

func (in *Model_ExportFormatObservedState) DeepCopy() *Model_ExportFormatObservedState

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Model_ExportFormatObservedState.

func (*Model_ExportFormatObservedState) DeepCopyInto 

func (in *Model_ExportFormatObservedState) DeepCopyInto(out *Model_ExportFormatObservedState)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Model_OriginalModelInfo 

type Model_OriginalModelInfo struct {
}

+kcc:proto=google.cloud.aiplatform.v1.Model.OriginalModelInfo

func (*Model_OriginalModelInfo) DeepCopy 

func (in *Model_OriginalModelInfo) DeepCopy() *Model_OriginalModelInfo

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Model_OriginalModelInfo.

func (*Model_OriginalModelInfo) DeepCopyInto 

func (in *Model_OriginalModelInfo) DeepCopyInto(out *Model_OriginalModelInfo)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Model_OriginalModelInfoObservedState 

type Model_OriginalModelInfoObservedState struct {
	// Output only. 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}`
	// +kcc:proto:field=google.cloud.aiplatform.v1.Model.OriginalModelInfo.model
	Model *string `json:"model,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.Model.OriginalModelInfo

func (*Model_OriginalModelInfoObservedState) DeepCopy 

func (in *Model_OriginalModelInfoObservedState) DeepCopy() *Model_OriginalModelInfoObservedState

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Model_OriginalModelInfoObservedState.

func (*Model_OriginalModelInfoObservedState) DeepCopyInto 

func (in *Model_OriginalModelInfoObservedState) DeepCopyInto(out *Model_OriginalModelInfoObservedState)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Parent 

type Parent struct {

	// Immutable. The location where the model should reside.
	// +required
	Location *string `json:"location,omitempty"`

	// The project that this resource belongs to.
	// +required
	ProjectRef *v1beta1.ProjectRef `json:"projectRef,omitempty"`
}

func (*Parent) DeepCopy 

func (in *Parent) DeepCopy() *Parent

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Parent.

func (*Parent) DeepCopyInto 

func (in *Parent) DeepCopyInto(out *Parent)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Port 

type Port 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Port.container_port
	ContainerPort *int32 `json:"containerPort,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.Port

func (*Port) DeepCopy 

func (in *Port) DeepCopy() *Port

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Port.

func (*Port) DeepCopyInto 

func (in *Port) DeepCopyInto(out *Port)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type PredictSchemata 

type PredictSchemata 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][google.cloud.aiplatform.v1.PredictRequest.instances],
	//  [ExplainRequest.instances][google.cloud.aiplatform.v1.ExplainRequest.instances]
	//  and
	//  [BatchPredictionJob.input_config][google.cloud.aiplatform.v1.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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri
	InstanceSchemaURI *string `json:"instanceSchemaURI,omitempty"`

	// Immutable. Points to a YAML file stored on Google Cloud Storage describing
	//  the parameters of prediction and explanation via
	//  [PredictRequest.parameters][google.cloud.aiplatform.v1.PredictRequest.parameters],
	//  [ExplainRequest.parameters][google.cloud.aiplatform.v1.ExplainRequest.parameters]
	//  and
	//  [BatchPredictionJob.model_parameters][google.cloud.aiplatform.v1.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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri
	ParametersSchemaURI *string `json:"parametersSchemaURI,omitempty"`

	// 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][google.cloud.aiplatform.v1.PredictResponse.predictions],
	//  [ExplainResponse.explanations][google.cloud.aiplatform.v1.ExplainResponse.explanations],
	//  and
	//  [BatchPredictionJob.output_config][google.cloud.aiplatform.v1.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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.PredictSchemata.prediction_schema_uri
	PredictionSchemaURI *string `json:"predictionSchemaURI,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.PredictSchemata

func (*PredictSchemata) DeepCopy 

func (in *PredictSchemata) DeepCopy() *PredictSchemata

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new PredictSchemata.

func (*PredictSchemata) DeepCopyInto 

func (in *PredictSchemata) DeepCopyInto(out *PredictSchemata)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Presets 

type Presets struct {
	// Preset option controlling parameters for speed-precision trade-off when
	//  querying for examples. If omitted, defaults to `PRECISE`.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Presets.query
	Query *string `json:"query,omitempty"`

	// 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Presets.modality
	Modality *string `json:"modality,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.Presets

func (*Presets) DeepCopy 

func (in *Presets) DeepCopy() *Presets

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Presets.

func (*Presets) DeepCopyInto 

func (in *Presets) DeepCopyInto(out *Presets)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Probe 

type Probe struct {
	// ExecAction probes the health of a container by executing a command.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Probe.exec
	Exec *Probe_ExecAction `json:"exec,omitempty"`

	// 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'.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Probe.period_seconds
	PeriodSeconds *int32 `json:"periodSeconds,omitempty"`

	// 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'.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Probe.timeout_seconds
	TimeoutSeconds *int32 `json:"timeoutSeconds,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.Probe

func (*Probe) DeepCopy 

func (in *Probe) DeepCopy() *Probe

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Probe.

func (*Probe) DeepCopyInto 

func (in *Probe) DeepCopyInto(out *Probe)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Probe_ExecAction 

type Probe_ExecAction 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.Probe.ExecAction.command
	Command []string `json:"command,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.Probe.ExecAction

func (*Probe_ExecAction) DeepCopy 

func (in *Probe_ExecAction) DeepCopy() *Probe_ExecAction

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Probe_ExecAction.

func (*Probe_ExecAction) DeepCopyInto 

func (in *Probe_ExecAction) DeepCopyInto(out *Probe_ExecAction)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type SampledShapleyAttribution 

type SampledShapleyAttribution struct {
	// Required. The number of feature permutations to consider when approximating
	//  the Shapley values.
	//
	//  Valid range of its value is [1, 50], inclusively.
	// +kcc:proto:field=google.cloud.aiplatform.v1.SampledShapleyAttribution.path_count
	PathCount *int32 `json:"pathCount,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.SampledShapleyAttribution

func (*SampledShapleyAttribution) DeepCopy 

func (in *SampledShapleyAttribution) DeepCopy() *SampledShapleyAttribution

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new SampledShapleyAttribution.

func (*SampledShapleyAttribution) DeepCopyInto 

func (in *SampledShapleyAttribution) DeepCopyInto(out *SampledShapleyAttribution)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type SmoothGradConfig 

type SmoothGradConfig struct {
	// 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][google.cloud.aiplatform.v1.SmoothGradConfig.feature_noise_sigma]
	//  instead for each feature.
	// +kcc:proto:field=google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma
	NoiseSigma *float32 `json:"noiseSigma,omitempty"`

	// This is similar to
	//  [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.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][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma]
	//  will be used for all features.
	// +kcc:proto:field=google.cloud.aiplatform.v1.SmoothGradConfig.feature_noise_sigma
	FeatureNoiseSigma *FeatureNoiseSigma `json:"featureNoiseSigma,omitempty"`

	// 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.SmoothGradConfig.noisy_sample_count
	NoisySampleCount *int32 `json:"noisySampleCount,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.SmoothGradConfig

func (*SmoothGradConfig) DeepCopy 

func (in *SmoothGradConfig) DeepCopy() *SmoothGradConfig

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new SmoothGradConfig.

func (*SmoothGradConfig) DeepCopyInto 

func (in *SmoothGradConfig) DeepCopyInto(out *SmoothGradConfig)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type Value 

type Value struct {
	// Represents a null value.
	// +kcc:proto:field=google.protobuf.Value.null_value
	NullValue *string `json:"nullValue,omitempty"`

	// Represents a double value.
	// +kcc:proto:field=google.protobuf.Value.number_value
	NumberValue *float64 `json:"numberValue,omitempty"`

	// Represents a string value.
	// +kcc:proto:field=google.protobuf.Value.string_value
	StringValue *string `json:"stringValue,omitempty"`

	// Represents a boolean value.
	// +kcc:proto:field=google.protobuf.Value.bool_value
	BoolValue *bool `json:"boolValue,omitempty"`

	// Represents a structured value.
	// +kcc:proto:field=google.protobuf.Value.struct_value
	StructValue map[string]string `json:"structValue,omitempty"`
}

+kcc:proto=google.protobuf.Value

func (*Value) DeepCopy 

func (in *Value) DeepCopy() *Value

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new Value.

func (*Value) DeepCopyInto 

func (in *Value) DeepCopyInto(out *Value)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

type XraiAttribution 

type XraiAttribution struct {
	// Required. 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.
	// +kcc:proto:field=google.cloud.aiplatform.v1.XraiAttribution.step_count
	StepCount *int32 `json:"stepCount,omitempty"`

	// 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
	// +kcc:proto:field=google.cloud.aiplatform.v1.XraiAttribution.smooth_grad_config
	SmoothGradConfig *SmoothGradConfig `json:"smoothGradConfig,omitempty"`

	// 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
	// +kcc:proto:field=google.cloud.aiplatform.v1.XraiAttribution.blur_baseline_config
	BlurBaselineConfig *BlurBaselineConfig `json:"blurBaselineConfig,omitempty"`
}

+kcc:proto=google.cloud.aiplatform.v1.XraiAttribution

func (*XraiAttribution) DeepCopy 

func (in *XraiAttribution) DeepCopy() *XraiAttribution

DeepCopy is an autogenerated deepcopy function, copying the receiver, creating a new XraiAttribution.

func (*XraiAttribution) DeepCopyInto 

func (in *XraiAttribution) DeepCopyInto(out *XraiAttribution)

DeepCopyInto is an autogenerated deepcopy function, copying the receiver, writing into out. in must be non-nil.

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