Documentation
Overview ¶
Package sagemaker provides the API client, operations, and parameter types for Amazon SageMaker Service.
Provides APIs for creating and managing Amazon SageMaker resources. Other Resources:
* Amazon SageMaker Developer Guide (https://docs.aws.amazon.com/sagemaker/latest/dg/whatis.html#first-time-user)
* Amazon Augmented AI Runtime API Reference (https://docs.aws.amazon.com/augmented-ai/2019-11-07/APIReference/Welcome.html)
Index ¶
- Constants
- func NewDefaultEndpointResolver() *internalendpoints.Resolver
- func WithAPIOptions(optFns ...func(*middleware.Stack) error) func(*Options)
- func WithEndpointResolver(v EndpointResolver) func(*Options)
- type AddAssociationInput
- type AddAssociationOutput
- type AddTagsInput
- type AddTagsOutput
- type AssociateTrialComponentInput
- type AssociateTrialComponentOutput
- type Client
- func (c *Client) AddAssociation(ctx context.Context, params *AddAssociationInput, optFns ...func(*Options)) (*AddAssociationOutput, error)
- func (c *Client) AddTags(ctx context.Context, params *AddTagsInput, optFns ...func(*Options)) (*AddTagsOutput, error)
- func (c *Client) AssociateTrialComponent(ctx context.Context, params *AssociateTrialComponentInput, ...) (*AssociateTrialComponentOutput, error)
- func (c *Client) CreateAction(ctx context.Context, params *CreateActionInput, optFns ...func(*Options)) (*CreateActionOutput, error)
- func (c *Client) CreateAlgorithm(ctx context.Context, params *CreateAlgorithmInput, optFns ...func(*Options)) (*CreateAlgorithmOutput, error)
- func (c *Client) CreateApp(ctx context.Context, params *CreateAppInput, optFns ...func(*Options)) (*CreateAppOutput, error)
- func (c *Client) CreateAppImageConfig(ctx context.Context, params *CreateAppImageConfigInput, ...) (*CreateAppImageConfigOutput, error)
- func (c *Client) CreateArtifact(ctx context.Context, params *CreateArtifactInput, optFns ...func(*Options)) (*CreateArtifactOutput, error)
- func (c *Client) CreateAutoMLJob(ctx context.Context, params *CreateAutoMLJobInput, optFns ...func(*Options)) (*CreateAutoMLJobOutput, error)
- func (c *Client) CreateCodeRepository(ctx context.Context, params *CreateCodeRepositoryInput, ...) (*CreateCodeRepositoryOutput, error)
- func (c *Client) CreateCompilationJob(ctx context.Context, params *CreateCompilationJobInput, ...) (*CreateCompilationJobOutput, error)
- func (c *Client) CreateContext(ctx context.Context, params *CreateContextInput, optFns ...func(*Options)) (*CreateContextOutput, error)
- func (c *Client) CreateDataQualityJobDefinition(ctx context.Context, params *CreateDataQualityJobDefinitionInput, ...) (*CreateDataQualityJobDefinitionOutput, error)
- func (c *Client) CreateDeviceFleet(ctx context.Context, params *CreateDeviceFleetInput, optFns ...func(*Options)) (*CreateDeviceFleetOutput, error)
- func (c *Client) CreateDomain(ctx context.Context, params *CreateDomainInput, optFns ...func(*Options)) (*CreateDomainOutput, error)
- func (c *Client) CreateEdgePackagingJob(ctx context.Context, params *CreateEdgePackagingJobInput, ...) (*CreateEdgePackagingJobOutput, error)
- func (c *Client) CreateEndpoint(ctx context.Context, params *CreateEndpointInput, optFns ...func(*Options)) (*CreateEndpointOutput, error)
- func (c *Client) CreateEndpointConfig(ctx context.Context, params *CreateEndpointConfigInput, ...) (*CreateEndpointConfigOutput, error)
- func (c *Client) CreateExperiment(ctx context.Context, params *CreateExperimentInput, optFns ...func(*Options)) (*CreateExperimentOutput, error)
- func (c *Client) CreateFeatureGroup(ctx context.Context, params *CreateFeatureGroupInput, optFns ...func(*Options)) (*CreateFeatureGroupOutput, error)
- func (c *Client) CreateFlowDefinition(ctx context.Context, params *CreateFlowDefinitionInput, ...) (*CreateFlowDefinitionOutput, error)
- func (c *Client) CreateHumanTaskUi(ctx context.Context, params *CreateHumanTaskUiInput, optFns ...func(*Options)) (*CreateHumanTaskUiOutput, error)
- func (c *Client) CreateHyperParameterTuningJob(ctx context.Context, params *CreateHyperParameterTuningJobInput, ...) (*CreateHyperParameterTuningJobOutput, error)
- func (c *Client) CreateImage(ctx context.Context, params *CreateImageInput, optFns ...func(*Options)) (*CreateImageOutput, error)
- func (c *Client) CreateImageVersion(ctx context.Context, params *CreateImageVersionInput, optFns ...func(*Options)) (*CreateImageVersionOutput, error)
- func (c *Client) CreateLabelingJob(ctx context.Context, params *CreateLabelingJobInput, optFns ...func(*Options)) (*CreateLabelingJobOutput, error)
- func (c *Client) CreateModel(ctx context.Context, params *CreateModelInput, optFns ...func(*Options)) (*CreateModelOutput, error)
- func (c *Client) CreateModelBiasJobDefinition(ctx context.Context, params *CreateModelBiasJobDefinitionInput, ...) (*CreateModelBiasJobDefinitionOutput, error)
- func (c *Client) CreateModelExplainabilityJobDefinition(ctx context.Context, params *CreateModelExplainabilityJobDefinitionInput, ...) (*CreateModelExplainabilityJobDefinitionOutput, error)
- func (c *Client) CreateModelPackage(ctx context.Context, params *CreateModelPackageInput, optFns ...func(*Options)) (*CreateModelPackageOutput, error)
- func (c *Client) CreateModelPackageGroup(ctx context.Context, params *CreateModelPackageGroupInput, ...) (*CreateModelPackageGroupOutput, error)
- func (c *Client) CreateModelQualityJobDefinition(ctx context.Context, params *CreateModelQualityJobDefinitionInput, ...) (*CreateModelQualityJobDefinitionOutput, error)
- func (c *Client) CreateMonitoringSchedule(ctx context.Context, params *CreateMonitoringScheduleInput, ...) (*CreateMonitoringScheduleOutput, error)
- func (c *Client) CreateNotebookInstance(ctx context.Context, params *CreateNotebookInstanceInput, ...) (*CreateNotebookInstanceOutput, error)
- func (c *Client) CreateNotebookInstanceLifecycleConfig(ctx context.Context, params *CreateNotebookInstanceLifecycleConfigInput, ...) (*CreateNotebookInstanceLifecycleConfigOutput, error)
- func (c *Client) CreatePipeline(ctx context.Context, params *CreatePipelineInput, optFns ...func(*Options)) (*CreatePipelineOutput, error)
- func (c *Client) CreatePresignedDomainUrl(ctx context.Context, params *CreatePresignedDomainUrlInput, ...) (*CreatePresignedDomainUrlOutput, error)
- func (c *Client) CreatePresignedNotebookInstanceUrl(ctx context.Context, params *CreatePresignedNotebookInstanceUrlInput, ...) (*CreatePresignedNotebookInstanceUrlOutput, error)
- func (c *Client) CreateProcessingJob(ctx context.Context, params *CreateProcessingJobInput, ...) (*CreateProcessingJobOutput, error)
- func (c *Client) CreateProject(ctx context.Context, params *CreateProjectInput, optFns ...func(*Options)) (*CreateProjectOutput, error)
- func (c *Client) CreateTrainingJob(ctx context.Context, params *CreateTrainingJobInput, optFns ...func(*Options)) (*CreateTrainingJobOutput, error)
- func (c *Client) CreateTransformJob(ctx context.Context, params *CreateTransformJobInput, optFns ...func(*Options)) (*CreateTransformJobOutput, error)
- func (c *Client) CreateTrial(ctx context.Context, params *CreateTrialInput, optFns ...func(*Options)) (*CreateTrialOutput, error)
- func (c *Client) CreateTrialComponent(ctx context.Context, params *CreateTrialComponentInput, ...) (*CreateTrialComponentOutput, error)
- func (c *Client) CreateUserProfile(ctx context.Context, params *CreateUserProfileInput, optFns ...func(*Options)) (*CreateUserProfileOutput, error)
- func (c *Client) CreateWorkforce(ctx context.Context, params *CreateWorkforceInput, optFns ...func(*Options)) (*CreateWorkforceOutput, error)
- func (c *Client) CreateWorkteam(ctx context.Context, params *CreateWorkteamInput, optFns ...func(*Options)) (*CreateWorkteamOutput, error)
- func (c *Client) DeleteAction(ctx context.Context, params *DeleteActionInput, optFns ...func(*Options)) (*DeleteActionOutput, error)
- func (c *Client) DeleteAlgorithm(ctx context.Context, params *DeleteAlgorithmInput, optFns ...func(*Options)) (*DeleteAlgorithmOutput, error)
- func (c *Client) DeleteApp(ctx context.Context, params *DeleteAppInput, optFns ...func(*Options)) (*DeleteAppOutput, error)
- func (c *Client) DeleteAppImageConfig(ctx context.Context, params *DeleteAppImageConfigInput, ...) (*DeleteAppImageConfigOutput, error)
- func (c *Client) DeleteArtifact(ctx context.Context, params *DeleteArtifactInput, optFns ...func(*Options)) (*DeleteArtifactOutput, error)
- func (c *Client) DeleteAssociation(ctx context.Context, params *DeleteAssociationInput, optFns ...func(*Options)) (*DeleteAssociationOutput, error)
- func (c *Client) DeleteCodeRepository(ctx context.Context, params *DeleteCodeRepositoryInput, ...) (*DeleteCodeRepositoryOutput, error)
- func (c *Client) DeleteContext(ctx context.Context, params *DeleteContextInput, optFns ...func(*Options)) (*DeleteContextOutput, error)
- func (c *Client) DeleteDataQualityJobDefinition(ctx context.Context, params *DeleteDataQualityJobDefinitionInput, ...) (*DeleteDataQualityJobDefinitionOutput, error)
- func (c *Client) DeleteDeviceFleet(ctx context.Context, params *DeleteDeviceFleetInput, optFns ...func(*Options)) (*DeleteDeviceFleetOutput, error)
- func (c *Client) DeleteDomain(ctx context.Context, params *DeleteDomainInput, optFns ...func(*Options)) (*DeleteDomainOutput, error)
- func (c *Client) DeleteEndpoint(ctx context.Context, params *DeleteEndpointInput, optFns ...func(*Options)) (*DeleteEndpointOutput, error)
- func (c *Client) DeleteEndpointConfig(ctx context.Context, params *DeleteEndpointConfigInput, ...) (*DeleteEndpointConfigOutput, error)
- func (c *Client) DeleteExperiment(ctx context.Context, params *DeleteExperimentInput, optFns ...func(*Options)) (*DeleteExperimentOutput, error)
- func (c *Client) DeleteFeatureGroup(ctx context.Context, params *DeleteFeatureGroupInput, optFns ...func(*Options)) (*DeleteFeatureGroupOutput, error)
- func (c *Client) DeleteFlowDefinition(ctx context.Context, params *DeleteFlowDefinitionInput, ...) (*DeleteFlowDefinitionOutput, error)
- func (c *Client) DeleteHumanTaskUi(ctx context.Context, params *DeleteHumanTaskUiInput, optFns ...func(*Options)) (*DeleteHumanTaskUiOutput, error)
- func (c *Client) DeleteImage(ctx context.Context, params *DeleteImageInput, optFns ...func(*Options)) (*DeleteImageOutput, error)
- func (c *Client) DeleteImageVersion(ctx context.Context, params *DeleteImageVersionInput, optFns ...func(*Options)) (*DeleteImageVersionOutput, error)
- func (c *Client) DeleteModel(ctx context.Context, params *DeleteModelInput, optFns ...func(*Options)) (*DeleteModelOutput, error)
- func (c *Client) DeleteModelBiasJobDefinition(ctx context.Context, params *DeleteModelBiasJobDefinitionInput, ...) (*DeleteModelBiasJobDefinitionOutput, error)
- func (c *Client) DeleteModelExplainabilityJobDefinition(ctx context.Context, params *DeleteModelExplainabilityJobDefinitionInput, ...) (*DeleteModelExplainabilityJobDefinitionOutput, error)
- func (c *Client) DeleteModelPackage(ctx context.Context, params *DeleteModelPackageInput, optFns ...func(*Options)) (*DeleteModelPackageOutput, error)
- func (c *Client) DeleteModelPackageGroup(ctx context.Context, params *DeleteModelPackageGroupInput, ...) (*DeleteModelPackageGroupOutput, error)
- func (c *Client) DeleteModelPackageGroupPolicy(ctx context.Context, params *DeleteModelPackageGroupPolicyInput, ...) (*DeleteModelPackageGroupPolicyOutput, error)
- func (c *Client) DeleteModelQualityJobDefinition(ctx context.Context, params *DeleteModelQualityJobDefinitionInput, ...) (*DeleteModelQualityJobDefinitionOutput, error)
- func (c *Client) DeleteMonitoringSchedule(ctx context.Context, params *DeleteMonitoringScheduleInput, ...) (*DeleteMonitoringScheduleOutput, error)
- func (c *Client) DeleteNotebookInstance(ctx context.Context, params *DeleteNotebookInstanceInput, ...) (*DeleteNotebookInstanceOutput, error)
- func (c *Client) DeleteNotebookInstanceLifecycleConfig(ctx context.Context, params *DeleteNotebookInstanceLifecycleConfigInput, ...) (*DeleteNotebookInstanceLifecycleConfigOutput, error)
- func (c *Client) DeletePipeline(ctx context.Context, params *DeletePipelineInput, optFns ...func(*Options)) (*DeletePipelineOutput, error)
- func (c *Client) DeleteProject(ctx context.Context, params *DeleteProjectInput, optFns ...func(*Options)) (*DeleteProjectOutput, error)
- func (c *Client) DeleteTags(ctx context.Context, params *DeleteTagsInput, optFns ...func(*Options)) (*DeleteTagsOutput, error)
- func (c *Client) DeleteTrial(ctx context.Context, params *DeleteTrialInput, optFns ...func(*Options)) (*DeleteTrialOutput, error)
- func (c *Client) DeleteTrialComponent(ctx context.Context, params *DeleteTrialComponentInput, ...) (*DeleteTrialComponentOutput, error)
- func (c *Client) DeleteUserProfile(ctx context.Context, params *DeleteUserProfileInput, optFns ...func(*Options)) (*DeleteUserProfileOutput, error)
- func (c *Client) DeleteWorkforce(ctx context.Context, params *DeleteWorkforceInput, optFns ...func(*Options)) (*DeleteWorkforceOutput, error)
- func (c *Client) DeleteWorkteam(ctx context.Context, params *DeleteWorkteamInput, optFns ...func(*Options)) (*DeleteWorkteamOutput, error)
- func (c *Client) DeregisterDevices(ctx context.Context, params *DeregisterDevicesInput, optFns ...func(*Options)) (*DeregisterDevicesOutput, error)
- func (c *Client) DescribeAction(ctx context.Context, params *DescribeActionInput, optFns ...func(*Options)) (*DescribeActionOutput, error)
- func (c *Client) DescribeAlgorithm(ctx context.Context, params *DescribeAlgorithmInput, optFns ...func(*Options)) (*DescribeAlgorithmOutput, error)
- func (c *Client) DescribeApp(ctx context.Context, params *DescribeAppInput, optFns ...func(*Options)) (*DescribeAppOutput, error)
- func (c *Client) DescribeAppImageConfig(ctx context.Context, params *DescribeAppImageConfigInput, ...) (*DescribeAppImageConfigOutput, error)
- func (c *Client) DescribeArtifact(ctx context.Context, params *DescribeArtifactInput, optFns ...func(*Options)) (*DescribeArtifactOutput, error)
- func (c *Client) DescribeAutoMLJob(ctx context.Context, params *DescribeAutoMLJobInput, optFns ...func(*Options)) (*DescribeAutoMLJobOutput, error)
- func (c *Client) DescribeCodeRepository(ctx context.Context, params *DescribeCodeRepositoryInput, ...) (*DescribeCodeRepositoryOutput, error)
- func (c *Client) DescribeCompilationJob(ctx context.Context, params *DescribeCompilationJobInput, ...) (*DescribeCompilationJobOutput, error)
- func (c *Client) DescribeContext(ctx context.Context, params *DescribeContextInput, optFns ...func(*Options)) (*DescribeContextOutput, error)
- func (c *Client) DescribeDataQualityJobDefinition(ctx context.Context, params *DescribeDataQualityJobDefinitionInput, ...) (*DescribeDataQualityJobDefinitionOutput, error)
- func (c *Client) DescribeDevice(ctx context.Context, params *DescribeDeviceInput, optFns ...func(*Options)) (*DescribeDeviceOutput, error)
- func (c *Client) DescribeDeviceFleet(ctx context.Context, params *DescribeDeviceFleetInput, ...) (*DescribeDeviceFleetOutput, error)
- func (c *Client) DescribeDomain(ctx context.Context, params *DescribeDomainInput, optFns ...func(*Options)) (*DescribeDomainOutput, error)
- func (c *Client) DescribeEdgePackagingJob(ctx context.Context, params *DescribeEdgePackagingJobInput, ...) (*DescribeEdgePackagingJobOutput, error)
- func (c *Client) DescribeEndpoint(ctx context.Context, params *DescribeEndpointInput, optFns ...func(*Options)) (*DescribeEndpointOutput, error)
- func (c *Client) DescribeEndpointConfig(ctx context.Context, params *DescribeEndpointConfigInput, ...) (*DescribeEndpointConfigOutput, error)
- func (c *Client) DescribeExperiment(ctx context.Context, params *DescribeExperimentInput, optFns ...func(*Options)) (*DescribeExperimentOutput, error)
- func (c *Client) DescribeFeatureGroup(ctx context.Context, params *DescribeFeatureGroupInput, ...) (*DescribeFeatureGroupOutput, error)
- func (c *Client) DescribeFlowDefinition(ctx context.Context, params *DescribeFlowDefinitionInput, ...) (*DescribeFlowDefinitionOutput, error)
- func (c *Client) DescribeHumanTaskUi(ctx context.Context, params *DescribeHumanTaskUiInput, ...) (*DescribeHumanTaskUiOutput, error)
- func (c *Client) DescribeHyperParameterTuningJob(ctx context.Context, params *DescribeHyperParameterTuningJobInput, ...) (*DescribeHyperParameterTuningJobOutput, error)
- func (c *Client) DescribeImage(ctx context.Context, params *DescribeImageInput, optFns ...func(*Options)) (*DescribeImageOutput, error)
- func (c *Client) DescribeImageVersion(ctx context.Context, params *DescribeImageVersionInput, ...) (*DescribeImageVersionOutput, error)
- func (c *Client) DescribeLabelingJob(ctx context.Context, params *DescribeLabelingJobInput, ...) (*DescribeLabelingJobOutput, error)
- func (c *Client) DescribeModel(ctx context.Context, params *DescribeModelInput, optFns ...func(*Options)) (*DescribeModelOutput, error)
- func (c *Client) DescribeModelBiasJobDefinition(ctx context.Context, params *DescribeModelBiasJobDefinitionInput, ...) (*DescribeModelBiasJobDefinitionOutput, error)
- func (c *Client) DescribeModelExplainabilityJobDefinition(ctx context.Context, params *DescribeModelExplainabilityJobDefinitionInput, ...) (*DescribeModelExplainabilityJobDefinitionOutput, error)
- func (c *Client) DescribeModelPackage(ctx context.Context, params *DescribeModelPackageInput, ...) (*DescribeModelPackageOutput, error)
- func (c *Client) DescribeModelPackageGroup(ctx context.Context, params *DescribeModelPackageGroupInput, ...) (*DescribeModelPackageGroupOutput, error)
- func (c *Client) DescribeModelQualityJobDefinition(ctx context.Context, params *DescribeModelQualityJobDefinitionInput, ...) (*DescribeModelQualityJobDefinitionOutput, error)
- func (c *Client) DescribeMonitoringSchedule(ctx context.Context, params *DescribeMonitoringScheduleInput, ...) (*DescribeMonitoringScheduleOutput, error)
- func (c *Client) DescribeNotebookInstance(ctx context.Context, params *DescribeNotebookInstanceInput, ...) (*DescribeNotebookInstanceOutput, error)
- func (c *Client) DescribeNotebookInstanceLifecycleConfig(ctx context.Context, params *DescribeNotebookInstanceLifecycleConfigInput, ...) (*DescribeNotebookInstanceLifecycleConfigOutput, error)
- func (c *Client) DescribePipeline(ctx context.Context, params *DescribePipelineInput, optFns ...func(*Options)) (*DescribePipelineOutput, error)
- func (c *Client) DescribePipelineDefinitionForExecution(ctx context.Context, params *DescribePipelineDefinitionForExecutionInput, ...) (*DescribePipelineDefinitionForExecutionOutput, error)
- func (c *Client) DescribePipelineExecution(ctx context.Context, params *DescribePipelineExecutionInput, ...) (*DescribePipelineExecutionOutput, error)
- func (c *Client) DescribeProcessingJob(ctx context.Context, params *DescribeProcessingJobInput, ...) (*DescribeProcessingJobOutput, error)
- func (c *Client) DescribeProject(ctx context.Context, params *DescribeProjectInput, optFns ...func(*Options)) (*DescribeProjectOutput, error)
- func (c *Client) DescribeSubscribedWorkteam(ctx context.Context, params *DescribeSubscribedWorkteamInput, ...) (*DescribeSubscribedWorkteamOutput, error)
- func (c *Client) DescribeTrainingJob(ctx context.Context, params *DescribeTrainingJobInput, ...) (*DescribeTrainingJobOutput, error)
- func (c *Client) DescribeTransformJob(ctx context.Context, params *DescribeTransformJobInput, ...) (*DescribeTransformJobOutput, error)
- func (c *Client) DescribeTrial(ctx context.Context, params *DescribeTrialInput, optFns ...func(*Options)) (*DescribeTrialOutput, error)
- func (c *Client) DescribeTrialComponent(ctx context.Context, params *DescribeTrialComponentInput, ...) (*DescribeTrialComponentOutput, error)
- func (c *Client) DescribeUserProfile(ctx context.Context, params *DescribeUserProfileInput, ...) (*DescribeUserProfileOutput, error)
- func (c *Client) DescribeWorkforce(ctx context.Context, params *DescribeWorkforceInput, optFns ...func(*Options)) (*DescribeWorkforceOutput, error)
- func (c *Client) DescribeWorkteam(ctx context.Context, params *DescribeWorkteamInput, optFns ...func(*Options)) (*DescribeWorkteamOutput, error)
- func (c *Client) DisableSagemakerServicecatalogPortfolio(ctx context.Context, params *DisableSagemakerServicecatalogPortfolioInput, ...) (*DisableSagemakerServicecatalogPortfolioOutput, error)
- func (c *Client) DisassociateTrialComponent(ctx context.Context, params *DisassociateTrialComponentInput, ...) (*DisassociateTrialComponentOutput, error)
- func (c *Client) EnableSagemakerServicecatalogPortfolio(ctx context.Context, params *EnableSagemakerServicecatalogPortfolioInput, ...) (*EnableSagemakerServicecatalogPortfolioOutput, error)
- func (c *Client) GetDeviceFleetReport(ctx context.Context, params *GetDeviceFleetReportInput, ...) (*GetDeviceFleetReportOutput, error)
- func (c *Client) GetModelPackageGroupPolicy(ctx context.Context, params *GetModelPackageGroupPolicyInput, ...) (*GetModelPackageGroupPolicyOutput, error)
- func (c *Client) GetSagemakerServicecatalogPortfolioStatus(ctx context.Context, params *GetSagemakerServicecatalogPortfolioStatusInput, ...) (*GetSagemakerServicecatalogPortfolioStatusOutput, error)
- func (c *Client) GetSearchSuggestions(ctx context.Context, params *GetSearchSuggestionsInput, ...) (*GetSearchSuggestionsOutput, error)
- func (c *Client) ListActions(ctx context.Context, params *ListActionsInput, optFns ...func(*Options)) (*ListActionsOutput, error)
- func (c *Client) ListAlgorithms(ctx context.Context, params *ListAlgorithmsInput, optFns ...func(*Options)) (*ListAlgorithmsOutput, error)
- func (c *Client) ListAppImageConfigs(ctx context.Context, params *ListAppImageConfigsInput, ...) (*ListAppImageConfigsOutput, error)
- func (c *Client) ListApps(ctx context.Context, params *ListAppsInput, optFns ...func(*Options)) (*ListAppsOutput, error)
- func (c *Client) ListArtifacts(ctx context.Context, params *ListArtifactsInput, optFns ...func(*Options)) (*ListArtifactsOutput, error)
- func (c *Client) ListAssociations(ctx context.Context, params *ListAssociationsInput, optFns ...func(*Options)) (*ListAssociationsOutput, error)
- func (c *Client) ListAutoMLJobs(ctx context.Context, params *ListAutoMLJobsInput, optFns ...func(*Options)) (*ListAutoMLJobsOutput, error)
- func (c *Client) ListCandidatesForAutoMLJob(ctx context.Context, params *ListCandidatesForAutoMLJobInput, ...) (*ListCandidatesForAutoMLJobOutput, error)
- func (c *Client) ListCodeRepositories(ctx context.Context, params *ListCodeRepositoriesInput, ...) (*ListCodeRepositoriesOutput, error)
- func (c *Client) ListCompilationJobs(ctx context.Context, params *ListCompilationJobsInput, ...) (*ListCompilationJobsOutput, error)
- func (c *Client) ListContexts(ctx context.Context, params *ListContextsInput, optFns ...func(*Options)) (*ListContextsOutput, error)
- func (c *Client) ListDataQualityJobDefinitions(ctx context.Context, params *ListDataQualityJobDefinitionsInput, ...) (*ListDataQualityJobDefinitionsOutput, error)
- func (c *Client) ListDeviceFleets(ctx context.Context, params *ListDeviceFleetsInput, optFns ...func(*Options)) (*ListDeviceFleetsOutput, error)
- func (c *Client) ListDevices(ctx context.Context, params *ListDevicesInput, optFns ...func(*Options)) (*ListDevicesOutput, error)
- func (c *Client) ListDomains(ctx context.Context, params *ListDomainsInput, optFns ...func(*Options)) (*ListDomainsOutput, error)
- func (c *Client) ListEdgePackagingJobs(ctx context.Context, params *ListEdgePackagingJobsInput, ...) (*ListEdgePackagingJobsOutput, error)
- func (c *Client) ListEndpointConfigs(ctx context.Context, params *ListEndpointConfigsInput, ...) (*ListEndpointConfigsOutput, error)
- func (c *Client) ListEndpoints(ctx context.Context, params *ListEndpointsInput, optFns ...func(*Options)) (*ListEndpointsOutput, error)
- func (c *Client) ListExperiments(ctx context.Context, params *ListExperimentsInput, optFns ...func(*Options)) (*ListExperimentsOutput, error)
- func (c *Client) ListFeatureGroups(ctx context.Context, params *ListFeatureGroupsInput, optFns ...func(*Options)) (*ListFeatureGroupsOutput, error)
- func (c *Client) ListFlowDefinitions(ctx context.Context, params *ListFlowDefinitionsInput, ...) (*ListFlowDefinitionsOutput, error)
- func (c *Client) ListHumanTaskUis(ctx context.Context, params *ListHumanTaskUisInput, optFns ...func(*Options)) (*ListHumanTaskUisOutput, error)
- func (c *Client) ListHyperParameterTuningJobs(ctx context.Context, params *ListHyperParameterTuningJobsInput, ...) (*ListHyperParameterTuningJobsOutput, error)
- func (c *Client) ListImageVersions(ctx context.Context, params *ListImageVersionsInput, optFns ...func(*Options)) (*ListImageVersionsOutput, error)
- func (c *Client) ListImages(ctx context.Context, params *ListImagesInput, optFns ...func(*Options)) (*ListImagesOutput, error)
- func (c *Client) ListLabelingJobs(ctx context.Context, params *ListLabelingJobsInput, optFns ...func(*Options)) (*ListLabelingJobsOutput, error)
- func (c *Client) ListLabelingJobsForWorkteam(ctx context.Context, params *ListLabelingJobsForWorkteamInput, ...) (*ListLabelingJobsForWorkteamOutput, error)
- func (c *Client) ListModelBiasJobDefinitions(ctx context.Context, params *ListModelBiasJobDefinitionsInput, ...) (*ListModelBiasJobDefinitionsOutput, error)
- func (c *Client) ListModelExplainabilityJobDefinitions(ctx context.Context, params *ListModelExplainabilityJobDefinitionsInput, ...) (*ListModelExplainabilityJobDefinitionsOutput, error)
- func (c *Client) ListModelPackageGroups(ctx context.Context, params *ListModelPackageGroupsInput, ...) (*ListModelPackageGroupsOutput, error)
- func (c *Client) ListModelPackages(ctx context.Context, params *ListModelPackagesInput, optFns ...func(*Options)) (*ListModelPackagesOutput, error)
- func (c *Client) ListModelQualityJobDefinitions(ctx context.Context, params *ListModelQualityJobDefinitionsInput, ...) (*ListModelQualityJobDefinitionsOutput, error)
- func (c *Client) ListModels(ctx context.Context, params *ListModelsInput, optFns ...func(*Options)) (*ListModelsOutput, error)
- func (c *Client) ListMonitoringExecutions(ctx context.Context, params *ListMonitoringExecutionsInput, ...) (*ListMonitoringExecutionsOutput, error)
- func (c *Client) ListMonitoringSchedules(ctx context.Context, params *ListMonitoringSchedulesInput, ...) (*ListMonitoringSchedulesOutput, error)
- func (c *Client) ListNotebookInstanceLifecycleConfigs(ctx context.Context, params *ListNotebookInstanceLifecycleConfigsInput, ...) (*ListNotebookInstanceLifecycleConfigsOutput, error)
- func (c *Client) ListNotebookInstances(ctx context.Context, params *ListNotebookInstancesInput, ...) (*ListNotebookInstancesOutput, error)
- func (c *Client) ListPipelineExecutionSteps(ctx context.Context, params *ListPipelineExecutionStepsInput, ...) (*ListPipelineExecutionStepsOutput, error)
- func (c *Client) ListPipelineExecutions(ctx context.Context, params *ListPipelineExecutionsInput, ...) (*ListPipelineExecutionsOutput, error)
- func (c *Client) ListPipelineParametersForExecution(ctx context.Context, params *ListPipelineParametersForExecutionInput, ...) (*ListPipelineParametersForExecutionOutput, error)
- func (c *Client) ListPipelines(ctx context.Context, params *ListPipelinesInput, optFns ...func(*Options)) (*ListPipelinesOutput, error)
- func (c *Client) ListProcessingJobs(ctx context.Context, params *ListProcessingJobsInput, optFns ...func(*Options)) (*ListProcessingJobsOutput, error)
- func (c *Client) ListProjects(ctx context.Context, params *ListProjectsInput, optFns ...func(*Options)) (*ListProjectsOutput, error)
- func (c *Client) ListSubscribedWorkteams(ctx context.Context, params *ListSubscribedWorkteamsInput, ...) (*ListSubscribedWorkteamsOutput, error)
- func (c *Client) ListTags(ctx context.Context, params *ListTagsInput, optFns ...func(*Options)) (*ListTagsOutput, error)
- func (c *Client) ListTrainingJobs(ctx context.Context, params *ListTrainingJobsInput, optFns ...func(*Options)) (*ListTrainingJobsOutput, error)
- func (c *Client) ListTrainingJobsForHyperParameterTuningJob(ctx context.Context, params *ListTrainingJobsForHyperParameterTuningJobInput, ...) (*ListTrainingJobsForHyperParameterTuningJobOutput, error)
- func (c *Client) ListTransformJobs(ctx context.Context, params *ListTransformJobsInput, optFns ...func(*Options)) (*ListTransformJobsOutput, error)
- func (c *Client) ListTrialComponents(ctx context.Context, params *ListTrialComponentsInput, ...) (*ListTrialComponentsOutput, error)
- func (c *Client) ListTrials(ctx context.Context, params *ListTrialsInput, optFns ...func(*Options)) (*ListTrialsOutput, error)
- func (c *Client) ListUserProfiles(ctx context.Context, params *ListUserProfilesInput, optFns ...func(*Options)) (*ListUserProfilesOutput, error)
- func (c *Client) ListWorkforces(ctx context.Context, params *ListWorkforcesInput, optFns ...func(*Options)) (*ListWorkforcesOutput, error)
- func (c *Client) ListWorkteams(ctx context.Context, params *ListWorkteamsInput, optFns ...func(*Options)) (*ListWorkteamsOutput, error)
- func (c *Client) PutModelPackageGroupPolicy(ctx context.Context, params *PutModelPackageGroupPolicyInput, ...) (*PutModelPackageGroupPolicyOutput, error)
- func (c *Client) RegisterDevices(ctx context.Context, params *RegisterDevicesInput, optFns ...func(*Options)) (*RegisterDevicesOutput, error)
- func (c *Client) RenderUiTemplate(ctx context.Context, params *RenderUiTemplateInput, optFns ...func(*Options)) (*RenderUiTemplateOutput, error)
- func (c *Client) Search(ctx context.Context, params *SearchInput, optFns ...func(*Options)) (*SearchOutput, error)
- func (c *Client) StartMonitoringSchedule(ctx context.Context, params *StartMonitoringScheduleInput, ...) (*StartMonitoringScheduleOutput, error)
- func (c *Client) StartNotebookInstance(ctx context.Context, params *StartNotebookInstanceInput, ...) (*StartNotebookInstanceOutput, error)
- func (c *Client) StartPipelineExecution(ctx context.Context, params *StartPipelineExecutionInput, ...) (*StartPipelineExecutionOutput, error)
- func (c *Client) StopAutoMLJob(ctx context.Context, params *StopAutoMLJobInput, optFns ...func(*Options)) (*StopAutoMLJobOutput, error)
- func (c *Client) StopCompilationJob(ctx context.Context, params *StopCompilationJobInput, optFns ...func(*Options)) (*StopCompilationJobOutput, error)
- func (c *Client) StopEdgePackagingJob(ctx context.Context, params *StopEdgePackagingJobInput, ...) (*StopEdgePackagingJobOutput, error)
- func (c *Client) StopHyperParameterTuningJob(ctx context.Context, params *StopHyperParameterTuningJobInput, ...) (*StopHyperParameterTuningJobOutput, error)
- func (c *Client) StopLabelingJob(ctx context.Context, params *StopLabelingJobInput, optFns ...func(*Options)) (*StopLabelingJobOutput, error)
- func (c *Client) StopMonitoringSchedule(ctx context.Context, params *StopMonitoringScheduleInput, ...) (*StopMonitoringScheduleOutput, error)
- func (c *Client) StopNotebookInstance(ctx context.Context, params *StopNotebookInstanceInput, ...) (*StopNotebookInstanceOutput, error)
- func (c *Client) StopPipelineExecution(ctx context.Context, params *StopPipelineExecutionInput, ...) (*StopPipelineExecutionOutput, error)
- func (c *Client) StopProcessingJob(ctx context.Context, params *StopProcessingJobInput, optFns ...func(*Options)) (*StopProcessingJobOutput, error)
- func (c *Client) StopTrainingJob(ctx context.Context, params *StopTrainingJobInput, optFns ...func(*Options)) (*StopTrainingJobOutput, error)
- func (c *Client) StopTransformJob(ctx context.Context, params *StopTransformJobInput, optFns ...func(*Options)) (*StopTransformJobOutput, error)
- func (c *Client) UpdateAction(ctx context.Context, params *UpdateActionInput, optFns ...func(*Options)) (*UpdateActionOutput, error)
- func (c *Client) UpdateAppImageConfig(ctx context.Context, params *UpdateAppImageConfigInput, ...) (*UpdateAppImageConfigOutput, error)
- func (c *Client) UpdateArtifact(ctx context.Context, params *UpdateArtifactInput, optFns ...func(*Options)) (*UpdateArtifactOutput, error)
- func (c *Client) UpdateCodeRepository(ctx context.Context, params *UpdateCodeRepositoryInput, ...) (*UpdateCodeRepositoryOutput, error)
- func (c *Client) UpdateContext(ctx context.Context, params *UpdateContextInput, optFns ...func(*Options)) (*UpdateContextOutput, error)
- func (c *Client) UpdateDeviceFleet(ctx context.Context, params *UpdateDeviceFleetInput, optFns ...func(*Options)) (*UpdateDeviceFleetOutput, error)
- func (c *Client) UpdateDevices(ctx context.Context, params *UpdateDevicesInput, optFns ...func(*Options)) (*UpdateDevicesOutput, error)
- func (c *Client) UpdateDomain(ctx context.Context, params *UpdateDomainInput, optFns ...func(*Options)) (*UpdateDomainOutput, error)
- func (c *Client) UpdateEndpoint(ctx context.Context, params *UpdateEndpointInput, optFns ...func(*Options)) (*UpdateEndpointOutput, error)
- func (c *Client) UpdateEndpointWeightsAndCapacities(ctx context.Context, params *UpdateEndpointWeightsAndCapacitiesInput, ...) (*UpdateEndpointWeightsAndCapacitiesOutput, error)
- func (c *Client) UpdateExperiment(ctx context.Context, params *UpdateExperimentInput, optFns ...func(*Options)) (*UpdateExperimentOutput, error)
- func (c *Client) UpdateImage(ctx context.Context, params *UpdateImageInput, optFns ...func(*Options)) (*UpdateImageOutput, error)
- func (c *Client) UpdateModelPackage(ctx context.Context, params *UpdateModelPackageInput, optFns ...func(*Options)) (*UpdateModelPackageOutput, error)
- func (c *Client) UpdateMonitoringSchedule(ctx context.Context, params *UpdateMonitoringScheduleInput, ...) (*UpdateMonitoringScheduleOutput, error)
- func (c *Client) UpdateNotebookInstance(ctx context.Context, params *UpdateNotebookInstanceInput, ...) (*UpdateNotebookInstanceOutput, error)
- func (c *Client) UpdateNotebookInstanceLifecycleConfig(ctx context.Context, params *UpdateNotebookInstanceLifecycleConfigInput, ...) (*UpdateNotebookInstanceLifecycleConfigOutput, error)
- func (c *Client) UpdatePipeline(ctx context.Context, params *UpdatePipelineInput, optFns ...func(*Options)) (*UpdatePipelineOutput, error)
- func (c *Client) UpdatePipelineExecution(ctx context.Context, params *UpdatePipelineExecutionInput, ...) (*UpdatePipelineExecutionOutput, error)
- func (c *Client) UpdateTrainingJob(ctx context.Context, params *UpdateTrainingJobInput, optFns ...func(*Options)) (*UpdateTrainingJobOutput, error)
- func (c *Client) UpdateTrial(ctx context.Context, params *UpdateTrialInput, optFns ...func(*Options)) (*UpdateTrialOutput, error)
- func (c *Client) UpdateTrialComponent(ctx context.Context, params *UpdateTrialComponentInput, ...) (*UpdateTrialComponentOutput, error)
- func (c *Client) UpdateUserProfile(ctx context.Context, params *UpdateUserProfileInput, optFns ...func(*Options)) (*UpdateUserProfileOutput, error)
- func (c *Client) UpdateWorkforce(ctx context.Context, params *UpdateWorkforceInput, optFns ...func(*Options)) (*UpdateWorkforceOutput, error)
- func (c *Client) UpdateWorkteam(ctx context.Context, params *UpdateWorkteamInput, optFns ...func(*Options)) (*UpdateWorkteamOutput, error)
- type CreateActionInput
- type CreateActionOutput
- type CreateAlgorithmInput
- type CreateAlgorithmOutput
- type CreateAppImageConfigInput
- type CreateAppImageConfigOutput
- type CreateAppInput
- type CreateAppOutput
- type CreateArtifactInput
- type CreateArtifactOutput
- type CreateAutoMLJobInput
- type CreateAutoMLJobOutput
- type CreateCodeRepositoryInput
- type CreateCodeRepositoryOutput
- type CreateCompilationJobInput
- type CreateCompilationJobOutput
- type CreateContextInput
- type CreateContextOutput
- type CreateDataQualityJobDefinitionInput
- type CreateDataQualityJobDefinitionOutput
- type CreateDeviceFleetInput
- type CreateDeviceFleetOutput
- type CreateDomainInput
- type CreateDomainOutput
- type CreateEdgePackagingJobInput
- type CreateEdgePackagingJobOutput
- type CreateEndpointConfigInput
- type CreateEndpointConfigOutput
- type CreateEndpointInput
- type CreateEndpointOutput
- type CreateExperimentInput
- type CreateExperimentOutput
- type CreateFeatureGroupInput
- type CreateFeatureGroupOutput
- type CreateFlowDefinitionInput
- type CreateFlowDefinitionOutput
- type CreateHumanTaskUiInput
- type CreateHumanTaskUiOutput
- type CreateHyperParameterTuningJobInput
- type CreateHyperParameterTuningJobOutput
- type CreateImageInput
- type CreateImageOutput
- type CreateImageVersionInput
- type CreateImageVersionOutput
- type CreateLabelingJobInput
- type CreateLabelingJobOutput
- type CreateModelBiasJobDefinitionInput
- type CreateModelBiasJobDefinitionOutput
- type CreateModelExplainabilityJobDefinitionInput
- type CreateModelExplainabilityJobDefinitionOutput
- type CreateModelInput
- type CreateModelOutput
- type CreateModelPackageGroupInput
- type CreateModelPackageGroupOutput
- type CreateModelPackageInput
- type CreateModelPackageOutput
- type CreateModelQualityJobDefinitionInput
- type CreateModelQualityJobDefinitionOutput
- type CreateMonitoringScheduleInput
- type CreateMonitoringScheduleOutput
- type CreateNotebookInstanceInput
- type CreateNotebookInstanceLifecycleConfigInput
- type CreateNotebookInstanceLifecycleConfigOutput
- type CreateNotebookInstanceOutput
- type CreatePipelineInput
- type CreatePipelineOutput
- type CreatePresignedDomainUrlInput
- type CreatePresignedDomainUrlOutput
- type CreatePresignedNotebookInstanceUrlInput
- type CreatePresignedNotebookInstanceUrlOutput
- type CreateProcessingJobInput
- type CreateProcessingJobOutput
- type CreateProjectInput
- type CreateProjectOutput
- type CreateTrainingJobInput
- type CreateTrainingJobOutput
- type CreateTransformJobInput
- type CreateTransformJobOutput
- type CreateTrialComponentInput
- type CreateTrialComponentOutput
- type CreateTrialInput
- type CreateTrialOutput
- type CreateUserProfileInput
- type CreateUserProfileOutput
- type CreateWorkforceInput
- type CreateWorkforceOutput
- type CreateWorkteamInput
- type CreateWorkteamOutput
- type DeleteActionInput
- type DeleteActionOutput
- type DeleteAlgorithmInput
- type DeleteAlgorithmOutput
- type DeleteAppImageConfigInput
- type DeleteAppImageConfigOutput
- type DeleteAppInput
- type DeleteAppOutput
- type DeleteArtifactInput
- type DeleteArtifactOutput
- type DeleteAssociationInput
- type DeleteAssociationOutput
- type DeleteCodeRepositoryInput
- type DeleteCodeRepositoryOutput
- type DeleteContextInput
- type DeleteContextOutput
- type DeleteDataQualityJobDefinitionInput
- type DeleteDataQualityJobDefinitionOutput
- type DeleteDeviceFleetInput
- type DeleteDeviceFleetOutput
- type DeleteDomainInput
- type DeleteDomainOutput
- type DeleteEndpointConfigInput
- type DeleteEndpointConfigOutput
- type DeleteEndpointInput
- type DeleteEndpointOutput
- type DeleteExperimentInput
- type DeleteExperimentOutput
- type DeleteFeatureGroupInput
- type DeleteFeatureGroupOutput
- type DeleteFlowDefinitionInput
- type DeleteFlowDefinitionOutput
- type DeleteHumanTaskUiInput
- type DeleteHumanTaskUiOutput
- type DeleteImageInput
- type DeleteImageOutput
- type DeleteImageVersionInput
- type DeleteImageVersionOutput
- type DeleteModelBiasJobDefinitionInput
- type DeleteModelBiasJobDefinitionOutput
- type DeleteModelExplainabilityJobDefinitionInput
- type DeleteModelExplainabilityJobDefinitionOutput
- type DeleteModelInput
- type DeleteModelOutput
- type DeleteModelPackageGroupInput
- type DeleteModelPackageGroupOutput
- type DeleteModelPackageGroupPolicyInput
- type DeleteModelPackageGroupPolicyOutput
- type DeleteModelPackageInput
- type DeleteModelPackageOutput
- type DeleteModelQualityJobDefinitionInput
- type DeleteModelQualityJobDefinitionOutput
- type DeleteMonitoringScheduleInput
- type DeleteMonitoringScheduleOutput
- type DeleteNotebookInstanceInput
- type DeleteNotebookInstanceLifecycleConfigInput
- type DeleteNotebookInstanceLifecycleConfigOutput
- type DeleteNotebookInstanceOutput
- type DeletePipelineInput
- type DeletePipelineOutput
- type DeleteProjectInput
- type DeleteProjectOutput
- type DeleteTagsInput
- type DeleteTagsOutput
- type DeleteTrialComponentInput
- type DeleteTrialComponentOutput
- type DeleteTrialInput
- type DeleteTrialOutput
- type DeleteUserProfileInput
- type DeleteUserProfileOutput
- type DeleteWorkforceInput
- type DeleteWorkforceOutput
- type DeleteWorkteamInput
- type DeleteWorkteamOutput
- type DeregisterDevicesInput
- type DeregisterDevicesOutput
- type DescribeActionInput
- type DescribeActionOutput
- type DescribeAlgorithmInput
- type DescribeAlgorithmOutput
- type DescribeAppImageConfigInput
- type DescribeAppImageConfigOutput
- type DescribeAppInput
- type DescribeAppOutput
- type DescribeArtifactInput
- type DescribeArtifactOutput
- type DescribeAutoMLJobInput
- type DescribeAutoMLJobOutput
- type DescribeCodeRepositoryInput
- type DescribeCodeRepositoryOutput
- type DescribeCompilationJobInput
- type DescribeCompilationJobOutput
- type DescribeContextInput
- type DescribeContextOutput
- type DescribeDataQualityJobDefinitionInput
- type DescribeDataQualityJobDefinitionOutput
- type DescribeDeviceFleetInput
- type DescribeDeviceFleetOutput
- type DescribeDeviceInput
- type DescribeDeviceOutput
- type DescribeDomainInput
- type DescribeDomainOutput
- type DescribeEdgePackagingJobInput
- type DescribeEdgePackagingJobOutput
- type DescribeEndpointConfigInput
- type DescribeEndpointConfigOutput
- type DescribeEndpointInput
- type DescribeEndpointOutput
- type DescribeExperimentInput
- type DescribeExperimentOutput
- type DescribeFeatureGroupInput
- type DescribeFeatureGroupOutput
- type DescribeFlowDefinitionInput
- type DescribeFlowDefinitionOutput
- type DescribeHumanTaskUiInput
- type DescribeHumanTaskUiOutput
- type DescribeHyperParameterTuningJobInput
- type DescribeHyperParameterTuningJobOutput
- type DescribeImageInput
- type DescribeImageOutput
- type DescribeImageVersionInput
- type DescribeImageVersionOutput
- type DescribeLabelingJobInput
- type DescribeLabelingJobOutput
- type DescribeModelBiasJobDefinitionInput
- type DescribeModelBiasJobDefinitionOutput
- type DescribeModelExplainabilityJobDefinitionInput
- type DescribeModelExplainabilityJobDefinitionOutput
- type DescribeModelInput
- type DescribeModelOutput
- type DescribeModelPackageGroupInput
- type DescribeModelPackageGroupOutput
- type DescribeModelPackageInput
- type DescribeModelPackageOutput
- type DescribeModelQualityJobDefinitionInput
- type DescribeModelQualityJobDefinitionOutput
- type DescribeMonitoringScheduleInput
- type DescribeMonitoringScheduleOutput
- type DescribeNotebookInstanceAPIClient
- type DescribeNotebookInstanceInput
- type DescribeNotebookInstanceLifecycleConfigInput
- type DescribeNotebookInstanceLifecycleConfigOutput
- type DescribeNotebookInstanceOutput
- type DescribePipelineDefinitionForExecutionInput
- type DescribePipelineDefinitionForExecutionOutput
- type DescribePipelineExecutionInput
- type DescribePipelineExecutionOutput
- type DescribePipelineInput
- type DescribePipelineOutput
- type DescribeProcessingJobInput
- type DescribeProcessingJobOutput
- type DescribeProjectInput
- type DescribeProjectOutput
- type DescribeSubscribedWorkteamInput
- type DescribeSubscribedWorkteamOutput
- type DescribeTrainingJobInput
- type DescribeTrainingJobOutput
- type DescribeTransformJobInput
- type DescribeTransformJobOutput
- type DescribeTrialComponentInput
- type DescribeTrialComponentOutput
- type DescribeTrialInput
- type DescribeTrialOutput
- type DescribeUserProfileInput
- type DescribeUserProfileOutput
- type DescribeWorkforceInput
- type DescribeWorkforceOutput
- type DescribeWorkteamInput
- type DescribeWorkteamOutput
- type DisableSagemakerServicecatalogPortfolioInput
- type DisableSagemakerServicecatalogPortfolioOutput
- type DisassociateTrialComponentInput
- type DisassociateTrialComponentOutput
- type EnableSagemakerServicecatalogPortfolioInput
- type EnableSagemakerServicecatalogPortfolioOutput
- type EndpointResolver
- type EndpointResolverFunc
- type EndpointResolverOptions
- type GetDeviceFleetReportInput
- type GetDeviceFleetReportOutput
- type GetModelPackageGroupPolicyInput
- type GetModelPackageGroupPolicyOutput
- type GetSagemakerServicecatalogPortfolioStatusInput
- type GetSagemakerServicecatalogPortfolioStatusOutput
- type GetSearchSuggestionsInput
- type GetSearchSuggestionsOutput
- type HTTPClient
- type HTTPSignerV4
- type IdempotencyTokenProvider
- type ListActionsAPIClient
- type ListActionsInput
- type ListActionsOutput
- type ListActionsPaginator
- type ListActionsPaginatorOptions
- type ListAlgorithmsAPIClient
- type ListAlgorithmsInput
- type ListAlgorithmsOutput
- type ListAlgorithmsPaginator
- type ListAlgorithmsPaginatorOptions
- type ListAppImageConfigsAPIClient
- type ListAppImageConfigsInput
- type ListAppImageConfigsOutput
- type ListAppImageConfigsPaginator
- type ListAppImageConfigsPaginatorOptions
- type ListAppsAPIClient
- type ListAppsInput
- type ListAppsOutput
- type ListAppsPaginator
- type ListAppsPaginatorOptions
- type ListArtifactsAPIClient
- type ListArtifactsInput
- type ListArtifactsOutput
- type ListArtifactsPaginator
- type ListArtifactsPaginatorOptions
- type ListAssociationsAPIClient
- type ListAssociationsInput
- type ListAssociationsOutput
- type ListAssociationsPaginator
- type ListAssociationsPaginatorOptions
- type ListAutoMLJobsAPIClient
- type ListAutoMLJobsInput
- type ListAutoMLJobsOutput
- type ListAutoMLJobsPaginator
- type ListAutoMLJobsPaginatorOptions
- type ListCandidatesForAutoMLJobAPIClient
- type ListCandidatesForAutoMLJobInput
- type ListCandidatesForAutoMLJobOutput
- type ListCandidatesForAutoMLJobPaginator
- type ListCandidatesForAutoMLJobPaginatorOptions
- type ListCodeRepositoriesAPIClient
- type ListCodeRepositoriesInput
- type ListCodeRepositoriesOutput
- type ListCodeRepositoriesPaginator
- type ListCodeRepositoriesPaginatorOptions
- type ListCompilationJobsAPIClient
- type ListCompilationJobsInput
- type ListCompilationJobsOutput
- type ListCompilationJobsPaginator
- type ListCompilationJobsPaginatorOptions
- type ListContextsAPIClient
- type ListContextsInput
- type ListContextsOutput
- type ListContextsPaginator
- type ListContextsPaginatorOptions
- type ListDataQualityJobDefinitionsAPIClient
- type ListDataQualityJobDefinitionsInput
- type ListDataQualityJobDefinitionsOutput
- type ListDataQualityJobDefinitionsPaginator
- type ListDataQualityJobDefinitionsPaginatorOptions
- type ListDeviceFleetsAPIClient
- type ListDeviceFleetsInput
- type ListDeviceFleetsOutput
- type ListDeviceFleetsPaginator
- type ListDeviceFleetsPaginatorOptions
- type ListDevicesAPIClient
- type ListDevicesInput
- type ListDevicesOutput
- type ListDevicesPaginator
- type ListDevicesPaginatorOptions
- type ListDomainsAPIClient
- type ListDomainsInput
- type ListDomainsOutput
- type ListDomainsPaginator
- type ListDomainsPaginatorOptions
- type ListEdgePackagingJobsAPIClient
- type ListEdgePackagingJobsInput
- type ListEdgePackagingJobsOutput
- type ListEdgePackagingJobsPaginator
- type ListEdgePackagingJobsPaginatorOptions
- type ListEndpointConfigsAPIClient
- type ListEndpointConfigsInput
- type ListEndpointConfigsOutput
- type ListEndpointConfigsPaginator
- type ListEndpointConfigsPaginatorOptions
- type ListEndpointsAPIClient
- type ListEndpointsInput
- type ListEndpointsOutput
- type ListEndpointsPaginator
- type ListEndpointsPaginatorOptions
- type ListExperimentsAPIClient
- type ListExperimentsInput
- type ListExperimentsOutput
- type ListExperimentsPaginator
- type ListExperimentsPaginatorOptions
- type ListFeatureGroupsInput
- type ListFeatureGroupsOutput
- type ListFlowDefinitionsAPIClient
- type ListFlowDefinitionsInput
- type ListFlowDefinitionsOutput
- type ListFlowDefinitionsPaginator
- type ListFlowDefinitionsPaginatorOptions
- type ListHumanTaskUisAPIClient
- type ListHumanTaskUisInput
- type ListHumanTaskUisOutput
- type ListHumanTaskUisPaginator
- type ListHumanTaskUisPaginatorOptions
- type ListHyperParameterTuningJobsAPIClient
- type ListHyperParameterTuningJobsInput
- type ListHyperParameterTuningJobsOutput
- type ListHyperParameterTuningJobsPaginator
- type ListHyperParameterTuningJobsPaginatorOptions
- type ListImageVersionsAPIClient
- type ListImageVersionsInput
- type ListImageVersionsOutput
- type ListImageVersionsPaginator
- type ListImageVersionsPaginatorOptions
- type ListImagesAPIClient
- type ListImagesInput
- type ListImagesOutput
- type ListImagesPaginator
- type ListImagesPaginatorOptions
- type ListLabelingJobsAPIClient
- type ListLabelingJobsForWorkteamAPIClient
- type ListLabelingJobsForWorkteamInput
- type ListLabelingJobsForWorkteamOutput
- type ListLabelingJobsForWorkteamPaginator
- type ListLabelingJobsForWorkteamPaginatorOptions
- type ListLabelingJobsInput
- type ListLabelingJobsOutput
- type ListLabelingJobsPaginator
- type ListLabelingJobsPaginatorOptions
- type ListModelBiasJobDefinitionsAPIClient
- type ListModelBiasJobDefinitionsInput
- type ListModelBiasJobDefinitionsOutput
- type ListModelBiasJobDefinitionsPaginator
- type ListModelBiasJobDefinitionsPaginatorOptions
- type ListModelExplainabilityJobDefinitionsAPIClient
- type ListModelExplainabilityJobDefinitionsInput
- type ListModelExplainabilityJobDefinitionsOutput
- type ListModelExplainabilityJobDefinitionsPaginator
- type ListModelExplainabilityJobDefinitionsPaginatorOptions
- type ListModelPackageGroupsAPIClient
- type ListModelPackageGroupsInput
- type ListModelPackageGroupsOutput
- type ListModelPackageGroupsPaginator
- type ListModelPackageGroupsPaginatorOptions
- type ListModelPackagesAPIClient
- type ListModelPackagesInput
- type ListModelPackagesOutput
- type ListModelPackagesPaginator
- type ListModelPackagesPaginatorOptions
- type ListModelQualityJobDefinitionsAPIClient
- type ListModelQualityJobDefinitionsInput
- type ListModelQualityJobDefinitionsOutput
- type ListModelQualityJobDefinitionsPaginator
- type ListModelQualityJobDefinitionsPaginatorOptions
- type ListModelsAPIClient
- type ListModelsInput
- type ListModelsOutput
- type ListModelsPaginator
- type ListModelsPaginatorOptions
- type ListMonitoringExecutionsAPIClient
- type ListMonitoringExecutionsInput
- type ListMonitoringExecutionsOutput
- type ListMonitoringExecutionsPaginator
- type ListMonitoringExecutionsPaginatorOptions
- type ListMonitoringSchedulesAPIClient
- type ListMonitoringSchedulesInput
- type ListMonitoringSchedulesOutput
- type ListMonitoringSchedulesPaginator
- type ListMonitoringSchedulesPaginatorOptions
- type ListNotebookInstanceLifecycleConfigsAPIClient
- type ListNotebookInstanceLifecycleConfigsInput
- type ListNotebookInstanceLifecycleConfigsOutput
- type ListNotebookInstanceLifecycleConfigsPaginator
- type ListNotebookInstanceLifecycleConfigsPaginatorOptions
- type ListNotebookInstancesAPIClient
- type ListNotebookInstancesInput
- type ListNotebookInstancesOutput
- type ListNotebookInstancesPaginator
- type ListNotebookInstancesPaginatorOptions
- type ListPipelineExecutionStepsAPIClient
- type ListPipelineExecutionStepsInput
- type ListPipelineExecutionStepsOutput
- type ListPipelineExecutionStepsPaginator
- type ListPipelineExecutionStepsPaginatorOptions
- type ListPipelineExecutionsAPIClient
- type ListPipelineExecutionsInput
- type ListPipelineExecutionsOutput
- type ListPipelineExecutionsPaginator
- type ListPipelineExecutionsPaginatorOptions
- type ListPipelineParametersForExecutionAPIClient
- type ListPipelineParametersForExecutionInput
- type ListPipelineParametersForExecutionOutput
- type ListPipelineParametersForExecutionPaginator
- type ListPipelineParametersForExecutionPaginatorOptions
- type ListPipelinesAPIClient
- type ListPipelinesInput
- type ListPipelinesOutput
- type ListPipelinesPaginator
- type ListPipelinesPaginatorOptions
- type ListProcessingJobsAPIClient
- type ListProcessingJobsInput
- type ListProcessingJobsOutput
- type ListProcessingJobsPaginator
- type ListProcessingJobsPaginatorOptions
- type ListProjectsAPIClient
- type ListProjectsInput
- type ListProjectsOutput
- type ListProjectsPaginator
- type ListProjectsPaginatorOptions
- type ListSubscribedWorkteamsAPIClient
- type ListSubscribedWorkteamsInput
- type ListSubscribedWorkteamsOutput
- type ListSubscribedWorkteamsPaginator
- type ListSubscribedWorkteamsPaginatorOptions
- type ListTagsAPIClient
- type ListTagsInput
- type ListTagsOutput
- type ListTagsPaginator
- type ListTagsPaginatorOptions
- type ListTrainingJobsAPIClient
- type ListTrainingJobsForHyperParameterTuningJobAPIClient
- type ListTrainingJobsForHyperParameterTuningJobInput
- type ListTrainingJobsForHyperParameterTuningJobOutput
- type ListTrainingJobsForHyperParameterTuningJobPaginator
- type ListTrainingJobsForHyperParameterTuningJobPaginatorOptions
- type ListTrainingJobsInput
- type ListTrainingJobsOutput
- type ListTrainingJobsPaginator
- type ListTrainingJobsPaginatorOptions
- type ListTransformJobsAPIClient
- type ListTransformJobsInput
- type ListTransformJobsOutput
- type ListTransformJobsPaginator
- type ListTransformJobsPaginatorOptions
- type ListTrialComponentsAPIClient
- type ListTrialComponentsInput
- type ListTrialComponentsOutput
- type ListTrialComponentsPaginator
- type ListTrialComponentsPaginatorOptions
- type ListTrialsAPIClient
- type ListTrialsInput
- type ListTrialsOutput
- type ListTrialsPaginator
- type ListTrialsPaginatorOptions
- type ListUserProfilesAPIClient
- type ListUserProfilesInput
- type ListUserProfilesOutput
- type ListUserProfilesPaginator
- type ListUserProfilesPaginatorOptions
- type ListWorkforcesAPIClient
- type ListWorkforcesInput
- type ListWorkforcesOutput
- type ListWorkforcesPaginator
- type ListWorkforcesPaginatorOptions
- type ListWorkteamsAPIClient
- type ListWorkteamsInput
- type ListWorkteamsOutput
- type ListWorkteamsPaginator
- type ListWorkteamsPaginatorOptions
- type NotebookInstanceInServiceWaiter
- type NotebookInstanceInServiceWaiterOptions
- type NotebookInstanceStoppedWaiter
- type NotebookInstanceStoppedWaiterOptions
- type Options
- type PutModelPackageGroupPolicyInput
- type PutModelPackageGroupPolicyOutput
- type RegisterDevicesInput
- type RegisterDevicesOutput
- type RenderUiTemplateInput
- type RenderUiTemplateOutput
- type ResolveEndpoint
- type SearchAPIClient
- type SearchInput
- type SearchOutput
- type SearchPaginator
- type SearchPaginatorOptions
- type StartMonitoringScheduleInput
- type StartMonitoringScheduleOutput
- type StartNotebookInstanceInput
- type StartNotebookInstanceOutput
- type StartPipelineExecutionInput
- type StartPipelineExecutionOutput
- type StopAutoMLJobInput
- type StopAutoMLJobOutput
- type StopCompilationJobInput
- type StopCompilationJobOutput
- type StopEdgePackagingJobInput
- type StopEdgePackagingJobOutput
- type StopHyperParameterTuningJobInput
- type StopHyperParameterTuningJobOutput
- type StopLabelingJobInput
- type StopLabelingJobOutput
- type StopMonitoringScheduleInput
- type StopMonitoringScheduleOutput
- type StopNotebookInstanceInput
- type StopNotebookInstanceOutput
- type StopPipelineExecutionInput
- type StopPipelineExecutionOutput
- type StopProcessingJobInput
- type StopProcessingJobOutput
- type StopTrainingJobInput
- type StopTrainingJobOutput
- type StopTransformJobInput
- type StopTransformJobOutput
- type UpdateActionInput
- type UpdateActionOutput
- type UpdateAppImageConfigInput
- type UpdateAppImageConfigOutput
- type UpdateArtifactInput
- type UpdateArtifactOutput
- type UpdateCodeRepositoryInput
- type UpdateCodeRepositoryOutput
- type UpdateContextInput
- type UpdateContextOutput
- type UpdateDeviceFleetInput
- type UpdateDeviceFleetOutput
- type UpdateDevicesInput
- type UpdateDevicesOutput
- type UpdateDomainInput
- type UpdateDomainOutput
- type UpdateEndpointInput
- type UpdateEndpointOutput
- type UpdateEndpointWeightsAndCapacitiesInput
- type UpdateEndpointWeightsAndCapacitiesOutput
- type UpdateExperimentInput
- type UpdateExperimentOutput
- type UpdateImageInput
- type UpdateImageOutput
- type UpdateModelPackageInput
- type UpdateModelPackageOutput
- type UpdateMonitoringScheduleInput
- type UpdateMonitoringScheduleOutput
- type UpdateNotebookInstanceInput
- type UpdateNotebookInstanceLifecycleConfigInput
- type UpdateNotebookInstanceLifecycleConfigOutput
- type UpdateNotebookInstanceOutput
- type UpdatePipelineExecutionInput
- type UpdatePipelineExecutionOutput
- type UpdatePipelineInput
- type UpdatePipelineOutput
- type UpdateTrainingJobInput
- type UpdateTrainingJobOutput
- type UpdateTrialComponentInput
- type UpdateTrialComponentOutput
- type UpdateTrialInput
- type UpdateTrialOutput
- type UpdateUserProfileInput
- type UpdateUserProfileOutput
- type UpdateWorkforceInput
- type UpdateWorkforceOutput
- type UpdateWorkteamInput
- type UpdateWorkteamOutput
Constants ¶
const ServiceAPIVersion = "2017-07-24"
const ServiceID = "SageMaker"
Variables ¶
Functions ¶
func NewDefaultEndpointResolver ¶
func NewDefaultEndpointResolver() *internalendpoints.Resolver
NewDefaultEndpointResolver constructs a new service endpoint resolver
func WithAPIOptions ¶
func WithAPIOptions(optFns ...func(*middleware.Stack) error) func(*Options)
WithAPIOptions returns a functional option for setting the Client's APIOptions option.
func WithEndpointResolver ¶
func WithEndpointResolver(v EndpointResolver) func(*Options)
WithEndpointResolver returns a functional option for setting the Client's EndpointResolver option.
Types ¶
type AddAssociationInput ¶
type AddAssociationInput struct { // The Amazon Resource Name (ARN) of the destination. // // This member is required. DestinationArn *string // The ARN of the source. // // This member is required. SourceArn *string // The type of association. The following are suggested uses for each type. Amazon // SageMaker places no restrictions on their use. // // * ContributedTo - The source // contributed to the destination or had a part in enabling the destination. For // example, the training data contributed to the training job. // // * AssociatedWith - // The source is connected to the destination. For example, an approval workflow is // associated with a model deployment. // // * DerivedFrom - The destination is a // modification of the source. For example, a digest output of a channel input for // a processing job is derived from the original inputs. // // * Produced - The source // generated the destination. For example, a training job produced a model // artifact. AssociationType types.AssociationEdgeType }
type AddAssociationOutput ¶
type AddAssociationOutput struct { // The Amazon Resource Name (ARN) of the destination. DestinationArn *string // The ARN of the source. SourceArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type AddTagsInput ¶
type AddTagsInput struct { // The Amazon Resource Name (ARN) of the resource that you want to tag. // // This member is required. ResourceArn *string // An array of key-value pairs. You can use tags to categorize your AWS resources // in different ways, for example, by purpose, owner, or environment. For more // information, see Tagging AWS Resources // (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html). // // This member is required. Tags []types.Tag }
type AddTagsOutput ¶
type AddTagsOutput struct { // A list of tags associated with the Amazon SageMaker resource. Tags []types.Tag // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type AssociateTrialComponentOutput ¶
type AssociateTrialComponentOutput struct { // The Amazon Resource Name (ARN) of the trial. TrialArn *string // The ARN of the trial component. TrialComponentArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type Client ¶
type Client struct {
// contains filtered or unexported fields
}
Client provides the API client to make operations call for Amazon SageMaker Service.
func New ¶
New returns an initialized Client based on the functional options. Provide additional functional options to further configure the behavior of the client, such as changing the client's endpoint or adding custom middleware behavior.
func NewFromConfig ¶
NewFromConfig returns a new client from the provided config.
func (*Client) AddAssociation ¶
func (c *Client) AddAssociation(ctx context.Context, params *AddAssociationInput, optFns ...func(*Options)) (*AddAssociationOutput, error)
Creates an association between the source and the destination. A source can be associated with multiple destinations, and a destination can be associated with multiple sources. An association is a lineage tracking entity. For more information, see Amazon SageMaker ML Lineage Tracking (https://docs.aws.amazon.com/sagemaker/latest/dg/lineage-tracking.html).
func (*Client) AddTags ¶
func (c *Client) AddTags(ctx context.Context, params *AddTagsInput, optFns ...func(*Options)) (*AddTagsOutput, error)
Adds or overwrites one or more tags for the specified Amazon SageMaker resource. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. Each tag consists of a key and an optional value. Tag keys must be unique per resource. For more information about tags, see For more information, see AWS Tagging Strategies (https://aws.amazon.com/answers/account-management/aws-tagging-strategies/). Tags that you add to a hyperparameter tuning job by calling this API are also added to any training jobs that the hyperparameter tuning job launches after you call this API, but not to training jobs that the hyperparameter tuning job launched before you called this API. To make sure that the tags associated with a hyperparameter tuning job are also added to all training jobs that the hyperparameter tuning job launches, add the tags when you first create the tuning job by specifying them in the Tags parameter of CreateHyperParameterTuningJob
func (*Client) AssociateTrialComponent ¶
func (c *Client) AssociateTrialComponent(ctx context.Context, params *AssociateTrialComponentInput, optFns ...func(*Options)) (*AssociateTrialComponentOutput, error)
Associates a trial component with a trial. A trial component can be associated with multiple trials. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
func (*Client) CreateAction ¶
func (c *Client) CreateAction(ctx context.Context, params *CreateActionInput, optFns ...func(*Options)) (*CreateActionOutput, error)
Creates an action. An action is a lineage tracking entity that represents an action or activity. For example, a model deployment or an HPO job. Generally, an action involves at least one input or output artifact. For more information, see Amazon SageMaker ML Lineage Tracking (https://docs.aws.amazon.com/sagemaker/latest/dg/lineage-tracking.html).
func (*Client) CreateAlgorithm ¶
func (c *Client) CreateAlgorithm(ctx context.Context, params *CreateAlgorithmInput, optFns ...func(*Options)) (*CreateAlgorithmOutput, error)
Create a machine learning algorithm that you can use in Amazon SageMaker and list in the AWS Marketplace.
func (*Client) CreateApp ¶
func (c *Client) CreateApp(ctx context.Context, params *CreateAppInput, optFns ...func(*Options)) (*CreateAppOutput, error)
Creates a running App for the specified UserProfile. Supported Apps are JupyterServer and KernelGateway. This operation is automatically invoked by Amazon SageMaker Studio upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.
func (*Client) CreateAppImageConfig ¶
func (c *Client) CreateAppImageConfig(ctx context.Context, params *CreateAppImageConfigInput, optFns ...func(*Options)) (*CreateAppImageConfigOutput, error)
Creates a configuration for running a SageMaker image as a KernelGateway app. The configuration specifies the Amazon Elastic File System (EFS) storage volume on the image, and a list of the kernels in the image.
func (*Client) CreateArtifact ¶
func (c *Client) CreateArtifact(ctx context.Context, params *CreateArtifactInput, optFns ...func(*Options)) (*CreateArtifactOutput, error)
Creates an artifact. An artifact is a lineage tracking entity that represents a URI addressable object or data. Some examples are the S3 URI of a dataset and the ECR registry path of an image. For more information, see Amazon SageMaker ML Lineage Tracking (https://docs.aws.amazon.com/sagemaker/latest/dg/lineage-tracking.html).
func (*Client) CreateAutoMLJob ¶
func (c *Client) CreateAutoMLJob(ctx context.Context, params *CreateAutoMLJobInput, optFns ...func(*Options)) (*CreateAutoMLJobOutput, error)
Creates an Autopilot job. Find the best performing model after you run an Autopilot job by calling . Deploy that model by following the steps described in Step 6.1: Deploy the Model to Amazon SageMaker Hosting Services (https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html). For information about how to use Autopilot, see Automate Model Development with Amazon SageMaker Autopilot (https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html).
func (*Client) CreateCodeRepository ¶
func (c *Client) CreateCodeRepository(ctx context.Context, params *CreateCodeRepositoryInput, optFns ...func(*Options)) (*CreateCodeRepositoryOutput, error)
Creates a Git repository as a resource in your Amazon SageMaker account. You can associate the repository with notebook instances so that you can use Git source control for the notebooks you create. The Git repository is a resource in your Amazon SageMaker account, so it can be associated with more than one notebook instance, and it persists independently from the lifecycle of any notebook instances it is associated with. The repository can be hosted either in AWS CodeCommit (https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html) or in any other Git repository.
func (*Client) CreateCompilationJob ¶
func (c *Client) CreateCompilationJob(ctx context.Context, params *CreateCompilationJobInput, optFns ...func(*Options)) (*CreateCompilationJobOutput, error)
Starts a model compilation job. After the model has been compiled, Amazon SageMaker saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify. If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with AWS IoT Greengrass. In that case, deploy them as an ML resource. In the request body, you provide the following:
* A name for the compilation job
* Information about the input model artifacts
* The output location for the compiled model and the device (target) that the model runs on
* The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker assumes to perform the model compilation job.
You can also provide a Tag to track the model compilation job's resource use and costs. The response body contains the CompilationJobArn for the compiled job. To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
func (*Client) CreateContext ¶
func (c *Client) CreateContext(ctx context.Context, params *CreateContextInput, optFns ...func(*Options)) (*CreateContextOutput, error)
Creates a context. A context is a lineage tracking entity that represents a logical grouping of other tracking or experiment entities. Some examples are an endpoint and a model package. For more information, see Amazon SageMaker ML Lineage Tracking (https://docs.aws.amazon.com/sagemaker/latest/dg/lineage-tracking.html).
func (*Client) CreateDataQualityJobDefinition ¶
func (c *Client) CreateDataQualityJobDefinition(ctx context.Context, params *CreateDataQualityJobDefinitionInput, optFns ...func(*Options)) (*CreateDataQualityJobDefinitionOutput, error)
Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor (https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor.html).
func (*Client) CreateDeviceFleet ¶
func (c *Client) CreateDeviceFleet(ctx context.Context, params *CreateDeviceFleetInput, optFns ...func(*Options)) (*CreateDeviceFleetOutput, error)
Creates a device fleet.
func (*Client) CreateDomain ¶
func (c *Client) CreateDomain(ctx context.Context, params *CreateDomainInput, optFns ...func(*Options)) (*CreateDomainOutput, error)
Creates a Domain used by Amazon SageMaker Studio. A domain consists of an associated Amazon Elastic File System (EFS) volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. An AWS account is limited to one domain per region. Users within a domain can share notebook files and other artifacts with each other. EFS storage When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files. SageMaker uses the AWS Key Management Service (AWS KMS) to encrypt the EFS volume attached to the domain with an AWS managed customer master key (CMK) by default. For more control, you can specify a customer managed CMK. For more information, see Protect Data at Rest Using Encryption (https://docs.aws.amazon.com/sagemaker/latest/dg/encryption-at-rest.html). VPC configuration All SageMaker Studio traffic between the domain and the EFS volume is through the specified VPC and subnets. For other Studio traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to Studio. The following options are available:
* PublicInternetOnly - Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.
* VpcOnly - All Studio traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway. When internet access is disabled, you won't be able to run a Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.
For more information, see Connect SageMaker Studio Notebooks to Resources in a VPC (https://docs.aws.amazon.com/sagemaker/latest/dg/studio-notebooks-and-internet-access.html).
func (*Client) CreateEdgePackagingJob ¶
func (c *Client) CreateEdgePackagingJob(ctx context.Context, params *CreateEdgePackagingJobInput, optFns ...func(*Options)) (*CreateEdgePackagingJobOutput, error)
Starts a SageMaker Edge Manager model packaging job. Edge Manager will use the model artifacts from the Amazon Simple Storage Service bucket that you specify. After the model has been packaged, Amazon SageMaker saves the resulting artifacts to an S3 bucket that you specify.
func (*Client) CreateEndpoint ¶
func (c *Client) CreateEndpoint(ctx context.Context, params *CreateEndpointInput, optFns ...func(*Options)) (*CreateEndpointOutput, error)
Creates an endpoint using the endpoint configuration specified in the request. Amazon SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API. Use this API to deploy models using Amazon SageMaker hosting services. For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)). (https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto) You must not delete an EndpointConfig that is in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig. The endpoint name must be unique within an AWS Region in your AWS account. When it receives the request, Amazon SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them. When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads (https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadConsistency.html), the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read. When Amazon SageMaker receives the request, it sets the endpoint status to Creating. After it creates the endpoint, it sets the status to InService. Amazon SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API. If any of the models hosted at this endpoint get model data from an Amazon S3 location, Amazon SageMaker uses AWS Security Token Service to download model artifacts from the S3 path you provided. AWS STS is activated in your IAM user account by default. If you previously deactivated AWS STS for a region, you need to reactivate AWS STS for that region. For more information, see Activating and Deactivating AWS STS in an AWS Region (https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html) in the AWS Identity and Access Management User Guide. To add the IAM role policies for using this API operation, go to the IAM console (https://console.aws.amazon.com/iam/), and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the role.
* Option 1: For a full Amazon SageMaker access, search and attach the AmazonSageMakerFullAccess policy.
* Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role: "Action": ["sagemaker:CreateEndpoint", "sagemaker:CreateEndpointConfig"]"Resource": ["arn:aws:sagemaker:region:account-id:endpoint/endpointName""arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"] For more information, see Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference (https://docs.aws.amazon.com/sagemaker/latest/dg/api-permissions-reference.html).
func (*Client) CreateEndpointConfig ¶
func (c *Client) CreateEndpointConfig(ctx context.Context, params *CreateEndpointConfigInput, optFns ...func(*Options)) (*CreateEndpointConfigOutput, error)
Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want Amazon SageMaker to provision. Then you call the CreateEndpoint API. Use this API if you want to use Amazon SageMaker hosting services to deploy models into production. In the request, you define a ProductionVariant, for each model that you want to deploy. Each ProductionVariant parameter also describes the resources that you want Amazon SageMaker to provision. This includes the number and type of ML compute instances to deploy. If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. Amazon SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B. For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)). (https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto) When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads (https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadConsistency.html), the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
func (*Client) CreateExperiment ¶
func (c *Client) CreateExperiment(ctx context.Context, params *CreateExperimentInput, optFns ...func(*Options)) (*CreateExperimentOutput, error)
Creates an SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model. The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant. When you use Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK. You can add tags to experiments, trials, trial components and then use the Search API to search for the tags. To add a description to an experiment, specify the optional Description parameter. To add a description later, or to change the description, call the UpdateExperiment API. To get a list of all your experiments, call the ListExperiments API. To view an experiment's properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
func (*Client) CreateFeatureGroup ¶
func (c *Client) CreateFeatureGroup(ctx context.Context, params *CreateFeatureGroupInput, optFns ...func(*Options)) (*CreateFeatureGroupOutput, error)
Create a new FeatureGroup. A FeatureGroup is a group of Features defined in the FeatureStore to describe a Record. The FeatureGroup defines the schema and features contained in the FeatureGroup. A FeatureGroup definition is composed of a list of Features, a RecordIdentifierFeatureName, an EventTimeFeatureName and configurations for its OnlineStore and OfflineStore. Check AWS service quotas (https://docs.aws.amazon.com/general/latest/gr/aws_service_limits.html) to see the FeatureGroups quota for your AWS account. You must include at least one of OnlineStoreConfig and OfflineStoreConfig to create a FeatureGroup.
func (*Client) CreateFlowDefinition ¶
func (c *Client) CreateFlowDefinition(ctx context.Context, params *CreateFlowDefinitionInput, optFns ...func(*Options)) (*CreateFlowDefinitionOutput, error)
Creates a flow definition.
func (*Client) CreateHumanTaskUi ¶
func (c *Client) CreateHumanTaskUi(ctx context.Context, params *CreateHumanTaskUiInput, optFns ...func(*Options)) (*CreateHumanTaskUiOutput, error)
Defines the settings you will use for the human review workflow user interface. Reviewers will see a three-panel interface with an instruction area, the item to review, and an input area.
func (*Client) CreateHyperParameterTuningJob ¶
func (c *Client) CreateHyperParameterTuningJob(ctx context.Context, params *CreateHyperParameterTuningJobInput, optFns ...func(*Options)) (*CreateHyperParameterTuningJobOutput, error)
Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by an objective metric that you choose.
func (*Client) CreateImage ¶
func (c *Client) CreateImage(ctx context.Context, params *CreateImageInput, optFns ...func(*Options)) (*CreateImageOutput, error)
Creates a custom SageMaker image. A SageMaker image is a set of image versions. Each image version represents a container image stored in Amazon Container Registry (ECR). For more information, see Bring your own SageMaker image (https://docs.aws.amazon.com/sagemaker/latest/dg/studio-byoi.html).
func (*Client) CreateImageVersion ¶
func (c *Client) CreateImageVersion(ctx context.Context, params *CreateImageVersionInput, optFns ...func(*Options)) (*CreateImageVersionOutput, error)
Creates a version of the SageMaker image specified by ImageName. The version represents the Amazon Container Registry (ECR) container image specified by BaseImage.
func (*Client) CreateLabelingJob ¶
func (c *Client) CreateLabelingJob(ctx context.Context, params *CreateLabelingJobInput, optFns ...func(*Options)) (*CreateLabelingJobOutput, error)
Creates a job that uses workers to label the data objects in your input dataset. You can use the labeled data to train machine learning models. You can select your workforce from one of three providers:
* A private workforce that you create. It can include employees, contractors, and outside experts. Use a private workforce when want the data to stay within your organization or when a specific set of skills is required.
* One or more vendors that you select from the AWS Marketplace. Vendors provide expertise in specific areas.
* The Amazon Mechanical Turk workforce. This is the largest workforce, but it should only be used for public data or data that has been stripped of any personally identifiable information.
You can also use automated data labeling to reduce the number of data objects that need to be labeled by a human. Automated data labeling uses active learning to determine if a data object can be labeled by machine or if it needs to be sent to a human worker. For more information, see Using Automated Data Labeling (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-automated-labeling.html). The data objects to be labeled are contained in an Amazon S3 bucket. You create a manifest file that describes the location of each object. For more information, see Using Input and Output Data (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-data.html). The output can be used as the manifest file for another labeling job or as training data for your machine learning models.
func (*Client) CreateModel ¶
func (c *Client) CreateModel(ctx context.Context, params *CreateModelInput, optFns ...func(*Options)) (*CreateModelOutput, error)
Creates a model in Amazon SageMaker. In the request, you name the model and describe a primary container. For the primary container, you specify the Docker image that contains inference code, artifacts (from prior training), and a custom environment map that the inference code uses when you deploy the model for predictions. Use this API to create a model if you want to use Amazon SageMaker hosting services or run a batch transform job. To host your model, you create an endpoint configuration with the CreateEndpointConfig API, and then create an endpoint with the CreateEndpoint API. Amazon SageMaker then deploys all of the containers that you defined for the model in the hosting environment. For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)). (https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto) To run a batch transform using your model, you start a job with the CreateTransformJob API. Amazon SageMaker uses your model and your dataset to get inferences which are then saved to a specified S3 location. In the CreateModel request, you must define a container with the PrimaryContainer parameter. In the request, you also provide an IAM role that Amazon SageMaker can assume to access model artifacts and docker image for deployment on ML compute hosting instances or for batch transform jobs. In addition, you also use the IAM role to manage permissions the inference code needs. For example, if the inference code access any other AWS resources, you grant necessary permissions via this role.
func (*Client) CreateModelBiasJobDefinition ¶
func (c *Client) CreateModelBiasJobDefinition(ctx context.Context, params *CreateModelBiasJobDefinitionInput, optFns ...func(*Options)) (*CreateModelBiasJobDefinitionOutput, error)
Creates the definition for a model bias job.
func (*Client) CreateModelExplainabilityJobDefinition ¶
func (c *Client) CreateModelExplainabilityJobDefinition(ctx context.Context, params *CreateModelExplainabilityJobDefinitionInput, optFns ...func(*Options)) (*CreateModelExplainabilityJobDefinitionOutput, error)
Creates the definition for a model explainability job.
func (*Client) CreateModelPackage ¶
func (c *Client) CreateModelPackage(ctx context.Context, params *CreateModelPackageInput, optFns ...func(*Options)) (*CreateModelPackageOutput, error)
Creates a model package that you can use to create Amazon SageMaker models or list on AWS Marketplace, or a versioned model that is part of a model group. Buyers can subscribe to model packages listed on AWS Marketplace to create models in Amazon SageMaker. To create a model package by specifying a Docker container that contains your inference code and the Amazon S3 location of your model artifacts, provide values for InferenceSpecification. To create a model from an algorithm resource that you created or subscribed to in AWS Marketplace, provide a value for SourceAlgorithmSpecification. There are two types of model packages:
* Versioned - a model that is part of a model group in the model registry.
* Unversioned - a model package that is not part of a model group.
func (*Client) CreateModelPackageGroup ¶
func (c *Client) CreateModelPackageGroup(ctx context.Context, params *CreateModelPackageGroupInput, optFns ...func(*Options)) (*CreateModelPackageGroupOutput, error)
Creates a model group. A model group contains a group of model versions.
func (*Client) CreateModelQualityJobDefinition ¶
func (c *Client) CreateModelQualityJobDefinition(ctx context.Context, params *CreateModelQualityJobDefinitionInput, optFns ...func(*Options)) (*CreateModelQualityJobDefinitionOutput, error)
Creates a definition for a job that monitors model quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor (https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor.html).
func (*Client) CreateMonitoringSchedule ¶
func (c *Client) CreateMonitoringSchedule(ctx context.Context, params *CreateMonitoringScheduleInput, optFns ...func(*Options)) (*CreateMonitoringScheduleOutput, error)
Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endoint.
func (*Client) CreateNotebookInstance ¶
func (c *Client) CreateNotebookInstance(ctx context.Context, params *CreateNotebookInstanceInput, optFns ...func(*Options)) (*CreateNotebookInstanceOutput, error)
Creates an Amazon SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook. In a CreateNotebookInstance request, specify the type of ML compute instance that you want to run. Amazon SageMaker launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance. Amazon SageMaker also provides a set of example notebooks. Each notebook demonstrates how to use Amazon SageMaker with a specific algorithm or with a machine learning framework. After receiving the request, Amazon SageMaker does the following:
* Creates a network interface in the Amazon SageMaker VPC.
* (Option) If you specified SubnetId, Amazon SageMaker creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, Amazon SageMaker attaches the security group that you specified in the request to the network interface that it creates in your VPC.
* Launches an EC2 instance of the type specified in the request in the Amazon SageMaker VPC. If you specified SubnetId of your VPC, Amazon SageMaker specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.
After creating the notebook instance, Amazon SageMaker returns its Amazon Resource Name (ARN). You can't change the name of a notebook instance after you create it. After Amazon SageMaker creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating Amazon SageMaker endpoints, and validate hosted models. For more information, see How It Works (https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works.html).
func (*Client) CreateNotebookInstanceLifecycleConfig ¶
func (c *Client) CreateNotebookInstanceLifecycleConfig(ctx context.Context, params *CreateNotebookInstanceLifecycleConfigInput, optFns ...func(*Options)) (*CreateNotebookInstanceLifecycleConfigOutput, error)
Creates a lifecycle configuration that you can associate with a notebook instance. A lifecycle configuration is a collection of shell scripts that run when you create or start a notebook instance. Each lifecycle configuration script has a limit of 16384 characters. The value of the $PATH environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin. View CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances in log stream [notebook-instance-name]/[LifecycleConfigHook]. Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started. For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance (https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html).
func (*Client) CreatePipeline ¶
func (c *Client) CreatePipeline(ctx context.Context, params *CreatePipelineInput, optFns ...func(*Options)) (*CreatePipelineOutput, error)
Creates a pipeline using a JSON pipeline definition.
func (*Client) CreatePresignedDomainUrl ¶
func (c *Client) CreatePresignedDomainUrl(ctx context.Context, params *CreatePresignedDomainUrlInput, optFns ...func(*Options)) (*CreatePresignedDomainUrlOutput, error)
Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to Amazon SageMaker Studio, and granted access to all of the Apps and files associated with the Domain's Amazon Elastic File System (EFS) volume. This operation can only be called when the authentication mode equals IAM. The URL that you get from a call to CreatePresignedDomainUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the AWS console sign-in page.
func (*Client) CreatePresignedNotebookInstanceUrl ¶
func (c *Client) CreatePresignedNotebookInstanceUrl(ctx context.Context, params *CreatePresignedNotebookInstanceUrlInput, optFns ...func(*Options)) (*CreatePresignedNotebookInstanceUrlOutput, error)
Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the Amazon SageMaker console, when you choose Open next to a notebook instance, Amazon SageMaker opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page. The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance. You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress condition operator and the aws:SourceIP condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address (https://docs.aws.amazon.com/sagemaker/latest/dg/security_iam_id-based-policy-examples.html#nbi-ip-filter). The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the AWS console sign-in page.
func (*Client) CreateProcessingJob ¶
func (c *Client) CreateProcessingJob(ctx context.Context, params *CreateProcessingJobInput, optFns ...func(*Options)) (*CreateProcessingJobOutput, error)
Creates a processing job.
func (*Client) CreateProject ¶
func (c *Client) CreateProject(ctx context.Context, params *CreateProjectInput, optFns ...func(*Options)) (*CreateProjectOutput, error)
Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.
func (*Client) CreateTrainingJob ¶
func (c *Client) CreateTrainingJob(ctx context.Context, params *CreateTrainingJobInput, optFns ...func(*Options)) (*CreateTrainingJobOutput, error)
Starts a model training job. After training completes, Amazon SageMaker saves the resulting model artifacts to an Amazon S3 location that you specify. If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts in a machine learning service other than Amazon SageMaker, provided that you know how to use them for inference. In the request body, you provide the following:
* AlgorithmSpecification - Identifies the training algorithm to use.
* HyperParameters - Specify these algorithm-specific parameters to enable the estimation of model parameters during training. Hyperparameters can be tuned to optimize this learning process. For a list of hyperparameters for each training algorithm provided by Amazon SageMaker, see Algorithms (https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html).
* InputDataConfig - Describes the training dataset and the Amazon S3, EFS, or FSx location where it is stored.
* OutputDataConfig - Identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of model training.
* ResourceConfig - Identifies the resources, ML compute instances, and ML storage volumes to deploy for model training. In distributed training, you specify more than one instance.
* EnableManagedSpotTraining - Optimize the cost of training machine learning models by up to 80% by using Amazon EC2 Spot instances. For more information, see Managed Spot Training (https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.html).
* RoleArn - The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during model training. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete model training.
* StoppingCondition - To help cap training costs, use MaxRuntimeInSeconds to set a time limit for training. Use MaxWaitTimeInSeconds to specify how long you are willing to wait for a managed spot training job to complete.
For more information about Amazon SageMaker, see How It Works (https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works.html).
func (*Client) CreateTransformJob ¶
func (c *Client) CreateTransformJob(ctx context.Context, params *CreateTransformJobInput, optFns ...func(*Options)) (*CreateTransformJobOutput, error)
Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify. To perform batch transformations, you create a transform job and use the data that you have readily available. In the request body, you provide the following:
* TransformJobName - Identifies the transform job. The name must be unique within an AWS Region in an AWS account.
* ModelName - Identifies the model to use. ModelName must be the name of an existing Amazon SageMaker model in the same AWS Region and AWS account. For information on creating a model, see CreateModel.
* TransformInput - Describes the dataset to be transformed and the Amazon S3 location where it is stored.
* TransformOutput - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
* TransformResources - Identifies the ML compute instances for the transform job.
For more information about how batch transformation works, see Batch Transform (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html).
func (*Client) CreateTrial ¶
func (c *Client) CreateTrial(ctx context.Context, params *CreateTrialInput, optFns ...func(*Options)) (*CreateTrialOutput, error)
Creates an Amazon SageMaker trial. A trial is a set of steps called trial components that produce a machine learning model. A trial is part of a single Amazon SageMaker experiment. When you use Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK. You can add tags to a trial and then use the Search API to search for the tags. To get a list of all your trials, call the ListTrials API. To view a trial's properties, call the DescribeTrial API. To create a trial component, call the CreateTrialComponent API.
func (*Client) CreateTrialComponent ¶
func (c *Client) CreateTrialComponent(ctx context.Context, params *CreateTrialComponentInput, optFns ...func(*Options)) (*CreateTrialComponentOutput, error)
Creates a trial component, which is a stage of a machine learning trial. A trial is composed of one or more trial components. A trial component can be used in multiple trials. Trial components include pre-processing jobs, training jobs, and batch transform jobs. When you use Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK. You can add tags to a trial component and then use the Search API to search for the tags. CreateTrialComponent can only be invoked from within an Amazon SageMaker managed environment. This includes Amazon SageMaker training jobs, processing jobs, transform jobs, and Amazon SageMaker notebooks. A call to CreateTrialComponent from outside one of these environments results in an error.
func (*Client) CreateUserProfile ¶
func (c *Client) CreateUserProfile(ctx context.Context, params *CreateUserProfileInput, optFns ...func(*Options)) (*CreateUserProfileOutput, error)
Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a "person" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to Amazon SageMaker Studio. If an administrator invites a person by email or imports them from SSO, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user's private Amazon Elastic File System (EFS) home directory.
func (*Client) CreateWorkforce ¶
func (c *Client) CreateWorkforce(ctx context.Context, params *CreateWorkforceInput, optFns ...func(*Options)) (*CreateWorkforceOutput, error)
Use this operation to create a workforce. This operation will return an error if a workforce already exists in the AWS Region that you specify. You can only create one workforce in each AWS Region per AWS account. If you want to create a new workforce in an AWS Region where a workforce already exists, use the API operation to delete the existing workforce and then use CreateWorkforce to create a new workforce. To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito) (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private.html). To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig. Your OIDC IdP must support groups because groups are used by Ground Truth and Amazon A2I to create work teams. For more information, see Create a Private Workforce (OIDC IdP) (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private-oidc.html).
func (*Client) CreateWorkteam ¶
func (c *Client) CreateWorkteam(ctx context.Context, params *CreateWorkteamInput, optFns ...func(*Options)) (*CreateWorkteamOutput, error)
Creates a new work team for labeling your data. A work team is defined by one or more Amazon Cognito user pools. You must first create the user pools before you can create a work team. You cannot create more than 25 work teams in an account and region.
func (*Client) DeleteAction ¶
func (c *Client) DeleteAction(ctx context.Context, params *DeleteActionInput, optFns ...func(*Options)) (*DeleteActionOutput, error)
Deletes an action.
func (*Client) DeleteAlgorithm ¶
func (c *Client) DeleteAlgorithm(ctx context.Context, params *DeleteAlgorithmInput, optFns ...func(*Options)) (*DeleteAlgorithmOutput, error)
Removes the specified algorithm from your account.
func (*Client) DeleteApp ¶
func (c *Client) DeleteApp(ctx context.Context, params *DeleteAppInput, optFns ...func(*Options)) (*DeleteAppOutput, error)
Used to stop and delete an app.
func (*Client) DeleteAppImageConfig ¶
func (c *Client) DeleteAppImageConfig(ctx context.Context, params *DeleteAppImageConfigInput, optFns ...func(*Options)) (*DeleteAppImageConfigOutput, error)
Deletes an AppImageConfig.
func (*Client) DeleteArtifact ¶
func (c *Client) DeleteArtifact(ctx context.Context, params *DeleteArtifactInput, optFns ...func(*Options)) (*DeleteArtifactOutput, error)
Deletes an artifact. Either ArtifactArn or Source must be specified.
func (*Client) DeleteAssociation ¶
func (c *Client) DeleteAssociation(ctx context.Context, params *DeleteAssociationInput, optFns ...func(*Options)) (*DeleteAssociationOutput, error)
Deletes an association.
func (*Client) DeleteCodeRepository ¶
func (c *Client) DeleteCodeRepository(ctx context.Context, params *DeleteCodeRepositoryInput, optFns ...func(*Options)) (*DeleteCodeRepositoryOutput, error)
Deletes the specified Git repository from your account.
func (*Client) DeleteContext ¶
func (c *Client) DeleteContext(ctx context.Context, params *DeleteContextInput, optFns ...func(*Options)) (*DeleteContextOutput, error)
Deletes an context.
func (*Client) DeleteDataQualityJobDefinition ¶
func (c *Client) DeleteDataQualityJobDefinition(ctx context.Context, params *DeleteDataQualityJobDefinitionInput, optFns ...func(*Options)) (*DeleteDataQualityJobDefinitionOutput, error)
Deletes a data quality monitoring job definition.
func (*Client) DeleteDeviceFleet ¶
func (c *Client) DeleteDeviceFleet(ctx context.Context, params *DeleteDeviceFleetInput, optFns ...func(*Options)) (*DeleteDeviceFleetOutput, error)
Deletes a fleet.
func (*Client) DeleteDomain ¶
func (c *Client) DeleteDomain(ctx context.Context, params *DeleteDomainInput, optFns ...func(*Options)) (*DeleteDomainOutput, error)
Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using SSO. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.
func (*Client) DeleteEndpoint ¶
func (c *Client) DeleteEndpoint(ctx context.Context, params *DeleteEndpointInput, optFns ...func(*Options)) (*DeleteEndpointOutput, error)
Deletes an endpoint. Amazon SageMaker frees up all of the resources that were deployed when the endpoint was created. Amazon SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don't need to use the RevokeGrant (http://docs.aws.amazon.com/kms/latest/APIReference/API_RevokeGrant.html) API call.
func (*Client) DeleteEndpointConfig ¶
func (c *Client) DeleteEndpointConfig(ctx context.Context, params *DeleteEndpointConfigInput, optFns ...func(*Options)) (*DeleteEndpointConfigOutput, error)
Deletes an endpoint configuration. The DeleteEndpointConfig API deletes only the specified configuration. It does not delete endpoints created using the configuration. You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
func (*Client) DeleteExperiment ¶
func (c *Client) DeleteExperiment(ctx context.Context, params *DeleteExperimentInput, optFns ...func(*Options)) (*DeleteExperimentOutput, error)
Deletes an Amazon SageMaker experiment. All trials associated with the experiment must be deleted first. Use the ListTrials API to get a list of the trials associated with the experiment.
func (*Client) DeleteFeatureGroup ¶
func (c *Client) DeleteFeatureGroup(ctx context.Context, params *DeleteFeatureGroupInput, optFns ...func(*Options)) (*DeleteFeatureGroupOutput, error)
Delete the FeatureGroup and any data that was written to the OnlineStore of the FeatureGroup. Data cannot be accessed from the OnlineStore immediately after DeleteFeatureGroup is called. Data written into the OfflineStore will not be deleted. The AWS Glue database and tables that are automatically created for your OfflineStore are not deleted.
func (*Client) DeleteFlowDefinition ¶
func (c *Client) DeleteFlowDefinition(ctx context.Context, params *DeleteFlowDefinitionInput, optFns ...func(*Options)) (*DeleteFlowDefinitionOutput, error)
Deletes the specified flow definition.
func (*Client) DeleteHumanTaskUi ¶
func (c *Client) DeleteHumanTaskUi(ctx context.Context, params *DeleteHumanTaskUiInput, optFns ...func(*Options)) (*DeleteHumanTaskUiOutput, error)
Use this operation to delete a human task user interface (worker task template). To see a list of human task user interfaces (work task templates) in your account, use . When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.
func (*Client) DeleteImage ¶
func (c *Client) DeleteImage(ctx context.Context, params *DeleteImageInput, optFns ...func(*Options)) (*DeleteImageOutput, error)
Deletes a SageMaker image and all versions of the image. The container images aren't deleted.
func (*Client) DeleteImageVersion ¶
func (c *Client) DeleteImageVersion(ctx context.Context, params *DeleteImageVersionInput, optFns ...func(*Options)) (*DeleteImageVersionOutput, error)
Deletes a version of a SageMaker image. The container image the version represents isn't deleted.
func (*Client) DeleteModel ¶
func (c *Client) DeleteModel(ctx context.Context, params *DeleteModelInput, optFns ...func(*Options)) (*DeleteModelOutput, error)
Deletes a model. The DeleteModel API deletes only the model entry that was created in Amazon SageMaker when you called the CreateModel API. It does not delete model artifacts, inference code, or the IAM role that you specified when creating the model.
func (*Client) DeleteModelBiasJobDefinition ¶
func (c *Client) DeleteModelBiasJobDefinition(ctx context.Context, params *DeleteModelBiasJobDefinitionInput, optFns ...func(*Options)) (*DeleteModelBiasJobDefinitionOutput, error)
Deletes an Amazon SageMaker model bias job definition.
func (*Client) DeleteModelExplainabilityJobDefinition ¶
func (c *Client) DeleteModelExplainabilityJobDefinition(ctx context.Context, params *DeleteModelExplainabilityJobDefinitionInput, optFns ...func(*Options)) (*DeleteModelExplainabilityJobDefinitionOutput, error)
Deletes an Amazon SageMaker model explainability job definition.
func (*Client) DeleteModelPackage ¶
func (c *Client) DeleteModelPackage(ctx context.Context, params *DeleteModelPackageInput, optFns ...func(*Options)) (*DeleteModelPackageOutput, error)
Deletes a model package. A model package is used to create Amazon SageMaker models or list on AWS Marketplace. Buyers can subscribe to model packages listed on AWS Marketplace to create models in Amazon SageMaker.
func (*Client) DeleteModelPackageGroup ¶
func (c *Client) DeleteModelPackageGroup(ctx context.Context, params *DeleteModelPackageGroupInput, optFns ...func(*Options)) (*DeleteModelPackageGroupOutput, error)
Deletes the specified model group.
func (*Client) DeleteModelPackageGroupPolicy ¶
func (c *Client) DeleteModelPackageGroupPolicy(ctx context.Context, params *DeleteModelPackageGroupPolicyInput, optFns ...func(*Options)) (*DeleteModelPackageGroupPolicyOutput, error)
Deletes a model group resource policy.
func (*Client) DeleteModelQualityJobDefinition ¶
func (c *Client) DeleteModelQualityJobDefinition(ctx context.Context, params *DeleteModelQualityJobDefinitionInput, optFns ...func(*Options)) (*DeleteModelQualityJobDefinitionOutput, error)
Deletes the secified model quality monitoring job definition.
func (*Client) DeleteMonitoringSchedule ¶
func (c *Client) DeleteMonitoringSchedule(ctx context.Context, params *DeleteMonitoringScheduleInput, optFns ...func(*Options)) (*DeleteMonitoringScheduleOutput, error)
Deletes a monitoring schedule. Also stops the schedule had not already been stopped. This does not delete the job execution history of the monitoring schedule.
func (*Client) DeleteNotebookInstance ¶
func (c *Client) DeleteNotebookInstance(ctx context.Context, params *DeleteNotebookInstanceInput, optFns ...func(*Options)) (*DeleteNotebookInstanceOutput, error)
Deletes an Amazon SageMaker notebook instance. Before you can delete a notebook instance, you must call the StopNotebookInstance API. When you delete a notebook instance, you lose all of your data. Amazon SageMaker removes the ML compute instance, and deletes the ML storage volume and the network interface associated with the notebook instance.
func (*Client) DeleteNotebookInstanceLifecycleConfig ¶
func (c *Client) DeleteNotebookInstanceLifecycleConfig(ctx context.Context, params *DeleteNotebookInstanceLifecycleConfigInput, optFns ...func(*Options)) (*DeleteNotebookInstanceLifecycleConfigOutput, error)
Deletes a notebook instance lifecycle configuration.
func (*Client) DeletePipeline ¶
func (c *Client) DeletePipeline(ctx context.Context, params *DeletePipelineInput, optFns ...func(*Options)) (*DeletePipelineOutput, error)
Deletes a pipeline if there are no in-progress executions.
func (*Client) DeleteProject ¶
func (c *Client) DeleteProject(ctx context.Context, params *DeleteProjectInput, optFns ...func(*Options)) (*DeleteProjectOutput, error)
Delete the specified project.
func (*Client) DeleteTags ¶
func (c *Client) DeleteTags(ctx context.Context, params *DeleteTagsInput, optFns ...func(*Options)) (*DeleteTagsOutput, error)
Deletes the specified tags from an Amazon SageMaker resource. To list a resource's tags, use the ListTags API. When you call this API to delete tags from a hyperparameter tuning job, the deleted tags are not removed from training jobs that the hyperparameter tuning job launched before you called this API.
func (*Client) DeleteTrial ¶
func (c *Client) DeleteTrial(ctx context.Context, params *DeleteTrialInput, optFns ...func(*Options)) (*DeleteTrialOutput, error)
Deletes the specified trial. All trial components that make up the trial must be deleted first. Use the DescribeTrialComponent API to get the list of trial components.
func (*Client) DeleteTrialComponent ¶
func (c *Client) DeleteTrialComponent(ctx context.Context, params *DeleteTrialComponentInput, optFns ...func(*Options)) (*DeleteTrialComponentOutput, error)
Deletes the specified trial component. A trial component must be disassociated from all trials before the trial component can be deleted. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
func (*Client) DeleteUserProfile ¶
func (c *Client) DeleteUserProfile(ctx context.Context, params *DeleteUserProfileInput, optFns ...func(*Options)) (*DeleteUserProfileOutput, error)
Deletes a user profile. When a user profile is deleted, the user loses access to their EFS volume, including data, notebooks, and other artifacts.
func (*Client) DeleteWorkforce ¶
func (c *Client) DeleteWorkforce(ctx context.Context, params *DeleteWorkforceInput, optFns ...func(*Options)) (*DeleteWorkforceOutput, error)
Use this operation to delete a workforce. If you want to create a new workforce in an AWS Region where a workforce already exists, use this operation to delete the existing workforce and then use to create a new workforce. If a private workforce contains one or more work teams, you must use the operation to delete all work teams before you delete the workforce. If you try to delete a workforce that contains one or more work teams, you will recieve a ResourceInUse error.
func (*Client) DeleteWorkteam ¶
func (c *Client) DeleteWorkteam(ctx context.Context, params *DeleteWorkteamInput, optFns ...func(*Options)) (*DeleteWorkteamOutput, error)
Deletes an existing work team. This operation can't be undone.
func (*Client) DeregisterDevices ¶
func (c *Client) DeregisterDevices(ctx context.Context, params *DeregisterDevicesInput, optFns ...func(*Options)) (*DeregisterDevicesOutput, error)
Deregisters the specified devices. After you deregister a device, you will need to re-register the devices.
func (*Client) DescribeAction ¶
func (c *Client) DescribeAction(ctx context.Context, params *DescribeActionInput, optFns ...func(*Options)) (*DescribeActionOutput, error)
Describes an action.
func (*Client) DescribeAlgorithm ¶
func (c *Client) DescribeAlgorithm(ctx context.Context, params *DescribeAlgorithmInput, optFns ...func(*Options)) (*DescribeAlgorithmOutput, error)
Returns a description of the specified algorithm that is in your account.
func (*Client) DescribeApp ¶
func (c *Client) DescribeApp(ctx context.Context, params *DescribeAppInput, optFns ...func(*Options)) (*DescribeAppOutput, error)
Describes the app.
func (*Client) DescribeAppImageConfig ¶
func (c *Client) DescribeAppImageConfig(ctx context.Context, params *DescribeAppImageConfigInput, optFns ...func(*Options)) (*DescribeAppImageConfigOutput, error)
Describes an AppImageConfig.
func (*Client) DescribeArtifact ¶
func (c *Client) DescribeArtifact(ctx context.Context, params *DescribeArtifactInput, optFns ...func(*Options)) (*DescribeArtifactOutput, error)
Describes an artifact.
func (*Client) DescribeAutoMLJob ¶
func (c *Client) DescribeAutoMLJob(ctx context.Context, params *DescribeAutoMLJobInput, optFns ...func(*Options)) (*DescribeAutoMLJobOutput, error)
Returns information about an Amazon SageMaker job.
func (*Client) DescribeCodeRepository ¶
func (c *Client) DescribeCodeRepository(ctx context.Context, params *DescribeCodeRepositoryInput, optFns ...func(*Options)) (*DescribeCodeRepositoryOutput, error)
Gets details about the specified Git repository.
func (*Client) DescribeCompilationJob ¶
func (c *Client) DescribeCompilationJob(ctx context.Context, params *DescribeCompilationJobInput, optFns ...func(*Options)) (*DescribeCompilationJobOutput, error)
Returns information about a model compilation job. To create a model compilation job, use CreateCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
func (*Client) DescribeContext ¶
func (c *Client) DescribeContext(ctx context.Context, params *DescribeContextInput, optFns ...func(*Options)) (*DescribeContextOutput, error)
Describes a context.
func (*Client) DescribeDataQualityJobDefinition ¶
func (c *Client) DescribeDataQualityJobDefinition(ctx context.Context, params *DescribeDataQualityJobDefinitionInput, optFns ...func(*Options)) (*DescribeDataQualityJobDefinitionOutput, error)
Gets the details of a data quality monitoring job definition.
func (*Client) DescribeDevice ¶
func (c *Client) DescribeDevice(ctx context.Context, params *DescribeDeviceInput, optFns ...func(*Options)) (*DescribeDeviceOutput, error)
Describes the device.
func (*Client) DescribeDeviceFleet ¶
func (c *Client) DescribeDeviceFleet(ctx context.Context, params *DescribeDeviceFleetInput, optFns ...func(*Options)) (*DescribeDeviceFleetOutput, error)
A description of the fleet the device belongs to.
func (*Client) DescribeDomain ¶
func (c *Client) DescribeDomain(ctx context.Context, params *DescribeDomainInput, optFns ...func(*Options)) (*DescribeDomainOutput, error)
The description of the domain.
func (*Client) DescribeEdgePackagingJob ¶
func (c *Client) DescribeEdgePackagingJob(ctx context.Context, params *DescribeEdgePackagingJobInput, optFns ...func(*Options)) (*DescribeEdgePackagingJobOutput, error)
A description of edge packaging jobs.
func (*Client) DescribeEndpoint ¶
func (c *Client) DescribeEndpoint(ctx context.Context, params *DescribeEndpointInput, optFns ...func(*Options)) (*DescribeEndpointOutput, error)
Returns the description of an endpoint.
func (*Client) DescribeEndpointConfig ¶
func (c *Client) DescribeEndpointConfig(ctx context.Context, params *DescribeEndpointConfigInput, optFns ...func(*Options)) (*DescribeEndpointConfigOutput, error)
Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
func (*Client) DescribeExperiment ¶
func (c *Client) DescribeExperiment(ctx context.Context, params *DescribeExperimentInput, optFns ...func(*Options)) (*DescribeExperimentOutput, error)
Provides a list of an experiment's properties.
func (*Client) DescribeFeatureGroup ¶
func (c *Client) DescribeFeatureGroup(ctx context.Context, params *DescribeFeatureGroupInput, optFns ...func(*Options)) (*DescribeFeatureGroupOutput, error)
Use this operation to describe a FeatureGroup. The response includes information on the creation time, FeatureGroup name, the unique identifier for each FeatureGroup, and more.
func (*Client) DescribeFlowDefinition ¶
func (c *Client) DescribeFlowDefinition(ctx context.Context, params *DescribeFlowDefinitionInput, optFns ...func(*Options)) (*DescribeFlowDefinitionOutput, error)
Returns information about the specified flow definition.
func (*Client) DescribeHumanTaskUi ¶
func (c *Client) DescribeHumanTaskUi(ctx context.Context, params *DescribeHumanTaskUiInput, optFns ...func(*Options)) (*DescribeHumanTaskUiOutput, error)
Returns information about the requested human task user interface (worker task template).
func (*Client) DescribeHyperParameterTuningJob ¶
func (c *Client) DescribeHyperParameterTuningJob(ctx context.Context, params *DescribeHyperParameterTuningJobInput, optFns ...func(*Options)) (*DescribeHyperParameterTuningJobOutput, error)
Gets a description of a hyperparameter tuning job.
func (*Client) DescribeImage ¶
func (c *Client) DescribeImage(ctx context.Context, params *DescribeImageInput, optFns ...func(*Options)) (*DescribeImageOutput, error)
Describes a SageMaker image.
func (*Client) DescribeImageVersion ¶
func (c *Client) DescribeImageVersion(ctx context.Context, params *DescribeImageVersionInput, optFns ...func(*Options)) (*DescribeImageVersionOutput, error)
Describes a version of a SageMaker image.
func (*Client) DescribeLabelingJob ¶
func (c *Client) DescribeLabelingJob(ctx context.Context, params *DescribeLabelingJobInput, optFns ...func(*Options)) (*DescribeLabelingJobOutput, error)
Gets information about a labeling job.
func (*Client) DescribeModel ¶
func (c *Client) DescribeModel(ctx context.Context, params *DescribeModelInput, optFns ...func(*Options)) (*DescribeModelOutput, error)
Describes a model that you created using the CreateModel API.
func (*Client) DescribeModelBiasJobDefinition ¶
func (c *Client) DescribeModelBiasJobDefinition(ctx context.Context, params *DescribeModelBiasJobDefinitionInput, optFns ...func(*Options)) (*DescribeModelBiasJobDefinitionOutput, error)
Returns a description of a model bias job definition.
func (*Client) DescribeModelExplainabilityJobDefinition ¶
func (c *Client) DescribeModelExplainabilityJobDefinition(ctx context.Context, params *DescribeModelExplainabilityJobDefinitionInput, optFns ...func(*Options)) (*DescribeModelExplainabilityJobDefinitionOutput, error)
Returns a description of a model explainability job definition.
func (*Client) DescribeModelPackage ¶
func (c *Client) DescribeModelPackage(ctx context.Context, params *DescribeModelPackageInput, optFns ...func(*Options)) (*DescribeModelPackageOutput, error)
Returns a description of the specified model package, which is used to create Amazon SageMaker models or list them on AWS Marketplace. To create models in Amazon SageMaker, buyers can subscribe to model packages listed on AWS Marketplace.
func (*Client) DescribeModelPackageGroup ¶
func (c *Client) DescribeModelPackageGroup(ctx context.Context, params *DescribeModelPackageGroupInput, optFns ...func(*Options)) (*DescribeModelPackageGroupOutput, error)
Gets a description for the specified model group.
func (*Client) DescribeModelQualityJobDefinition ¶
func (c *Client) DescribeModelQualityJobDefinition(ctx context.Context, params *DescribeModelQualityJobDefinitionInput, optFns ...func(*Options)) (*DescribeModelQualityJobDefinitionOutput, error)
Returns a description of a model quality job definition.
func (*Client) DescribeMonitoringSchedule ¶
func (c *Client) DescribeMonitoringSchedule(ctx context.Context, params *DescribeMonitoringScheduleInput, optFns ...func(*Options)) (*DescribeMonitoringScheduleOutput, error)
Describes the schedule for a monitoring job.
func (*Client) DescribeNotebookInstance ¶
func (c *Client) DescribeNotebookInstance(ctx context.Context, params *DescribeNotebookInstanceInput, optFns ...func(*Options)) (*DescribeNotebookInstanceOutput, error)
Returns information about a notebook instance.
func (*Client) DescribeNotebookInstanceLifecycleConfig ¶
func (c *Client) DescribeNotebookInstanceLifecycleConfig(ctx context.Context, params *DescribeNotebookInstanceLifecycleConfigInput, optFns ...func(*Options)) (*DescribeNotebookInstanceLifecycleConfigOutput, error)
Returns a description of a notebook instance lifecycle configuration. For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance (https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html).
func (*Client) DescribePipeline ¶
func (c *Client) DescribePipeline(ctx context.Context, params *DescribePipelineInput, optFns ...func(*Options)) (*DescribePipelineOutput, error)
Describes the details of a pipeline.
func (*Client) DescribePipelineDefinitionForExecution ¶
func (c *Client) DescribePipelineDefinitionForExecution(ctx context.Context, params *DescribePipelineDefinitionForExecutionInput, optFns ...func(*Options)) (*DescribePipelineDefinitionForExecutionOutput, error)
Describes the details of an execution's pipeline definition.
func (*Client) DescribePipelineExecution ¶
func (c *Client) DescribePipelineExecution(ctx context.Context, params *DescribePipelineExecutionInput, optFns ...func(*Options)) (*DescribePipelineExecutionOutput, error)
Describes the details of a pipeline execution.
func (*Client) DescribeProcessingJob ¶
func (c *Client) DescribeProcessingJob(ctx context.Context, params *DescribeProcessingJobInput, optFns ...func(*Options)) (*DescribeProcessingJobOutput, error)
Returns a description of a processing job.
func (*Client) DescribeProject ¶
func (c *Client) DescribeProject(ctx context.Context, params *DescribeProjectInput, optFns ...func(*Options)) (*DescribeProjectOutput, error)
Describes the details of a project.
func (*Client) DescribeSubscribedWorkteam ¶
func (c *Client) DescribeSubscribedWorkteam(ctx context.Context, params *DescribeSubscribedWorkteamInput, optFns ...func(*Options)) (*DescribeSubscribedWorkteamOutput, error)
Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the AWS Marketplace.
func (*Client) DescribeTrainingJob ¶
func (c *Client) DescribeTrainingJob(ctx context.Context, params *DescribeTrainingJobInput, optFns ...func(*Options)) (*DescribeTrainingJobOutput, error)
Returns information about a training job.
func (*Client) DescribeTransformJob ¶
func (c *Client) DescribeTransformJob(ctx context.Context, params *DescribeTransformJobInput, optFns ...func(*Options)) (*DescribeTransformJobOutput, error)
Returns information about a transform job.
func (*Client) DescribeTrial ¶
func (c *Client) DescribeTrial(ctx context.Context, params *DescribeTrialInput, optFns ...func(*Options)) (*DescribeTrialOutput, error)
Provides a list of a trial's properties.
func (*Client) DescribeTrialComponent ¶
func (c *Client) DescribeTrialComponent(ctx context.Context, params *DescribeTrialComponentInput, optFns ...func(*Options)) (*DescribeTrialComponentOutput, error)
Provides a list of a trials component's properties.
func (*Client) DescribeUserProfile ¶
func (c *Client) DescribeUserProfile(ctx context.Context, params *DescribeUserProfileInput, optFns ...func(*Options)) (*DescribeUserProfileOutput, error)
Describes a user profile. For more information, see CreateUserProfile.
func (*Client) DescribeWorkforce ¶
func (c *Client) DescribeWorkforce(ctx context.Context, params *DescribeWorkforceInput, optFns ...func(*Options)) (*DescribeWorkforceOutput, error)
Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs (https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html)). Allowable IP address ranges are the IP addresses that workers can use to access tasks. This operation applies only to private workforces.
func (*Client) DescribeWorkteam ¶
func (c *Client) DescribeWorkteam(ctx context.Context, params *DescribeWorkteamInput, optFns ...func(*Options)) (*DescribeWorkteamOutput, error)
Gets information about a specific work team. You can see information such as the create date, the last updated date, membership information, and the work team's Amazon Resource Name (ARN).
func (*Client) DisableSagemakerServicecatalogPortfolio ¶
func (c *Client) DisableSagemakerServicecatalogPortfolio(ctx context.Context, params *DisableSagemakerServicecatalogPortfolioInput, optFns ...func(*Options)) (*DisableSagemakerServicecatalogPortfolioOutput, error)
Disables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
func (*Client) DisassociateTrialComponent ¶
func (c *Client) DisassociateTrialComponent(ctx context.Context, params *DisassociateTrialComponentInput, optFns ...func(*Options)) (*DisassociateTrialComponentOutput, error)
Disassociates a trial component from a trial. This doesn't effect other trials the component is associated with. Before you can delete a component, you must disassociate the component from all trials it is associated with. To associate a trial component with a trial, call the AssociateTrialComponent API. To get a list of the trials a component is associated with, use the Search API. Specify ExperimentTrialComponent for the Resource parameter. The list appears in the response under Results.TrialComponent.Parents.
func (*Client) EnableSagemakerServicecatalogPortfolio ¶
func (c *Client) EnableSagemakerServicecatalogPortfolio(ctx context.Context, params *EnableSagemakerServicecatalogPortfolioInput, optFns ...func(*Options)) (*EnableSagemakerServicecatalogPortfolioOutput, error)
Enables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
func (*Client) GetDeviceFleetReport ¶
func (c *Client) GetDeviceFleetReport(ctx context.Context, params *GetDeviceFleetReportInput, optFns ...func(*Options)) (*GetDeviceFleetReportOutput, error)
Describes a fleet.
func (*Client) GetModelPackageGroupPolicy ¶
func (c *Client) GetModelPackageGroupPolicy(ctx context.Context, params *GetModelPackageGroupPolicyInput, optFns ...func(*Options)) (*GetModelPackageGroupPolicyOutput, error)
Gets a resource policy that manages access for a model group. For information about resource policies, see Identity-based policies and resource-based policies (https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_identity-vs-resource.html) in the AWS Identity and Access Management User Guide..
func (*Client) GetSagemakerServicecatalogPortfolioStatus ¶
func (c *Client) GetSagemakerServicecatalogPortfolioStatus(ctx context.Context, params *GetSagemakerServicecatalogPortfolioStatusInput, optFns ...func(*Options)) (*GetSagemakerServicecatalogPortfolioStatusOutput, error)
Gets the status of Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
func (*Client) GetSearchSuggestions ¶
func (c *Client) GetSearchSuggestions(ctx context.Context, params *GetSearchSuggestionsInput, optFns ...func(*Options)) (*GetSearchSuggestionsOutput, error)
An auto-complete API for the search functionality in the Amazon SageMaker console. It returns suggestions of possible matches for the property name to use in Search queries. Provides suggestions for HyperParameters, Tags, and Metrics.
func (*Client) ListActions ¶
func (c *Client) ListActions(ctx context.Context, params *ListActionsInput, optFns ...func(*Options)) (*ListActionsOutput, error)
Lists the actions in your account and their properties.
func (*Client) ListAlgorithms ¶
func (c *Client) ListAlgorithms(ctx context.Context, params *ListAlgorithmsInput, optFns ...func(*Options)) (*ListAlgorithmsOutput, error)
Lists the machine learning algorithms that have been created.
func (*Client) ListAppImageConfigs ¶
func (c *Client) ListAppImageConfigs(ctx context.Context, params *ListAppImageConfigsInput, optFns ...func(*Options)) (*ListAppImageConfigsOutput, error)
Lists the AppImageConfigs in your account and their properties. The list can be filtered by creation time or modified time, and whether the AppImageConfig name contains a specified string.
func (*Client) ListApps ¶
func (c *Client) ListApps(ctx context.Context, params *ListAppsInput, optFns ...func(*Options)) (*ListAppsOutput, error)
Lists apps.
func (*Client) ListArtifacts ¶
func (c *Client) ListArtifacts(ctx context.Context, params *ListArtifactsInput, optFns ...func(*Options)) (*ListArtifactsOutput, error)
Lists the artifacts in your account and their properties.
func (*Client) ListAssociations ¶
func (c *Client) ListAssociations(ctx context.Context, params *ListAssociationsInput, optFns ...func(*Options)) (*ListAssociationsOutput, error)
Lists the associations in your account and their properties.
func (*Client) ListAutoMLJobs ¶
func (c *Client) ListAutoMLJobs(ctx context.Context, params *ListAutoMLJobsInput, optFns ...func(*Options)) (*ListAutoMLJobsOutput, error)
Request a list of jobs.
func (*Client) ListCandidatesForAutoMLJob ¶
func (c *Client) ListCandidatesForAutoMLJob(ctx context.Context, params *ListCandidatesForAutoMLJobInput, optFns ...func(*Options)) (*ListCandidatesForAutoMLJobOutput, error)
List the Candidates created for the job.
func (*Client) ListCodeRepositories ¶
func (c *Client) ListCodeRepositories(ctx context.Context, params *ListCodeRepositoriesInput, optFns ...func(*Options)) (*ListCodeRepositoriesOutput, error)
Gets a list of the Git repositories in your account.
func (*Client) ListCompilationJobs ¶
func (c *Client) ListCompilationJobs(ctx context.Context, params *ListCompilationJobsInput, optFns ...func(*Options)) (*ListCompilationJobsOutput, error)
Lists model compilation jobs that satisfy various filters. To create a model compilation job, use CreateCompilationJob. To get information about a particular model compilation job you have created, use DescribeCompilationJob.
func (*Client) ListContexts ¶
func (c *Client) ListContexts(ctx context.Context, params *ListContextsInput, optFns ...func(*Options)) (*ListContextsOutput, error)
Lists the contexts in your account and their properties.
func (*Client) ListDataQualityJobDefinitions ¶
func (c *Client) ListDataQualityJobDefinitions(ctx context.Context, params *ListDataQualityJobDefinitionsInput, optFns ...func(*Options)) (*ListDataQualityJobDefinitionsOutput, error)
Lists the data quality job definitions in your account.
func (*Client) ListDeviceFleets ¶
func (c *Client) ListDeviceFleets(ctx context.Context, params *ListDeviceFleetsInput, optFns ...func(*Options)) (*ListDeviceFleetsOutput, error)
Returns a list of devices in the fleet.
func (*Client) ListDevices ¶
func (c *Client) ListDevices(ctx context.Context, params *ListDevicesInput, optFns ...func(*Options)) (*ListDevicesOutput, error)
A list of devices.
func (*Client) ListDomains ¶
func (c *Client) ListDomains(ctx context.Context, params *ListDomainsInput, optFns ...func(*Options)) (*ListDomainsOutput, error)
Lists the domains.
func (*Client) ListEdgePackagingJobs ¶
func (c *Client) ListEdgePackagingJobs(ctx context.Context, params *ListEdgePackagingJobsInput, optFns ...func(*Options)) (*ListEdgePackagingJobsOutput, error)
Returns a list of edge packaging jobs.
func (*Client) ListEndpointConfigs ¶
func (c *Client) ListEndpointConfigs(ctx context.Context, params *ListEndpointConfigsInput, optFns ...func(*Options)) (*ListEndpointConfigsOutput, error)
Lists endpoint configurations.
func (*Client) ListEndpoints ¶
func (c *Client) ListEndpoints(ctx context.Context, params *ListEndpointsInput, optFns ...func(*Options)) (*ListEndpointsOutput, error)
Lists endpoints.
func (*Client) ListExperiments ¶
func (c *Client) ListExperiments(ctx context.Context, params *ListExperimentsInput, optFns ...func(*Options)) (*ListExperimentsOutput, error)
Lists all the experiments in your account. The list can be filtered to show only experiments that were created in a specific time range. The list can be sorted by experiment name or creation time.
func (*Client) ListFeatureGroups ¶
func (c *Client) ListFeatureGroups(ctx context.Context, params *ListFeatureGroupsInput, optFns ...func(*Options)) (*ListFeatureGroupsOutput, error)
List FeatureGroups based on given filter and order.
func (*Client) ListFlowDefinitions ¶
func (c *Client) ListFlowDefinitions(ctx context.Context, params *ListFlowDefinitionsInput, optFns ...func(*Options)) (*ListFlowDefinitionsOutput, error)
Returns information about the flow definitions in your account.
func (*Client) ListHumanTaskUis ¶
func (c *Client) ListHumanTaskUis(ctx context.Context, params *ListHumanTaskUisInput, optFns ...func(*Options)) (*ListHumanTaskUisOutput, error)
Returns information about the human task user interfaces in your account.
func (*Client) ListHyperParameterTuningJobs ¶
func (c *Client) ListHyperParameterTuningJobs(ctx context.Context, params *ListHyperParameterTuningJobsInput, optFns ...func(*Options)) (*ListHyperParameterTuningJobsOutput, error)
Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.
func (*Client) ListImageVersions ¶
func (c *Client) ListImageVersions(ctx context.Context, params *ListImageVersionsInput, optFns ...func(*Options)) (*ListImageVersionsOutput, error)
Lists the versions of a specified image and their properties. The list can be filtered by creation time or modified time.
func (*Client) ListImages ¶
func (c *Client) ListImages(ctx context.Context, params *ListImagesInput, optFns ...func(*Options)) (*ListImagesOutput, error)
Lists the images in your account and their properties. The list can be filtered by creation time or modified time, and whether the image name contains a specified string.
func (*Client) ListLabelingJobs ¶
func (c *Client) ListLabelingJobs(ctx context.Context, params *ListLabelingJobsInput, optFns ...func(*Options)) (*ListLabelingJobsOutput, error)
Gets a list of labeling jobs.
func (*Client) ListLabelingJobsForWorkteam ¶
func (c *Client) ListLabelingJobsForWorkteam(ctx context.Context, params *ListLabelingJobsForWorkteamInput, optFns ...func(*Options)) (*ListLabelingJobsForWorkteamOutput, error)
Gets a list of labeling jobs assigned to a specified work team.
func (*Client) ListModelBiasJobDefinitions ¶
func (c *Client) ListModelBiasJobDefinitions(ctx context.Context, params *ListModelBiasJobDefinitionsInput, optFns ...func(*Options)) (*ListModelBiasJobDefinitionsOutput, error)
Lists model bias jobs definitions that satisfy various filters.
func (*Client) ListModelExplainabilityJobDefinitions ¶
func (c *Client) ListModelExplainabilityJobDefinitions(ctx context.Context, params *ListModelExplainabilityJobDefinitionsInput, optFns ...func(*Options)) (*ListModelExplainabilityJobDefinitionsOutput, error)
Lists model explainability job definitions that satisfy various filters.
func (*Client) ListModelPackageGroups ¶
func (c *Client) ListModelPackageGroups(ctx context.Context, params *ListModelPackageGroupsInput, optFns ...func(*Options)) (*ListModelPackageGroupsOutput, error)
Gets a list of the model groups in your AWS account.
func (*Client) ListModelPackages ¶
func (c *Client) ListModelPackages(ctx context.Context, params *ListModelPackagesInput, optFns ...func(*Options)) (*ListModelPackagesOutput, error)
Lists the model packages that have been created.
func (*Client) ListModelQualityJobDefinitions ¶
func (c *Client) ListModelQualityJobDefinitions(ctx context.Context, params *ListModelQualityJobDefinitionsInput, optFns ...func(*Options)) (*ListModelQualityJobDefinitionsOutput, error)
Gets a list of model quality monitoring job definitions in your account.
func (*Client) ListModels ¶
func (c *Client) ListModels(ctx context.Context, params *ListModelsInput, optFns ...func(*Options)) (*ListModelsOutput, error)
Lists models created with the CreateModel API.
func (*Client) ListMonitoringExecutions ¶
func (c *Client) ListMonitoringExecutions(ctx context.Context, params *ListMonitoringExecutionsInput, optFns ...func(*Options)) (*ListMonitoringExecutionsOutput, error)
Returns list of all monitoring job executions.
func (*Client) ListMonitoringSchedules ¶
func (c *Client) ListMonitoringSchedules(ctx context.Context, params *ListMonitoringSchedulesInput, optFns ...func(*Options)) (*ListMonitoringSchedulesOutput, error)
Returns list of all monitoring schedules.
func (*Client) ListNotebookInstanceLifecycleConfigs ¶
func (c *Client) ListNotebookInstanceLifecycleConfigs(ctx context.Context, params *ListNotebookInstanceLifecycleConfigsInput, optFns ...func(*Options)) (*ListNotebookInstanceLifecycleConfigsOutput, error)
Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API.
func (*Client) ListNotebookInstances ¶
func (c *Client) ListNotebookInstances(ctx context.Context, params *ListNotebookInstancesInput, optFns ...func(*Options)) (*ListNotebookInstancesOutput, error)
Returns a list of the Amazon SageMaker notebook instances in the requester's account in an AWS Region.
func (*Client) ListPipelineExecutionSteps ¶
func (c *Client) ListPipelineExecutionSteps(ctx context.Context, params *ListPipelineExecutionStepsInput, optFns ...func(*Options)) (*ListPipelineExecutionStepsOutput, error)
Gets a list of PipeLineExecutionStep objects.
func (*Client) ListPipelineExecutions ¶
func (c *Client) ListPipelineExecutions(ctx context.Context, params *ListPipelineExecutionsInput, optFns ...func(*Options)) (*ListPipelineExecutionsOutput, error)
Gets a list of the pipeline executions.
func (*Client) ListPipelineParametersForExecution ¶
func (c *Client) ListPipelineParametersForExecution(ctx context.Context, params *ListPipelineParametersForExecutionInput, optFns ...func(*Options)) (*ListPipelineParametersForExecutionOutput, error)
Gets a list of parameters for a pipeline execution.
func (*Client) ListPipelines ¶
func (c *Client) ListPipelines(ctx context.Context, params *ListPipelinesInput, optFns ...func(*Options)) (*ListPipelinesOutput, error)
Gets a list of pipelines.
func (*Client) ListProcessingJobs ¶
func (c *Client) ListProcessingJobs(ctx context.Context, params *ListProcessingJobsInput, optFns ...func(*Options)) (*ListProcessingJobsOutput, error)
Lists processing jobs that satisfy various filters.
func (*Client) ListProjects ¶
func (c *Client) ListProjects(ctx context.Context, params *ListProjectsInput, optFns ...func(*Options)) (*ListProjectsOutput, error)
Gets a list of the projects in an AWS account.
func (*Client) ListSubscribedWorkteams ¶
func (c *Client) ListSubscribedWorkteams(ctx context.Context, params *ListSubscribedWorkteamsInput, optFns ...func(*Options)) (*ListSubscribedWorkteamsOutput, error)
Gets a list of the work teams that you are subscribed to in the AWS Marketplace. The list may be empty if no work team satisfies the filter specified in the NameContains parameter.
func (*Client) ListTags ¶
func (c *Client) ListTags(ctx context.Context, params *ListTagsInput, optFns ...func(*Options)) (*ListTagsOutput, error)
Returns the tags for the specified Amazon SageMaker resource.
func (*Client) ListTrainingJobs ¶
func (c *Client) ListTrainingJobs(ctx context.Context, params *ListTrainingJobsInput, optFns ...func(*Options)) (*ListTrainingJobsOutput, error)
Lists training jobs.
func (*Client) ListTrainingJobsForHyperParameterTuningJob ¶
func (c *Client) ListTrainingJobsForHyperParameterTuningJob(ctx context.Context, params *ListTrainingJobsForHyperParameterTuningJobInput, optFns ...func(*Options)) (*ListTrainingJobsForHyperParameterTuningJobOutput, error)
Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.
func (*Client) ListTransformJobs ¶
func (c *Client) ListTransformJobs(ctx context.Context, params *ListTransformJobsInput, optFns ...func(*Options)) (*ListTransformJobsOutput, error)
Lists transform jobs.
func (*Client) ListTrialComponents ¶
func (c *Client) ListTrialComponents(ctx context.Context, params *ListTrialComponentsInput, optFns ...func(*Options)) (*ListTrialComponentsOutput, error)
Lists the trial components in your account. You can sort the list by trial component name or creation time. You can filter the list to show only components that were created in a specific time range. You can also filter on one of the following:
* ExperimentName
* SourceArn
* TrialName
func (*Client) ListTrials ¶
func (c *Client) ListTrials(ctx context.Context, params *ListTrialsInput, optFns ...func(*Options)) (*ListTrialsOutput, error)
Lists the trials in your account. Specify an experiment name to limit the list to the trials that are part of that experiment. Specify a trial component name to limit the list to the trials that associated with that trial component. The list can be filtered to show only trials that were created in a specific time range. The list can be sorted by trial name or creation time.
func (*Client) ListUserProfiles ¶
func (c *Client) ListUserProfiles(ctx context.Context, params *ListUserProfilesInput, optFns ...func(*Options)) (*ListUserProfilesOutput, error)
Lists user profiles.
func (*Client) ListWorkforces ¶
func (c *Client) ListWorkforces(ctx context.Context, params *ListWorkforcesInput, optFns ...func(*Options)) (*ListWorkforcesOutput, error)
Use this operation to list all private and vendor workforces in an AWS Region. Note that you can only have one private workforce per AWS Region.
func (*Client) ListWorkteams ¶
func (c *Client) ListWorkteams(ctx context.Context, params *ListWorkteamsInput, optFns ...func(*Options)) (*ListWorkteamsOutput, error)
Gets a list of private work teams that you have defined in a region. The list may be empty if no work team satisfies the filter specified in the NameContains parameter.
func (*Client) PutModelPackageGroupPolicy ¶
func (c *Client) PutModelPackageGroupPolicy(ctx context.Context, params *PutModelPackageGroupPolicyInput, optFns ...func(*Options)) (*PutModelPackageGroupPolicyOutput, error)
Adds a resouce policy to control access to a model group. For information about resoure policies, see Identity-based policies and resource-based policies (https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_identity-vs-resource.html) in the AWS Identity and Access Management User Guide..
func (*Client) RegisterDevices ¶
func (c *Client) RegisterDevices(ctx context.Context, params *RegisterDevicesInput, optFns ...func(*Options)) (*RegisterDevicesOutput, error)
Register devices.
func (*Client) RenderUiTemplate ¶
func (c *Client) RenderUiTemplate(ctx context.Context, params *RenderUiTemplateInput, optFns ...func(*Options)) (*RenderUiTemplateOutput, error)
Renders the UI template so that you can preview the worker's experience.
func (*Client) Search ¶
func (c *Client) Search(ctx context.Context, params *SearchInput, optFns ...func(*Options)) (*SearchOutput, error)
Finds Amazon SageMaker resources that match a search query. Matching resources are returned as a list of SearchRecord objects in the response. You can sort the search results by any resource property in a ascending or descending order. You can query against the following value types: numeric, text, Boolean, and timestamp.
func (*Client) StartMonitoringSchedule ¶
func (c *Client) StartMonitoringSchedule(ctx context.Context, params *StartMonitoringScheduleInput, optFns ...func(*Options)) (*StartMonitoringScheduleOutput, error)
Starts a previously stopped monitoring schedule. By default, when you successfully create a new schedule, the status of a monitoring schedule is scheduled.
func (*Client) StartNotebookInstance ¶
func (c *Client) StartNotebookInstance(ctx context.Context, params *StartNotebookInstanceInput, optFns ...func(*Options)) (*StartNotebookInstanceOutput, error)
Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume. After configuring the notebook instance, Amazon SageMaker sets the notebook instance status to InService. A notebook instance's status must be InService before you can connect to your Jupyter notebook.
func (*Client) StartPipelineExecution ¶
func (c *Client) StartPipelineExecution(ctx context.Context, params *StartPipelineExecutionInput, optFns ...func(*Options)) (*StartPipelineExecutionOutput, error)
Starts a pipeline execution.
func (*Client) StopAutoMLJob ¶
func (c *Client) StopAutoMLJob(ctx context.Context, params *StopAutoMLJobInput, optFns ...func(*Options)) (*StopAutoMLJobOutput, error)
A method for forcing the termination of a running job.
func (*Client) StopCompilationJob ¶
func (c *Client) StopCompilationJob(ctx context.Context, params *StopCompilationJobInput, optFns ...func(*Options)) (*StopCompilationJobOutput, error)
Stops a model compilation job. To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job hasn't stopped, it sends the SIGKILL signal. When it receives a StopCompilationJob request, Amazon SageMaker changes the CompilationJobSummary$CompilationJobStatus of the job to Stopping. After Amazon SageMaker stops the job, it sets the CompilationJobSummary$CompilationJobStatus to Stopped.
func (*Client) StopEdgePackagingJob ¶
func (c *Client) StopEdgePackagingJob(ctx context.Context, params *StopEdgePackagingJobInput, optFns ...func(*Options)) (*StopEdgePackagingJobOutput, error)
Request to stop an edge packaging job.
func (*Client) StopHyperParameterTuningJob ¶
func (c *Client) StopHyperParameterTuningJob(ctx context.Context, params *StopHyperParameterTuningJobInput, optFns ...func(*Options)) (*StopHyperParameterTuningJobOutput, error)
Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched. All model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3). All data that the training jobs write to Amazon CloudWatch Logs are still available in CloudWatch. After the tuning job moves to the Stopped state, it releases all reserved resources for the tuning job.
func (*Client) StopLabelingJob ¶
func (c *Client) StopLabelingJob(ctx context.Context, params *StopLabelingJobInput, optFns ...func(*Options)) (*StopLabelingJobOutput, error)
Stops a running labeling job. A job that is stopped cannot be restarted. Any results obtained before the job is stopped are placed in the Amazon S3 output bucket.
func (*Client) StopMonitoringSchedule ¶
func (c *Client) StopMonitoringSchedule(ctx context.Context, params *StopMonitoringScheduleInput, optFns ...func(*Options)) (*StopMonitoringScheduleOutput, error)
Stops a previously started monitoring schedule.
func (*Client) StopNotebookInstance ¶
func (c *Client) StopNotebookInstance(ctx context.Context, params *StopNotebookInstanceInput, optFns ...func(*Options)) (*StopNotebookInstanceOutput, error)
Terminates the ML compute instance. Before terminating the instance, Amazon SageMaker disconnects the ML storage volume from it. Amazon SageMaker preserves the ML storage volume. Amazon SageMaker stops charging you for the ML compute instance when you call StopNotebookInstance. To access data on the ML storage volume for a notebook instance that has been terminated, call the StartNotebookInstance API. StartNotebookInstance launches another ML compute instance, configures it, and attaches the preserved ML storage volume so you can continue your work.
func (*Client) StopPipelineExecution ¶
func (c *Client) StopPipelineExecution(ctx context.Context, params *StopPipelineExecutionInput, optFns ...func(*Options)) (*StopPipelineExecutionOutput, error)
Stops a pipeline execution.
func (*Client) StopProcessingJob ¶
func (c *Client) StopProcessingJob(ctx context.Context, params *StopProcessingJobInput, optFns ...func(*Options)) (*StopProcessingJobOutput, error)
Stops a processing job.
func (*Client) StopTrainingJob ¶
func (c *Client) StopTrainingJob(ctx context.Context, params *StopTrainingJobInput, optFns ...func(*Options)) (*StopTrainingJobOutput, error)
Stops a training job. To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts, so the results of the training is not lost. When it receives a StopTrainingJob request, Amazon SageMaker changes the status of the job to Stopping. After Amazon SageMaker stops the job, it sets the status to Stopped.
func (*Client) StopTransformJob ¶
func (c *Client) StopTransformJob(ctx context.Context, params *StopTransformJobInput, optFns ...func(*Options)) (*StopTransformJobOutput, error)
Stops a transform job. When Amazon SageMaker receives a StopTransformJob request, the status of the job changes to Stopping. After Amazon SageMaker stops the job, the status is set to Stopped. When you stop a transform job before it is completed, Amazon SageMaker doesn't store the job's output in Amazon S3.
func (*Client) UpdateAction ¶
func (c *Client) UpdateAction(ctx context.Context, params *UpdateActionInput, optFns ...func(*Options)) (*UpdateActionOutput, error)
Updates an action.
func (*Client) UpdateAppImageConfig ¶
func (c *Client) UpdateAppImageConfig(ctx context.Context, params *UpdateAppImageConfigInput, optFns ...func(*Options)) (*UpdateAppImageConfigOutput, error)
Updates the properties of an AppImageConfig.
func (*Client) UpdateArtifact ¶
func (c *Client) UpdateArtifact(ctx context.Context, params *UpdateArtifactInput, optFns ...func(*Options)) (*UpdateArtifactOutput, error)
Updates an artifact.
func (*Client) UpdateCodeRepository ¶
func (c *Client) UpdateCodeRepository(ctx context.Context, params *UpdateCodeRepositoryInput, optFns ...func(*Options)) (*UpdateCodeRepositoryOutput, error)
Updates the specified Git repository with the specified values.
func (*Client) UpdateContext ¶
func (c *Client) UpdateContext(ctx context.Context, params *UpdateContextInput, optFns ...func(*Options)) (*UpdateContextOutput, error)
Updates a context.
func (*Client) UpdateDeviceFleet ¶
func (c *Client) UpdateDeviceFleet(ctx context.Context, params *UpdateDeviceFleetInput, optFns ...func(*Options)) (*UpdateDeviceFleetOutput, error)
Updates a fleet of devices.
func (*Client) UpdateDevices ¶
func (c *Client) UpdateDevices(ctx context.Context, params *UpdateDevicesInput, optFns ...func(*Options)) (*UpdateDevicesOutput, error)
Updates one or more devices in a fleet.
func (*Client) UpdateDomain ¶
func (c *Client) UpdateDomain(ctx context.Context, params *UpdateDomainInput, optFns ...func(*Options)) (*UpdateDomainOutput, error)
Updates the default settings for new user profiles in the domain.
func (*Client) UpdateEndpoint ¶
func (c *Client) UpdateEndpoint(ctx context.Context, params *UpdateEndpointInput, optFns ...func(*Options)) (*UpdateEndpointOutput, error)
Deploys the new EndpointConfig specified in the request, switches to using newly created endpoint, and then deletes resources provisioned for the endpoint using the previous EndpointConfig (there is no availability loss). When Amazon SageMaker receives the request, it sets the endpoint status to Updating. After updating the endpoint, it sets the status to InService. To check the status of an endpoint, use the DescribeEndpoint API. You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig. If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
func (*Client) UpdateEndpointWeightsAndCapacities ¶
func (c *Client) UpdateEndpointWeightsAndCapacities(ctx context.Context, params *UpdateEndpointWeightsAndCapacitiesInput, optFns ...func(*Options)) (*UpdateEndpointWeightsAndCapacitiesOutput, error)
Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint. When it receives the request, Amazon SageMaker sets the endpoint status to Updating. After updating the endpoint, it sets the status to InService. To check the status of an endpoint, use the DescribeEndpoint API.
func (*Client) UpdateExperiment ¶
func (c *Client) UpdateExperiment(ctx context.Context, params *UpdateExperimentInput, optFns ...func(*Options)) (*UpdateExperimentOutput, error)
Adds, updates, or removes the description of an experiment. Updates the display name of an experiment.
func (*Client) UpdateImage ¶
func (c *Client) UpdateImage(ctx context.Context, params *UpdateImageInput, optFns ...func(*Options)) (*UpdateImageOutput, error)
Updates the properties of a SageMaker image. To change the image's tags, use the AddTags and DeleteTags APIs.
func (*Client) UpdateModelPackage ¶
func (c *Client) UpdateModelPackage(ctx context.Context, params *UpdateModelPackageInput, optFns ...func(*Options)) (*UpdateModelPackageOutput, error)
Updates a versioned model.
func (*Client) UpdateMonitoringSchedule ¶
func (c *Client) UpdateMonitoringSchedule(ctx context.Context, params *UpdateMonitoringScheduleInput, optFns ...func(*Options)) (*UpdateMonitoringScheduleOutput, error)
Updates a previously created schedule.
func (*Client) UpdateNotebookInstance ¶
func (c *Client) UpdateNotebookInstance(ctx context.Context, params *UpdateNotebookInstanceInput, optFns ...func(*Options)) (*UpdateNotebookInstanceOutput, error)
Updates a notebook instance. NotebookInstance updates include upgrading or downgrading the ML compute instance used for your notebook instance to accommodate changes in your workload requirements.
func (*Client) UpdateNotebookInstanceLifecycleConfig ¶
func (c *Client) UpdateNotebookInstanceLifecycleConfig(ctx context.Context, params *UpdateNotebookInstanceLifecycleConfigInput, optFns ...func(*Options)) (*UpdateNotebookInstanceLifecycleConfigOutput, error)
Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API.
func (*Client) UpdatePipeline ¶
func (c *Client) UpdatePipeline(ctx context.Context, params *UpdatePipelineInput, optFns ...func(*Options)) (*UpdatePipelineOutput, error)
Updates a pipeline.
func (*Client) UpdatePipelineExecution ¶
func (c *Client) UpdatePipelineExecution(ctx context.Context, params *UpdatePipelineExecutionInput, optFns ...func(*Options)) (*UpdatePipelineExecutionOutput, error)
Updates a pipeline execution.
func (*Client) UpdateTrainingJob ¶
func (c *Client) UpdateTrainingJob(ctx context.Context, params *UpdateTrainingJobInput, optFns ...func(*Options)) (*UpdateTrainingJobOutput, error)
Update a model training job to request a new Debugger profiling configuration.
func (*Client) UpdateTrial ¶
func (c *Client) UpdateTrial(ctx context.Context, params *UpdateTrialInput, optFns ...func(*Options)) (*UpdateTrialOutput, error)
Updates the display name of a trial.
func (*Client) UpdateTrialComponent ¶
func (c *Client) UpdateTrialComponent(ctx context.Context, params *UpdateTrialComponentInput, optFns ...func(*Options)) (*UpdateTrialComponentOutput, error)
Updates one or more properties of a trial component.
func (*Client) UpdateUserProfile ¶
func (c *Client) UpdateUserProfile(ctx context.Context, params *UpdateUserProfileInput, optFns ...func(*Options)) (*UpdateUserProfileOutput, error)
Updates a user profile.
func (*Client) UpdateWorkforce ¶
func (c *Client) UpdateWorkforce(ctx context.Context, params *UpdateWorkforceInput, optFns ...func(*Options)) (*UpdateWorkforceOutput, error)
Use this operation to update your workforce. You can use this operation to require that workers use specific IP addresses to work on tasks and to update your OpenID Connect (OIDC) Identity Provider (IdP) workforce configuration. Use SourceIpConfig to restrict worker access to tasks to a specific range of IP addresses. You specify allowed IP addresses by creating a list of up to ten CIDRs (https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html). By default, a workforce isn't restricted to specific IP addresses. If you specify a range of IP addresses, workers who attempt to access tasks using any IP address outside the specified range are denied and get a Not Found error message on the worker portal. Use OidcConfig to update the configuration of a workforce created using your own OIDC IdP. You can only update your OIDC IdP configuration when there are no work teams associated with your workforce. You can delete work teams using the operation. After restricting access to a range of IP addresses or updating your OIDC IdP configuration with this operation, you can view details about your update workforce using the operation. This operation only applies to private workforces.
func (*Client) UpdateWorkteam ¶
func (c *Client) UpdateWorkteam(ctx context.Context, params *UpdateWorkteamInput, optFns ...func(*Options)) (*UpdateWorkteamOutput, error)
Updates an existing work team with new member definitions or description.
type CreateActionInput ¶
type CreateActionInput struct { // The name of the action. Must be unique to your account in an AWS Region. // // This member is required. ActionName *string // The action type. // // This member is required. ActionType *string // The source type, ID, and URI. // // This member is required. Source *types.ActionSource // The description of the action. Description *string // Metadata properties of the tracking entity, trial, or trial component. MetadataProperties *types.MetadataProperties // A list of properties to add to the action. Properties map[string]string // The status of the action. Status types.ActionStatus // A list of tags to apply to the action. Tags []types.Tag }
type CreateActionOutput ¶
type CreateActionOutput struct { // The Amazon Resource Name (ARN) of the action. ActionArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateAlgorithmInput ¶
type CreateAlgorithmInput struct { // The name of the algorithm. // // This member is required. AlgorithmName *string // Specifies details about training jobs run by this algorithm, including the // following: // // * The Amazon ECR path of the container and the version digest of the // algorithm. // // * The hyperparameters that the algorithm supports. // // * The instance // types that the algorithm supports for training. // // * Whether the algorithm // supports distributed training. // // * The metrics that the algorithm emits to Amazon // CloudWatch. // // * Which metrics that the algorithm emits can be used as the // objective metric for hyperparameter tuning jobs. // // * The input channels that the // algorithm supports for training data. For example, an algorithm might support // train, validation, and test channels. // // This member is required. TrainingSpecification *types.TrainingSpecification // A description of the algorithm. AlgorithmDescription *string // Whether to certify the algorithm so that it can be listed in AWS Marketplace. CertifyForMarketplace bool // Specifies details about inference jobs that the algorithm runs, including the // following: // // * The Amazon ECR paths of containers that contain the inference code // and model artifacts. // // * The instance types that the algorithm supports for // transform jobs and real-time endpoints used for inference. // // * The input and // output content formats that the algorithm supports for inference. InferenceSpecification *types.InferenceSpecification // An array of key-value pairs. You can use tags to categorize your AWS resources // in different ways, for example, by purpose, owner, or environment. For more // information, see Tagging AWS Resources // (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html). Tags []types.Tag // Specifies configurations for one or more training jobs and that Amazon SageMaker // runs to test the algorithm's training code and, optionally, one or more batch // transform jobs that Amazon SageMaker runs to test the algorithm's inference // code. ValidationSpecification *types.AlgorithmValidationSpecification }
type CreateAlgorithmOutput ¶
type CreateAlgorithmOutput struct { // The Amazon Resource Name (ARN) of the new algorithm. // // This member is required. AlgorithmArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateAppImageConfigInput ¶
type CreateAppImageConfigInput struct { // The name of the AppImageConfig. Must be unique to your account. // // This member is required. AppImageConfigName *string // The KernelGatewayImageConfig. KernelGatewayImageConfig *types.KernelGatewayImageConfig // A list of tags to apply to the AppImageConfig. Tags []types.Tag }
type CreateAppImageConfigOutput ¶
type CreateAppImageConfigOutput struct { // The Amazon Resource Name (ARN) of the AppImageConfig. AppImageConfigArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateAppInput ¶
type CreateAppInput struct { // The name of the app. // // This member is required. AppName *string // The type of app. // // This member is required. AppType types.AppType // The domain ID. // // This member is required. DomainId *string // The user profile name. // // This member is required. UserProfileName *string // The instance type and the Amazon Resource Name (ARN) of the SageMaker image // created on the instance. ResourceSpec *types.ResourceSpec // Each tag consists of a key and an optional value. Tag keys must be unique per // resource. Tags []types.Tag }
type CreateAppOutput ¶
type CreateAppOutput struct { // The Amazon Resource Name (ARN) of the app. AppArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateArtifactInput ¶
type CreateArtifactInput struct { // The artifact type. // // This member is required. ArtifactType *string // The ID, ID type, and URI of the source. // // This member is required. Source *types.ArtifactSource // The name of the artifact. Must be unique to your account in an AWS Region. ArtifactName *string // Metadata properties of the tracking entity, trial, or trial component. MetadataProperties *types.MetadataProperties // A list of properties to add to the artifact. Properties map[string]string // A list of tags to apply to the artifact. Tags []types.Tag }
type CreateArtifactOutput ¶
type CreateArtifactOutput struct { // The Amazon Resource Name (ARN) of the artifact. ArtifactArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateAutoMLJobInput ¶
type CreateAutoMLJobInput struct { // Identifies an Autopilot job. Must be unique to your account and is // case-insensitive. // // This member is required. AutoMLJobName *string // Similar to InputDataConfig supported by Tuning. Format(s) supported: CSV. // Minimum of 500 rows. // // This member is required. InputDataConfig []types.AutoMLChannel // Similar to OutputDataConfig supported by Tuning. Format(s) supported: CSV. // // This member is required. OutputDataConfig *types.AutoMLOutputDataConfig // The ARN of the role that is used to access the data. // // This member is required. RoleArn *string // Contains CompletionCriteria and SecurityConfig. AutoMLJobConfig *types.AutoMLJobConfig // Defines the objective of a an AutoML job. You provide a // AutoMLJobObjective$MetricName and Autopilot infers whether to minimize or // maximize it. If a metric is not specified, the most commonly used // ObjectiveMetric for problem type is automaically selected. AutoMLJobObjective *types.AutoMLJobObjective // Generates possible candidates without training a model. A candidate is a // combination of data preprocessors, algorithms, and algorithm parameter settings. GenerateCandidateDefinitionsOnly bool // Defines the kind of preprocessing and algorithms intended for the candidates. // Options include: BinaryClassification, MulticlassClassification, and Regression. ProblemType types.ProblemType // Each tag consists of a key and an optional value. Tag keys must be unique per // resource. Tags []types.Tag }
type CreateAutoMLJobOutput ¶
type CreateAutoMLJobOutput struct { // When a job is created, it is assigned a unique ARN. // // This member is required. AutoMLJobArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateCodeRepositoryInput ¶
type CreateCodeRepositoryInput struct { // The name of the Git repository. The name must have 1 to 63 characters. Valid // characters are a-z, A-Z, 0-9, and - (hyphen). // // This member is required. CodeRepositoryName *string // Specifies details about the repository, including the URL where the repository // is located, the default branch, and credentials to use to access the repository. // // This member is required. GitConfig *types.GitConfig // An array of key-value pairs. You can use tags to categorize your AWS resources // in different ways, for example, by purpose, owner, or environment. For more // information, see Tagging AWS Resources // (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html). Tags []types.Tag }
type CreateCodeRepositoryOutput ¶
type CreateCodeRepositoryOutput struct { // The Amazon Resource Name (ARN) of the new repository. // // This member is required. CodeRepositoryArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateCompilationJobInput ¶
type CreateCompilationJobInput struct { // A name for the model compilation job. The name must be unique within the AWS // Region and within your AWS account. // // This member is required. CompilationJobName *string // Provides information about the location of input model artifacts, the name and // shape of the expected data inputs, and the framework in which the model was // trained. // // This member is required. InputConfig *types.InputConfig // Provides information about the output location for the compiled model and the // target device the model runs on. // // This member is required. OutputConfig *types.OutputConfig // The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to // perform tasks on your behalf. During model compilation, Amazon SageMaker needs // your permission to: // // * Read input data from an S3 bucket // // * Write model // artifacts to an S3 bucket // // * Write logs to Amazon CloudWatch Logs // // * Publish // metrics to Amazon CloudWatch // // You grant permissions for all of these tasks to an // IAM role. To pass this role to Amazon SageMaker, the caller of this API must // have the iam:PassRole permission. For more information, see Amazon SageMaker // Roles. (https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html) // // This member is required. RoleArn *string // Specifies a limit to how long a model compilation job can run. When the job // reaches the time limit, Amazon SageMaker ends the compilation job. Use this API // to cap model training costs. // // This member is required. StoppingCondition *types.StoppingCondition // An array of key-value pairs. You can use tags to categorize your AWS resources // in different ways, for example, by purpose, owner, or environment. For more // information, see Tagging AWS Resources // (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html). Tags []types.Tag }
type CreateCompilationJobOutput ¶
type CreateCompilationJobOutput struct { // If the action is successful, the service sends back an HTTP 200 response. Amazon // SageMaker returns the following data in JSON format: // // * CompilationJobArn: The // Amazon Resource Name (ARN) of the compiled job. // // This member is required. CompilationJobArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateContextInput ¶
type CreateContextInput struct { // The name of the context. Must be unique to your account in an AWS Region. // // This member is required. ContextName *string // The context type. // // This member is required. ContextType *string // The source type, ID, and URI. // // This member is required. Source *types.ContextSource // The description of the context. Description *string // A list of properties to add to the context. Properties map[string]string // A list of tags to apply to the context. Tags []types.Tag }
type CreateContextOutput ¶
type CreateContextOutput struct { // The Amazon Resource Name (ARN) of the context. ContextArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateDataQualityJobDefinitionInput ¶
type CreateDataQualityJobDefinitionInput struct { // Specifies the container that runs the monitoring job. // // This member is required. DataQualityAppSpecification *types.DataQualityAppSpecification // A list of inputs for the monitoring job. Currently endpoints are supported as // monitoring inputs. // // This member is required. DataQualityJobInput *types.DataQualityJobInput // The output configuration for monitoring jobs. // // This member is required. DataQualityJobOutputConfig *types.MonitoringOutputConfig // The name for the monitoring job definition. // // This member is required. JobDefinitionName *string // Identifies the resources to deploy for a monitoring job. // // This member is required. JobResources *types.MonitoringResources // The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume // to perform tasks on your behalf. // // This member is required. RoleArn *string // Configures the constraints and baselines for the monitoring job. DataQualityBaselineConfig *types.DataQualityBaselineConfig // Specifies networking configuration for the monitoring job. NetworkConfig *types.MonitoringNetworkConfig // A time limit for how long the monitoring job is allowed to run before stopping. StoppingCondition *types.MonitoringStoppingCondition // (Optional) An array of key-value pairs. For more information, see Using Cost // Allocation Tags // (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL) // in the AWS Billing and Cost Management User Guide. Tags []types.Tag }
type CreateDataQualityJobDefinitionOutput ¶
type CreateDataQualityJobDefinitionOutput struct { // The Amazon Resource Name (ARN) of the job definition. // // This member is required. JobDefinitionArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateDeviceFleetInput ¶
type CreateDeviceFleetInput struct { // The name of the fleet that the device belongs to. // // This member is required. DeviceFleetName *string // The output configuration for storing sample data collected by the fleet. // // This member is required. OutputConfig *types.EdgeOutputConfig // A description of the fleet. Description *string // The Amazon Resource Name (ARN) that has access to AWS Internet of Things (IoT). RoleArn *string // Creates tags for the specified fleet. Tags []types.Tag }
type CreateDeviceFleetOutput ¶
type CreateDeviceFleetOutput struct { // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateDomainInput ¶
type CreateDomainInput struct { // The mode of authentication that members use to access the domain. // // This member is required. AuthMode types.AuthMode // The default user settings. // // This member is required. DefaultUserSettings *types.UserSettings // A name for the domain. // // This member is required. DomainName *string // The VPC subnets that Studio uses for communication. // // This member is required. SubnetIds []string // The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for // communication. // // This member is required. VpcId *string // Specifies the VPC used for non-EFS traffic. The default value is // PublicInternetOnly. // // * PublicInternetOnly - Non-EFS traffic is through a VPC // managed by Amazon SageMaker, which allows direct internet access // // * VpcOnly - // All Studio traffic is through the specified VPC and subnets AppNetworkAccessType types.AppNetworkAccessType // This member is deprecated and replaced with KmsKeyId. // // Deprecated: This property is deprecated, use KmsKeyId instead. HomeEfsFileSystemKmsKeyId *string // SageMaker uses AWS KMS to encrypt the EFS volume attached to the domain with an // AWS managed customer master key (CMK) by default. For more control, specify a // customer managed CMK. KmsKeyId *string // Tags to associated with the Domain. Each tag consists of a key and an optional // value. Tag keys must be unique per resource. Tags are searchable using the // Search API. Tags []types.Tag }
type CreateDomainOutput ¶
type CreateDomainOutput struct { // The Amazon Resource Name (ARN) of the created domain. DomainArn *string // The URL to the created domain. Url *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateEdgePackagingJobInput ¶
type CreateEdgePackagingJobInput struct { // The name of the SageMaker Neo compilation job that will be used to locate model // artifacts for packaging. // // This member is required. CompilationJobName *string // The name of the edge packaging job. // // This member is required. EdgePackagingJobName *string // The name of the model. // // This member is required. ModelName *string // The version of the model. // // This member is required. ModelVersion *string // Provides information about the output location for the packaged model. // // This member is required. OutputConfig *types.EdgeOutputConfig // The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to // download and upload the model, and to contact SageMaker Neo. // // This member is required. RoleArn *string // The CMK to use when encrypting the EBS volume the edge packaging job runs on. ResourceKey *string // Creates tags for the packaging job. Tags []types.Tag }
type CreateEdgePackagingJobOutput ¶
type CreateEdgePackagingJobOutput struct { // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateEndpointConfigInput ¶
type CreateEndpointConfigInput struct { // The name of the endpoint configuration. You specify this name in a // CreateEndpoint request. // // This member is required. EndpointConfigName *string // An list of ProductionVariant objects, one for each model that you want to host // at this endpoint. // // This member is required. ProductionVariants []types.ProductionVariant // DataCaptureConfig *types.DataCaptureConfig // The Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon // SageMaker uses to encrypt data on the storage volume attached to the ML compute // instance that hosts the endpoint. The KmsKeyId can be any of the following // formats: // // * Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab // // * Key ARN: // arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab // // * // Alias name: alias/ExampleAlias // // * Alias name ARN: // arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias // // The KMS key policy must // grant permission to the IAM role that you specify in your CreateEndpoint, // UpdateEndpoint requests. For more information, refer to the AWS Key Management // Service section Using Key Policies in AWS KMS // (https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html) // Certain Nitro-based instances include local storage, dependent on the instance // type. Local storage volumes are encrypted using a hardware module on the // instance. You can't request a KmsKeyId when using an instance type with local // storage. If any of the models that you specify in the ProductionVariants // parameter use nitro-based instances with local storage, do not specify a value // for the KmsKeyId parameter. If you specify a value for KmsKeyId when using any // nitro-based instances with local storage, the call to CreateEndpointConfig // fails. For a list of instance types that support local instance storage, see // Instance Store Volumes // (https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes). // For more information about local instance storage encryption, see SSD Instance // Store Volumes // (https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.html). KmsKeyId *string // An array of key-value pairs. You can use tags to categorize your AWS resources // in different ways, for example, by purpose, owner, or environment. For more // information, see Tagging AWS Resources // (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html). Tags []types.Tag }
type CreateEndpointConfigOutput ¶
type CreateEndpointConfigOutput struct { // The Amazon Resource Name (ARN) of the endpoint configuration. // // This member is required. EndpointConfigArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateEndpointInput ¶
type CreateEndpointInput struct { // The name of an endpoint configuration. For more information, see // CreateEndpointConfig. // // This member is required. EndpointConfigName *string // The name of the endpoint.The name must be unique within an AWS Region in your // AWS account. The name is case-insensitive in CreateEndpoint, but the case is // preserved and must be matched in . // // This member is required. EndpointName *string // An array of key-value pairs. You can use tags to categorize your AWS resources // in different ways, for example, by purpose, owner, or environment. For more // information, see Tagging AWS Resources // (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html). Tags []types.Tag }
type CreateEndpointOutput ¶
type CreateEndpointOutput struct { // The Amazon Resource Name (ARN) of the endpoint. // // This member is required. EndpointArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateExperimentInput ¶
type CreateExperimentInput struct { // The name of the experiment. The name must be unique in your AWS account and is // not case-sensitive. // // This member is required. ExperimentName *string // The description of the experiment. Description *string // The name of the experiment as displayed. The name doesn't need to be unique. If // you don't specify DisplayName, the value in ExperimentName is displayed. DisplayName *string // A list of tags to associate with the experiment. You can use Search API to // search on the tags. Tags []types.Tag }
type CreateExperimentOutput ¶
type CreateExperimentOutput struct { // The Amazon Resource Name (ARN) of the experiment. ExperimentArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateFeatureGroupInput ¶
type CreateFeatureGroupInput struct { // The name of the feature that stores the EventTime of a Record in a FeatureGroup. // An EventTime is a point in time when a new event occurs that corresponds to the // creation or update of a Record in a FeatureGroup. All Records in the // FeatureGroup must have a corresponding EventTime. An EventTime can be a String // or Fractional. // // * Fractional: EventTime feature values must be a Unix timestamp // in seconds. // // * String: EventTime feature values must be an ISO-8601 string in // the format. The following formats are supported yyyy-MM-dd'T'HH:mm:ssZ and // yyyy-MM-dd'T'HH:mm:ss.SSSZ where yyyy, MM, and dd represent the year, month, and // day respectively and HH, mm, ss, and if applicable, SSS represent the hour, // month, second and milliseconds respsectively. 'T' and Z are constants. // // This member is required. EventTimeFeatureName *string // A list of Feature names and types. Name and Type is compulsory per Feature. // Valid feature FeatureTypes are Integral, Fractional and String. FeatureNames // cannot be any of the following: is_deleted, write_time, api_invocation_time You // can create up to 2,500 FeatureDefinitions per FeatureGroup. // // This member is required. FeatureDefinitions []types.FeatureDefinition // The name of the FeatureGroup. The name must be unique within an AWS Region in an // AWS account. The name: // // * Must start and end with an alphanumeric character. // // * // Can only contain alphanumeric character and hyphens. Spaces are not allowed. // // This member is required. FeatureGroupName *string // The name of the Feature whose value uniquely identifies a Record defined in the // FeatureStore. Only the latest record per identifier value will be stored in the // OnlineStore. RecordIdentifierFeatureName must be one of feature definitions' // names. You use the RecordIdentifierFeatureName to access data in a FeatureStore. // This name: // // * Must start and end with an alphanumeric character. // // * Can only // contains alphanumeric characters, hyphens, underscores. Spaces are not allowed. // // This member is required. RecordIdentifierFeatureName *string // A free-form description of a FeatureGroup. Description *string // Use this to configure an OfflineFeatureStore. This parameter allows you to // specify: // // * The Amazon Simple Storage Service (Amazon S3) location of an // OfflineStore. // // * A configuration for an AWS Glue or AWS Hive data cataolgue. // // * // An KMS encryption key to encrypt the Amazon S3 location used for // OfflineStore. // // To learn more about this parameter, see OfflineStoreConfig. OfflineStoreConfig *types.OfflineStoreConfig // You can turn the OnlineStore on or off by specifying True for the // EnableOnlineStore flag in OnlineStoreConfig; the default value is False. You can // also include an AWS KMS key ID (KMSKeyId) for at-rest encryption of the // OnlineStore. OnlineStoreConfig *types.OnlineStoreConfig // The Amazon Resource Name (ARN) of the IAM execution role used to persist data // into the OfflineStore if an OfflineStoreConfig is provided. RoleArn *string // Tags used to identify Features in each FeatureGroup. Tags []types.Tag }
type CreateFeatureGroupOutput ¶
type CreateFeatureGroupOutput struct { // The Amazon Resource Name (ARN) of the FeatureGroup. This is a unique identifier // for the feature group. // // This member is required. FeatureGroupArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateFlowDefinitionInput ¶
type CreateFlowDefinitionInput struct { // The name of your flow definition. // // This member is required. FlowDefinitionName *string // An object containing information about the tasks the human reviewers will // perform. // // This member is required. HumanLoopConfig *types.HumanLoopConfig // An object containing information about where the human review results will be // uploaded. // // This member is required. OutputConfig *types.FlowDefinitionOutputConfig // The Amazon Resource Name (ARN) of the role needed to call other services on your // behalf. For example, // arn:aws:iam::1234567890:role/service-role/AmazonSageMaker-ExecutionRole-20180111T151298. // // This member is required. RoleArn *string // An object containing information about the events that trigger a human workflow. HumanLoopActivationConfig *types.HumanLoopActivationConfig // Container for configuring the source of human task requests. Use to specify if // Amazon Rekognition or Amazon Textract is used as an integration source. HumanLoopRequestSource *types.HumanLoopRequestSource // An array of key-value pairs that contain metadata to help you categorize and // organize a flow definition. Each tag consists of a key and a value, both of // which you define. Tags []types.Tag }
type CreateFlowDefinitionOutput ¶
type CreateFlowDefinitionOutput struct { // The Amazon Resource Name (ARN) of the flow definition you create. // // This member is required. FlowDefinitionArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateHumanTaskUiInput ¶
type CreateHumanTaskUiInput struct { // The name of the user interface you are creating. // // This member is required. HumanTaskUiName *string // The Liquid template for the worker user interface. // // This member is required. UiTemplate *types.UiTemplate // An array of key-value pairs that contain metadata to help you categorize and // organize a human review workflow user interface. Each tag consists of a key and // a value, both of which you define. Tags []types.Tag }
type CreateHumanTaskUiOutput ¶
type CreateHumanTaskUiOutput struct { // The Amazon Resource Name (ARN) of the human review workflow user interface you // create. // // This member is required. HumanTaskUiArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateHyperParameterTuningJobInput ¶
type CreateHyperParameterTuningJobInput struct { // The HyperParameterTuningJobConfig object that describes the tuning job, // including the search strategy, the objective metric used to evaluate training // jobs, ranges of parameters to search, and resource limits for the tuning job. // For more information, see How Hyperparameter Tuning Works // (https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-how-it-works.html). // // This member is required. HyperParameterTuningJobConfig *types.HyperParameterTuningJobConfig // The name of the tuning job. This name is the prefix for the names of all // training jobs that this tuning job launches. The name must be unique within the // same AWS account and AWS Region. The name must have 1 to 32 characters. Valid // characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case // sensitive. // // This member is required. HyperParameterTuningJobName *string // An array of key-value pairs. You can use tags to categorize your AWS resources // in different ways, for example, by purpose, owner, or environment. For more // information, see Tagging AWS Resources // (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html). Tags that you // specify for the tuning job are also added to all training jobs that the tuning // job launches. Tags []types.Tag // The HyperParameterTrainingJobDefinition object that describes the training jobs // that this tuning job launches, including static hyperparameters, input data // configuration, output data configuration, resource configuration, and stopping // condition. TrainingJobDefinition *types.HyperParameterTrainingJobDefinition // A list of the HyperParameterTrainingJobDefinition objects launched for this // tuning job. TrainingJobDefinitions []types.HyperParameterTrainingJobDefinition // Specifies the configuration for starting the hyperparameter tuning job using one // or more previous tuning jobs as a starting point. The results of previous tuning // jobs are used to inform which combinations of hyperparameters to search over in // the new tuning job. All training jobs launched by the new hyperparameter tuning // job are evaluated by using the objective metric. If you specify // IDENTICAL_DATA_AND_ALGORITHM as the WarmStartType value for the warm start // configuration, the training job that performs the best in the new tuning job is // compared to the best training jobs from the parent tuning jobs. From these, the // training job that performs the best as measured by the objective metric is // returned as the overall best training job. All training jobs launched by parent // hyperparameter tuning jobs and the new hyperparameter tuning jobs count against // the limit of training jobs for the tuning job. WarmStartConfig *types.HyperParameterTuningJobWarmStartConfig }
type CreateHyperParameterTuningJobOutput ¶
type CreateHyperParameterTuningJobOutput struct { // The Amazon Resource Name (ARN) of the tuning job. Amazon SageMaker assigns an // ARN to a hyperparameter tuning job when you create it. // // This member is required. HyperParameterTuningJobArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateImageInput ¶
type CreateImageInput struct { // The name of the image. Must be unique to your account. // // This member is required. ImageName *string // The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to // perform tasks on your behalf. // // This member is required. RoleArn *string // The description of the image. Description *string // The display name of the image. If not provided, ImageName is displayed. DisplayName *string // A list of tags to apply to the image. Tags []types.Tag }
type CreateImageOutput ¶
type CreateImageOutput struct { // The Amazon Resource Name (ARN) of the image. ImageArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateImageVersionInput ¶
type CreateImageVersionInput struct { // The registry path of the container image to use as the starting point for this // version. The path is an Amazon Container Registry (ECR) URI in the following // format: .dkr.ecr..amazonaws.com/ // // This member is required. BaseImage *string // A unique ID. If not specified, the AWS CLI and AWS SDKs, such as the SDK for // Python (Boto3), add a unique value to the call. // // This member is required. ClientToken *string // The ImageName of the Image to create a version of. // // This member is required. ImageName *string }
type CreateImageVersionOutput ¶
type CreateImageVersionOutput struct { // The Amazon Resource Name (ARN) of the image version. ImageVersionArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateLabelingJobInput ¶
type CreateLabelingJobInput struct { // Configures the labeling task and how it is presented to workers; including, but // not limited to price, keywords, and batch size (task count). // // This member is required. HumanTaskConfig *types.HumanTaskConfig // Input data for the labeling job, such as the Amazon S3 location of the data // objects and the location of the manifest file that describes the data objects. // // This member is required. InputConfig *types.LabelingJobInputConfig // The attribute name to use for the label in the output manifest file. This is the // key for the key/value pair formed with the label that a worker assigns to the // object. The name can't end with "-metadata". If you are running a semantic // segmentation labeling job, the attribute name must end with "-ref". If you are // running any other kind of labeling job, the attribute name must not end with // "-ref". // // This member is required. LabelAttributeName *string // The name of the labeling job. This name is used to identify the job in a list of // labeling jobs. // // This member is required. LabelingJobName *string // The location of the output data and the AWS Key Management Service key ID for // the key used to encrypt the output data, if any. // // This member is required. OutputConfig *types.LabelingJobOutputConfig // The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks // on your behalf during data labeling. You must grant this role the necessary // permissions so that Amazon SageMaker can successfully complete data labeling. // // This member is required. RoleArn *string // The S3 URI of the file that defines the categories used to label the data // objects. For 3D point cloud task types, see Create a Labeling Category // Configuration File for 3D Point Cloud Labeling Jobs // (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud-label-category-config.html). // For all other built-in task types // (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html) and custom // tasks // (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates.html), // your label category configuration file must be a JSON file in the following // format. Identify the labels you want to use by replacing label_1, // label_2,...,label_n with your label categories. { // "document-version": // "2018-11-28" // // "labels": [ // // { // // "label": "label_1" // // }, // // { // // // "label": "label_2" // // }, // // ... // // { // // "label": "label_n" // // } // // // ] // // } LabelCategoryConfigS3Uri *string // Configures the information required to perform automated data labeling. LabelingJobAlgorithmsConfig *types.LabelingJobAlgorithmsConfig // A set of conditions for stopping the labeling job. If any of the conditions are // met, the job is automatically stopped. You can use these conditions to control // the cost of data labeling. StoppingConditions *types.LabelingJobStoppingConditions // An array of key/value pairs. For more information, see Using Cost Allocation // Tags // (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what) // in the AWS Billing and Cost Management User Guide. Tags []types.Tag }
type CreateLabelingJobOutput ¶
type CreateLabelingJobOutput struct { // The Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify // the labeling job. // // This member is required. LabelingJobArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateModelBiasJobDefinitionInput ¶
type CreateModelBiasJobDefinitionInput struct { // The name of the bias job definition. The name must be unique within an AWS // Region in the AWS account. // // This member is required. JobDefinitionName *string // Identifies the resources to deploy for a monitoring job. // // This member is required. JobResources *types.MonitoringResources // Configures the model bias job to run a specified Docker container image. // // This member is required. ModelBiasAppSpecification *types.ModelBiasAppSpecification // Inputs for the model bias job. // // This member is required. ModelBiasJobInput *types.ModelBiasJobInput // The output configuration for monitoring jobs. // // This member is required. ModelBiasJobOutputConfig *types.MonitoringOutputConfig // The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume // to perform tasks on your behalf. // // This member is required. RoleArn *string // The baseline configuration for a model bias job. ModelBiasBaselineConfig *types.ModelBiasBaselineConfig // Networking options for a model bias job. NetworkConfig *types.MonitoringNetworkConfig // A time limit for how long the monitoring job is allowed to run before stopping. StoppingCondition *types.MonitoringStoppingCondition // (Optional) An array of key-value pairs. For more information, see Using Cost // Allocation Tags // (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL) // in the AWS Billing and Cost Management User Guide. Tags []types.Tag }
type CreateModelBiasJobDefinitionOutput ¶
type CreateModelBiasJobDefinitionOutput struct { // The Amazon Resource Name (ARN) of the model bias job. // // This member is required. JobDefinitionArn *string // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata }
type CreateModelExplainabilityJobDefinitionInput ¶
type CreateModelExplainabilityJobDefinitionInput struct { // The name of the model explainability job definition. The name must be unique // within an AWS Region in the AWS account. // // This member is required. JobDefinitionName *string // Identifies