Amazon SageMaker Service 2017-07-24
- Client: Aws\SageMaker\SageMakerClient
- Service ID: sagemaker
- Version: 2017-07-24
This page describes the parameters and results for the operations of the Amazon SageMaker Service (2017-07-24), and shows how to use the Aws\SageMaker\SageMakerClient object to call the described operations. This documentation is specific to the 2017-07-24 API version of the service.
Operation Summary
Each of the following operations can be created from a client using
$client->getCommand('CommandName')
, where "CommandName" is the
name of one of the following operations. Note: a command is a value that
encapsulates an operation and the parameters used to create an HTTP request.
You can also create and send a command immediately using the magic methods
available on a client object: $client->commandName(/* parameters */)
.
You can send the command asynchronously (returning a promise) by appending the
word "Async" to the operation name: $client->commandNameAsync(/* parameters */)
.
- AddAssociation ( array $params = [] )
- Creates an association between the source and the destination.
- AddTags ( array $params = [] )
- Adds or overwrites one or more tags for the specified SageMaker resource.
- AssociateTrialComponent ( array $params = [] )
- Associates a trial component with a trial.
- BatchDescribeModelPackage ( array $params = [] )
- This action batch describes a list of versioned model packages
- CreateAction ( array $params = [] )
- Creates an action.
- CreateAlgorithm ( array $params = [] )
- Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace.
- CreateApp ( array $params = [] )
- Creates a running app for the specified UserProfile.
- CreateAppImageConfig ( array $params = [] )
- Creates a configuration for running a SageMaker image as a KernelGateway app.
- CreateArtifact ( array $params = [] )
- Creates an artifact.
- CreateAutoMLJob ( array $params = [] )
- Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
- CreateAutoMLJobV2 ( array $params = [] )
- Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.
- CreateCluster ( array $params = [] )
- Creates a SageMaker HyperPod cluster.
- CreateCodeRepository ( array $params = [] )
- Creates a Git repository as a resource in your SageMaker account.
- CreateCompilationJob ( array $params = [] )
- Starts a model compilation job.
- CreateContext ( array $params = [] )
- Creates a context.
- CreateDataQualityJobDefinition ( array $params = [] )
- Creates a definition for a job that monitors data quality and drift.
- CreateDeviceFleet ( array $params = [] )
- Creates a device fleet.
- CreateDomain ( array $params = [] )
- Creates a Domain.
- CreateEdgeDeploymentPlan ( array $params = [] )
- Creates an edge deployment plan, consisting of multiple stages.
- CreateEdgeDeploymentStage ( array $params = [] )
- Creates a new stage in an existing edge deployment plan.
- CreateEdgePackagingJob ( array $params = [] )
- Starts a SageMaker Edge Manager model packaging job.
- CreateEndpoint ( array $params = [] )
- Creates an endpoint using the endpoint configuration specified in the request.
- CreateEndpointConfig ( array $params = [] )
- Creates an endpoint configuration that SageMaker hosting services uses to deploy models.
- CreateExperiment ( array $params = [] )
- Creates a SageMaker experiment.
- CreateFeatureGroup ( array $params = [] )
- Create a new FeatureGroup.
- CreateFlowDefinition ( array $params = [] )
- Creates a flow definition.
- CreateHub ( array $params = [] )
- Create a hub.
- CreateHubContentReference ( array $params = [] )
- Create a hub content reference in order to add a model in the JumpStart public hub to a private hub.
- CreateHumanTaskUi ( array $params = [] )
- Defines the settings you will use for the human review workflow user interface.
- CreateHyperParameterTuningJob ( array $params = [] )
- Starts a hyperparameter tuning job.
- CreateImage ( array $params = [] )
- Creates a custom SageMaker image.
- CreateImageVersion ( array $params = [] )
- Creates a version of the SageMaker image specified by ImageName.
- CreateInferenceComponent ( array $params = [] )
- Creates an inference component, which is a SageMaker hosting object that you can use to deploy a model to an endpoint.
- CreateInferenceExperiment ( array $params = [] )
- Creates an inference experiment using the configurations specified in the request.
- CreateInferenceRecommendationsJob ( array $params = [] )
- Starts a recommendation job.
- CreateLabelingJob ( array $params = [] )
- Creates a job that uses workers to label the data objects in your input dataset.
- CreateMlflowTrackingServer ( array $params = [] )
- Creates an MLflow Tracking Server using a general purpose Amazon S3 bucket as the artifact store.
- CreateModel ( array $params = [] )
- Creates a model in SageMaker.
- CreateModelBiasJobDefinition ( array $params = [] )
- Creates the definition for a model bias job.
- CreateModelCard ( array $params = [] )
- Creates an Amazon SageMaker Model Card.
- CreateModelCardExportJob ( array $params = [] )
- Creates an Amazon SageMaker Model Card export job.
- CreateModelExplainabilityJobDefinition ( array $params = [] )
- Creates the definition for a model explainability job.
- CreateModelPackage ( array $params = [] )
- Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group.
- CreateModelPackageGroup ( array $params = [] )
- Creates a model group.
- CreateModelQualityJobDefinition ( array $params = [] )
- Creates a definition for a job that monitors model quality and drift.
- CreateMonitoringSchedule ( array $params = [] )
- Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endpoint.
- CreateNotebookInstance ( array $params = [] )
- Creates an SageMaker notebook instance.
- CreateNotebookInstanceLifecycleConfig ( array $params = [] )
- Creates a lifecycle configuration that you can associate with a notebook instance.
- CreateOptimizationJob ( array $params = [] )
- Creates a job that optimizes a model for inference performance.
- CreatePipeline ( array $params = [] )
- Creates a pipeline using a JSON pipeline definition.
- CreatePresignedDomainUrl ( array $params = [] )
- Creates a URL for a specified UserProfile in a Domain.
- CreatePresignedMlflowTrackingServerUrl ( array $params = [] )
- Returns a presigned URL that you can use to connect to the MLflow UI attached to your tracking server.
- CreatePresignedNotebookInstanceUrl ( array $params = [] )
- Returns a URL that you can use to connect to the Jupyter server from a notebook instance.
- CreateProcessingJob ( array $params = [] )
- Creates a processing job.
- CreateProject ( array $params = [] )
- 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.
- CreateSpace ( array $params = [] )
- Creates a private space or a space used for real time collaboration in a domain.
- CreateStudioLifecycleConfig ( array $params = [] )
- Creates a new Amazon SageMaker Studio Lifecycle Configuration.
- CreateTrainingJob ( array $params = [] )
- Starts a model training job.
- CreateTransformJob ( array $params = [] )
- Starts a transform job.
- CreateTrial ( array $params = [] )
- Creates an SageMaker trial.
- CreateTrialComponent ( array $params = [] )
- Creates a trial component, which is a stage of a machine learning trial.
- CreateUserProfile ( array $params = [] )
- Creates a user profile.
- CreateWorkforce ( array $params = [] )
- Use this operation to create a workforce.
- CreateWorkteam ( array $params = [] )
- Creates a new work team for labeling your data.
- DeleteAction ( array $params = [] )
- Deletes an action.
- DeleteAlgorithm ( array $params = [] )
- Removes the specified algorithm from your account.
- DeleteApp ( array $params = [] )
- Used to stop and delete an app.
- DeleteAppImageConfig ( array $params = [] )
- Deletes an AppImageConfig.
- DeleteArtifact ( array $params = [] )
- Deletes an artifact.
- DeleteAssociation ( array $params = [] )
- Deletes an association.
- DeleteCluster ( array $params = [] )
- Delete a SageMaker HyperPod cluster.
- DeleteCodeRepository ( array $params = [] )
- Deletes the specified Git repository from your account.
- DeleteCompilationJob ( array $params = [] )
- Deletes the specified compilation job.
- DeleteContext ( array $params = [] )
- Deletes an context.
- DeleteDataQualityJobDefinition ( array $params = [] )
- Deletes a data quality monitoring job definition.
- DeleteDeviceFleet ( array $params = [] )
- Deletes a fleet.
- DeleteDomain ( array $params = [] )
- Used to delete a domain.
- DeleteEdgeDeploymentPlan ( array $params = [] )
- Deletes an edge deployment plan if (and only if) all the stages in the plan are inactive or there are no stages in the plan.
- DeleteEdgeDeploymentStage ( array $params = [] )
- Delete a stage in an edge deployment plan if (and only if) the stage is inactive.
- DeleteEndpoint ( array $params = [] )
- Deletes an endpoint.
- DeleteEndpointConfig ( array $params = [] )
- Deletes an endpoint configuration.
- DeleteExperiment ( array $params = [] )
- Deletes an SageMaker experiment.
- DeleteFeatureGroup ( array $params = [] )
- Delete the FeatureGroup and any data that was written to the OnlineStore of the FeatureGroup.
- DeleteFlowDefinition ( array $params = [] )
- Deletes the specified flow definition.
- DeleteHub ( array $params = [] )
- Delete a hub.
- DeleteHubContent ( array $params = [] )
- Delete the contents of a hub.
- DeleteHubContentReference ( array $params = [] )
- Delete a hub content reference in order to remove a model from a private hub.
- DeleteHumanTaskUi ( array $params = [] )
- Use this operation to delete a human task user interface (worker task template).
- DeleteHyperParameterTuningJob ( array $params = [] )
- Deletes a hyperparameter tuning job.
- DeleteImage ( array $params = [] )
- Deletes a SageMaker image and all versions of the image.
- DeleteImageVersion ( array $params = [] )
- Deletes a version of a SageMaker image.
- DeleteInferenceComponent ( array $params = [] )
- Deletes an inference component.
- DeleteInferenceExperiment ( array $params = [] )
- Deletes an inference experiment.
- DeleteMlflowTrackingServer ( array $params = [] )
- Deletes an MLflow Tracking Server.
- DeleteModel ( array $params = [] )
- Deletes a model.
- DeleteModelBiasJobDefinition ( array $params = [] )
- Deletes an Amazon SageMaker model bias job definition.
- DeleteModelCard ( array $params = [] )
- Deletes an Amazon SageMaker Model Card.
- DeleteModelExplainabilityJobDefinition ( array $params = [] )
- Deletes an Amazon SageMaker model explainability job definition.
- DeleteModelPackage ( array $params = [] )
- Deletes a model package.
- DeleteModelPackageGroup ( array $params = [] )
- Deletes the specified model group.
- DeleteModelPackageGroupPolicy ( array $params = [] )
- Deletes a model group resource policy.
- DeleteModelQualityJobDefinition ( array $params = [] )
- Deletes the secified model quality monitoring job definition.
- DeleteMonitoringSchedule ( array $params = [] )
- Deletes a monitoring schedule.
- DeleteNotebookInstance ( array $params = [] )
- Deletes an SageMaker notebook instance.
- DeleteNotebookInstanceLifecycleConfig ( array $params = [] )
- Deletes a notebook instance lifecycle configuration.
- DeleteOptimizationJob ( array $params = [] )
- Deletes an optimization job.
- DeletePipeline ( array $params = [] )
- Deletes a pipeline if there are no running instances of the pipeline.
- DeleteProject ( array $params = [] )
- Delete the specified project.
- DeleteSpace ( array $params = [] )
- Used to delete a space.
- DeleteStudioLifecycleConfig ( array $params = [] )
- Deletes the Amazon SageMaker Studio Lifecycle Configuration.
- DeleteTags ( array $params = [] )
- Deletes the specified tags from an SageMaker resource.
- DeleteTrial ( array $params = [] )
- Deletes the specified trial.
- DeleteTrialComponent ( array $params = [] )
- Deletes the specified trial component.
- DeleteUserProfile ( array $params = [] )
- Deletes a user profile.
- DeleteWorkforce ( array $params = [] )
- Use this operation to delete a workforce.
- DeleteWorkteam ( array $params = [] )
- Deletes an existing work team.
- DeregisterDevices ( array $params = [] )
- Deregisters the specified devices.
- DescribeAction ( array $params = [] )
- Describes an action.
- DescribeAlgorithm ( array $params = [] )
- Returns a description of the specified algorithm that is in your account.
- DescribeApp ( array $params = [] )
- Describes the app.
- DescribeAppImageConfig ( array $params = [] )
- Describes an AppImageConfig.
- DescribeArtifact ( array $params = [] )
- Describes an artifact.
- DescribeAutoMLJob ( array $params = [] )
- Returns information about an AutoML job created by calling CreateAutoMLJob.
- DescribeAutoMLJobV2 ( array $params = [] )
- Returns information about an AutoML job created by calling CreateAutoMLJobV2 or CreateAutoMLJob.
- DescribeCluster ( array $params = [] )
- Retrieves information of a SageMaker HyperPod cluster.
- DescribeClusterNode ( array $params = [] )
- Retrieves information of a node (also called a instance interchangeably) of a SageMaker HyperPod cluster.
- DescribeCodeRepository ( array $params = [] )
- Gets details about the specified Git repository.
- DescribeCompilationJob ( array $params = [] )
- Returns information about a model compilation job.
- DescribeContext ( array $params = [] )
- Describes a context.
- DescribeDataQualityJobDefinition ( array $params = [] )
- Gets the details of a data quality monitoring job definition.
- DescribeDevice ( array $params = [] )
- Describes the device.
- DescribeDeviceFleet ( array $params = [] )
- A description of the fleet the device belongs to.
- DescribeDomain ( array $params = [] )
- The description of the domain.
- DescribeEdgeDeploymentPlan ( array $params = [] )
- Describes an edge deployment plan with deployment status per stage.
- DescribeEdgePackagingJob ( array $params = [] )
- A description of edge packaging jobs.
- DescribeEndpoint ( array $params = [] )
- Returns the description of an endpoint.
- DescribeEndpointConfig ( array $params = [] )
- Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
- DescribeExperiment ( array $params = [] )
- Provides a list of an experiment's properties.
- DescribeFeatureGroup ( array $params = [] )
- Use this operation to describe a FeatureGroup.
- DescribeFeatureMetadata ( array $params = [] )
- Shows the metadata for a feature within a feature group.
- DescribeFlowDefinition ( array $params = [] )
- Returns information about the specified flow definition.
- DescribeHub ( array $params = [] )
- Describes a hub.
- DescribeHubContent ( array $params = [] )
- Describe the content of a hub.
- DescribeHumanTaskUi ( array $params = [] )
- Returns information about the requested human task user interface (worker task template).
- DescribeHyperParameterTuningJob ( array $params = [] )
- Returns a description of a hyperparameter tuning job, depending on the fields selected.
- DescribeImage ( array $params = [] )
- Describes a SageMaker image.
- DescribeImageVersion ( array $params = [] )
- Describes a version of a SageMaker image.
- DescribeInferenceComponent ( array $params = [] )
- Returns information about an inference component.
- DescribeInferenceExperiment ( array $params = [] )
- Returns details about an inference experiment.
- DescribeInferenceRecommendationsJob ( array $params = [] )
- Provides the results of the Inference Recommender job.
- DescribeLabelingJob ( array $params = [] )
- Gets information about a labeling job.
- DescribeLineageGroup ( array $params = [] )
- Provides a list of properties for the requested lineage group.
- DescribeMlflowTrackingServer ( array $params = [] )
- Returns information about an MLflow Tracking Server.
- DescribeModel ( array $params = [] )
- Describes a model that you created using the CreateModel API.
- DescribeModelBiasJobDefinition ( array $params = [] )
- Returns a description of a model bias job definition.
- DescribeModelCard ( array $params = [] )
- Describes the content, creation time, and security configuration of an Amazon SageMaker Model Card.
- DescribeModelCardExportJob ( array $params = [] )
- Describes an Amazon SageMaker Model Card export job.
- DescribeModelExplainabilityJobDefinition ( array $params = [] )
- Returns a description of a model explainability job definition.
- DescribeModelPackage ( array $params = [] )
- Returns a description of the specified model package, which is used to create SageMaker models or list them on Amazon Web Services Marketplace.
- DescribeModelPackageGroup ( array $params = [] )
- Gets a description for the specified model group.
- DescribeModelQualityJobDefinition ( array $params = [] )
- Returns a description of a model quality job definition.
- DescribeMonitoringSchedule ( array $params = [] )
- Describes the schedule for a monitoring job.
- DescribeNotebookInstance ( array $params = [] )
- Returns information about a notebook instance.
- DescribeNotebookInstanceLifecycleConfig ( array $params = [] )
- Returns a description of a notebook instance lifecycle configuration.
- DescribeOptimizationJob ( array $params = [] )
- Provides the properties of the specified optimization job.
- DescribePipeline ( array $params = [] )
- Describes the details of a pipeline.
- DescribePipelineDefinitionForExecution ( array $params = [] )
- Describes the details of an execution's pipeline definition.
- DescribePipelineExecution ( array $params = [] )
- Describes the details of a pipeline execution.
- DescribeProcessingJob ( array $params = [] )
- Returns a description of a processing job.
- DescribeProject ( array $params = [] )
- Describes the details of a project.
- DescribeSpace ( array $params = [] )
- Describes the space.
- DescribeStudioLifecycleConfig ( array $params = [] )
- Describes the Amazon SageMaker Studio Lifecycle Configuration.
- DescribeSubscribedWorkteam ( array $params = [] )
- Gets information about a work team provided by a vendor.
- DescribeTrainingJob ( array $params = [] )
- Returns information about a training job.
- DescribeTransformJob ( array $params = [] )
- Returns information about a transform job.
- DescribeTrial ( array $params = [] )
- Provides a list of a trial's properties.
- DescribeTrialComponent ( array $params = [] )
- Provides a list of a trials component's properties.
- DescribeUserProfile ( array $params = [] )
- Describes a user profile.
- DescribeWorkforce ( array $params = [] )
- Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs).
- DescribeWorkteam ( array $params = [] )
- Gets information about a specific work team.
- DisableSagemakerServicecatalogPortfolio ( array $params = [] )
- Disables using Service Catalog in SageMaker.
- DisassociateTrialComponent ( array $params = [] )
- Disassociates a trial component from a trial.
- EnableSagemakerServicecatalogPortfolio ( array $params = [] )
- Enables using Service Catalog in SageMaker.
- GetDeviceFleetReport ( array $params = [] )
- Describes a fleet.
- GetLineageGroupPolicy ( array $params = [] )
- The resource policy for the lineage group.
- GetModelPackageGroupPolicy ( array $params = [] )
- Gets a resource policy that manages access for a model group.
- GetSagemakerServicecatalogPortfolioStatus ( array $params = [] )
- Gets the status of Service Catalog in SageMaker.
- GetScalingConfigurationRecommendation ( array $params = [] )
- Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job.
- GetSearchSuggestions ( array $params = [] )
- An auto-complete API for the search functionality in the SageMaker console.
- ImportHubContent ( array $params = [] )
- Import hub content.
- ListActions ( array $params = [] )
- Lists the actions in your account and their properties.
- ListAlgorithms ( array $params = [] )
- Lists the machine learning algorithms that have been created.
- ListAliases ( array $params = [] )
- Lists the aliases of a specified image or image version.
- ListAppImageConfigs ( array $params = [] )
- Lists the AppImageConfigs in your account and their properties.
- ListApps ( array $params = [] )
- Lists apps.
- ListArtifacts ( array $params = [] )
- Lists the artifacts in your account and their properties.
- ListAssociations ( array $params = [] )
- Lists the associations in your account and their properties.
- ListAutoMLJobs ( array $params = [] )
- Request a list of jobs.
- ListCandidatesForAutoMLJob ( array $params = [] )
- List the candidates created for the job.
- ListClusterNodes ( array $params = [] )
- Retrieves the list of instances (also called nodes interchangeably) in a SageMaker HyperPod cluster.
- ListClusters ( array $params = [] )
- Retrieves the list of SageMaker HyperPod clusters.
- ListCodeRepositories ( array $params = [] )
- Gets a list of the Git repositories in your account.
- ListCompilationJobs ( array $params = [] )
- Lists model compilation jobs that satisfy various filters.
- ListContexts ( array $params = [] )
- Lists the contexts in your account and their properties.
- ListDataQualityJobDefinitions ( array $params = [] )
- Lists the data quality job definitions in your account.
- ListDeviceFleets ( array $params = [] )
- Returns a list of devices in the fleet.
- ListDevices ( array $params = [] )
- A list of devices.
- ListDomains ( array $params = [] )
- Lists the domains.
- ListEdgeDeploymentPlans ( array $params = [] )
- Lists all edge deployment plans.
- ListEdgePackagingJobs ( array $params = [] )
- Returns a list of edge packaging jobs.
- ListEndpointConfigs ( array $params = [] )
- Lists endpoint configurations.
- ListEndpoints ( array $params = [] )
- Lists endpoints.
- ListExperiments ( array $params = [] )
- Lists all the experiments in your account.
- ListFeatureGroups ( array $params = [] )
- List FeatureGroups based on given filter and order.
- ListFlowDefinitions ( array $params = [] )
- Returns information about the flow definitions in your account.
- ListHubContentVersions ( array $params = [] )
- List hub content versions.
- ListHubContents ( array $params = [] )
- List the contents of a hub.
- ListHubs ( array $params = [] )
- List all existing hubs.
- ListHumanTaskUis ( array $params = [] )
- Returns information about the human task user interfaces in your account.
- ListHyperParameterTuningJobs ( array $params = [] )
- Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.
- ListImageVersions ( array $params = [] )
- Lists the versions of a specified image and their properties.
- ListImages ( array $params = [] )
- Lists the images in your account and their properties.
- ListInferenceComponents ( array $params = [] )
- Lists the inference components in your account and their properties.
- ListInferenceExperiments ( array $params = [] )
- Returns the list of all inference experiments.
- ListInferenceRecommendationsJobSteps ( array $params = [] )
- Returns a list of the subtasks for an Inference Recommender job.
- ListInferenceRecommendationsJobs ( array $params = [] )
- Lists recommendation jobs that satisfy various filters.
- ListLabelingJobs ( array $params = [] )
- Gets a list of labeling jobs.
- ListLabelingJobsForWorkteam ( array $params = [] )
- Gets a list of labeling jobs assigned to a specified work team.
- ListLineageGroups ( array $params = [] )
- A list of lineage groups shared with your Amazon Web Services account.
- ListMlflowTrackingServers ( array $params = [] )
- Lists all MLflow Tracking Servers.
- ListModelBiasJobDefinitions ( array $params = [] )
- Lists model bias jobs definitions that satisfy various filters.
- ListModelCardExportJobs ( array $params = [] )
- List the export jobs for the Amazon SageMaker Model Card.
- ListModelCardVersions ( array $params = [] )
- List existing versions of an Amazon SageMaker Model Card.
- ListModelCards ( array $params = [] )
- List existing model cards.
- ListModelExplainabilityJobDefinitions ( array $params = [] )
- Lists model explainability job definitions that satisfy various filters.
- ListModelMetadata ( array $params = [] )
- Lists the domain, framework, task, and model name of standard machine learning models found in common model zoos.
- ListModelPackageGroups ( array $params = [] )
- Gets a list of the model groups in your Amazon Web Services account.
- ListModelPackages ( array $params = [] )
- Lists the model packages that have been created.
- ListModelQualityJobDefinitions ( array $params = [] )
- Gets a list of model quality monitoring job definitions in your account.
- ListModels ( array $params = [] )
- Lists models created with the CreateModel API.
- ListMonitoringAlertHistory ( array $params = [] )
- Gets a list of past alerts in a model monitoring schedule.
- ListMonitoringAlerts ( array $params = [] )
- Gets the alerts for a single monitoring schedule.
- ListMonitoringExecutions ( array $params = [] )
- Returns list of all monitoring job executions.
- ListMonitoringSchedules ( array $params = [] )
- Returns list of all monitoring schedules.
- ListNotebookInstanceLifecycleConfigs ( array $params = [] )
- Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API.
- ListNotebookInstances ( array $params = [] )
- Returns a list of the SageMaker notebook instances in the requester's account in an Amazon Web Services Region.
- ListOptimizationJobs ( array $params = [] )
- Lists the optimization jobs in your account and their properties.
- ListPipelineExecutionSteps ( array $params = [] )
- Gets a list of PipeLineExecutionStep objects.
- ListPipelineExecutions ( array $params = [] )
- Gets a list of the pipeline executions.
- ListPipelineParametersForExecution ( array $params = [] )
- Gets a list of parameters for a pipeline execution.
- ListPipelines ( array $params = [] )
- Gets a list of pipelines.
- ListProcessingJobs ( array $params = [] )
- Lists processing jobs that satisfy various filters.
- ListProjects ( array $params = [] )
- Gets a list of the projects in an Amazon Web Services account.
- ListResourceCatalogs ( array $params = [] )
- Lists Amazon SageMaker Catalogs based on given filters and orders.
- ListSpaces ( array $params = [] )
- Lists spaces.
- ListStageDevices ( array $params = [] )
- Lists devices allocated to the stage, containing detailed device information and deployment status.
- ListStudioLifecycleConfigs ( array $params = [] )
- Lists the Amazon SageMaker Studio Lifecycle Configurations in your Amazon Web Services Account.
- ListSubscribedWorkteams ( array $params = [] )
- Gets a list of the work teams that you are subscribed to in the Amazon Web Services Marketplace.
- ListTags ( array $params = [] )
- Returns the tags for the specified SageMaker resource.
- ListTrainingJobs ( array $params = [] )
- Lists training jobs.
- ListTrainingJobsForHyperParameterTuningJob ( array $params = [] )
- Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.
- ListTransformJobs ( array $params = [] )
- Lists transform jobs.
- ListTrialComponents ( array $params = [] )
- Lists the trial components in your account.
- ListTrials ( array $params = [] )
- Lists the trials in your account.
- ListUserProfiles ( array $params = [] )
- Lists user profiles.
- ListWorkforces ( array $params = [] )
- Use this operation to list all private and vendor workforces in an Amazon Web Services Region.
- ListWorkteams ( array $params = [] )
- Gets a list of private work teams that you have defined in a region.
- PutModelPackageGroupPolicy ( array $params = [] )
- Adds a resouce policy to control access to a model group.
- QueryLineage ( array $params = [] )
- Use this action to inspect your lineage and discover relationships between entities.
- RegisterDevices ( array $params = [] )
- Register devices.
- RenderUiTemplate ( array $params = [] )
- Renders the UI template so that you can preview the worker's experience.
- RetryPipelineExecution ( array $params = [] )
- Retry the execution of the pipeline.
- Search ( array $params = [] )
- Finds SageMaker resources that match a search query.
- SendPipelineExecutionStepFailure ( array $params = [] )
- Notifies the pipeline that the execution of a callback step failed, along with a message describing why.
- SendPipelineExecutionStepSuccess ( array $params = [] )
- Notifies the pipeline that the execution of a callback step succeeded and provides a list of the step's output parameters.
- StartEdgeDeploymentStage ( array $params = [] )
- Starts a stage in an edge deployment plan.
- StartInferenceExperiment ( array $params = [] )
- Starts an inference experiment.
- StartMlflowTrackingServer ( array $params = [] )
- Programmatically start an MLflow Tracking Server.
- StartMonitoringSchedule ( array $params = [] )
- Starts a previously stopped monitoring schedule.
- StartNotebookInstance ( array $params = [] )
- Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume.
- StartPipelineExecution ( array $params = [] )
- Starts a pipeline execution.
- StopAutoMLJob ( array $params = [] )
- A method for forcing a running job to shut down.
- StopCompilationJob ( array $params = [] )
- Stops a model compilation job.
- StopEdgeDeploymentStage ( array $params = [] )
- Stops a stage in an edge deployment plan.
- StopEdgePackagingJob ( array $params = [] )
- Request to stop an edge packaging job.
- StopHyperParameterTuningJob ( array $params = [] )
- Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.
- StopInferenceExperiment ( array $params = [] )
- Stops an inference experiment.
- StopInferenceRecommendationsJob ( array $params = [] )
- Stops an Inference Recommender job.
- StopLabelingJob ( array $params = [] )
- Stops a running labeling job.
- StopMlflowTrackingServer ( array $params = [] )
- Programmatically stop an MLflow Tracking Server.
- StopMonitoringSchedule ( array $params = [] )
- Stops a previously started monitoring schedule.
- StopNotebookInstance ( array $params = [] )
- Terminates the ML compute instance.
- StopOptimizationJob ( array $params = [] )
- Ends a running inference optimization job.
- StopPipelineExecution ( array $params = [] )
- Stops a pipeline execution.
- StopProcessingJob ( array $params = [] )
- Stops a processing job.
- StopTrainingJob ( array $params = [] )
- Stops a training job.
- StopTransformJob ( array $params = [] )
- Stops a batch transform job.
- UpdateAction ( array $params = [] )
- Updates an action.
- UpdateAppImageConfig ( array $params = [] )
- Updates the properties of an AppImageConfig.
- UpdateArtifact ( array $params = [] )
- Updates an artifact.
- UpdateCluster ( array $params = [] )
- Updates a SageMaker HyperPod cluster.
- UpdateClusterSoftware ( array $params = [] )
- Updates the platform software of a SageMaker HyperPod cluster for security patching.
- UpdateCodeRepository ( array $params = [] )
- Updates the specified Git repository with the specified values.
- UpdateContext ( array $params = [] )
- Updates a context.
- UpdateDeviceFleet ( array $params = [] )
- Updates a fleet of devices.
- UpdateDevices ( array $params = [] )
- Updates one or more devices in a fleet.
- UpdateDomain ( array $params = [] )
- Updates the default settings for new user profiles in the domain.
- UpdateEndpoint ( array $params = [] )
- Deploys the EndpointConfig specified in the request to a new fleet of instances.
- UpdateEndpointWeightsAndCapacities ( array $params = [] )
- Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint.
- UpdateExperiment ( array $params = [] )
- Adds, updates, or removes the description of an experiment.
- UpdateFeatureGroup ( array $params = [] )
- Updates the feature group by either adding features or updating the online store configuration.
- UpdateFeatureMetadata ( array $params = [] )
- Updates the description and parameters of the feature group.
- UpdateHub ( array $params = [] )
- Update a hub.
- UpdateImage ( array $params = [] )
- Updates the properties of a SageMaker image.
- UpdateImageVersion ( array $params = [] )
- Updates the properties of a SageMaker image version.
- UpdateInferenceComponent ( array $params = [] )
- Updates an inference component.
- UpdateInferenceComponentRuntimeConfig ( array $params = [] )
- Runtime settings for a model that is deployed with an inference component.
- UpdateInferenceExperiment ( array $params = [] )
- Updates an inference experiment that you created.
- UpdateMlflowTrackingServer ( array $params = [] )
- Updates properties of an existing MLflow Tracking Server.
- UpdateModelCard ( array $params = [] )
- Update an Amazon SageMaker Model Card.
- UpdateModelPackage ( array $params = [] )
- Updates a versioned model.
- UpdateMonitoringAlert ( array $params = [] )
- Update the parameters of a model monitor alert.
- UpdateMonitoringSchedule ( array $params = [] )
- Updates a previously created schedule.
- UpdateNotebookInstance ( array $params = [] )
- Updates a notebook instance.
- UpdateNotebookInstanceLifecycleConfig ( array $params = [] )
- Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API.
- UpdatePipeline ( array $params = [] )
- Updates a pipeline.
- UpdatePipelineExecution ( array $params = [] )
- Updates a pipeline execution.
- UpdateProject ( array $params = [] )
- Updates a machine learning (ML) project that is created from a template that sets up an ML pipeline from training to deploying an approved model.
- UpdateSpace ( array $params = [] )
- Updates the settings of a space.
- UpdateTrainingJob ( array $params = [] )
- Update a model training job to request a new Debugger profiling configuration or to change warm pool retention length.
- UpdateTrial ( array $params = [] )
- Updates the display name of a trial.
- UpdateTrialComponent ( array $params = [] )
- Updates one or more properties of a trial component.
- UpdateUserProfile ( array $params = [] )
- Updates a user profile.
- UpdateWorkforce ( array $params = [] )
- Use this operation to update your workforce.
- UpdateWorkteam ( array $params = [] )
- Updates an existing work team with new member definitions or description.
Paginators
Paginators handle automatically iterating over paginated API results. Paginators are associated with specific API operations, and they accept the parameters that the corresponding API operation accepts. You can get a paginator from a client class using getPaginator($paginatorName, $operationParameters). This client supports the following paginators:
- ListActions
- ListAlgorithms
- ListAliases
- ListAppImageConfigs
- ListApps
- ListArtifacts
- ListAssociations
- ListAutoMLJobs
- ListCandidatesForAutoMLJob
- ListClusterNodes
- ListClusters
- ListCodeRepositories
- ListCompilationJobs
- ListContexts
- ListDataQualityJobDefinitions
- ListDeviceFleets
- ListDevices
- ListDomains
- ListEdgeDeploymentPlans
- ListEdgePackagingJobs
- ListEndpointConfigs
- ListEndpoints
- ListExperiments
- ListFeatureGroups
- ListFlowDefinitions
- ListHumanTaskUis
- ListHyperParameterTuningJobs
- ListImageVersions
- ListImages
- ListInferenceComponents
- ListInferenceExperiments
- ListInferenceRecommendationsJobSteps
- ListInferenceRecommendationsJobs
- ListLabelingJobs
- ListLabelingJobsForWorkteam
- ListLineageGroups
- ListMlflowTrackingServers
- ListModelBiasJobDefinitions
- ListModelCardExportJobs
- ListModelCardVersions
- ListModelCards
- ListModelExplainabilityJobDefinitions
- ListModelMetadata
- ListModelPackageGroups
- ListModelPackages
- ListModelQualityJobDefinitions
- ListModels
- ListMonitoringAlertHistory
- ListMonitoringAlerts
- ListMonitoringExecutions
- ListMonitoringSchedules
- ListNotebookInstanceLifecycleConfigs
- ListNotebookInstances
- ListOptimizationJobs
- ListPipelineExecutionSteps
- ListPipelineExecutions
- ListPipelineParametersForExecution
- ListPipelines
- ListProcessingJobs
- ListProjects
- ListResourceCatalogs
- ListSpaces
- ListStageDevices
- ListStudioLifecycleConfigs
- ListSubscribedWorkteams
- ListTags
- ListTrainingJobs
- ListTrainingJobsForHyperParameterTuningJob
- ListTransformJobs
- ListTrialComponents
- ListTrials
- ListUserProfiles
- ListWorkforces
- ListWorkteams
- QueryLineage
- Search
Waiters
Waiters allow you to poll a resource until it enters into a desired state. A waiter has a name used to describe what it does, and is associated with an API operation. When creating a waiter, you can provide the API operation parameters associated with the corresponding operation. Waiters can be accessed using the getWaiter($waiterName, $operationParameters) method of a client object. This client supports the following waiters:
Waiter name | API Operation | Delay | Max Attempts |
---|---|---|---|
NotebookInstanceInService | DescribeNotebookInstance | 30 | 60 |
NotebookInstanceStopped | DescribeNotebookInstance | 30 | 60 |
NotebookInstanceDeleted | DescribeNotebookInstance | 30 | 60 |
TrainingJobCompletedOrStopped | DescribeTrainingJob | 120 | 180 |
EndpointInService | DescribeEndpoint | 30 | 120 |
EndpointDeleted | DescribeEndpoint | 30 | 60 |
TransformJobCompletedOrStopped | DescribeTransformJob | 60 | 60 |
ProcessingJobCompletedOrStopped | DescribeProcessingJob | 60 | 60 |
ImageCreated | DescribeImage | 60 | 60 |
ImageUpdated | DescribeImage | 60 | 60 |
ImageDeleted | DescribeImage | 60 | 60 |
ImageVersionCreated | DescribeImageVersion | 60 | 60 |
ImageVersionDeleted | DescribeImageVersion | 60 | 60 |
Operations
AddAssociation
$result = $client->addAssociation
([/* ... */]); $promise = $client->addAssociationAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->addAssociation([ 'AssociationType' => 'ContributedTo|AssociatedWith|DerivedFrom|Produced|SameAs', 'DestinationArn' => '<string>', // REQUIRED 'SourceArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
- AssociationType
-
- Type: 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.
- DestinationArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the destination.
- SourceArn
-
- Required: Yes
- Type: string
The ARN of the source.
Result Syntax
[ 'DestinationArn' => '<string>', 'SourceArn' => '<string>', ]
Result Details
Members
- DestinationArn
-
- Type: string
The Amazon Resource Name (ARN) of the destination.
- SourceArn
-
- Type: string
The ARN of the source.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
AddTags
$result = $client->addTags
([/* ... */]); $promise = $client->addTagsAsync
([/* ... */]);
Adds or overwrites one or more tags for the specified 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 Amazon Web Services 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
Tags that you add to a SageMaker Domain or User Profile by calling this API are also added to any Apps that the Domain or User Profile launches after you call this API, but not to Apps that the Domain or User Profile launched before you called this API. To make sure that the tags associated with a Domain or User Profile are also added to all Apps that the Domain or User Profile launches, add the tags when you first create the Domain or User Profile by specifying them in the Tags
parameter of CreateDomain or CreateUserProfile.
Parameter Syntax
$result = $client->addTags([ 'ResourceArn' => '<string>', // REQUIRED 'Tags' => [ // REQUIRED [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- ResourceArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the resource that you want to tag.
- Tags
-
- Required: Yes
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Result Syntax
[ 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ]
Result Details
Members
- Tags
-
- Type: Array of Tag structures
A list of tags associated with the SageMaker resource.
Errors
There are no errors described for this operation.
AssociateTrialComponent
$result = $client->associateTrialComponent
([/* ... */]); $promise = $client->associateTrialComponentAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->associateTrialComponent([ 'TrialComponentName' => '<string>', // REQUIRED 'TrialName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TrialComponentName
-
- Required: Yes
- Type: string
The name of the component to associated with the trial.
- TrialName
-
- Required: Yes
- Type: string
The name of the trial to associate with.
Result Syntax
[ 'TrialArn' => '<string>', 'TrialComponentArn' => '<string>', ]
Result Details
Members
- TrialArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial.
- TrialComponentArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial component.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
BatchDescribeModelPackage
$result = $client->batchDescribeModelPackage
([/* ... */]); $promise = $client->batchDescribeModelPackageAsync
([/* ... */]);
This action batch describes a list of versioned model packages
Parameter Syntax
$result = $client->batchDescribeModelPackage([ 'ModelPackageArnList' => ['<string>', ...], // REQUIRED ]);
Parameter Details
Members
- ModelPackageArnList
-
- Required: Yes
- Type: Array of strings
The list of Amazon Resource Name (ARN) of the model package groups.
Result Syntax
[ 'BatchDescribeModelPackageErrorMap' => [ '<ModelPackageArn>' => [ 'ErrorCode' => '<string>', 'ErrorResponse' => '<string>', ], // ... ], 'ModelPackageSummaries' => [ '<ModelPackageArn>' => [ 'CreationTime' => <DateTime>, 'InferenceSpecification' => [ 'Containers' => [ [ 'AdditionalS3DataSource' => [ 'CompressionType' => 'None|Gzip', 'S3DataType' => 'S3Object|S3Prefix', 'S3Uri' => '<string>', ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'Image' => '<string>', 'ImageDigest' => '<string>', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], 'ModelDataUrl' => '<string>', 'ModelInput' => [ 'DataInputConfig' => '<string>', ], 'NearestModelName' => '<string>', 'ProductId' => '<string>', ], // ... ], 'SupportedContentTypes' => ['<string>', ...], 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'SupportedTransformInstanceTypes' => ['<string>', ...], ], 'ModelApprovalStatus' => 'Approved|Rejected|PendingManualApproval', 'ModelPackageArn' => '<string>', 'ModelPackageDescription' => '<string>', 'ModelPackageGroupName' => '<string>', 'ModelPackageStatus' => 'Pending|InProgress|Completed|Failed|Deleting', 'ModelPackageVersion' => <integer>, ], // ... ], ]
Result Details
Members
- BatchDescribeModelPackageErrorMap
-
- Type: Associative array of custom strings keys (ModelPackageArn) to BatchDescribeModelPackageError structures
A map of the resource and BatchDescribeModelPackageError objects reporting the error associated with describing the model package.
- ModelPackageSummaries
-
- Type: Associative array of custom strings keys (ModelPackageArn) to BatchDescribeModelPackageSummary structures
The summaries for the model package versions
Errors
There are no errors described for this operation.
CreateAction
$result = $client->createAction
([/* ... */]); $promise = $client->createActionAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->createAction([ 'ActionName' => '<string>', // REQUIRED 'ActionType' => '<string>', // REQUIRED 'Description' => '<string>', 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'Properties' => ['<string>', ...], 'Source' => [ // REQUIRED 'SourceId' => '<string>', 'SourceType' => '<string>', 'SourceUri' => '<string>', // REQUIRED ], 'Status' => 'Unknown|InProgress|Completed|Failed|Stopping|Stopped', 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- ActionName
-
- Required: Yes
- Type: string
The name of the action. Must be unique to your account in an Amazon Web Services Region.
- ActionType
-
- Required: Yes
- Type: string
The action type.
- Description
-
- Type: string
The description of the action.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- Properties
-
- Type: Associative array of custom strings keys (StringParameterValue) to strings
A list of properties to add to the action.
- Source
-
- Required: Yes
- Type: ActionSource structure
The source type, ID, and URI.
- Status
-
- Type: string
The status of the action.
- Tags
-
- Type: Array of Tag structures
A list of tags to apply to the action.
Result Syntax
[ 'ActionArn' => '<string>', ]
Result Details
Members
- ActionArn
-
- Type: string
The Amazon Resource Name (ARN) of the action.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateAlgorithm
$result = $client->createAlgorithm
([/* ... */]); $promise = $client->createAlgorithmAsync
([/* ... */]);
Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace.
Parameter Syntax
$result = $client->createAlgorithm([ 'AlgorithmDescription' => '<string>', 'AlgorithmName' => '<string>', // REQUIRED 'CertifyForMarketplace' => true || false, 'InferenceSpecification' => [ 'Containers' => [ // REQUIRED [ 'AdditionalS3DataSource' => [ 'CompressionType' => 'None|Gzip', 'S3DataType' => 'S3Object|S3Prefix', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'Image' => '<string>', // REQUIRED 'ImageDigest' => '<string>', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', // REQUIRED 'HubAccessConfig' => [ 'HubContentArn' => '<string>', // REQUIRED ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, // REQUIRED ], 'S3DataType' => 'S3Prefix|S3Object', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'ModelDataUrl' => '<string>', 'ModelInput' => [ 'DataInputConfig' => '<string>', // REQUIRED ], 'NearestModelName' => '<string>', 'ProductId' => '<string>', ], // ... ], 'SupportedContentTypes' => ['<string>', ...], 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'SupportedTransformInstanceTypes' => ['<string>', ...], ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'TrainingSpecification' => [ // REQUIRED 'AdditionalS3DataSource' => [ 'CompressionType' => 'None|Gzip', 'S3DataType' => 'S3Object|S3Prefix', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'MetricDefinitions' => [ [ 'Name' => '<string>', // REQUIRED 'Regex' => '<string>', // REQUIRED ], // ... ], 'SupportedHyperParameters' => [ [ 'DefaultValue' => '<string>', 'Description' => '<string>', 'IsRequired' => true || false, 'IsTunable' => true || false, 'Name' => '<string>', // REQUIRED 'Range' => [ 'CategoricalParameterRangeSpecification' => [ 'Values' => ['<string>', ...], // REQUIRED ], 'ContinuousParameterRangeSpecification' => [ 'MaxValue' => '<string>', // REQUIRED 'MinValue' => '<string>', // REQUIRED ], 'IntegerParameterRangeSpecification' => [ 'MaxValue' => '<string>', // REQUIRED 'MinValue' => '<string>', // REQUIRED ], ], 'Type' => 'Integer|Continuous|Categorical|FreeText', // REQUIRED ], // ... ], 'SupportedTrainingInstanceTypes' => ['<string>', ...], // REQUIRED 'SupportedTuningJobObjectiveMetrics' => [ [ 'MetricName' => '<string>', // REQUIRED 'Type' => 'Maximize|Minimize', // REQUIRED ], // ... ], 'SupportsDistributedTraining' => true || false, 'TrainingChannels' => [ // REQUIRED [ 'Description' => '<string>', 'IsRequired' => true || false, 'Name' => '<string>', // REQUIRED 'SupportedCompressionTypes' => ['<string>', ...], 'SupportedContentTypes' => ['<string>', ...], // REQUIRED 'SupportedInputModes' => ['<string>', ...], // REQUIRED ], // ... ], 'TrainingImage' => '<string>', // REQUIRED 'TrainingImageDigest' => '<string>', ], 'ValidationSpecification' => [ 'ValidationProfiles' => [ // REQUIRED [ 'ProfileName' => '<string>', // REQUIRED 'TrainingJobDefinition' => [ // REQUIRED 'HyperParameters' => ['<string>', ...], 'InputDataConfig' => [ // REQUIRED [ 'ChannelName' => '<string>', // REQUIRED 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ // REQUIRED 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', // REQUIRED 'FileSystemAccessMode' => 'rw|ro', // REQUIRED 'FileSystemId' => '<string>', // REQUIRED 'FileSystemType' => 'EFS|FSxLustre', // REQUIRED ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'InstanceGroupNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'InputMode' => 'Pipe|File|FastFile', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, // REQUIRED ], ], // ... ], 'OutputDataConfig' => [ // REQUIRED 'CompressionType' => 'GZIP|NONE', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'ResourceConfig' => [ // REQUIRED 'InstanceCount' => <integer>, 'InstanceGroups' => [ [ 'InstanceCount' => <integer>, // REQUIRED 'InstanceGroupName' => '<string>', // REQUIRED 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', // REQUIRED ], // ... ], 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'KeepAlivePeriodInSeconds' => <integer>, 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], 'StoppingCondition' => [ // REQUIRED 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TrainingInputMode' => 'Pipe|File|FastFile', // REQUIRED ], 'TransformJobDefinition' => [ 'BatchStrategy' => 'MultiRecord|SingleRecord', 'Environment' => ['<string>', ...], 'MaxConcurrentTransforms' => <integer>, 'MaxPayloadInMB' => <integer>, 'TransformInput' => [ // REQUIRED 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ // REQUIRED 'S3DataSource' => [ // REQUIRED 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'SplitType' => 'None|Line|RecordIO|TFRecord', ], 'TransformOutput' => [ // REQUIRED 'Accept' => '<string>', 'AssembleWith' => 'None|Line', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'TransformResources' => [ // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge', // REQUIRED 'VolumeKmsKeyId' => '<string>', ], ], ], // ... ], 'ValidationRole' => '<string>', // REQUIRED ], ]);
Parameter Details
Members
- AlgorithmDescription
-
- Type: string
A description of the algorithm.
- AlgorithmName
-
- Required: Yes
- Type: string
The name of the algorithm.
- CertifyForMarketplace
-
- Type: boolean
Whether to certify the algorithm so that it can be listed in Amazon Web Services Marketplace.
- InferenceSpecification
-
- Type: InferenceSpecification structure
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.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
- TrainingSpecification
-
- Required: Yes
- Type: TrainingSpecification structure
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
, andtest
channels.
- ValidationSpecification
-
- Type: AlgorithmValidationSpecification structure
Specifies configurations for one or more training jobs and that SageMaker runs to test the algorithm's training code and, optionally, one or more batch transform jobs that SageMaker runs to test the algorithm's inference code.
Result Syntax
[ 'AlgorithmArn' => '<string>', ]
Result Details
Members
- AlgorithmArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the new algorithm.
Errors
There are no errors described for this operation.
CreateApp
$result = $client->createApp
([/* ... */]); $promise = $client->createAppAsync
([/* ... */]);
Creates a running app for the specified UserProfile. This operation is automatically invoked by Amazon SageMaker upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.
Parameter Syntax
$result = $client->createApp([ 'AppName' => '<string>', // REQUIRED 'AppType' => 'JupyterServer|KernelGateway|DetailedProfiler|TensorBoard|CodeEditor|JupyterLab|RStudioServerPro|RSessionGateway|Canvas', // REQUIRED 'DomainId' => '<string>', // REQUIRED 'ResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'SpaceName' => '<string>', 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'UserProfileName' => '<string>', ]);
Parameter Details
Members
- AppName
-
- Required: Yes
- Type: string
The name of the app.
- AppType
-
- Required: Yes
- Type: string
The type of app.
- DomainId
-
- Required: Yes
- Type: string
The domain ID.
- ResourceSpec
-
- Type: ResourceSpec structure
The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
The value of
InstanceType
passed as part of theResourceSpec
in theCreateApp
call overrides the value passed as part of theResourceSpec
configured for the user profile or the domain. IfInstanceType
is not specified in any of those threeResourceSpec
values for aKernelGateway
app, theCreateApp
call fails with a request validation error. - SpaceName
-
- Type: string
The name of the space. If this value is not set, then
UserProfileName
must be set. - Tags
-
- Type: Array of Tag structures
Each tag consists of a key and an optional value. Tag keys must be unique per resource.
- UserProfileName
-
- Type: string
The user profile name. If this value is not set, then
SpaceName
must be set.
Result Syntax
[ 'AppArn' => '<string>', ]
Result Details
Members
- AppArn
-
- Type: string
The Amazon Resource Name (ARN) of the app.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
CreateAppImageConfig
$result = $client->createAppImageConfig
([/* ... */]); $promise = $client->createAppImageConfigAsync
([/* ... */]);
Creates a configuration for running a SageMaker image as a KernelGateway app. The configuration specifies the Amazon Elastic File System storage volume on the image, and a list of the kernels in the image.
Parameter Syntax
$result = $client->createAppImageConfig([ 'AppImageConfigName' => '<string>', // REQUIRED 'CodeEditorAppImageConfig' => [ 'ContainerConfig' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ContainerEnvironmentVariables' => ['<string>', ...], ], 'FileSystemConfig' => [ 'DefaultGid' => <integer>, 'DefaultUid' => <integer>, 'MountPath' => '<string>', ], ], 'JupyterLabAppImageConfig' => [ 'ContainerConfig' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ContainerEnvironmentVariables' => ['<string>', ...], ], 'FileSystemConfig' => [ 'DefaultGid' => <integer>, 'DefaultUid' => <integer>, 'MountPath' => '<string>', ], ], 'KernelGatewayImageConfig' => [ 'FileSystemConfig' => [ 'DefaultGid' => <integer>, 'DefaultUid' => <integer>, 'MountPath' => '<string>', ], 'KernelSpecs' => [ // REQUIRED [ 'DisplayName' => '<string>', 'Name' => '<string>', // REQUIRED ], // ... ], ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- AppImageConfigName
-
- Required: Yes
- Type: string
The name of the AppImageConfig. Must be unique to your account.
- CodeEditorAppImageConfig
-
- Type: CodeEditorAppImageConfig structure
The
CodeEditorAppImageConfig
. You can only specify one image kernel in the AppImageConfig API. This kernel is shown to users before the image starts. After the image runs, all kernels are visible in Code Editor. - JupyterLabAppImageConfig
-
- Type: JupyterLabAppImageConfig structure
The
JupyterLabAppImageConfig
. You can only specify one image kernel in theAppImageConfig
API. This kernel is shown to users before the image starts. After the image runs, all kernels are visible in JupyterLab. - KernelGatewayImageConfig
-
- Type: KernelGatewayImageConfig structure
The KernelGatewayImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel will be shown to users before the image starts. Once the image runs, all kernels are visible in JupyterLab.
- Tags
-
- Type: Array of Tag structures
A list of tags to apply to the AppImageConfig.
Result Syntax
[ 'AppImageConfigArn' => '<string>', ]
Result Details
Members
- AppImageConfigArn
-
- Type: string
The ARN of the AppImageConfig.
Errors
- ResourceInUse:
Resource being accessed is in use.
CreateArtifact
$result = $client->createArtifact
([/* ... */]); $promise = $client->createArtifactAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->createArtifact([ 'ArtifactName' => '<string>', 'ArtifactType' => '<string>', // REQUIRED 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'Properties' => ['<string>', ...], 'Source' => [ // REQUIRED 'SourceTypes' => [ [ 'SourceIdType' => 'MD5Hash|S3ETag|S3Version|Custom', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'SourceUri' => '<string>', // REQUIRED ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- ArtifactName
-
- Type: string
The name of the artifact. Must be unique to your account in an Amazon Web Services Region.
- ArtifactType
-
- Required: Yes
- Type: string
The artifact type.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- Properties
-
- Type: Associative array of custom strings keys (StringParameterValue) to strings
A list of properties to add to the artifact.
- Source
-
- Required: Yes
- Type: ArtifactSource structure
The ID, ID type, and URI of the source.
- Tags
-
- Type: Array of Tag structures
A list of tags to apply to the artifact.
Result Syntax
[ 'ArtifactArn' => '<string>', ]
Result Details
Members
- ArtifactArn
-
- Type: string
The Amazon Resource Name (ARN) of the artifact.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateAutoMLJob
$result = $client->createAutoMLJob
([/* ... */]); $promise = $client->createAutoMLJobAsync
([/* ... */]);
Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
An AutoML job in SageMaker is a fully automated process that allows you to build machine learning models with minimal effort and machine learning expertise. When initiating an AutoML job, you provide your data and optionally specify parameters tailored to your use case. SageMaker then automates the entire model development lifecycle, including data preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify and accelerate the model building process by automating various tasks and exploring different combinations of machine learning algorithms, data preprocessing techniques, and hyperparameter values. The output of an AutoML job comprises one or more trained models ready for deployment and inference. Additionally, SageMaker AutoML jobs generate a candidate model leaderboard, allowing you to select the best-performing model for deployment.
For more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html in the SageMaker developer guide.
We recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.
CreateAutoMLJobV2
can manage tabular problem types identical to those of its previous version CreateAutoMLJob
, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob
to CreateAutoMLJobV2
in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.
Parameter Syntax
$result = $client->createAutoMLJob([ 'AutoMLJobConfig' => [ 'CandidateGenerationConfig' => [ 'AlgorithmsConfig' => [ [ 'AutoMLAlgorithms' => ['<string>', ...], // REQUIRED ], // ... ], 'FeatureSpecificationS3Uri' => '<string>', ], 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'DataSplitConfig' => [ 'ValidationFraction' => <float>, ], 'Mode' => 'AUTO|ENSEMBLING|HYPERPARAMETER_TUNING', 'SecurityConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'VolumeKmsKeyId' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], ], 'AutoMLJobName' => '<string>', // REQUIRED 'AutoMLJobObjective' => [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', // REQUIRED ], 'GenerateCandidateDefinitionsOnly' => true || false, 'InputDataConfig' => [ // REQUIRED [ 'ChannelType' => 'training|validation', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'S3DataSource' => [ // REQUIRED 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'SampleWeightAttributeName' => '<string>', 'TargetAttributeName' => '<string>', // REQUIRED ], // ... ], 'ModelDeployConfig' => [ 'AutoGenerateEndpointName' => true || false, 'EndpointName' => '<string>', ], 'OutputDataConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'ProblemType' => 'BinaryClassification|MulticlassClassification|Regression', 'RoleArn' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- AutoMLJobConfig
-
- Type: AutoMLJobConfig structure
A collection of settings used to configure an AutoML job.
- AutoMLJobName
-
- Required: Yes
- Type: string
Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
- AutoMLJobObjective
-
- Type: AutoMLJobObjective structure
Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. See AutoMLJobObjective for the default values.
- GenerateCandidateDefinitionsOnly
-
- Type: boolean
Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
- InputDataConfig
-
- Required: Yes
- Type: Array of AutoMLChannel structures
An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to
InputDataConfig
supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset. - ModelDeployConfig
-
- Type: ModelDeployConfig structure
Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
- OutputDataConfig
-
- Required: Yes
- Type: AutoMLOutputDataConfig structure
Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.
- ProblemType
-
- Type: string
Defines the type of supervised learning problem available for the candidates. For more information, see SageMaker Autopilot problem types.
- RoleArn
-
- Required: Yes
- Type: string
The ARN of the role that is used to access the data.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
Result Syntax
[ 'AutoMLJobArn' => '<string>', ]
Result Details
Members
- AutoMLJobArn
-
- Required: Yes
- Type: string
The unique ARN assigned to the AutoML job when it is created.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateAutoMLJobV2
$result = $client->createAutoMLJobV2
([/* ... */]); $promise = $client->createAutoMLJobV2Async
([/* ... */]);
Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.
An AutoML job in SageMaker is a fully automated process that allows you to build machine learning models with minimal effort and machine learning expertise. When initiating an AutoML job, you provide your data and optionally specify parameters tailored to your use case. SageMaker then automates the entire model development lifecycle, including data preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify and accelerate the model building process by automating various tasks and exploring different combinations of machine learning algorithms, data preprocessing techniques, and hyperparameter values. The output of an AutoML job comprises one or more trained models ready for deployment and inference. Additionally, SageMaker AutoML jobs generate a candidate model leaderboard, allowing you to select the best-performing model for deployment.
For more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html in the SageMaker developer guide.
AutoML jobs V2 support various problem types such as regression, binary, and multiclass classification with tabular data, text and image classification, time-series forecasting, and fine-tuning of large language models (LLMs) for text generation.
CreateAutoMLJobV2 and DescribeAutoMLJobV2 are new versions of CreateAutoMLJob and DescribeAutoMLJob which offer backward compatibility.
CreateAutoMLJobV2
can manage tabular problem types identical to those of its previous version CreateAutoMLJob
, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob
to CreateAutoMLJobV2
in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
For the list of available problem types supported by CreateAutoMLJobV2
, see AutoMLProblemTypeConfig.
You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.
Parameter Syntax
$result = $client->createAutoMLJobV2([ 'AutoMLComputeConfig' => [ 'EmrServerlessComputeConfig' => [ 'ExecutionRoleARN' => '<string>', // REQUIRED ], ], 'AutoMLJobInputDataConfig' => [ // REQUIRED [ 'ChannelType' => 'training|validation', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'S3DataSource' => [ // REQUIRED 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], ], // ... ], 'AutoMLJobName' => '<string>', // REQUIRED 'AutoMLJobObjective' => [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', // REQUIRED ], 'AutoMLProblemTypeConfig' => [ // REQUIRED 'ImageClassificationJobConfig' => [ 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], ], 'TabularJobConfig' => [ 'CandidateGenerationConfig' => [ 'AlgorithmsConfig' => [ [ 'AutoMLAlgorithms' => ['<string>', ...], // REQUIRED ], // ... ], ], 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'FeatureSpecificationS3Uri' => '<string>', 'GenerateCandidateDefinitionsOnly' => true || false, 'Mode' => 'AUTO|ENSEMBLING|HYPERPARAMETER_TUNING', 'ProblemType' => 'BinaryClassification|MulticlassClassification|Regression', 'SampleWeightAttributeName' => '<string>', 'TargetAttributeName' => '<string>', // REQUIRED ], 'TextClassificationJobConfig' => [ 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'ContentColumn' => '<string>', // REQUIRED 'TargetLabelColumn' => '<string>', // REQUIRED ], 'TextGenerationJobConfig' => [ 'BaseModelName' => '<string>', 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, // REQUIRED ], 'TextGenerationHyperParameters' => ['<string>', ...], ], 'TimeSeriesForecastingJobConfig' => [ 'CandidateGenerationConfig' => [ 'AlgorithmsConfig' => [ [ 'AutoMLAlgorithms' => ['<string>', ...], // REQUIRED ], // ... ], ], 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'FeatureSpecificationS3Uri' => '<string>', 'ForecastFrequency' => '<string>', // REQUIRED 'ForecastHorizon' => <integer>, // REQUIRED 'ForecastQuantiles' => ['<string>', ...], 'HolidayConfig' => [ [ 'CountryCode' => '<string>', ], // ... ], 'TimeSeriesConfig' => [ // REQUIRED 'GroupingAttributeNames' => ['<string>', ...], 'ItemIdentifierAttributeName' => '<string>', // REQUIRED 'TargetAttributeName' => '<string>', // REQUIRED 'TimestampAttributeName' => '<string>', // REQUIRED ], 'Transformations' => [ 'Aggregation' => ['<string>', ...], 'Filling' => [ '<TransformationAttributeName>' => ['<string>', ...], // ... ], ], ], ], 'DataSplitConfig' => [ 'ValidationFraction' => <float>, ], 'ModelDeployConfig' => [ 'AutoGenerateEndpointName' => true || false, 'EndpointName' => '<string>', ], 'OutputDataConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'RoleArn' => '<string>', // REQUIRED 'SecurityConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'VolumeKmsKeyId' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- AutoMLComputeConfig
-
- Type: AutoMLComputeConfig structure
Specifies the compute configuration for the AutoML job V2.
- AutoMLJobInputDataConfig
-
- Required: Yes
- Type: Array of AutoMLJobChannel structures
An array of channel objects describing the input data and their location. Each channel is a named input source. Similar to the InputDataConfig attribute in the
CreateAutoMLJob
input parameters. The supported formats depend on the problem type:-
For tabular problem types:
S3Prefix
,ManifestFile
. -
For image classification:
S3Prefix
,ManifestFile
,AugmentedManifestFile
. -
For text classification:
S3Prefix
. -
For time-series forecasting:
S3Prefix
. -
For text generation (LLMs fine-tuning):
S3Prefix
.
- AutoMLJobName
-
- Required: Yes
- Type: string
Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
- AutoMLJobObjective
-
- Type: AutoMLJobObjective structure
Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. For the list of default values per problem type, see AutoMLJobObjective.
-
For tabular problem types: You must either provide both the
AutoMLJobObjective
and indicate the type of supervised learning problem inAutoMLProblemTypeConfig
(TabularJobConfig.ProblemType
), or none at all. -
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the
AutoMLJobObjective
field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
- AutoMLProblemTypeConfig
-
- Required: Yes
- Type: AutoMLProblemTypeConfig structure
Defines the configuration settings of one of the supported problem types.
- DataSplitConfig
-
- Type: AutoMLDataSplitConfig structure
This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling
CreateAutoMLJob
, the validation dataset must be less than 2 GB in size.This attribute must not be set for the time-series forecasting problem type, as Autopilot automatically splits the input dataset into training and validation sets.
- ModelDeployConfig
-
- Type: ModelDeployConfig structure
Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
- OutputDataConfig
-
- Required: Yes
- Type: AutoMLOutputDataConfig structure
Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.
- RoleArn
-
- Required: Yes
- Type: string
The ARN of the role that is used to access the data.
- SecurityConfig
-
- Type: AutoMLSecurityConfig structure
The security configuration for traffic encryption or Amazon VPC settings.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, such as by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
Result Syntax
[ 'AutoMLJobArn' => '<string>', ]
Result Details
Members
- AutoMLJobArn
-
- Required: Yes
- Type: string
The unique ARN assigned to the AutoMLJob when it is created.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateCluster
$result = $client->createCluster
([/* ... */]); $promise = $client->createClusterAsync
([/* ... */]);
Creates a SageMaker HyperPod cluster. SageMaker HyperPod is a capability of SageMaker for creating and managing persistent clusters for developing large machine learning models, such as large language models (LLMs) and diffusion models. To learn more, see Amazon SageMaker HyperPod in the Amazon SageMaker Developer Guide.
Parameter Syntax
$result = $client->createCluster([ 'ClusterName' => '<string>', // REQUIRED 'InstanceGroups' => [ // REQUIRED [ 'ExecutionRole' => '<string>', // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceGroupName' => '<string>', // REQUIRED 'InstanceStorageConfigs' => [ [ 'EbsVolumeConfig' => [ 'VolumeSizeInGB' => <integer>, // REQUIRED ], ], // ... ], 'InstanceType' => 'ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.c5n.large|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge', // REQUIRED 'LifeCycleConfig' => [ // REQUIRED 'OnCreate' => '<string>', // REQUIRED 'SourceS3Uri' => '<string>', // REQUIRED ], 'ThreadsPerCore' => <integer>, ], // ... ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ]);
Parameter Details
Members
- ClusterName
-
- Required: Yes
- Type: string
The name for the new SageMaker HyperPod cluster.
- InstanceGroups
-
- Required: Yes
- Type: Array of ClusterInstanceGroupSpecification structures
The instance groups to be created in the SageMaker HyperPod cluster.
- Tags
-
- Type: Array of Tag structures
Custom tags for managing the SageMaker HyperPod cluster as an Amazon Web Services resource. You can add tags to your cluster in the same way you add them in other Amazon Web Services services that support tagging. To learn more about tagging Amazon Web Services resources in general, see Tagging Amazon Web Services Resources User Guide.
- VpcConfig
-
- Type: VpcConfig structure
Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
Result Syntax
[ 'ClusterArn' => '<string>', ]
Result Details
Members
- ClusterArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the cluster.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
CreateCodeRepository
$result = $client->createCodeRepository
([/* ... */]); $promise = $client->createCodeRepositoryAsync
([/* ... */]);
Creates a Git repository as a resource in your 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 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 Amazon Web Services CodeCommit or in any other Git repository.
Parameter Syntax
$result = $client->createCodeRepository([ 'CodeRepositoryName' => '<string>', // REQUIRED 'GitConfig' => [ // REQUIRED 'Branch' => '<string>', 'RepositoryUrl' => '<string>', // REQUIRED 'SecretArn' => '<string>', ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- CodeRepositoryName
-
- Required: Yes
- Type: string
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).
- GitConfig
-
- Required: Yes
- Type: GitConfig structure
Specifies details about the repository, including the URL where the repository is located, the default branch, and credentials to use to access the repository.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Result Syntax
[ 'CodeRepositoryArn' => '<string>', ]
Result Details
Members
- CodeRepositoryArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the new repository.
Errors
There are no errors described for this operation.
CreateCompilationJob
$result = $client->createCompilationJob
([/* ... */]); $promise = $client->createCompilationJobAsync
([/* ... */]);
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 Amazon Web Services 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.
Parameter Syntax
$result = $client->createCompilationJob([ 'CompilationJobName' => '<string>', // REQUIRED 'InputConfig' => [ 'DataInputConfig' => '<string>', 'Framework' => 'TENSORFLOW|KERAS|MXNET|ONNX|PYTORCH|XGBOOST|TFLITE|DARKNET|SKLEARN', // REQUIRED 'FrameworkVersion' => '<string>', 'S3Uri' => '<string>', // REQUIRED ], 'ModelPackageVersionArn' => '<string>', 'OutputConfig' => [ // REQUIRED 'CompilerOptions' => '<string>', 'KmsKeyId' => '<string>', 'S3OutputLocation' => '<string>', // REQUIRED 'TargetDevice' => 'lambda|ml_m4|ml_m5|ml_m6g|ml_c4|ml_c5|ml_c6g|ml_p2|ml_p3|ml_g4dn|ml_inf1|ml_inf2|ml_trn1|ml_eia2|jetson_tx1|jetson_tx2|jetson_nano|jetson_xavier|rasp3b|rasp4b|imx8qm|deeplens|rk3399|rk3288|aisage|sbe_c|qcs605|qcs603|sitara_am57x|amba_cv2|amba_cv22|amba_cv25|x86_win32|x86_win64|coreml|jacinto_tda4vm|imx8mplus', 'TargetPlatform' => [ 'Accelerator' => 'INTEL_GRAPHICS|MALI|NVIDIA|NNA', 'Arch' => 'X86_64|X86|ARM64|ARM_EABI|ARM_EABIHF', // REQUIRED 'Os' => 'ANDROID|LINUX', // REQUIRED ], ], 'RoleArn' => '<string>', // REQUIRED 'StoppingCondition' => [ // REQUIRED 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ]);
Parameter Details
Members
- CompilationJobName
-
- Required: Yes
- Type: string
A name for the model compilation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account.
- InputConfig
-
- Type: InputConfig structure
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.
- ModelPackageVersionArn
-
- Type: string
The Amazon Resource Name (ARN) of a versioned model package. Provide either a
ModelPackageVersionArn
or anInputConfig
object in the request syntax. The presence of both objects in theCreateCompilationJob
request will return an exception. - OutputConfig
-
- Required: Yes
- Type: OutputConfig structure
Provides information about the output location for the compiled model and the target device the model runs on.
- RoleArn
-
- Required: Yes
- Type: string
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. - StoppingCondition
-
- Required: Yes
- Type: StoppingCondition structure
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.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
- VpcConfig
-
- Type: NeoVpcConfig structure
A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
Result Syntax
[ 'CompilationJobArn' => '<string>', ]
Result Details
Members
- CompilationJobArn
-
- Required: Yes
- Type: string
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.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateContext
$result = $client->createContext
([/* ... */]); $promise = $client->createContextAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->createContext([ 'ContextName' => '<string>', // REQUIRED 'ContextType' => '<string>', // REQUIRED 'Description' => '<string>', 'Properties' => ['<string>', ...], 'Source' => [ // REQUIRED 'SourceId' => '<string>', 'SourceType' => '<string>', 'SourceUri' => '<string>', // REQUIRED ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- ContextName
-
- Required: Yes
- Type: string
The name of the context. Must be unique to your account in an Amazon Web Services Region.
- ContextType
-
- Required: Yes
- Type: string
The context type.
- Description
-
- Type: string
The description of the context.
- Properties
-
- Type: Associative array of custom strings keys (StringParameterValue) to strings
A list of properties to add to the context.
- Source
-
- Required: Yes
- Type: ContextSource structure
The source type, ID, and URI.
- Tags
-
- Type: Array of Tag structures
A list of tags to apply to the context.
Result Syntax
[ 'ContextArn' => '<string>', ]
Result Details
Members
- ContextArn
-
- Type: string
The Amazon Resource Name (ARN) of the context.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateDataQualityJobDefinition
$result = $client->createDataQualityJobDefinition
([/* ... */]); $promise = $client->createDataQualityJobDefinitionAsync
([/* ... */]);
Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
Parameter Syntax
$result = $client->createDataQualityJobDefinition([ 'DataQualityAppSpecification' => [ // REQUIRED 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', // REQUIRED 'PostAnalyticsProcessorSourceUri' => '<string>', 'RecordPreprocessorSourceUri' => '<string>', ], 'DataQualityBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], 'StatisticsResource' => [ 'S3Uri' => '<string>', ], ], 'DataQualityJobInput' => [ // REQUIRED 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', // REQUIRED 'DatasetFormat' => [ // REQUIRED 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', // REQUIRED 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', // REQUIRED 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', // REQUIRED 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], ], 'DataQualityJobOutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ // REQUIRED [ 'S3Output' => [ // REQUIRED 'LocalPath' => '<string>', // REQUIRED 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', // REQUIRED ], ], // ... ], ], 'JobDefinitionName' => '<string>', // REQUIRED 'JobResources' => [ // REQUIRED 'ClusterConfig' => [ // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', // REQUIRED 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], 'RoleArn' => '<string>', // REQUIRED 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, // REQUIRED ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- DataQualityAppSpecification
-
- Required: Yes
- Type: DataQualityAppSpecification structure
Specifies the container that runs the monitoring job.
- DataQualityBaselineConfig
-
- Type: DataQualityBaselineConfig structure
Configures the constraints and baselines for the monitoring job.
- DataQualityJobInput
-
- Required: Yes
- Type: DataQualityJobInput structure
A list of inputs for the monitoring job. Currently endpoints are supported as monitoring inputs.
- DataQualityJobOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The output configuration for monitoring jobs.
- JobDefinitionName
-
- Required: Yes
- Type: string
The name for the monitoring job definition.
- JobResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources to deploy for a monitoring job.
- NetworkConfig
-
- Type: MonitoringNetworkConfig structure
Specifies networking configuration for the monitoring job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
A time limit for how long the monitoring job is allowed to run before stopping.
- Tags
-
- Type: Array of Tag structures
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
Result Syntax
[ 'JobDefinitionArn' => '<string>', ]
Result Details
Members
- JobDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the job definition.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
CreateDeviceFleet
$result = $client->createDeviceFleet
([/* ... */]); $promise = $client->createDeviceFleetAsync
([/* ... */]);
Creates a device fleet.
Parameter Syntax
$result = $client->createDeviceFleet([ 'Description' => '<string>', 'DeviceFleetName' => '<string>', // REQUIRED 'EnableIotRoleAlias' => true || false, 'OutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'PresetDeploymentConfig' => '<string>', 'PresetDeploymentType' => 'GreengrassV2Component', 'S3OutputLocation' => '<string>', // REQUIRED ], 'RoleArn' => '<string>', 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- Description
-
- Type: string
A description of the fleet.
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the fleet that the device belongs to.
- EnableIotRoleAlias
-
- Type: boolean
Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".
For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".
- OutputConfig
-
- Required: Yes
- Type: EdgeOutputConfig structure
The output configuration for storing sample data collected by the fleet.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).
- Tags
-
- Type: Array of Tag structures
Creates tags for the specified fleet.
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateDomain
$result = $client->createDomain
([/* ... */]); $promise = $client->createDomainAsync
([/* ... */]);
Creates a Domain
. A domain consists of an associated Amazon Elastic File System volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. 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 Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption.
VPC configuration
All traffic between the domain and the Amazon EFS volume is through the specified VPC and subnets. For other traffic, you can specify the AppNetworkAccessType
parameter. AppNetworkAccessType
corresponds to the network access type that you choose when you onboard to the domain. 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 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 Amazon SageMaker 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.
NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a Amazon SageMaker Studio app successfully.
For more information, see Connect Amazon SageMaker Studio Notebooks to Resources in a VPC.
Parameter Syntax
$result = $client->createDomain([ 'AppNetworkAccessType' => 'PublicInternetOnly|VpcOnly', 'AppSecurityGroupManagement' => 'Service|Customer', 'AuthMode' => 'SSO|IAM', // REQUIRED 'DefaultSpaceSettings' => [ 'CustomFileSystemConfigs' => [ [ 'EFSFileSystemConfig' => [ 'FileSystemId' => '<string>', // REQUIRED 'FileSystemPath' => '<string>', ], ], // ... ], 'CustomPosixUserConfig' => [ 'Gid' => <integer>, // REQUIRED 'Uid' => <integer>, // REQUIRED ], 'ExecutionRole' => '<string>', 'JupyterLabAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'EmrSettings' => [ 'AssumableRoleArns' => ['<string>', ...], 'ExecutionRoleArns' => ['<string>', ...], ], 'LifecycleConfigArns' => ['<string>', ...], ], 'JupyterServerAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'KernelGatewayAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'SecurityGroups' => ['<string>', ...], 'SpaceStorageSettings' => [ 'DefaultEbsStorageSettings' => [ 'DefaultEbsVolumeSizeInGb' => <integer>, // REQUIRED 'MaximumEbsVolumeSizeInGb' => <integer>, // REQUIRED ], ], ], 'DefaultUserSettings' => [ // REQUIRED 'CanvasAppSettings' => [ 'DirectDeploySettings' => [ 'Status' => 'ENABLED|DISABLED', ], 'EmrServerlessSettings' => [ 'ExecutionRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'GenerativeAiSettings' => [ 'AmazonBedrockRoleArn' => '<string>', ], 'IdentityProviderOAuthSettings' => [ [ 'DataSourceName' => 'SalesforceGenie|Snowflake', 'SecretArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], // ... ], 'KendraSettings' => [ 'Status' => 'ENABLED|DISABLED', ], 'ModelRegisterSettings' => [ 'CrossAccountModelRegisterRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'TimeSeriesForecastingSettings' => [ 'AmazonForecastRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'WorkspaceSettings' => [ 'S3ArtifactPath' => '<string>', 'S3KmsKeyId' => '<string>', ], ], 'CodeEditorAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'CustomFileSystemConfigs' => [ [ 'EFSFileSystemConfig' => [ 'FileSystemId' => '<string>', // REQUIRED 'FileSystemPath' => '<string>', ], ], // ... ], 'CustomPosixUserConfig' => [ 'Gid' => <integer>, // REQUIRED 'Uid' => <integer>, // REQUIRED ], 'DefaultLandingUri' => '<string>', 'ExecutionRole' => '<string>', 'JupyterLabAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'EmrSettings' => [ 'AssumableRoleArns' => ['<string>', ...], 'ExecutionRoleArns' => ['<string>', ...], ], 'LifecycleConfigArns' => ['<string>', ...], ], 'JupyterServerAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'KernelGatewayAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'RSessionAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'RStudioServerProAppSettings' => [ 'AccessStatus' => 'ENABLED|DISABLED', 'UserGroup' => 'R_STUDIO_ADMIN|R_STUDIO_USER', ], 'SecurityGroups' => ['<string>', ...], 'SharingSettings' => [ 'NotebookOutputOption' => 'Allowed|Disabled', 'S3KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'SpaceStorageSettings' => [ 'DefaultEbsStorageSettings' => [ 'DefaultEbsVolumeSizeInGb' => <integer>, // REQUIRED 'MaximumEbsVolumeSizeInGb' => <integer>, // REQUIRED ], ], 'StudioWebPortal' => 'ENABLED|DISABLED', 'StudioWebPortalSettings' => [ 'HiddenAppTypes' => ['<string>', ...], 'HiddenMlTools' => ['<string>', ...], ], 'TensorBoardAppSettings' => [ 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], ], 'DomainName' => '<string>', // REQUIRED 'DomainSettings' => [ 'AmazonQSettings' => [ 'QProfileArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'DockerSettings' => [ 'EnableDockerAccess' => 'ENABLED|DISABLED', 'VpcOnlyTrustedAccounts' => ['<string>', ...], ], 'ExecutionRoleIdentityConfig' => 'USER_PROFILE_NAME|DISABLED', 'RStudioServerProDomainSettings' => [ 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'DomainExecutionRoleArn' => '<string>', // REQUIRED 'RStudioConnectUrl' => '<string>', 'RStudioPackageManagerUrl' => '<string>', ], 'SecurityGroupIds' => ['<string>', ...], ], 'HomeEfsFileSystemKmsKeyId' => '<string>', 'KmsKeyId' => '<string>', 'SubnetIds' => ['<string>', ...], // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'VpcId' => '<string>', // REQUIRED ]);
Parameter Details
Members
- AppNetworkAccessType
-
- Type: 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 traffic is through the specified VPC and subnets
- AppSecurityGroupManagement
-
- Type: string
The entity that creates and manages the required security groups for inter-app communication in
VPCOnly
mode. Required whenCreateDomain.AppNetworkAccessType
isVPCOnly
andDomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is provided. If setting up the domain for use with RStudio, this value must be set toService
. - AuthMode
-
- Required: Yes
- Type: string
The mode of authentication that members use to access the domain.
- DefaultSpaceSettings
-
- Type: DefaultSpaceSettings structure
The default settings used to create a space.
- DefaultUserSettings
-
- Required: Yes
- Type: UserSettings structure
The default settings to use to create a user profile when
UserSettings
isn't specified in the call to theCreateUserProfile
API.SecurityGroups
is aggregated when specified in both calls. For all other settings inUserSettings
, the values specified inCreateUserProfile
take precedence over those specified inCreateDomain
. - DomainName
-
- Required: Yes
- Type: string
A name for the domain.
- DomainSettings
-
- Type: DomainSettings structure
A collection of
Domain
settings. - HomeEfsFileSystemKmsKeyId
-
- Type: string
Use
KmsKeyId
. - KmsKeyId
-
- Type: string
SageMaker uses Amazon Web Services KMS to encrypt EFS and EBS volumes attached to the domain with an Amazon Web Services managed key by default. For more control, specify a customer managed key.
- SubnetIds
-
- Required: Yes
- Type: Array of strings
The VPC subnets that the domain uses for communication.
- Tags
-
- Type: Array of Tag structures
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 that you specify for the Domain are also added to all Apps that the Domain launches.
- VpcId
-
- Required: Yes
- Type: string
The ID of the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.
Result Syntax
[ 'DomainArn' => '<string>', 'Url' => '<string>', ]
Result Details
Members
- DomainArn
-
- Type: string
The Amazon Resource Name (ARN) of the created domain.
- Url
-
- Type: string
The URL to the created domain.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
CreateEdgeDeploymentPlan
$result = $client->createEdgeDeploymentPlan
([/* ... */]); $promise = $client->createEdgeDeploymentPlanAsync
([/* ... */]);
Creates an edge deployment plan, consisting of multiple stages. Each stage may have a different deployment configuration and devices.
Parameter Syntax
$result = $client->createEdgeDeploymentPlan([ 'DeviceFleetName' => '<string>', // REQUIRED 'EdgeDeploymentPlanName' => '<string>', // REQUIRED 'ModelConfigs' => [ // REQUIRED [ 'EdgePackagingJobName' => '<string>', // REQUIRED 'ModelHandle' => '<string>', // REQUIRED ], // ... ], 'Stages' => [ [ 'DeploymentConfig' => [ 'FailureHandlingPolicy' => 'ROLLBACK_ON_FAILURE|DO_NOTHING', // REQUIRED ], 'DeviceSelectionConfig' => [ // REQUIRED 'DeviceNameContains' => '<string>', 'DeviceNames' => ['<string>', ...], 'DeviceSubsetType' => 'PERCENTAGE|SELECTION|NAMECONTAINS', // REQUIRED 'Percentage' => <integer>, ], 'StageName' => '<string>', // REQUIRED ], // ... ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- DeviceFleetName
-
- Required: Yes
- Type: string
The device fleet used for this edge deployment plan.
- EdgeDeploymentPlanName
-
- Required: Yes
- Type: string
The name of the edge deployment plan.
- ModelConfigs
-
- Required: Yes
- Type: Array of EdgeDeploymentModelConfig structures
List of models associated with the edge deployment plan.
- Stages
-
- Type: Array of DeploymentStage structures
List of stages of the edge deployment plan. The number of stages is limited to 10 per deployment.
- Tags
-
- Type: Array of Tag structures
List of tags with which to tag the edge deployment plan.
Result Syntax
[ 'EdgeDeploymentPlanArn' => '<string>', ]
Result Details
Members
- EdgeDeploymentPlanArn
-
- Required: Yes
- Type: string
The ARN of the edge deployment plan.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateEdgeDeploymentStage
$result = $client->createEdgeDeploymentStage
([/* ... */]); $promise = $client->createEdgeDeploymentStageAsync
([/* ... */]);
Creates a new stage in an existing edge deployment plan.
Parameter Syntax
$result = $client->createEdgeDeploymentStage([ 'EdgeDeploymentPlanName' => '<string>', // REQUIRED 'Stages' => [ // REQUIRED [ 'DeploymentConfig' => [ 'FailureHandlingPolicy' => 'ROLLBACK_ON_FAILURE|DO_NOTHING', // REQUIRED ], 'DeviceSelectionConfig' => [ // REQUIRED 'DeviceNameContains' => '<string>', 'DeviceNames' => ['<string>', ...], 'DeviceSubsetType' => 'PERCENTAGE|SELECTION|NAMECONTAINS', // REQUIRED 'Percentage' => <integer>, ], 'StageName' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- EdgeDeploymentPlanName
-
- Required: Yes
- Type: string
The name of the edge deployment plan.
- Stages
-
- Required: Yes
- Type: Array of DeploymentStage structures
List of stages to be added to the edge deployment plan.
Result Syntax
[]
Result Details
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateEdgePackagingJob
$result = $client->createEdgePackagingJob
([/* ... */]); $promise = $client->createEdgePackagingJobAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->createEdgePackagingJob([ 'CompilationJobName' => '<string>', // REQUIRED 'EdgePackagingJobName' => '<string>', // REQUIRED 'ModelName' => '<string>', // REQUIRED 'ModelVersion' => '<string>', // REQUIRED 'OutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'PresetDeploymentConfig' => '<string>', 'PresetDeploymentType' => 'GreengrassV2Component', 'S3OutputLocation' => '<string>', // REQUIRED ], 'ResourceKey' => '<string>', 'RoleArn' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- CompilationJobName
-
- Required: Yes
- Type: string
The name of the SageMaker Neo compilation job that will be used to locate model artifacts for packaging.
- EdgePackagingJobName
-
- Required: Yes
- Type: string
The name of the edge packaging job.
- ModelName
-
- Required: Yes
- Type: string
The name of the model.
- ModelVersion
-
- Required: Yes
- Type: string
The version of the model.
- OutputConfig
-
- Required: Yes
- Type: EdgeOutputConfig structure
Provides information about the output location for the packaged model.
- ResourceKey
-
- Type: string
The Amazon Web Services KMS key to use when encrypting the EBS volume the edge packaging job runs on.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact SageMaker Neo.
- Tags
-
- Type: Array of Tag structures
Creates tags for the packaging job.
Result Syntax
[]
Result Details
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateEndpoint
$result = $client->createEndpoint
([/* ... */]); $promise = $client->createEndpointAsync
([/* ... */]);
Creates an endpoint using the endpoint configuration specified in the request. 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 SageMaker hosting services.
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 Amazon Web Services Region in your Amazon Web Services account.
When it receives the request, 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
, 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 SageMaker receives the request, it sets the endpoint status to Creating
. After it creates the endpoint, it sets the status to InService
. 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, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provided. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
To add the IAM role policies for using this API operation, go to the IAM console, 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 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 SageMaker API Permissions: Actions, Permissions, and Resources Reference.
Parameter Syntax
$result = $client->createEndpoint([ 'DeploymentConfig' => [ 'AutoRollbackConfiguration' => [ 'Alarms' => [ [ 'AlarmName' => '<string>', ], // ... ], ], 'BlueGreenUpdatePolicy' => [ 'MaximumExecutionTimeoutInSeconds' => <integer>, 'TerminationWaitInSeconds' => <integer>, 'TrafficRoutingConfiguration' => [ // REQUIRED 'CanarySize' => [ 'Type' => 'INSTANCE_COUNT|CAPACITY_PERCENT', // REQUIRED 'Value' => <integer>, // REQUIRED ], 'LinearStepSize' => [ 'Type' => 'INSTANCE_COUNT|CAPACITY_PERCENT', // REQUIRED 'Value' => <integer>, // REQUIRED ], 'Type' => 'ALL_AT_ONCE|CANARY|LINEAR', // REQUIRED 'WaitIntervalInSeconds' => <integer>, // REQUIRED ], ], 'RollingUpdatePolicy' => [ 'MaximumBatchSize' => [ // REQUIRED 'Type' => 'INSTANCE_COUNT|CAPACITY_PERCENT', // REQUIRED 'Value' => <integer>, // REQUIRED ], 'MaximumExecutionTimeoutInSeconds' => <integer>, 'RollbackMaximumBatchSize' => [ 'Type' => 'INSTANCE_COUNT|CAPACITY_PERCENT', // REQUIRED 'Value' => <integer>, // REQUIRED ], 'WaitIntervalInSeconds' => <integer>, // REQUIRED ], ], 'EndpointConfigName' => '<string>', // REQUIRED 'EndpointName' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- DeploymentConfig
-
- Type: DeploymentConfig structure
The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
- EndpointConfigName
-
- Required: Yes
- Type: string
The name of an endpoint configuration. For more information, see CreateEndpointConfig.
- EndpointName
-
- Required: Yes
- Type: string
The name of the endpoint.The name must be unique within an Amazon Web Services Region in your Amazon Web Services account. The name is case-insensitive in
CreateEndpoint
, but the case is preserved and must be matched in InvokeEndpoint. - Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Result Syntax
[ 'EndpointArn' => '<string>', ]
Result Details
Members
- EndpointArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the endpoint.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateEndpointConfig
$result = $client->createEndpointConfig
([/* ... */]); $promise = $client->createEndpointConfigAsync
([/* ... */]);
Creates an endpoint configuration that 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 SageMaker to provision. Then you call the CreateEndpoint API.
Use this API if you want to use 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 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. SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.
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
, 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.
Parameter Syntax
$result = $client->createEndpointConfig([ 'AsyncInferenceConfig' => [ 'ClientConfig' => [ 'MaxConcurrentInvocationsPerInstance' => <integer>, ], 'OutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'NotificationConfig' => [ 'ErrorTopic' => '<string>', 'IncludeInferenceResponseIn' => ['<string>', ...], 'SuccessTopic' => '<string>', ], 'S3FailurePath' => '<string>', 'S3OutputPath' => '<string>', ], ], 'DataCaptureConfig' => [ 'CaptureContentTypeHeader' => [ 'CsvContentTypes' => ['<string>', ...], 'JsonContentTypes' => ['<string>', ...], ], 'CaptureOptions' => [ // REQUIRED [ 'CaptureMode' => 'Input|Output|InputAndOutput', // REQUIRED ], // ... ], 'DestinationS3Uri' => '<string>', // REQUIRED 'EnableCapture' => true || false, 'InitialSamplingPercentage' => <integer>, // REQUIRED 'KmsKeyId' => '<string>', ], 'EnableNetworkIsolation' => true || false, 'EndpointConfigName' => '<string>', // REQUIRED 'ExecutionRoleArn' => '<string>', 'ExplainerConfig' => [ 'ClarifyExplainerConfig' => [ 'EnableExplanations' => '<string>', 'InferenceConfig' => [ 'ContentTemplate' => '<string>', 'FeatureHeaders' => ['<string>', ...], 'FeatureTypes' => ['<string>', ...], 'FeaturesAttribute' => '<string>', 'LabelAttribute' => '<string>', 'LabelHeaders' => ['<string>', ...], 'LabelIndex' => <integer>, 'MaxPayloadInMB' => <integer>, 'MaxRecordCount' => <integer>, 'ProbabilityAttribute' => '<string>', 'ProbabilityIndex' => <integer>, ], 'ShapConfig' => [ // REQUIRED 'NumberOfSamples' => <integer>, 'Seed' => <integer>, 'ShapBaselineConfig' => [ // REQUIRED 'MimeType' => '<string>', 'ShapBaseline' => '<string>', 'ShapBaselineUri' => '<string>', ], 'TextConfig' => [ 'Granularity' => 'token|sentence|paragraph', // REQUIRED 'Language' => 'af|sq|ar|hy|eu|bn|bg|ca|zh|hr|cs|da|nl|en|et|fi|fr|de|el|gu|he|hi|hu|is|id|ga|it|kn|ky|lv|lt|lb|mk|ml|mr|ne|nb|fa|pl|pt|ro|ru|sa|sr|tn|si|sk|sl|es|sv|tl|ta|tt|te|tr|uk|ur|yo|lij|xx', // REQUIRED ], 'UseLogit' => true || false, ], ], ], 'KmsKeyId' => '<string>', 'ProductionVariants' => [ // REQUIRED [ 'AcceleratorType' => 'ml.eia1.medium|ml.eia1.large|ml.eia1.xlarge|ml.eia2.medium|ml.eia2.large|ml.eia2.xlarge', 'ContainerStartupHealthCheckTimeoutInSeconds' => <integer>, 'CoreDumpConfig' => [ 'DestinationS3Uri' => '<string>', // REQUIRED 'KmsKeyId' => '<string>', ], 'EnableSSMAccess' => true || false, 'InferenceAmiVersion' => 'al2-ami-sagemaker-inference-gpu-2', 'InitialInstanceCount' => <integer>, 'InitialVariantWeight' => <float>, 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.12xlarge|ml.m5d.24xlarge|ml.c4.large|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.large|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.12xlarge|ml.r5.24xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.12xlarge|ml.r5d.24xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.dl1.24xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.p4d.24xlarge|ml.c7g.large|ml.c7g.xlarge|ml.c7g.2xlarge|ml.c7g.4xlarge|ml.c7g.8xlarge|ml.c7g.12xlarge|ml.c7g.16xlarge|ml.m6g.large|ml.m6g.xlarge|ml.m6g.2xlarge|ml.m6g.4xlarge|ml.m6g.8xlarge|ml.m6g.12xlarge|ml.m6g.16xlarge|ml.m6gd.large|ml.m6gd.xlarge|ml.m6gd.2xlarge|ml.m6gd.4xlarge|ml.m6gd.8xlarge|ml.m6gd.12xlarge|ml.m6gd.16xlarge|ml.c6g.large|ml.c6g.xlarge|ml.c6g.2xlarge|ml.c6g.4xlarge|ml.c6g.8xlarge|ml.c6g.12xlarge|ml.c6g.16xlarge|ml.c6gd.large|ml.c6gd.xlarge|ml.c6gd.2xlarge|ml.c6gd.4xlarge|ml.c6gd.8xlarge|ml.c6gd.12xlarge|ml.c6gd.16xlarge|ml.c6gn.large|ml.c6gn.xlarge|ml.c6gn.2xlarge|ml.c6gn.4xlarge|ml.c6gn.8xlarge|ml.c6gn.12xlarge|ml.c6gn.16xlarge|ml.r6g.large|ml.r6g.xlarge|ml.r6g.2xlarge|ml.r6g.4xlarge|ml.r6g.8xlarge|ml.r6g.12xlarge|ml.r6g.16xlarge|ml.r6gd.large|ml.r6gd.xlarge|ml.r6gd.2xlarge|ml.r6gd.4xlarge|ml.r6gd.8xlarge|ml.r6gd.12xlarge|ml.r6gd.16xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.p5.48xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge', 'ManagedInstanceScaling' => [ 'MaxInstanceCount' => <integer>, 'MinInstanceCount' => <integer>, 'Status' => 'ENABLED|DISABLED', ], 'ModelDataDownloadTimeoutInSeconds' => <integer>, 'ModelName' => '<string>', 'RoutingConfig' => [ 'RoutingStrategy' => 'LEAST_OUTSTANDING_REQUESTS|RANDOM', // REQUIRED ], 'ServerlessConfig' => [ 'MaxConcurrency' => <integer>, // REQUIRED 'MemorySizeInMB' => <integer>, // REQUIRED 'ProvisionedConcurrency' => <integer>, ], 'VariantName' => '<string>', // REQUIRED 'VolumeSizeInGB' => <integer>, ], // ... ], 'ShadowProductionVariants' => [ [ 'AcceleratorType' => 'ml.eia1.medium|ml.eia1.large|ml.eia1.xlarge|ml.eia2.medium|ml.eia2.large|ml.eia2.xlarge', 'ContainerStartupHealthCheckTimeoutInSeconds' => <integer>, 'CoreDumpConfig' => [ 'DestinationS3Uri' => '<string>', // REQUIRED 'KmsKeyId' => '<string>', ], 'EnableSSMAccess' => true || false, 'InferenceAmiVersion' => 'al2-ami-sagemaker-inference-gpu-2', 'InitialInstanceCount' => <integer>, 'InitialVariantWeight' => <float>, 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.12xlarge|ml.m5d.24xlarge|ml.c4.large|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.large|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.12xlarge|ml.r5.24xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.12xlarge|ml.r5d.24xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.dl1.24xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.p4d.24xlarge|ml.c7g.large|ml.c7g.xlarge|ml.c7g.2xlarge|ml.c7g.4xlarge|ml.c7g.8xlarge|ml.c7g.12xlarge|ml.c7g.16xlarge|ml.m6g.large|ml.m6g.xlarge|ml.m6g.2xlarge|ml.m6g.4xlarge|ml.m6g.8xlarge|ml.m6g.12xlarge|ml.m6g.16xlarge|ml.m6gd.large|ml.m6gd.xlarge|ml.m6gd.2xlarge|ml.m6gd.4xlarge|ml.m6gd.8xlarge|ml.m6gd.12xlarge|ml.m6gd.16xlarge|ml.c6g.large|ml.c6g.xlarge|ml.c6g.2xlarge|ml.c6g.4xlarge|ml.c6g.8xlarge|ml.c6g.12xlarge|ml.c6g.16xlarge|ml.c6gd.large|ml.c6gd.xlarge|ml.c6gd.2xlarge|ml.c6gd.4xlarge|ml.c6gd.8xlarge|ml.c6gd.12xlarge|ml.c6gd.16xlarge|ml.c6gn.large|ml.c6gn.xlarge|ml.c6gn.2xlarge|ml.c6gn.4xlarge|ml.c6gn.8xlarge|ml.c6gn.12xlarge|ml.c6gn.16xlarge|ml.r6g.large|ml.r6g.xlarge|ml.r6g.2xlarge|ml.r6g.4xlarge|ml.r6g.8xlarge|ml.r6g.12xlarge|ml.r6g.16xlarge|ml.r6gd.large|ml.r6gd.xlarge|ml.r6gd.2xlarge|ml.r6gd.4xlarge|ml.r6gd.8xlarge|ml.r6gd.12xlarge|ml.r6gd.16xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.p5.48xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge', 'ManagedInstanceScaling' => [ 'MaxInstanceCount' => <integer>, 'MinInstanceCount' => <integer>, 'Status' => 'ENABLED|DISABLED', ], 'ModelDataDownloadTimeoutInSeconds' => <integer>, 'ModelName' => '<string>', 'RoutingConfig' => [ 'RoutingStrategy' => 'LEAST_OUTSTANDING_REQUESTS|RANDOM', // REQUIRED ], 'ServerlessConfig' => [ 'MaxConcurrency' => <integer>, // REQUIRED 'MemorySizeInMB' => <integer>, // REQUIRED 'ProvisionedConcurrency' => <integer>, ], 'VariantName' => '<string>', // REQUIRED 'VolumeSizeInGB' => <integer>, ], // ... ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ]);
Parameter Details
Members
- AsyncInferenceConfig
-
- Type: AsyncInferenceConfig structure
Specifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using InvokeEndpointAsync.
- DataCaptureConfig
-
- Type: DataCaptureConfig structure
Configuration to control how SageMaker captures inference data.
- EnableNetworkIsolation
-
- Type: boolean
Sets whether all model containers deployed to the endpoint are isolated. If they are, no inbound or outbound network calls can be made to or from the model containers.
- EndpointConfigName
-
- Required: Yes
- Type: string
The name of the endpoint configuration. You specify this name in a CreateEndpoint request.
- ExecutionRoleArn
-
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform actions on your behalf. For more information, see SageMaker Roles.
To be able to pass this role to Amazon SageMaker, the caller of this action must have the
iam:PassRole
permission. - ExplainerConfig
-
- Type: ExplainerConfig structure
A member of
CreateEndpointConfig
that enables explainers. - KmsKeyId
-
- Type: string
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that 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 Amazon Web Services Key Management Service section Using Key Policies in Amazon Web Services KMSCertain 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 theProductionVariants
parameter use nitro-based instances with local storage, do not specify a value for theKmsKeyId
parameter. If you specify a value forKmsKeyId
when using any nitro-based instances with local storage, the call toCreateEndpointConfig
fails.For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
- ProductionVariants
-
- Required: Yes
- Type: Array of ProductionVariant structures
An array of
ProductionVariant
objects, one for each model that you want to host at this endpoint. - ShadowProductionVariants
-
- Type: Array of ProductionVariant structures
An array of
ProductionVariant
objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified onProductionVariants
. If you use this field, you can only specify one variant forProductionVariants
and one variant forShadowProductionVariants
. - Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
- VpcConfig
-
- Type: VpcConfig structure
Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
Result Syntax
[ 'EndpointConfigArn' => '<string>', ]
Result Details
Members
- EndpointConfigArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the endpoint configuration.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateExperiment
$result = $client->createExperiment
([/* ... */]); $promise = $client->createExperimentAsync
([/* ... */]);
Creates a 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.
In the Studio UI, trials are referred to as run groups and trial components are referred to as runs.
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 SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services 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.
Parameter Syntax
$result = $client->createExperiment([ 'Description' => '<string>', 'DisplayName' => '<string>', 'ExperimentName' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- Description
-
- Type: string
The description of the experiment.
- DisplayName
-
- Type: string
The name of the experiment as displayed. The name doesn't need to be unique. If you don't specify
DisplayName
, the value inExperimentName
is displayed. - ExperimentName
-
- Required: Yes
- Type: string
The name of the experiment. The name must be unique in your Amazon Web Services account and is not case-sensitive.
- Tags
-
- Type: Array of Tag structures
A list of tags to associate with the experiment. You can use Search API to search on the tags.
Result Syntax
[ 'ExperimentArn' => '<string>', ]
Result Details
Members
- ExperimentArn
-
- Type: string
The Amazon Resource Name (ARN) of the experiment.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateFeatureGroup
$result = $client->createFeatureGroup
([/* ... */]); $promise = $client->createFeatureGroupAsync
([/* ... */]);
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 Amazon Web Services service quotas to see the FeatureGroup
s quota for your Amazon Web Services account.
Note that it can take approximately 10-15 minutes to provision an OnlineStore
FeatureGroup
with the InMemory
StorageType
.
You must include at least one of OnlineStoreConfig
and OfflineStoreConfig
to create a FeatureGroup
.
Parameter Syntax
$result = $client->createFeatureGroup([ 'Description' => '<string>', 'EventTimeFeatureName' => '<string>', // REQUIRED 'FeatureDefinitions' => [ // REQUIRED [ 'CollectionConfig' => [ 'VectorConfig' => [ 'Dimension' => <integer>, // REQUIRED ], ], 'CollectionType' => 'List|Set|Vector', 'FeatureName' => '<string>', // REQUIRED 'FeatureType' => 'Integral|Fractional|String', // REQUIRED ], // ... ], 'FeatureGroupName' => '<string>', // REQUIRED 'OfflineStoreConfig' => [ 'DataCatalogConfig' => [ 'Catalog' => '<string>', // REQUIRED 'Database' => '<string>', // REQUIRED 'TableName' => '<string>', // REQUIRED ], 'DisableGlueTableCreation' => true || false, 'S3StorageConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'ResolvedOutputS3Uri' => '<string>', 'S3Uri' => '<string>', // REQUIRED ], 'TableFormat' => 'Default|Glue|Iceberg', ], 'OnlineStoreConfig' => [ 'EnableOnlineStore' => true || false, 'SecurityConfig' => [ 'KmsKeyId' => '<string>', ], 'StorageType' => 'Standard|InMemory', 'TtlDuration' => [ 'Unit' => 'Seconds|Minutes|Hours|Days|Weeks', 'Value' => <integer>, ], ], 'RecordIdentifierFeatureName' => '<string>', // REQUIRED 'RoleArn' => '<string>', 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'ThroughputConfig' => [ 'ProvisionedReadCapacityUnits' => <integer>, 'ProvisionedWriteCapacityUnits' => <integer>, 'ThroughputMode' => 'OnDemand|Provisioned', // REQUIRED ], ]);
Parameter Details
Members
- Description
-
- Type: string
A free-form description of a
FeatureGroup
. - EventTimeFeatureName
-
- Required: Yes
- Type: string
The name of the feature that stores the
EventTime
of aRecord
in aFeatureGroup
.An
EventTime
is a point in time when a new event occurs that corresponds to the creation or update of aRecord
in aFeatureGroup
. AllRecords
in theFeatureGroup
must have a correspondingEventTime
.An
EventTime
can be aString
orFractional
.-
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 supportedyyyy-MM-dd'T'HH:mm:ssZ
andyyyy-MM-dd'T'HH:mm:ss.SSSZ
whereyyyy
,MM
, anddd
represent the year, month, and day respectively andHH
,mm
,ss
, and if applicable,SSS
represent the hour, month, second and milliseconds respsectively.'T'
andZ
are constants.
- FeatureDefinitions
-
- Required: Yes
- Type: Array of FeatureDefinition structures
A list of
Feature
names and types.Name
andType
is compulsory perFeature
.Valid feature
FeatureType
s areIntegral
,Fractional
andString
.FeatureName
s cannot be any of the following:is_deleted
,write_time
,api_invocation_time
You can create up to 2,500
FeatureDefinition
s perFeatureGroup
. - FeatureGroupName
-
- Required: Yes
- Type: string
The name of the
FeatureGroup
. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.The name:
-
Must start with an alphanumeric character.
-
Can only include alphanumeric characters, underscores, and hyphens. Spaces are not allowed.
- OfflineStoreConfig
-
- Type: OfflineStoreConfig structure
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 Amazon Web Services Glue or Amazon Web Services Hive data catalog.
-
An KMS encryption key to encrypt the Amazon S3 location used for
OfflineStore
. If KMS encryption key is not specified, by default we encrypt all data at rest using Amazon Web Services KMS key. By defining your bucket-level key for SSE, you can reduce Amazon Web Services KMS requests costs by up to 99 percent. -
Format for the offline store table. Supported formats are Glue (Default) and Apache Iceberg.
To learn more about this parameter, see OfflineStoreConfig.
- OnlineStoreConfig
-
- Type: OnlineStoreConfig structure
You can turn the
OnlineStore
on or off by specifyingTrue
for theEnableOnlineStore
flag inOnlineStoreConfig
.You can also include an Amazon Web Services KMS key ID (
KMSKeyId
) for at-rest encryption of theOnlineStore
.The default value is
False
. - RecordIdentifierFeatureName
-
- Required: Yes
- Type: string
The name of the
Feature
whose value uniquely identifies aRecord
defined in theFeatureStore
. Only the latest record per identifier value will be stored in theOnlineStore
.RecordIdentifierFeatureName
must be one of feature definitions' names.You use the
RecordIdentifierFeatureName
to access data in aFeatureStore
.This name:
-
Must start with an alphanumeric character.
-
Can only contains alphanumeric characters, hyphens, underscores. Spaces are not allowed.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the
OfflineStore
if anOfflineStoreConfig
is provided. - Tags
-
- Type: Array of Tag structures
Tags used to identify
Features
in eachFeatureGroup
. - ThroughputConfig
-
- Type: ThroughputConfig structure
Used to set feature group throughput configuration. There are two modes:
ON_DEMAND
andPROVISIONED
. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.Note:
PROVISIONED
throughput mode is supported only for feature groups that are offline-only, or use theStandard
tier online store.
Result Syntax
[ 'FeatureGroupArn' => '<string>', ]
Result Details
Members
- FeatureGroupArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the
FeatureGroup
. This is a unique identifier for the feature group.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateFlowDefinition
$result = $client->createFlowDefinition
([/* ... */]); $promise = $client->createFlowDefinitionAsync
([/* ... */]);
Creates a flow definition.
Parameter Syntax
$result = $client->createFlowDefinition([ 'FlowDefinitionName' => '<string>', // REQUIRED 'HumanLoopActivationConfig' => [ 'HumanLoopActivationConditionsConfig' => [ // REQUIRED 'HumanLoopActivationConditions' => '<string>', // REQUIRED ], ], 'HumanLoopConfig' => [ 'HumanTaskUiArn' => '<string>', // REQUIRED 'PublicWorkforceTaskPrice' => [ 'AmountInUsd' => [ 'Cents' => <integer>, 'Dollars' => <integer>, 'TenthFractionsOfACent' => <integer>, ], ], 'TaskAvailabilityLifetimeInSeconds' => <integer>, 'TaskCount' => <integer>, // REQUIRED 'TaskDescription' => '<string>', // REQUIRED 'TaskKeywords' => ['<string>', ...], 'TaskTimeLimitInSeconds' => <integer>, 'TaskTitle' => '<string>', // REQUIRED 'WorkteamArn' => '<string>', // REQUIRED ], 'HumanLoopRequestSource' => [ 'AwsManagedHumanLoopRequestSource' => 'AWS/Rekognition/DetectModerationLabels/Image/V3|AWS/Textract/AnalyzeDocument/Forms/V1', // REQUIRED ], 'OutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'RoleArn' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- FlowDefinitionName
-
- Required: Yes
- Type: string
The name of your flow definition.
- HumanLoopActivationConfig
-
- Type: HumanLoopActivationConfig structure
An object containing information about the events that trigger a human workflow.
- HumanLoopConfig
-
- Type: HumanLoopConfig structure
An object containing information about the tasks the human reviewers will perform.
- HumanLoopRequestSource
-
- Type: HumanLoopRequestSource structure
Container for configuring the source of human task requests. Use to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
- OutputConfig
-
- Required: Yes
- Type: FlowDefinitionOutputConfig structure
An object containing information about where the human review results will be uploaded.
- RoleArn
-
- Required: Yes
- Type: string
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
. - Tags
-
- Type: Array of Tag structures
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.
Result Syntax
[ 'FlowDefinitionArn' => '<string>', ]
Result Details
Members
- FlowDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the flow definition you create.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
CreateHub
$result = $client->createHub
([/* ... */]); $promise = $client->createHubAsync
([/* ... */]);
Create a hub.
Parameter Syntax
$result = $client->createHub([ 'HubDescription' => '<string>', // REQUIRED 'HubDisplayName' => '<string>', 'HubName' => '<string>', // REQUIRED 'HubSearchKeywords' => ['<string>', ...], 'S3StorageConfig' => [ 'S3OutputPath' => '<string>', ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- HubDescription
-
- Required: Yes
- Type: string
A description of the hub.
- HubDisplayName
-
- Type: string
The display name of the hub.
- HubName
-
- Required: Yes
- Type: string
The name of the hub to create.
- HubSearchKeywords
-
- Type: Array of strings
The searchable keywords for the hub.
- S3StorageConfig
-
- Type: HubS3StorageConfig structure
The Amazon S3 storage configuration for the hub.
- Tags
-
- Type: Array of Tag structures
Any tags to associate with the hub.
Result Syntax
[ 'HubArn' => '<string>', ]
Result Details
Members
- HubArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the hub.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateHubContentReference
$result = $client->createHubContentReference
([/* ... */]); $promise = $client->createHubContentReferenceAsync
([/* ... */]);
Create a hub content reference in order to add a model in the JumpStart public hub to a private hub.
Parameter Syntax
$result = $client->createHubContentReference([ 'HubContentName' => '<string>', 'HubName' => '<string>', // REQUIRED 'MinVersion' => '<string>', 'SageMakerPublicHubContentArn' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- HubContentName
-
- Type: string
The name of the hub content to reference.
- HubName
-
- Required: Yes
- Type: string
The name of the hub to add the hub content reference to.
- MinVersion
-
- Type: string
The minimum version of the hub content to reference.
- SageMakerPublicHubContentArn
-
- Required: Yes
- Type: string
The ARN of the public hub content to reference.
- Tags
-
- Type: Array of Tag structures
Any tags associated with the hub content to reference.
Result Syntax
[ 'HubArn' => '<string>', 'HubContentArn' => '<string>', ]
Result Details
Members
- HubArn
-
- Required: Yes
- Type: string
The ARN of the hub that the hub content reference was added to.
- HubContentArn
-
- Required: Yes
- Type: string
The ARN of the hub content.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateHumanTaskUi
$result = $client->createHumanTaskUi
([/* ... */]); $promise = $client->createHumanTaskUiAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->createHumanTaskUi([ 'HumanTaskUiName' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'UiTemplate' => [ // REQUIRED 'Content' => '<string>', // REQUIRED ], ]);
Parameter Details
Members
- HumanTaskUiName
-
- Required: Yes
- Type: string
The name of the user interface you are creating.
- Tags
-
- Type: Array of Tag structures
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.
- UiTemplate
-
- Required: Yes
- Type: UiTemplate structure
The Liquid template for the worker user interface.
Result Syntax
[ 'HumanTaskUiArn' => '<string>', ]
Result Details
Members
- HumanTaskUiArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the human review workflow user interface you create.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
CreateHyperParameterTuningJob
$result = $client->createHyperParameterTuningJob
([/* ... */]); $promise = $client->createHyperParameterTuningJobAsync
([/* ... */]);
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.
A hyperparameter tuning job automatically creates Amazon SageMaker experiments, trials, and trial components for each training job that it runs. You can view these entities in Amazon SageMaker Studio. For more information, see View Experiments, Trials, and Trial Components.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
Parameter Syntax
$result = $client->createHyperParameterTuningJob([ 'Autotune' => [ 'Mode' => 'Enabled', // REQUIRED ], 'HyperParameterTuningJobConfig' => [ // REQUIRED 'HyperParameterTuningJobObjective' => [ 'MetricName' => '<string>', // REQUIRED 'Type' => 'Maximize|Minimize', // REQUIRED ], 'ParameterRanges' => [ 'AutoParameters' => [ [ 'Name' => '<string>', // REQUIRED 'ValueHint' => '<string>', // REQUIRED ], // ... ], 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', // REQUIRED 'Values' => ['<string>', ...], // REQUIRED ], // ... ], 'ContinuousParameterRanges' => [ [ 'MaxValue' => '<string>', // REQUIRED 'MinValue' => '<string>', // REQUIRED 'Name' => '<string>', // REQUIRED 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], 'IntegerParameterRanges' => [ [ 'MaxValue' => '<string>', // REQUIRED 'MinValue' => '<string>', // REQUIRED 'Name' => '<string>', // REQUIRED 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], ], 'RandomSeed' => <integer>, 'ResourceLimits' => [ // REQUIRED 'MaxNumberOfTrainingJobs' => <integer>, 'MaxParallelTrainingJobs' => <integer>, // REQUIRED 'MaxRuntimeInSeconds' => <integer>, ], 'Strategy' => 'Bayesian|Random|Hyperband|Grid', // REQUIRED 'StrategyConfig' => [ 'HyperbandStrategyConfig' => [ 'MaxResource' => <integer>, 'MinResource' => <integer>, ], ], 'TrainingJobEarlyStoppingType' => 'Off|Auto', 'TuningJobCompletionCriteria' => [ 'BestObjectiveNotImproving' => [ 'MaxNumberOfTrainingJobsNotImproving' => <integer>, ], 'ConvergenceDetected' => [ 'CompleteOnConvergence' => 'Disabled|Enabled', ], 'TargetObjectiveMetricValue' => <float>, ], ], 'HyperParameterTuningJobName' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'TrainingJobDefinition' => [ 'AlgorithmSpecification' => [ // REQUIRED 'AlgorithmName' => '<string>', 'MetricDefinitions' => [ [ 'Name' => '<string>', // REQUIRED 'Regex' => '<string>', // REQUIRED ], // ... ], 'TrainingImage' => '<string>', 'TrainingInputMode' => 'Pipe|File|FastFile', // REQUIRED ], 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', // REQUIRED ], 'DefinitionName' => '<string>', 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'Environment' => ['<string>', ...], 'HyperParameterRanges' => [ 'AutoParameters' => [ [ 'Name' => '<string>', // REQUIRED 'ValueHint' => '<string>', // REQUIRED ], // ... ], 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', // REQUIRED 'Values' => ['<string>', ...], // REQUIRED ], // ... ], 'ContinuousParameterRanges' => [ [ 'MaxValue' => '<string>', // REQUIRED 'MinValue' => '<string>', // REQUIRED 'Name' => '<string>', // REQUIRED 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], 'IntegerParameterRanges' => [ [ 'MaxValue' => '<string>', // REQUIRED 'MinValue' => '<string>', // REQUIRED 'Name' => '<string>', // REQUIRED 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], ], 'HyperParameterTuningResourceConfig' => [ 'AllocationStrategy' => 'Prioritized', 'InstanceConfigs' => [ [ 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', // REQUIRED 'VolumeSizeInGB' => <integer>, // REQUIRED ], // ... ], 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', // REQUIRED 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ // REQUIRED 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', // REQUIRED 'FileSystemAccessMode' => 'rw|ro', // REQUIRED 'FileSystemId' => '<string>', // REQUIRED 'FileSystemType' => 'EFS|FSxLustre', // REQUIRED ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'InstanceGroupNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'InputMode' => 'Pipe|File|FastFile', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, // REQUIRED ], ], // ... ], 'OutputDataConfig' => [ // REQUIRED 'CompressionType' => 'GZIP|NONE', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'ResourceConfig' => [ 'InstanceCount' => <integer>, 'InstanceGroups' => [ [ 'InstanceCount' => <integer>, // REQUIRED 'InstanceGroupName' => '<string>', // REQUIRED 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', // REQUIRED ], // ... ], 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'KeepAlivePeriodInSeconds' => <integer>, 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], 'RetryStrategy' => [ 'MaximumRetryAttempts' => <integer>, // REQUIRED ], 'RoleArn' => '<string>', // REQUIRED 'StaticHyperParameters' => ['<string>', ...], 'StoppingCondition' => [ // REQUIRED 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TuningObjective' => [ 'MetricName' => '<string>', // REQUIRED 'Type' => 'Maximize|Minimize', // REQUIRED ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], 'TrainingJobDefinitions' => [ [ 'AlgorithmSpecification' => [ // REQUIRED 'AlgorithmName' => '<string>', 'MetricDefinitions' => [ [ 'Name' => '<string>', // REQUIRED 'Regex' => '<string>', // REQUIRED ], // ... ], 'TrainingImage' => '<string>', 'TrainingInputMode' => 'Pipe|File|FastFile', // REQUIRED ], 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', // REQUIRED ], 'DefinitionName' => '<string>', 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'Environment' => ['<string>', ...], 'HyperParameterRanges' => [ 'AutoParameters' => [ [ 'Name' => '<string>', // REQUIRED 'ValueHint' => '<string>', // REQUIRED ], // ... ], 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', // REQUIRED 'Values' => ['<string>', ...], // REQUIRED ], // ... ], 'ContinuousParameterRanges' => [ [ 'MaxValue' => '<string>', // REQUIRED 'MinValue' => '<string>', // REQUIRED 'Name' => '<string>', // REQUIRED 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], 'IntegerParameterRanges' => [ [ 'MaxValue' => '<string>', // REQUIRED 'MinValue' => '<string>', // REQUIRED 'Name' => '<string>', // REQUIRED 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], ], 'HyperParameterTuningResourceConfig' => [ 'AllocationStrategy' => 'Prioritized', 'InstanceConfigs' => [ [ 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', // REQUIRED 'VolumeSizeInGB' => <integer>, // REQUIRED ], // ... ], 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', // REQUIRED 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ // REQUIRED 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', // REQUIRED 'FileSystemAccessMode' => 'rw|ro', // REQUIRED 'FileSystemId' => '<string>', // REQUIRED 'FileSystemType' => 'EFS|FSxLustre', // REQUIRED ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'InstanceGroupNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'InputMode' => 'Pipe|File|FastFile', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, // REQUIRED ], ], // ... ], 'OutputDataConfig' => [ // REQUIRED 'CompressionType' => 'GZIP|NONE', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'ResourceConfig' => [ 'InstanceCount' => <integer>, 'InstanceGroups' => [ [ 'InstanceCount' => <integer>, // REQUIRED 'InstanceGroupName' => '<string>', // REQUIRED 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', // REQUIRED ], // ... ], 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'KeepAlivePeriodInSeconds' => <integer>, 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], 'RetryStrategy' => [ 'MaximumRetryAttempts' => <integer>, // REQUIRED ], 'RoleArn' => '<string>', // REQUIRED 'StaticHyperParameters' => ['<string>', ...], 'StoppingCondition' => [ // REQUIRED 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TuningObjective' => [ 'MetricName' => '<string>', // REQUIRED 'Type' => 'Maximize|Minimize', // REQUIRED ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], // ... ], 'WarmStartConfig' => [ 'ParentHyperParameterTuningJobs' => [ // REQUIRED [ 'HyperParameterTuningJobName' => '<string>', ], // ... ], 'WarmStartType' => 'IdenticalDataAndAlgorithm|TransferLearning', // REQUIRED ], ]);
Parameter Details
Members
- Autotune
-
- Type: Autotune structure
Configures SageMaker Automatic model tuning (AMT) to automatically find optimal parameters for the following fields:
-
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
-
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
-
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
-
RetryStrategy: The number of times to retry a training job.
-
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
-
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
- HyperParameterTuningJobConfig
-
- Required: Yes
- Type: HyperParameterTuningJobConfig structure
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.
- HyperParameterTuningJobName
-
- Required: Yes
- Type: string
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 Amazon Web Services account and Amazon Web Services 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.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.
- TrainingJobDefinition
-
- Type: HyperParameterTrainingJobDefinition structure
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.
- TrainingJobDefinitions
-
- Type: Array of HyperParameterTrainingJobDefinition structures
A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
- WarmStartConfig
-
- Type: HyperParameterTuningJobWarmStartConfig structure
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 theWarmStartType
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.
Result Syntax
[ 'HyperParameterTuningJobArn' => '<string>', ]
Result Details
Members
- HyperParameterTuningJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an ARN to a hyperparameter tuning job when you create it.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateImage
$result = $client->createImage
([/* ... */]); $promise = $client->createImageAsync
([/* ... */]);
Creates a custom SageMaker image. A SageMaker image is a set of image versions. Each image version represents a container image stored in Amazon ECR. For more information, see Bring your own SageMaker image.
Parameter Syntax
$result = $client->createImage([ 'Description' => '<string>', 'DisplayName' => '<string>', 'ImageName' => '<string>', // REQUIRED 'RoleArn' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- Description
-
- Type: string
The description of the image.
- DisplayName
-
- Type: string
The display name of the image. If not provided,
ImageName
is displayed. - ImageName
-
- Required: Yes
- Type: string
The name of the image. Must be unique to your account.
- RoleArn
-
- Required: Yes
- Type: string
The ARN of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
- Tags
-
- Type: Array of Tag structures
A list of tags to apply to the image.
Result Syntax
[ 'ImageArn' => '<string>', ]
Result Details
Members
- ImageArn
-
- Type: string
The ARN of the image.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateImageVersion
$result = $client->createImageVersion
([/* ... */]); $promise = $client->createImageVersionAsync
([/* ... */]);
Creates a version of the SageMaker image specified by ImageName
. The version represents the Amazon ECR container image specified by BaseImage
.
Parameter Syntax
$result = $client->createImageVersion([ 'Aliases' => ['<string>', ...], 'BaseImage' => '<string>', // REQUIRED 'ClientToken' => '<string>', // REQUIRED 'Horovod' => true || false, 'ImageName' => '<string>', // REQUIRED 'JobType' => 'TRAINING|INFERENCE|NOTEBOOK_KERNEL', 'MLFramework' => '<string>', 'Processor' => 'CPU|GPU', 'ProgrammingLang' => '<string>', 'ReleaseNotes' => '<string>', 'VendorGuidance' => 'NOT_PROVIDED|STABLE|TO_BE_ARCHIVED|ARCHIVED', ]);
Parameter Details
Members
- Aliases
-
- Type: Array of strings
A list of aliases created with the image version.
- BaseImage
-
- Required: Yes
- Type: string
The registry path of the container image to use as the starting point for this version. The path is an Amazon ECR URI in the following format:
<acct-id>.dkr.ecr.<region>.amazonaws.com/<repo-name[:tag] or [@digest]>
- ClientToken
-
- Required: Yes
- Type: string
A unique ID. If not specified, the Amazon Web Services CLI and Amazon Web Services SDKs, such as the SDK for Python (Boto3), add a unique value to the call.
- Horovod
-
- Type: boolean
Indicates Horovod compatibility.
- ImageName
-
- Required: Yes
- Type: string
The
ImageName
of theImage
to create a version of. - JobType
-
- Type: string
Indicates SageMaker job type compatibility.
-
TRAINING
: The image version is compatible with SageMaker training jobs. -
INFERENCE
: The image version is compatible with SageMaker inference jobs. -
NOTEBOOK_KERNEL
: The image version is compatible with SageMaker notebook kernels.
- MLFramework
-
- Type: string
The machine learning framework vended in the image version.
- Processor
-
- Type: string
Indicates CPU or GPU compatibility.
-
CPU
: The image version is compatible with CPU. -
GPU
: The image version is compatible with GPU.
- ProgrammingLang
-
- Type: string
The supported programming language and its version.
- ReleaseNotes
-
- Type: string
The maintainer description of the image version.
- VendorGuidance
-
- Type: string
The stability of the image version, specified by the maintainer.
-
NOT_PROVIDED
: The maintainers did not provide a status for image version stability. -
STABLE
: The image version is stable. -
TO_BE_ARCHIVED
: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months. -
ARCHIVED
: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
Result Syntax
[ 'ImageVersionArn' => '<string>', ]
Result Details
Members
- ImageVersionArn
-
- Type: string
The ARN of the image version.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceNotFound:
Resource being access is not found.
CreateInferenceComponent
$result = $client->createInferenceComponent
([/* ... */]); $promise = $client->createInferenceComponentAsync
([/* ... */]);
Creates an inference component, which is a SageMaker hosting object that you can use to deploy a model to an endpoint. In the inference component settings, you specify the model, the endpoint, and how the model utilizes the resources that the endpoint hosts. You can optimize resource utilization by tailoring how the required CPU cores, accelerators, and memory are allocated. You can deploy multiple inference components to an endpoint, where each inference component contains one model and the resource utilization needs for that individual model. After you deploy an inference component, you can directly invoke the associated model when you use the InvokeEndpoint API action.
Parameter Syntax
$result = $client->createInferenceComponent([ 'EndpointName' => '<string>', // REQUIRED 'InferenceComponentName' => '<string>', // REQUIRED 'RuntimeConfig' => [ // REQUIRED 'CopyCount' => <integer>, // REQUIRED ], 'Specification' => [ // REQUIRED 'ComputeResourceRequirements' => [ // REQUIRED 'MaxMemoryRequiredInMb' => <integer>, 'MinMemoryRequiredInMb' => <integer>, // REQUIRED 'NumberOfAcceleratorDevicesRequired' => <float>, 'NumberOfCpuCoresRequired' => <float>, ], 'Container' => [ 'ArtifactUrl' => '<string>', 'Environment' => ['<string>', ...], 'Image' => '<string>', ], 'ModelName' => '<string>', 'StartupParameters' => [ 'ContainerStartupHealthCheckTimeoutInSeconds' => <integer>, 'ModelDataDownloadTimeoutInSeconds' => <integer>, ], ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'VariantName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- EndpointName
-
- Required: Yes
- Type: string
The name of an existing endpoint where you host the inference component.
- InferenceComponentName
-
- Required: Yes
- Type: string
A unique name to assign to the inference component.
- RuntimeConfig
-
- Required: Yes
- Type: InferenceComponentRuntimeConfig structure
Runtime settings for a model that is deployed with an inference component.
- Specification
-
- Required: Yes
- Type: InferenceComponentSpecification structure
Details about the resources to deploy with this inference component, including the model, container, and compute resources.
- Tags
-
- Type: Array of Tag structures
A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference.
- VariantName
-
- Required: Yes
- Type: string
The name of an existing production variant where you host the inference component.
Result Syntax
[ 'InferenceComponentArn' => '<string>', ]
Result Details
Members
- InferenceComponentArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the inference component.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateInferenceExperiment
$result = $client->createInferenceExperiment
([/* ... */]); $promise = $client->createInferenceExperimentAsync
([/* ... */]);
Creates an inference experiment using the configurations specified in the request.
Use this API to setup and schedule an experiment to compare model variants on a Amazon SageMaker inference endpoint. For more information about inference experiments, see Shadow tests.
Amazon SageMaker begins your experiment at the scheduled time and routes traffic to your endpoint's model variants based on your specified configuration.
While the experiment is in progress or after it has concluded, you can view metrics that compare your model variants. For more information, see View, monitor, and edit shadow tests.
Parameter Syntax
$result = $client->createInferenceExperiment([ 'DataStorageConfig' => [ 'ContentType' => [ 'CsvContentTypes' => ['<string>', ...], 'JsonContentTypes' => ['<string>', ...], ], 'Destination' => '<string>', // REQUIRED 'KmsKey' => '<string>', ], 'Description' => '<string>', 'EndpointName' => '<string>', // REQUIRED 'KmsKey' => '<string>', 'ModelVariants' => [ // REQUIRED [ 'InfrastructureConfig' => [ // REQUIRED 'InfrastructureType' => 'RealTimeInference', // REQUIRED 'RealTimeInferenceConfig' => [ // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge', // REQUIRED ], ], 'ModelName' => '<string>', // REQUIRED 'VariantName' => '<string>', // REQUIRED ], // ... ], 'Name' => '<string>', // REQUIRED 'RoleArn' => '<string>', // REQUIRED 'Schedule' => [ 'EndTime' => <integer || string || DateTime>, 'StartTime' => <integer || string || DateTime>, ], 'ShadowModeConfig' => [ // REQUIRED 'ShadowModelVariants' => [ // REQUIRED [ 'SamplingPercentage' => <integer>, // REQUIRED 'ShadowModelVariantName' => '<string>', // REQUIRED ], // ... ], 'SourceModelVariantName' => '<string>', // REQUIRED ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'Type' => 'ShadowMode', // REQUIRED ]);
Parameter Details
Members
- DataStorageConfig
-
- Type: InferenceExperimentDataStorageConfig structure
The Amazon S3 location and configuration for storing inference request and response data.
This is an optional parameter that you can use for data capture. For more information, see Capture data.
- Description
-
- Type: string
A description for the inference experiment.
- EndpointName
-
- Required: Yes
- Type: string
The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.
- KmsKey
-
- Type: string
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. The
KmsKey
can be any of the following formats:-
KMS key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
-
Amazon Resource Name (ARN) of a KMS key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
-
KMS key Alias
"alias/ExampleAlias"
-
Amazon Resource Name (ARN) of a KMS key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to call
kms:Encrypt
. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. Amazon SageMaker uses server-side encryption with KMS managed keys forOutputDataConfig
. If you use a bucket policy with ans3:PutObject
permission that only allows objects with server-side encryption, set the condition key ofs3:x-amz-server-side-encryption
to"aws:kms"
. For more information, see KMS managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your
CreateEndpoint
andUpdateEndpoint
requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide. - ModelVariants
-
- Required: Yes
- Type: Array of ModelVariantConfig structures
An array of
ModelVariantConfig
objects. There is one for each variant in the inference experiment. EachModelVariantConfig
object in the array describes the infrastructure configuration for the corresponding variant. - Name
-
- Required: Yes
- Type: string
The name for the inference experiment.
- RoleArn
-
- Required: Yes
- Type: string
The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
- Schedule
-
- Type: InferenceExperimentSchedule structure
The duration for which you want the inference experiment to run. If you don't specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.
- ShadowModeConfig
-
- Required: Yes
- Type: ShadowModeConfig structure
The configuration of
ShadowMode
inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates. - Tags
-
- Type: Array of Tag structures
Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.
- Type
-
- Required: Yes
- Type: string
The type of the inference experiment that you want to run. The following types of experiments are possible:
-
ShadowMode
: You can use this type to validate a shadow variant. For more information, see Shadow tests.
Result Syntax
[ 'InferenceExperimentArn' => '<string>', ]
Result Details
Members
- InferenceExperimentArn
-
- Required: Yes
- Type: string
The ARN for your inference experiment.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateInferenceRecommendationsJob
$result = $client->createInferenceRecommendationsJob
([/* ... */]); $promise = $client->createInferenceRecommendationsJobAsync
([/* ... */]);
Starts a recommendation job. You can create either an instance recommendation or load test job.
Parameter Syntax
$result = $client->createInferenceRecommendationsJob([ 'InputConfig' => [ // REQUIRED 'ContainerConfig' => [ 'DataInputConfig' => '<string>', 'Domain' => '<string>', 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'NearestModelName' => '<string>', 'PayloadConfig' => [ 'SamplePayloadUrl' => '<string>', 'SupportedContentTypes' => ['<string>', ...], ], 'SupportedEndpointType' => 'RealTime|Serverless', 'SupportedInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'Task' => '<string>', ], 'EndpointConfigurations' => [ [ 'EnvironmentParameterRanges' => [ 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', // REQUIRED 'Value' => ['<string>', ...], // REQUIRED ], // ... ], ], 'InferenceSpecificationName' => '<string>', 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.12xlarge|ml.m5d.24xlarge|ml.c4.large|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.large|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.12xlarge|ml.r5.24xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.12xlarge|ml.r5d.24xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.dl1.24xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.p4d.24xlarge|ml.c7g.large|ml.c7g.xlarge|ml.c7g.2xlarge|ml.c7g.4xlarge|ml.c7g.8xlarge|ml.c7g.12xlarge|ml.c7g.16xlarge|ml.m6g.large|ml.m6g.xlarge|ml.m6g.2xlarge|ml.m6g.4xlarge|ml.m6g.8xlarge|ml.m6g.12xlarge|ml.m6g.16xlarge|ml.m6gd.large|ml.m6gd.xlarge|ml.m6gd.2xlarge|ml.m6gd.4xlarge|ml.m6gd.8xlarge|ml.m6gd.12xlarge|ml.m6gd.16xlarge|ml.c6g.large|ml.c6g.xlarge|ml.c6g.2xlarge|ml.c6g.4xlarge|ml.c6g.8xlarge|ml.c6g.12xlarge|ml.c6g.16xlarge|ml.c6gd.large|ml.c6gd.xlarge|ml.c6gd.2xlarge|ml.c6gd.4xlarge|ml.c6gd.8xlarge|ml.c6gd.12xlarge|ml.c6gd.16xlarge|ml.c6gn.large|ml.c6gn.xlarge|ml.c6gn.2xlarge|ml.c6gn.4xlarge|ml.c6gn.8xlarge|ml.c6gn.12xlarge|ml.c6gn.16xlarge|ml.r6g.large|ml.r6g.xlarge|ml.r6g.2xlarge|ml.r6g.4xlarge|ml.r6g.8xlarge|ml.r6g.12xlarge|ml.r6g.16xlarge|ml.r6gd.large|ml.r6gd.xlarge|ml.r6gd.2xlarge|ml.r6gd.4xlarge|ml.r6gd.8xlarge|ml.r6gd.12xlarge|ml.r6gd.16xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.p5.48xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge', 'ServerlessConfig' => [ 'MaxConcurrency' => <integer>, // REQUIRED 'MemorySizeInMB' => <integer>, // REQUIRED 'ProvisionedConcurrency' => <integer>, ], ], // ... ], 'Endpoints' => [ [ 'EndpointName' => '<string>', ], // ... ], 'JobDurationInSeconds' => <integer>, 'ModelName' => '<string>', 'ModelPackageVersionArn' => '<string>', 'ResourceLimit' => [ 'MaxNumberOfTests' => <integer>, 'MaxParallelOfTests' => <integer>, ], 'TrafficPattern' => [ 'Phases' => [ [ 'DurationInSeconds' => <integer>, 'InitialNumberOfUsers' => <integer>, 'SpawnRate' => <integer>, ], // ... ], 'Stairs' => [ 'DurationInSeconds' => <integer>, 'NumberOfSteps' => <integer>, 'UsersPerStep' => <integer>, ], 'TrafficType' => 'PHASES|STAIRS', ], 'VolumeKmsKeyId' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], 'JobDescription' => '<string>', 'JobName' => '<string>', // REQUIRED 'JobType' => 'Default|Advanced', // REQUIRED 'OutputConfig' => [ 'CompiledOutputConfig' => [ 'S3OutputUri' => '<string>', ], 'KmsKeyId' => '<string>', ], 'RoleArn' => '<string>', // REQUIRED 'StoppingConditions' => [ 'FlatInvocations' => 'Continue|Stop', 'MaxInvocations' => <integer>, 'ModelLatencyThresholds' => [ [ 'Percentile' => '<string>', 'ValueInMilliseconds' => <integer>, ], // ... ], ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- InputConfig
-
- Required: Yes
- Type: RecommendationJobInputConfig structure
Provides information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations.
- JobDescription
-
- Type: string
Description of the recommendation job.
- JobName
-
- Required: Yes
- Type: string
A name for the recommendation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account. The job name is passed down to the resources created by the recommendation job. The names of resources (such as the model, endpoint configuration, endpoint, and compilation) that are prefixed with the job name are truncated at 40 characters.
- JobType
-
- Required: Yes
- Type: string
Defines the type of recommendation job. Specify
Default
to initiate an instance recommendation andAdvanced
to initiate a load test. If left unspecified, Amazon SageMaker Inference Recommender will run an instance recommendation (DEFAULT
) job. - OutputConfig
-
- Type: RecommendationJobOutputConfig structure
Provides information about the output artifacts and the KMS key to use for Amazon S3 server-side encryption.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
- StoppingConditions
-
- Type: RecommendationJobStoppingConditions structure
A set of conditions for stopping a recommendation job. If any of the conditions are met, the job is automatically stopped.
- Tags
-
- Type: Array of Tag structures
The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define. For more information, see Tagging Amazon Web Services Resources in the Amazon Web Services General Reference.
Result Syntax
[ 'JobArn' => '<string>', ]
Result Details
Members
- JobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the recommendation job.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateLabelingJob
$result = $client->createLabelingJob
([/* ... */]); $promise = $client->createLabelingJobAsync
([/* ... */]);
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 Amazon Web Services 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.
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.
The output can be used as the manifest file for another labeling job or as training data for your machine learning models.
You can use this operation to create a static labeling job or a streaming labeling job. A static labeling job stops if all data objects in the input manifest file identified in ManifestS3Uri
have been labeled. A streaming labeling job runs perpetually until it is manually stopped, or remains idle for 10 days. You can send new data objects to an active (InProgress
) streaming labeling job in real time. To learn how to create a static labeling job, see Create a Labeling Job (API) in the Amazon SageMaker Developer Guide. To learn how to create a streaming labeling job, see Create a Streaming Labeling Job.
Parameter Syntax
$result = $client->createLabelingJob([ 'HumanTaskConfig' => [ // REQUIRED 'AnnotationConsolidationConfig' => [ // REQUIRED 'AnnotationConsolidationLambdaArn' => '<string>', // REQUIRED ], 'MaxConcurrentTaskCount' => <integer>, 'NumberOfHumanWorkersPerDataObject' => <integer>, // REQUIRED 'PreHumanTaskLambdaArn' => '<string>', // REQUIRED 'PublicWorkforceTaskPrice' => [ 'AmountInUsd' => [ 'Cents' => <integer>, 'Dollars' => <integer>, 'TenthFractionsOfACent' => <integer>, ], ], 'TaskAvailabilityLifetimeInSeconds' => <integer>, 'TaskDescription' => '<string>', // REQUIRED 'TaskKeywords' => ['<string>', ...], 'TaskTimeLimitInSeconds' => <integer>, // REQUIRED 'TaskTitle' => '<string>', // REQUIRED 'UiConfig' => [ // REQUIRED 'HumanTaskUiArn' => '<string>', 'UiTemplateS3Uri' => '<string>', ], 'WorkteamArn' => '<string>', // REQUIRED ], 'InputConfig' => [ // REQUIRED 'DataAttributes' => [ 'ContentClassifiers' => ['<string>', ...], ], 'DataSource' => [ // REQUIRED 'S3DataSource' => [ 'ManifestS3Uri' => '<string>', // REQUIRED ], 'SnsDataSource' => [ 'SnsTopicArn' => '<string>', // REQUIRED ], ], ], 'LabelAttributeName' => '<string>', // REQUIRED 'LabelCategoryConfigS3Uri' => '<string>', 'LabelingJobAlgorithmsConfig' => [ 'InitialActiveLearningModelArn' => '<string>', 'LabelingJobAlgorithmSpecificationArn' => '<string>', // REQUIRED 'LabelingJobResourceConfig' => [ 'VolumeKmsKeyId' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], ], 'LabelingJobName' => '<string>', // REQUIRED 'OutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED 'SnsTopicArn' => '<string>', ], 'RoleArn' => '<string>', // REQUIRED 'StoppingConditions' => [ 'MaxHumanLabeledObjectCount' => <integer>, 'MaxPercentageOfInputDatasetLabeled' => <integer>, ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- HumanTaskConfig
-
- Required: Yes
- Type: HumanTaskConfig structure
Configures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).
- InputConfig
-
- Required: Yes
- Type: LabelingJobInputConfig structure
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.
You must specify at least one of the following:
S3DataSource
orSnsDataSource
.-
Use
SnsDataSource
to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled. -
Use
S3DataSource
to specify an input manifest file for both streaming and one-time labeling jobs. Adding anS3DataSource
is optional if you useSnsDataSource
to create a streaming labeling job.
If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use
ContentClassifiers
to specify that your data is free of personally identifiable information and adult content. - LabelAttributeName
-
- Required: Yes
- Type: string
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
LabelAttributeName
must meet the following requirements.-
The name can't end with "-metadata".
-
If you are using one of the following built-in task types, the attribute name must end with "-ref". If the task type you are using is not listed below, the attribute name must not end with "-ref".
-
Image semantic segmentation (
SemanticSegmentation)
, and adjustment (AdjustmentSemanticSegmentation
) and verification (VerificationSemanticSegmentation
) labeling jobs for this task type. -
Video frame object detection (
VideoObjectDetection
), and adjustment and verification (AdjustmentVideoObjectDetection
) labeling jobs for this task type. -
Video frame object tracking (
VideoObjectTracking
), and adjustment and verification (AdjustmentVideoObjectTracking
) labeling jobs for this task type. -
3D point cloud semantic segmentation (
3DPointCloudSemanticSegmentation
), and adjustment and verification (Adjustment3DPointCloudSemanticSegmentation
) labeling jobs for this task type. -
3D point cloud object tracking (
3DPointCloudObjectTracking
), and adjustment and verification (Adjustment3DPointCloudObjectTracking
) labeling jobs for this task type.
-
If you are creating an adjustment or verification labeling job, you must use a different
LabelAttributeName
than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see Verify and Adjust Labels. - LabelCategoryConfigS3Uri
-
- Type: string
The S3 URI of the file, referred to as a label category configuration file, that defines the categories used to label the data objects.
For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see Create a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.
For named entity recognition jobs, in addition to
"labels"
, you must provide worker instructions in the label category configuration file using the"instructions"
parameter:"instructions": {"shortInstruction":"<h1>Add header</h1><p>Add Instructions</p>", "fullInstruction":"<p>Add additional instructions.</p>"}
. For details and an example, see Create a Named Entity Recognition Labeling Job (API) .For all other built-in task types and custom tasks, 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"}]
}
Note the following about the label category configuration file:
-
For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.
-
Each label category must be unique, you cannot specify duplicate label categories.
-
If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include
auditLabelAttributeName
in the label category configuration. Use this parameter to enter theLabelAttributeName
of the labeling job you want to adjust or verify annotations of.
- LabelingJobAlgorithmsConfig
-
- Type: LabelingJobAlgorithmsConfig structure
Configures the information required to perform automated data labeling.
- LabelingJobName
-
- Required: Yes
- Type: string
The name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region.
LabelingJobName
is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth. - OutputConfig
-
- Required: Yes
- Type: LabelingJobOutputConfig structure
The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
- RoleArn
-
- Required: Yes
- Type: string
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.
- StoppingConditions
-
- Type: LabelingJobStoppingConditions structure
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.
- Tags
-
- Type: Array of Tag structures
An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
Result Syntax
[ 'LabelingJobArn' => '<string>', ]
Result Details
Members
- LabelingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify the labeling job.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateMlflowTrackingServer
$result = $client->createMlflowTrackingServer
([/* ... */]); $promise = $client->createMlflowTrackingServerAsync
([/* ... */]);
Creates an MLflow Tracking Server using a general purpose Amazon S3 bucket as the artifact store. For more information, see Create an MLflow Tracking Server.
Parameter Syntax
$result = $client->createMlflowTrackingServer([ 'ArtifactStoreUri' => '<string>', // REQUIRED 'AutomaticModelRegistration' => true || false, 'MlflowVersion' => '<string>', 'RoleArn' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'TrackingServerName' => '<string>', // REQUIRED 'TrackingServerSize' => 'Small|Medium|Large', 'WeeklyMaintenanceWindowStart' => '<string>', ]);
Parameter Details
Members
- ArtifactStoreUri
-
- Required: Yes
- Type: string
The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
- AutomaticModelRegistration
-
- Type: boolean
Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry. To enable automatic model registration, set this value to
True
. To disable automatic model registration, set this value toFalse
. If not specified,AutomaticModelRegistration
defaults toFalse
. - MlflowVersion
-
- Type: string
The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) for an IAM role in your account that the MLflow Tracking Server uses to access the artifact store in Amazon S3. The role should have
AmazonS3FullAccess
permissions. For more information on IAM permissions for tracking server creation, see Set up IAM permissions for MLflow. - Tags
-
- Type: Array of Tag structures
Tags consisting of key-value pairs used to manage metadata for the tracking server.
- TrackingServerName
-
- Required: Yes
- Type: string
A unique string identifying the tracking server name. This string is part of the tracking server ARN.
- TrackingServerSize
-
- Type: string
The size of the tracking server you want to create. You can choose between
"Small"
,"Medium"
, and"Large"
. The default MLflow Tracking Server configuration size is"Small"
. You can choose a size depending on the projected use of the tracking server such as the volume of data logged, number of users, and frequency of use.We recommend using a small tracking server for teams of up to 25 users, a medium tracking server for teams of up to 50 users, and a large tracking server for teams of up to 100 users.
- WeeklyMaintenanceWindowStart
-
- Type: string
The day and time of the week in Coordinated Universal Time (UTC) 24-hour standard time that weekly maintenance updates are scheduled. For example: TUE:03:30.
Result Syntax
[ 'TrackingServerArn' => '<string>', ]
Result Details
Members
- TrackingServerArn
-
- Type: string
The ARN of the tracking server.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateModel
$result = $client->createModel
([/* ... */]); $promise = $client->createModelAsync
([/* ... */]);
Creates a model in 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 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. SageMaker then deploys all of the containers that you defined for the model in the hosting environment.
To run a batch transform using your model, you start a job with the CreateTransformJob
API. SageMaker uses your model and your dataset to get inferences which are then saved to a specified S3 location.
In the request, you also provide an IAM role that 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 Amazon Web Services resources, you grant necessary permissions via this role.
Parameter Syntax
$result = $client->createModel([ 'Containers' => [ [ 'AdditionalModelDataSources' => [ [ 'ChannelName' => '<string>', // REQUIRED 'S3DataSource' => [ // REQUIRED 'CompressionType' => 'None|Gzip', // REQUIRED 'HubAccessConfig' => [ 'HubContentArn' => '<string>', // REQUIRED ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, // REQUIRED ], 'S3DataType' => 'S3Prefix|S3Object', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], // ... ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ImageConfig' => [ 'RepositoryAccessMode' => 'Platform|Vpc', // REQUIRED 'RepositoryAuthConfig' => [ 'RepositoryCredentialsProviderArn' => '<string>', // REQUIRED ], ], 'InferenceSpecificationName' => '<string>', 'Mode' => 'SingleModel|MultiModel', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', // REQUIRED 'HubAccessConfig' => [ 'HubContentArn' => '<string>', // REQUIRED ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, // REQUIRED ], 'S3DataType' => 'S3Prefix|S3Object', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'ModelDataUrl' => '<string>', 'ModelPackageName' => '<string>', 'MultiModelConfig' => [ 'ModelCacheSetting' => 'Enabled|Disabled', ], ], // ... ], 'EnableNetworkIsolation' => true || false, 'ExecutionRoleArn' => '<string>', 'InferenceExecutionConfig' => [ 'Mode' => 'Serial|Direct', // REQUIRED ], 'ModelName' => '<string>', // REQUIRED 'PrimaryContainer' => [ 'AdditionalModelDataSources' => [ [ 'ChannelName' => '<string>', // REQUIRED 'S3DataSource' => [ // REQUIRED 'CompressionType' => 'None|Gzip', // REQUIRED 'HubAccessConfig' => [ 'HubContentArn' => '<string>', // REQUIRED ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, // REQUIRED ], 'S3DataType' => 'S3Prefix|S3Object', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], // ... ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ImageConfig' => [ 'RepositoryAccessMode' => 'Platform|Vpc', // REQUIRED 'RepositoryAuthConfig' => [ 'RepositoryCredentialsProviderArn' => '<string>', // REQUIRED ], ], 'InferenceSpecificationName' => '<string>', 'Mode' => 'SingleModel|MultiModel', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', // REQUIRED 'HubAccessConfig' => [ 'HubContentArn' => '<string>', // REQUIRED ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, // REQUIRED ], 'S3DataType' => 'S3Prefix|S3Object', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'ModelDataUrl' => '<string>', 'ModelPackageName' => '<string>', 'MultiModelConfig' => [ 'ModelCacheSetting' => 'Enabled|Disabled', ], ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ]);
Parameter Details
Members
- Containers
-
- Type: Array of ContainerDefinition structures
Specifies the containers in the inference pipeline.
- EnableNetworkIsolation
-
- Type: boolean
Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
- ExecutionRoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute instances is part of model hosting. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the
iam:PassRole
permission. - InferenceExecutionConfig
-
- Type: InferenceExecutionConfig structure
Specifies details of how containers in a multi-container endpoint are called.
- ModelName
-
- Required: Yes
- Type: string
The name of the new model.
- PrimaryContainer
-
- Type: ContainerDefinition structure
The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
- VpcConfig
-
- Type: VpcConfig structure
A VpcConfig object that specifies the VPC that you want your model to connect to. Control access to and from your model container by configuring the VPC.
VpcConfig
is used in hosting services and in batch transform. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Data in Batch Transform Jobs by Using an Amazon Virtual Private Cloud.
Result Syntax
[ 'ModelArn' => '<string>', ]
Result Details
Members
- ModelArn
-
- Required: Yes
- Type: string
The ARN of the model created in SageMaker.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateModelBiasJobDefinition
$result = $client->createModelBiasJobDefinition
([/* ... */]); $promise = $client->createModelBiasJobDefinitionAsync
([/* ... */]);
Creates the definition for a model bias job.
Parameter Syntax
$result = $client->createModelBiasJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED 'JobResources' => [ // REQUIRED 'ClusterConfig' => [ // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', // REQUIRED 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], ], 'ModelBiasAppSpecification' => [ // REQUIRED 'ConfigUri' => '<string>', // REQUIRED 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', // REQUIRED ], 'ModelBiasBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], ], 'ModelBiasJobInput' => [ // REQUIRED 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', // REQUIRED 'DatasetFormat' => [ // REQUIRED 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', // REQUIRED 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', // REQUIRED 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', // REQUIRED 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'GroundTruthS3Input' => [ // REQUIRED 'S3Uri' => '<string>', ], ], 'ModelBiasJobOutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ // REQUIRED [ 'S3Output' => [ // REQUIRED 'LocalPath' => '<string>', // REQUIRED 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', // REQUIRED ], ], // ... ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], 'RoleArn' => '<string>', // REQUIRED 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, // REQUIRED ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
- JobResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources to deploy for a monitoring job.
- ModelBiasAppSpecification
-
- Required: Yes
- Type: ModelBiasAppSpecification structure
Configures the model bias job to run a specified Docker container image.
- ModelBiasBaselineConfig
-
- Type: ModelBiasBaselineConfig structure
The baseline configuration for a model bias job.
- ModelBiasJobInput
-
- Required: Yes
- Type: ModelBiasJobInput structure
Inputs for the model bias job.
- ModelBiasJobOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The output configuration for monitoring jobs.
- NetworkConfig
-
- Type: MonitoringNetworkConfig structure
Networking options for a model bias job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
A time limit for how long the monitoring job is allowed to run before stopping.
- Tags
-
- Type: Array of Tag structures
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
Result Syntax
[ 'JobDefinitionArn' => '<string>', ]
Result Details
Members
- JobDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model bias job.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
CreateModelCard
$result = $client->createModelCard
([/* ... */]); $promise = $client->createModelCardAsync
([/* ... */]);
Creates an Amazon SageMaker Model Card.
For information about how to use model cards, see Amazon SageMaker Model Card.
Parameter Syntax
$result = $client->createModelCard([ 'Content' => '<string>', // REQUIRED 'ModelCardName' => '<string>', // REQUIRED 'ModelCardStatus' => 'Draft|PendingReview|Approved|Archived', // REQUIRED 'SecurityConfig' => [ 'KmsKeyId' => '<string>', ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- Content
-
- Required: Yes
- Type: string
The content of the model card. Content must be in model card JSON schema and provided as a string.
- ModelCardName
-
- Required: Yes
- Type: string
The unique name of the model card.
- ModelCardStatus
-
- Required: Yes
- Type: string
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
-
Draft
: The model card is a work in progress. -
PendingReview
: The model card is pending review. -
Approved
: The model card is approved. -
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
- SecurityConfig
-
- Type: ModelCardSecurityConfig structure
An optional Key Management Service key to encrypt, decrypt, and re-encrypt model card content for regulated workloads with highly sensitive data.
- Tags
-
- Type: Array of Tag structures
Key-value pairs used to manage metadata for model cards.
Result Syntax
[ 'ModelCardArn' => '<string>', ]
Result Details
Members
- ModelCardArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the successfully created model card.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
CreateModelCardExportJob
$result = $client->createModelCardExportJob
([/* ... */]); $promise = $client->createModelCardExportJobAsync
([/* ... */]);
Creates an Amazon SageMaker Model Card export job.
Parameter Syntax
$result = $client->createModelCardExportJob([ 'ModelCardExportJobName' => '<string>', // REQUIRED 'ModelCardName' => '<string>', // REQUIRED 'ModelCardVersion' => <integer>, 'OutputConfig' => [ // REQUIRED 'S3OutputPath' => '<string>', // REQUIRED ], ]);
Parameter Details
Members
- ModelCardExportJobName
-
- Required: Yes
- Type: string
The name of the model card export job.
- ModelCardName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the model card to export.
- ModelCardVersion
-
- Type: int
The version of the model card to export. If a version is not provided, then the latest version of the model card is exported.
- OutputConfig
-
- Required: Yes
- Type: ModelCardExportOutputConfig structure
The model card output configuration that specifies the Amazon S3 path for exporting.
Result Syntax
[ 'ModelCardExportJobArn' => '<string>', ]
Result Details
Members
- ModelCardExportJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model card export job.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
CreateModelExplainabilityJobDefinition
$result = $client->createModelExplainabilityJobDefinition
([/* ... */]); $promise = $client->createModelExplainabilityJobDefinitionAsync
([/* ... */]);
Creates the definition for a model explainability job.
Parameter Syntax
$result = $client->createModelExplainabilityJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED 'JobResources' => [ // REQUIRED 'ClusterConfig' => [ // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', // REQUIRED 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], ], 'ModelExplainabilityAppSpecification' => [ // REQUIRED 'ConfigUri' => '<string>', // REQUIRED 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', // REQUIRED ], 'ModelExplainabilityBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], ], 'ModelExplainabilityJobInput' => [ // REQUIRED 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', // REQUIRED 'DatasetFormat' => [ // REQUIRED 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', // REQUIRED 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', // REQUIRED 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', // REQUIRED 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], ], 'ModelExplainabilityJobOutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ // REQUIRED [ 'S3Output' => [ // REQUIRED 'LocalPath' => '<string>', // REQUIRED 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', // REQUIRED ], ], // ... ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], 'RoleArn' => '<string>', // REQUIRED 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, // REQUIRED ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
- JobResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources to deploy for a monitoring job.
- ModelExplainabilityAppSpecification
-
- Required: Yes
- Type: ModelExplainabilityAppSpecification structure
Configures the model explainability job to run a specified Docker container image.
- ModelExplainabilityBaselineConfig
-
- Type: ModelExplainabilityBaselineConfig structure
The baseline configuration for a model explainability job.
- ModelExplainabilityJobInput
-
- Required: Yes
- Type: ModelExplainabilityJobInput structure
Inputs for the model explainability job.
- ModelExplainabilityJobOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The output configuration for monitoring jobs.
- NetworkConfig
-
- Type: MonitoringNetworkConfig structure
Networking options for a model explainability job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
A time limit for how long the monitoring job is allowed to run before stopping.
- Tags
-
- Type: Array of Tag structures
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
Result Syntax
[ 'JobDefinitionArn' => '<string>', ]
Result Details
Members
- JobDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model explainability job.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
CreateModelPackage
$result = $client->createModelPackage
([/* ... */]); $promise = $client->createModelPackageAsync
([/* ... */]);
Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in 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 Amazon Web Services 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.
Parameter Syntax
$result = $client->createModelPackage([ 'AdditionalInferenceSpecifications' => [ [ 'Containers' => [ // REQUIRED [ 'AdditionalS3DataSource' => [ 'CompressionType' => 'None|Gzip', 'S3DataType' => 'S3Object|S3Prefix', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'Image' => '<string>', // REQUIRED 'ImageDigest' => '<string>', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', // REQUIRED 'HubAccessConfig' => [ 'HubContentArn' => '<string>', // REQUIRED ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, // REQUIRED ], 'S3DataType' => 'S3Prefix|S3Object', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'ModelDataUrl' => '<string>', 'ModelInput' => [ 'DataInputConfig' => '<string>', // REQUIRED ], 'NearestModelName' => '<string>', 'ProductId' => '<string>', ], // ... ], 'Description' => '<string>', 'Name' => '<string>', // REQUIRED 'SupportedContentTypes' => ['<string>', ...], 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'SupportedTransformInstanceTypes' => ['<string>', ...], ], // ... ], 'CertifyForMarketplace' => true || false, 'ClientToken' => '<string>', 'CustomerMetadataProperties' => ['<string>', ...], 'Domain' => '<string>', 'DriftCheckBaselines' => [ 'Bias' => [ 'ConfigFile' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', // REQUIRED ], 'PostTrainingConstraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'PreTrainingConstraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'Explainability' => [ 'ConfigFile' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', // REQUIRED ], 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'ModelDataQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'ModelQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], ], 'InferenceSpecification' => [ 'Containers' => [ // REQUIRED [ 'AdditionalS3DataSource' => [ 'CompressionType' => 'None|Gzip', 'S3DataType' => 'S3Object|S3Prefix', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'Image' => '<string>', // REQUIRED 'ImageDigest' => '<string>', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', // REQUIRED 'HubAccessConfig' => [ 'HubContentArn' => '<string>', // REQUIRED ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, // REQUIRED ], 'S3DataType' => 'S3Prefix|S3Object', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'ModelDataUrl' => '<string>', 'ModelInput' => [ 'DataInputConfig' => '<string>', // REQUIRED ], 'NearestModelName' => '<string>', 'ProductId' => '<string>', ], // ... ], 'SupportedContentTypes' => ['<string>', ...], 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'SupportedTransformInstanceTypes' => ['<string>', ...], ], 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'ModelApprovalStatus' => 'Approved|Rejected|PendingManualApproval', 'ModelCard' => [ 'ModelCardContent' => '<string>', 'ModelCardStatus' => 'Draft|PendingReview|Approved|Archived', ], 'ModelMetrics' => [ 'Bias' => [ 'PostTrainingReport' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'PreTrainingReport' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'Report' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'Explainability' => [ 'Report' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'ModelDataQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'ModelQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], ], 'ModelPackageDescription' => '<string>', 'ModelPackageGroupName' => '<string>', 'ModelPackageName' => '<string>', 'SamplePayloadUrl' => '<string>', 'SecurityConfig' => [ 'KmsKeyId' => '<string>', // REQUIRED ], 'SkipModelValidation' => 'All|None', 'SourceAlgorithmSpecification' => [ 'SourceAlgorithms' => [ // REQUIRED [ 'AlgorithmName' => '<string>', // REQUIRED 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', // REQUIRED 'HubAccessConfig' => [ 'HubContentArn' => '<string>', // REQUIRED ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, // REQUIRED ], 'S3DataType' => 'S3Prefix|S3Object', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'ModelDataUrl' => '<string>', ], // ... ], ], 'SourceUri' => '<string>', 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'Task' => '<string>', 'ValidationSpecification' => [ 'ValidationProfiles' => [ // REQUIRED [ 'ProfileName' => '<string>', // REQUIRED 'TransformJobDefinition' => [ // REQUIRED 'BatchStrategy' => 'MultiRecord|SingleRecord', 'Environment' => ['<string>', ...], 'MaxConcurrentTransforms' => <integer>, 'MaxPayloadInMB' => <integer>, 'TransformInput' => [ // REQUIRED 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ // REQUIRED 'S3DataSource' => [ // REQUIRED 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'SplitType' => 'None|Line|RecordIO|TFRecord', ], 'TransformOutput' => [ // REQUIRED 'Accept' => '<string>', 'AssembleWith' => 'None|Line', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'TransformResources' => [ // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge', // REQUIRED 'VolumeKmsKeyId' => '<string>', ], ], ], // ... ], 'ValidationRole' => '<string>', // REQUIRED ], ]);
Parameter Details
Members
- AdditionalInferenceSpecifications
-
- Type: Array of AdditionalInferenceSpecificationDefinition structures
An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
- CertifyForMarketplace
-
- Type: boolean
Whether to certify the model package for listing on Amazon Web Services Marketplace.
This parameter is optional for unversioned models, and does not apply to versioned models.
- ClientToken
-
- Type: string
A unique token that guarantees that the call to this API is idempotent.
- CustomerMetadataProperties
-
- Type: Associative array of custom strings keys (CustomerMetadataKey) to strings
The metadata properties associated with the model package versions.
- Domain
-
- Type: string
The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
- DriftCheckBaselines
-
- Type: DriftCheckBaselines structure
Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
- InferenceSpecification
-
- Type: InferenceSpecification structure
Specifies details about inference jobs that you can run with models based on this model package, including the following information:
-
The Amazon ECR paths of containers that contain the inference code and model artifacts.
-
The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
-
The input and output content formats that the model package supports for inference.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- ModelApprovalStatus
-
- Type: string
Whether the model is approved for deployment.
This parameter is optional for versioned models, and does not apply to unversioned models.
For versioned models, the value of this parameter must be set to
Approved
to deploy the model. - ModelCard
-
- Type: ModelPackageModelCard structure
The model card associated with the model package. Since
ModelPackageModelCard
is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema ofModelCard
. TheModelPackageModelCard
schema does not includemodel_package_details
, andmodel_overview
is composed of themodel_creator
andmodel_artifact
properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version. - ModelMetrics
-
- Type: ModelMetrics structure
A structure that contains model metrics reports.
- ModelPackageDescription
-
- Type: string
A description of the model package.
- ModelPackageGroupName
-
- Type: string
The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.
This parameter is required for versioned models, and does not apply to unversioned models.
- ModelPackageName
-
- Type: string
The name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
This parameter is required for unversioned models. It is not applicable to versioned models.
- SamplePayloadUrl
-
- Type: string
The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the InvokeEndpoint call.
- SecurityConfig
-
- Type: ModelPackageSecurityConfig structure
The KMS Key ID (
KMSKeyId
) used for encryption of model package information. - SkipModelValidation
-
- Type: string
Indicates if you want to skip model validation.
- SourceAlgorithmSpecification
-
- Type: SourceAlgorithmSpecification structure
Details about the algorithm that was used to create the model package.
- SourceUri
-
- Type: string
The URI of the source for the model package. If you want to clone a model package, set it to the model package Amazon Resource Name (ARN). If you want to register a model, set it to the model ARN.
- Tags
-
- Type: Array of Tag structures
A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
If you supply
ModelPackageGroupName
, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply atag
argument. - Task
-
- Type: string
The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification. The following tasks are supported by Inference Recommender:
"IMAGE_CLASSIFICATION"
|"OBJECT_DETECTION"
|"TEXT_GENERATION"
|"IMAGE_SEGMENTATION"
|"FILL_MASK"
|"CLASSIFICATION"
|"REGRESSION"
|"OTHER"
.Specify "OTHER" if none of the tasks listed fit your use case.
- ValidationSpecification
-
- Type: ModelPackageValidationSpecification structure
Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.
Result Syntax
[ 'ModelPackageArn' => '<string>', ]
Result Details
Members
- ModelPackageArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the new model package.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateModelPackageGroup
$result = $client->createModelPackageGroup
([/* ... */]); $promise = $client->createModelPackageGroupAsync
([/* ... */]);
Creates a model group. A model group contains a group of model versions.
Parameter Syntax
$result = $client->createModelPackageGroup([ 'ModelPackageGroupDescription' => '<string>', 'ModelPackageGroupName' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- ModelPackageGroupDescription
-
- Type: string
A description for the model group.
- ModelPackageGroupName
-
- Required: Yes
- Type: string
The name of the model group.
- Tags
-
- Type: Array of Tag structures
A list of key value pairs associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
Result Syntax
[ 'ModelPackageGroupArn' => '<string>', ]
Result Details
Members
- ModelPackageGroupArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model group.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateModelQualityJobDefinition
$result = $client->createModelQualityJobDefinition
([/* ... */]); $promise = $client->createModelQualityJobDefinitionAsync
([/* ... */]);
Creates a definition for a job that monitors model quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
Parameter Syntax
$result = $client->createModelQualityJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED 'JobResources' => [ // REQUIRED 'ClusterConfig' => [ // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', // REQUIRED 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], ], 'ModelQualityAppSpecification' => [ // REQUIRED 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', // REQUIRED 'PostAnalyticsProcessorSourceUri' => '<string>', 'ProblemType' => 'BinaryClassification|MulticlassClassification|Regression', 'RecordPreprocessorSourceUri' => '<string>', ], 'ModelQualityBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], ], 'ModelQualityJobInput' => [ // REQUIRED 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', // REQUIRED 'DatasetFormat' => [ // REQUIRED 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', // REQUIRED 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', // REQUIRED 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', // REQUIRED 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'GroundTruthS3Input' => [ // REQUIRED 'S3Uri' => '<string>', ], ], 'ModelQualityJobOutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ // REQUIRED [ 'S3Output' => [ // REQUIRED 'LocalPath' => '<string>', // REQUIRED 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', // REQUIRED ], ], // ... ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], 'RoleArn' => '<string>', // REQUIRED 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, // REQUIRED ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the monitoring job definition.
- JobResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources to deploy for a monitoring job.
- ModelQualityAppSpecification
-
- Required: Yes
- Type: ModelQualityAppSpecification structure
The container that runs the monitoring job.
- ModelQualityBaselineConfig
-
- Type: ModelQualityBaselineConfig structure
Specifies the constraints and baselines for the monitoring job.
- ModelQualityJobInput
-
- Required: Yes
- Type: ModelQualityJobInput structure
A list of the inputs that are monitored. Currently endpoints are supported.
- ModelQualityJobOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The output configuration for monitoring jobs.
- NetworkConfig
-
- Type: MonitoringNetworkConfig structure
Specifies the network configuration for the monitoring job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
A time limit for how long the monitoring job is allowed to run before stopping.
- Tags
-
- Type: Array of Tag structures
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
Result Syntax
[ 'JobDefinitionArn' => '<string>', ]
Result Details
Members
- JobDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model quality monitoring job.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
CreateMonitoringSchedule
$result = $client->createMonitoringSchedule
([/* ... */]); $promise = $client->createMonitoringScheduleAsync
([/* ... */]);
Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endpoint.
Parameter Syntax
$result = $client->createMonitoringSchedule([ 'MonitoringScheduleConfig' => [ // REQUIRED 'MonitoringJobDefinition' => [ 'BaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], 'StatisticsResource' => [ 'S3Uri' => '<string>', ], ], 'Environment' => ['<string>', ...], 'MonitoringAppSpecification' => [ // REQUIRED 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ImageUri' => '<string>', // REQUIRED 'PostAnalyticsProcessorSourceUri' => '<string>', 'RecordPreprocessorSourceUri' => '<string>', ], 'MonitoringInputs' => [ // REQUIRED [ 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', // REQUIRED 'DatasetFormat' => [ // REQUIRED 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', // REQUIRED 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', // REQUIRED 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', // REQUIRED 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], ], // ... ], 'MonitoringOutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ // REQUIRED [ 'S3Output' => [ // REQUIRED 'LocalPath' => '<string>', // REQUIRED 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', // REQUIRED ], ], // ... ], ], 'MonitoringResources' => [ // REQUIRED 'ClusterConfig' => [ // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', // REQUIRED 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], 'RoleArn' => '<string>', // REQUIRED 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, // REQUIRED ], ], 'MonitoringJobDefinitionName' => '<string>', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'ScheduleConfig' => [ 'DataAnalysisEndTime' => '<string>', 'DataAnalysisStartTime' => '<string>', 'ScheduleExpression' => '<string>', // REQUIRED ], ], 'MonitoringScheduleName' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- MonitoringScheduleConfig
-
- Required: Yes
- Type: MonitoringScheduleConfig structure
The configuration object that specifies the monitoring schedule and defines the monitoring job.
- MonitoringScheduleName
-
- Required: Yes
- Type: string
The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
- Tags
-
- Type: Array of Tag structures
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
Result Syntax
[ 'MonitoringScheduleArn' => '<string>', ]
Result Details
Members
- MonitoringScheduleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the monitoring schedule.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
CreateNotebookInstance
$result = $client->createNotebookInstance
([/* ... */]); $promise = $client->createNotebookInstanceAsync
([/* ... */]);
Creates an 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. 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.
SageMaker also provides a set of example notebooks. Each notebook demonstrates how to use SageMaker with a specific algorithm or with a machine learning framework.
After receiving the request, SageMaker does the following:
-
Creates a network interface in the SageMaker VPC.
-
(Option) If you specified
SubnetId
, 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, 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 SageMaker VPC. If you specified
SubnetId
of your VPC, 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, SageMaker returns its Amazon Resource Name (ARN). You can't change the name of a notebook instance after you create it.
After 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 SageMaker endpoints, and validate hosted models.
For more information, see How It Works.
Parameter Syntax
$result = $client->createNotebookInstance([ 'AcceleratorTypes' => ['<string>', ...], 'AdditionalCodeRepositories' => ['<string>', ...], 'DefaultCodeRepository' => '<string>', 'DirectInternetAccess' => 'Enabled|Disabled', 'InstanceMetadataServiceConfiguration' => [ 'MinimumInstanceMetadataServiceVersion' => '<string>', // REQUIRED ], 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge', // REQUIRED 'KmsKeyId' => '<string>', 'LifecycleConfigName' => '<string>', 'NotebookInstanceName' => '<string>', // REQUIRED 'PlatformIdentifier' => '<string>', 'RoleArn' => '<string>', // REQUIRED 'RootAccess' => 'Enabled|Disabled', 'SecurityGroupIds' => ['<string>', ...], 'SubnetId' => '<string>', 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'VolumeSizeInGB' => <integer>, ]);
Parameter Details
Members
- AcceleratorTypes
-
- Type: Array of strings
A list of Elastic Inference (EI) instance types to associate with this notebook instance. Currently, only one instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
- AdditionalCodeRepositories
-
- Type: Array of strings
An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
- DefaultCodeRepository
-
- Type: string
A Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
- DirectInternetAccess
-
- Type: string
Sets whether SageMaker provides internet access to the notebook instance. If you set this to
Disabled
this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker training and endpoint services unless you configure a NAT Gateway in your VPC.For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value of this parameter to
Disabled
only if you set a value for theSubnetId
parameter. - InstanceMetadataServiceConfiguration
-
- Type: InstanceMetadataServiceConfiguration structure
Information on the IMDS configuration of the notebook instance
- InstanceType
-
- Required: Yes
- Type: string
The type of ML compute instance to launch for the notebook instance.
- KmsKeyId
-
- Type: string
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see Enabling and Disabling Keys in the Amazon Web Services Key Management Service Developer Guide.
- LifecycleConfigName
-
- Type: string
The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
- NotebookInstanceName
-
- Required: Yes
- Type: string
The name of the new notebook instance.
- PlatformIdentifier
-
- Type: string
The platform identifier of the notebook instance runtime environment.
- RoleArn
-
- Required: Yes
- Type: string
When you send any requests to Amazon Web Services resources from the notebook instance, SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker can perform these tasks. The policy must allow the SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the
iam:PassRole
permission. - RootAccess
-
- Type: string
Whether root access is enabled or disabled for users of the notebook instance. The default value is
Enabled
.Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
- SecurityGroupIds
-
- Type: Array of strings
The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
- SubnetId
-
- Type: string
The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
- VolumeSizeInGB
-
- Type: int
The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
Result Syntax
[ 'NotebookInstanceArn' => '<string>', ]
Result Details
Members
- NotebookInstanceArn
-
- Type: string
The Amazon Resource Name (ARN) of the notebook instance.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateNotebookInstanceLifecycleConfig
$result = $client->createNotebookInstanceLifecycleConfig
([/* ... */]); $promise = $client->createNotebookInstanceLifecycleConfigAsync
([/* ... */]);
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 Amazon 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.
Parameter Syntax
$result = $client->createNotebookInstanceLifecycleConfig([ 'NotebookInstanceLifecycleConfigName' => '<string>', // REQUIRED 'OnCreate' => [ [ 'Content' => '<string>', ], // ... ], 'OnStart' => [ [ 'Content' => '<string>', ], // ... ], ]);
Parameter Details
Members
- NotebookInstanceLifecycleConfigName
-
- Required: Yes
- Type: string
The name of the lifecycle configuration.
- OnCreate
-
- Type: Array of NotebookInstanceLifecycleHook structures
A shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
- OnStart
-
- Type: Array of NotebookInstanceLifecycleHook structures
A shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
Result Syntax
[ 'NotebookInstanceLifecycleConfigArn' => '<string>', ]
Result Details
Members
- NotebookInstanceLifecycleConfigArn
-
- Type: string
The Amazon Resource Name (ARN) of the lifecycle configuration.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateOptimizationJob
$result = $client->createOptimizationJob
([/* ... */]); $promise = $client->createOptimizationJobAsync
([/* ... */]);
Creates a job that optimizes a model for inference performance. To create the job, you provide the location of a source model, and you provide the settings for the optimization techniques that you want the job to apply. When the job completes successfully, SageMaker uploads the new optimized model to the output destination that you specify.
For more information about how to use this action, and about the supported optimization techniques, see Optimize model inference with Amazon SageMaker.
Parameter Syntax
$result = $client->createOptimizationJob([ 'DeploymentInstanceType' => 'ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge', // REQUIRED 'ModelSource' => [ // REQUIRED 'S3' => [ 'ModelAccessConfig' => [ 'AcceptEula' => true || false, // REQUIRED ], 'S3Uri' => '<string>', ], ], 'OptimizationConfigs' => [ // REQUIRED [ 'ModelCompilationConfig' => [ 'Image' => '<string>', 'OverrideEnvironment' => ['<string>', ...], ], 'ModelQuantizationConfig' => [ 'Image' => '<string>', 'OverrideEnvironment' => ['<string>', ...], ], ], // ... ], 'OptimizationEnvironment' => ['<string>', ...], 'OptimizationJobName' => '<string>', // REQUIRED 'OutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'S3OutputLocation' => '<string>', // REQUIRED ], 'RoleArn' => '<string>', // REQUIRED 'StoppingCondition' => [ // REQUIRED 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ]);
Parameter Details
Members
- DeploymentInstanceType
-
- Required: Yes
- Type: string
The type of instance that hosts the optimized model that you create with the optimization job.
- ModelSource
-
- Required: Yes
- Type: OptimizationJobModelSource structure
The location of the source model to optimize with an optimization job.
- OptimizationConfigs
-
- Required: Yes
- Type: Array of OptimizationConfig structures
Settings for each of the optimization techniques that the job applies.
- OptimizationEnvironment
-
- Type: Associative array of custom strings keys (NonEmptyString256) to strings
The environment variables to set in the model container.
- OptimizationJobName
-
- Required: Yes
- Type: string
A custom name for the new optimization job.
- OutputConfig
-
- Required: Yes
- Type: OptimizationJobOutputConfig structure
Details for where to store the optimized model that you create with the optimization job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
During model optimization, 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. - StoppingCondition
-
- Required: Yes
- Type: StoppingCondition structure
Specifies a limit to how long a job can run. When the job reaches the time limit, SageMaker ends the job. Use this API to cap costs.
To stop a training job, SageMaker sends the algorithm the
SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.The training algorithms provided by SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with
CreateModel
.The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.
- Tags
-
- Type: Array of Tag structures
A list of key-value pairs associated with the optimization job. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
- VpcConfig
-
- Type: OptimizationVpcConfig structure
A VPC in Amazon VPC that your optimized model has access to.
Result Syntax
[ 'OptimizationJobArn' => '<string>', ]
Result Details
Members
- OptimizationJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the optimization job.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreatePipeline
$result = $client->createPipeline
([/* ... */]); $promise = $client->createPipelineAsync
([/* ... */]);
Creates a pipeline using a JSON pipeline definition.
Parameter Syntax
$result = $client->createPipeline([ 'ClientRequestToken' => '<string>', // REQUIRED 'ParallelismConfiguration' => [ 'MaxParallelExecutionSteps' => <integer>, // REQUIRED ], 'PipelineDefinition' => '<string>', 'PipelineDefinitionS3Location' => [ 'Bucket' => '<string>', // REQUIRED 'ObjectKey' => '<string>', // REQUIRED 'VersionId' => '<string>', ], 'PipelineDescription' => '<string>', 'PipelineDisplayName' => '<string>', 'PipelineName' => '<string>', // REQUIRED 'RoleArn' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- ClientRequestToken
-
- Required: Yes
- Type: string
A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
- ParallelismConfiguration
-
- Type: ParallelismConfiguration structure
This is the configuration that controls the parallelism of the pipeline. If specified, it applies to all runs of this pipeline by default.
- PipelineDefinition
-
- Type: string
The JSON pipeline definition of the pipeline.
- PipelineDefinitionS3Location
-
- Type: PipelineDefinitionS3Location structure
The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
- PipelineDescription
-
- Type: string
A description of the pipeline.
- PipelineDisplayName
-
- Type: string
The display name of the pipeline.
- PipelineName
-
- Required: Yes
- Type: string
The name of the pipeline.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the role used by the pipeline to access and create resources.
- Tags
-
- Type: Array of Tag structures
A list of tags to apply to the created pipeline.
Result Syntax
[ 'PipelineArn' => '<string>', ]
Result Details
Members
- PipelineArn
-
- Type: string
The Amazon Resource Name (ARN) of the created pipeline.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
CreatePresignedDomainUrl
$result = $client->createPresignedDomainUrl
([/* ... */]); $promise = $client->createPresignedDomainUrlAsync
([/* ... */]);
Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to the domain, and granted access to all of the Apps and files associated with the Domain's Amazon Elastic File System volume. This operation can only be called when the authentication mode equals IAM.
The IAM role or user passed to this API defines the permissions to access the app. 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 app.
You can restrict access to this API and to the URL that it returns to a list of IP addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more information, see Connect to Amazon SageMaker Studio Through an Interface VPC Endpoint .
The URL that you get from a call to CreatePresignedDomainUrl
has a default timeout of 5 minutes. You can configure this value using ExpiresInSeconds
. If you try to use the URL after the timeout limit expires, you are directed to the Amazon Web Services console sign-in page.
Parameter Syntax
$result = $client->createPresignedDomainUrl([ 'DomainId' => '<string>', // REQUIRED 'ExpiresInSeconds' => <integer>, 'LandingUri' => '<string>', 'SessionExpirationDurationInSeconds' => <integer>, 'SpaceName' => '<string>', 'UserProfileName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DomainId
-
- Required: Yes
- Type: string
The domain ID.
- ExpiresInSeconds
-
- Type: int
The number of seconds until the pre-signed URL expires. This value defaults to 300.
- LandingUri
-
- Type: string
The landing page that the user is directed to when accessing the presigned URL. Using this value, users can access Studio or Studio Classic, even if it is not the default experience for the domain. The supported values are:
-
studio::relative/path
: Directs users to the relative path in Studio. -
app:JupyterServer:relative/path
: Directs users to the relative path in the Studio Classic application. -
app:JupyterLab:relative/path
: Directs users to the relative path in the JupyterLab application. -
app:RStudioServerPro:relative/path
: Directs users to the relative path in the RStudio application. -
app:CodeEditor:relative/path
: Directs users to the relative path in the Code Editor, based on Code-OSS, Visual Studio Code - Open Source application. -
app:Canvas:relative/path
: Directs users to the relative path in the Canvas application.
- SessionExpirationDurationInSeconds
-
- Type: int
The session expiration duration in seconds. This value defaults to 43200.
- SpaceName
-
- Type: string
The name of the space.
- UserProfileName
-
- Required: Yes
- Type: string
The name of the UserProfile to sign-in as.
Result Syntax
[ 'AuthorizedUrl' => '<string>', ]
Result Details
Members
- AuthorizedUrl
-
- Type: string
The presigned URL.
Errors
- ResourceNotFound:
Resource being access is not found.
CreatePresignedMlflowTrackingServerUrl
$result = $client->createPresignedMlflowTrackingServerUrl
([/* ... */]); $promise = $client->createPresignedMlflowTrackingServerUrlAsync
([/* ... */]);
Returns a presigned URL that you can use to connect to the MLflow UI attached to your tracking server. For more information, see Launch the MLflow UI using a presigned URL.
Parameter Syntax
$result = $client->createPresignedMlflowTrackingServerUrl([ 'ExpiresInSeconds' => <integer>, 'SessionExpirationDurationInSeconds' => <integer>, 'TrackingServerName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ExpiresInSeconds
-
- Type: int
The duration in seconds that your presigned URL is valid. The presigned URL can be used only once.
- SessionExpirationDurationInSeconds
-
- Type: int
The duration in seconds that your MLflow UI session is valid.
- TrackingServerName
-
- Required: Yes
- Type: string
The name of the tracking server to connect to your MLflow UI.
Result Syntax
[ 'AuthorizedUrl' => '<string>', ]
Result Details
Members
- AuthorizedUrl
-
- Type: string
A presigned URL with an authorization token.
Errors
- ResourceNotFound:
Resource being access is not found.
CreatePresignedNotebookInstanceUrl
$result = $client->createPresignedNotebookInstanceUrl
([/* ... */]); $promise = $client->createPresignedNotebookInstanceUrlAsync
([/* ... */]);
Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the SageMaker console, when you choose Open
next to a notebook instance, 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.
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 Amazon Web Services console sign-in page.
Parameter Syntax
$result = $client->createPresignedNotebookInstanceUrl([ 'NotebookInstanceName' => '<string>', // REQUIRED 'SessionExpirationDurationInSeconds' => <integer>, ]);
Parameter Details
Members
- NotebookInstanceName
-
- Required: Yes
- Type: string
The name of the notebook instance.
- SessionExpirationDurationInSeconds
-
- Type: int
The duration of the session, in seconds. The default is 12 hours.
Result Syntax
[ 'AuthorizedUrl' => '<string>', ]
Result Details
Members
- AuthorizedUrl
-
- Type: string
A JSON object that contains the URL string.
Errors
There are no errors described for this operation.
CreateProcessingJob
$result = $client->createProcessingJob
([/* ... */]); $promise = $client->createProcessingJobAsync
([/* ... */]);
Creates a processing job.
Parameter Syntax
$result = $client->createProcessingJob([ 'AppSpecification' => [ // REQUIRED 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ImageUri' => '<string>', // REQUIRED ], 'Environment' => ['<string>', ...], 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'RunName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], 'ProcessingInputs' => [ [ 'AppManaged' => true || false, 'DatasetDefinition' => [ 'AthenaDatasetDefinition' => [ 'Catalog' => '<string>', // REQUIRED 'Database' => '<string>', // REQUIRED 'KmsKeyId' => '<string>', 'OutputCompression' => 'GZIP|SNAPPY|ZLIB', 'OutputFormat' => 'PARQUET|ORC|AVRO|JSON|TEXTFILE', // REQUIRED 'OutputS3Uri' => '<string>', // REQUIRED 'QueryString' => '<string>', // REQUIRED 'WorkGroup' => '<string>', ], 'DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'InputMode' => 'Pipe|File', 'LocalPath' => '<string>', 'RedshiftDatasetDefinition' => [ 'ClusterId' => '<string>', // REQUIRED 'ClusterRoleArn' => '<string>', // REQUIRED 'Database' => '<string>', // REQUIRED 'DbUser' => '<string>', // REQUIRED 'KmsKeyId' => '<string>', 'OutputCompression' => 'None|GZIP|BZIP2|ZSTD|SNAPPY', 'OutputFormat' => 'PARQUET|CSV', // REQUIRED 'OutputS3Uri' => '<string>', // REQUIRED 'QueryString' => '<string>', // REQUIRED ], ], 'InputName' => '<string>', // REQUIRED 'S3Input' => [ 'LocalPath' => '<string>', 'S3CompressionType' => 'None|Gzip', 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix', // REQUIRED 'S3InputMode' => 'Pipe|File', 'S3Uri' => '<string>', // REQUIRED ], ], // ... ], 'ProcessingJobName' => '<string>', // REQUIRED 'ProcessingOutputConfig' => [ 'KmsKeyId' => '<string>', 'Outputs' => [ // REQUIRED [ 'AppManaged' => true || false, 'FeatureStoreOutput' => [ 'FeatureGroupName' => '<string>', // REQUIRED ], 'OutputName' => '<string>', // REQUIRED 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], // ... ], ], 'ProcessingResources' => [ // REQUIRED 'ClusterConfig' => [ // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', // REQUIRED 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], ], 'RoleArn' => '<string>', // REQUIRED 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, // REQUIRED ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- AppSpecification
-
- Required: Yes
- Type: AppSpecification structure
Configures the processing job to run a specified Docker container image.
- Environment
-
- Type: Associative array of custom strings keys (ProcessingEnvironmentKey) to strings
The environment variables to set in the Docker container. Up to 100 key and values entries in the map are supported.
- ExperimentConfig
-
- Type: ExperimentConfig structure
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
- NetworkConfig
-
- Type: NetworkConfig structure
Networking options for a processing job, such as whether to allow inbound and outbound network calls to and from processing containers, and the VPC subnets and security groups to use for VPC-enabled processing jobs.
- ProcessingInputs
-
- Type: Array of ProcessingInput structures
An array of inputs configuring the data to download into the processing container.
- ProcessingJobName
-
- Required: Yes
- Type: string
The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
- ProcessingOutputConfig
-
- Type: ProcessingOutputConfig structure
Output configuration for the processing job.
- ProcessingResources
-
- Required: Yes
- Type: ProcessingResources structure
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- StoppingCondition
-
- Type: ProcessingStoppingCondition structure
The time limit for how long the processing job is allowed to run.
- Tags
-
- Type: Array of Tag structures
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
Result Syntax
[ 'ProcessingJobArn' => '<string>', ]
Result Details
Members
- ProcessingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the processing job.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceNotFound:
Resource being access is not found.
CreateProject
$result = $client->createProject
([/* ... */]); $promise = $client->createProjectAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->createProject([ 'ProjectDescription' => '<string>', 'ProjectName' => '<string>', // REQUIRED 'ServiceCatalogProvisioningDetails' => [ // REQUIRED 'PathId' => '<string>', 'ProductId' => '<string>', // REQUIRED 'ProvisioningArtifactId' => '<string>', 'ProvisioningParameters' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- ProjectDescription
-
- Type: string
A description for the project.
- ProjectName
-
- Required: Yes
- Type: string
The name of the project.
- ServiceCatalogProvisioningDetails
-
- Required: Yes
- Type: ServiceCatalogProvisioningDetails structure
The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs that you want to use to organize and track your Amazon Web Services resource costs. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
Result Syntax
[ 'ProjectArn' => '<string>', 'ProjectId' => '<string>', ]
Result Details
Members
- ProjectArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the project.
- ProjectId
-
- Required: Yes
- Type: string
The ID of the new project.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateSpace
$result = $client->createSpace
([/* ... */]); $promise = $client->createSpaceAsync
([/* ... */]);
Creates a private space or a space used for real time collaboration in a domain.
Parameter Syntax
$result = $client->createSpace([ 'DomainId' => '<string>', // REQUIRED 'OwnershipSettings' => [ 'OwnerUserProfileName' => '<string>', // REQUIRED ], 'SpaceDisplayName' => '<string>', 'SpaceName' => '<string>', // REQUIRED 'SpaceSettings' => [ 'AppType' => 'JupyterServer|KernelGateway|DetailedProfiler|TensorBoard|CodeEditor|JupyterLab|RStudioServerPro|RSessionGateway|Canvas', 'CodeEditorAppSettings' => [ 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'CustomFileSystems' => [ [ 'EFSFileSystem' => [ 'FileSystemId' => '<string>', // REQUIRED ], ], // ... ], 'JupyterLabAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'JupyterServerAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'KernelGatewayAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'SpaceStorageSettings' => [ 'EbsStorageSettings' => [ 'EbsVolumeSizeInGb' => <integer>, // REQUIRED ], ], ], 'SpaceSharingSettings' => [ 'SharingType' => 'Private|Shared', // REQUIRED ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- DomainId
-
- Required: Yes
- Type: string
The ID of the associated domain.
- OwnershipSettings
-
- Type: OwnershipSettings structure
A collection of ownership settings.
- SpaceDisplayName
-
- Type: string
The name of the space that appears in the SageMaker Studio UI.
- SpaceName
-
- Required: Yes
- Type: string
The name of the space.
- SpaceSettings
-
- Type: SpaceSettings structure
A collection of space settings.
- SpaceSharingSettings
-
- Type: SpaceSharingSettings structure
A collection of space sharing settings.
- Tags
-
- Type: Array of Tag structures
Tags to associated with the space. Each tag consists of a key and an optional value. Tag keys must be unique for each resource. Tags are searchable using the
Search
API.
Result Syntax
[ 'SpaceArn' => '<string>', ]
Result Details
Members
- SpaceArn
-
- Type: string
The space's Amazon Resource Name (ARN).
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
CreateStudioLifecycleConfig
$result = $client->createStudioLifecycleConfig
([/* ... */]); $promise = $client->createStudioLifecycleConfigAsync
([/* ... */]);
Creates a new Amazon SageMaker Studio Lifecycle Configuration.
Parameter Syntax
$result = $client->createStudioLifecycleConfig([ 'StudioLifecycleConfigAppType' => 'JupyterServer|KernelGateway|CodeEditor|JupyterLab', // REQUIRED 'StudioLifecycleConfigContent' => '<string>', // REQUIRED 'StudioLifecycleConfigName' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- StudioLifecycleConfigAppType
-
- Required: Yes
- Type: string
The App type that the Lifecycle Configuration is attached to.
- StudioLifecycleConfigContent
-
- Required: Yes
- Type: string
The content of your Amazon SageMaker Studio Lifecycle Configuration script. This content must be base64 encoded.
- StudioLifecycleConfigName
-
- Required: Yes
- Type: string
The name of the Amazon SageMaker Studio Lifecycle Configuration to create.
- Tags
-
- Type: Array of Tag structures
Tags to be associated with the Lifecycle Configuration. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.
Result Syntax
[ 'StudioLifecycleConfigArn' => '<string>', ]
Result Details
Members
- StudioLifecycleConfigArn
-
- Type: string
The ARN of your created Lifecycle Configuration.
Errors
- ResourceInUse:
Resource being accessed is in use.
CreateTrainingJob
$result = $client->createTrainingJob
([/* ... */]); $promise = $client->createTrainingJobAsync
([/* ... */]);
Starts a model training job. After training completes, SageMaker saves the resulting model artifacts to an Amazon S3 location that you specify.
If you choose to host your model using 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 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 SageMaker, see Algorithms.Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
-
InputDataConfig
- Describes the input required by the training job and the Amazon S3, EFS, or FSx location where it is stored. -
OutputDataConfig
- Identifies the Amazon S3 bucket where you want 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. -
RoleArn
- The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during model training. You must grant this role the necessary permissions so that SageMaker can successfully complete model training. -
StoppingCondition
- To help cap training costs, useMaxRuntimeInSeconds
to set a time limit for training. UseMaxWaitTimeInSeconds
to specify how long a managed spot training job has to complete. -
Environment
- The environment variables to set in the Docker container. -
RetryStrategy
- The number of times to retry the job when the job fails due to anInternalServerError
.
For more information about SageMaker, see How It Works.
Parameter Syntax
$result = $client->createTrainingJob([ 'AlgorithmSpecification' => [ // REQUIRED 'AlgorithmName' => '<string>', 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'EnableSageMakerMetricsTimeSeries' => true || false, 'MetricDefinitions' => [ [ 'Name' => '<string>', // REQUIRED 'Regex' => '<string>', // REQUIRED ], // ... ], 'TrainingImage' => '<string>', 'TrainingImageConfig' => [ 'TrainingRepositoryAccessMode' => 'Platform|Vpc', // REQUIRED 'TrainingRepositoryAuthConfig' => [ 'TrainingRepositoryCredentialsProviderArn' => '<string>', // REQUIRED ], ], 'TrainingInputMode' => 'Pipe|File|FastFile', // REQUIRED ], 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', // REQUIRED ], 'DebugHookConfig' => [ 'CollectionConfigurations' => [ [ 'CollectionName' => '<string>', 'CollectionParameters' => ['<string>', ...], ], // ... ], 'HookParameters' => ['<string>', ...], 'LocalPath' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'DebugRuleConfigurations' => [ [ 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'LocalPath' => '<string>', 'RuleConfigurationName' => '<string>', // REQUIRED 'RuleEvaluatorImage' => '<string>', // REQUIRED 'RuleParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', 'VolumeSizeInGB' => <integer>, ], // ... ], 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'Environment' => ['<string>', ...], 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'RunName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'HyperParameters' => ['<string>', ...], 'InfraCheckConfig' => [ 'EnableInfraCheck' => true || false, ], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', // REQUIRED 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ // REQUIRED 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', // REQUIRED 'FileSystemAccessMode' => 'rw|ro', // REQUIRED 'FileSystemId' => '<string>', // REQUIRED 'FileSystemType' => 'EFS|FSxLustre', // REQUIRED ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'InstanceGroupNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'InputMode' => 'Pipe|File|FastFile', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, // REQUIRED ], ], // ... ], 'OutputDataConfig' => [ // REQUIRED 'CompressionType' => 'GZIP|NONE', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'ProfilerConfig' => [ 'DisableProfiler' => true || false, 'ProfilingIntervalInMilliseconds' => <integer>, 'ProfilingParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', ], 'ProfilerRuleConfigurations' => [ [ 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'LocalPath' => '<string>', 'RuleConfigurationName' => '<string>', // REQUIRED 'RuleEvaluatorImage' => '<string>', // REQUIRED 'RuleParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', 'VolumeSizeInGB' => <integer>, ], // ... ], 'RemoteDebugConfig' => [ 'EnableRemoteDebug' => true || false, ], 'ResourceConfig' => [ // REQUIRED 'InstanceCount' => <integer>, 'InstanceGroups' => [ [ 'InstanceCount' => <integer>, // REQUIRED 'InstanceGroupName' => '<string>', // REQUIRED 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', // REQUIRED ], // ... ], 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'KeepAlivePeriodInSeconds' => <integer>, 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], 'RetryStrategy' => [ 'MaximumRetryAttempts' => <integer>, // REQUIRED ], 'RoleArn' => '<string>', // REQUIRED 'SessionChainingConfig' => [ 'EnableSessionTagChaining' => true || false, ], 'StoppingCondition' => [ // REQUIRED 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'TensorBoardOutputConfig' => [ 'LocalPath' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'TrainingJobName' => '<string>', // REQUIRED 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ]);
Parameter Details
Members
- AlgorithmSpecification
-
- Required: Yes
- Type: AlgorithmSpecification structure
The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata, including the input mode. For more information about algorithms provided by SageMaker, see Algorithms. For information about providing your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
- CheckpointConfig
-
- Type: CheckpointConfig structure
Contains information about the output location for managed spot training checkpoint data.
- DebugHookConfig
-
- Type: DebugHookConfig structure
Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the
DebugHookConfig
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job. - DebugRuleConfigurations
-
- Type: Array of DebugRuleConfiguration structures
Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
- EnableInterContainerTrafficEncryption
-
- Type: boolean
To encrypt all communications between ML compute instances in distributed training, choose
True
. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training. For more information, see Protect Communications Between ML Compute Instances in a Distributed Training Job. - EnableManagedSpotTraining
-
- Type: boolean
To train models using managed spot training, choose
True
. Managed spot training provides a fully managed and scalable infrastructure for training machine learning models. this option is useful when training jobs can be interrupted and when there is flexibility when the training job is run.The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a starting point to train models incrementally. Amazon SageMaker provides metrics and logs in CloudWatch. They can be used to see when managed spot training jobs are running, interrupted, resumed, or completed.
- EnableNetworkIsolation
-
- Type: boolean
Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
- Environment
-
- Type: Associative array of custom strings keys (TrainingEnvironmentKey) to strings
The environment variables to set in the Docker container.
- ExperimentConfig
-
- Type: ExperimentConfig structure
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
- HyperParameters
-
- Type: Associative array of custom strings keys (HyperParameterKey) to strings
Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and value is limited to 256 characters, as specified by the
Length Constraint
.Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
- InfraCheckConfig
-
- Type: InfraCheckConfig structure
Contains information about the infrastructure health check configuration for the training job.
- InputDataConfig
-
- Type: Array of Channel structures
An array of
Channel
objects. Each channel is a named input source.InputDataConfig
describes the input data and its location.Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels of input data,
training_data
andvalidation_data
. The configuration for each channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3 bucket to a local directory in the Docker container, or makes it available as input streams. For example, if you specify an EFS location, input data files are available as input streams. They do not need to be downloaded.
Your input must be in the same Amazon Web Services region as your training job.
- OutputDataConfig
-
- Required: Yes
- Type: OutputDataConfig structure
Specifies the path to the S3 location where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
- ProfilerConfig
-
- Type: ProfilerConfig structure
Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
- ProfilerRuleConfigurations
-
- Type: Array of ProfilerRuleConfiguration structures
Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
- RemoteDebugConfig
-
- Type: RemoteDebugConfig structure
Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
- ResourceConfig
-
- Required: Yes
- Type: ResourceConfig structure
The resources, including the ML compute instances and ML storage volumes, to use for model training.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the training data, choose
File
as theTrainingInputMode
in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1. - RetryStrategy
-
- Type: RetryStrategy structure
The number of times to retry the job when the job fails due to an
InternalServerError
. - RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
During model training, SageMaker needs your permission to read input data from an S3 bucket, download a Docker image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks to an IAM role. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the
iam:PassRole
permission. - SessionChainingConfig
-
- Type: SessionChainingConfig structure
Contains information about attribute-based access control (ABAC) for the training job.
- StoppingCondition
-
- Required: Yes
- Type: StoppingCondition structure
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the
SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost. - Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
- TensorBoardOutputConfig
-
- Type: TensorBoardOutputConfig structure
Configuration of storage locations for the Amazon SageMaker Debugger TensorBoard output data.
- TrainingJobName
-
- Required: Yes
- Type: string
The name of the training job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
- VpcConfig
-
- Type: VpcConfig structure
A VpcConfig object that specifies the VPC that you want your training job to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
Result Syntax
[ 'TrainingJobArn' => '<string>', ]
Result Details
Members
- TrainingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the training job.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceNotFound:
Resource being access is not found.
CreateTransformJob
$result = $client->createTransformJob
([/* ... */]); $promise = $client->createTransformJobAsync
([/* ... */]);
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 Amazon Web Services Region in an Amazon Web Services account. -
ModelName
- Identifies the model to use.ModelName
must be the name of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon Web Services 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.
Parameter Syntax
$result = $client->createTransformJob([ 'BatchStrategy' => 'MultiRecord|SingleRecord', 'DataCaptureConfig' => [ 'DestinationS3Uri' => '<string>', // REQUIRED 'GenerateInferenceId' => true || false, 'KmsKeyId' => '<string>', ], 'DataProcessing' => [ 'InputFilter' => '<string>', 'JoinSource' => 'Input|None', 'OutputFilter' => '<string>', ], 'Environment' => ['<string>', ...], 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'RunName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'MaxConcurrentTransforms' => <integer>, 'MaxPayloadInMB' => <integer>, 'ModelClientConfig' => [ 'InvocationsMaxRetries' => <integer>, 'InvocationsTimeoutInSeconds' => <integer>, ], 'ModelName' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'TransformInput' => [ // REQUIRED 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ // REQUIRED 'S3DataSource' => [ // REQUIRED 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'SplitType' => 'None|Line|RecordIO|TFRecord', ], 'TransformJobName' => '<string>', // REQUIRED 'TransformOutput' => [ // REQUIRED 'Accept' => '<string>', 'AssembleWith' => 'None|Line', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'TransformResources' => [ // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge', // REQUIRED 'VolumeKmsKeyId' => '<string>', ], ]);
Parameter Details
Members
- BatchStrategy
-
- Type: string
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set the
SplitType
property toLine
,RecordIO
, orTFRecord
.To use only one record when making an HTTP invocation request to a container, set
BatchStrategy
toSingleRecord
andSplitType
toLine
.To fit as many records in a mini-batch as can fit within the
MaxPayloadInMB
limit, setBatchStrategy
toMultiRecord
andSplitType
toLine
. - DataCaptureConfig
-
- Type: BatchDataCaptureConfig structure
Configuration to control how SageMaker captures inference data.
- DataProcessing
-
- Type: DataProcessing structure
The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
- Environment
-
- Type: Associative array of custom strings keys (TransformEnvironmentKey) to strings
The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
- ExperimentConfig
-
- Type: ExperimentConfig structure
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
- MaxConcurrentTransforms
-
- Type: int
The maximum number of parallel requests that can be sent to each instance in a transform job. If
MaxConcurrentTransforms
is set to0
or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is1
. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don't need to set a value forMaxConcurrentTransforms
. - MaxPayloadInMB
-
- Type: int
The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in
MaxPayloadInMB
must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is6
MB.The value of
MaxPayloadInMB
cannot be greater than 100 MB. If you specify theMaxConcurrentTransforms
parameter, the value of(MaxConcurrentTransforms * MaxPayloadInMB)
also cannot exceed 100 MB.For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to
0
. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding. - ModelClientConfig
-
- Type: ModelClientConfig structure
Configures the timeout and maximum number of retries for processing a transform job invocation.
- ModelName
-
- Required: Yes
- Type: string
The name of the model that you want to use for the transform job.
ModelName
must be the name of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services account. - Tags
-
- Type: Array of Tag structures
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
- TransformInput
-
- Required: Yes
- Type: TransformInput structure
Describes the input source and the way the transform job consumes it.
- TransformJobName
-
- Required: Yes
- Type: string
The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
- TransformOutput
-
- Required: Yes
- Type: TransformOutput structure
Describes the results of the transform job.
- TransformResources
-
- Required: Yes
- Type: TransformResources structure
Describes the resources, including ML instance types and ML instance count, to use for the transform job.
Result Syntax
[ 'TransformJobArn' => '<string>', ]
Result Details
Members
- TransformJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the transform job.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceNotFound:
Resource being access is not found.
CreateTrial
$result = $client->createTrial
([/* ... */]); $promise = $client->createTrialAsync
([/* ... */]);
Creates an 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 SageMaker experiment.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services 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.
Parameter Syntax
$result = $client->createTrial([ 'DisplayName' => '<string>', 'ExperimentName' => '<string>', // REQUIRED 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'TrialName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DisplayName
-
- Type: string
The name of the trial as displayed. The name doesn't need to be unique. If
DisplayName
isn't specified,TrialName
is displayed. - ExperimentName
-
- Required: Yes
- Type: string
The name of the experiment to associate the trial with.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- Tags
-
- Type: Array of Tag structures
A list of tags to associate with the trial. You can use Search API to search on the tags.
- TrialName
-
- Required: Yes
- Type: string
The name of the trial. The name must be unique in your Amazon Web Services account and is not case-sensitive.
Result Syntax
[ 'TrialArn' => '<string>', ]
Result Details
Members
- TrialArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateTrialComponent
$result = $client->createTrialComponent
([/* ... */]); $promise = $client->createTrialComponentAsync
([/* ... */]);
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 SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services 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.
Parameter Syntax
$result = $client->createTrialComponent([ 'DisplayName' => '<string>', 'EndTime' => <integer || string || DateTime>, 'InputArtifacts' => [ '<TrialComponentKey128>' => [ 'MediaType' => '<string>', 'Value' => '<string>', // REQUIRED ], // ... ], 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'OutputArtifacts' => [ '<TrialComponentKey128>' => [ 'MediaType' => '<string>', 'Value' => '<string>', // REQUIRED ], // ... ], 'Parameters' => [ '<TrialComponentKey320>' => [ 'NumberValue' => <float>, 'StringValue' => '<string>', ], // ... ], 'StartTime' => <integer || string || DateTime>, 'Status' => [ 'Message' => '<string>', 'PrimaryStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'TrialComponentName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DisplayName
-
- Type: string
The name of the component as displayed. The name doesn't need to be unique. If
DisplayName
isn't specified,TrialComponentName
is displayed. - EndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component ended.
- InputArtifacts
-
- Type: Associative array of custom strings keys (TrialComponentKey128) to TrialComponentArtifact structures
The input artifacts for the component. Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- OutputArtifacts
-
- Type: Associative array of custom strings keys (TrialComponentKey128) to TrialComponentArtifact structures
The output artifacts for the component. Examples of output artifacts are metrics, snapshots, logs, and images.
- Parameters
-
- Type: Associative array of custom strings keys (TrialComponentKey320) to TrialComponentParameterValue structures
The hyperparameters for the component.
- StartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component started.
- Status
-
- Type: TrialComponentStatus structure
The status of the component. States include:
-
InProgress
-
Completed
-
Failed
- Tags
-
- Type: Array of Tag structures
A list of tags to associate with the component. You can use Search API to search on the tags.
- TrialComponentName
-
- Required: Yes
- Type: string
The name of the component. The name must be unique in your Amazon Web Services account and is not case-sensitive.
Result Syntax
[ 'TrialComponentArn' => '<string>', ]
Result Details
Members
- TrialComponentArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial component.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
CreateUserProfile
$result = $client->createUserProfile
([/* ... */]); $promise = $client->createUserProfileAsync
([/* ... */]);
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 a domain. If an administrator invites a person by email or imports them from IAM Identity Center, 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 home directory.
Parameter Syntax
$result = $client->createUserProfile([ 'DomainId' => '<string>', // REQUIRED 'SingleSignOnUserIdentifier' => '<string>', 'SingleSignOnUserValue' => '<string>', 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'UserProfileName' => '<string>', // REQUIRED 'UserSettings' => [ 'CanvasAppSettings' => [ 'DirectDeploySettings' => [ 'Status' => 'ENABLED|DISABLED', ], 'EmrServerlessSettings' => [ 'ExecutionRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'GenerativeAiSettings' => [ 'AmazonBedrockRoleArn' => '<string>', ], 'IdentityProviderOAuthSettings' => [ [ 'DataSourceName' => 'SalesforceGenie|Snowflake', 'SecretArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], // ... ], 'KendraSettings' => [ 'Status' => 'ENABLED|DISABLED', ], 'ModelRegisterSettings' => [ 'CrossAccountModelRegisterRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'TimeSeriesForecastingSettings' => [ 'AmazonForecastRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'WorkspaceSettings' => [ 'S3ArtifactPath' => '<string>', 'S3KmsKeyId' => '<string>', ], ], 'CodeEditorAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'CustomFileSystemConfigs' => [ [ 'EFSFileSystemConfig' => [ 'FileSystemId' => '<string>', // REQUIRED 'FileSystemPath' => '<string>', ], ], // ... ], 'CustomPosixUserConfig' => [ 'Gid' => <integer>, // REQUIRED 'Uid' => <integer>, // REQUIRED ], 'DefaultLandingUri' => '<string>', 'ExecutionRole' => '<string>', 'JupyterLabAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'EmrSettings' => [ 'AssumableRoleArns' => ['<string>', ...], 'ExecutionRoleArns' => ['<string>', ...], ], 'LifecycleConfigArns' => ['<string>', ...], ], 'JupyterServerAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'KernelGatewayAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'RSessionAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'RStudioServerProAppSettings' => [ 'AccessStatus' => 'ENABLED|DISABLED', 'UserGroup' => 'R_STUDIO_ADMIN|R_STUDIO_USER', ], 'SecurityGroups' => ['<string>', ...], 'SharingSettings' => [ 'NotebookOutputOption' => 'Allowed|Disabled', 'S3KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'SpaceStorageSettings' => [ 'DefaultEbsStorageSettings' => [ 'DefaultEbsVolumeSizeInGb' => <integer>, // REQUIRED 'MaximumEbsVolumeSizeInGb' => <integer>, // REQUIRED ], ], 'StudioWebPortal' => 'ENABLED|DISABLED', 'StudioWebPortalSettings' => [ 'HiddenAppTypes' => ['<string>', ...], 'HiddenMlTools' => ['<string>', ...], ], 'TensorBoardAppSettings' => [ 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], ], ]);
Parameter Details
Members
- DomainId
-
- Required: Yes
- Type: string
The ID of the associated Domain.
- SingleSignOnUserIdentifier
-
- Type: string
A specifier for the type of value specified in SingleSignOnUserValue. Currently, the only supported value is "UserName". If the Domain's AuthMode is IAM Identity Center, this field is required. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.
- SingleSignOnUserValue
-
- Type: string
The username of the associated Amazon Web Services Single Sign-On User for this UserProfile. If the Domain's AuthMode is IAM Identity Center, this field is required, and must match a valid username of a user in your directory. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.
- Tags
-
- Type: Array of Tag structures
Each tag consists of a key and an optional value. Tag keys must be unique per resource.
Tags that you specify for the User Profile are also added to all Apps that the User Profile launches.
- UserProfileName
-
- Required: Yes
- Type: string
A name for the UserProfile. This value is not case sensitive.
- UserSettings
-
- Type: UserSettings structure
A collection of settings.
Result Syntax
[ 'UserProfileArn' => '<string>', ]
Result Details
Members
- UserProfileArn
-
- Type: string
The user profile Amazon Resource Name (ARN).
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
CreateWorkforce
$result = $client->createWorkforce
([/* ... */]); $promise = $client->createWorkforceAsync
([/* ... */]);
Use this operation to create a workforce. This operation will return an error if a workforce already exists in the Amazon Web Services Region that you specify. You can only create one workforce in each Amazon Web Services Region per Amazon Web Services account.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use the DeleteWorkforce 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).
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).
Parameter Syntax
$result = $client->createWorkforce([ 'CognitoConfig' => [ 'ClientId' => '<string>', // REQUIRED 'UserPool' => '<string>', // REQUIRED ], 'OidcConfig' => [ 'AuthenticationRequestExtraParams' => ['<string>', ...], 'AuthorizationEndpoint' => '<string>', // REQUIRED 'ClientId' => '<string>', // REQUIRED 'ClientSecret' => '<string>', // REQUIRED 'Issuer' => '<string>', // REQUIRED 'JwksUri' => '<string>', // REQUIRED 'LogoutEndpoint' => '<string>', // REQUIRED 'Scope' => '<string>', 'TokenEndpoint' => '<string>', // REQUIRED 'UserInfoEndpoint' => '<string>', // REQUIRED ], 'SourceIpConfig' => [ 'Cidrs' => ['<string>', ...], // REQUIRED ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'WorkforceName' => '<string>', // REQUIRED 'WorkforceVpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], 'VpcId' => '<string>', ], ]);
Parameter Details
Members
- CognitoConfig
-
- Type: CognitoConfig structure
Use this parameter to configure an Amazon Cognito private workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
Do not use
OidcConfig
if you specify values forCognitoConfig
. - OidcConfig
-
- Type: OidcConfig structure
Use this parameter to configure a private workforce using your own OIDC Identity Provider.
Do not use
CognitoConfig
if you specify values forOidcConfig
. - SourceIpConfig
-
- Type: SourceIpConfig structure
A list of IP address ranges (CIDRs). Used to create an allow list of IP addresses for a private workforce. Workers will only be able to log in to their worker portal from an IP address within this range. By default, a workforce isn't restricted to specific IP addresses.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs that contain metadata to help you categorize and organize our workforce. Each tag consists of a key and a value, both of which you define.
- WorkforceName
-
- Required: Yes
- Type: string
The name of the private workforce.
- WorkforceVpcConfig
-
- Type: WorkforceVpcConfigRequest structure
Use this parameter to configure a workforce using VPC.
Result Syntax
[ 'WorkforceArn' => '<string>', ]
Result Details
Members
- WorkforceArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the workforce.
Errors
There are no errors described for this operation.
CreateWorkteam
$result = $client->createWorkteam
([/* ... */]); $promise = $client->createWorkteamAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->createWorkteam([ 'Description' => '<string>', // REQUIRED 'MemberDefinitions' => [ // REQUIRED [ 'CognitoMemberDefinition' => [ 'ClientId' => '<string>', // REQUIRED 'UserGroup' => '<string>', // REQUIRED 'UserPool' => '<string>', // REQUIRED ], 'OidcMemberDefinition' => [ 'Groups' => ['<string>', ...], ], ], // ... ], 'NotificationConfiguration' => [ 'NotificationTopicArn' => '<string>', ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'WorkerAccessConfiguration' => [ 'S3Presign' => [ 'IamPolicyConstraints' => [ 'SourceIp' => 'Enabled|Disabled', 'VpcSourceIp' => 'Enabled|Disabled', ], ], ], 'WorkforceName' => '<string>', 'WorkteamName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- Description
-
- Required: Yes
- Type: string
A description of the work team.
- MemberDefinitions
-
- Required: Yes
- Type: Array of MemberDefinition structures
A list of
MemberDefinition
objects that contains objects that identify the workers that make up the work team.Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use
CognitoMemberDefinition
. For workforces created using your own OIDC identity provider (IdP) useOidcMemberDefinition
. Do not provide input for both of these parameters in a single request.For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the
CognitoMemberDefinition
objects that make up the member definition must have the sameClientId
andUserPool
values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in
OidcMemberDefinition
by listing those groups inGroups
. - NotificationConfiguration
-
- Type: NotificationConfiguration structure
Configures notification of workers regarding available or expiring work items.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs.
For more information, see Resource Tag and Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
- WorkerAccessConfiguration
-
- Type: WorkerAccessConfiguration structure
Use this optional parameter to constrain access to an Amazon S3 resource based on the IP address using supported IAM global condition keys. The Amazon S3 resource is accessed in the worker portal using a Amazon S3 presigned URL.
- WorkforceName
-
- Type: string
The name of the workforce.
- WorkteamName
-
- Required: Yes
- Type: string
The name of the work team. Use this name to identify the work team.
Result Syntax
[ 'WorkteamArn' => '<string>', ]
Result Details
Members
- WorkteamArn
-
- Type: string
The Amazon Resource Name (ARN) of the work team. You can use this ARN to identify the work team.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
DeleteAction
$result = $client->deleteAction
([/* ... */]); $promise = $client->deleteActionAsync
([/* ... */]);
Deletes an action.
Parameter Syntax
$result = $client->deleteAction([ 'ActionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ActionName
-
- Required: Yes
- Type: string
The name of the action to delete.
Result Syntax
[ 'ActionArn' => '<string>', ]
Result Details
Members
- ActionArn
-
- Type: string
The Amazon Resource Name (ARN) of the action.
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteAlgorithm
$result = $client->deleteAlgorithm
([/* ... */]); $promise = $client->deleteAlgorithmAsync
([/* ... */]);
Removes the specified algorithm from your account.
Parameter Syntax
$result = $client->deleteAlgorithm([ 'AlgorithmName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- AlgorithmName
-
- Required: Yes
- Type: string
The name of the algorithm to delete.
Result Syntax
[]
Result Details
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
DeleteApp
$result = $client->deleteApp
([/* ... */]); $promise = $client->deleteAppAsync
([/* ... */]);
Used to stop and delete an app.
Parameter Syntax
$result = $client->deleteApp([ 'AppName' => '<string>', // REQUIRED 'AppType' => 'JupyterServer|KernelGateway|DetailedProfiler|TensorBoard|CodeEditor|JupyterLab|RStudioServerPro|RSessionGateway|Canvas', // REQUIRED 'DomainId' => '<string>', // REQUIRED 'SpaceName' => '<string>', 'UserProfileName' => '<string>', ]);
Parameter Details
Members
- AppName
-
- Required: Yes
- Type: string
The name of the app.
- AppType
-
- Required: Yes
- Type: string
The type of app.
- DomainId
-
- Required: Yes
- Type: string
The domain ID.
- SpaceName
-
- Type: string
The name of the space. If this value is not set, then
UserProfileName
must be set. - UserProfileName
-
- Type: string
The user profile name. If this value is not set, then
SpaceName
must be set.
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
DeleteAppImageConfig
$result = $client->deleteAppImageConfig
([/* ... */]); $promise = $client->deleteAppImageConfigAsync
([/* ... */]);
Deletes an AppImageConfig.
Parameter Syntax
$result = $client->deleteAppImageConfig([ 'AppImageConfigName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- AppImageConfigName
-
- Required: Yes
- Type: string
The name of the AppImageConfig to delete.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteArtifact
$result = $client->deleteArtifact
([/* ... */]); $promise = $client->deleteArtifactAsync
([/* ... */]);
Deletes an artifact. Either ArtifactArn
or Source
must be specified.
Parameter Syntax
$result = $client->deleteArtifact([ 'ArtifactArn' => '<string>', 'Source' => [ 'SourceTypes' => [ [ 'SourceIdType' => 'MD5Hash|S3ETag|S3Version|Custom', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'SourceUri' => '<string>', // REQUIRED ], ]);
Parameter Details
Members
- ArtifactArn
-
- Type: string
The Amazon Resource Name (ARN) of the artifact to delete.
- Source
-
- Type: ArtifactSource structure
The URI of the source.
Result Syntax
[ 'ArtifactArn' => '<string>', ]
Result Details
Members
- ArtifactArn
-
- Type: string
The Amazon Resource Name (ARN) of the artifact.
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteAssociation
$result = $client->deleteAssociation
([/* ... */]); $promise = $client->deleteAssociationAsync
([/* ... */]);
Deletes an association.
Parameter Syntax
$result = $client->deleteAssociation([ 'DestinationArn' => '<string>', // REQUIRED 'SourceArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DestinationArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the destination.
- SourceArn
-
- Required: Yes
- Type: string
The ARN of the source.
Result Syntax
[ 'DestinationArn' => '<string>', 'SourceArn' => '<string>', ]
Result Details
Members
- DestinationArn
-
- Type: string
The Amazon Resource Name (ARN) of the destination.
- SourceArn
-
- Type: string
The ARN of the source.
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteCluster
$result = $client->deleteCluster
([/* ... */]); $promise = $client->deleteClusterAsync
([/* ... */]);
Delete a SageMaker HyperPod cluster.
Parameter Syntax
$result = $client->deleteCluster([ 'ClusterName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ClusterName
-
- Required: Yes
- Type: string
The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster to delete.
Result Syntax
[ 'ClusterArn' => '<string>', ]
Result Details
Members
- ClusterArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster to delete.
Errors
- ResourceNotFound:
Resource being access is not found.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
DeleteCodeRepository
$result = $client->deleteCodeRepository
([/* ... */]); $promise = $client->deleteCodeRepositoryAsync
([/* ... */]);
Deletes the specified Git repository from your account.
Parameter Syntax
$result = $client->deleteCodeRepository([ 'CodeRepositoryName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- CodeRepositoryName
-
- Required: Yes
- Type: string
The name of the Git repository to delete.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteCompilationJob
$result = $client->deleteCompilationJob
([/* ... */]); $promise = $client->deleteCompilationJobAsync
([/* ... */]);
Deletes the specified compilation job. This action deletes only the compilation job resource in Amazon SageMaker. It doesn't delete other resources that are related to that job, such as the model artifacts that the job creates, the compilation logs in CloudWatch, the compiled model, or the IAM role.
You can delete a compilation job only if its current status is COMPLETED
, FAILED
, or STOPPED
. If the job status is STARTING
or INPROGRESS
, stop the job, and then delete it after its status becomes STOPPED
.
Parameter Syntax
$result = $client->deleteCompilationJob([ 'CompilationJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- CompilationJobName
-
- Required: Yes
- Type: string
The name of the compilation job to delete.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteContext
$result = $client->deleteContext
([/* ... */]); $promise = $client->deleteContextAsync
([/* ... */]);
Deletes an context.
Parameter Syntax
$result = $client->deleteContext([ 'ContextName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ContextName
-
- Required: Yes
- Type: string
The name of the context to delete.
Result Syntax
[ 'ContextArn' => '<string>', ]
Result Details
Members
- ContextArn
-
- Type: string
The Amazon Resource Name (ARN) of the context.
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteDataQualityJobDefinition
$result = $client->deleteDataQualityJobDefinition
([/* ... */]); $promise = $client->deleteDataQualityJobDefinitionAsync
([/* ... */]);
Deletes a data quality monitoring job definition.
Parameter Syntax
$result = $client->deleteDataQualityJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the data quality monitoring job definition to delete.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteDeviceFleet
$result = $client->deleteDeviceFleet
([/* ... */]); $promise = $client->deleteDeviceFleetAsync
([/* ... */]);
Deletes a fleet.
Parameter Syntax
$result = $client->deleteDeviceFleet([ 'DeviceFleetName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the fleet to delete.
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
DeleteDomain
$result = $client->deleteDomain
([/* ... */]); $promise = $client->deleteDomainAsync
([/* ... */]);
Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using IAM Identity Center. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.
Parameter Syntax
$result = $client->deleteDomain([ 'DomainId' => '<string>', // REQUIRED 'RetentionPolicy' => [ 'HomeEfsFileSystem' => 'Retain|Delete', ], ]);
Parameter Details
Members
- DomainId
-
- Required: Yes
- Type: string
The domain ID.
- RetentionPolicy
-
- Type: RetentionPolicy structure
The retention policy for this domain, which specifies whether resources will be retained after the Domain is deleted. By default, all resources are retained (not automatically deleted).
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
DeleteEdgeDeploymentPlan
$result = $client->deleteEdgeDeploymentPlan
([/* ... */]); $promise = $client->deleteEdgeDeploymentPlanAsync
([/* ... */]);
Deletes an edge deployment plan if (and only if) all the stages in the plan are inactive or there are no stages in the plan.
Parameter Syntax
$result = $client->deleteEdgeDeploymentPlan([ 'EdgeDeploymentPlanName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- EdgeDeploymentPlanName
-
- Required: Yes
- Type: string
The name of the edge deployment plan to delete.
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
DeleteEdgeDeploymentStage
$result = $client->deleteEdgeDeploymentStage
([/* ... */]); $promise = $client->deleteEdgeDeploymentStageAsync
([/* ... */]);
Delete a stage in an edge deployment plan if (and only if) the stage is inactive.
Parameter Syntax
$result = $client->deleteEdgeDeploymentStage([ 'EdgeDeploymentPlanName' => '<string>', // REQUIRED 'StageName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- EdgeDeploymentPlanName
-
- Required: Yes
- Type: string
The name of the edge deployment plan from which the stage will be deleted.
- StageName
-
- Required: Yes
- Type: string
The name of the stage.
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
DeleteEndpoint
$result = $client->deleteEndpoint
([/* ... */]); $promise = $client->deleteEndpointAsync
([/* ... */]);
Deletes an endpoint. SageMaker frees up all of the resources that were deployed when the endpoint was created.
SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don't need to use the RevokeGrant API call.
When you delete your endpoint, SageMaker asynchronously deletes associated endpoint resources such as KMS key grants. You might still see these resources in your account for a few minutes after deleting your endpoint. Do not delete or revoke the permissions for your ExecutionRoleArn
, otherwise SageMaker cannot delete these resources.
Parameter Syntax
$result = $client->deleteEndpoint([ 'EndpointName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- EndpointName
-
- Required: Yes
- Type: string
The name of the endpoint that you want to delete.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteEndpointConfig
$result = $client->deleteEndpointConfig
([/* ... */]); $promise = $client->deleteEndpointConfigAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->deleteEndpointConfig([ 'EndpointConfigName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- EndpointConfigName
-
- Required: Yes
- Type: string
The name of the endpoint configuration that you want to delete.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteExperiment
$result = $client->deleteExperiment
([/* ... */]); $promise = $client->deleteExperimentAsync
([/* ... */]);
Deletes an 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.
Parameter Syntax
$result = $client->deleteExperiment([ 'ExperimentName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ExperimentName
-
- Required: Yes
- Type: string
The name of the experiment to delete.
Result Syntax
[ 'ExperimentArn' => '<string>', ]
Result Details
Members
- ExperimentArn
-
- Type: string
The Amazon Resource Name (ARN) of the experiment that is being deleted.
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteFeatureGroup
$result = $client->deleteFeatureGroup
([/* ... */]); $promise = $client->deleteFeatureGroupAsync
([/* ... */]);
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 Amazon Web Services Glue database and tables that are automatically created for your OfflineStore
are not deleted.
Note that it can take approximately 10-15 minutes to delete an OnlineStore
FeatureGroup
with the InMemory
StorageType
.
Parameter Syntax
$result = $client->deleteFeatureGroup([ 'FeatureGroupName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- FeatureGroupName
-
- Required: Yes
- Type: string
The name of the
FeatureGroup
you want to delete. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteFlowDefinition
$result = $client->deleteFlowDefinition
([/* ... */]); $promise = $client->deleteFlowDefinitionAsync
([/* ... */]);
Deletes the specified flow definition.
Parameter Syntax
$result = $client->deleteFlowDefinition([ 'FlowDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- FlowDefinitionName
-
- Required: Yes
- Type: string
The name of the flow definition you are deleting.
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
DeleteHub
$result = $client->deleteHub
([/* ... */]); $promise = $client->deleteHubAsync
([/* ... */]);
Delete a hub.
Parameter Syntax
$result = $client->deleteHub([ 'HubName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- HubName
-
- Required: Yes
- Type: string
The name of the hub to delete.
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
DeleteHubContent
$result = $client->deleteHubContent
([/* ... */]); $promise = $client->deleteHubContentAsync
([/* ... */]);
Delete the contents of a hub.
Parameter Syntax
$result = $client->deleteHubContent([ 'HubContentName' => '<string>', // REQUIRED 'HubContentType' => 'Model|Notebook|ModelReference', // REQUIRED 'HubContentVersion' => '<string>', // REQUIRED 'HubName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- HubContentName
-
- Required: Yes
- Type: string
The name of the content that you want to delete from a hub.
- HubContentType
-
- Required: Yes
- Type: string
The type of content that you want to delete from a hub.
- HubContentVersion
-
- Required: Yes
- Type: string
The version of the content that you want to delete from a hub.
- HubName
-
- Required: Yes
- Type: string
The name of the hub that you want to delete content in.
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
DeleteHubContentReference
$result = $client->deleteHubContentReference
([/* ... */]); $promise = $client->deleteHubContentReferenceAsync
([/* ... */]);
Delete a hub content reference in order to remove a model from a private hub.
Parameter Syntax
$result = $client->deleteHubContentReference([ 'HubContentName' => '<string>', // REQUIRED 'HubContentType' => 'Model|Notebook|ModelReference', // REQUIRED 'HubName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- HubContentName
-
- Required: Yes
- Type: string
The name of the hub content to delete.
- HubContentType
-
- Required: Yes
- Type: string
The type of hub content reference to delete. The only supported type of hub content reference to delete is
ModelReference
. - HubName
-
- Required: Yes
- Type: string
The name of the hub to delete the hub content reference from.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteHumanTaskUi
$result = $client->deleteHumanTaskUi
([/* ... */]); $promise = $client->deleteHumanTaskUiAsync
([/* ... */]);
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 ListHumanTaskUis. When you delete a worker task template, it no longer appears when you call ListHumanTaskUis
.
Parameter Syntax
$result = $client->deleteHumanTaskUi([ 'HumanTaskUiName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- HumanTaskUiName
-
- Required: Yes
- Type: string
The name of the human task user interface (work task template) you want to delete.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteHyperParameterTuningJob
$result = $client->deleteHyperParameterTuningJob
([/* ... */]); $promise = $client->deleteHyperParameterTuningJobAsync
([/* ... */]);
Deletes a hyperparameter tuning job. The DeleteHyperParameterTuningJob
API deletes only the tuning job entry that was created in SageMaker when you called the CreateHyperParameterTuningJob
API. It does not delete training jobs, artifacts, or the IAM role that you specified when creating the model.
Parameter Syntax
$result = $client->deleteHyperParameterTuningJob([ 'HyperParameterTuningJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- HyperParameterTuningJobName
-
- Required: Yes
- Type: string
The name of the hyperparameter tuning job that you want to delete.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteImage
$result = $client->deleteImage
([/* ... */]); $promise = $client->deleteImageAsync
([/* ... */]);
Deletes a SageMaker image and all versions of the image. The container images aren't deleted.
Parameter Syntax
$result = $client->deleteImage([ 'ImageName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ImageName
-
- Required: Yes
- Type: string
The name of the image to delete.
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
DeleteImageVersion
$result = $client->deleteImageVersion
([/* ... */]); $promise = $client->deleteImageVersionAsync
([/* ... */]);
Deletes a version of a SageMaker image. The container image the version represents isn't deleted.
Parameter Syntax
$result = $client->deleteImageVersion([ 'Alias' => '<string>', 'ImageName' => '<string>', // REQUIRED 'Version' => <integer>, ]);
Parameter Details
Members
- Alias
-
- Type: string
The alias of the image to delete.
- ImageName
-
- Required: Yes
- Type: string
The name of the image to delete.
- Version
-
- Type: int
The version to delete.
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
DeleteInferenceComponent
$result = $client->deleteInferenceComponent
([/* ... */]); $promise = $client->deleteInferenceComponentAsync
([/* ... */]);
Deletes an inference component.
Parameter Syntax
$result = $client->deleteInferenceComponent([ 'InferenceComponentName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- InferenceComponentName
-
- Required: Yes
- Type: string
The name of the inference component to delete.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteInferenceExperiment
$result = $client->deleteInferenceExperiment
([/* ... */]); $promise = $client->deleteInferenceExperimentAsync
([/* ... */]);
Deletes an inference experiment.
This operation does not delete your endpoint, variants, or any underlying resources. This operation only deletes the metadata of your experiment.
Parameter Syntax
$result = $client->deleteInferenceExperiment([ 'Name' => '<string>', // REQUIRED ]);
Parameter Details
Members
- Name
-
- Required: Yes
- Type: string
The name of the inference experiment you want to delete.
Result Syntax
[ 'InferenceExperimentArn' => '<string>', ]
Result Details
Members
- InferenceExperimentArn
-
- Required: Yes
- Type: string
The ARN of the deleted inference experiment.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.- ResourceNotFound:
Resource being access is not found.
DeleteMlflowTrackingServer
$result = $client->deleteMlflowTrackingServer
([/* ... */]); $promise = $client->deleteMlflowTrackingServerAsync
([/* ... */]);
Deletes an MLflow Tracking Server. For more information, see Clean up MLflow resources.
Parameter Syntax
$result = $client->deleteMlflowTrackingServer([ 'TrackingServerName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TrackingServerName
-
- Required: Yes
- Type: string
The name of the the tracking server to delete.
Result Syntax
[ 'TrackingServerArn' => '<string>', ]
Result Details
Members
- TrackingServerArn
-
- Type: string
A
TrackingServerArn
object, the ARN of the tracking server that is deleted if successfully found.
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteModel
$result = $client->deleteModel
([/* ... */]); $promise = $client->deleteModelAsync
([/* ... */]);
Deletes a model. The DeleteModel
API deletes only the model entry that was created in 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.
Parameter Syntax
$result = $client->deleteModel([ 'ModelName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ModelName
-
- Required: Yes
- Type: string
The name of the model to delete.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteModelBiasJobDefinition
$result = $client->deleteModelBiasJobDefinition
([/* ... */]); $promise = $client->deleteModelBiasJobDefinitionAsync
([/* ... */]);
Deletes an Amazon SageMaker model bias job definition.
Parameter Syntax
$result = $client->deleteModelBiasJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the model bias job definition to delete.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteModelCard
$result = $client->deleteModelCard
([/* ... */]); $promise = $client->deleteModelCardAsync
([/* ... */]);
Deletes an Amazon SageMaker Model Card.
Parameter Syntax
$result = $client->deleteModelCard([ 'ModelCardName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ModelCardName
-
- Required: Yes
- Type: string
The name of the model card to delete.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
DeleteModelExplainabilityJobDefinition
$result = $client->deleteModelExplainabilityJobDefinition
([/* ... */]); $promise = $client->deleteModelExplainabilityJobDefinitionAsync
([/* ... */]);
Deletes an Amazon SageMaker model explainability job definition.
Parameter Syntax
$result = $client->deleteModelExplainabilityJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the model explainability job definition to delete.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteModelPackage
$result = $client->deleteModelPackage
([/* ... */]); $promise = $client->deleteModelPackageAsync
([/* ... */]);
Deletes a model package.
A model package is used to create SageMaker models or list on Amazon Web Services Marketplace. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
Parameter Syntax
$result = $client->deleteModelPackage([ 'ModelPackageName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ModelPackageName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the model package to delete.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
Result Syntax
[]
Result Details
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
DeleteModelPackageGroup
$result = $client->deleteModelPackageGroup
([/* ... */]); $promise = $client->deleteModelPackageGroupAsync
([/* ... */]);
Deletes the specified model group.
Parameter Syntax
$result = $client->deleteModelPackageGroup([ 'ModelPackageGroupName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ModelPackageGroupName
-
- Required: Yes
- Type: string
The name of the model group to delete.
Result Syntax
[]
Result Details
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
DeleteModelPackageGroupPolicy
$result = $client->deleteModelPackageGroupPolicy
([/* ... */]); $promise = $client->deleteModelPackageGroupPolicyAsync
([/* ... */]);
Deletes a model group resource policy.
Parameter Syntax
$result = $client->deleteModelPackageGroupPolicy([ 'ModelPackageGroupName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ModelPackageGroupName
-
- Required: Yes
- Type: string
The name of the model group for which to delete the policy.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteModelQualityJobDefinition
$result = $client->deleteModelQualityJobDefinition
([/* ... */]); $promise = $client->deleteModelQualityJobDefinitionAsync
([/* ... */]);
Deletes the secified model quality monitoring job definition.
Parameter Syntax
$result = $client->deleteModelQualityJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the model quality monitoring job definition to delete.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteMonitoringSchedule
$result = $client->deleteMonitoringSchedule
([/* ... */]); $promise = $client->deleteMonitoringScheduleAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->deleteMonitoringSchedule([ 'MonitoringScheduleName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- MonitoringScheduleName
-
- Required: Yes
- Type: string
The name of the monitoring schedule to delete.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteNotebookInstance
$result = $client->deleteNotebookInstance
([/* ... */]); $promise = $client->deleteNotebookInstanceAsync
([/* ... */]);
Deletes an 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. SageMaker removes the ML compute instance, and deletes the ML storage volume and the network interface associated with the notebook instance.
Parameter Syntax
$result = $client->deleteNotebookInstance([ 'NotebookInstanceName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- NotebookInstanceName
-
- Required: Yes
- Type: string
The name of the SageMaker notebook instance to delete.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteNotebookInstanceLifecycleConfig
$result = $client->deleteNotebookInstanceLifecycleConfig
([/* ... */]); $promise = $client->deleteNotebookInstanceLifecycleConfigAsync
([/* ... */]);
Deletes a notebook instance lifecycle configuration.
Parameter Syntax
$result = $client->deleteNotebookInstanceLifecycleConfig([ 'NotebookInstanceLifecycleConfigName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- NotebookInstanceLifecycleConfigName
-
- Required: Yes
- Type: string
The name of the lifecycle configuration to delete.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteOptimizationJob
$result = $client->deleteOptimizationJob
([/* ... */]); $promise = $client->deleteOptimizationJobAsync
([/* ... */]);
Deletes an optimization job.
Parameter Syntax
$result = $client->deleteOptimizationJob([ 'OptimizationJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- OptimizationJobName
-
- Required: Yes
- Type: string
The name that you assigned to the optimization job.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
DeletePipeline
$result = $client->deletePipeline
([/* ... */]); $promise = $client->deletePipelineAsync
([/* ... */]);
Deletes a pipeline if there are no running instances of the pipeline. To delete a pipeline, you must stop all running instances of the pipeline using the StopPipelineExecution
API. When you delete a pipeline, all instances of the pipeline are deleted.
Parameter Syntax
$result = $client->deletePipeline([ 'ClientRequestToken' => '<string>', // REQUIRED 'PipelineName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ClientRequestToken
-
- Required: Yes
- Type: string
A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
- PipelineName
-
- Required: Yes
- Type: string
The name of the pipeline to delete.
Result Syntax
[ 'PipelineArn' => '<string>', ]
Result Details
Members
- PipelineArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline to delete.
Errors
- ResourceNotFound:
Resource being access is not found.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
DeleteProject
$result = $client->deleteProject
([/* ... */]); $promise = $client->deleteProjectAsync
([/* ... */]);
Delete the specified project.
Parameter Syntax
$result = $client->deleteProject([ 'ProjectName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ProjectName
-
- Required: Yes
- Type: string
The name of the project to delete.
Result Syntax
[]
Result Details
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
DeleteSpace
$result = $client->deleteSpace
([/* ... */]); $promise = $client->deleteSpaceAsync
([/* ... */]);
Used to delete a space.
Parameter Syntax
$result = $client->deleteSpace([ 'DomainId' => '<string>', // REQUIRED 'SpaceName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DomainId
-
- Required: Yes
- Type: string
The ID of the associated domain.
- SpaceName
-
- Required: Yes
- Type: string
The name of the space.
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
DeleteStudioLifecycleConfig
$result = $client->deleteStudioLifecycleConfig
([/* ... */]); $promise = $client->deleteStudioLifecycleConfigAsync
([/* ... */]);
Deletes the Amazon SageMaker Studio Lifecycle Configuration. In order to delete the Lifecycle Configuration, there must be no running apps using the Lifecycle Configuration. You must also remove the Lifecycle Configuration from UserSettings in all Domains and UserProfiles.
Parameter Syntax
$result = $client->deleteStudioLifecycleConfig([ 'StudioLifecycleConfigName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- StudioLifecycleConfigName
-
- Required: Yes
- Type: string
The name of the Amazon SageMaker Studio Lifecycle Configuration to delete.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceInUse:
Resource being accessed is in use.
DeleteTags
$result = $client->deleteTags
([/* ... */]); $promise = $client->deleteTagsAsync
([/* ... */]);
Deletes the specified tags from an 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.
When you call this API to delete tags from a SageMaker Domain or User Profile, the deleted tags are not removed from Apps that the SageMaker Domain or User Profile launched before you called this API.
Parameter Syntax
$result = $client->deleteTags([ 'ResourceArn' => '<string>', // REQUIRED 'TagKeys' => ['<string>', ...], // REQUIRED ]);
Parameter Details
Members
- ResourceArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the resource whose tags you want to delete.
- TagKeys
-
- Required: Yes
- Type: Array of strings
An array or one or more tag keys to delete.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteTrial
$result = $client->deleteTrial
([/* ... */]); $promise = $client->deleteTrialAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->deleteTrial([ 'TrialName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TrialName
-
- Required: Yes
- Type: string
The name of the trial to delete.
Result Syntax
[ 'TrialArn' => '<string>', ]
Result Details
Members
- TrialArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial that is being deleted.
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteTrialComponent
$result = $client->deleteTrialComponent
([/* ... */]); $promise = $client->deleteTrialComponentAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->deleteTrialComponent([ 'TrialComponentName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TrialComponentName
-
- Required: Yes
- Type: string
The name of the component to delete.
Result Syntax
[ 'TrialComponentArn' => '<string>', ]
Result Details
Members
- TrialComponentArn
-
- Type: string
The Amazon Resource Name (ARN) of the component is being deleted.
Errors
- ResourceNotFound:
Resource being access is not found.
DeleteUserProfile
$result = $client->deleteUserProfile
([/* ... */]); $promise = $client->deleteUserProfileAsync
([/* ... */]);
Deletes a user profile. When a user profile is deleted, the user loses access to their EFS volume, including data, notebooks, and other artifacts.
Parameter Syntax
$result = $client->deleteUserProfile([ 'DomainId' => '<string>', // REQUIRED 'UserProfileName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DomainId
-
- Required: Yes
- Type: string
The domain ID.
- UserProfileName
-
- Required: Yes
- Type: string
The user profile name.
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
DeleteWorkforce
$result = $client->deleteWorkforce
([/* ... */]); $promise = $client->deleteWorkforceAsync
([/* ... */]);
Use this operation to delete a workforce.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use this operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.
If a private workforce contains one or more work teams, you must use the DeleteWorkteam 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 receive a ResourceInUse
error.
Parameter Syntax
$result = $client->deleteWorkforce([ 'WorkforceName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- WorkforceName
-
- Required: Yes
- Type: string
The name of the workforce.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteWorkteam
$result = $client->deleteWorkteam
([/* ... */]); $promise = $client->deleteWorkteamAsync
([/* ... */]);
Deletes an existing work team. This operation can't be undone.
Parameter Syntax
$result = $client->deleteWorkteam([ 'WorkteamName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- WorkteamName
-
- Required: Yes
- Type: string
The name of the work team to delete.
Result Syntax
[ 'Success' => true || false, ]
Result Details
Members
- Success
-
- Required: Yes
- Type: boolean
Returns
true
if the work team was successfully deleted; otherwise, returnsfalse
.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
DeregisterDevices
$result = $client->deregisterDevices
([/* ... */]); $promise = $client->deregisterDevicesAsync
([/* ... */]);
Deregisters the specified devices. After you deregister a device, you will need to re-register the devices.
Parameter Syntax
$result = $client->deregisterDevices([ 'DeviceFleetName' => '<string>', // REQUIRED 'DeviceNames' => ['<string>', ...], // REQUIRED ]);
Parameter Details
Members
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the fleet the devices belong to.
- DeviceNames
-
- Required: Yes
- Type: Array of strings
The unique IDs of the devices.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DescribeAction
$result = $client->describeAction
([/* ... */]); $promise = $client->describeActionAsync
([/* ... */]);
Describes an action.
Parameter Syntax
$result = $client->describeAction([ 'ActionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ActionName
-
- Required: Yes
- Type: string
The name of the action to describe.
Result Syntax
[ 'ActionArn' => '<string>', 'ActionName' => '<string>', 'ActionType' => '<string>', 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'Description' => '<string>', 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'LineageGroupArn' => '<string>', 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'Properties' => ['<string>', ...], 'Source' => [ 'SourceId' => '<string>', 'SourceType' => '<string>', 'SourceUri' => '<string>', ], 'Status' => 'Unknown|InProgress|Completed|Failed|Stopping|Stopped', ]
Result Details
Members
- ActionArn
-
- Type: string
The Amazon Resource Name (ARN) of the action.
- ActionName
-
- Type: string
The name of the action.
- ActionType
-
- Type: string
The type of the action.
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the action was created.
- Description
-
- Type: string
The description of the action.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the action was last modified.
- LineageGroupArn
-
- Type: string
The Amazon Resource Name (ARN) of the lineage group.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- Properties
-
- Type: Associative array of custom strings keys (StringParameterValue) to strings
A list of the action's properties.
- Source
-
- Type: ActionSource structure
The source of the action.
- Status
-
- Type: string
The status of the action.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeAlgorithm
$result = $client->describeAlgorithm
([/* ... */]); $promise = $client->describeAlgorithmAsync
([/* ... */]);
Returns a description of the specified algorithm that is in your account.
Parameter Syntax
$result = $client->describeAlgorithm([ 'AlgorithmName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- AlgorithmName
-
- Required: Yes
- Type: string
The name of the algorithm to describe.
Result Syntax
[ 'AlgorithmArn' => '<string>', 'AlgorithmDescription' => '<string>', 'AlgorithmName' => '<string>', 'AlgorithmStatus' => 'Pending|InProgress|Completed|Failed|Deleting', 'AlgorithmStatusDetails' => [ 'ImageScanStatuses' => [ [ 'FailureReason' => '<string>', 'Name' => '<string>', 'Status' => 'NotStarted|InProgress|Completed|Failed', ], // ... ], 'ValidationStatuses' => [ [ 'FailureReason' => '<string>', 'Name' => '<string>', 'Status' => 'NotStarted|InProgress|Completed|Failed', ], // ... ], ], 'CertifyForMarketplace' => true || false, 'CreationTime' => <DateTime>, 'InferenceSpecification' => [ 'Containers' => [ [ 'AdditionalS3DataSource' => [ 'CompressionType' => 'None|Gzip', 'S3DataType' => 'S3Object|S3Prefix', 'S3Uri' => '<string>', ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'Image' => '<string>', 'ImageDigest' => '<string>', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], 'ModelDataUrl' => '<string>', 'ModelInput' => [ 'DataInputConfig' => '<string>', ], 'NearestModelName' => '<string>', 'ProductId' => '<string>', ], // ... ], 'SupportedContentTypes' => ['<string>', ...], 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'SupportedTransformInstanceTypes' => ['<string>', ...], ], 'ProductId' => '<string>', 'TrainingSpecification' => [ 'AdditionalS3DataSource' => [ 'CompressionType' => 'None|Gzip', 'S3DataType' => 'S3Object|S3Prefix', 'S3Uri' => '<string>', ], 'MetricDefinitions' => [ [ 'Name' => '<string>', 'Regex' => '<string>', ], // ... ], 'SupportedHyperParameters' => [ [ 'DefaultValue' => '<string>', 'Description' => '<string>', 'IsRequired' => true || false, 'IsTunable' => true || false, 'Name' => '<string>', 'Range' => [ 'CategoricalParameterRangeSpecification' => [ 'Values' => ['<string>', ...], ], 'ContinuousParameterRangeSpecification' => [ 'MaxValue' => '<string>', 'MinValue' => '<string>', ], 'IntegerParameterRangeSpecification' => [ 'MaxValue' => '<string>', 'MinValue' => '<string>', ], ], 'Type' => 'Integer|Continuous|Categorical|FreeText', ], // ... ], 'SupportedTrainingInstanceTypes' => ['<string>', ...], 'SupportedTuningJobObjectiveMetrics' => [ [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', ], // ... ], 'SupportsDistributedTraining' => true || false, 'TrainingChannels' => [ [ 'Description' => '<string>', 'IsRequired' => true || false, 'Name' => '<string>', 'SupportedCompressionTypes' => ['<string>', ...], 'SupportedContentTypes' => ['<string>', ...], 'SupportedInputModes' => ['<string>', ...], ], // ... ], 'TrainingImage' => '<string>', 'TrainingImageDigest' => '<string>', ], 'ValidationSpecification' => [ 'ValidationProfiles' => [ [ 'ProfileName' => '<string>', 'TrainingJobDefinition' => [ 'HyperParameters' => ['<string>', ...], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', 'FileSystemAccessMode' => 'rw|ro', 'FileSystemId' => '<string>', 'FileSystemType' => 'EFS|FSxLustre', ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'InstanceGroupNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'InputMode' => 'Pipe|File|FastFile', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, ], ], // ... ], 'OutputDataConfig' => [ 'CompressionType' => 'GZIP|NONE', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'ResourceConfig' => [ 'InstanceCount' => <integer>, 'InstanceGroups' => [ [ 'InstanceCount' => <integer>, 'InstanceGroupName' => '<string>', 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', ], // ... ], 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'KeepAlivePeriodInSeconds' => <integer>, 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'StoppingCondition' => [ 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TrainingInputMode' => 'Pipe|File|FastFile', ], 'TransformJobDefinition' => [ 'BatchStrategy' => 'MultiRecord|SingleRecord', 'Environment' => ['<string>', ...], 'MaxConcurrentTransforms' => <integer>, 'MaxPayloadInMB' => <integer>, 'TransformInput' => [ 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'S3DataSource' => [ 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'SplitType' => 'None|Line|RecordIO|TFRecord', ], 'TransformOutput' => [ 'Accept' => '<string>', 'AssembleWith' => 'None|Line', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'TransformResources' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge', 'VolumeKmsKeyId' => '<string>', ], ], ], // ... ], 'ValidationRole' => '<string>', ], ]
Result Details
Members
- AlgorithmArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the algorithm.
- AlgorithmDescription
-
- Type: string
A brief summary about the algorithm.
- AlgorithmName
-
- Required: Yes
- Type: string
The name of the algorithm being described.
- AlgorithmStatus
-
- Required: Yes
- Type: string
The current status of the algorithm.
- AlgorithmStatusDetails
-
- Required: Yes
- Type: AlgorithmStatusDetails structure
Details about the current status of the algorithm.
- CertifyForMarketplace
-
- Type: boolean
Whether the algorithm is certified to be listed in Amazon Web Services Marketplace.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp specifying when the algorithm was created.
- InferenceSpecification
-
- Type: InferenceSpecification structure
Details about inference jobs that the algorithm runs.
- ProductId
-
- Type: string
The product identifier of the algorithm.
- TrainingSpecification
-
- Required: Yes
- Type: TrainingSpecification structure
Details about training jobs run by this algorithm.
- ValidationSpecification
-
- Type: AlgorithmValidationSpecification structure
Details about configurations for one or more training jobs that SageMaker runs to test the algorithm.
Errors
There are no errors described for this operation.
DescribeApp
$result = $client->describeApp
([/* ... */]); $promise = $client->describeAppAsync
([/* ... */]);
Describes the app.
Parameter Syntax
$result = $client->describeApp([ 'AppName' => '<string>', // REQUIRED 'AppType' => 'JupyterServer|KernelGateway|DetailedProfiler|TensorBoard|CodeEditor|JupyterLab|RStudioServerPro|RSessionGateway|Canvas', // REQUIRED 'DomainId' => '<string>', // REQUIRED 'SpaceName' => '<string>', 'UserProfileName' => '<string>', ]);
Parameter Details
Members
- AppName
-
- Required: Yes
- Type: string
The name of the app.
- AppType
-
- Required: Yes
- Type: string
The type of app.
- DomainId
-
- Required: Yes
- Type: string
The domain ID.
- SpaceName
-
- Type: string
The name of the space.
- UserProfileName
-
- Type: string
The user profile name. If this value is not set, then
SpaceName
must be set.
Result Syntax
[ 'AppArn' => '<string>', 'AppName' => '<string>', 'AppType' => 'JupyterServer|KernelGateway|DetailedProfiler|TensorBoard|CodeEditor|JupyterLab|RStudioServerPro|RSessionGateway|Canvas', 'CreationTime' => <DateTime>, 'DomainId' => '<string>', 'FailureReason' => '<string>', 'LastHealthCheckTimestamp' => <DateTime>, 'LastUserActivityTimestamp' => <DateTime>, 'ResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'SpaceName' => '<string>', 'Status' => 'Deleted|Deleting|Failed|InService|Pending', 'UserProfileName' => '<string>', ]
Result Details
Members
- AppArn
-
- Type: string
The Amazon Resource Name (ARN) of the app.
- AppName
-
- Type: string
The name of the app.
- AppType
-
- Type: string
The type of app.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time of the application.
After an application has been shut down for 24 hours, SageMaker deletes all metadata for the application. To be considered an update and retain application metadata, applications must be restarted within 24 hours after the previous application has been shut down. After this time window, creation of an application is considered a new application rather than an update of the previous application.
- DomainId
-
- Type: string
The domain ID.
- FailureReason
-
- Type: string
The failure reason.
- LastHealthCheckTimestamp
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of the last health check.
- LastUserActivityTimestamp
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of the last user's activity.
LastUserActivityTimestamp
is also updated when SageMaker performs health checks without user activity. As a result, this value is set to the same value asLastHealthCheckTimestamp
. - ResourceSpec
-
- Type: ResourceSpec structure
The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
- SpaceName
-
- Type: string
The name of the space. If this value is not set, then
UserProfileName
must be set. - Status
-
- Type: string
The status.
- UserProfileName
-
- Type: string
The user profile name.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeAppImageConfig
$result = $client->describeAppImageConfig
([/* ... */]); $promise = $client->describeAppImageConfigAsync
([/* ... */]);
Describes an AppImageConfig.
Parameter Syntax
$result = $client->describeAppImageConfig([ 'AppImageConfigName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- AppImageConfigName
-
- Required: Yes
- Type: string
The name of the AppImageConfig to describe.
Result Syntax
[ 'AppImageConfigArn' => '<string>', 'AppImageConfigName' => '<string>', 'CodeEditorAppImageConfig' => [ 'ContainerConfig' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ContainerEnvironmentVariables' => ['<string>', ...], ], 'FileSystemConfig' => [ 'DefaultGid' => <integer>, 'DefaultUid' => <integer>, 'MountPath' => '<string>', ], ], 'CreationTime' => <DateTime>, 'JupyterLabAppImageConfig' => [ 'ContainerConfig' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ContainerEnvironmentVariables' => ['<string>', ...], ], 'FileSystemConfig' => [ 'DefaultGid' => <integer>, 'DefaultUid' => <integer>, 'MountPath' => '<string>', ], ], 'KernelGatewayImageConfig' => [ 'FileSystemConfig' => [ 'DefaultGid' => <integer>, 'DefaultUid' => <integer>, 'MountPath' => '<string>', ], 'KernelSpecs' => [ [ 'DisplayName' => '<string>', 'Name' => '<string>', ], // ... ], ], 'LastModifiedTime' => <DateTime>, ]
Result Details
Members
- AppImageConfigArn
-
- Type: string
The ARN of the AppImageConfig.
- AppImageConfigName
-
- Type: string
The name of the AppImageConfig.
- CodeEditorAppImageConfig
-
- Type: CodeEditorAppImageConfig structure
The configuration of the Code Editor app.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the AppImageConfig was created.
- JupyterLabAppImageConfig
-
- Type: JupyterLabAppImageConfig structure
The configuration of the JupyterLab app.
- KernelGatewayImageConfig
-
- Type: KernelGatewayImageConfig structure
The configuration of a KernelGateway app.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the AppImageConfig was last modified.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeArtifact
$result = $client->describeArtifact
([/* ... */]); $promise = $client->describeArtifactAsync
([/* ... */]);
Describes an artifact.
Parameter Syntax
$result = $client->describeArtifact([ 'ArtifactArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ArtifactArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the artifact to describe.
Result Syntax
[ 'ArtifactArn' => '<string>', 'ArtifactName' => '<string>', 'ArtifactType' => '<string>', 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'LineageGroupArn' => '<string>', 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'Properties' => ['<string>', ...], 'Source' => [ 'SourceTypes' => [ [ 'SourceIdType' => 'MD5Hash|S3ETag|S3Version|Custom', 'Value' => '<string>', ], // ... ], 'SourceUri' => '<string>', ], ]
Result Details
Members
- ArtifactArn
-
- Type: string
The Amazon Resource Name (ARN) of the artifact.
- ArtifactName
-
- Type: string
The name of the artifact.
- ArtifactType
-
- Type: string
The type of the artifact.
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the artifact was created.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the artifact was last modified.
- LineageGroupArn
-
- Type: string
The Amazon Resource Name (ARN) of the lineage group.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- Properties
-
- Type: Associative array of custom strings keys (StringParameterValue) to strings
A list of the artifact's properties.
- Source
-
- Type: ArtifactSource structure
The source of the artifact.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeAutoMLJob
$result = $client->describeAutoMLJob
([/* ... */]); $promise = $client->describeAutoMLJobAsync
([/* ... */]);
Returns information about an AutoML job created by calling CreateAutoMLJob.
AutoML jobs created by calling CreateAutoMLJobV2 cannot be described by DescribeAutoMLJob
.
Parameter Syntax
$result = $client->describeAutoMLJob([ 'AutoMLJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- AutoMLJobName
-
- Required: Yes
- Type: string
Requests information about an AutoML job using its unique name.
Result Syntax
[ 'AutoMLJobArn' => '<string>', 'AutoMLJobArtifacts' => [ 'CandidateDefinitionNotebookLocation' => '<string>', 'DataExplorationNotebookLocation' => '<string>', ], 'AutoMLJobConfig' => [ 'CandidateGenerationConfig' => [ 'AlgorithmsConfig' => [ [ 'AutoMLAlgorithms' => ['<string>', ...], ], // ... ], 'FeatureSpecificationS3Uri' => '<string>', ], 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'DataSplitConfig' => [ 'ValidationFraction' => <float>, ], 'Mode' => 'AUTO|ENSEMBLING|HYPERPARAMETER_TUNING', 'SecurityConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'VolumeKmsKeyId' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], ], 'AutoMLJobName' => '<string>', 'AutoMLJobObjective' => [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', ], 'AutoMLJobSecondaryStatus' => 'Starting|MaxCandidatesReached|Failed|Stopped|MaxAutoMLJobRuntimeReached|Stopping|CandidateDefinitionsGenerated|Completed|ExplainabilityError|DeployingModel|ModelDeploymentError|GeneratingModelInsightsReport|ModelInsightsError|AnalyzingData|FeatureEngineering|ModelTuning|GeneratingExplainabilityReport|TrainingModels|PreTraining', 'AutoMLJobStatus' => 'Completed|InProgress|Failed|Stopped|Stopping', 'BestCandidate' => [ 'CandidateName' => '<string>', 'CandidateProperties' => [ 'CandidateArtifactLocations' => [ 'BacktestResults' => '<string>', 'Explainability' => '<string>', 'ModelInsights' => '<string>', ], 'CandidateMetrics' => [ [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', 'Set' => 'Train|Validation|Test', 'StandardMetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|MAE|R2|BalancedAccuracy|Precision|PrecisionMacro|Recall|RecallMacro|LogLoss|InferenceLatency|MAPE|MASE|WAPE|AverageWeightedQuantileLoss|Rouge1|Rouge2|RougeL|RougeLSum|Perplexity|ValidationLoss|TrainingLoss', 'Value' => <float>, ], // ... ], ], 'CandidateStatus' => 'Completed|InProgress|Failed|Stopped|Stopping', 'CandidateSteps' => [ [ 'CandidateStepArn' => '<string>', 'CandidateStepName' => '<string>', 'CandidateStepType' => 'AWS::SageMaker::TrainingJob|AWS::SageMaker::TransformJob|AWS::SageMaker::ProcessingJob', ], // ... ], 'CreationTime' => <DateTime>, 'EndTime' => <DateTime>, 'FailureReason' => '<string>', 'FinalAutoMLJobObjectiveMetric' => [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', 'StandardMetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', 'Type' => 'Maximize|Minimize', 'Value' => <float>, ], 'InferenceContainerDefinitions' => [ '<AutoMLProcessingUnit>' => [ [ 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ModelDataUrl' => '<string>', ], // ... ], // ... ], 'InferenceContainers' => [ [ 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ModelDataUrl' => '<string>', ], // ... ], 'LastModifiedTime' => <DateTime>, 'ObjectiveStatus' => 'Succeeded|Pending|Failed', ], 'CreationTime' => <DateTime>, 'EndTime' => <DateTime>, 'FailureReason' => '<string>', 'GenerateCandidateDefinitionsOnly' => true || false, 'InputDataConfig' => [ [ 'ChannelType' => 'training|validation', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'S3DataSource' => [ 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'SampleWeightAttributeName' => '<string>', 'TargetAttributeName' => '<string>', ], // ... ], 'LastModifiedTime' => <DateTime>, 'ModelDeployConfig' => [ 'AutoGenerateEndpointName' => true || false, 'EndpointName' => '<string>', ], 'ModelDeployResult' => [ 'EndpointName' => '<string>', ], 'OutputDataConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'PartialFailureReasons' => [ [ 'PartialFailureMessage' => '<string>', ], // ... ], 'ProblemType' => 'BinaryClassification|MulticlassClassification|Regression', 'ResolvedAttributes' => [ 'AutoMLJobObjective' => [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', ], 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'ProblemType' => 'BinaryClassification|MulticlassClassification|Regression', ], 'RoleArn' => '<string>', ]
Result Details
Members
- AutoMLJobArn
-
- Required: Yes
- Type: string
Returns the ARN of the AutoML job.
- AutoMLJobArtifacts
-
- Type: AutoMLJobArtifacts structure
Returns information on the job's artifacts found in
AutoMLJobArtifacts
. - AutoMLJobConfig
-
- Type: AutoMLJobConfig structure
Returns the configuration for the AutoML job.
- AutoMLJobName
-
- Required: Yes
- Type: string
Returns the name of the AutoML job.
- AutoMLJobObjective
-
- Type: AutoMLJobObjective structure
Returns the job's objective.
- AutoMLJobSecondaryStatus
-
- Required: Yes
- Type: string
Returns the secondary status of the AutoML job.
- AutoMLJobStatus
-
- Required: Yes
- Type: string
Returns the status of the AutoML job.
- BestCandidate
-
- Type: AutoMLCandidate structure
The best model candidate selected by SageMaker Autopilot using both the best objective metric and lowest InferenceLatency for an experiment.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Returns the creation time of the AutoML job.
- EndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Returns the end time of the AutoML job.
- FailureReason
-
- Type: string
Returns the failure reason for an AutoML job, when applicable.
- GenerateCandidateDefinitionsOnly
-
- Type: boolean
Indicates whether the output for an AutoML job generates candidate definitions only.
- InputDataConfig
-
- Required: Yes
- Type: Array of AutoMLChannel structures
Returns the input data configuration for the AutoML job.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Returns the job's last modified time.
- ModelDeployConfig
-
- Type: ModelDeployConfig structure
Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
- ModelDeployResult
-
- Type: ModelDeployResult structure
Provides information about endpoint for the model deployment.
- OutputDataConfig
-
- Required: Yes
- Type: AutoMLOutputDataConfig structure
Returns the job's output data config.
- PartialFailureReasons
-
- Type: Array of AutoMLPartialFailureReason structures
Returns a list of reasons for partial failures within an AutoML job.
- ProblemType
-
- Type: string
Returns the job's problem type.
- ResolvedAttributes
-
- Type: ResolvedAttributes structure
Contains
ProblemType
,AutoMLJobObjective
, andCompletionCriteria
. If you do not provide these values, they are inferred. - RoleArn
-
- Required: Yes
- Type: string
The ARN of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeAutoMLJobV2
$result = $client->describeAutoMLJobV2
([/* ... */]); $promise = $client->describeAutoMLJobV2Async
([/* ... */]);
Returns information about an AutoML job created by calling CreateAutoMLJobV2 or CreateAutoMLJob.
Parameter Syntax
$result = $client->describeAutoMLJobV2([ 'AutoMLJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- AutoMLJobName
-
- Required: Yes
- Type: string
Requests information about an AutoML job V2 using its unique name.
Result Syntax
[ 'AutoMLComputeConfig' => [ 'EmrServerlessComputeConfig' => [ 'ExecutionRoleARN' => '<string>', ], ], 'AutoMLJobArn' => '<string>', 'AutoMLJobArtifacts' => [ 'CandidateDefinitionNotebookLocation' => '<string>', 'DataExplorationNotebookLocation' => '<string>', ], 'AutoMLJobInputDataConfig' => [ [ 'ChannelType' => 'training|validation', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'S3DataSource' => [ 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], ], // ... ], 'AutoMLJobName' => '<string>', 'AutoMLJobObjective' => [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', ], 'AutoMLJobSecondaryStatus' => 'Starting|MaxCandidatesReached|Failed|Stopped|MaxAutoMLJobRuntimeReached|Stopping|CandidateDefinitionsGenerated|Completed|ExplainabilityError|DeployingModel|ModelDeploymentError|GeneratingModelInsightsReport|ModelInsightsError|AnalyzingData|FeatureEngineering|ModelTuning|GeneratingExplainabilityReport|TrainingModels|PreTraining', 'AutoMLJobStatus' => 'Completed|InProgress|Failed|Stopped|Stopping', 'AutoMLProblemTypeConfig' => [ 'ImageClassificationJobConfig' => [ 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], ], 'TabularJobConfig' => [ 'CandidateGenerationConfig' => [ 'AlgorithmsConfig' => [ [ 'AutoMLAlgorithms' => ['<string>', ...], ], // ... ], ], 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'FeatureSpecificationS3Uri' => '<string>', 'GenerateCandidateDefinitionsOnly' => true || false, 'Mode' => 'AUTO|ENSEMBLING|HYPERPARAMETER_TUNING', 'ProblemType' => 'BinaryClassification|MulticlassClassification|Regression', 'SampleWeightAttributeName' => '<string>', 'TargetAttributeName' => '<string>', ], 'TextClassificationJobConfig' => [ 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'ContentColumn' => '<string>', 'TargetLabelColumn' => '<string>', ], 'TextGenerationJobConfig' => [ 'BaseModelName' => '<string>', 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'TextGenerationHyperParameters' => ['<string>', ...], ], 'TimeSeriesForecastingJobConfig' => [ 'CandidateGenerationConfig' => [ 'AlgorithmsConfig' => [ [ 'AutoMLAlgorithms' => ['<string>', ...], ], // ... ], ], 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'FeatureSpecificationS3Uri' => '<string>', 'ForecastFrequency' => '<string>', 'ForecastHorizon' => <integer>, 'ForecastQuantiles' => ['<string>', ...], 'HolidayConfig' => [ [ 'CountryCode' => '<string>', ], // ... ], 'TimeSeriesConfig' => [ 'GroupingAttributeNames' => ['<string>', ...], 'ItemIdentifierAttributeName' => '<string>', 'TargetAttributeName' => '<string>', 'TimestampAttributeName' => '<string>', ], 'Transformations' => [ 'Aggregation' => ['<string>', ...], 'Filling' => [ '<TransformationAttributeName>' => ['<string>', ...], // ... ], ], ], ], 'AutoMLProblemTypeConfigName' => 'ImageClassification|TextClassification|TimeSeriesForecasting|Tabular|TextGeneration', 'BestCandidate' => [ 'CandidateName' => '<string>', 'CandidateProperties' => [ 'CandidateArtifactLocations' => [ 'BacktestResults' => '<string>', 'Explainability' => '<string>', 'ModelInsights' => '<string>', ], 'CandidateMetrics' => [ [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', 'Set' => 'Train|Validation|Test', 'StandardMetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|MAE|R2|BalancedAccuracy|Precision|PrecisionMacro|Recall|RecallMacro|LogLoss|InferenceLatency|MAPE|MASE|WAPE|AverageWeightedQuantileLoss|Rouge1|Rouge2|RougeL|RougeLSum|Perplexity|ValidationLoss|TrainingLoss', 'Value' => <float>, ], // ... ], ], 'CandidateStatus' => 'Completed|InProgress|Failed|Stopped|Stopping', 'CandidateSteps' => [ [ 'CandidateStepArn' => '<string>', 'CandidateStepName' => '<string>', 'CandidateStepType' => 'AWS::SageMaker::TrainingJob|AWS::SageMaker::TransformJob|AWS::SageMaker::ProcessingJob', ], // ... ], 'CreationTime' => <DateTime>, 'EndTime' => <DateTime>, 'FailureReason' => '<string>', 'FinalAutoMLJobObjectiveMetric' => [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', 'StandardMetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', 'Type' => 'Maximize|Minimize', 'Value' => <float>, ], 'InferenceContainerDefinitions' => [ '<AutoMLProcessingUnit>' => [ [ 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ModelDataUrl' => '<string>', ], // ... ], // ... ], 'InferenceContainers' => [ [ 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ModelDataUrl' => '<string>', ], // ... ], 'LastModifiedTime' => <DateTime>, 'ObjectiveStatus' => 'Succeeded|Pending|Failed', ], 'CreationTime' => <DateTime>, 'DataSplitConfig' => [ 'ValidationFraction' => <float>, ], 'EndTime' => <DateTime>, 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'ModelDeployConfig' => [ 'AutoGenerateEndpointName' => true || false, 'EndpointName' => '<string>', ], 'ModelDeployResult' => [ 'EndpointName' => '<string>', ], 'OutputDataConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'PartialFailureReasons' => [ [ 'PartialFailureMessage' => '<string>', ], // ... ], 'ResolvedAttributes' => [ 'AutoMLJobObjective' => [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', ], 'AutoMLProblemTypeResolvedAttributes' => [ 'TabularResolvedAttributes' => [ 'ProblemType' => 'BinaryClassification|MulticlassClassification|Regression', ], 'TextGenerationResolvedAttributes' => [ 'BaseModelName' => '<string>', ], ], 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], ], 'RoleArn' => '<string>', 'SecurityConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'VolumeKmsKeyId' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], ]
Result Details
Members
- AutoMLComputeConfig
-
- Type: AutoMLComputeConfig structure
The compute configuration used for the AutoML job V2.
- AutoMLJobArn
-
- Required: Yes
- Type: string
Returns the Amazon Resource Name (ARN) of the AutoML job V2.
- AutoMLJobArtifacts
-
- Type: AutoMLJobArtifacts structure
The artifacts that are generated during an AutoML job.
- AutoMLJobInputDataConfig
-
- Required: Yes
- Type: Array of AutoMLJobChannel structures
Returns an array of channel objects describing the input data and their location.
- AutoMLJobName
-
- Required: Yes
- Type: string
Returns the name of the AutoML job V2.
- AutoMLJobObjective
-
- Type: AutoMLJobObjective structure
Returns the job's objective.
- AutoMLJobSecondaryStatus
-
- Required: Yes
- Type: string
Returns the secondary status of the AutoML job V2.
- AutoMLJobStatus
-
- Required: Yes
- Type: string
Returns the status of the AutoML job V2.
- AutoMLProblemTypeConfig
-
- Type: AutoMLProblemTypeConfig structure
Returns the configuration settings of the problem type set for the AutoML job V2.
- AutoMLProblemTypeConfigName
-
- Type: string
Returns the name of the problem type configuration set for the AutoML job V2.
- BestCandidate
-
- Type: AutoMLCandidate structure
Information about the candidate produced by an AutoML training job V2, including its status, steps, and other properties.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Returns the creation time of the AutoML job V2.
- DataSplitConfig
-
- Type: AutoMLDataSplitConfig structure
Returns the configuration settings of how the data are split into train and validation datasets.
- EndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Returns the end time of the AutoML job V2.
- FailureReason
-
- Type: string
Returns the reason for the failure of the AutoML job V2, when applicable.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Returns the job's last modified time.
- ModelDeployConfig
-
- Type: ModelDeployConfig structure
Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
- ModelDeployResult
-
- Type: ModelDeployResult structure
Provides information about endpoint for the model deployment.
- OutputDataConfig
-
- Required: Yes
- Type: AutoMLOutputDataConfig structure
Returns the job's output data config.
- PartialFailureReasons
-
- Type: Array of AutoMLPartialFailureReason structures
Returns a list of reasons for partial failures within an AutoML job V2.
- ResolvedAttributes
-
- Type: AutoMLResolvedAttributes structure
Returns the resolved attributes used by the AutoML job V2.
- RoleArn
-
- Required: Yes
- Type: string
The ARN of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
- SecurityConfig
-
- Type: AutoMLSecurityConfig structure
Returns the security configuration for traffic encryption or Amazon VPC settings.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeCluster
$result = $client->describeCluster
([/* ... */]); $promise = $client->describeClusterAsync
([/* ... */]);
Retrieves information of a SageMaker HyperPod cluster.
Parameter Syntax
$result = $client->describeCluster([ 'ClusterName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ClusterName
-
- Required: Yes
- Type: string
The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.
Result Syntax
[ 'ClusterArn' => '<string>', 'ClusterName' => '<string>', 'ClusterStatus' => 'Creating|Deleting|Failed|InService|RollingBack|SystemUpdating|Updating', 'CreationTime' => <DateTime>, 'FailureMessage' => '<string>', 'InstanceGroups' => [ [ 'CurrentCount' => <integer>, 'ExecutionRole' => '<string>', 'InstanceGroupName' => '<string>', 'InstanceStorageConfigs' => [ [ 'EbsVolumeConfig' => [ 'VolumeSizeInGB' => <integer>, ], ], // ... ], 'InstanceType' => 'ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.c5n.large|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge', 'LifeCycleConfig' => [ 'OnCreate' => '<string>', 'SourceS3Uri' => '<string>', ], 'TargetCount' => <integer>, 'ThreadsPerCore' => <integer>, ], // ... ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ]
Result Details
Members
- ClusterArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.
- ClusterName
-
- Type: string
The name of the SageMaker HyperPod cluster.
- ClusterStatus
-
- Required: Yes
- Type: string
The status of the SageMaker HyperPod cluster.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the SageMaker Cluster is created.
- FailureMessage
-
- Type: string
The failure message of the SageMaker HyperPod cluster.
- InstanceGroups
-
- Required: Yes
- Type: Array of ClusterInstanceGroupDetails structures
The instance groups of the SageMaker HyperPod cluster.
- VpcConfig
-
- Type: VpcConfig structure
Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeClusterNode
$result = $client->describeClusterNode
([/* ... */]); $promise = $client->describeClusterNodeAsync
([/* ... */]);
Retrieves information of a node (also called a instance interchangeably) of a SageMaker HyperPod cluster.
Parameter Syntax
$result = $client->describeClusterNode([ 'ClusterName' => '<string>', // REQUIRED 'NodeId' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ClusterName
-
- Required: Yes
- Type: string
The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster in which the node is.
- NodeId
-
- Required: Yes
- Type: string
The ID of the SageMaker HyperPod cluster node.
Result Syntax
[ 'NodeDetails' => [ 'InstanceGroupName' => '<string>', 'InstanceId' => '<string>', 'InstanceStatus' => [ 'Message' => '<string>', 'Status' => 'Running|Failure|Pending|ShuttingDown|SystemUpdating', ], 'InstanceStorageConfigs' => [ [ 'EbsVolumeConfig' => [ 'VolumeSizeInGB' => <integer>, ], ], // ... ], 'InstanceType' => 'ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.c5n.large|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge', 'LaunchTime' => <DateTime>, 'LifeCycleConfig' => [ 'OnCreate' => '<string>', 'SourceS3Uri' => '<string>', ], 'Placement' => [ 'AvailabilityZone' => '<string>', 'AvailabilityZoneId' => '<string>', ], 'PrivateDnsHostname' => '<string>', 'PrivatePrimaryIp' => '<string>', 'ThreadsPerCore' => <integer>, ], ]
Result Details
Members
- NodeDetails
-
- Required: Yes
- Type: ClusterNodeDetails structure
The details of the SageMaker HyperPod cluster node.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeCodeRepository
$result = $client->describeCodeRepository
([/* ... */]); $promise = $client->describeCodeRepositoryAsync
([/* ... */]);
Gets details about the specified Git repository.
Parameter Syntax
$result = $client->describeCodeRepository([ 'CodeRepositoryName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- CodeRepositoryName
-
- Required: Yes
- Type: string
The name of the Git repository to describe.
Result Syntax
[ 'CodeRepositoryArn' => '<string>', 'CodeRepositoryName' => '<string>', 'CreationTime' => <DateTime>, 'GitConfig' => [ 'Branch' => '<string>', 'RepositoryUrl' => '<string>', 'SecretArn' => '<string>', ], 'LastModifiedTime' => <DateTime>, ]
Result Details
Members
- CodeRepositoryArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the Git repository.
- CodeRepositoryName
-
- Required: Yes
- Type: string
The name of the Git repository.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the repository was created.
- GitConfig
-
- Type: GitConfig structure
Configuration details about the repository, including the URL where the repository is located, the default branch, and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the repository was last changed.
Errors
There are no errors described for this operation.
DescribeCompilationJob
$result = $client->describeCompilationJob
([/* ... */]); $promise = $client->describeCompilationJobAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->describeCompilationJob([ 'CompilationJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- CompilationJobName
-
- Required: Yes
- Type: string
The name of the model compilation job that you want information about.
Result Syntax
[ 'CompilationEndTime' => <DateTime>, 'CompilationJobArn' => '<string>', 'CompilationJobName' => '<string>', 'CompilationJobStatus' => 'INPROGRESS|COMPLETED|FAILED|STARTING|STOPPING|STOPPED', 'CompilationStartTime' => <DateTime>, 'CreationTime' => <DateTime>, 'DerivedInformation' => [ 'DerivedDataInputConfig' => '<string>', ], 'FailureReason' => '<string>', 'InferenceImage' => '<string>', 'InputConfig' => [ 'DataInputConfig' => '<string>', 'Framework' => 'TENSORFLOW|KERAS|MXNET|ONNX|PYTORCH|XGBOOST|TFLITE|DARKNET|SKLEARN', 'FrameworkVersion' => '<string>', 'S3Uri' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'ModelArtifacts' => [ 'S3ModelArtifacts' => '<string>', ], 'ModelDigests' => [ 'ArtifactDigest' => '<string>', ], 'ModelPackageVersionArn' => '<string>', 'OutputConfig' => [ 'CompilerOptions' => '<string>', 'KmsKeyId' => '<string>', 'S3OutputLocation' => '<string>', 'TargetDevice' => 'lambda|ml_m4|ml_m5|ml_m6g|ml_c4|ml_c5|ml_c6g|ml_p2|ml_p3|ml_g4dn|ml_inf1|ml_inf2|ml_trn1|ml_eia2|jetson_tx1|jetson_tx2|jetson_nano|jetson_xavier|rasp3b|rasp4b|imx8qm|deeplens|rk3399|rk3288|aisage|sbe_c|qcs605|qcs603|sitara_am57x|amba_cv2|amba_cv22|amba_cv25|x86_win32|x86_win64|coreml|jacinto_tda4vm|imx8mplus', 'TargetPlatform' => [ 'Accelerator' => 'INTEL_GRAPHICS|MALI|NVIDIA|NNA', 'Arch' => 'X86_64|X86|ARM64|ARM_EABI|ARM_EABIHF', 'Os' => 'ANDROID|LINUX', ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ]
Result Details
Members
- CompilationEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the model compilation job on a compilation job instance ended. For a successful or stopped job, this is when the job's model artifacts have finished uploading. For a failed job, this is when Amazon SageMaker detected that the job failed.
- CompilationJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model compilation job.
- CompilationJobName
-
- Required: Yes
- Type: string
The name of the model compilation job.
- CompilationJobStatus
-
- Required: Yes
- Type: string
The status of the model compilation job.
- CompilationStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the model compilation job started the
CompilationJob
instances.You are billed for the time between this timestamp and the timestamp in the
CompilationEndTime
field. In Amazon CloudWatch Logs, the start time might be later than this time. That's because it takes time to download the compilation job, which depends on the size of the compilation job container. - CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the model compilation job was created.
- DerivedInformation
-
- Type: DerivedInformation structure
Information that SageMaker Neo automatically derived about the model.
- FailureReason
-
- Required: Yes
- Type: string
If a model compilation job failed, the reason it failed.
- InferenceImage
-
- Type: string
The inference image to use when compiling a model. Specify an image only if the target device is a cloud instance.
- InputConfig
-
- Required: Yes
- Type: InputConfig structure
Information about the location in Amazon S3 of the input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the status of the model compilation job was last modified.
- ModelArtifacts
-
- Required: Yes
- Type: ModelArtifacts structure
Information about the location in Amazon S3 that has been configured for storing the model artifacts used in the compilation job.
- ModelDigests
-
- Type: ModelDigests structure
Provides a BLAKE2 hash value that identifies the compiled model artifacts in Amazon S3.
- ModelPackageVersionArn
-
- Type: string
The Amazon Resource Name (ARN) of the versioned model package that was provided to SageMaker Neo when you initiated a compilation job.
- OutputConfig
-
- Required: Yes
- Type: OutputConfig structure
Information about the output location for the compiled model and the target device that the model runs on.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker assumes to perform the model compilation job.
- StoppingCondition
-
- Required: Yes
- Type: StoppingCondition structure
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.
- VpcConfig
-
- Type: NeoVpcConfig structure
A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeContext
$result = $client->describeContext
([/* ... */]); $promise = $client->describeContextAsync
([/* ... */]);
Describes a context.
Parameter Syntax
$result = $client->describeContext([ 'ContextName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ContextName
-
- Required: Yes
- Type: string
The name of the context to describe.
Result Syntax
[ 'ContextArn' => '<string>', 'ContextName' => '<string>', 'ContextType' => '<string>', 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'Description' => '<string>', 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'LineageGroupArn' => '<string>', 'Properties' => ['<string>', ...], 'Source' => [ 'SourceId' => '<string>', 'SourceType' => '<string>', 'SourceUri' => '<string>', ], ]
Result Details
Members
- ContextArn
-
- Type: string
The Amazon Resource Name (ARN) of the context.
- ContextName
-
- Type: string
The name of the context.
- ContextType
-
- Type: string
The type of the context.
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the context was created.
- Description
-
- Type: string
The description of the context.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the context was last modified.
- LineageGroupArn
-
- Type: string
The Amazon Resource Name (ARN) of the lineage group.
- Properties
-
- Type: Associative array of custom strings keys (StringParameterValue) to strings
A list of the context's properties.
- Source
-
- Type: ContextSource structure
The source of the context.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeDataQualityJobDefinition
$result = $client->describeDataQualityJobDefinition
([/* ... */]); $promise = $client->describeDataQualityJobDefinitionAsync
([/* ... */]);
Gets the details of a data quality monitoring job definition.
Parameter Syntax
$result = $client->describeDataQualityJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the data quality monitoring job definition to describe.
Result Syntax
[ 'CreationTime' => <DateTime>, 'DataQualityAppSpecification' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', 'PostAnalyticsProcessorSourceUri' => '<string>', 'RecordPreprocessorSourceUri' => '<string>', ], 'DataQualityBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], 'StatisticsResource' => [ 'S3Uri' => '<string>', ], ], 'DataQualityJobInput' => [ 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', 'DatasetFormat' => [ 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], ], 'DataQualityJobOutputConfig' => [ 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ [ 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'JobDefinitionArn' => '<string>', 'JobDefinitionName' => '<string>', 'JobResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the data quality monitoring job definition was created.
- DataQualityAppSpecification
-
- Required: Yes
- Type: DataQualityAppSpecification structure
Information about the container that runs the data quality monitoring job.
- DataQualityBaselineConfig
-
- Type: DataQualityBaselineConfig structure
The constraints and baselines for the data quality monitoring job definition.
- DataQualityJobInput
-
- Required: Yes
- Type: DataQualityJobInput structure
The list of inputs for the data quality monitoring job. Currently endpoints are supported.
- DataQualityJobOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The output configuration for monitoring jobs.
- JobDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the data quality monitoring job definition.
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the data quality monitoring job definition.
- JobResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources to deploy for a monitoring job.
- NetworkConfig
-
- Type: MonitoringNetworkConfig structure
The networking configuration for the data quality monitoring job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
A time limit for how long the monitoring job is allowed to run before stopping.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeDevice
$result = $client->describeDevice
([/* ... */]); $promise = $client->describeDeviceAsync
([/* ... */]);
Describes the device.
Parameter Syntax
$result = $client->describeDevice([ 'DeviceFleetName' => '<string>', // REQUIRED 'DeviceName' => '<string>', // REQUIRED 'NextToken' => '<string>', ]);
Parameter Details
Members
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the fleet the devices belong to.
- DeviceName
-
- Required: Yes
- Type: string
The unique ID of the device.
- NextToken
-
- Type: string
Next token of device description.
Result Syntax
[ 'AgentVersion' => '<string>', 'Description' => '<string>', 'DeviceArn' => '<string>', 'DeviceFleetName' => '<string>', 'DeviceName' => '<string>', 'IotThingName' => '<string>', 'LatestHeartbeat' => <DateTime>, 'MaxModels' => <integer>, 'Models' => [ [ 'LatestInference' => <DateTime>, 'LatestSampleTime' => <DateTime>, 'ModelName' => '<string>', 'ModelVersion' => '<string>', ], // ... ], 'NextToken' => '<string>', 'RegistrationTime' => <DateTime>, ]
Result Details
Members
- AgentVersion
-
- Type: string
Edge Manager agent version.
- Description
-
- Type: string
A description of the device.
- DeviceArn
-
- Type: string
The Amazon Resource Name (ARN) of the device.
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the fleet the device belongs to.
- DeviceName
-
- Required: Yes
- Type: string
The unique identifier of the device.
- IotThingName
-
- Type: string
The Amazon Web Services Internet of Things (IoT) object thing name associated with the device.
- LatestHeartbeat
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last heartbeat received from the device.
- MaxModels
-
- Type: int
The maximum number of models.
- Models
-
- Type: Array of EdgeModel structures
Models on the device.
- NextToken
-
- Type: string
The response from the last list when returning a list large enough to need tokening.
- RegistrationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of the last registration or de-reregistration.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeDeviceFleet
$result = $client->describeDeviceFleet
([/* ... */]); $promise = $client->describeDeviceFleetAsync
([/* ... */]);
A description of the fleet the device belongs to.
Parameter Syntax
$result = $client->describeDeviceFleet([ 'DeviceFleetName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the fleet.
Result Syntax
[ 'CreationTime' => <DateTime>, 'Description' => '<string>', 'DeviceFleetArn' => '<string>', 'DeviceFleetName' => '<string>', 'IotRoleAlias' => '<string>', 'LastModifiedTime' => <DateTime>, 'OutputConfig' => [ 'KmsKeyId' => '<string>', 'PresetDeploymentConfig' => '<string>', 'PresetDeploymentType' => 'GreengrassV2Component', 'S3OutputLocation' => '<string>', ], 'RoleArn' => '<string>', ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Timestamp of when the device fleet was created.
- Description
-
- Type: string
A description of the fleet.
- DeviceFleetArn
-
- Required: Yes
- Type: string
The The Amazon Resource Name (ARN) of the fleet.
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the fleet.
- IotRoleAlias
-
- Type: string
The Amazon Resource Name (ARN) alias created in Amazon Web Services Internet of Things (IoT).
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Timestamp of when the device fleet was last updated.
- OutputConfig
-
- Required: Yes
- Type: EdgeOutputConfig structure
The output configuration for storing sampled data.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeDomain
$result = $client->describeDomain
([/* ... */]); $promise = $client->describeDomainAsync
([/* ... */]);
The description of the domain.
Parameter Syntax
$result = $client->describeDomain([ 'DomainId' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DomainId
-
- Required: Yes
- Type: string
The domain ID.
Result Syntax
[ 'AppNetworkAccessType' => 'PublicInternetOnly|VpcOnly', 'AppSecurityGroupManagement' => 'Service|Customer', 'AuthMode' => 'SSO|IAM', 'CreationTime' => <DateTime>, 'DefaultSpaceSettings' => [ 'CustomFileSystemConfigs' => [ [ 'EFSFileSystemConfig' => [ 'FileSystemId' => '<string>', 'FileSystemPath' => '<string>', ], ], // ... ], 'CustomPosixUserConfig' => [ 'Gid' => <integer>, 'Uid' => <integer>, ], 'ExecutionRole' => '<string>', 'JupyterLabAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', ], // ... ], 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', 'ImageName' => '<string>', 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'EmrSettings' => [ 'AssumableRoleArns' => ['<string>', ...], 'ExecutionRoleArns' => ['<string>', ...], ], 'LifecycleConfigArns' => ['<string>', ...], ], 'JupyterServerAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'KernelGatewayAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', 'ImageName' => '<string>', 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'SecurityGroups' => ['<string>', ...], 'SpaceStorageSettings' => [ 'DefaultEbsStorageSettings' => [ 'DefaultEbsVolumeSizeInGb' => <integer>, 'MaximumEbsVolumeSizeInGb' => <integer>, ], ], ], 'DefaultUserSettings' => [ 'CanvasAppSettings' => [ 'DirectDeploySettings' => [ 'Status' => 'ENABLED|DISABLED', ], 'EmrServerlessSettings' => [ 'ExecutionRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'GenerativeAiSettings' => [ 'AmazonBedrockRoleArn' => '<string>', ], 'IdentityProviderOAuthSettings' => [ [ 'DataSourceName' => 'SalesforceGenie|Snowflake', 'SecretArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], // ... ], 'KendraSettings' => [ 'Status' => 'ENABLED|DISABLED', ], 'ModelRegisterSettings' => [ 'CrossAccountModelRegisterRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'TimeSeriesForecastingSettings' => [ 'AmazonForecastRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'WorkspaceSettings' => [ 'S3ArtifactPath' => '<string>', 'S3KmsKeyId' => '<string>', ], ], 'CodeEditorAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', 'ImageName' => '<string>', 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'CustomFileSystemConfigs' => [ [ 'EFSFileSystemConfig' => [ 'FileSystemId' => '<string>', 'FileSystemPath' => '<string>', ], ], // ... ], 'CustomPosixUserConfig' => [ 'Gid' => <integer>, 'Uid' => <integer>, ], 'DefaultLandingUri' => '<string>', 'ExecutionRole' => '<string>', 'JupyterLabAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', ], // ... ], 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', 'ImageName' => '<string>', 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'EmrSettings' => [ 'AssumableRoleArns' => ['<string>', ...], 'ExecutionRoleArns' => ['<string>', ...], ], 'LifecycleConfigArns' => ['<string>', ...], ], 'JupyterServerAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'KernelGatewayAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', 'ImageName' => '<string>', 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'RSessionAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', 'ImageName' => '<string>', 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'RStudioServerProAppSettings' => [ 'AccessStatus' => 'ENABLED|DISABLED', 'UserGroup' => 'R_STUDIO_ADMIN|R_STUDIO_USER', ], 'SecurityGroups' => ['<string>', ...], 'SharingSettings' => [ 'NotebookOutputOption' => 'Allowed|Disabled', 'S3KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'SpaceStorageSettings' => [ 'DefaultEbsStorageSettings' => [ 'DefaultEbsVolumeSizeInGb' => <integer>, 'MaximumEbsVolumeSizeInGb' => <integer>, ], ], 'StudioWebPortal' => 'ENABLED|DISABLED', 'StudioWebPortalSettings' => [ 'HiddenAppTypes' => ['<string>', ...], 'HiddenMlTools' => ['<string>', ...], ], 'TensorBoardAppSettings' => [ 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], ], 'DomainArn' => '<string>', 'DomainId' => '<string>', 'DomainName' => '<string>', 'DomainSettings' => [ 'AmazonQSettings' => [ 'QProfileArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'DockerSettings' => [ 'EnableDockerAccess' => 'ENABLED|DISABLED', 'VpcOnlyTrustedAccounts' => ['<string>', ...], ], 'ExecutionRoleIdentityConfig' => 'USER_PROFILE_NAME|DISABLED', 'RStudioServerProDomainSettings' => [ 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'DomainExecutionRoleArn' => '<string>', 'RStudioConnectUrl' => '<string>', 'RStudioPackageManagerUrl' => '<string>', ], 'SecurityGroupIds' => ['<string>', ...], ], 'FailureReason' => '<string>', 'HomeEfsFileSystemId' => '<string>', 'HomeEfsFileSystemKmsKeyId' => '<string>', 'KmsKeyId' => '<string>', 'LastModifiedTime' => <DateTime>, 'SecurityGroupIdForDomainBoundary' => '<string>', 'SingleSignOnApplicationArn' => '<string>', 'SingleSignOnManagedApplicationInstanceId' => '<string>', 'Status' => 'Deleting|Failed|InService|Pending|Updating|Update_Failed|Delete_Failed', 'SubnetIds' => ['<string>', ...], 'Url' => '<string>', 'VpcId' => '<string>', ]
Result Details
Members
- AppNetworkAccessType
-
- Type: 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 traffic is through the specified VPC and subnets
- AppSecurityGroupManagement
-
- Type: string
The entity that creates and manages the required security groups for inter-app communication in
VPCOnly
mode. Required whenCreateDomain.AppNetworkAccessType
isVPCOnly
andDomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is provided. - AuthMode
-
- Type: string
The domain's authentication mode.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time.
- DefaultSpaceSettings
-
- Type: DefaultSpaceSettings structure
The default settings used to create a space.
- DefaultUserSettings
-
- Type: UserSettings structure
Settings which are applied to UserProfiles in this domain if settings are not explicitly specified in a given UserProfile.
- DomainArn
-
- Type: string
The domain's Amazon Resource Name (ARN).
- DomainId
-
- Type: string
The domain ID.
- DomainName
-
- Type: string
The domain name.
- DomainSettings
-
- Type: DomainSettings structure
A collection of
Domain
settings. - FailureReason
-
- Type: string
The failure reason.
- HomeEfsFileSystemId
-
- Type: string
The ID of the Amazon Elastic File System managed by this Domain.
- HomeEfsFileSystemKmsKeyId
-
- Type: string
Use
KmsKeyId
. - KmsKeyId
-
- Type: string
The Amazon Web Services KMS customer managed key used to encrypt the EFS volume attached to the domain.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last modified time.
- SecurityGroupIdForDomainBoundary
-
- Type: string
The ID of the security group that authorizes traffic between the
RSessionGateway
apps and theRStudioServerPro
app. - SingleSignOnApplicationArn
-
- Type: string
The ARN of the application managed by SageMaker in IAM Identity Center. This value is only returned for domains created after October 1, 2023.
- SingleSignOnManagedApplicationInstanceId
-
- Type: string
The IAM Identity Center managed application instance ID.
- Status
-
- Type: string
The status.
- SubnetIds
-
- Type: Array of strings
The VPC subnets that the domain uses for communication.
- Url
-
- Type: string
The domain's URL.
- VpcId
-
- Type: string
The ID of the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeEdgeDeploymentPlan
$result = $client->describeEdgeDeploymentPlan
([/* ... */]); $promise = $client->describeEdgeDeploymentPlanAsync
([/* ... */]);
Describes an edge deployment plan with deployment status per stage.
Parameter Syntax
$result = $client->describeEdgeDeploymentPlan([ 'EdgeDeploymentPlanName' => '<string>', // REQUIRED 'MaxResults' => <integer>, 'NextToken' => '<string>', ]);
Parameter Details
Members
- EdgeDeploymentPlanName
-
- Required: Yes
- Type: string
The name of the deployment plan to describe.
- MaxResults
-
- Type: int
The maximum number of results to select (50 by default).
- NextToken
-
- Type: string
If the edge deployment plan has enough stages to require tokening, then this is the response from the last list of stages returned.
Result Syntax
[ 'CreationTime' => <DateTime>, 'DeviceFleetName' => '<string>', 'EdgeDeploymentFailed' => <integer>, 'EdgeDeploymentPending' => <integer>, 'EdgeDeploymentPlanArn' => '<string>', 'EdgeDeploymentPlanName' => '<string>', 'EdgeDeploymentSuccess' => <integer>, 'LastModifiedTime' => <DateTime>, 'ModelConfigs' => [ [ 'EdgePackagingJobName' => '<string>', 'ModelHandle' => '<string>', ], // ... ], 'NextToken' => '<string>', 'Stages' => [ [ 'DeploymentConfig' => [ 'FailureHandlingPolicy' => 'ROLLBACK_ON_FAILURE|DO_NOTHING', ], 'DeploymentStatus' => [ 'EdgeDeploymentFailedInStage' => <integer>, 'EdgeDeploymentPendingInStage' => <integer>, 'EdgeDeploymentStageStartTime' => <DateTime>, 'EdgeDeploymentStatusMessage' => '<string>', 'EdgeDeploymentSuccessInStage' => <integer>, 'StageStatus' => 'CREATING|READYTODEPLOY|STARTING|INPROGRESS|DEPLOYED|FAILED|STOPPING|STOPPED', ], 'DeviceSelectionConfig' => [ 'DeviceNameContains' => '<string>', 'DeviceNames' => ['<string>', ...], 'DeviceSubsetType' => 'PERCENTAGE|SELECTION|NAMECONTAINS', 'Percentage' => <integer>, ], 'StageName' => '<string>', ], // ... ], ]
Result Details
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the edge deployment plan was created.
- DeviceFleetName
-
- Required: Yes
- Type: string
The device fleet used for this edge deployment plan.
- EdgeDeploymentFailed
-
- Type: int
The number of edge devices that failed the deployment.
- EdgeDeploymentPending
-
- Type: int
The number of edge devices yet to pick up deployment, or in progress.
- EdgeDeploymentPlanArn
-
- Required: Yes
- Type: string
The ARN of edge deployment plan.
- EdgeDeploymentPlanName
-
- Required: Yes
- Type: string
The name of the edge deployment plan.
- EdgeDeploymentSuccess
-
- Type: int
The number of edge devices with the successful deployment.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the edge deployment plan was last updated.
- ModelConfigs
-
- Required: Yes
- Type: Array of EdgeDeploymentModelConfig structures
List of models associated with the edge deployment plan.
- NextToken
-
- Type: string
Token to use when calling the next set of stages in the edge deployment plan.
- Stages
-
- Required: Yes
- Type: Array of DeploymentStageStatusSummary structures
List of stages in the edge deployment plan.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeEdgePackagingJob
$result = $client->describeEdgePackagingJob
([/* ... */]); $promise = $client->describeEdgePackagingJobAsync
([/* ... */]);
A description of edge packaging jobs.
Parameter Syntax
$result = $client->describeEdgePackagingJob([ 'EdgePackagingJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- EdgePackagingJobName
-
- Required: Yes
- Type: string
The name of the edge packaging job.
Result Syntax
[ 'CompilationJobName' => '<string>', 'CreationTime' => <DateTime>, 'EdgePackagingJobArn' => '<string>', 'EdgePackagingJobName' => '<string>', 'EdgePackagingJobStatus' => 'STARTING|INPROGRESS|COMPLETED|FAILED|STOPPING|STOPPED', 'EdgePackagingJobStatusMessage' => '<string>', 'LastModifiedTime' => <DateTime>, 'ModelArtifact' => '<string>', 'ModelName' => '<string>', 'ModelSignature' => '<string>', 'ModelVersion' => '<string>', 'OutputConfig' => [ 'KmsKeyId' => '<string>', 'PresetDeploymentConfig' => '<string>', 'PresetDeploymentType' => 'GreengrassV2Component', 'S3OutputLocation' => '<string>', ], 'PresetDeploymentOutput' => [ 'Artifact' => '<string>', 'Status' => 'COMPLETED|FAILED', 'StatusMessage' => '<string>', 'Type' => 'GreengrassV2Component', ], 'ResourceKey' => '<string>', 'RoleArn' => '<string>', ]
Result Details
Members
- CompilationJobName
-
- Type: string
The name of the SageMaker Neo compilation job that is used to locate model artifacts that are being packaged.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of when the packaging job was created.
- EdgePackagingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the edge packaging job.
- EdgePackagingJobName
-
- Required: Yes
- Type: string
The name of the edge packaging job.
- EdgePackagingJobStatus
-
- Required: Yes
- Type: string
The current status of the packaging job.
- EdgePackagingJobStatusMessage
-
- Type: string
Returns a message describing the job status and error messages.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of when the job was last updated.
- ModelArtifact
-
- Type: string
The Amazon Simple Storage (S3) URI where model artifacts ares stored.
- ModelName
-
- Type: string
The name of the model.
- ModelSignature
-
- Type: string
The signature document of files in the model artifact.
- ModelVersion
-
- Type: string
The version of the model.
- OutputConfig
-
- Type: EdgeOutputConfig structure
The output configuration for the edge packaging job.
- PresetDeploymentOutput
-
- Type: EdgePresetDeploymentOutput structure
The output of a SageMaker Edge Manager deployable resource.
- ResourceKey
-
- Type: string
The Amazon Web Services KMS key to use when encrypting the EBS volume the job run on.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact Neo.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeEndpoint
$result = $client->describeEndpoint
([/* ... */]); $promise = $client->describeEndpointAsync
([/* ... */]);
Returns the description of an endpoint.
Parameter Syntax
$result = $client->describeEndpoint([ 'EndpointName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- EndpointName
-
- Required: Yes
- Type: string
The name of the endpoint.
Result Syntax
[ 'AsyncInferenceConfig' => [ 'ClientConfig' => [ 'MaxConcurrentInvocationsPerInstance' => <integer>, ], 'OutputConfig' => [ 'KmsKeyId' => '<string>', 'NotificationConfig' => [ 'ErrorTopic' => '<string>', 'IncludeInferenceResponseIn' => ['<string>', ...], 'SuccessTopic' => '<string>', ], 'S3FailurePath' => '<string>', 'S3OutputPath' => '<string>', ], ], 'CreationTime' => <DateTime>, 'DataCaptureConfig' => [ 'CaptureStatus' => 'Started|Stopped', 'CurrentSamplingPercentage' => <integer>, 'DestinationS3Uri' => '<string>', 'EnableCapture' => true || false, 'KmsKeyId' => '<string>', ], 'EndpointArn' => '<string>', 'EndpointConfigName' => '<string>', 'EndpointName' => '<string>', 'EndpointStatus' => 'OutOfService|Creating|Updating|SystemUpdating|RollingBack|InService|Deleting|Failed|UpdateRollbackFailed', 'ExplainerConfig' => [ 'ClarifyExplainerConfig' => [ 'EnableExplanations' => '<string>', 'InferenceConfig' => [ 'ContentTemplate' => '<string>', 'FeatureHeaders' => ['<string>', ...], 'FeatureTypes' => ['<string>', ...], 'FeaturesAttribute' => '<string>', 'LabelAttribute' => '<string>', 'LabelHeaders' => ['<string>', ...], 'LabelIndex' => <integer>, 'MaxPayloadInMB' => <integer>, 'MaxRecordCount' => <integer>, 'ProbabilityAttribute' => '<string>', 'ProbabilityIndex' => <integer>, ], 'ShapConfig' => [ 'NumberOfSamples' => <integer>, 'Seed' => <integer>, 'ShapBaselineConfig' => [ 'MimeType' => '<string>', 'ShapBaseline' => '<string>', 'ShapBaselineUri' => '<string>', ], 'TextConfig' => [ 'Granularity' => 'token|sentence|paragraph', 'Language' => 'af|sq|ar|hy|eu|bn|bg|ca|zh|hr|cs|da|nl|en|et|fi|fr|de|el|gu|he|hi|hu|is|id|ga|it|kn|ky|lv|lt|lb|mk|ml|mr|ne|nb|fa|pl|pt|ro|ru|sa|sr|tn|si|sk|sl|es|sv|tl|ta|tt|te|tr|uk|ur|yo|lij|xx', ], 'UseLogit' => true || false, ], ], ], 'FailureReason' => '<string>', 'LastDeploymentConfig' => [ 'AutoRollbackConfiguration' => [ 'Alarms' => [ [ 'AlarmName' => '<string>', ], // ... ], ], 'BlueGreenUpdatePolicy' => [ 'MaximumExecutionTimeoutInSeconds' => <integer>, 'TerminationWaitInSeconds' => <integer>, 'TrafficRoutingConfiguration' => [ 'CanarySize' => [ 'Type' => 'INSTANCE_COUNT|CAPACITY_PERCENT', 'Value' => <integer>, ], 'LinearStepSize' => [ 'Type' => 'INSTANCE_COUNT|CAPACITY_PERCENT', 'Value' => <integer>, ], 'Type' => 'ALL_AT_ONCE|CANARY|LINEAR', 'WaitIntervalInSeconds' => <integer>, ], ], 'RollingUpdatePolicy' => [ 'MaximumBatchSize' => [ 'Type' => 'INSTANCE_COUNT|CAPACITY_PERCENT', 'Value' => <integer>, ], 'MaximumExecutionTimeoutInSeconds' => <integer>, 'RollbackMaximumBatchSize' => [ 'Type' => 'INSTANCE_COUNT|CAPACITY_PERCENT', 'Value' => <integer>, ], 'WaitIntervalInSeconds' => <integer>, ], ], 'LastModifiedTime' => <DateTime>, 'PendingDeploymentSummary' => [ 'EndpointConfigName' => '<string>', 'ProductionVariants' => [ [ 'AcceleratorType' => 'ml.eia1.medium|ml.eia1.large|ml.eia1.xlarge|ml.eia2.medium|ml.eia2.large|ml.eia2.xlarge', 'CurrentInstanceCount' => <integer>, 'CurrentServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'CurrentWeight' => <float>, 'DeployedImages' => [ [ 'ResolutionTime' => <DateTime>, 'ResolvedImage' => '<string>', 'SpecifiedImage' => '<string>', ], // ... ], 'DesiredInstanceCount' => <integer>, 'DesiredServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'DesiredWeight' => <float>, 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.12xlarge|ml.m5d.24xlarge|ml.c4.large|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.large|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.12xlarge|ml.r5.24xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.12xlarge|ml.r5d.24xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.dl1.24xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.p4d.24xlarge|ml.c7g.large|ml.c7g.xlarge|ml.c7g.2xlarge|ml.c7g.4xlarge|ml.c7g.8xlarge|ml.c7g.12xlarge|ml.c7g.16xlarge|ml.m6g.large|ml.m6g.xlarge|ml.m6g.2xlarge|ml.m6g.4xlarge|ml.m6g.8xlarge|ml.m6g.12xlarge|ml.m6g.16xlarge|ml.m6gd.large|ml.m6gd.xlarge|ml.m6gd.2xlarge|ml.m6gd.4xlarge|ml.m6gd.8xlarge|ml.m6gd.12xlarge|ml.m6gd.16xlarge|ml.c6g.large|ml.c6g.xlarge|ml.c6g.2xlarge|ml.c6g.4xlarge|ml.c6g.8xlarge|ml.c6g.12xlarge|ml.c6g.16xlarge|ml.c6gd.large|ml.c6gd.xlarge|ml.c6gd.2xlarge|ml.c6gd.4xlarge|ml.c6gd.8xlarge|ml.c6gd.12xlarge|ml.c6gd.16xlarge|ml.c6gn.large|ml.c6gn.xlarge|ml.c6gn.2xlarge|ml.c6gn.4xlarge|ml.c6gn.8xlarge|ml.c6gn.12xlarge|ml.c6gn.16xlarge|ml.r6g.large|ml.r6g.xlarge|ml.r6g.2xlarge|ml.r6g.4xlarge|ml.r6g.8xlarge|ml.r6g.12xlarge|ml.r6g.16xlarge|ml.r6gd.large|ml.r6gd.xlarge|ml.r6gd.2xlarge|ml.r6gd.4xlarge|ml.r6gd.8xlarge|ml.r6gd.12xlarge|ml.r6gd.16xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.p5.48xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge', 'ManagedInstanceScaling' => [ 'MaxInstanceCount' => <integer>, 'MinInstanceCount' => <integer>, 'Status' => 'ENABLED|DISABLED', ], 'RoutingConfig' => [ 'RoutingStrategy' => 'LEAST_OUTSTANDING_REQUESTS|RANDOM', ], 'VariantName' => '<string>', 'VariantStatus' => [ [ 'StartTime' => <DateTime>, 'Status' => 'Creating|Updating|Deleting|ActivatingTraffic|Baking', 'StatusMessage' => '<string>', ], // ... ], ], // ... ], 'ShadowProductionVariants' => [ [ 'AcceleratorType' => 'ml.eia1.medium|ml.eia1.large|ml.eia1.xlarge|ml.eia2.medium|ml.eia2.large|ml.eia2.xlarge', 'CurrentInstanceCount' => <integer>, 'CurrentServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'CurrentWeight' => <float>, 'DeployedImages' => [ [ 'ResolutionTime' => <DateTime>, 'ResolvedImage' => '<string>', 'SpecifiedImage' => '<string>', ], // ... ], 'DesiredInstanceCount' => <integer>, 'DesiredServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'DesiredWeight' => <float>, 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.12xlarge|ml.m5d.24xlarge|ml.c4.large|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.large|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.12xlarge|ml.r5.24xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.12xlarge|ml.r5d.24xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.dl1.24xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.p4d.24xlarge|ml.c7g.large|ml.c7g.xlarge|ml.c7g.2xlarge|ml.c7g.4xlarge|ml.c7g.8xlarge|ml.c7g.12xlarge|ml.c7g.16xlarge|ml.m6g.large|ml.m6g.xlarge|ml.m6g.2xlarge|ml.m6g.4xlarge|ml.m6g.8xlarge|ml.m6g.12xlarge|ml.m6g.16xlarge|ml.m6gd.large|ml.m6gd.xlarge|ml.m6gd.2xlarge|ml.m6gd.4xlarge|ml.m6gd.8xlarge|ml.m6gd.12xlarge|ml.m6gd.16xlarge|ml.c6g.large|ml.c6g.xlarge|ml.c6g.2xlarge|ml.c6g.4xlarge|ml.c6g.8xlarge|ml.c6g.12xlarge|ml.c6g.16xlarge|ml.c6gd.large|ml.c6gd.xlarge|ml.c6gd.2xlarge|ml.c6gd.4xlarge|ml.c6gd.8xlarge|ml.c6gd.12xlarge|ml.c6gd.16xlarge|ml.c6gn.large|ml.c6gn.xlarge|ml.c6gn.2xlarge|ml.c6gn.4xlarge|ml.c6gn.8xlarge|ml.c6gn.12xlarge|ml.c6gn.16xlarge|ml.r6g.large|ml.r6g.xlarge|ml.r6g.2xlarge|ml.r6g.4xlarge|ml.r6g.8xlarge|ml.r6g.12xlarge|ml.r6g.16xlarge|ml.r6gd.large|ml.r6gd.xlarge|ml.r6gd.2xlarge|ml.r6gd.4xlarge|ml.r6gd.8xlarge|ml.r6gd.12xlarge|ml.r6gd.16xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.p5.48xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge', 'ManagedInstanceScaling' => [ 'MaxInstanceCount' => <integer>, 'MinInstanceCount' => <integer>, 'Status' => 'ENABLED|DISABLED', ], 'RoutingConfig' => [ 'RoutingStrategy' => 'LEAST_OUTSTANDING_REQUESTS|RANDOM', ], 'VariantName' => '<string>', 'VariantStatus' => [ [ 'StartTime' => <DateTime>, 'Status' => 'Creating|Updating|Deleting|ActivatingTraffic|Baking', 'StatusMessage' => '<string>', ], // ... ], ], // ... ], 'StartTime' => <DateTime>, ], 'ProductionVariants' => [ [ 'CurrentInstanceCount' => <integer>, 'CurrentServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'CurrentWeight' => <float>, 'DeployedImages' => [ [ 'ResolutionTime' => <DateTime>, 'ResolvedImage' => '<string>', 'SpecifiedImage' => '<string>', ], // ... ], 'DesiredInstanceCount' => <integer>, 'DesiredServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'DesiredWeight' => <float>, 'ManagedInstanceScaling' => [ 'MaxInstanceCount' => <integer>, 'MinInstanceCount' => <integer>, 'Status' => 'ENABLED|DISABLED', ], 'RoutingConfig' => [ 'RoutingStrategy' => 'LEAST_OUTSTANDING_REQUESTS|RANDOM', ], 'VariantName' => '<string>', 'VariantStatus' => [ [ 'StartTime' => <DateTime>, 'Status' => 'Creating|Updating|Deleting|ActivatingTraffic|Baking', 'StatusMessage' => '<string>', ], // ... ], ], // ... ], 'ShadowProductionVariants' => [ [ 'CurrentInstanceCount' => <integer>, 'CurrentServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'CurrentWeight' => <float>, 'DeployedImages' => [ [ 'ResolutionTime' => <DateTime>, 'ResolvedImage' => '<string>', 'SpecifiedImage' => '<string>', ], // ... ], 'DesiredInstanceCount' => <integer>, 'DesiredServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'DesiredWeight' => <float>, 'ManagedInstanceScaling' => [ 'MaxInstanceCount' => <integer>, 'MinInstanceCount' => <integer>, 'Status' => 'ENABLED|DISABLED', ], 'RoutingConfig' => [ 'RoutingStrategy' => 'LEAST_OUTSTANDING_REQUESTS|RANDOM', ], 'VariantName' => '<string>', 'VariantStatus' => [ [ 'StartTime' => <DateTime>, 'Status' => 'Creating|Updating|Deleting|ActivatingTraffic|Baking', 'StatusMessage' => '<string>', ], // ... ], ], // ... ], ]
Result Details
Members
- AsyncInferenceConfig
-
- Type: AsyncInferenceConfig structure
Returns the description of an endpoint configuration created using the
CreateEndpointConfig
API. - CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the endpoint was created.
- DataCaptureConfig
-
- Type: DataCaptureConfigSummary structure
The currently active data capture configuration used by your Endpoint.
- EndpointArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the endpoint.
- EndpointConfigName
-
- Type: string
The name of the endpoint configuration associated with this endpoint.
- EndpointName
-
- Required: Yes
- Type: string
Name of the endpoint.
- EndpointStatus
-
- Required: Yes
- Type: string
The status of the endpoint.
-
OutOfService
: Endpoint is not available to take incoming requests. -
Creating
: CreateEndpoint is executing. -
Updating
: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing. -
SystemUpdating
: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count. -
RollingBack
: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to anInService
status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly. -
InService
: Endpoint is available to process incoming requests. -
Deleting
: DeleteEndpoint is executing. -
Failed
: Endpoint could not be created, updated, or re-scaled. Use theFailureReason
value returned by DescribeEndpoint for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint. -
UpdateRollbackFailed
: Both the rolling deployment and auto-rollback failed. Your endpoint is in service with a mix of the old and new endpoint configurations. For information about how to remedy this issue and restore the endpoint's status toInService
, see Rolling Deployments.
- ExplainerConfig
-
- Type: ExplainerConfig structure
The configuration parameters for an explainer.
- FailureReason
-
- Type: string
If the status of the endpoint is
Failed
, the reason why it failed. - LastDeploymentConfig
-
- Type: DeploymentConfig structure
The most recent deployment configuration for the endpoint.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the endpoint was last modified.
- PendingDeploymentSummary
-
- Type: PendingDeploymentSummary structure
Returns the summary of an in-progress deployment. This field is only returned when the endpoint is creating or updating with a new endpoint configuration.
- ProductionVariants
-
- Type: Array of ProductionVariantSummary structures
An array of ProductionVariantSummary objects, one for each model hosted behind this endpoint.
- ShadowProductionVariants
-
- Type: Array of ProductionVariantSummary structures
An array of ProductionVariantSummary objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on
ProductionVariants
.
Errors
There are no errors described for this operation.
DescribeEndpointConfig
$result = $client->describeEndpointConfig
([/* ... */]); $promise = $client->describeEndpointConfigAsync
([/* ... */]);
Returns the description of an endpoint configuration created using the CreateEndpointConfig
API.
Parameter Syntax
$result = $client->describeEndpointConfig([ 'EndpointConfigName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- EndpointConfigName
-
- Required: Yes
- Type: string
The name of the endpoint configuration.
Result Syntax
[ 'AsyncInferenceConfig' => [ 'ClientConfig' => [ 'MaxConcurrentInvocationsPerInstance' => <integer>, ], 'OutputConfig' => [ 'KmsKeyId' => '<string>', 'NotificationConfig' => [ 'ErrorTopic' => '<string>', 'IncludeInferenceResponseIn' => ['<string>', ...], 'SuccessTopic' => '<string>', ], 'S3FailurePath' => '<string>', 'S3OutputPath' => '<string>', ], ], 'CreationTime' => <DateTime>, 'DataCaptureConfig' => [ 'CaptureContentTypeHeader' => [ 'CsvContentTypes' => ['<string>', ...], 'JsonContentTypes' => ['<string>', ...], ], 'CaptureOptions' => [ [ 'CaptureMode' => 'Input|Output|InputAndOutput', ], // ... ], 'DestinationS3Uri' => '<string>', 'EnableCapture' => true || false, 'InitialSamplingPercentage' => <integer>, 'KmsKeyId' => '<string>', ], 'EnableNetworkIsolation' => true || false, 'EndpointConfigArn' => '<string>', 'EndpointConfigName' => '<string>', 'ExecutionRoleArn' => '<string>', 'ExplainerConfig' => [ 'ClarifyExplainerConfig' => [ 'EnableExplanations' => '<string>', 'InferenceConfig' => [ 'ContentTemplate' => '<string>', 'FeatureHeaders' => ['<string>', ...], 'FeatureTypes' => ['<string>', ...], 'FeaturesAttribute' => '<string>', 'LabelAttribute' => '<string>', 'LabelHeaders' => ['<string>', ...], 'LabelIndex' => <integer>, 'MaxPayloadInMB' => <integer>, 'MaxRecordCount' => <integer>, 'ProbabilityAttribute' => '<string>', 'ProbabilityIndex' => <integer>, ], 'ShapConfig' => [ 'NumberOfSamples' => <integer>, 'Seed' => <integer>, 'ShapBaselineConfig' => [ 'MimeType' => '<string>', 'ShapBaseline' => '<string>', 'ShapBaselineUri' => '<string>', ], 'TextConfig' => [ 'Granularity' => 'token|sentence|paragraph', 'Language' => 'af|sq|ar|hy|eu|bn|bg|ca|zh|hr|cs|da|nl|en|et|fi|fr|de|el|gu|he|hi|hu|is|id|ga|it|kn|ky|lv|lt|lb|mk|ml|mr|ne|nb|fa|pl|pt|ro|ru|sa|sr|tn|si|sk|sl|es|sv|tl|ta|tt|te|tr|uk|ur|yo|lij|xx', ], 'UseLogit' => true || false, ], ], ], 'KmsKeyId' => '<string>', 'ProductionVariants' => [ [ 'AcceleratorType' => 'ml.eia1.medium|ml.eia1.large|ml.eia1.xlarge|ml.eia2.medium|ml.eia2.large|ml.eia2.xlarge', 'ContainerStartupHealthCheckTimeoutInSeconds' => <integer>, 'CoreDumpConfig' => [ 'DestinationS3Uri' => '<string>', 'KmsKeyId' => '<string>', ], 'EnableSSMAccess' => true || false, 'InferenceAmiVersion' => 'al2-ami-sagemaker-inference-gpu-2', 'InitialInstanceCount' => <integer>, 'InitialVariantWeight' => <float>, 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.12xlarge|ml.m5d.24xlarge|ml.c4.large|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.large|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.12xlarge|ml.r5.24xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.12xlarge|ml.r5d.24xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.dl1.24xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.p4d.24xlarge|ml.c7g.large|ml.c7g.xlarge|ml.c7g.2xlarge|ml.c7g.4xlarge|ml.c7g.8xlarge|ml.c7g.12xlarge|ml.c7g.16xlarge|ml.m6g.large|ml.m6g.xlarge|ml.m6g.2xlarge|ml.m6g.4xlarge|ml.m6g.8xlarge|ml.m6g.12xlarge|ml.m6g.16xlarge|ml.m6gd.large|ml.m6gd.xlarge|ml.m6gd.2xlarge|ml.m6gd.4xlarge|ml.m6gd.8xlarge|ml.m6gd.12xlarge|ml.m6gd.16xlarge|ml.c6g.large|ml.c6g.xlarge|ml.c6g.2xlarge|ml.c6g.4xlarge|ml.c6g.8xlarge|ml.c6g.12xlarge|ml.c6g.16xlarge|ml.c6gd.large|ml.c6gd.xlarge|ml.c6gd.2xlarge|ml.c6gd.4xlarge|ml.c6gd.8xlarge|ml.c6gd.12xlarge|ml.c6gd.16xlarge|ml.c6gn.large|ml.c6gn.xlarge|ml.c6gn.2xlarge|ml.c6gn.4xlarge|ml.c6gn.8xlarge|ml.c6gn.12xlarge|ml.c6gn.16xlarge|ml.r6g.large|ml.r6g.xlarge|ml.r6g.2xlarge|ml.r6g.4xlarge|ml.r6g.8xlarge|ml.r6g.12xlarge|ml.r6g.16xlarge|ml.r6gd.large|ml.r6gd.xlarge|ml.r6gd.2xlarge|ml.r6gd.4xlarge|ml.r6gd.8xlarge|ml.r6gd.12xlarge|ml.r6gd.16xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.p5.48xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge', 'ManagedInstanceScaling' => [ 'MaxInstanceCount' => <integer>, 'MinInstanceCount' => <integer>, 'Status' => 'ENABLED|DISABLED', ], 'ModelDataDownloadTimeoutInSeconds' => <integer>, 'ModelName' => '<string>', 'RoutingConfig' => [ 'RoutingStrategy' => 'LEAST_OUTSTANDING_REQUESTS|RANDOM', ], 'ServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'VariantName' => '<string>', 'VolumeSizeInGB' => <integer>, ], // ... ], 'ShadowProductionVariants' => [ [ 'AcceleratorType' => 'ml.eia1.medium|ml.eia1.large|ml.eia1.xlarge|ml.eia2.medium|ml.eia2.large|ml.eia2.xlarge', 'ContainerStartupHealthCheckTimeoutInSeconds' => <integer>, 'CoreDumpConfig' => [ 'DestinationS3Uri' => '<string>', 'KmsKeyId' => '<string>', ], 'EnableSSMAccess' => true || false, 'InferenceAmiVersion' => 'al2-ami-sagemaker-inference-gpu-2', 'InitialInstanceCount' => <integer>, 'InitialVariantWeight' => <float>, 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.12xlarge|ml.m5d.24xlarge|ml.c4.large|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.large|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.12xlarge|ml.r5.24xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.12xlarge|ml.r5d.24xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.dl1.24xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.p4d.24xlarge|ml.c7g.large|ml.c7g.xlarge|ml.c7g.2xlarge|ml.c7g.4xlarge|ml.c7g.8xlarge|ml.c7g.12xlarge|ml.c7g.16xlarge|ml.m6g.large|ml.m6g.xlarge|ml.m6g.2xlarge|ml.m6g.4xlarge|ml.m6g.8xlarge|ml.m6g.12xlarge|ml.m6g.16xlarge|ml.m6gd.large|ml.m6gd.xlarge|ml.m6gd.2xlarge|ml.m6gd.4xlarge|ml.m6gd.8xlarge|ml.m6gd.12xlarge|ml.m6gd.16xlarge|ml.c6g.large|ml.c6g.xlarge|ml.c6g.2xlarge|ml.c6g.4xlarge|ml.c6g.8xlarge|ml.c6g.12xlarge|ml.c6g.16xlarge|ml.c6gd.large|ml.c6gd.xlarge|ml.c6gd.2xlarge|ml.c6gd.4xlarge|ml.c6gd.8xlarge|ml.c6gd.12xlarge|ml.c6gd.16xlarge|ml.c6gn.large|ml.c6gn.xlarge|ml.c6gn.2xlarge|ml.c6gn.4xlarge|ml.c6gn.8xlarge|ml.c6gn.12xlarge|ml.c6gn.16xlarge|ml.r6g.large|ml.r6g.xlarge|ml.r6g.2xlarge|ml.r6g.4xlarge|ml.r6g.8xlarge|ml.r6g.12xlarge|ml.r6g.16xlarge|ml.r6gd.large|ml.r6gd.xlarge|ml.r6gd.2xlarge|ml.r6gd.4xlarge|ml.r6gd.8xlarge|ml.r6gd.12xlarge|ml.r6gd.16xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.p5.48xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge', 'ManagedInstanceScaling' => [ 'MaxInstanceCount' => <integer>, 'MinInstanceCount' => <integer>, 'Status' => 'ENABLED|DISABLED', ], 'ModelDataDownloadTimeoutInSeconds' => <integer>, 'ModelName' => '<string>', 'RoutingConfig' => [ 'RoutingStrategy' => 'LEAST_OUTSTANDING_REQUESTS|RANDOM', ], 'ServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'VariantName' => '<string>', 'VolumeSizeInGB' => <integer>, ], // ... ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ]
Result Details
Members
- AsyncInferenceConfig
-
- Type: AsyncInferenceConfig structure
Returns the description of an endpoint configuration created using the
CreateEndpointConfig
API. - CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the endpoint configuration was created.
- DataCaptureConfig
-
- Type: DataCaptureConfig structure
Configuration to control how SageMaker captures inference data.
- EnableNetworkIsolation
-
- Type: boolean
Indicates whether all model containers deployed to the endpoint are isolated. If they are, no inbound or outbound network calls can be made to or from the model containers.
- EndpointConfigArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the endpoint configuration.
- EndpointConfigName
-
- Required: Yes
- Type: string
Name of the SageMaker endpoint configuration.
- ExecutionRoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM role that you assigned to the endpoint configuration.
- ExplainerConfig
-
- Type: ExplainerConfig structure
The configuration parameters for an explainer.
- KmsKeyId
-
- Type: string
Amazon Web Services KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
- ProductionVariants
-
- Required: Yes
- Type: Array of ProductionVariant structures
An array of
ProductionVariant
objects, one for each model that you want to host at this endpoint. - ShadowProductionVariants
-
- Type: Array of ProductionVariant structures
An array of
ProductionVariant
objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified onProductionVariants
. - VpcConfig
-
- Type: VpcConfig structure
Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
Errors
There are no errors described for this operation.
DescribeExperiment
$result = $client->describeExperiment
([/* ... */]); $promise = $client->describeExperimentAsync
([/* ... */]);
Provides a list of an experiment's properties.
Parameter Syntax
$result = $client->describeExperiment([ 'ExperimentName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ExperimentName
-
- Required: Yes
- Type: string
The name of the experiment to describe.
Result Syntax
[ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'Description' => '<string>', 'DisplayName' => '<string>', 'ExperimentArn' => '<string>', 'ExperimentName' => '<string>', 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'Source' => [ 'SourceArn' => '<string>', 'SourceType' => '<string>', ], ]
Result Details
Members
- CreatedBy
-
- Type: UserContext structure
Who created the experiment.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the experiment was created.
- Description
-
- Type: string
The description of the experiment.
- DisplayName
-
- Type: string
The name of the experiment as displayed. If
DisplayName
isn't specified,ExperimentName
is displayed. - ExperimentArn
-
- Type: string
The Amazon Resource Name (ARN) of the experiment.
- ExperimentName
-
- Type: string
The name of the experiment.
- LastModifiedBy
-
- Type: UserContext structure
Who last modified the experiment.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the experiment was last modified.
- Source
-
- Type: ExperimentSource structure
The Amazon Resource Name (ARN) of the source and, optionally, the type.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeFeatureGroup
$result = $client->describeFeatureGroup
([/* ... */]); $promise = $client->describeFeatureGroupAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->describeFeatureGroup([ 'FeatureGroupName' => '<string>', // REQUIRED 'NextToken' => '<string>', ]);
Parameter Details
Members
- FeatureGroupName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the
FeatureGroup
you want described. - NextToken
-
- Type: string
A token to resume pagination of the list of
Features
(FeatureDefinitions
). 2,500Features
are returned by default.
Result Syntax
[ 'CreationTime' => <DateTime>, 'Description' => '<string>', 'EventTimeFeatureName' => '<string>', 'FailureReason' => '<string>', 'FeatureDefinitions' => [ [ 'CollectionConfig' => [ 'VectorConfig' => [ 'Dimension' => <integer>, ], ], 'CollectionType' => 'List|Set|Vector', 'FeatureName' => '<string>', 'FeatureType' => 'Integral|Fractional|String', ], // ... ], 'FeatureGroupArn' => '<string>', 'FeatureGroupName' => '<string>', 'FeatureGroupStatus' => 'Creating|Created|CreateFailed|Deleting|DeleteFailed', 'LastModifiedTime' => <DateTime>, 'LastUpdateStatus' => [ 'FailureReason' => '<string>', 'Status' => 'Successful|Failed|InProgress', ], 'NextToken' => '<string>', 'OfflineStoreConfig' => [ 'DataCatalogConfig' => [ 'Catalog' => '<string>', 'Database' => '<string>', 'TableName' => '<string>', ], 'DisableGlueTableCreation' => true || false, 'S3StorageConfig' => [ 'KmsKeyId' => '<string>', 'ResolvedOutputS3Uri' => '<string>', 'S3Uri' => '<string>', ], 'TableFormat' => 'Default|Glue|Iceberg', ], 'OfflineStoreStatus' => [ 'BlockedReason' => '<string>', 'Status' => 'Active|Blocked|Disabled', ], 'OnlineStoreConfig' => [ 'EnableOnlineStore' => true || false, 'SecurityConfig' => [ 'KmsKeyId' => '<string>', ], 'StorageType' => 'Standard|InMemory', 'TtlDuration' => [ 'Unit' => 'Seconds|Minutes|Hours|Days|Weeks', 'Value' => <integer>, ], ], 'OnlineStoreTotalSizeBytes' => <integer>, 'RecordIdentifierFeatureName' => '<string>', 'RoleArn' => '<string>', 'ThroughputConfig' => [ 'ProvisionedReadCapacityUnits' => <integer>, 'ProvisionedWriteCapacityUnits' => <integer>, 'ThroughputMode' => 'OnDemand|Provisioned', ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp indicating when SageMaker created the
FeatureGroup
. - Description
-
- Type: string
A free form description of the feature group.
- EventTimeFeatureName
-
- Required: Yes
- Type: string
The name of the feature that stores the
EventTime
of a Record in aFeatureGroup
.An
EventTime
is a point in time when a new event occurs that corresponds to the creation or update of aRecord
in aFeatureGroup
. AllRecords
in theFeatureGroup
have a correspondingEventTime
. - FailureReason
-
- Type: string
The reason that the
FeatureGroup
failed to be replicated in theOfflineStore
. This is failure can occur because:-
The
FeatureGroup
could not be created in theOfflineStore
. -
The
FeatureGroup
could not be deleted from theOfflineStore
.
- FeatureDefinitions
-
- Required: Yes
- Type: Array of FeatureDefinition structures
A list of the
Features
in theFeatureGroup
. Each feature is defined by aFeatureName
andFeatureType
. - FeatureGroupArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the
FeatureGroup
. - FeatureGroupName
-
- Required: Yes
- Type: string
he name of the
FeatureGroup
. - FeatureGroupStatus
-
- Type: string
The status of the feature group.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp indicating when the feature group was last updated.
- LastUpdateStatus
-
- Type: LastUpdateStatus structure
A value indicating whether the update made to the feature group was successful.
- NextToken
-
- Required: Yes
- Type: string
A token to resume pagination of the list of
Features
(FeatureDefinitions
). - OfflineStoreConfig
-
- Type: OfflineStoreConfig structure
The configuration of the offline store. It includes the following configurations:
-
Amazon S3 location of the offline store.
-
Configuration of the Glue data catalog.
-
Table format of the offline store.
-
Option to disable the automatic creation of a Glue table for the offline store.
-
Encryption configuration.
- OfflineStoreStatus
-
- Type: OfflineStoreStatus structure
The status of the
OfflineStore
. Notifies you if replicating data into theOfflineStore
has failed. Returns either:Active
orBlocked
- OnlineStoreConfig
-
- Type: OnlineStoreConfig structure
The configuration for the
OnlineStore
. - OnlineStoreTotalSizeBytes
-
- Type: long (int|float)
The size of the
OnlineStore
in bytes. - RecordIdentifierFeatureName
-
- Required: Yes
- Type: string
The name of the
Feature
used forRecordIdentifier
, whose value uniquely identifies a record stored in the feature store. - RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.
- ThroughputConfig
-
- Type: ThroughputConfigDescription structure
Active throughput configuration of the feature group. There are two modes:
ON_DEMAND
andPROVISIONED
. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.Note:
PROVISIONED
throughput mode is supported only for feature groups that are offline-only, or use theStandard
tier online store.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeFeatureMetadata
$result = $client->describeFeatureMetadata
([/* ... */]); $promise = $client->describeFeatureMetadataAsync
([/* ... */]);
Shows the metadata for a feature within a feature group.
Parameter Syntax
$result = $client->describeFeatureMetadata([ 'FeatureGroupName' => '<string>', // REQUIRED 'FeatureName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- FeatureGroupName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the feature group containing the feature.
- FeatureName
-
- Required: Yes
- Type: string
The name of the feature.
Result Syntax
[ 'CreationTime' => <DateTime>, 'Description' => '<string>', 'FeatureGroupArn' => '<string>', 'FeatureGroupName' => '<string>', 'FeatureName' => '<string>', 'FeatureType' => 'Integral|Fractional|String', 'LastModifiedTime' => <DateTime>, 'Parameters' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp indicating when the feature was created.
- Description
-
- Type: string
The description you added to describe the feature.
- FeatureGroupArn
-
- Required: Yes
- Type: string
The Amazon Resource Number (ARN) of the feature group that contains the feature.
- FeatureGroupName
-
- Required: Yes
- Type: string
The name of the feature group that you've specified.
- FeatureName
-
- Required: Yes
- Type: string
The name of the feature that you've specified.
- FeatureType
-
- Required: Yes
- Type: string
The data type of the feature.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp indicating when the metadata for the feature group was modified. For example, if you add a parameter describing the feature, the timestamp changes to reflect the last time you
- Parameters
-
- Type: Array of FeatureParameter structures
The key-value pairs that you added to describe the feature.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeFlowDefinition
$result = $client->describeFlowDefinition
([/* ... */]); $promise = $client->describeFlowDefinitionAsync
([/* ... */]);
Returns information about the specified flow definition.
Parameter Syntax
$result = $client->describeFlowDefinition([ 'FlowDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- FlowDefinitionName
-
- Required: Yes
- Type: string
The name of the flow definition.
Result Syntax
[ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'FlowDefinitionArn' => '<string>', 'FlowDefinitionName' => '<string>', 'FlowDefinitionStatus' => 'Initializing|Active|Failed|Deleting', 'HumanLoopActivationConfig' => [ 'HumanLoopActivationConditionsConfig' => [ 'HumanLoopActivationConditions' => '<string>', ], ], 'HumanLoopConfig' => [ 'HumanTaskUiArn' => '<string>', 'PublicWorkforceTaskPrice' => [ 'AmountInUsd' => [ 'Cents' => <integer>, 'Dollars' => <integer>, 'TenthFractionsOfACent' => <integer>, ], ], 'TaskAvailabilityLifetimeInSeconds' => <integer>, 'TaskCount' => <integer>, 'TaskDescription' => '<string>', 'TaskKeywords' => ['<string>', ...], 'TaskTimeLimitInSeconds' => <integer>, 'TaskTitle' => '<string>', 'WorkteamArn' => '<string>', ], 'HumanLoopRequestSource' => [ 'AwsManagedHumanLoopRequestSource' => 'AWS/Rekognition/DetectModerationLabels/Image/V3|AWS/Textract/AnalyzeDocument/Forms/V1', ], 'OutputConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'RoleArn' => '<string>', ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp when the flow definition was created.
- FailureReason
-
- Type: string
The reason your flow definition failed.
- FlowDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the flow defintion.
- FlowDefinitionName
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the flow definition.
- FlowDefinitionStatus
-
- Required: Yes
- Type: string
The status of the flow definition. Valid values are listed below.
- HumanLoopActivationConfig
-
- Type: HumanLoopActivationConfig structure
An object containing information about what triggers a human review workflow.
- HumanLoopConfig
-
- Type: HumanLoopConfig structure
An object containing information about who works on the task, the workforce task price, and other task details.
- HumanLoopRequestSource
-
- Type: HumanLoopRequestSource structure
Container for configuring the source of human task requests. Used to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
- OutputConfig
-
- Required: Yes
- Type: FlowDefinitionOutputConfig structure
An object containing information about the output file.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) execution role for the flow definition.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeHub
$result = $client->describeHub
([/* ... */]); $promise = $client->describeHubAsync
([/* ... */]);
Describes a hub.
Parameter Syntax
$result = $client->describeHub([ 'HubName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- HubName
-
- Required: Yes
- Type: string
The name of the hub to describe.
Result Syntax
[ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'HubArn' => '<string>', 'HubDescription' => '<string>', 'HubDisplayName' => '<string>', 'HubName' => '<string>', 'HubSearchKeywords' => ['<string>', ...], 'HubStatus' => 'InService|Creating|Updating|Deleting|CreateFailed|UpdateFailed|DeleteFailed', 'LastModifiedTime' => <DateTime>, 'S3StorageConfig' => [ 'S3OutputPath' => '<string>', ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the hub was created.
- FailureReason
-
- Type: string
The failure reason if importing hub content failed.
- HubArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the hub.
- HubDescription
-
- Type: string
A description of the hub.
- HubDisplayName
-
- Type: string
The display name of the hub.
- HubName
-
- Required: Yes
- Type: string
The name of the hub.
- HubSearchKeywords
-
- Type: Array of strings
The searchable keywords for the hub.
- HubStatus
-
- Required: Yes
- Type: string
The status of the hub.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the hub was last modified.
- S3StorageConfig
-
- Type: HubS3StorageConfig structure
The Amazon S3 storage configuration for the hub.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeHubContent
$result = $client->describeHubContent
([/* ... */]); $promise = $client->describeHubContentAsync
([/* ... */]);
Describe the content of a hub.
Parameter Syntax
$result = $client->describeHubContent([ 'HubContentName' => '<string>', // REQUIRED 'HubContentType' => 'Model|Notebook|ModelReference', // REQUIRED 'HubContentVersion' => '<string>', 'HubName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- HubContentName
-
- Required: Yes
- Type: string
The name of the content to describe.
- HubContentType
-
- Required: Yes
- Type: string
The type of content in the hub.
- HubContentVersion
-
- Type: string
The version of the content to describe.
- HubName
-
- Required: Yes
- Type: string
The name of the hub that contains the content to describe.
Result Syntax
[ 'CreationTime' => <DateTime>, 'DocumentSchemaVersion' => '<string>', 'FailureReason' => '<string>', 'HubArn' => '<string>', 'HubContentArn' => '<string>', 'HubContentDependencies' => [ [ 'DependencyCopyPath' => '<string>', 'DependencyOriginPath' => '<string>', ], // ... ], 'HubContentDescription' => '<string>', 'HubContentDisplayName' => '<string>', 'HubContentDocument' => '<string>', 'HubContentMarkdown' => '<string>', 'HubContentName' => '<string>', 'HubContentSearchKeywords' => ['<string>', ...], 'HubContentStatus' => 'Available|Importing|Deleting|ImportFailed|DeleteFailed', 'HubContentType' => 'Model|Notebook|ModelReference', 'HubContentVersion' => '<string>', 'HubName' => '<string>', 'ReferenceMinVersion' => '<string>', 'SageMakerPublicHubContentArn' => '<string>', 'SupportStatus' => 'Supported|Deprecated', ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that hub content was created.
- DocumentSchemaVersion
-
- Required: Yes
- Type: string
The document schema version for the hub content.
- FailureReason
-
- Type: string
The failure reason if importing hub content failed.
- HubArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the hub that contains the content.
- HubContentArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the hub content.
- HubContentDependencies
-
- Type: Array of HubContentDependency structures
The location of any dependencies that the hub content has, such as scripts, model artifacts, datasets, or notebooks.
- HubContentDescription
-
- Type: string
A description of the hub content.
- HubContentDisplayName
-
- Type: string
The display name of the hub content.
- HubContentDocument
-
- Required: Yes
- Type: string
The hub content document that describes information about the hub content such as type, associated containers, scripts, and more.
- HubContentMarkdown
-
- Type: string
A string that provides a description of the hub content. This string can include links, tables, and standard markdown formating.
- HubContentName
-
- Required: Yes
- Type: string
The name of the hub content.
- HubContentSearchKeywords
-
- Type: Array of strings
The searchable keywords for the hub content.
- HubContentStatus
-
- Required: Yes
- Type: string
The status of the hub content.
- HubContentType
-
- Required: Yes
- Type: string
The type of hub content.
- HubContentVersion
-
- Required: Yes
- Type: string
The version of the hub content.
- HubName
-
- Required: Yes
- Type: string
The name of the hub that contains the content.
- ReferenceMinVersion
-
- Type: string
The minimum version of the hub content.
- SageMakerPublicHubContentArn
-
- Type: string
The ARN of the public hub content.
- SupportStatus
-
- Type: string
The support status of the hub content.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeHumanTaskUi
$result = $client->describeHumanTaskUi
([/* ... */]); $promise = $client->describeHumanTaskUiAsync
([/* ... */]);
Returns information about the requested human task user interface (worker task template).
Parameter Syntax
$result = $client->describeHumanTaskUi([ 'HumanTaskUiName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- HumanTaskUiName
-
- Required: Yes
- Type: string
The name of the human task user interface (worker task template) you want information about.
Result Syntax
[ 'CreationTime' => <DateTime>, 'HumanTaskUiArn' => '<string>', 'HumanTaskUiName' => '<string>', 'HumanTaskUiStatus' => 'Active|Deleting', 'UiTemplate' => [ 'ContentSha256' => '<string>', 'Url' => '<string>', ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp when the human task user interface was created.
- HumanTaskUiArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the human task user interface (worker task template).
- HumanTaskUiName
-
- Required: Yes
- Type: string
The name of the human task user interface (worker task template).
- HumanTaskUiStatus
-
- Type: string
The status of the human task user interface (worker task template). Valid values are listed below.
- UiTemplate
-
- Required: Yes
- Type: UiTemplateInfo structure
Container for user interface template information.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeHyperParameterTuningJob
$result = $client->describeHyperParameterTuningJob
([/* ... */]); $promise = $client->describeHyperParameterTuningJobAsync
([/* ... */]);
Returns a description of a hyperparameter tuning job, depending on the fields selected. These fields can include the name, Amazon Resource Name (ARN), job status of your tuning job and more.
Parameter Syntax
$result = $client->describeHyperParameterTuningJob([ 'HyperParameterTuningJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- HyperParameterTuningJobName
-
- Required: Yes
- Type: string
The name of the tuning job.
Result Syntax
[ 'Autotune' => [ 'Mode' => 'Enabled', ], 'BestTrainingJob' => [ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'FinalHyperParameterTuningJobObjectiveMetric' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', 'Value' => <float>, ], 'ObjectiveStatus' => 'Succeeded|Pending|Failed', 'TrainingEndTime' => <DateTime>, 'TrainingJobArn' => '<string>', 'TrainingJobDefinitionName' => '<string>', 'TrainingJobName' => '<string>', 'TrainingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TrainingStartTime' => <DateTime>, 'TunedHyperParameters' => ['<string>', ...], 'TuningJobName' => '<string>', ], 'ConsumedResources' => [ 'RuntimeInSeconds' => <integer>, ], 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'HyperParameterTuningEndTime' => <DateTime>, 'HyperParameterTuningJobArn' => '<string>', 'HyperParameterTuningJobConfig' => [ 'HyperParameterTuningJobObjective' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', ], 'ParameterRanges' => [ 'AutoParameters' => [ [ 'Name' => '<string>', 'ValueHint' => '<string>', ], // ... ], 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', 'Values' => ['<string>', ...], ], // ... ], 'ContinuousParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], 'IntegerParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], ], 'RandomSeed' => <integer>, 'ResourceLimits' => [ 'MaxNumberOfTrainingJobs' => <integer>, 'MaxParallelTrainingJobs' => <integer>, 'MaxRuntimeInSeconds' => <integer>, ], 'Strategy' => 'Bayesian|Random|Hyperband|Grid', 'StrategyConfig' => [ 'HyperbandStrategyConfig' => [ 'MaxResource' => <integer>, 'MinResource' => <integer>, ], ], 'TrainingJobEarlyStoppingType' => 'Off|Auto', 'TuningJobCompletionCriteria' => [ 'BestObjectiveNotImproving' => [ 'MaxNumberOfTrainingJobsNotImproving' => <integer>, ], 'ConvergenceDetected' => [ 'CompleteOnConvergence' => 'Disabled|Enabled', ], 'TargetObjectiveMetricValue' => <float>, ], ], 'HyperParameterTuningJobName' => '<string>', 'HyperParameterTuningJobStatus' => 'Completed|InProgress|Failed|Stopped|Stopping|Deleting|DeleteFailed', 'LastModifiedTime' => <DateTime>, 'ObjectiveStatusCounters' => [ 'Failed' => <integer>, 'Pending' => <integer>, 'Succeeded' => <integer>, ], 'OverallBestTrainingJob' => [ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'FinalHyperParameterTuningJobObjectiveMetric' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', 'Value' => <float>, ], 'ObjectiveStatus' => 'Succeeded|Pending|Failed', 'TrainingEndTime' => <DateTime>, 'TrainingJobArn' => '<string>', 'TrainingJobDefinitionName' => '<string>', 'TrainingJobName' => '<string>', 'TrainingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TrainingStartTime' => <DateTime>, 'TunedHyperParameters' => ['<string>', ...], 'TuningJobName' => '<string>', ], 'TrainingJobDefinition' => [ 'AlgorithmSpecification' => [ 'AlgorithmName' => '<string>', 'MetricDefinitions' => [ [ 'Name' => '<string>', 'Regex' => '<string>', ], // ... ], 'TrainingImage' => '<string>', 'TrainingInputMode' => 'Pipe|File|FastFile', ], 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', ], 'DefinitionName' => '<string>', 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'Environment' => ['<string>', ...], 'HyperParameterRanges' => [ 'AutoParameters' => [ [ 'Name' => '<string>', 'ValueHint' => '<string>', ], // ... ], 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', 'Values' => ['<string>', ...], ], // ... ], 'ContinuousParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], 'IntegerParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], ], 'HyperParameterTuningResourceConfig' => [ 'AllocationStrategy' => 'Prioritized', 'InstanceConfigs' => [ [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeSizeInGB' => <integer>, ], // ... ], 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', 'FileSystemAccessMode' => 'rw|ro', 'FileSystemId' => '<string>', 'FileSystemType' => 'EFS|FSxLustre', ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'InstanceGroupNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'InputMode' => 'Pipe|File|FastFile', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, ], ], // ... ], 'OutputDataConfig' => [ 'CompressionType' => 'GZIP|NONE', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'ResourceConfig' => [ 'InstanceCount' => <integer>, 'InstanceGroups' => [ [ 'InstanceCount' => <integer>, 'InstanceGroupName' => '<string>', 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', ], // ... ], 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'KeepAlivePeriodInSeconds' => <integer>, 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'RetryStrategy' => [ 'MaximumRetryAttempts' => <integer>, ], 'RoleArn' => '<string>', 'StaticHyperParameters' => ['<string>', ...], 'StoppingCondition' => [ 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TuningObjective' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'TrainingJobDefinitions' => [ [ 'AlgorithmSpecification' => [ 'AlgorithmName' => '<string>', 'MetricDefinitions' => [ [ 'Name' => '<string>', 'Regex' => '<string>', ], // ... ], 'TrainingImage' => '<string>', 'TrainingInputMode' => 'Pipe|File|FastFile', ], 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', ], 'DefinitionName' => '<string>', 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'Environment' => ['<string>', ...], 'HyperParameterRanges' => [ 'AutoParameters' => [ [ 'Name' => '<string>', 'ValueHint' => '<string>', ], // ... ], 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', 'Values' => ['<string>', ...], ], // ... ], 'ContinuousParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], 'IntegerParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], ], 'HyperParameterTuningResourceConfig' => [ 'AllocationStrategy' => 'Prioritized', 'InstanceConfigs' => [ [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeSizeInGB' => <integer>, ], // ... ], 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', 'FileSystemAccessMode' => 'rw|ro', 'FileSystemId' => '<string>', 'FileSystemType' => 'EFS|FSxLustre', ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'InstanceGroupNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'InputMode' => 'Pipe|File|FastFile', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, ], ], // ... ], 'OutputDataConfig' => [ 'CompressionType' => 'GZIP|NONE', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'ResourceConfig' => [ 'InstanceCount' => <integer>, 'InstanceGroups' => [ [ 'InstanceCount' => <integer>, 'InstanceGroupName' => '<string>', 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', ], // ... ], 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'KeepAlivePeriodInSeconds' => <integer>, 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'RetryStrategy' => [ 'MaximumRetryAttempts' => <integer>, ], 'RoleArn' => '<string>', 'StaticHyperParameters' => ['<string>', ...], 'StoppingCondition' => [ 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TuningObjective' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], // ... ], 'TrainingJobStatusCounters' => [ 'Completed' => <integer>, 'InProgress' => <integer>, 'NonRetryableError' => <integer>, 'RetryableError' => <integer>, 'Stopped' => <integer>, ], 'TuningJobCompletionDetails' => [ 'ConvergenceDetectedTime' => <DateTime>, 'NumberOfTrainingJobsObjectiveNotImproving' => <integer>, ], 'WarmStartConfig' => [ 'ParentHyperParameterTuningJobs' => [ [ 'HyperParameterTuningJobName' => '<string>', ], // ... ], 'WarmStartType' => 'IdenticalDataAndAlgorithm|TransferLearning', ], ]
Result Details
Members
- Autotune
-
- Type: Autotune structure
A flag to indicate if autotune is enabled for the hyperparameter tuning job.
- BestTrainingJob
-
- Type: HyperParameterTrainingJobSummary structure
A TrainingJobSummary object that describes the training job that completed with the best current HyperParameterTuningJobObjective.
- ConsumedResources
-
- Type: HyperParameterTuningJobConsumedResources structure
The total resources consumed by your hyperparameter tuning job.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the tuning job started.
- FailureReason
-
- Type: string
If the tuning job failed, the reason it failed.
- HyperParameterTuningEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the tuning job ended.
- HyperParameterTuningJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the tuning job.
- HyperParameterTuningJobConfig
-
- Required: Yes
- Type: HyperParameterTuningJobConfig structure
The HyperParameterTuningJobConfig object that specifies the configuration of the tuning job.
- HyperParameterTuningJobName
-
- Required: Yes
- Type: string
The name of the hyperparameter tuning job.
- HyperParameterTuningJobStatus
-
- Required: Yes
- Type: string
The status of the tuning job.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the status of the tuning job was modified.
- ObjectiveStatusCounters
-
- Required: Yes
- Type: ObjectiveStatusCounters structure
The ObjectiveStatusCounters object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.
- OverallBestTrainingJob
-
- Type: HyperParameterTrainingJobSummary structure
If the hyperparameter tuning job is an warm start tuning job with a
WarmStartType
ofIDENTICAL_DATA_AND_ALGORITHM
, this is the TrainingJobSummary for the training job with the best objective metric value of all training jobs launched by this tuning job and all parent jobs specified for the warm start tuning job. - TrainingJobDefinition
-
- Type: HyperParameterTrainingJobDefinition structure
The HyperParameterTrainingJobDefinition object that specifies the definition of the training jobs that this tuning job launches.
- TrainingJobDefinitions
-
- Type: Array of HyperParameterTrainingJobDefinition structures
A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
- TrainingJobStatusCounters
-
- Required: Yes
- Type: TrainingJobStatusCounters structure
The TrainingJobStatusCounters object that specifies the number of training jobs, categorized by status, that this tuning job launched.
- TuningJobCompletionDetails
-
- Type: HyperParameterTuningJobCompletionDetails structure
Tuning job completion information returned as the response from a hyperparameter tuning job. This information tells if your tuning job has or has not converged. It also includes the number of training jobs that have not improved model performance as evaluated against the objective function.
- WarmStartConfig
-
- Type: HyperParameterTuningJobWarmStartConfig structure
The configuration for starting the hyperparameter parameter 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.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeImage
$result = $client->describeImage
([/* ... */]); $promise = $client->describeImageAsync
([/* ... */]);
Describes a SageMaker image.
Parameter Syntax
$result = $client->describeImage([ 'ImageName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ImageName
-
- Required: Yes
- Type: string
The name of the image to describe.
Result Syntax
[ 'CreationTime' => <DateTime>, 'Description' => '<string>', 'DisplayName' => '<string>', 'FailureReason' => '<string>', 'ImageArn' => '<string>', 'ImageName' => '<string>', 'ImageStatus' => 'CREATING|CREATED|CREATE_FAILED|UPDATING|UPDATE_FAILED|DELETING|DELETE_FAILED', 'LastModifiedTime' => <DateTime>, 'RoleArn' => '<string>', ]
Result Details
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the image was created.
- Description
-
- Type: string
The description of the image.
- DisplayName
-
- Type: string
The name of the image as displayed.
- FailureReason
-
- Type: string
When a create, update, or delete operation fails, the reason for the failure.
- ImageArn
-
- Type: string
The ARN of the image.
- ImageName
-
- Type: string
The name of the image.
- ImageStatus
-
- Type: string
The status of the image.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the image was last modified.
- RoleArn
-
- Type: string
The ARN of the IAM role that enables Amazon SageMaker to perform tasks on your behalf.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeImageVersion
$result = $client->describeImageVersion
([/* ... */]); $promise = $client->describeImageVersionAsync
([/* ... */]);
Describes a version of a SageMaker image.
Parameter Syntax
$result = $client->describeImageVersion([ 'Alias' => '<string>', 'ImageName' => '<string>', // REQUIRED 'Version' => <integer>, ]);
Parameter Details
Members
- Alias
-
- Type: string
The alias of the image version.
- ImageName
-
- Required: Yes
- Type: string
The name of the image.
- Version
-
- Type: int
The version of the image. If not specified, the latest version is described.
Result Syntax
[ 'BaseImage' => '<string>', 'ContainerImage' => '<string>', 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'Horovod' => true || false, 'ImageArn' => '<string>', 'ImageVersionArn' => '<string>', 'ImageVersionStatus' => 'CREATING|CREATED|CREATE_FAILED|DELETING|DELETE_FAILED', 'JobType' => 'TRAINING|INFERENCE|NOTEBOOK_KERNEL', 'LastModifiedTime' => <DateTime>, 'MLFramework' => '<string>', 'Processor' => 'CPU|GPU', 'ProgrammingLang' => '<string>', 'ReleaseNotes' => '<string>', 'VendorGuidance' => 'NOT_PROVIDED|STABLE|TO_BE_ARCHIVED|ARCHIVED', 'Version' => <integer>, ]
Result Details
Members
- BaseImage
-
- Type: string
The registry path of the container image on which this image version is based.
- ContainerImage
-
- Type: string
The registry path of the container image that contains this image version.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the version was created.
- FailureReason
-
- Type: string
When a create or delete operation fails, the reason for the failure.
- Horovod
-
- Type: boolean
Indicates Horovod compatibility.
- ImageArn
-
- Type: string
The ARN of the image the version is based on.
- ImageVersionArn
-
- Type: string
The ARN of the version.
- ImageVersionStatus
-
- Type: string
The status of the version.
- JobType
-
- Type: string
Indicates SageMaker job type compatibility.
-
TRAINING
: The image version is compatible with SageMaker training jobs. -
INFERENCE
: The image version is compatible with SageMaker inference jobs. -
NOTEBOOK_KERNEL
: The image version is compatible with SageMaker notebook kernels.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the version was last modified.
- MLFramework
-
- Type: string
The machine learning framework vended in the image version.
- Processor
-
- Type: string
Indicates CPU or GPU compatibility.
-
CPU
: The image version is compatible with CPU. -
GPU
: The image version is compatible with GPU.
- ProgrammingLang
-
- Type: string
The supported programming language and its version.
- ReleaseNotes
-
- Type: string
The maintainer description of the image version.
- VendorGuidance
-
- Type: string
The stability of the image version specified by the maintainer.
-
NOT_PROVIDED
: The maintainers did not provide a status for image version stability. -
STABLE
: The image version is stable. -
TO_BE_ARCHIVED
: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months. -
ARCHIVED
: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
- Version
-
- Type: int
The version number.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeInferenceComponent
$result = $client->describeInferenceComponent
([/* ... */]); $promise = $client->describeInferenceComponentAsync
([/* ... */]);
Returns information about an inference component.
Parameter Syntax
$result = $client->describeInferenceComponent([ 'InferenceComponentName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- InferenceComponentName
-
- Required: Yes
- Type: string
The name of the inference component.
Result Syntax
[ 'CreationTime' => <DateTime>, 'EndpointArn' => '<string>', 'EndpointName' => '<string>', 'FailureReason' => '<string>', 'InferenceComponentArn' => '<string>', 'InferenceComponentName' => '<string>', 'InferenceComponentStatus' => 'InService|Creating|Updating|Failed|Deleting', 'LastModifiedTime' => <DateTime>, 'RuntimeConfig' => [ 'CurrentCopyCount' => <integer>, 'DesiredCopyCount' => <integer>, ], 'Specification' => [ 'ComputeResourceRequirements' => [ 'MaxMemoryRequiredInMb' => <integer>, 'MinMemoryRequiredInMb' => <integer>, 'NumberOfAcceleratorDevicesRequired' => <float>, 'NumberOfCpuCoresRequired' => <float>, ], 'Container' => [ 'ArtifactUrl' => '<string>', 'DeployedImage' => [ 'ResolutionTime' => <DateTime>, 'ResolvedImage' => '<string>', 'SpecifiedImage' => '<string>', ], 'Environment' => ['<string>', ...], ], 'ModelName' => '<string>', 'StartupParameters' => [ 'ContainerStartupHealthCheckTimeoutInSeconds' => <integer>, 'ModelDataDownloadTimeoutInSeconds' => <integer>, ], ], 'VariantName' => '<string>', ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the inference component was created.
- EndpointArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the endpoint that hosts the inference component.
- EndpointName
-
- Required: Yes
- Type: string
The name of the endpoint that hosts the inference component.
- FailureReason
-
- Type: string
If the inference component status is
Failed
, the reason for the failure. - InferenceComponentArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the inference component.
- InferenceComponentName
-
- Required: Yes
- Type: string
The name of the inference component.
- InferenceComponentStatus
-
- Type: string
The status of the inference component.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the inference component was last updated.
- RuntimeConfig
-
- Type: InferenceComponentRuntimeConfigSummary structure
Details about the runtime settings for the model that is deployed with the inference component.
- Specification
-
- Type: InferenceComponentSpecificationSummary structure
Details about the resources that are deployed with this inference component.
- VariantName
-
- Type: string
The name of the production variant that hosts the inference component.
Errors
There are no errors described for this operation.
DescribeInferenceExperiment
$result = $client->describeInferenceExperiment
([/* ... */]); $promise = $client->describeInferenceExperimentAsync
([/* ... */]);
Returns details about an inference experiment.
Parameter Syntax
$result = $client->describeInferenceExperiment([ 'Name' => '<string>', // REQUIRED ]);
Parameter Details
Members
- Name
-
- Required: Yes
- Type: string
The name of the inference experiment to describe.
Result Syntax
[ 'Arn' => '<string>', 'CompletionTime' => <DateTime>, 'CreationTime' => <DateTime>, 'DataStorageConfig' => [ 'ContentType' => [ 'CsvContentTypes' => ['<string>', ...], 'JsonContentTypes' => ['<string>', ...], ], 'Destination' => '<string>', 'KmsKey' => '<string>', ], 'Description' => '<string>', 'EndpointMetadata' => [ 'EndpointConfigName' => '<string>', 'EndpointName' => '<string>', 'EndpointStatus' => 'OutOfService|Creating|Updating|SystemUpdating|RollingBack|InService|Deleting|Failed|UpdateRollbackFailed', 'FailureReason' => '<string>', ], 'KmsKey' => '<string>', 'LastModifiedTime' => <DateTime>, 'ModelVariants' => [ [ 'InfrastructureConfig' => [ 'InfrastructureType' => 'RealTimeInference', 'RealTimeInferenceConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge', ], ], 'ModelName' => '<string>', 'Status' => 'Creating|Updating|InService|Deleting|Deleted', 'VariantName' => '<string>', ], // ... ], 'Name' => '<string>', 'RoleArn' => '<string>', 'Schedule' => [ 'EndTime' => <DateTime>, 'StartTime' => <DateTime>, ], 'ShadowModeConfig' => [ 'ShadowModelVariants' => [ [ 'SamplingPercentage' => <integer>, 'ShadowModelVariantName' => '<string>', ], // ... ], 'SourceModelVariantName' => '<string>', ], 'Status' => 'Creating|Created|Updating|Running|Starting|Stopping|Completed|Cancelled', 'StatusReason' => '<string>', 'Type' => 'ShadowMode', ]
Result Details
Members
- Arn
-
- Required: Yes
- Type: string
The ARN of the inference experiment being described.
- CompletionTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp at which the inference experiment was completed.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp at which you created the inference experiment.
- DataStorageConfig
-
- Type: InferenceExperimentDataStorageConfig structure
The Amazon S3 location and configuration for storing inference request and response data.
- Description
-
- Type: string
The description of the inference experiment.
- EndpointMetadata
-
- Required: Yes
- Type: EndpointMetadata structure
The metadata of the endpoint on which the inference experiment ran.
- KmsKey
-
- Type: string
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. For more information, see CreateInferenceExperiment.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp at which you last modified the inference experiment.
- ModelVariants
-
- Required: Yes
- Type: Array of ModelVariantConfigSummary structures
An array of
ModelVariantConfigSummary
objects. There is one for each variant in the inference experiment. EachModelVariantConfigSummary
object in the array describes the infrastructure configuration for deploying the corresponding variant. - Name
-
- Required: Yes
- Type: string
The name of the inference experiment.
- RoleArn
-
- Type: string
The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
- Schedule
-
- Type: InferenceExperimentSchedule structure
The duration for which the inference experiment ran or will run.
- ShadowModeConfig
-
- Type: ShadowModeConfig structure
The configuration of
ShadowMode
inference experiment type, which shows the production variant that takes all the inference requests, and the shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also shows the percentage of requests that Amazon SageMaker replicates. - Status
-
- Required: Yes
- Type: string
The status of the inference experiment. The following are the possible statuses for an inference experiment:
-
Creating
- Amazon SageMaker is creating your experiment. -
Created
- Amazon SageMaker has finished the creation of your experiment and will begin the experiment at the scheduled time. -
Updating
- When you make changes to your experiment, your experiment shows as updating. -
Starting
- Amazon SageMaker is beginning your experiment. -
Running
- Your experiment is in progress. -
Stopping
- Amazon SageMaker is stopping your experiment. -
Completed
- Your experiment has completed. -
Cancelled
- When you conclude your experiment early using the StopInferenceExperiment API, or if any operation fails with an unexpected error, it shows as cancelled.
- StatusReason
-
- Type: string
The error message or client-specified
Reason
from the StopInferenceExperiment API, that explains the status of the inference experiment. - Type
-
- Required: Yes
- Type: string
The type of the inference experiment.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeInferenceRecommendationsJob
$result = $client->describeInferenceRecommendationsJob
([/* ... */]); $promise = $client->describeInferenceRecommendationsJobAsync
([/* ... */]);
Provides the results of the Inference Recommender job. One or more recommendation jobs are returned.
Parameter Syntax
$result = $client->describeInferenceRecommendationsJob([ 'JobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- JobName
-
- Required: Yes
- Type: string
The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
Result Syntax
[ 'CompletionTime' => <DateTime>, 'CreationTime' => <DateTime>, 'EndpointPerformances' => [ [ 'EndpointInfo' => [ 'EndpointName' => '<string>', ], 'Metrics' => [ 'MaxInvocations' => <integer>, 'ModelLatency' => <integer>, ], ], // ... ], 'FailureReason' => '<string>', 'InferenceRecommendations' => [ [ 'EndpointConfiguration' => [ 'EndpointName' => '<string>', 'InitialInstanceCount' => <integer>, 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.12xlarge|ml.m5d.24xlarge|ml.c4.large|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.large|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.12xlarge|ml.r5.24xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.12xlarge|ml.r5d.24xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.dl1.24xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.p4d.24xlarge|ml.c7g.large|ml.c7g.xlarge|ml.c7g.2xlarge|ml.c7g.4xlarge|ml.c7g.8xlarge|ml.c7g.12xlarge|ml.c7g.16xlarge|ml.m6g.large|ml.m6g.xlarge|ml.m6g.2xlarge|ml.m6g.4xlarge|ml.m6g.8xlarge|ml.m6g.12xlarge|ml.m6g.16xlarge|ml.m6gd.large|ml.m6gd.xlarge|ml.m6gd.2xlarge|ml.m6gd.4xlarge|ml.m6gd.8xlarge|ml.m6gd.12xlarge|ml.m6gd.16xlarge|ml.c6g.large|ml.c6g.xlarge|ml.c6g.2xlarge|ml.c6g.4xlarge|ml.c6g.8xlarge|ml.c6g.12xlarge|ml.c6g.16xlarge|ml.c6gd.large|ml.c6gd.xlarge|ml.c6gd.2xlarge|ml.c6gd.4xlarge|ml.c6gd.8xlarge|ml.c6gd.12xlarge|ml.c6gd.16xlarge|ml.c6gn.large|ml.c6gn.xlarge|ml.c6gn.2xlarge|ml.c6gn.4xlarge|ml.c6gn.8xlarge|ml.c6gn.12xlarge|ml.c6gn.16xlarge|ml.r6g.large|ml.r6g.xlarge|ml.r6g.2xlarge|ml.r6g.4xlarge|ml.r6g.8xlarge|ml.r6g.12xlarge|ml.r6g.16xlarge|ml.r6gd.large|ml.r6gd.xlarge|ml.r6gd.2xlarge|ml.r6gd.4xlarge|ml.r6gd.8xlarge|ml.r6gd.12xlarge|ml.r6gd.16xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.p5.48xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge', 'ServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'VariantName' => '<string>', ], 'InvocationEndTime' => <DateTime>, 'InvocationStartTime' => <DateTime>, 'Metrics' => [ 'CostPerHour' => <float>, 'CostPerInference' => <float>, 'CpuUtilization' => <float>, 'MaxInvocations' => <integer>, 'MemoryUtilization' => <float>, 'ModelLatency' => <integer>, 'ModelSetupTime' => <integer>, ], 'ModelConfiguration' => [ 'CompilationJobName' => '<string>', 'EnvironmentParameters' => [ [ 'Key' => '<string>', 'Value' => '<string>', 'ValueType' => '<string>', ], // ... ], 'InferenceSpecificationName' => '<string>', ], 'RecommendationId' => '<string>', ], // ... ], 'InputConfig' => [ 'ContainerConfig' => [ 'DataInputConfig' => '<string>', 'Domain' => '<string>', 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'NearestModelName' => '<string>', 'PayloadConfig' => [ 'SamplePayloadUrl' => '<string>', 'SupportedContentTypes' => ['<string>', ...], ], 'SupportedEndpointType' => 'RealTime|Serverless', 'SupportedInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'Task' => '<string>', ], 'EndpointConfigurations' => [ [ 'EnvironmentParameterRanges' => [ 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', 'Value' => ['<string>', ...], ], // ... ], ], 'InferenceSpecificationName' => '<string>', 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.12xlarge|ml.m5d.24xlarge|ml.c4.large|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.large|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.12xlarge|ml.r5.24xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.12xlarge|ml.r5d.24xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.dl1.24xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.p4d.24xlarge|ml.c7g.large|ml.c7g.xlarge|ml.c7g.2xlarge|ml.c7g.4xlarge|ml.c7g.8xlarge|ml.c7g.12xlarge|ml.c7g.16xlarge|ml.m6g.large|ml.m6g.xlarge|ml.m6g.2xlarge|ml.m6g.4xlarge|ml.m6g.8xlarge|ml.m6g.12xlarge|ml.m6g.16xlarge|ml.m6gd.large|ml.m6gd.xlarge|ml.m6gd.2xlarge|ml.m6gd.4xlarge|ml.m6gd.8xlarge|ml.m6gd.12xlarge|ml.m6gd.16xlarge|ml.c6g.large|ml.c6g.xlarge|ml.c6g.2xlarge|ml.c6g.4xlarge|ml.c6g.8xlarge|ml.c6g.12xlarge|ml.c6g.16xlarge|ml.c6gd.large|ml.c6gd.xlarge|ml.c6gd.2xlarge|ml.c6gd.4xlarge|ml.c6gd.8xlarge|ml.c6gd.12xlarge|ml.c6gd.16xlarge|ml.c6gn.large|ml.c6gn.xlarge|ml.c6gn.2xlarge|ml.c6gn.4xlarge|ml.c6gn.8xlarge|ml.c6gn.12xlarge|ml.c6gn.16xlarge|ml.r6g.large|ml.r6g.xlarge|ml.r6g.2xlarge|ml.r6g.4xlarge|ml.r6g.8xlarge|ml.r6g.12xlarge|ml.r6g.16xlarge|ml.r6gd.large|ml.r6gd.xlarge|ml.r6gd.2xlarge|ml.r6gd.4xlarge|ml.r6gd.8xlarge|ml.r6gd.12xlarge|ml.r6gd.16xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.p5.48xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge', 'ServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], ], // ... ], 'Endpoints' => [ [ 'EndpointName' => '<string>', ], // ... ], 'JobDurationInSeconds' => <integer>, 'ModelName' => '<string>', 'ModelPackageVersionArn' => '<string>', 'ResourceLimit' => [ 'MaxNumberOfTests' => <integer>, 'MaxParallelOfTests' => <integer>, ], 'TrafficPattern' => [ 'Phases' => [ [ 'DurationInSeconds' => <integer>, 'InitialNumberOfUsers' => <integer>, 'SpawnRate' => <integer>, ], // ... ], 'Stairs' => [ 'DurationInSeconds' => <integer>, 'NumberOfSteps' => <integer>, 'UsersPerStep' => <integer>, ], 'TrafficType' => 'PHASES|STAIRS', ], 'VolumeKmsKeyId' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'JobArn' => '<string>', 'JobDescription' => '<string>', 'JobName' => '<string>', 'JobType' => 'Default|Advanced', 'LastModifiedTime' => <DateTime>, 'RoleArn' => '<string>', 'Status' => 'PENDING|IN_PROGRESS|COMPLETED|FAILED|STOPPING|STOPPED|DELETING|DELETED', 'StoppingConditions' => [ 'FlatInvocations' => 'Continue|Stop', 'MaxInvocations' => <integer>, 'ModelLatencyThresholds' => [ [ 'Percentile' => '<string>', 'ValueInMilliseconds' => <integer>, ], // ... ], ], ]
Result Details
Members
- CompletionTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the job completed.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the job was created.
- EndpointPerformances
-
- Type: Array of EndpointPerformance structures
The performance results from running an Inference Recommender job on an existing endpoint.
- FailureReason
-
- Type: string
If the job fails, provides information why the job failed.
- InferenceRecommendations
-
- Type: Array of InferenceRecommendation structures
The recommendations made by Inference Recommender.
- InputConfig
-
- Required: Yes
- Type: RecommendationJobInputConfig structure
Returns information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations you provided when you initiated the job.
- JobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the job.
- JobDescription
-
- Type: string
The job description that you provided when you initiated the job.
- JobName
-
- Required: Yes
- Type: string
The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
- JobType
-
- Required: Yes
- Type: string
The job type that you provided when you initiated the job.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the job was last modified.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role you provided when you initiated the job.
- Status
-
- Required: Yes
- Type: string
The status of the job.
- StoppingConditions
-
- Type: RecommendationJobStoppingConditions structure
The stopping conditions that you provided when you initiated the job.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeLabelingJob
$result = $client->describeLabelingJob
([/* ... */]); $promise = $client->describeLabelingJobAsync
([/* ... */]);
Gets information about a labeling job.
Parameter Syntax
$result = $client->describeLabelingJob([ 'LabelingJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- LabelingJobName
-
- Required: Yes
- Type: string
The name of the labeling job to return information for.
Result Syntax
[ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'HumanTaskConfig' => [ 'AnnotationConsolidationConfig' => [ 'AnnotationConsolidationLambdaArn' => '<string>', ], 'MaxConcurrentTaskCount' => <integer>, 'NumberOfHumanWorkersPerDataObject' => <integer>, 'PreHumanTaskLambdaArn' => '<string>', 'PublicWorkforceTaskPrice' => [ 'AmountInUsd' => [ 'Cents' => <integer>, 'Dollars' => <integer>, 'TenthFractionsOfACent' => <integer>, ], ], 'TaskAvailabilityLifetimeInSeconds' => <integer>, 'TaskDescription' => '<string>', 'TaskKeywords' => ['<string>', ...], 'TaskTimeLimitInSeconds' => <integer>, 'TaskTitle' => '<string>', 'UiConfig' => [ 'HumanTaskUiArn' => '<string>', 'UiTemplateS3Uri' => '<string>', ], 'WorkteamArn' => '<string>', ], 'InputConfig' => [ 'DataAttributes' => [ 'ContentClassifiers' => ['<string>', ...], ], 'DataSource' => [ 'S3DataSource' => [ 'ManifestS3Uri' => '<string>', ], 'SnsDataSource' => [ 'SnsTopicArn' => '<string>', ], ], ], 'JobReferenceCode' => '<string>', 'LabelAttributeName' => '<string>', 'LabelCategoryConfigS3Uri' => '<string>', 'LabelCounters' => [ 'FailedNonRetryableError' => <integer>, 'HumanLabeled' => <integer>, 'MachineLabeled' => <integer>, 'TotalLabeled' => <integer>, 'Unlabeled' => <integer>, ], 'LabelingJobAlgorithmsConfig' => [ 'InitialActiveLearningModelArn' => '<string>', 'LabelingJobAlgorithmSpecificationArn' => '<string>', 'LabelingJobResourceConfig' => [ 'VolumeKmsKeyId' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], ], 'LabelingJobArn' => '<string>', 'LabelingJobName' => '<string>', 'LabelingJobOutput' => [ 'FinalActiveLearningModelArn' => '<string>', 'OutputDatasetS3Uri' => '<string>', ], 'LabelingJobStatus' => 'Initializing|InProgress|Completed|Failed|Stopping|Stopped', 'LastModifiedTime' => <DateTime>, 'OutputConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', 'SnsTopicArn' => '<string>', ], 'RoleArn' => '<string>', 'StoppingConditions' => [ 'MaxHumanLabeledObjectCount' => <integer>, 'MaxPercentageOfInputDatasetLabeled' => <integer>, ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the labeling job was created.
- FailureReason
-
- Type: string
If the job failed, the reason that it failed.
- HumanTaskConfig
-
- Required: Yes
- Type: HumanTaskConfig structure
Configuration information required for human workers to complete a labeling task.
- InputConfig
-
- Required: Yes
- Type: LabelingJobInputConfig structure
Input configuration information 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.
- JobReferenceCode
-
- Required: Yes
- Type: string
A unique identifier for work done as part of a labeling job.
- LabelAttributeName
-
- Type: string
The attribute used as the label in the output manifest file.
- LabelCategoryConfigS3Uri
-
- Type: string
The S3 location of the JSON file that defines the categories used to label data objects. Please note the following label-category limits:
-
Semantic segmentation labeling jobs using automated labeling: 20 labels
-
Box bounding labeling jobs (all): 10 labels
The file is a JSON structure in the following format:
{
"document-version": "2018-11-28"
"labels": [
{
"label": "label 1"
},
{
"label": "label 2"
},
...
{
"label": "label n"
}
]
}
- LabelCounters
-
- Required: Yes
- Type: LabelCounters structure
Provides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn't be labeled, and the total number of objects labeled.
- LabelingJobAlgorithmsConfig
-
- Type: LabelingJobAlgorithmsConfig structure
Configuration information for automated data labeling.
- LabelingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the labeling job.
- LabelingJobName
-
- Required: Yes
- Type: string
The name assigned to the labeling job when it was created.
- LabelingJobOutput
-
- Type: LabelingJobOutput structure
The location of the output produced by the labeling job.
- LabelingJobStatus
-
- Required: Yes
- Type: string
The processing status of the labeling job.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the labeling job was last updated.
- OutputConfig
-
- Required: Yes
- Type: LabelingJobOutputConfig structure
The location of the job's output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during data labeling.
- StoppingConditions
-
- Type: LabelingJobStoppingConditions structure
A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeLineageGroup
$result = $client->describeLineageGroup
([/* ... */]); $promise = $client->describeLineageGroupAsync
([/* ... */]);
Provides a list of properties for the requested lineage group. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
Parameter Syntax
$result = $client->describeLineageGroup([ 'LineageGroupName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- LineageGroupName
-
- Required: Yes
- Type: string
The name of the lineage group.
Result Syntax
[ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'Description' => '<string>', 'DisplayName' => '<string>', 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'LineageGroupArn' => '<string>', 'LineageGroupName' => '<string>', ]
Result Details
Members
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time of lineage group.
- Description
-
- Type: string
The description of the lineage group.
- DisplayName
-
- Type: string
The display name of the lineage group.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last modified time of the lineage group.
- LineageGroupArn
-
- Type: string
The Amazon Resource Name (ARN) of the lineage group.
- LineageGroupName
-
- Type: string
The name of the lineage group.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeMlflowTrackingServer
$result = $client->describeMlflowTrackingServer
([/* ... */]); $promise = $client->describeMlflowTrackingServerAsync
([/* ... */]);
Returns information about an MLflow Tracking Server.
Parameter Syntax
$result = $client->describeMlflowTrackingServer([ 'TrackingServerName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TrackingServerName
-
- Required: Yes
- Type: string
The name of the MLflow Tracking Server to describe.
Result Syntax
[ 'ArtifactStoreUri' => '<string>', 'AutomaticModelRegistration' => true || false, 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'IsActive' => 'Active|Inactive', 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'MlflowVersion' => '<string>', 'RoleArn' => '<string>', 'TrackingServerArn' => '<string>', 'TrackingServerName' => '<string>', 'TrackingServerSize' => 'Small|Medium|Large', 'TrackingServerStatus' => 'Creating|Created|CreateFailed|Updating|Updated|UpdateFailed|Deleting|DeleteFailed|Stopping|Stopped|StopFailed|Starting|Started|StartFailed|MaintenanceInProgress|MaintenanceComplete|MaintenanceFailed', 'TrackingServerUrl' => '<string>', 'WeeklyMaintenanceWindowStart' => '<string>', ]
Result Details
Members
- ArtifactStoreUri
-
- Type: string
The S3 URI of the general purpose bucket used as the MLflow Tracking Server artifact store.
- AutomaticModelRegistration
-
- Type: boolean
Whether automatic registration of new MLflow models to the SageMaker Model Registry is enabled.
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of when the described MLflow Tracking Server was created.
- IsActive
-
- Type: string
Whether the described MLflow Tracking Server is currently active.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of when the described MLflow Tracking Server was last modified.
- MlflowVersion
-
- Type: string
The MLflow version used for the described tracking server.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) for an IAM role in your account that the described MLflow Tracking Server uses to access the artifact store in Amazon S3.
- TrackingServerArn
-
- Type: string
The ARN of the described tracking server.
- TrackingServerName
-
- Type: string
The name of the described tracking server.
- TrackingServerSize
-
- Type: string
The size of the described tracking server.
- TrackingServerStatus
-
- Type: string
The current creation status of the described MLflow Tracking Server.
- TrackingServerUrl
-
- Type: string
The URL to connect to the MLflow user interface for the described tracking server.
- WeeklyMaintenanceWindowStart
-
- Type: string
The day and time of the week when weekly maintenance occurs on the described tracking server.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeModel
$result = $client->describeModel
([/* ... */]); $promise = $client->describeModelAsync
([/* ... */]);
Describes a model that you created using the CreateModel
API.
Parameter Syntax
$result = $client->describeModel([ 'ModelName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ModelName
-
- Required: Yes
- Type: string
The name of the model.
Result Syntax
[ 'Containers' => [ [ 'AdditionalModelDataSources' => [ [ 'ChannelName' => '<string>', 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], // ... ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ImageConfig' => [ 'RepositoryAccessMode' => 'Platform|Vpc', 'RepositoryAuthConfig' => [ 'RepositoryCredentialsProviderArn' => '<string>', ], ], 'InferenceSpecificationName' => '<string>', 'Mode' => 'SingleModel|MultiModel', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], 'ModelDataUrl' => '<string>', 'ModelPackageName' => '<string>', 'MultiModelConfig' => [ 'ModelCacheSetting' => 'Enabled|Disabled', ], ], // ... ], 'CreationTime' => <DateTime>, 'DeploymentRecommendation' => [ 'RealTimeInferenceRecommendations' => [ [ 'Environment' => ['<string>', ...], 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.12xlarge|ml.m5d.24xlarge|ml.c4.large|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.large|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.12xlarge|ml.r5.24xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.12xlarge|ml.r5d.24xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.dl1.24xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.p4d.24xlarge|ml.c7g.large|ml.c7g.xlarge|ml.c7g.2xlarge|ml.c7g.4xlarge|ml.c7g.8xlarge|ml.c7g.12xlarge|ml.c7g.16xlarge|ml.m6g.large|ml.m6g.xlarge|ml.m6g.2xlarge|ml.m6g.4xlarge|ml.m6g.8xlarge|ml.m6g.12xlarge|ml.m6g.16xlarge|ml.m6gd.large|ml.m6gd.xlarge|ml.m6gd.2xlarge|ml.m6gd.4xlarge|ml.m6gd.8xlarge|ml.m6gd.12xlarge|ml.m6gd.16xlarge|ml.c6g.large|ml.c6g.xlarge|ml.c6g.2xlarge|ml.c6g.4xlarge|ml.c6g.8xlarge|ml.c6g.12xlarge|ml.c6g.16xlarge|ml.c6gd.large|ml.c6gd.xlarge|ml.c6gd.2xlarge|ml.c6gd.4xlarge|ml.c6gd.8xlarge|ml.c6gd.12xlarge|ml.c6gd.16xlarge|ml.c6gn.large|ml.c6gn.xlarge|ml.c6gn.2xlarge|ml.c6gn.4xlarge|ml.c6gn.8xlarge|ml.c6gn.12xlarge|ml.c6gn.16xlarge|ml.r6g.large|ml.r6g.xlarge|ml.r6g.2xlarge|ml.r6g.4xlarge|ml.r6g.8xlarge|ml.r6g.12xlarge|ml.r6g.16xlarge|ml.r6gd.large|ml.r6gd.xlarge|ml.r6gd.2xlarge|ml.r6gd.4xlarge|ml.r6gd.8xlarge|ml.r6gd.12xlarge|ml.r6gd.16xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.p5.48xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge', 'RecommendationId' => '<string>', ], // ... ], 'RecommendationStatus' => 'IN_PROGRESS|COMPLETED|FAILED|NOT_APPLICABLE', ], 'EnableNetworkIsolation' => true || false, 'ExecutionRoleArn' => '<string>', 'InferenceExecutionConfig' => [ 'Mode' => 'Serial|Direct', ], 'ModelArn' => '<string>', 'ModelName' => '<string>', 'PrimaryContainer' => [ 'AdditionalModelDataSources' => [ [ 'ChannelName' => '<string>', 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], // ... ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ImageConfig' => [ 'RepositoryAccessMode' => 'Platform|Vpc', 'RepositoryAuthConfig' => [ 'RepositoryCredentialsProviderArn' => '<string>', ], ], 'InferenceSpecificationName' => '<string>', 'Mode' => 'SingleModel|MultiModel', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], 'ModelDataUrl' => '<string>', 'ModelPackageName' => '<string>', 'MultiModelConfig' => [ 'ModelCacheSetting' => 'Enabled|Disabled', ], ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ]
Result Details
Members
- Containers
-
- Type: Array of ContainerDefinition structures
The containers in the inference pipeline.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the model was created.
- DeploymentRecommendation
-
- Type: DeploymentRecommendation structure
A set of recommended deployment configurations for the model.
- EnableNetworkIsolation
-
- Type: boolean
If
True
, no inbound or outbound network calls can be made to or from the model container. - ExecutionRoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
- InferenceExecutionConfig
-
- Type: InferenceExecutionConfig structure
Specifies details of how containers in a multi-container endpoint are called.
- ModelArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model.
- ModelName
-
- Required: Yes
- Type: string
Name of the SageMaker model.
- PrimaryContainer
-
- Type: ContainerDefinition structure
The location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production.
- VpcConfig
-
- Type: VpcConfig structure
A VpcConfig object that specifies the VPC that this model has access to. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud
Errors
There are no errors described for this operation.
DescribeModelBiasJobDefinition
$result = $client->describeModelBiasJobDefinition
([/* ... */]); $promise = $client->describeModelBiasJobDefinitionAsync
([/* ... */]);
Returns a description of a model bias job definition.
Parameter Syntax
$result = $client->describeModelBiasJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the model bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
Result Syntax
[ 'CreationTime' => <DateTime>, 'JobDefinitionArn' => '<string>', 'JobDefinitionName' => '<string>', 'JobResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'ModelBiasAppSpecification' => [ 'ConfigUri' => '<string>', 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', ], 'ModelBiasBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], ], 'ModelBiasJobInput' => [ 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', 'DatasetFormat' => [ 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'GroundTruthS3Input' => [ 'S3Uri' => '<string>', ], ], 'ModelBiasJobOutputConfig' => [ 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ [ 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the model bias job was created.
- JobDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model bias job.
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
- JobResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources to deploy for a monitoring job.
- ModelBiasAppSpecification
-
- Required: Yes
- Type: ModelBiasAppSpecification structure
Configures the model bias job to run a specified Docker container image.
- ModelBiasBaselineConfig
-
- Type: ModelBiasBaselineConfig structure
The baseline configuration for a model bias job.
- ModelBiasJobInput
-
- Required: Yes
- Type: ModelBiasJobInput structure
Inputs for the model bias job.
- ModelBiasJobOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The output configuration for monitoring jobs.
- NetworkConfig
-
- Type: MonitoringNetworkConfig structure
Networking options for a model bias job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
A time limit for how long the monitoring job is allowed to run before stopping.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeModelCard
$result = $client->describeModelCard
([/* ... */]); $promise = $client->describeModelCardAsync
([/* ... */]);
Describes the content, creation time, and security configuration of an Amazon SageMaker Model Card.
Parameter Syntax
$result = $client->describeModelCard([ 'ModelCardName' => '<string>', // REQUIRED 'ModelCardVersion' => <integer>, ]);
Parameter Details
Members
- ModelCardName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the model card to describe.
- ModelCardVersion
-
- Type: int
The version of the model card to describe. If a version is not provided, then the latest version of the model card is described.
Result Syntax
[ 'Content' => '<string>', 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'ModelCardArn' => '<string>', 'ModelCardName' => '<string>', 'ModelCardProcessingStatus' => 'DeleteInProgress|DeletePending|ContentDeleted|ExportJobsDeleted|DeleteCompleted|DeleteFailed', 'ModelCardStatus' => 'Draft|PendingReview|Approved|Archived', 'ModelCardVersion' => <integer>, 'SecurityConfig' => [ 'KmsKeyId' => '<string>', ], ]
Result Details
Members
- Content
-
- Required: Yes
- Type: string
The content of the model card.
- CreatedBy
-
- Required: Yes
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time the model card was created.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time the model card was last modified.
- ModelCardArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model card.
- ModelCardName
-
- Required: Yes
- Type: string
The name of the model card.
- ModelCardProcessingStatus
-
- Type: string
The processing status of model card deletion. The
ModelCardProcessingStatus
updates throughout the different deletion steps.-
DeletePending
: Model card deletion request received. -
DeleteInProgress
: Model card deletion is in progress. -
ContentDeleted
: Deleted model card content. -
ExportJobsDeleted
: Deleted all export jobs associated with the model card. -
DeleteCompleted
: Successfully deleted the model card. -
DeleteFailed
: The model card failed to delete.
- ModelCardStatus
-
- Required: Yes
- Type: string
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
-
Draft
: The model card is a work in progress. -
PendingReview
: The model card is pending review. -
Approved
: The model card is approved. -
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
- ModelCardVersion
-
- Required: Yes
- Type: int
The version of the model card.
- SecurityConfig
-
- Type: ModelCardSecurityConfig structure
The security configuration used to protect model card content.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeModelCardExportJob
$result = $client->describeModelCardExportJob
([/* ... */]); $promise = $client->describeModelCardExportJobAsync
([/* ... */]);
Describes an Amazon SageMaker Model Card export job.
Parameter Syntax
$result = $client->describeModelCardExportJob([ 'ModelCardExportJobArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ModelCardExportJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model card export job to describe.
Result Syntax
[ 'CreatedAt' => <DateTime>, 'ExportArtifacts' => [ 'S3ExportArtifacts' => '<string>', ], 'FailureReason' => '<string>', 'LastModifiedAt' => <DateTime>, 'ModelCardExportJobArn' => '<string>', 'ModelCardExportJobName' => '<string>', 'ModelCardName' => '<string>', 'ModelCardVersion' => <integer>, 'OutputConfig' => [ 'S3OutputPath' => '<string>', ], 'Status' => 'InProgress|Completed|Failed', ]
Result Details
Members
- CreatedAt
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the model export job was created.
- ExportArtifacts
-
- Type: ModelCardExportArtifacts structure
The exported model card artifacts.
- FailureReason
-
- Type: string
The failure reason if the model export job fails.
- LastModifiedAt
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the model export job was last modified.
- ModelCardExportJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model card export job.
- ModelCardExportJobName
-
- Required: Yes
- Type: string
The name of the model card export job to describe.
- ModelCardName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the model card that the model export job exports.
- ModelCardVersion
-
- Required: Yes
- Type: int
The version of the model card that the model export job exports.
- OutputConfig
-
- Required: Yes
- Type: ModelCardExportOutputConfig structure
The export output details for the model card.
- Status
-
- Required: Yes
- Type: string
The completion status of the model card export job.
-
InProgress
: The model card export job is in progress. -
Completed
: The model card export job is complete. -
Failed
: The model card export job failed. To see the reason for the failure, see theFailureReason
field in the response to aDescribeModelCardExportJob
call.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeModelExplainabilityJobDefinition
$result = $client->describeModelExplainabilityJobDefinition
([/* ... */]); $promise = $client->describeModelExplainabilityJobDefinitionAsync
([/* ... */]);
Returns a description of a model explainability job definition.
Parameter Syntax
$result = $client->describeModelExplainabilityJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
Result Syntax
[ 'CreationTime' => <DateTime>, 'JobDefinitionArn' => '<string>', 'JobDefinitionName' => '<string>', 'JobResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'ModelExplainabilityAppSpecification' => [ 'ConfigUri' => '<string>', 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', ], 'ModelExplainabilityBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], ], 'ModelExplainabilityJobInput' => [ 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', 'DatasetFormat' => [ 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], ], 'ModelExplainabilityJobOutputConfig' => [ 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ [ 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the model explainability job was created.
- JobDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model explainability job.
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
- JobResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources to deploy for a monitoring job.
- ModelExplainabilityAppSpecification
-
- Required: Yes
- Type: ModelExplainabilityAppSpecification structure
Configures the model explainability job to run a specified Docker container image.
- ModelExplainabilityBaselineConfig
-
- Type: ModelExplainabilityBaselineConfig structure
The baseline configuration for a model explainability job.
- ModelExplainabilityJobInput
-
- Required: Yes
- Type: ModelExplainabilityJobInput structure
Inputs for the model explainability job.
- ModelExplainabilityJobOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The output configuration for monitoring jobs.
- NetworkConfig
-
- Type: MonitoringNetworkConfig structure
Networking options for a model explainability job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
A time limit for how long the monitoring job is allowed to run before stopping.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeModelPackage
$result = $client->describeModelPackage
([/* ... */]); $promise = $client->describeModelPackageAsync
([/* ... */]);
Returns a description of the specified model package, which is used to create SageMaker models or list them on Amazon Web Services Marketplace.
If you provided a KMS Key ID when you created your model package, you will see the KMS Decrypt API call in your CloudTrail logs when you use this API.
To create models in SageMaker, buyers can subscribe to model packages listed on Amazon Web Services Marketplace.
Parameter Syntax
$result = $client->describeModelPackage([ 'ModelPackageName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ModelPackageName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the model package to describe.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
Result Syntax
[ 'AdditionalInferenceSpecifications' => [ [ 'Containers' => [ [ 'AdditionalS3DataSource' => [ 'CompressionType' => 'None|Gzip', 'S3DataType' => 'S3Object|S3Prefix', 'S3Uri' => '<string>', ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'Image' => '<string>', 'ImageDigest' => '<string>', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], 'ModelDataUrl' => '<string>', 'ModelInput' => [ 'DataInputConfig' => '<string>', ], 'NearestModelName' => '<string>', 'ProductId' => '<string>', ], // ... ], 'Description' => '<string>', 'Name' => '<string>', 'SupportedContentTypes' => ['<string>', ...], 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'SupportedTransformInstanceTypes' => ['<string>', ...], ], // ... ], 'ApprovalDescription' => '<string>', 'CertifyForMarketplace' => true || false, 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'CustomerMetadataProperties' => ['<string>', ...], 'Domain' => '<string>', 'DriftCheckBaselines' => [ 'Bias' => [ 'ConfigFile' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'PostTrainingConstraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'PreTrainingConstraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'Explainability' => [ 'ConfigFile' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'ModelDataQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'ModelQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], ], 'InferenceSpecification' => [ 'Containers' => [ [ 'AdditionalS3DataSource' => [ 'CompressionType' => 'None|Gzip', 'S3DataType' => 'S3Object|S3Prefix', 'S3Uri' => '<string>', ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'Image' => '<string>', 'ImageDigest' => '<string>', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], 'ModelDataUrl' => '<string>', 'ModelInput' => [ 'DataInputConfig' => '<string>', ], 'NearestModelName' => '<string>', 'ProductId' => '<string>', ], // ... ], 'SupportedContentTypes' => ['<string>', ...], 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'SupportedTransformInstanceTypes' => ['<string>', ...], ], 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'ModelApprovalStatus' => 'Approved|Rejected|PendingManualApproval', 'ModelCard' => [ 'ModelCardContent' => '<string>', 'ModelCardStatus' => 'Draft|PendingReview|Approved|Archived', ], 'ModelMetrics' => [ 'Bias' => [ 'PostTrainingReport' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'PreTrainingReport' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Report' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'Explainability' => [ 'Report' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'ModelDataQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'ModelQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], ], 'ModelPackageArn' => '<string>', 'ModelPackageDescription' => '<string>', 'ModelPackageGroupName' => '<string>', 'ModelPackageName' => '<string>', 'ModelPackageStatus' => 'Pending|InProgress|Completed|Failed|Deleting', 'ModelPackageStatusDetails' => [ 'ImageScanStatuses' => [ [ 'FailureReason' => '<string>', 'Name' => '<string>', 'Status' => 'NotStarted|InProgress|Completed|Failed', ], // ... ], 'ValidationStatuses' => [ [ 'FailureReason' => '<string>', 'Name' => '<string>', 'Status' => 'NotStarted|InProgress|Completed|Failed', ], // ... ], ], 'ModelPackageVersion' => <integer>, 'SamplePayloadUrl' => '<string>', 'SecurityConfig' => [ 'KmsKeyId' => '<string>', ], 'SkipModelValidation' => 'All|None', 'SourceAlgorithmSpecification' => [ 'SourceAlgorithms' => [ [ 'AlgorithmName' => '<string>', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], 'ModelDataUrl' => '<string>', ], // ... ], ], 'SourceUri' => '<string>', 'Task' => '<string>', 'ValidationSpecification' => [ 'ValidationProfiles' => [ [ 'ProfileName' => '<string>', 'TransformJobDefinition' => [ 'BatchStrategy' => 'MultiRecord|SingleRecord', 'Environment' => ['<string>', ...], 'MaxConcurrentTransforms' => <integer>, 'MaxPayloadInMB' => <integer>, 'TransformInput' => [ 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'S3DataSource' => [ 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'SplitType' => 'None|Line|RecordIO|TFRecord', ], 'TransformOutput' => [ 'Accept' => '<string>', 'AssembleWith' => 'None|Line', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'TransformResources' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge', 'VolumeKmsKeyId' => '<string>', ], ], ], // ... ], 'ValidationRole' => '<string>', ], ]
Result Details
Members
- AdditionalInferenceSpecifications
-
- Type: Array of AdditionalInferenceSpecificationDefinition structures
An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
- ApprovalDescription
-
- Type: string
A description provided for the model approval.
- CertifyForMarketplace
-
- Type: boolean
Whether the model package is certified for listing on Amazon Web Services Marketplace.
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp specifying when the model package was created.
- CustomerMetadataProperties
-
- Type: Associative array of custom strings keys (CustomerMetadataKey) to strings
The metadata properties associated with the model package versions.
- Domain
-
- Type: string
The machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing.
- DriftCheckBaselines
-
- Type: DriftCheckBaselines structure
Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
- InferenceSpecification
-
- Type: InferenceSpecification structure
Details about inference jobs that you can run with models based on this model package.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last time that the model package was modified.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- ModelApprovalStatus
-
- Type: string
The approval status of the model package.
- ModelCard
-
- Type: ModelPackageModelCard structure
The model card associated with the model package. Since
ModelPackageModelCard
is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema ofModelCard
. TheModelPackageModelCard
schema does not includemodel_package_details
, andmodel_overview
is composed of themodel_creator
andmodel_artifact
properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version. - ModelMetrics
-
- Type: ModelMetrics structure
Metrics for the model.
- ModelPackageArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model package.
- ModelPackageDescription
-
- Type: string
A brief summary of the model package.
- ModelPackageGroupName
-
- Type: string
If the model is a versioned model, the name of the model group that the versioned model belongs to.
- ModelPackageName
-
- Required: Yes
- Type: string
The name of the model package being described.
- ModelPackageStatus
-
- Required: Yes
- Type: string
The current status of the model package.
- ModelPackageStatusDetails
-
- Required: Yes
- Type: ModelPackageStatusDetails structure
Details about the current status of the model package.
- ModelPackageVersion
-
- Type: int
The version of the model package.
- SamplePayloadUrl
-
- Type: string
The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix).
- SecurityConfig
-
- Type: ModelPackageSecurityConfig structure
The KMS Key ID (
KMSKeyId
) used for encryption of model package information. - SkipModelValidation
-
- Type: string
Indicates if you want to skip model validation.
- SourceAlgorithmSpecification
-
- Type: SourceAlgorithmSpecification structure
Details about the algorithm that was used to create the model package.
- SourceUri
-
- Type: string
The URI of the source for the model package.
- Task
-
- Type: string
The machine learning task you specified that your model package accomplishes. Common machine learning tasks include object detection and image classification.
- ValidationSpecification
-
- Type: ModelPackageValidationSpecification structure
Configurations for one or more transform jobs that SageMaker runs to test the model package.
Errors
There are no errors described for this operation.
DescribeModelPackageGroup
$result = $client->describeModelPackageGroup
([/* ... */]); $promise = $client->describeModelPackageGroupAsync
([/* ... */]);
Gets a description for the specified model group.
Parameter Syntax
$result = $client->describeModelPackageGroup([ 'ModelPackageGroupName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ModelPackageGroupName
-
- Required: Yes
- Type: string
The name of the model group to describe.
Result Syntax
[ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'ModelPackageGroupArn' => '<string>', 'ModelPackageGroupDescription' => '<string>', 'ModelPackageGroupName' => '<string>', 'ModelPackageGroupStatus' => 'Pending|InProgress|Completed|Failed|Deleting|DeleteFailed', ]
Result Details
Members
- CreatedBy
-
- Required: Yes
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the model group was created.
- ModelPackageGroupArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model group.
- ModelPackageGroupDescription
-
- Type: string
A description of the model group.
- ModelPackageGroupName
-
- Required: Yes
- Type: string
The name of the model group.
- ModelPackageGroupStatus
-
- Required: Yes
- Type: string
The status of the model group.
Errors
There are no errors described for this operation.
DescribeModelQualityJobDefinition
$result = $client->describeModelQualityJobDefinition
([/* ... */]); $promise = $client->describeModelQualityJobDefinitionAsync
([/* ... */]);
Returns a description of a model quality job definition.
Parameter Syntax
$result = $client->describeModelQualityJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the model quality job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
Result Syntax
[ 'CreationTime' => <DateTime>, 'JobDefinitionArn' => '<string>', 'JobDefinitionName' => '<string>', 'JobResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'ModelQualityAppSpecification' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', 'PostAnalyticsProcessorSourceUri' => '<string>', 'ProblemType' => 'BinaryClassification|MulticlassClassification|Regression', 'RecordPreprocessorSourceUri' => '<string>', ], 'ModelQualityBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], ], 'ModelQualityJobInput' => [ 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', 'DatasetFormat' => [ 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'GroundTruthS3Input' => [ 'S3Uri' => '<string>', ], ], 'ModelQualityJobOutputConfig' => [ 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ [ 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the model quality job was created.
- JobDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model quality job.
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the quality job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
- JobResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources to deploy for a monitoring job.
- ModelQualityAppSpecification
-
- Required: Yes
- Type: ModelQualityAppSpecification structure
Configures the model quality job to run a specified Docker container image.
- ModelQualityBaselineConfig
-
- Type: ModelQualityBaselineConfig structure
The baseline configuration for a model quality job.
- ModelQualityJobInput
-
- Required: Yes
- Type: ModelQualityJobInput structure
Inputs for the model quality job.
- ModelQualityJobOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The output configuration for monitoring jobs.
- NetworkConfig
-
- Type: MonitoringNetworkConfig structure
Networking options for a model quality job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
A time limit for how long the monitoring job is allowed to run before stopping.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeMonitoringSchedule
$result = $client->describeMonitoringSchedule
([/* ... */]); $promise = $client->describeMonitoringScheduleAsync
([/* ... */]);
Describes the schedule for a monitoring job.
Parameter Syntax
$result = $client->describeMonitoringSchedule([ 'MonitoringScheduleName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- MonitoringScheduleName
-
- Required: Yes
- Type: string
Name of a previously created monitoring schedule.
Result Syntax
[ 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'LastMonitoringExecutionSummary' => [ 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'MonitoringExecutionStatus' => 'Pending|Completed|CompletedWithViolations|InProgress|Failed|Stopping|Stopped', 'MonitoringJobDefinitionName' => '<string>', 'MonitoringScheduleName' => '<string>', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'ProcessingJobArn' => '<string>', 'ScheduledTime' => <DateTime>, ], 'MonitoringScheduleArn' => '<string>', 'MonitoringScheduleConfig' => [ 'MonitoringJobDefinition' => [ 'BaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], 'StatisticsResource' => [ 'S3Uri' => '<string>', ], ], 'Environment' => ['<string>', ...], 'MonitoringAppSpecification' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ImageUri' => '<string>', 'PostAnalyticsProcessorSourceUri' => '<string>', 'RecordPreprocessorSourceUri' => '<string>', ], 'MonitoringInputs' => [ [ 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', 'DatasetFormat' => [ 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], ], // ... ], 'MonitoringOutputConfig' => [ 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ [ 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'MonitoringResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], ], 'MonitoringJobDefinitionName' => '<string>', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'ScheduleConfig' => [ 'DataAnalysisEndTime' => '<string>', 'DataAnalysisStartTime' => '<string>', 'ScheduleExpression' => '<string>', ], ], 'MonitoringScheduleName' => '<string>', 'MonitoringScheduleStatus' => 'Pending|Failed|Scheduled|Stopped', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the monitoring job was created.
- EndpointName
-
- Type: string
The name of the endpoint for the monitoring job.
- FailureReason
-
- Type: string
A string, up to one KB in size, that contains the reason a monitoring job failed, if it failed.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the monitoring job was last modified.
- LastMonitoringExecutionSummary
-
- Type: MonitoringExecutionSummary structure
Describes metadata on the last execution to run, if there was one.
- MonitoringScheduleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the monitoring schedule.
- MonitoringScheduleConfig
-
- Required: Yes
- Type: MonitoringScheduleConfig structure
The configuration object that specifies the monitoring schedule and defines the monitoring job.
- MonitoringScheduleName
-
- Required: Yes
- Type: string
Name of the monitoring schedule.
- MonitoringScheduleStatus
-
- Required: Yes
- Type: string
The status of an monitoring job.
- MonitoringType
-
- Type: string
The type of the monitoring job that this schedule runs. This is one of the following values.
-
DATA_QUALITY
- The schedule is for a data quality monitoring job. -
MODEL_QUALITY
- The schedule is for a model quality monitoring job. -
MODEL_BIAS
- The schedule is for a bias monitoring job. -
MODEL_EXPLAINABILITY
- The schedule is for an explainability monitoring job.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeNotebookInstance
$result = $client->describeNotebookInstance
([/* ... */]); $promise = $client->describeNotebookInstanceAsync
([/* ... */]);
Returns information about a notebook instance.
Parameter Syntax
$result = $client->describeNotebookInstance([ 'NotebookInstanceName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- NotebookInstanceName
-
- Required: Yes
- Type: string
The name of the notebook instance that you want information about.
Result Syntax
[ 'AcceleratorTypes' => ['<string>', ...], 'AdditionalCodeRepositories' => ['<string>', ...], 'CreationTime' => <DateTime>, 'DefaultCodeRepository' => '<string>', 'DirectInternetAccess' => 'Enabled|Disabled', 'FailureReason' => '<string>', 'InstanceMetadataServiceConfiguration' => [ 'MinimumInstanceMetadataServiceVersion' => '<string>', ], 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge', 'KmsKeyId' => '<string>', 'LastModifiedTime' => <DateTime>, 'NetworkInterfaceId' => '<string>', 'NotebookInstanceArn' => '<string>', 'NotebookInstanceLifecycleConfigName' => '<string>', 'NotebookInstanceName' => '<string>', 'NotebookInstanceStatus' => 'Pending|InService|Stopping|Stopped|Failed|Deleting|Updating', 'PlatformIdentifier' => '<string>', 'RoleArn' => '<string>', 'RootAccess' => 'Enabled|Disabled', 'SecurityGroups' => ['<string>', ...], 'SubnetId' => '<string>', 'Url' => '<string>', 'VolumeSizeInGB' => <integer>, ]
Result Details
Members
- AcceleratorTypes
-
- Type: Array of strings
A list of the Elastic Inference (EI) instance types associated with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
- AdditionalCodeRepositories
-
- Type: Array of strings
An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp. Use this parameter to return the time when the notebook instance was created
- DefaultCodeRepository
-
- Type: string
The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
- DirectInternetAccess
-
- Type: string
Describes whether SageMaker provides internet access to the notebook instance. If this value is set to Disabled, the notebook instance does not have internet access, and cannot connect to SageMaker training and endpoint services.
For more information, see Notebook Instances Are Internet-Enabled by Default.
- FailureReason
-
- Type: string
If status is
Failed
, the reason it failed. - InstanceMetadataServiceConfiguration
-
- Type: InstanceMetadataServiceConfiguration structure
Information on the IMDS configuration of the notebook instance
- InstanceType
-
- Type: string
The type of ML compute instance running on the notebook instance.
- KmsKeyId
-
- Type: string
The Amazon Web Services KMS key ID SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp. Use this parameter to retrieve the time when the notebook instance was last modified.
- NetworkInterfaceId
-
- Type: string
The network interface IDs that SageMaker created at the time of creating the instance.
- NotebookInstanceArn
-
- Type: string
The Amazon Resource Name (ARN) of the notebook instance.
- NotebookInstanceLifecycleConfigName
-
- Type: string
Returns the name of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance
- NotebookInstanceName
-
- Type: string
The name of the SageMaker notebook instance.
- NotebookInstanceStatus
-
- Type: string
The status of the notebook instance.
- PlatformIdentifier
-
- Type: string
The platform identifier of the notebook instance runtime environment.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM role associated with the instance.
- RootAccess
-
- Type: string
Whether root access is enabled or disabled for users of the notebook instance.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
- SecurityGroups
-
- Type: Array of strings
The IDs of the VPC security groups.
- SubnetId
-
- Type: string
The ID of the VPC subnet.
- Url
-
- Type: string
The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
- VolumeSizeInGB
-
- Type: int
The size, in GB, of the ML storage volume attached to the notebook instance.
Errors
There are no errors described for this operation.
DescribeNotebookInstanceLifecycleConfig
$result = $client->describeNotebookInstanceLifecycleConfig
([/* ... */]); $promise = $client->describeNotebookInstanceLifecycleConfigAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->describeNotebookInstanceLifecycleConfig([ 'NotebookInstanceLifecycleConfigName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- NotebookInstanceLifecycleConfigName
-
- Required: Yes
- Type: string
The name of the lifecycle configuration to describe.
Result Syntax
[ 'CreationTime' => <DateTime>, 'LastModifiedTime' => <DateTime>, 'NotebookInstanceLifecycleConfigArn' => '<string>', 'NotebookInstanceLifecycleConfigName' => '<string>', 'OnCreate' => [ [ 'Content' => '<string>', ], // ... ], 'OnStart' => [ [ 'Content' => '<string>', ], // ... ], ]
Result Details
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that tells when the lifecycle configuration was created.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that tells when the lifecycle configuration was last modified.
- NotebookInstanceLifecycleConfigArn
-
- Type: string
The Amazon Resource Name (ARN) of the lifecycle configuration.
- NotebookInstanceLifecycleConfigName
-
- Type: string
The name of the lifecycle configuration.
- OnCreate
-
- Type: Array of NotebookInstanceLifecycleHook structures
The shell script that runs only once, when you create a notebook instance.
- OnStart
-
- Type: Array of NotebookInstanceLifecycleHook structures
The shell script that runs every time you start a notebook instance, including when you create the notebook instance.
Errors
There are no errors described for this operation.
DescribeOptimizationJob
$result = $client->describeOptimizationJob
([/* ... */]); $promise = $client->describeOptimizationJobAsync
([/* ... */]);
Provides the properties of the specified optimization job.
Parameter Syntax
$result = $client->describeOptimizationJob([ 'OptimizationJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- OptimizationJobName
-
- Required: Yes
- Type: string
The name that you assigned to the optimization job.
Result Syntax
[ 'CreationTime' => <DateTime>, 'DeploymentInstanceType' => 'ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge', 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'ModelSource' => [ 'S3' => [ 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3Uri' => '<string>', ], ], 'OptimizationConfigs' => [ [ 'ModelCompilationConfig' => [ 'Image' => '<string>', 'OverrideEnvironment' => ['<string>', ...], ], 'ModelQuantizationConfig' => [ 'Image' => '<string>', 'OverrideEnvironment' => ['<string>', ...], ], ], // ... ], 'OptimizationEndTime' => <DateTime>, 'OptimizationEnvironment' => ['<string>', ...], 'OptimizationJobArn' => '<string>', 'OptimizationJobName' => '<string>', 'OptimizationJobStatus' => 'INPROGRESS|COMPLETED|FAILED|STARTING|STOPPING|STOPPED', 'OptimizationOutput' => [ 'RecommendedInferenceImage' => '<string>', ], 'OptimizationStartTime' => <DateTime>, 'OutputConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputLocation' => '<string>', ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when you created the optimization job.
- DeploymentInstanceType
-
- Required: Yes
- Type: string
The type of instance that hosts the optimized model that you create with the optimization job.
- FailureReason
-
- Type: string
If the optimization job status is
FAILED
, the reason for the failure. - LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the optimization job was last updated.
- ModelSource
-
- Required: Yes
- Type: OptimizationJobModelSource structure
The location of the source model to optimize with an optimization job.
- OptimizationConfigs
-
- Required: Yes
- Type: Array of OptimizationConfig structures
Settings for each of the optimization techniques that the job applies.
- OptimizationEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the optimization job finished processing.
- OptimizationEnvironment
-
- Type: Associative array of custom strings keys (NonEmptyString256) to strings
The environment variables to set in the model container.
- OptimizationJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the optimization job.
- OptimizationJobName
-
- Required: Yes
- Type: string
The name that you assigned to the optimization job.
- OptimizationJobStatus
-
- Required: Yes
- Type: string
The current status of the optimization job.
- OptimizationOutput
-
- Type: OptimizationOutput structure
Output values produced by an optimization job.
- OptimizationStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the optimization job started.
- OutputConfig
-
- Required: Yes
- Type: OptimizationJobOutputConfig structure
Details for where to store the optimized model that you create with the optimization job.
- RoleArn
-
- Required: Yes
- Type: string
The ARN of the IAM role that you assigned to the optimization job.
- StoppingCondition
-
- Required: Yes
- Type: StoppingCondition structure
Specifies a limit to how long a job can run. When the job reaches the time limit, SageMaker ends the job. Use this API to cap costs.
To stop a training job, SageMaker sends the algorithm the
SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.The training algorithms provided by SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with
CreateModel
.The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.
- VpcConfig
-
- Type: OptimizationVpcConfig structure
A VPC in Amazon VPC that your optimized model has access to.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribePipeline
$result = $client->describePipeline
([/* ... */]); $promise = $client->describePipelineAsync
([/* ... */]);
Describes the details of a pipeline.
Parameter Syntax
$result = $client->describePipeline([ 'PipelineName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- PipelineName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the pipeline to describe.
Result Syntax
[ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'LastRunTime' => <DateTime>, 'ParallelismConfiguration' => [ 'MaxParallelExecutionSteps' => <integer>, ], 'PipelineArn' => '<string>', 'PipelineDefinition' => '<string>', 'PipelineDescription' => '<string>', 'PipelineDisplayName' => '<string>', 'PipelineName' => '<string>', 'PipelineStatus' => 'Active|Deleting', 'RoleArn' => '<string>', ]
Result Details
Members
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the pipeline was created.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the pipeline was last modified.
- LastRunTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the pipeline was last run.
- ParallelismConfiguration
-
- Type: ParallelismConfiguration structure
Lists the parallelism configuration applied to the pipeline.
- PipelineArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline.
- PipelineDefinition
-
- Type: string
The JSON pipeline definition.
- PipelineDescription
-
- Type: string
The description of the pipeline.
- PipelineDisplayName
-
- Type: string
The display name of the pipeline.
- PipelineName
-
- Type: string
The name of the pipeline.
- PipelineStatus
-
- Type: string
The status of the pipeline execution.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) that the pipeline uses to execute.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribePipelineDefinitionForExecution
$result = $client->describePipelineDefinitionForExecution
([/* ... */]); $promise = $client->describePipelineDefinitionForExecutionAsync
([/* ... */]);
Describes the details of an execution's pipeline definition.
Parameter Syntax
$result = $client->describePipelineDefinitionForExecution([ 'PipelineExecutionArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
- PipelineExecutionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
Result Syntax
[ 'CreationTime' => <DateTime>, 'PipelineDefinition' => '<string>', ]
Result Details
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the pipeline was created.
- PipelineDefinition
-
- Type: string
The JSON pipeline definition.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribePipelineExecution
$result = $client->describePipelineExecution
([/* ... */]); $promise = $client->describePipelineExecutionAsync
([/* ... */]);
Describes the details of a pipeline execution.
Parameter Syntax
$result = $client->describePipelineExecution([ 'PipelineExecutionArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
- PipelineExecutionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
Result Syntax
[ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'ParallelismConfiguration' => [ 'MaxParallelExecutionSteps' => <integer>, ], 'PipelineArn' => '<string>', 'PipelineExecutionArn' => '<string>', 'PipelineExecutionDescription' => '<string>', 'PipelineExecutionDisplayName' => '<string>', 'PipelineExecutionStatus' => 'Executing|Stopping|Stopped|Failed|Succeeded', 'PipelineExperimentConfig' => [ 'ExperimentName' => '<string>', 'TrialName' => '<string>', ], 'SelectiveExecutionConfig' => [ 'SelectedSteps' => [ [ 'StepName' => '<string>', ], // ... ], 'SourcePipelineExecutionArn' => '<string>', ], ]
Result Details
Members
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the pipeline execution was created.
- FailureReason
-
- Type: string
If the execution failed, a message describing why.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the pipeline execution was modified last.
- ParallelismConfiguration
-
- Type: ParallelismConfiguration structure
The parallelism configuration applied to the pipeline.
- PipelineArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline.
- PipelineExecutionArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
- PipelineExecutionDescription
-
- Type: string
The description of the pipeline execution.
- PipelineExecutionDisplayName
-
- Type: string
The display name of the pipeline execution.
- PipelineExecutionStatus
-
- Type: string
The status of the pipeline execution.
- PipelineExperimentConfig
-
- Type: PipelineExperimentConfig structure
Specifies the names of the experiment and trial created by a pipeline.
- SelectiveExecutionConfig
-
- Type: SelectiveExecutionConfig structure
The selective execution configuration applied to the pipeline run.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeProcessingJob
$result = $client->describeProcessingJob
([/* ... */]); $promise = $client->describeProcessingJobAsync
([/* ... */]);
Returns a description of a processing job.
Parameter Syntax
$result = $client->describeProcessingJob([ 'ProcessingJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ProcessingJobName
-
- Required: Yes
- Type: string
The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
Result Syntax
[ 'AppSpecification' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ImageUri' => '<string>', ], 'AutoMLJobArn' => '<string>', 'CreationTime' => <DateTime>, 'Environment' => ['<string>', ...], 'ExitMessage' => '<string>', 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'RunName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'MonitoringScheduleArn' => '<string>', 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'ProcessingEndTime' => <DateTime>, 'ProcessingInputs' => [ [ 'AppManaged' => true || false, 'DatasetDefinition' => [ 'AthenaDatasetDefinition' => [ 'Catalog' => '<string>', 'Database' => '<string>', 'KmsKeyId' => '<string>', 'OutputCompression' => 'GZIP|SNAPPY|ZLIB', 'OutputFormat' => 'PARQUET|ORC|AVRO|JSON|TEXTFILE', 'OutputS3Uri' => '<string>', 'QueryString' => '<string>', 'WorkGroup' => '<string>', ], 'DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'InputMode' => 'Pipe|File', 'LocalPath' => '<string>', 'RedshiftDatasetDefinition' => [ 'ClusterId' => '<string>', 'ClusterRoleArn' => '<string>', 'Database' => '<string>', 'DbUser' => '<string>', 'KmsKeyId' => '<string>', 'OutputCompression' => 'None|GZIP|BZIP2|ZSTD|SNAPPY', 'OutputFormat' => 'PARQUET|CSV', 'OutputS3Uri' => '<string>', 'QueryString' => '<string>', ], ], 'InputName' => '<string>', 'S3Input' => [ 'LocalPath' => '<string>', 'S3CompressionType' => 'None|Gzip', 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix', 'S3InputMode' => 'Pipe|File', 'S3Uri' => '<string>', ], ], // ... ], 'ProcessingJobArn' => '<string>', 'ProcessingJobName' => '<string>', 'ProcessingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'ProcessingOutputConfig' => [ 'KmsKeyId' => '<string>', 'Outputs' => [ [ 'AppManaged' => true || false, 'FeatureStoreOutput' => [ 'FeatureGroupName' => '<string>', ], 'OutputName' => '<string>', 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'ProcessingResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'ProcessingStartTime' => <DateTime>, 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], 'TrainingJobArn' => '<string>', ]
Result Details
Members
- AppSpecification
-
- Required: Yes
- Type: AppSpecification structure
Configures the processing job to run a specified container image.
- AutoMLJobArn
-
- Type: string
The ARN of an AutoML job associated with this processing job.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the processing job was created.
- Environment
-
- Type: Associative array of custom strings keys (ProcessingEnvironmentKey) to strings
The environment variables set in the Docker container.
- ExitMessage
-
- Type: string
An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
- ExperimentConfig
-
- Type: ExperimentConfig structure
The configuration information used to create an experiment.
- FailureReason
-
- Type: string
A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the processing job was last modified.
- MonitoringScheduleArn
-
- Type: string
The ARN of a monitoring schedule for an endpoint associated with this processing job.
- NetworkConfig
-
- Type: NetworkConfig structure
Networking options for a processing job.
- ProcessingEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the processing job completed.
- ProcessingInputs
-
- Type: Array of ProcessingInput structures
The inputs for a processing job.
- ProcessingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the processing job.
- ProcessingJobName
-
- Required: Yes
- Type: string
The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
- ProcessingJobStatus
-
- Required: Yes
- Type: string
Provides the status of a processing job.
- ProcessingOutputConfig
-
- Type: ProcessingOutputConfig structure
Output configuration for the processing job.
- ProcessingResources
-
- Required: Yes
- Type: ProcessingResources structure
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
- ProcessingStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the processing job started.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- StoppingCondition
-
- Type: ProcessingStoppingCondition structure
The time limit for how long the processing job is allowed to run.
- TrainingJobArn
-
- Type: string
The ARN of a training job associated with this processing job.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeProject
$result = $client->describeProject
([/* ... */]); $promise = $client->describeProjectAsync
([/* ... */]);
Describes the details of a project.
Parameter Syntax
$result = $client->describeProject([ 'ProjectName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ProjectName
-
- Required: Yes
- Type: string
The name of the project to describe.
Result Syntax
[ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'ProjectArn' => '<string>', 'ProjectDescription' => '<string>', 'ProjectId' => '<string>', 'ProjectName' => '<string>', 'ProjectStatus' => 'Pending|CreateInProgress|CreateCompleted|CreateFailed|DeleteInProgress|DeleteFailed|DeleteCompleted|UpdateInProgress|UpdateCompleted|UpdateFailed', 'ServiceCatalogProvisionedProductDetails' => [ 'ProvisionedProductId' => '<string>', 'ProvisionedProductStatusMessage' => '<string>', ], 'ServiceCatalogProvisioningDetails' => [ 'PathId' => '<string>', 'ProductId' => '<string>', 'ProvisioningArtifactId' => '<string>', 'ProvisioningParameters' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], ]
Result Details
Members
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the project was created.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp when project was last modified.
- ProjectArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the project.
- ProjectDescription
-
- Type: string
The description of the project.
- ProjectId
-
- Required: Yes
- Type: string
The ID of the project.
- ProjectName
-
- Required: Yes
- Type: string
The name of the project.
- ProjectStatus
-
- Required: Yes
- Type: string
The status of the project.
- ServiceCatalogProvisionedProductDetails
-
- Type: ServiceCatalogProvisionedProductDetails structure
Information about a provisioned service catalog product.
- ServiceCatalogProvisioningDetails
-
- Required: Yes
- Type: ServiceCatalogProvisioningDetails structure
Information used to provision a service catalog product. For information, see What is Amazon Web Services Service Catalog.
Errors
There are no errors described for this operation.
DescribeSpace
$result = $client->describeSpace
([/* ... */]); $promise = $client->describeSpaceAsync
([/* ... */]);
Describes the space.
Parameter Syntax
$result = $client->describeSpace([ 'DomainId' => '<string>', // REQUIRED 'SpaceName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DomainId
-
- Required: Yes
- Type: string
The ID of the associated domain.
- SpaceName
-
- Required: Yes
- Type: string
The name of the space.
Result Syntax
[ 'CreationTime' => <DateTime>, 'DomainId' => '<string>', 'FailureReason' => '<string>', 'HomeEfsFileSystemUid' => '<string>', 'LastModifiedTime' => <DateTime>, 'OwnershipSettings' => [ 'OwnerUserProfileName' => '<string>', ], 'SpaceArn' => '<string>', 'SpaceDisplayName' => '<string>', 'SpaceName' => '<string>', 'SpaceSettings' => [ 'AppType' => 'JupyterServer|KernelGateway|DetailedProfiler|TensorBoard|CodeEditor|JupyterLab|RStudioServerPro|RSessionGateway|Canvas', 'CodeEditorAppSettings' => [ 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'CustomFileSystems' => [ [ 'EFSFileSystem' => [ 'FileSystemId' => '<string>', ], ], // ... ], 'JupyterLabAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'JupyterServerAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'KernelGatewayAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', 'ImageName' => '<string>', 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'SpaceStorageSettings' => [ 'EbsStorageSettings' => [ 'EbsVolumeSizeInGb' => <integer>, ], ], ], 'SpaceSharingSettings' => [ 'SharingType' => 'Private|Shared', ], 'Status' => 'Deleting|Failed|InService|Pending|Updating|Update_Failed|Delete_Failed', 'Url' => '<string>', ]
Result Details
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time.
- DomainId
-
- Type: string
The ID of the associated domain.
- FailureReason
-
- Type: string
The failure reason.
- HomeEfsFileSystemUid
-
- Type: string
The ID of the space's profile in the Amazon EFS volume.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last modified time.
- OwnershipSettings
-
- Type: OwnershipSettings structure
The collection of ownership settings for a space.
- SpaceArn
-
- Type: string
The space's Amazon Resource Name (ARN).
- SpaceDisplayName
-
- Type: string
The name of the space that appears in the Amazon SageMaker Studio UI.
- SpaceName
-
- Type: string
The name of the space.
- SpaceSettings
-
- Type: SpaceSettings structure
A collection of space settings.
- SpaceSharingSettings
-
- Type: SpaceSharingSettings structure
The collection of space sharing settings for a space.
- Status
-
- Type: string
The status.
- Url
-
- Type: string
Returns the URL of the space. If the space is created with Amazon Web Services IAM Identity Center (Successor to Amazon Web Services Single Sign-On) authentication, users can navigate to the URL after appending the respective redirect parameter for the application type to be federated through Amazon Web Services IAM Identity Center.
The following application types are supported:
-
Studio Classic:
&redirect=JupyterServer
-
JupyterLab:
&redirect=JupyterLab
-
Code Editor, based on Code-OSS, Visual Studio Code - Open Source:
&redirect=CodeEditor
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeStudioLifecycleConfig
$result = $client->describeStudioLifecycleConfig
([/* ... */]); $promise = $client->describeStudioLifecycleConfigAsync
([/* ... */]);
Describes the Amazon SageMaker Studio Lifecycle Configuration.
Parameter Syntax
$result = $client->describeStudioLifecycleConfig([ 'StudioLifecycleConfigName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- StudioLifecycleConfigName
-
- Required: Yes
- Type: string
The name of the Amazon SageMaker Studio Lifecycle Configuration to describe.
Result Syntax
[ 'CreationTime' => <DateTime>, 'LastModifiedTime' => <DateTime>, 'StudioLifecycleConfigAppType' => 'JupyterServer|KernelGateway|CodeEditor|JupyterLab', 'StudioLifecycleConfigArn' => '<string>', 'StudioLifecycleConfigContent' => '<string>', 'StudioLifecycleConfigName' => '<string>', ]
Result Details
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time of the Amazon SageMaker Studio Lifecycle Configuration.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
This value is equivalent to CreationTime because Amazon SageMaker Studio Lifecycle Configurations are immutable.
- StudioLifecycleConfigAppType
-
- Type: string
The App type that the Lifecycle Configuration is attached to.
- StudioLifecycleConfigArn
-
- Type: string
The ARN of the Lifecycle Configuration to describe.
- StudioLifecycleConfigContent
-
- Type: string
The content of your Amazon SageMaker Studio Lifecycle Configuration script.
- StudioLifecycleConfigName
-
- Type: string
The name of the Amazon SageMaker Studio Lifecycle Configuration that is described.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeSubscribedWorkteam
$result = $client->describeSubscribedWorkteam
([/* ... */]); $promise = $client->describeSubscribedWorkteamAsync
([/* ... */]);
Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the Amazon Web Services Marketplace.
Parameter Syntax
$result = $client->describeSubscribedWorkteam([ 'WorkteamArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
- WorkteamArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the subscribed work team to describe.
Result Syntax
[ 'SubscribedWorkteam' => [ 'ListingId' => '<string>', 'MarketplaceDescription' => '<string>', 'MarketplaceTitle' => '<string>', 'SellerName' => '<string>', 'WorkteamArn' => '<string>', ], ]
Result Details
Members
- SubscribedWorkteam
-
- Required: Yes
- Type: SubscribedWorkteam structure
A
Workteam
instance that contains information about the work team.
Errors
There are no errors described for this operation.
DescribeTrainingJob
$result = $client->describeTrainingJob
([/* ... */]); $promise = $client->describeTrainingJobAsync
([/* ... */]);
Returns information about a training job.
Some of the attributes below only appear if the training job successfully starts. If the training job fails, TrainingJobStatus
is Failed
and, depending on the FailureReason
, attributes like TrainingStartTime
, TrainingTimeInSeconds
, TrainingEndTime
, and BillableTimeInSeconds
may not be present in the response.
Parameter Syntax
$result = $client->describeTrainingJob([ 'TrainingJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TrainingJobName
-
- Required: Yes
- Type: string
The name of the training job.
Result Syntax
[ 'AlgorithmSpecification' => [ 'AlgorithmName' => '<string>', 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'EnableSageMakerMetricsTimeSeries' => true || false, 'MetricDefinitions' => [ [ 'Name' => '<string>', 'Regex' => '<string>', ], // ... ], 'TrainingImage' => '<string>', 'TrainingImageConfig' => [ 'TrainingRepositoryAccessMode' => 'Platform|Vpc', 'TrainingRepositoryAuthConfig' => [ 'TrainingRepositoryCredentialsProviderArn' => '<string>', ], ], 'TrainingInputMode' => 'Pipe|File|FastFile', ], 'AutoMLJobArn' => '<string>', 'BillableTimeInSeconds' => <integer>, 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', ], 'CreationTime' => <DateTime>, 'DebugHookConfig' => [ 'CollectionConfigurations' => [ [ 'CollectionName' => '<string>', 'CollectionParameters' => ['<string>', ...], ], // ... ], 'HookParameters' => ['<string>', ...], 'LocalPath' => '<string>', 'S3OutputPath' => '<string>', ], 'DebugRuleConfigurations' => [ [ 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'LocalPath' => '<string>', 'RuleConfigurationName' => '<string>', 'RuleEvaluatorImage' => '<string>', 'RuleParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', 'VolumeSizeInGB' => <integer>, ], // ... ], 'DebugRuleEvaluationStatuses' => [ [ 'LastModifiedTime' => <DateTime>, 'RuleConfigurationName' => '<string>', 'RuleEvaluationJobArn' => '<string>', 'RuleEvaluationStatus' => 'InProgress|NoIssuesFound|IssuesFound|Error|Stopping|Stopped', 'StatusDetails' => '<string>', ], // ... ], 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'Environment' => ['<string>', ...], 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'RunName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'FailureReason' => '<string>', 'FinalMetricDataList' => [ [ 'MetricName' => '<string>', 'Timestamp' => <DateTime>, 'Value' => <float>, ], // ... ], 'HyperParameters' => ['<string>', ...], 'InfraCheckConfig' => [ 'EnableInfraCheck' => true || false, ], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', 'FileSystemAccessMode' => 'rw|ro', 'FileSystemId' => '<string>', 'FileSystemType' => 'EFS|FSxLustre', ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'InstanceGroupNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'InputMode' => 'Pipe|File|FastFile', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, ], ], // ... ], 'LabelingJobArn' => '<string>', 'LastModifiedTime' => <DateTime>, 'ModelArtifacts' => [ 'S3ModelArtifacts' => '<string>', ], 'OutputDataConfig' => [ 'CompressionType' => 'GZIP|NONE', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'ProfilerConfig' => [ 'DisableProfiler' => true || false, 'ProfilingIntervalInMilliseconds' => <integer>, 'ProfilingParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', ], 'ProfilerRuleConfigurations' => [ [ 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'LocalPath' => '<string>', 'RuleConfigurationName' => '<string>', 'RuleEvaluatorImage' => '<string>', 'RuleParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', 'VolumeSizeInGB' => <integer>, ], // ... ], 'ProfilerRuleEvaluationStatuses' => [ [ 'LastModifiedTime' => <DateTime>, 'RuleConfigurationName' => '<string>', 'RuleEvaluationJobArn' => '<string>', 'RuleEvaluationStatus' => 'InProgress|NoIssuesFound|IssuesFound|Error|Stopping|Stopped', 'StatusDetails' => '<string>', ], // ... ], 'ProfilingStatus' => 'Enabled|Disabled', 'RemoteDebugConfig' => [ 'EnableRemoteDebug' => true || false, ], 'ResourceConfig' => [ 'InstanceCount' => <integer>, 'InstanceGroups' => [ [ 'InstanceCount' => <integer>, 'InstanceGroupName' => '<string>', 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', ], // ... ], 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'KeepAlivePeriodInSeconds' => <integer>, 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'RetryStrategy' => [ 'MaximumRetryAttempts' => <integer>, ], 'RoleArn' => '<string>', 'SecondaryStatus' => 'Starting|LaunchingMLInstances|PreparingTrainingStack|Downloading|DownloadingTrainingImage|Training|Uploading|Stopping|Stopped|MaxRuntimeExceeded|Completed|Failed|Interrupted|MaxWaitTimeExceeded|Updating|Restarting|Pending', 'SecondaryStatusTransitions' => [ [ 'EndTime' => <DateTime>, 'StartTime' => <DateTime>, 'Status' => 'Starting|LaunchingMLInstances|PreparingTrainingStack|Downloading|DownloadingTrainingImage|Training|Uploading|Stopping|Stopped|MaxRuntimeExceeded|Completed|Failed|Interrupted|MaxWaitTimeExceeded|Updating|Restarting|Pending', 'StatusMessage' => '<string>', ], // ... ], 'StoppingCondition' => [ 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TensorBoardOutputConfig' => [ 'LocalPath' => '<string>', 'S3OutputPath' => '<string>', ], 'TrainingEndTime' => <DateTime>, 'TrainingJobArn' => '<string>', 'TrainingJobName' => '<string>', 'TrainingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TrainingStartTime' => <DateTime>, 'TrainingTimeInSeconds' => <integer>, 'TuningJobArn' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], 'WarmPoolStatus' => [ 'ResourceRetainedBillableTimeInSeconds' => <integer>, 'ReusedByJob' => '<string>', 'Status' => 'Available|Terminated|Reused|InUse', ], ]
Result Details
Members
- AlgorithmSpecification
-
- Required: Yes
- Type: AlgorithmSpecification structure
Information about the algorithm used for training, and algorithm metadata.
- AutoMLJobArn
-
- Type: string
The Amazon Resource Name (ARN) of an AutoML job.
- BillableTimeInSeconds
-
- Type: int
The billable time in seconds. Billable time refers to the absolute wall-clock time.
Multiply
BillableTimeInSeconds
by the number of instances (InstanceCount
) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows:BillableTimeInSeconds * InstanceCount
.You can calculate the savings from using managed spot training using the formula
(1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100
. For example, ifBillableTimeInSeconds
is 100 andTrainingTimeInSeconds
is 500, the savings is 80%. - CheckpointConfig
-
- Type: CheckpointConfig structure
Contains information about the output location for managed spot training checkpoint data.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the training job was created.
- DebugHookConfig
-
- Type: DebugHookConfig structure
Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the
DebugHookConfig
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job. - DebugRuleConfigurations
-
- Type: Array of DebugRuleConfiguration structures
Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
- DebugRuleEvaluationStatuses
-
- Type: Array of DebugRuleEvaluationStatus structures
Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.
- EnableInterContainerTrafficEncryption
-
- Type: boolean
To encrypt all communications between ML compute instances in distributed training, choose
True
. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training. - EnableManagedSpotTraining
-
- Type: boolean
A Boolean indicating whether managed spot training is enabled (
True
) or not (False
). - EnableNetworkIsolation
-
- Type: boolean
If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose
True
. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access. - Environment
-
- Type: Associative array of custom strings keys (TrainingEnvironmentKey) to strings
The environment variables to set in the Docker container.
- ExperimentConfig
-
- Type: ExperimentConfig structure
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
- FailureReason
-
- Type: string
If the training job failed, the reason it failed.
- FinalMetricDataList
-
- Type: Array of MetricData structures
A collection of
MetricData
objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch. - HyperParameters
-
- Type: Associative array of custom strings keys (HyperParameterKey) to strings
Algorithm-specific parameters.
- InfraCheckConfig
-
- Type: InfraCheckConfig structure
Contains information about the infrastructure health check configuration for the training job.
- InputDataConfig
-
- Type: Array of Channel structures
An array of
Channel
objects that describes each data input channel. - LabelingJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the status of the training job was last modified.
- ModelArtifacts
-
- Required: Yes
- Type: ModelArtifacts structure
Information about the Amazon S3 location that is configured for storing model artifacts.
- OutputDataConfig
-
- Type: OutputDataConfig structure
The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
- ProfilerConfig
-
- Type: ProfilerConfig structure
Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
- ProfilerRuleConfigurations
-
- Type: Array of ProfilerRuleConfiguration structures
Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
- ProfilerRuleEvaluationStatuses
-
- Type: Array of ProfilerRuleEvaluationStatus structures
Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.
- ProfilingStatus
-
- Type: string
Profiling status of a training job.
- RemoteDebugConfig
-
- Type: RemoteDebugConfig structure
Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
- ResourceConfig
-
- Required: Yes
- Type: ResourceConfig structure
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
- RetryStrategy
-
- Type: RetryStrategy structure
The number of times to retry the job when the job fails due to an
InternalServerError
. - RoleArn
-
- Type: string
The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
- SecondaryStatus
-
- Required: Yes
- Type: string
Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see
StatusMessage
under SecondaryStatusTransition.SageMaker provides primary statuses and secondary statuses that apply to each of them:
- InProgress
-
-
Starting
- Starting the training job. -
Downloading
- An optional stage for algorithms that supportFile
training input mode. It indicates that data is being downloaded to the ML storage volumes. -
Training
- Training is in progress. -
Interrupted
- The job stopped because the managed spot training instances were interrupted. -
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
-
- Completed
-
-
Completed
- The training job has completed.
-
- Failed
-
-
Failed
- The training job has failed. The reason for the failure is returned in theFailureReason
field ofDescribeTrainingJobResponse
.
-
- Stopped
-
-
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime. -
MaxWaitTimeExceeded
- The job stopped because it exceeded the maximum allowed wait time. -
Stopped
- The training job has stopped.
-
- Stopping
-
-
Stopping
- Stopping the training job.
-
Valid values for
SecondaryStatus
are subject to change.We no longer support the following secondary statuses:
-
LaunchingMLInstances
-
PreparingTraining
-
DownloadingTrainingImage
- SecondaryStatusTransitions
-
- Type: Array of SecondaryStatusTransition structures
A history of all of the secondary statuses that the training job has transitioned through.
- StoppingCondition
-
- Required: Yes
- Type: StoppingCondition structure
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the
SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost. - TensorBoardOutputConfig
-
- Type: TensorBoardOutputConfig structure
Configuration of storage locations for the Amazon SageMaker Debugger TensorBoard output data.
- TrainingEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of
TrainingStartTime
and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure. - TrainingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the training job.
- TrainingJobName
-
- Required: Yes
- Type: string
Name of the model training job.
- TrainingJobStatus
-
- Required: Yes
- Type: string
The status of the training job.
SageMaker provides the following training job statuses:
-
InProgress
- The training is in progress. -
Completed
- The training job has completed. -
Failed
- The training job has failed. To see the reason for the failure, see theFailureReason
field in the response to aDescribeTrainingJobResponse
call. -
Stopping
- The training job is stopping. -
Stopped
- The training job has stopped.
For more detailed information, see
SecondaryStatus
. - TrainingStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of
TrainingEndTime
. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container. - TrainingTimeInSeconds
-
- Type: int
The training time in seconds.
- TuningJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
- VpcConfig
-
- Type: VpcConfig structure
A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
- WarmPoolStatus
-
- Type: WarmPoolStatus structure
The status of the warm pool associated with the training job.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeTransformJob
$result = $client->describeTransformJob
([/* ... */]); $promise = $client->describeTransformJobAsync
([/* ... */]);
Returns information about a transform job.
Parameter Syntax
$result = $client->describeTransformJob([ 'TransformJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TransformJobName
-
- Required: Yes
- Type: string
The name of the transform job that you want to view details of.
Result Syntax
[ 'AutoMLJobArn' => '<string>', 'BatchStrategy' => 'MultiRecord|SingleRecord', 'CreationTime' => <DateTime>, 'DataCaptureConfig' => [ 'DestinationS3Uri' => '<string>', 'GenerateInferenceId' => true || false, 'KmsKeyId' => '<string>', ], 'DataProcessing' => [ 'InputFilter' => '<string>', 'JoinSource' => 'Input|None', 'OutputFilter' => '<string>', ], 'Environment' => ['<string>', ...], 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'RunName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'FailureReason' => '<string>', 'LabelingJobArn' => '<string>', 'MaxConcurrentTransforms' => <integer>, 'MaxPayloadInMB' => <integer>, 'ModelClientConfig' => [ 'InvocationsMaxRetries' => <integer>, 'InvocationsTimeoutInSeconds' => <integer>, ], 'ModelName' => '<string>', 'TransformEndTime' => <DateTime>, 'TransformInput' => [ 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'S3DataSource' => [ 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'SplitType' => 'None|Line|RecordIO|TFRecord', ], 'TransformJobArn' => '<string>', 'TransformJobName' => '<string>', 'TransformJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TransformOutput' => [ 'Accept' => '<string>', 'AssembleWith' => 'None|Line', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'TransformResources' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge', 'VolumeKmsKeyId' => '<string>', ], 'TransformStartTime' => <DateTime>, ]
Result Details
Members
- AutoMLJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the AutoML transform job.
- BatchStrategy
-
- Type: string
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set
SplitType
toLine
,RecordIO
, orTFRecord
. - CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the transform Job was created.
- DataCaptureConfig
-
- Type: BatchDataCaptureConfig structure
Configuration to control how SageMaker captures inference data.
- DataProcessing
-
- Type: DataProcessing structure
The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
- Environment
-
- Type: Associative array of custom strings keys (TransformEnvironmentKey) to strings
The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
- ExperimentConfig
-
- Type: ExperimentConfig structure
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
- FailureReason
-
- Type: string
If the transform job failed,
FailureReason
describes why it failed. A transform job creates a log file, which includes error messages, and stores it as an Amazon S3 object. For more information, see Log Amazon SageMaker Events with Amazon CloudWatch. - LabelingJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.
- MaxConcurrentTransforms
-
- Type: int
The maximum number of parallel requests on each instance node that can be launched in a transform job. The default value is 1.
- MaxPayloadInMB
-
- Type: int
The maximum payload size, in MB, used in the transform job.
- ModelClientConfig
-
- Type: ModelClientConfig structure
The timeout and maximum number of retries for processing a transform job invocation.
- ModelName
-
- Required: Yes
- Type: string
The name of the model used in the transform job.
- TransformEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of
TransformStartTime
. - TransformInput
-
- Required: Yes
- Type: TransformInput structure
Describes the dataset to be transformed and the Amazon S3 location where it is stored.
- TransformJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the transform job.
- TransformJobName
-
- Required: Yes
- Type: string
The name of the transform job.
- TransformJobStatus
-
- Required: Yes
- Type: string
The status of the transform job. If the transform job failed, the reason is returned in the
FailureReason
field. - TransformOutput
-
- Type: TransformOutput structure
Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
- TransformResources
-
- Required: Yes
- Type: TransformResources structure
Describes the resources, including ML instance types and ML instance count, to use for the transform job.
- TransformStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of
TransformEndTime
.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeTrial
$result = $client->describeTrial
([/* ... */]); $promise = $client->describeTrialAsync
([/* ... */]);
Provides a list of a trial's properties.
Parameter Syntax
$result = $client->describeTrial([ 'TrialName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TrialName
-
- Required: Yes
- Type: string
The name of the trial to describe.
Result Syntax
[ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'DisplayName' => '<string>', 'ExperimentName' => '<string>', 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'Source' => [ 'SourceArn' => '<string>', 'SourceType' => '<string>', ], 'TrialArn' => '<string>', 'TrialName' => '<string>', ]
Result Details
Members
- CreatedBy
-
- Type: UserContext structure
Who created the trial.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the trial was created.
- DisplayName
-
- Type: string
The name of the trial as displayed. If
DisplayName
isn't specified,TrialName
is displayed. - ExperimentName
-
- Type: string
The name of the experiment the trial is part of.
- LastModifiedBy
-
- Type: UserContext structure
Who last modified the trial.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the trial was last modified.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- Source
-
- Type: TrialSource structure
The Amazon Resource Name (ARN) of the source and, optionally, the job type.
- TrialArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial.
- TrialName
-
- Type: string
The name of the trial.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeTrialComponent
$result = $client->describeTrialComponent
([/* ... */]); $promise = $client->describeTrialComponentAsync
([/* ... */]);
Provides a list of a trials component's properties.
Parameter Syntax
$result = $client->describeTrialComponent([ 'TrialComponentName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TrialComponentName
-
- Required: Yes
- Type: string
The name of the trial component to describe.
Result Syntax
[ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'DisplayName' => '<string>', 'EndTime' => <DateTime>, 'InputArtifacts' => [ '<TrialComponentKey128>' => [ 'MediaType' => '<string>', 'Value' => '<string>', ], // ... ], 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'LineageGroupArn' => '<string>', 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'Metrics' => [ [ 'Avg' => <float>, 'Count' => <integer>, 'Last' => <float>, 'Max' => <float>, 'MetricName' => '<string>', 'Min' => <float>, 'SourceArn' => '<string>', 'StdDev' => <float>, 'TimeStamp' => <DateTime>, ], // ... ], 'OutputArtifacts' => [ '<TrialComponentKey128>' => [ 'MediaType' => '<string>', 'Value' => '<string>', ], // ... ], 'Parameters' => [ '<TrialComponentKey320>' => [ 'NumberValue' => <float>, 'StringValue' => '<string>', ], // ... ], 'Source' => [ 'SourceArn' => '<string>', 'SourceType' => '<string>', ], 'Sources' => [ [ 'SourceArn' => '<string>', 'SourceType' => '<string>', ], // ... ], 'StartTime' => <DateTime>, 'Status' => [ 'Message' => '<string>', 'PrimaryStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', ], 'TrialComponentArn' => '<string>', 'TrialComponentName' => '<string>', ]
Result Details
Members
- CreatedBy
-
- Type: UserContext structure
Who created the trial component.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component was created.
- DisplayName
-
- Type: string
The name of the component as displayed. If
DisplayName
isn't specified,TrialComponentName
is displayed. - EndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component ended.
- InputArtifacts
-
- Type: Associative array of custom strings keys (TrialComponentKey128) to TrialComponentArtifact structures
The input artifacts of the component.
- LastModifiedBy
-
- Type: UserContext structure
Who last modified the component.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component was last modified.
- LineageGroupArn
-
- Type: string
The Amazon Resource Name (ARN) of the lineage group.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- Metrics
-
- Type: Array of TrialComponentMetricSummary structures
The metrics for the component.
- OutputArtifacts
-
- Type: Associative array of custom strings keys (TrialComponentKey128) to TrialComponentArtifact structures
The output artifacts of the component.
- Parameters
-
- Type: Associative array of custom strings keys (TrialComponentKey320) to TrialComponentParameterValue structures
The hyperparameters of the component.
- Source
-
- Type: TrialComponentSource structure
The Amazon Resource Name (ARN) of the source and, optionally, the job type.
- Sources
-
- Type: Array of TrialComponentSource structures
A list of ARNs and, if applicable, job types for multiple sources of an experiment run.
- StartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component started.
- Status
-
- Type: TrialComponentStatus structure
The status of the component. States include:
-
InProgress
-
Completed
-
Failed
- TrialComponentArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial component.
- TrialComponentName
-
- Type: string
The name of the trial component.
Errors
- ResourceNotFound:
Resource being access is not found.
DescribeUserProfile
$result = $client->describeUserProfile
([/* ... */]); $promise = $client->describeUserProfileAsync
([/* ... */]);
Describes a user profile. For more information, see CreateUserProfile
.
Parameter Syntax
$result = $client->describeUserProfile([ 'DomainId' => '<string>', // REQUIRED 'UserProfileName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DomainId
-
- Required: Yes
- Type: string
The domain ID.
- UserProfileName
-
- Required: Yes
- Type: string
The user profile name. This value is not case sensitive.
Result Syntax
[ 'CreationTime' => <DateTime>, 'DomainId' => '<string>', 'FailureReason' => '<string>', 'HomeEfsFileSystemUid' => '<string>', 'LastModifiedTime' => <DateTime>, 'SingleSignOnUserIdentifier' => '<string>', 'SingleSignOnUserValue' => '<string>', 'Status' => 'Deleting|Failed|InService|Pending|Updating|Update_Failed|Delete_Failed', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', 'UserSettings' => [ 'CanvasAppSettings' => [ 'DirectDeploySettings' => [ 'Status' => 'ENABLED|DISABLED', ], 'EmrServerlessSettings' => [ 'ExecutionRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'GenerativeAiSettings' => [ 'AmazonBedrockRoleArn' => '<string>', ], 'IdentityProviderOAuthSettings' => [ [ 'DataSourceName' => 'SalesforceGenie|Snowflake', 'SecretArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], // ... ], 'KendraSettings' => [ 'Status' => 'ENABLED|DISABLED', ], 'ModelRegisterSettings' => [ 'CrossAccountModelRegisterRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'TimeSeriesForecastingSettings' => [ 'AmazonForecastRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'WorkspaceSettings' => [ 'S3ArtifactPath' => '<string>', 'S3KmsKeyId' => '<string>', ], ], 'CodeEditorAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', 'ImageName' => '<string>', 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'CustomFileSystemConfigs' => [ [ 'EFSFileSystemConfig' => [ 'FileSystemId' => '<string>', 'FileSystemPath' => '<string>', ], ], // ... ], 'CustomPosixUserConfig' => [ 'Gid' => <integer>, 'Uid' => <integer>, ], 'DefaultLandingUri' => '<string>', 'ExecutionRole' => '<string>', 'JupyterLabAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', ], // ... ], 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', 'ImageName' => '<string>', 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'EmrSettings' => [ 'AssumableRoleArns' => ['<string>', ...], 'ExecutionRoleArns' => ['<string>', ...], ], 'LifecycleConfigArns' => ['<string>', ...], ], 'JupyterServerAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'KernelGatewayAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', 'ImageName' => '<string>', 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'RSessionAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', 'ImageName' => '<string>', 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'RStudioServerProAppSettings' => [ 'AccessStatus' => 'ENABLED|DISABLED', 'UserGroup' => 'R_STUDIO_ADMIN|R_STUDIO_USER', ], 'SecurityGroups' => ['<string>', ...], 'SharingSettings' => [ 'NotebookOutputOption' => 'Allowed|Disabled', 'S3KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'SpaceStorageSettings' => [ 'DefaultEbsStorageSettings' => [ 'DefaultEbsVolumeSizeInGb' => <integer>, 'MaximumEbsVolumeSizeInGb' => <integer>, ], ], 'StudioWebPortal' => 'ENABLED|DISABLED', 'StudioWebPortalSettings' => [ 'HiddenAppTypes' => ['<string>', ...], 'HiddenMlTools' => ['<string>', ...], ], 'TensorBoardAppSettings' => [ 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], ], ]
Result Details
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time.
- DomainId
-
- Type: string
The ID of the domain that contains the profile.
- FailureReason
-
- Type: string
The failure reason.
- HomeEfsFileSystemUid
-
- Type: string
The ID of the user's profile in the Amazon Elastic File System volume.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last modified time.
- SingleSignOnUserIdentifier
-
- Type: string
The IAM Identity Center user identifier.
- SingleSignOnUserValue
-
- Type: string
The IAM Identity Center user value.
- Status
-
- Type: string
The status.
- UserProfileArn
-
- Type: string
The user profile Amazon Resource Name (ARN).
- UserProfileName
-
- Type: string
The user profile name.
- UserSettings
-
- Type: UserSettings structure
A collection of settings.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
DescribeWorkforce
$result = $client->describeWorkforce
([/* ... */]); $promise = $client->describeWorkforceAsync
([/* ... */]);
Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs). Allowable IP address ranges are the IP addresses that workers can use to access tasks.
This operation applies only to private workforces.
Parameter Syntax
$result = $client->describeWorkforce([ 'WorkforceName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- WorkforceName
-
- Required: Yes
- Type: string
The name of the private workforce whose access you want to restrict.
WorkforceName
is automatically set todefault
when a workforce is created and cannot be modified.
Result Syntax
[ 'Workforce' => [ 'CognitoConfig' => [ 'ClientId' => '<string>', 'UserPool' => '<string>', ], 'CreateDate' => <DateTime>, 'FailureReason' => '<string>', 'LastUpdatedDate' => <DateTime>, 'OidcConfig' => [ 'AuthenticationRequestExtraParams' => ['<string>', ...], 'AuthorizationEndpoint' => '<string>', 'ClientId' => '<string>', 'Issuer' => '<string>', 'JwksUri' => '<string>', 'LogoutEndpoint' => '<string>', 'Scope' => '<string>', 'TokenEndpoint' => '<string>', 'UserInfoEndpoint' => '<string>', ], 'SourceIpConfig' => [ 'Cidrs' => ['<string>', ...], ], 'Status' => 'Initializing|Updating|Deleting|Failed|Active', 'SubDomain' => '<string>', 'WorkforceArn' => '<string>', 'WorkforceName' => '<string>', 'WorkforceVpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], 'VpcEndpointId' => '<string>', 'VpcId' => '<string>', ], ], ]
Result Details
Members
- Workforce
-
- Required: Yes
- Type: Workforce structure
A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
Errors
There are no errors described for this operation.
DescribeWorkteam
$result = $client->describeWorkteam
([/* ... */]); $promise = $client->describeWorkteamAsync
([/* ... */]);
Gets information about a specific work team. You can see information such as the creation date, the last updated date, membership information, and the work team's Amazon Resource Name (ARN).
Parameter Syntax
$result = $client->describeWorkteam([ 'WorkteamName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- WorkteamName
-
- Required: Yes
- Type: string
The name of the work team to return a description of.
Result Syntax
[ 'Workteam' => [ 'CreateDate' => <DateTime>, 'Description' => '<string>', 'LastUpdatedDate' => <DateTime>, 'MemberDefinitions' => [ [ 'CognitoMemberDefinition' => [ 'ClientId' => '<string>', 'UserGroup' => '<string>', 'UserPool' => '<string>', ], 'OidcMemberDefinition' => [ 'Groups' => ['<string>', ...], ], ], // ... ], 'NotificationConfiguration' => [ 'NotificationTopicArn' => '<string>', ], 'ProductListingIds' => ['<string>', ...], 'SubDomain' => '<string>', 'WorkerAccessConfiguration' => [ 'S3Presign' => [ 'IamPolicyConstraints' => [ 'SourceIp' => 'Enabled|Disabled', 'VpcSourceIp' => 'Enabled|Disabled', ], ], ], 'WorkforceArn' => '<string>', 'WorkteamArn' => '<string>', 'WorkteamName' => '<string>', ], ]
Result Details
Members
- Workteam
-
- Required: Yes
- Type: Workteam structure
A
Workteam
instance that contains information about the work team.
Errors
There are no errors described for this operation.
DisableSagemakerServicecatalogPortfolio
$result = $client->disableSagemakerServicecatalogPortfolio
([/* ... */]); $promise = $client->disableSagemakerServicecatalogPortfolioAsync
([/* ... */]);
Disables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
Parameter Syntax
$result = $client->disableSagemakerServicecatalogPortfolio([ ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DisassociateTrialComponent
$result = $client->disassociateTrialComponent
([/* ... */]); $promise = $client->disassociateTrialComponentAsync
([/* ... */]);
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
.
Parameter Syntax
$result = $client->disassociateTrialComponent([ 'TrialComponentName' => '<string>', // REQUIRED 'TrialName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TrialComponentName
-
- Required: Yes
- Type: string
The name of the component to disassociate from the trial.
- TrialName
-
- Required: Yes
- Type: string
The name of the trial to disassociate from.
Result Syntax
[ 'TrialArn' => '<string>', 'TrialComponentArn' => '<string>', ]
Result Details
Members
- TrialArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial.
- TrialComponentArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial component.
Errors
- ResourceNotFound:
Resource being access is not found.
EnableSagemakerServicecatalogPortfolio
$result = $client->enableSagemakerServicecatalogPortfolio
([/* ... */]); $promise = $client->enableSagemakerServicecatalogPortfolioAsync
([/* ... */]);
Enables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
Parameter Syntax
$result = $client->enableSagemakerServicecatalogPortfolio([ ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
GetDeviceFleetReport
$result = $client->getDeviceFleetReport
([/* ... */]); $promise = $client->getDeviceFleetReportAsync
([/* ... */]);
Describes a fleet.
Parameter Syntax
$result = $client->getDeviceFleetReport([ 'DeviceFleetName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the fleet.
Result Syntax
[ 'AgentVersions' => [ [ 'AgentCount' => <integer>, 'Version' => '<string>', ], // ... ], 'Description' => '<string>', 'DeviceFleetArn' => '<string>', 'DeviceFleetName' => '<string>', 'DeviceStats' => [ 'ConnectedDeviceCount' => <integer>, 'RegisteredDeviceCount' => <integer>, ], 'ModelStats' => [ [ 'ActiveDeviceCount' => <integer>, 'ConnectedDeviceCount' => <integer>, 'ModelName' => '<string>', 'ModelVersion' => '<string>', 'OfflineDeviceCount' => <integer>, 'SamplingDeviceCount' => <integer>, ], // ... ], 'OutputConfig' => [ 'KmsKeyId' => '<string>', 'PresetDeploymentConfig' => '<string>', 'PresetDeploymentType' => 'GreengrassV2Component', 'S3OutputLocation' => '<string>', ], 'ReportGenerated' => <DateTime>, ]
Result Details
Members
- AgentVersions
-
- Type: Array of AgentVersion structures
The versions of Edge Manager agent deployed on the fleet.
- Description
-
- Type: string
Description of the fleet.
- DeviceFleetArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the device.
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the fleet.
- DeviceStats
-
- Type: DeviceStats structure
Status of devices.
- ModelStats
-
- Type: Array of EdgeModelStat structures
Status of model on device.
- OutputConfig
-
- Type: EdgeOutputConfig structure
The output configuration for storing sample data collected by the fleet.
- ReportGenerated
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Timestamp of when the report was generated.
Errors
There are no errors described for this operation.
GetLineageGroupPolicy
$result = $client->getLineageGroupPolicy
([/* ... */]); $promise = $client->getLineageGroupPolicyAsync
([/* ... */]);
The resource policy for the lineage group.
Parameter Syntax
$result = $client->getLineageGroupPolicy([ 'LineageGroupName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- LineageGroupName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the lineage group.
Result Syntax
[ 'LineageGroupArn' => '<string>', 'ResourcePolicy' => '<string>', ]
Result Details
Members
- LineageGroupArn
-
- Type: string
The Amazon Resource Name (ARN) of the lineage group.
- ResourcePolicy
-
- Type: string
The resource policy that gives access to the lineage group in another account.
Errors
- ResourceNotFound:
Resource being access is not found.
GetModelPackageGroupPolicy
$result = $client->getModelPackageGroupPolicy
([/* ... */]); $promise = $client->getModelPackageGroupPolicyAsync
([/* ... */]);
Gets a resource policy that manages access for a model group. For information about resource policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
Parameter Syntax
$result = $client->getModelPackageGroupPolicy([ 'ModelPackageGroupName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ModelPackageGroupName
-
- Required: Yes
- Type: string
The name of the model group for which to get the resource policy.
Result Syntax
[ 'ResourcePolicy' => '<string>', ]
Result Details
Members
- ResourcePolicy
-
- Required: Yes
- Type: string
The resource policy for the model group.
Errors
There are no errors described for this operation.
GetSagemakerServicecatalogPortfolioStatus
$result = $client->getSagemakerServicecatalogPortfolioStatus
([/* ... */]); $promise = $client->getSagemakerServicecatalogPortfolioStatusAsync
([/* ... */]);
Gets the status of Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
Parameter Syntax
$result = $client->getSagemakerServicecatalogPortfolioStatus([ ]);
Parameter Details
Members
Result Syntax
[ 'Status' => 'Enabled|Disabled', ]
Result Details
Members
- Status
-
- Type: string
Whether Service Catalog is enabled or disabled in SageMaker.
Errors
There are no errors described for this operation.
GetScalingConfigurationRecommendation
$result = $client->getScalingConfigurationRecommendation
([/* ... */]); $promise = $client->getScalingConfigurationRecommendationAsync
([/* ... */]);
Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job. Returns recommendations for autoscaling policies that you can apply to your SageMaker endpoint.
Parameter Syntax
$result = $client->getScalingConfigurationRecommendation([ 'EndpointName' => '<string>', 'InferenceRecommendationsJobName' => '<string>', // REQUIRED 'RecommendationId' => '<string>', 'ScalingPolicyObjective' => [ 'MaxInvocationsPerMinute' => <integer>, 'MinInvocationsPerMinute' => <integer>, ], 'TargetCpuUtilizationPerCore' => <integer>, ]);
Parameter Details
Members
- EndpointName
-
- Type: string
The name of an endpoint benchmarked during a previously completed inference recommendation job. This name should come from one of the recommendations returned by the job specified in the
InferenceRecommendationsJobName
field.Specify either this field or the
RecommendationId
field. - InferenceRecommendationsJobName
-
- Required: Yes
- Type: string
The name of a previously completed Inference Recommender job.
- RecommendationId
-
- Type: string
The recommendation ID of a previously completed inference recommendation. This ID should come from one of the recommendations returned by the job specified in the
InferenceRecommendationsJobName
field.Specify either this field or the
EndpointName
field. - ScalingPolicyObjective
-
- Type: ScalingPolicyObjective structure
An object where you specify the anticipated traffic pattern for an endpoint.
- TargetCpuUtilizationPerCore
-
- Type: int
The percentage of how much utilization you want an instance to use before autoscaling. The default value is 50%.
Result Syntax
[ 'DynamicScalingConfiguration' => [ 'MaxCapacity' => <integer>, 'MinCapacity' => <integer>, 'ScaleInCooldown' => <integer>, 'ScaleOutCooldown' => <integer>, 'ScalingPolicies' => [ [ 'TargetTracking' => [ 'MetricSpecification' => [ 'Customized' => [ 'MetricName' => '<string>', 'Namespace' => '<string>', 'Statistic' => 'Average|Minimum|Maximum|SampleCount|Sum', ], 'Predefined' => [ 'PredefinedMetricType' => '<string>', ], ], 'TargetValue' => <float>, ], ], // ... ], ], 'EndpointName' => '<string>', 'InferenceRecommendationsJobName' => '<string>', 'Metric' => [ 'InvocationsPerInstance' => <integer>, 'ModelLatency' => <integer>, ], 'RecommendationId' => '<string>', 'ScalingPolicyObjective' => [ 'MaxInvocationsPerMinute' => <integer>, 'MinInvocationsPerMinute' => <integer>, ], 'TargetCpuUtilizationPerCore' => <integer>, ]
Result Details
Members
- DynamicScalingConfiguration
-
- Type: DynamicScalingConfiguration structure
An object with the recommended values for you to specify when creating an autoscaling policy.
- EndpointName
-
- Type: string
The name of an endpoint benchmarked during a previously completed Inference Recommender job.
- InferenceRecommendationsJobName
-
- Type: string
The name of a previously completed Inference Recommender job.
- Metric
-
- Type: ScalingPolicyMetric structure
An object with a list of metrics that were benchmarked during the previously completed Inference Recommender job.
- RecommendationId
-
- Type: string
The recommendation ID of a previously completed inference recommendation.
- ScalingPolicyObjective
-
- Type: ScalingPolicyObjective structure
An object representing the anticipated traffic pattern for an endpoint that you specified in the request.
- TargetCpuUtilizationPerCore
-
- Type: int
The percentage of how much utilization you want an instance to use before autoscaling, which you specified in the request. The default value is 50%.
Errors
- ResourceNotFound:
Resource being access is not found.
GetSearchSuggestions
$result = $client->getSearchSuggestions
([/* ... */]); $promise = $client->getSearchSuggestionsAsync
([/* ... */]);
An auto-complete API for the search functionality in the SageMaker console. It returns suggestions of possible matches for the property name to use in Search
queries. Provides suggestions for HyperParameters
, Tags
, and Metrics
.
Parameter Syntax
$result = $client->getSearchSuggestions([ 'Resource' => 'TrainingJob|Experiment|ExperimentTrial|ExperimentTrialComponent|Endpoint|Model|ModelPackage|ModelPackageGroup|Pipeline|PipelineExecution|FeatureGroup|FeatureMetadata|Image|ImageVersion|Project|HyperParameterTuningJob|ModelCard', // REQUIRED 'SuggestionQuery' => [ 'PropertyNameQuery' => [ 'PropertyNameHint' => '<string>', // REQUIRED ], ], ]);
Parameter Details
Members
- Resource
-
- Required: Yes
- Type: string
The name of the SageMaker resource to search for.
- SuggestionQuery
-
- Type: SuggestionQuery structure
Limits the property names that are included in the response.
Result Syntax
[ 'PropertyNameSuggestions' => [ [ 'PropertyName' => '<string>', ], // ... ], ]
Result Details
Members
- PropertyNameSuggestions
-
- Type: Array of PropertyNameSuggestion structures
A list of property names for a
Resource
that match aSuggestionQuery
.
Errors
There are no errors described for this operation.
ImportHubContent
$result = $client->importHubContent
([/* ... */]); $promise = $client->importHubContentAsync
([/* ... */]);
Import hub content.
Parameter Syntax
$result = $client->importHubContent([ 'DocumentSchemaVersion' => '<string>', // REQUIRED 'HubContentDescription' => '<string>', 'HubContentDisplayName' => '<string>', 'HubContentDocument' => '<string>', // REQUIRED 'HubContentMarkdown' => '<string>', 'HubContentName' => '<string>', // REQUIRED 'HubContentSearchKeywords' => ['<string>', ...], 'HubContentType' => 'Model|Notebook|ModelReference', // REQUIRED 'HubContentVersion' => '<string>', 'HubName' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- DocumentSchemaVersion
-
- Required: Yes
- Type: string
The version of the hub content schema to import.
- HubContentDescription
-
- Type: string
A description of the hub content to import.
- HubContentDisplayName
-
- Type: string
The display name of the hub content to import.
- HubContentDocument
-
- Required: Yes
- Type: string
The hub content document that describes information about the hub content such as type, associated containers, scripts, and more.
- HubContentMarkdown
-
- Type: string
A string that provides a description of the hub content. This string can include links, tables, and standard markdown formating.
- HubContentName
-
- Required: Yes
- Type: string
The name of the hub content to import.
- HubContentSearchKeywords
-
- Type: Array of strings
The searchable keywords of the hub content.
- HubContentType
-
- Required: Yes
- Type: string
The type of hub content to import.
- HubContentVersion
-
- Type: string
The version of the hub content to import.
- HubName
-
- Required: Yes
- Type: string
The name of the hub to import content into.
- Tags
-
- Type: Array of Tag structures
Any tags associated with the hub content.
Result Syntax
[ 'HubArn' => '<string>', 'HubContentArn' => '<string>', ]
Result Details
Members
- HubArn
-
- Required: Yes
- Type: string
The ARN of the hub that the content was imported into.
- HubContentArn
-
- Required: Yes
- Type: string
The ARN of the hub content that was imported.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceNotFound:
Resource being access is not found.
ListActions
$result = $client->listActions
([/* ... */]); $promise = $client->listActionsAsync
([/* ... */]);
Lists the actions in your account and their properties.
Parameter Syntax
$result = $client->listActions([ 'ActionType' => '<string>', 'CreatedAfter' => <integer || string || DateTime>, 'CreatedBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', 'SourceUri' => '<string>', ]);
Parameter Details
Members
- ActionType
-
- Type: string
A filter that returns only actions of the specified type.
- CreatedAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only actions created on or after the specified time.
- CreatedBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only actions created on or before the specified time.
- MaxResults
-
- Type: int
The maximum number of actions to return in the response. The default value is 10.
- NextToken
-
- Type: string
If the previous call to
ListActions
didn't return the full set of actions, the call returns a token for getting the next set of actions. - SortBy
-
- Type: string
The property used to sort results. The default value is
CreationTime
. - SortOrder
-
- Type: string
The sort order. The default value is
Descending
. - SourceUri
-
- Type: string
A filter that returns only actions with the specified source URI.
Result Syntax
[ 'ActionSummaries' => [ [ 'ActionArn' => '<string>', 'ActionName' => '<string>', 'ActionType' => '<string>', 'CreationTime' => <DateTime>, 'LastModifiedTime' => <DateTime>, 'Source' => [ 'SourceId' => '<string>', 'SourceType' => '<string>', 'SourceUri' => '<string>', ], 'Status' => 'Unknown|InProgress|Completed|Failed|Stopping|Stopped', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- ActionSummaries
-
- Type: Array of ActionSummary structures
A list of actions and their properties.
- NextToken
-
- Type: string
A token for getting the next set of actions, if there are any.
Errors
- ResourceNotFound:
Resource being access is not found.
ListAlgorithms
$result = $client->listAlgorithms
([/* ... */]); $promise = $client->listAlgorithmsAsync
([/* ... */]);
Lists the machine learning algorithms that have been created.
Parameter Syntax
$result = $client->listAlgorithms([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only algorithms created after the specified time (timestamp).
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only algorithms created before the specified time (timestamp).
- MaxResults
-
- Type: int
The maximum number of algorithms to return in the response.
- NameContains
-
- Type: string
A string in the algorithm name. This filter returns only algorithms whose name contains the specified string.
- NextToken
-
- Type: string
If the response to a previous
ListAlgorithms
request was truncated, the response includes aNextToken
. To retrieve the next set of algorithms, use the token in the next request. - SortBy
-
- Type: string
The parameter by which to sort the results. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for the results. The default is
Ascending
.
Result Syntax
[ 'AlgorithmSummaryList' => [ [ 'AlgorithmArn' => '<string>', 'AlgorithmDescription' => '<string>', 'AlgorithmName' => '<string>', 'AlgorithmStatus' => 'Pending|InProgress|Completed|Failed|Deleting', 'CreationTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- AlgorithmSummaryList
-
- Required: Yes
- Type: Array of AlgorithmSummary structures
>An array of
AlgorithmSummary
objects, each of which lists an algorithm. - NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
Errors
There are no errors described for this operation.
ListAliases
$result = $client->listAliases
([/* ... */]); $promise = $client->listAliasesAsync
([/* ... */]);
Lists the aliases of a specified image or image version.
Parameter Syntax
$result = $client->listAliases([ 'Alias' => '<string>', 'ImageName' => '<string>', // REQUIRED 'MaxResults' => <integer>, 'NextToken' => '<string>', 'Version' => <integer>, ]);
Parameter Details
Members
- Alias
-
- Type: string
The alias of the image version.
- ImageName
-
- Required: Yes
- Type: string
The name of the image.
- MaxResults
-
- Type: int
The maximum number of aliases to return.
- NextToken
-
- Type: string
If the previous call to
ListAliases
didn't return the full set of aliases, the call returns a token for retrieving the next set of aliases. - Version
-
- Type: int
The version of the image. If image version is not specified, the aliases of all versions of the image are listed.
Result Syntax
[ 'NextToken' => '<string>', 'SageMakerImageVersionAliases' => ['<string>', ...], ]
Result Details
Members
- NextToken
-
- Type: string
A token for getting the next set of aliases, if more aliases exist.
- SageMakerImageVersionAliases
-
- Type: Array of strings
A list of SageMaker image version aliases.
Errors
- ResourceNotFound:
Resource being access is not found.
ListAppImageConfigs
$result = $client->listAppImageConfigs
([/* ... */]); $promise = $client->listAppImageConfigsAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->listAppImageConfigs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'ModifiedTimeAfter' => <integer || string || DateTime>, 'ModifiedTimeBefore' => <integer || string || DateTime>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'CreationTime|LastModifiedTime|Name', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only AppImageConfigs created on or after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only AppImageConfigs created on or before the specified time.
- MaxResults
-
- Type: int
The total number of items to return in the response. If the total number of items available is more than the value specified, a
NextToken
is provided in the response. To resume pagination, provide theNextToken
value in the as part of a subsequent call. The default value is 10. - ModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only AppImageConfigs modified on or after the specified time.
- ModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only AppImageConfigs modified on or before the specified time.
- NameContains
-
- Type: string
A filter that returns only AppImageConfigs whose name contains the specified string.
- NextToken
-
- Type: string
If the previous call to
ListImages
didn't return the full set of AppImageConfigs, the call returns a token for getting the next set of AppImageConfigs. - SortBy
-
- Type: string
The property used to sort results. The default value is
CreationTime
. - SortOrder
-
- Type: string
The sort order. The default value is
Descending
.
Result Syntax
[ 'AppImageConfigs' => [ [ 'AppImageConfigArn' => '<string>', 'AppImageConfigName' => '<string>', 'CodeEditorAppImageConfig' => [ 'ContainerConfig' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ContainerEnvironmentVariables' => ['<string>', ...], ], 'FileSystemConfig' => [ 'DefaultGid' => <integer>, 'DefaultUid' => <integer>, 'MountPath' => '<string>', ], ], 'CreationTime' => <DateTime>, 'JupyterLabAppImageConfig' => [ 'ContainerConfig' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ContainerEnvironmentVariables' => ['<string>', ...], ], 'FileSystemConfig' => [ 'DefaultGid' => <integer>, 'DefaultUid' => <integer>, 'MountPath' => '<string>', ], ], 'KernelGatewayImageConfig' => [ 'FileSystemConfig' => [ 'DefaultGid' => <integer>, 'DefaultUid' => <integer>, 'MountPath' => '<string>', ], 'KernelSpecs' => [ [ 'DisplayName' => '<string>', 'Name' => '<string>', ], // ... ], ], 'LastModifiedTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- AppImageConfigs
-
- Type: Array of AppImageConfigDetails structures
A list of AppImageConfigs and their properties.
- NextToken
-
- Type: string
A token for getting the next set of AppImageConfigs, if there are any.
Errors
There are no errors described for this operation.
ListApps
$result = $client->listApps
([/* ... */]); $promise = $client->listAppsAsync
([/* ... */]);
Lists apps.
Parameter Syntax
$result = $client->listApps([ 'DomainIdEquals' => '<string>', 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'CreationTime', 'SortOrder' => 'Ascending|Descending', 'SpaceNameEquals' => '<string>', 'UserProfileNameEquals' => '<string>', ]);
Parameter Details
Members
- DomainIdEquals
-
- Type: string
A parameter to search for the domain ID.
- MaxResults
-
- Type: int
This parameter defines the maximum number of results that can be return in a single response. The
MaxResults
parameter is an upper bound, not a target. If there are more results available than the value specified, aNextToken
is provided in the response. TheNextToken
indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value forMaxResults
is 10. - NextToken
-
- Type: string
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
- SortBy
-
- Type: string
The parameter by which to sort the results. The default is CreationTime.
- SortOrder
-
- Type: string
The sort order for the results. The default is Ascending.
- SpaceNameEquals
-
- Type: string
A parameter to search by space name. If
UserProfileNameEquals
is set, then this value cannot be set. - UserProfileNameEquals
-
- Type: string
A parameter to search by user profile name. If
SpaceNameEquals
is set, then this value cannot be set.
Result Syntax
[ 'Apps' => [ [ 'AppName' => '<string>', 'AppType' => 'JupyterServer|KernelGateway|DetailedProfiler|TensorBoard|CodeEditor|JupyterLab|RStudioServerPro|RSessionGateway|Canvas', 'CreationTime' => <DateTime>, 'DomainId' => '<string>', 'ResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'SpaceName' => '<string>', 'Status' => 'Deleted|Deleting|Failed|InService|Pending', 'UserProfileName' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- Apps
-
- Type: Array of AppDetails structures
The list of apps.
- NextToken
-
- Type: string
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
Errors
There are no errors described for this operation.
ListArtifacts
$result = $client->listArtifacts
([/* ... */]); $promise = $client->listArtifactsAsync
([/* ... */]);
Lists the artifacts in your account and their properties.
Parameter Syntax
$result = $client->listArtifacts([ 'ArtifactType' => '<string>', 'CreatedAfter' => <integer || string || DateTime>, 'CreatedBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'CreationTime', 'SortOrder' => 'Ascending|Descending', 'SourceUri' => '<string>', ]);
Parameter Details
Members
- ArtifactType
-
- Type: string
A filter that returns only artifacts of the specified type.
- CreatedAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only artifacts created on or after the specified time.
- CreatedBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only artifacts created on or before the specified time.
- MaxResults
-
- Type: int
The maximum number of artifacts to return in the response. The default value is 10.
- NextToken
-
- Type: string
If the previous call to
ListArtifacts
didn't return the full set of artifacts, the call returns a token for getting the next set of artifacts. - SortBy
-
- Type: string
The property used to sort results. The default value is
CreationTime
. - SortOrder
-
- Type: string
The sort order. The default value is
Descending
. - SourceUri
-
- Type: string
A filter that returns only artifacts with the specified source URI.
Result Syntax
[ 'ArtifactSummaries' => [ [ 'ArtifactArn' => '<string>', 'ArtifactName' => '<string>', 'ArtifactType' => '<string>', 'CreationTime' => <DateTime>, 'LastModifiedTime' => <DateTime>, 'Source' => [ 'SourceTypes' => [ [ 'SourceIdType' => 'MD5Hash|S3ETag|S3Version|Custom', 'Value' => '<string>', ], // ... ], 'SourceUri' => '<string>', ], ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- ArtifactSummaries
-
- Type: Array of ArtifactSummary structures
A list of artifacts and their properties.
- NextToken
-
- Type: string
A token for getting the next set of artifacts, if there are any.
Errors
- ResourceNotFound:
Resource being access is not found.
ListAssociations
$result = $client->listAssociations
([/* ... */]); $promise = $client->listAssociationsAsync
([/* ... */]);
Lists the associations in your account and their properties.
Parameter Syntax
$result = $client->listAssociations([ 'AssociationType' => 'ContributedTo|AssociatedWith|DerivedFrom|Produced|SameAs', 'CreatedAfter' => <integer || string || DateTime>, 'CreatedBefore' => <integer || string || DateTime>, 'DestinationArn' => '<string>', 'DestinationType' => '<string>', 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'SourceArn|DestinationArn|SourceType|DestinationType|CreationTime', 'SortOrder' => 'Ascending|Descending', 'SourceArn' => '<string>', 'SourceType' => '<string>', ]);
Parameter Details
Members
- AssociationType
-
- Type: string
A filter that returns only associations of the specified type.
- CreatedAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only associations created on or after the specified time.
- CreatedBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only associations created on or before the specified time.
- DestinationArn
-
- Type: string
A filter that returns only associations with the specified destination Amazon Resource Name (ARN).
- DestinationType
-
- Type: string
A filter that returns only associations with the specified destination type.
- MaxResults
-
- Type: int
The maximum number of associations to return in the response. The default value is 10.
- NextToken
-
- Type: string
If the previous call to
ListAssociations
didn't return the full set of associations, the call returns a token for getting the next set of associations. - SortBy
-
- Type: string
The property used to sort results. The default value is
CreationTime
. - SortOrder
-
- Type: string
The sort order. The default value is
Descending
. - SourceArn
-
- Type: string
A filter that returns only associations with the specified source ARN.
- SourceType
-
- Type: string
A filter that returns only associations with the specified source type.
Result Syntax
[ 'AssociationSummaries' => [ [ 'AssociationType' => 'ContributedTo|AssociatedWith|DerivedFrom|Produced|SameAs', 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'DestinationArn' => '<string>', 'DestinationName' => '<string>', 'DestinationType' => '<string>', 'SourceArn' => '<string>', 'SourceName' => '<string>', 'SourceType' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- AssociationSummaries
-
- Type: Array of AssociationSummary structures
A list of associations and their properties.
- NextToken
-
- Type: string
A token for getting the next set of associations, if there are any.
Errors
- ResourceNotFound:
Resource being access is not found.
ListAutoMLJobs
$result = $client->listAutoMLJobs
([/* ... */]); $promise = $client->listAutoMLJobsAsync
([/* ... */]);
Request a list of jobs.
Parameter Syntax
$result = $client->listAutoMLJobs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'Completed|InProgress|Failed|Stopped|Stopping', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Request a list of jobs, using a filter for time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Request a list of jobs, using a filter for time.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Request a list of jobs, using a filter for time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Request a list of jobs, using a filter for time.
- MaxResults
-
- Type: int
Request a list of jobs up to a specified limit.
- NameContains
-
- Type: string
Request a list of jobs, using a search filter for name.
- NextToken
-
- Type: string
If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
- SortBy
-
- Type: string
The parameter by which to sort the results. The default is
Name
. - SortOrder
-
- Type: string
The sort order for the results. The default is
Descending
. - StatusEquals
-
- Type: string
Request a list of jobs, using a filter for status.
Result Syntax
[ 'AutoMLJobSummaries' => [ [ 'AutoMLJobArn' => '<string>', 'AutoMLJobName' => '<string>', 'AutoMLJobSecondaryStatus' => 'Starting|MaxCandidatesReached|Failed|Stopped|MaxAutoMLJobRuntimeReached|Stopping|CandidateDefinitionsGenerated|Completed|ExplainabilityError|DeployingModel|ModelDeploymentError|GeneratingModelInsightsReport|ModelInsightsError|AnalyzingData|FeatureEngineering|ModelTuning|GeneratingExplainabilityReport|TrainingModels|PreTraining', 'AutoMLJobStatus' => 'Completed|InProgress|Failed|Stopped|Stopping', 'CreationTime' => <DateTime>, 'EndTime' => <DateTime>, 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'PartialFailureReasons' => [ [ 'PartialFailureMessage' => '<string>', ], // ... ], ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- AutoMLJobSummaries
-
- Required: Yes
- Type: Array of AutoMLJobSummary structures
Returns a summary list of jobs.
- NextToken
-
- Type: string
If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
Errors
There are no errors described for this operation.
ListCandidatesForAutoMLJob
$result = $client->listCandidatesForAutoMLJob
([/* ... */]); $promise = $client->listCandidatesForAutoMLJobAsync
([/* ... */]);
List the candidates created for the job.
Parameter Syntax
$result = $client->listCandidatesForAutoMLJob([ 'AutoMLJobName' => '<string>', // REQUIRED 'CandidateNameEquals' => '<string>', 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'CreationTime|Status|FinalObjectiveMetricValue', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'Completed|InProgress|Failed|Stopped|Stopping', ]);
Parameter Details
Members
- AutoMLJobName
-
- Required: Yes
- Type: string
List the candidates created for the job by providing the job's name.
- CandidateNameEquals
-
- Type: string
List the candidates for the job and filter by candidate name.
- MaxResults
-
- Type: int
List the job's candidates up to a specified limit.
- NextToken
-
- Type: string
If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
- SortBy
-
- Type: string
The parameter by which to sort the results. The default is
Descending
. - SortOrder
-
- Type: string
The sort order for the results. The default is
Ascending
. - StatusEquals
-
- Type: string
List the candidates for the job and filter by status.
Result Syntax
[ 'Candidates' => [ [ 'CandidateName' => '<string>', 'CandidateProperties' => [ 'CandidateArtifactLocations' => [ 'BacktestResults' => '<string>', 'Explainability' => '<string>', 'ModelInsights' => '<string>', ], 'CandidateMetrics' => [ [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', 'Set' => 'Train|Validation|Test', 'StandardMetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|MAE|R2|BalancedAccuracy|Precision|PrecisionMacro|Recall|RecallMacro|LogLoss|InferenceLatency|MAPE|MASE|WAPE|AverageWeightedQuantileLoss|Rouge1|Rouge2|RougeL|RougeLSum|Perplexity|ValidationLoss|TrainingLoss', 'Value' => <float>, ], // ... ], ], 'CandidateStatus' => 'Completed|InProgress|Failed|Stopped|Stopping', 'CandidateSteps' => [ [ 'CandidateStepArn' => '<string>', 'CandidateStepName' => '<string>', 'CandidateStepType' => 'AWS::SageMaker::TrainingJob|AWS::SageMaker::TransformJob|AWS::SageMaker::ProcessingJob', ], // ... ], 'CreationTime' => <DateTime>, 'EndTime' => <DateTime>, 'FailureReason' => '<string>', 'FinalAutoMLJobObjectiveMetric' => [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', 'StandardMetricName' => 'Accuracy|MSE|F1|F1macro|AUC|RMSE|BalancedAccuracy|R2|Recall|RecallMacro|Precision|PrecisionMacro|MAE|MAPE|MASE|WAPE|AverageWeightedQuantileLoss', 'Type' => 'Maximize|Minimize', 'Value' => <float>, ], 'InferenceContainerDefinitions' => [ '<AutoMLProcessingUnit>' => [ [ 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ModelDataUrl' => '<string>', ], // ... ], // ... ], 'InferenceContainers' => [ [ 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ModelDataUrl' => '<string>', ], // ... ], 'LastModifiedTime' => <DateTime>, 'ObjectiveStatus' => 'Succeeded|Pending|Failed', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- Candidates
-
- Required: Yes
- Type: Array of AutoMLCandidate structures
Summaries about the
AutoMLCandidates
. - NextToken
-
- Type: string
If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
Errors
- ResourceNotFound:
Resource being access is not found.
ListClusterNodes
$result = $client->listClusterNodes
([/* ... */]); $promise = $client->listClusterNodesAsync
([/* ... */]);
Retrieves the list of instances (also called nodes interchangeably) in a SageMaker HyperPod cluster.
Parameter Syntax
$result = $client->listClusterNodes([ 'ClusterName' => '<string>', // REQUIRED 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'InstanceGroupNameContains' => '<string>', 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'CREATION_TIME|NAME', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- ClusterName
-
- Required: Yes
- Type: string
The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster in which you want to retrieve the list of nodes.
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns nodes in a SageMaker HyperPod cluster created after the specified time. Timestamps are formatted according to the ISO 8601 standard.
Acceptable formats include:
-
YYYY-MM-DDThh:mm:ss.sssTZD
(UTC), for example,2014-10-01T20:30:00.000Z
-
YYYY-MM-DDThh:mm:ss.sssTZD
(with offset), for example,2014-10-01T12:30:00.000-08:00
-
YYYY-MM-DD
, for example,2014-10-01
-
Unix time in seconds, for example,
1412195400
. This is also referred to as Unix Epoch time and represents the number of seconds since midnight, January 1, 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The acceptable formats are the same as the timestamp formats for
CreationTimeAfter
. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide. - InstanceGroupNameContains
-
- Type: string
A filter that returns the instance groups whose name contain a specified string.
- MaxResults
-
- Type: int
The maximum number of nodes to return in the response.
- NextToken
-
- Type: string
If the result of the previous
ListClusterNodes
request was truncated, the response includes aNextToken
. To retrieve the next set of cluster nodes, use the token in the next request. - SortBy
-
- Type: string
The field by which to sort results. The default value is
CREATION_TIME
. - SortOrder
-
- Type: string
The sort order for results. The default value is
Ascending
.
Result Syntax
[ 'ClusterNodeSummaries' => [ [ 'InstanceGroupName' => '<string>', 'InstanceId' => '<string>', 'InstanceStatus' => [ 'Message' => '<string>', 'Status' => 'Running|Failure|Pending|ShuttingDown|SystemUpdating', ], 'InstanceType' => 'ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.c5n.large|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge', 'LaunchTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- ClusterNodeSummaries
-
- Required: Yes
- Type: Array of ClusterNodeSummary structures
The summaries of listed instances in a SageMaker HyperPod cluster
- NextToken
-
- Required: Yes
- Type: string
The next token specified for listing instances in a SageMaker HyperPod cluster.
Errors
- ResourceNotFound:
Resource being access is not found.
ListClusters
$result = $client->listClusters
([/* ... */]); $promise = $client->listClustersAsync
([/* ... */]);
Retrieves the list of SageMaker HyperPod clusters.
Parameter Syntax
$result = $client->listClusters([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'CREATION_TIME|NAME', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Set a start time for the time range during which you want to list SageMaker HyperPod clusters. Timestamps are formatted according to the ISO 8601 standard.
Acceptable formats include:
-
YYYY-MM-DDThh:mm:ss.sssTZD
(UTC), for example,2014-10-01T20:30:00.000Z
-
YYYY-MM-DDThh:mm:ss.sssTZD
(with offset), for example,2014-10-01T12:30:00.000-08:00
-
YYYY-MM-DD
, for example,2014-10-01
-
Unix time in seconds, for example,
1412195400
. This is also referred to as Unix Epoch time and represents the number of seconds since midnight, January 1, 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Set an end time for the time range during which you want to list SageMaker HyperPod clusters. A filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The acceptable formats are the same as the timestamp formats for
CreationTimeAfter
. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide. - MaxResults
-
- Type: int
Set the maximum number of SageMaker HyperPod clusters to list.
- NameContains
-
- Type: string
Set the maximum number of instances to print in the list.
- NextToken
-
- Type: string
Set the next token to retrieve the list of SageMaker HyperPod clusters.
- SortBy
-
- Type: string
The field by which to sort results. The default value is
CREATION_TIME
. - SortOrder
-
- Type: string
The sort order for results. The default value is
Ascending
.
Result Syntax
[ 'ClusterSummaries' => [ [ 'ClusterArn' => '<string>', 'ClusterName' => '<string>', 'ClusterStatus' => 'Creating|Deleting|Failed|InService|RollingBack|SystemUpdating|Updating', 'CreationTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- ClusterSummaries
-
- Required: Yes
- Type: Array of ClusterSummary structures
The summaries of listed SageMaker HyperPod clusters.
- NextToken
-
- Required: Yes
- Type: string
If the result of the previous
ListClusters
request was truncated, the response includes aNextToken
. To retrieve the next set of clusters, use the token in the next request.
Errors
There are no errors described for this operation.
ListCodeRepositories
$result = $client->listCodeRepositories
([/* ... */]); $promise = $client->listCodeRepositoriesAsync
([/* ... */]);
Gets a list of the Git repositories in your account.
Parameter Syntax
$result = $client->listCodeRepositories([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|LastModifiedTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only Git repositories that were created after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only Git repositories that were created before the specified time.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only Git repositories that were last modified after the specified time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only Git repositories that were last modified before the specified time.
- MaxResults
-
- Type: int
The maximum number of Git repositories to return in the response.
- NameContains
-
- Type: string
A string in the Git repositories name. This filter returns only repositories whose name contains the specified string.
- NextToken
-
- Type: string
If the result of a
ListCodeRepositoriesOutput
request was truncated, the response includes aNextToken
. To get the next set of Git repositories, use the token in the next request. - SortBy
-
- Type: string
The field to sort results by. The default is
Name
. - SortOrder
-
- Type: string
The sort order for results. The default is
Ascending
.
Result Syntax
[ 'CodeRepositorySummaryList' => [ [ 'CodeRepositoryArn' => '<string>', 'CodeRepositoryName' => '<string>', 'CreationTime' => <DateTime>, 'GitConfig' => [ 'Branch' => '<string>', 'RepositoryUrl' => '<string>', 'SecretArn' => '<string>', ], 'LastModifiedTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- CodeRepositorySummaryList
-
- Required: Yes
- Type: Array of CodeRepositorySummary structures
Gets a list of summaries of the Git repositories. Each summary specifies the following values for the repository:
-
Name
-
Amazon Resource Name (ARN)
-
Creation time
-
Last modified time
-
Configuration information, including the URL location of the repository and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
- NextToken
-
- Type: string
If the result of a
ListCodeRepositoriesOutput
request was truncated, the response includes aNextToken
. To get the next set of Git repositories, use the token in the next request.
Errors
There are no errors described for this operation.
ListCompilationJobs
$result = $client->listCompilationJobs
([/* ... */]); $promise = $client->listCompilationJobsAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->listCompilationJobs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'INPROGRESS|COMPLETED|FAILED|STARTING|STOPPING|STOPPED', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns the model compilation jobs that were created after a specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns the model compilation jobs that were created before a specified time.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns the model compilation jobs that were modified after a specified time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns the model compilation jobs that were modified before a specified time.
- MaxResults
-
- Type: int
The maximum number of model compilation jobs to return in the response.
- NameContains
-
- Type: string
A filter that returns the model compilation jobs whose name contains a specified string.
- NextToken
-
- Type: string
If the result of the previous
ListCompilationJobs
request was truncated, the response includes aNextToken
. To retrieve the next set of model compilation jobs, use the token in the next request. - SortBy
-
- Type: string
The field by which to sort results. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results. The default is
Ascending
. - StatusEquals
-
- Type: string
A filter that retrieves model compilation jobs with a specific
CompilationJobStatus
status.
Result Syntax
[ 'CompilationJobSummaries' => [ [ 'CompilationEndTime' => <DateTime>, 'CompilationJobArn' => '<string>', 'CompilationJobName' => '<string>', 'CompilationJobStatus' => 'INPROGRESS|COMPLETED|FAILED|STARTING|STOPPING|STOPPED', 'CompilationStartTime' => <DateTime>, 'CompilationTargetDevice' => 'lambda|ml_m4|ml_m5|ml_m6g|ml_c4|ml_c5|ml_c6g|ml_p2|ml_p3|ml_g4dn|ml_inf1|ml_inf2|ml_trn1|ml_eia2|jetson_tx1|jetson_tx2|jetson_nano|jetson_xavier|rasp3b|rasp4b|imx8qm|deeplens|rk3399|rk3288|aisage|sbe_c|qcs605|qcs603|sitara_am57x|amba_cv2|amba_cv22|amba_cv25|x86_win32|x86_win64|coreml|jacinto_tda4vm|imx8mplus', 'CompilationTargetPlatformAccelerator' => 'INTEL_GRAPHICS|MALI|NVIDIA|NNA', 'CompilationTargetPlatformArch' => 'X86_64|X86|ARM64|ARM_EABI|ARM_EABIHF', 'CompilationTargetPlatformOs' => 'ANDROID|LINUX', 'CreationTime' => <DateTime>, 'LastModifiedTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- CompilationJobSummaries
-
- Required: Yes
- Type: Array of CompilationJobSummary structures
An array of CompilationJobSummary objects, each describing a model compilation job.
- NextToken
-
- Type: string
If the response is truncated, Amazon SageMaker returns this
NextToken
. To retrieve the next set of model compilation jobs, use this token in the next request.
Errors
There are no errors described for this operation.
ListContexts
$result = $client->listContexts
([/* ... */]); $promise = $client->listContextsAsync
([/* ... */]);
Lists the contexts in your account and their properties.
Parameter Syntax
$result = $client->listContexts([ 'ContextType' => '<string>', 'CreatedAfter' => <integer || string || DateTime>, 'CreatedBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', 'SourceUri' => '<string>', ]);
Parameter Details
Members
- ContextType
-
- Type: string
A filter that returns only contexts of the specified type.
- CreatedAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only contexts created on or after the specified time.
- CreatedBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only contexts created on or before the specified time.
- MaxResults
-
- Type: int
The maximum number of contexts to return in the response. The default value is 10.
- NextToken
-
- Type: string
If the previous call to
ListContexts
didn't return the full set of contexts, the call returns a token for getting the next set of contexts. - SortBy
-
- Type: string
The property used to sort results. The default value is
CreationTime
. - SortOrder
-
- Type: string
The sort order. The default value is
Descending
. - SourceUri
-
- Type: string
A filter that returns only contexts with the specified source URI.
Result Syntax
[ 'ContextSummaries' => [ [ 'ContextArn' => '<string>', 'ContextName' => '<string>', 'ContextType' => '<string>', 'CreationTime' => <DateTime>, 'LastModifiedTime' => <DateTime>, 'Source' => [ 'SourceId' => '<string>', 'SourceType' => '<string>', 'SourceUri' => '<string>', ], ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- ContextSummaries
-
- Type: Array of ContextSummary structures
A list of contexts and their properties.
- NextToken
-
- Type: string
A token for getting the next set of contexts, if there are any.
Errors
- ResourceNotFound:
Resource being access is not found.
ListDataQualityJobDefinitions
$result = $client->listDataQualityJobDefinitions
([/* ... */]); $promise = $client->listDataQualityJobDefinitionsAsync
([/* ... */]);
Lists the data quality job definitions in your account.
Parameter Syntax
$result = $client->listDataQualityJobDefinitions([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'EndpointName' => '<string>', 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only data quality monitoring job definitions created after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only data quality monitoring job definitions created before the specified time.
- EndpointName
-
- Type: string
A filter that lists the data quality job definitions associated with the specified endpoint.
- MaxResults
-
- Type: int
The maximum number of data quality monitoring job definitions to return in the response.
- NameContains
-
- Type: string
A string in the data quality monitoring job definition name. This filter returns only data quality monitoring job definitions whose name contains the specified string.
- NextToken
-
- Type: string
If the result of the previous
ListDataQualityJobDefinitions
request was truncated, the response includes aNextToken
. To retrieve the next set of transform jobs, use the token in the next request.> - SortBy
-
- Type: string
The field to sort results by. The default is
CreationTime
. - SortOrder
-
- Type: string
Whether to sort the results in
Ascending
orDescending
order. The default isDescending
.
Result Syntax
[ 'JobDefinitionSummaries' => [ [ 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'MonitoringJobDefinitionArn' => '<string>', 'MonitoringJobDefinitionName' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- JobDefinitionSummaries
-
- Required: Yes
- Type: Array of MonitoringJobDefinitionSummary structures
A list of data quality monitoring job definitions.
- NextToken
-
- Type: string
If the result of the previous
ListDataQualityJobDefinitions
request was truncated, the response includes aNextToken
. To retrieve the next set of data quality monitoring job definitions, use the token in the next request.
Errors
There are no errors described for this operation.
ListDeviceFleets
$result = $client->listDeviceFleets
([/* ... */]); $promise = $client->listDeviceFleetsAsync
([/* ... */]);
Returns a list of devices in the fleet.
Parameter Syntax
$result = $client->listDeviceFleets([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'NAME|CREATION_TIME|LAST_MODIFIED_TIME', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filter fleets where packaging job was created after specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filter fleets where the edge packaging job was created before specified time.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Select fleets where the job was updated after X
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Select fleets where the job was updated before X
- MaxResults
-
- Type: int
The maximum number of results to select.
- NameContains
-
- Type: string
Filter for fleets containing this name in their fleet device name.
- NextToken
-
- Type: string
The response from the last list when returning a list large enough to need tokening.
- SortBy
-
- Type: string
The column to sort by.
- SortOrder
-
- Type: string
What direction to sort in.
Result Syntax
[ 'DeviceFleetSummaries' => [ [ 'CreationTime' => <DateTime>, 'DeviceFleetArn' => '<string>', 'DeviceFleetName' => '<string>', 'LastModifiedTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- DeviceFleetSummaries
-
- Required: Yes
- Type: Array of DeviceFleetSummary structures
Summary of the device fleet.
- NextToken
-
- Type: string
The response from the last list when returning a list large enough to need tokening.
Errors
There are no errors described for this operation.
ListDevices
$result = $client->listDevices
([/* ... */]); $promise = $client->listDevicesAsync
([/* ... */]);
A list of devices.
Parameter Syntax
$result = $client->listDevices([ 'DeviceFleetName' => '<string>', 'LatestHeartbeatAfter' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'ModelName' => '<string>', 'NextToken' => '<string>', ]);
Parameter Details
Members
- DeviceFleetName
-
- Type: string
Filter for fleets containing this name in their device fleet name.
- LatestHeartbeatAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Select fleets where the job was updated after X
- MaxResults
-
- Type: int
Maximum number of results to select.
- ModelName
-
- Type: string
A filter that searches devices that contains this name in any of their models.
- NextToken
-
- Type: string
The response from the last list when returning a list large enough to need tokening.
Result Syntax
[ 'DeviceSummaries' => [ [ 'AgentVersion' => '<string>', 'Description' => '<string>', 'DeviceArn' => '<string>', 'DeviceFleetName' => '<string>', 'DeviceName' => '<string>', 'IotThingName' => '<string>', 'LatestHeartbeat' => <DateTime>, 'Models' => [ [ 'ModelName' => '<string>', 'ModelVersion' => '<string>', ], // ... ], 'RegistrationTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- DeviceSummaries
-
- Required: Yes
- Type: Array of DeviceSummary structures
Summary of devices.
- NextToken
-
- Type: string
The response from the last list when returning a list large enough to need tokening.
Errors
There are no errors described for this operation.
ListDomains
$result = $client->listDomains
([/* ... */]); $promise = $client->listDomainsAsync
([/* ... */]);
Lists the domains.
Parameter Syntax
$result = $client->listDomains([ 'MaxResults' => <integer>, 'NextToken' => '<string>', ]);
Parameter Details
Members
- MaxResults
-
- Type: int
This parameter defines the maximum number of results that can be return in a single response. The
MaxResults
parameter is an upper bound, not a target. If there are more results available than the value specified, aNextToken
is provided in the response. TheNextToken
indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value forMaxResults
is 10. - NextToken
-
- Type: string
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
Result Syntax
[ 'Domains' => [ [ 'CreationTime' => <DateTime>, 'DomainArn' => '<string>', 'DomainId' => '<string>', 'DomainName' => '<string>', 'LastModifiedTime' => <DateTime>, 'Status' => 'Deleting|Failed|InService|Pending|Updating|Update_Failed|Delete_Failed', 'Url' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- Domains
-
- Type: Array of DomainDetails structures
The list of domains.
- NextToken
-
- Type: string
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
Errors
There are no errors described for this operation.
ListEdgeDeploymentPlans
$result = $client->listEdgeDeploymentPlans
([/* ... */]); $promise = $client->listEdgeDeploymentPlansAsync
([/* ... */]);
Lists all edge deployment plans.
Parameter Syntax
$result = $client->listEdgeDeploymentPlans([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'DeviceFleetNameContains' => '<string>', 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'NAME|DEVICE_FLEET_NAME|CREATION_TIME|LAST_MODIFIED_TIME', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Selects edge deployment plans created after this time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Selects edge deployment plans created before this time.
- DeviceFleetNameContains
-
- Type: string
Selects edge deployment plans with a device fleet name containing this name.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Selects edge deployment plans that were last updated after this time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Selects edge deployment plans that were last updated before this time.
- MaxResults
-
- Type: int
The maximum number of results to select (50 by default).
- NameContains
-
- Type: string
Selects edge deployment plans with names containing this name.
- NextToken
-
- Type: string
The response from the last list when returning a list large enough to need tokening.
- SortBy
-
- Type: string
The column by which to sort the edge deployment plans. Can be one of
NAME
,DEVICEFLEETNAME
,CREATIONTIME
,LASTMODIFIEDTIME
. - SortOrder
-
- Type: string
The direction of the sorting (ascending or descending).
Result Syntax
[ 'EdgeDeploymentPlanSummaries' => [ [ 'CreationTime' => <DateTime>, 'DeviceFleetName' => '<string>', 'EdgeDeploymentFailed' => <integer>, 'EdgeDeploymentPending' => <integer>, 'EdgeDeploymentPlanArn' => '<string>', 'EdgeDeploymentPlanName' => '<string>', 'EdgeDeploymentSuccess' => <integer>, 'LastModifiedTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- EdgeDeploymentPlanSummaries
-
- Required: Yes
- Type: Array of EdgeDeploymentPlanSummary structures
List of summaries of edge deployment plans.
- NextToken
-
- Type: string
The token to use when calling the next page of results.
Errors
There are no errors described for this operation.
ListEdgePackagingJobs
$result = $client->listEdgePackagingJobs
([/* ... */]); $promise = $client->listEdgePackagingJobsAsync
([/* ... */]);
Returns a list of edge packaging jobs.
Parameter Syntax
$result = $client->listEdgePackagingJobs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'ModelNameContains' => '<string>', 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'NAME|MODEL_NAME|CREATION_TIME|LAST_MODIFIED_TIME|STATUS', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'STARTING|INPROGRESS|COMPLETED|FAILED|STOPPING|STOPPED', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Select jobs where the job was created after specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Select jobs where the job was created before specified time.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Select jobs where the job was updated after specified time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Select jobs where the job was updated before specified time.
- MaxResults
-
- Type: int
Maximum number of results to select.
- ModelNameContains
-
- Type: string
Filter for jobs where the model name contains this string.
- NameContains
-
- Type: string
Filter for jobs containing this name in their packaging job name.
- NextToken
-
- Type: string
The response from the last list when returning a list large enough to need tokening.
- SortBy
-
- Type: string
Use to specify what column to sort by.
- SortOrder
-
- Type: string
What direction to sort by.
- StatusEquals
-
- Type: string
The job status to filter for.
Result Syntax
[ 'EdgePackagingJobSummaries' => [ [ 'CompilationJobName' => '<string>', 'CreationTime' => <DateTime>, 'EdgePackagingJobArn' => '<string>', 'EdgePackagingJobName' => '<string>', 'EdgePackagingJobStatus' => 'STARTING|INPROGRESS|COMPLETED|FAILED|STOPPING|STOPPED', 'LastModifiedTime' => <DateTime>, 'ModelName' => '<string>', 'ModelVersion' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- EdgePackagingJobSummaries
-
- Required: Yes
- Type: Array of EdgePackagingJobSummary structures
Summaries of edge packaging jobs.
- NextToken
-
- Type: string
Token to use when calling the next page of results.
Errors
There are no errors described for this operation.
ListEndpointConfigs
$result = $client->listEndpointConfigs
([/* ... */]); $promise = $client->listEndpointConfigsAsync
([/* ... */]);
Lists endpoint configurations.
Parameter Syntax
$result = $client->listEndpointConfigs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only endpoint configurations with a creation time greater than or equal to the specified time (timestamp).
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only endpoint configurations created before the specified time (timestamp).
- MaxResults
-
- Type: int
The maximum number of training jobs to return in the response.
- NameContains
-
- Type: string
A string in the endpoint configuration name. This filter returns only endpoint configurations whose name contains the specified string.
- NextToken
-
- Type: string
If the result of the previous
ListEndpointConfig
request was truncated, the response includes aNextToken
. To retrieve the next set of endpoint configurations, use the token in the next request. - SortBy
-
- Type: string
The field to sort results by. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results. The default is
Descending
.
Result Syntax
[ 'EndpointConfigs' => [ [ 'CreationTime' => <DateTime>, 'EndpointConfigArn' => '<string>', 'EndpointConfigName' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- EndpointConfigs
-
- Required: Yes
- Type: Array of EndpointConfigSummary structures
An array of endpoint configurations.
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of endpoint configurations, use it in the subsequent request
Errors
There are no errors described for this operation.
ListEndpoints
$result = $client->listEndpoints
([/* ... */]); $promise = $client->listEndpointsAsync
([/* ... */]);
Lists endpoints.
Parameter Syntax
$result = $client->listEndpoints([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'OutOfService|Creating|Updating|SystemUpdating|RollingBack|InService|Deleting|Failed|UpdateRollbackFailed', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only endpoints with a creation time greater than or equal to the specified time (timestamp).
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only endpoints that were created before the specified time (timestamp).
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only endpoints that were modified after the specified timestamp.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only endpoints that were modified before the specified timestamp.
- MaxResults
-
- Type: int
The maximum number of endpoints to return in the response. This value defaults to 10.
- NameContains
-
- Type: string
A string in endpoint names. This filter returns only endpoints whose name contains the specified string.
- NextToken
-
- Type: string
If the result of a
ListEndpoints
request was truncated, the response includes aNextToken
. To retrieve the next set of endpoints, use the token in the next request. - SortBy
-
- Type: string
Sorts the list of results. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results. The default is
Descending
. - StatusEquals
-
- Type: string
A filter that returns only endpoints with the specified status.
Result Syntax
[ 'Endpoints' => [ [ 'CreationTime' => <DateTime>, 'EndpointArn' => '<string>', 'EndpointName' => '<string>', 'EndpointStatus' => 'OutOfService|Creating|Updating|SystemUpdating|RollingBack|InService|Deleting|Failed|UpdateRollbackFailed', 'LastModifiedTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- Endpoints
-
- Required: Yes
- Type: Array of EndpointSummary structures
An array or endpoint objects.
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
Errors
There are no errors described for this operation.
ListExperiments
$result = $client->listExperiments
([/* ... */]); $promise = $client->listExperimentsAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->listExperiments([ 'CreatedAfter' => <integer || string || DateTime>, 'CreatedBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreatedAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only experiments created after the specified time.
- CreatedBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only experiments created before the specified time.
- MaxResults
-
- Type: int
The maximum number of experiments to return in the response. The default value is 10.
- NextToken
-
- Type: string
If the previous call to
ListExperiments
didn't return the full set of experiments, the call returns a token for getting the next set of experiments. - SortBy
-
- Type: string
The property used to sort results. The default value is
CreationTime
. - SortOrder
-
- Type: string
The sort order. The default value is
Descending
.
Result Syntax
[ 'ExperimentSummaries' => [ [ 'CreationTime' => <DateTime>, 'DisplayName' => '<string>', 'ExperimentArn' => '<string>', 'ExperimentName' => '<string>', 'ExperimentSource' => [ 'SourceArn' => '<string>', 'SourceType' => '<string>', ], 'LastModifiedTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- ExperimentSummaries
-
- Type: Array of ExperimentSummary structures
A list of the summaries of your experiments.
- NextToken
-
- Type: string
A token for getting the next set of experiments, if there are any.
Errors
There are no errors described for this operation.
ListFeatureGroups
$result = $client->listFeatureGroups
([/* ... */]); $promise = $client->listFeatureGroupsAsync
([/* ... */]);
List FeatureGroup
s based on given filter and order.
Parameter Syntax
$result = $client->listFeatureGroups([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'FeatureGroupStatusEquals' => 'Creating|Created|CreateFailed|Deleting|DeleteFailed', 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'OfflineStoreStatusEquals' => 'Active|Blocked|Disabled', 'SortBy' => 'Name|FeatureGroupStatus|OfflineStoreStatus|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Use this parameter to search for
FeatureGroups
s created after a specific date and time. - CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Use this parameter to search for
FeatureGroups
s created before a specific date and time. - FeatureGroupStatusEquals
-
- Type: string
A
FeatureGroup
status. Filters byFeatureGroup
status. - MaxResults
-
- Type: int
The maximum number of results returned by
ListFeatureGroups
. - NameContains
-
- Type: string
A string that partially matches one or more
FeatureGroup
s names. FiltersFeatureGroup
s by name. - NextToken
-
- Type: string
A token to resume pagination of
ListFeatureGroups
results. - OfflineStoreStatusEquals
-
- Type: string
An
OfflineStore
status. Filters byOfflineStore
status. - SortBy
-
- Type: string
The value on which the feature group list is sorted.
- SortOrder
-
- Type: string
The order in which feature groups are listed.
Result Syntax
[ 'FeatureGroupSummaries' => [ [ 'CreationTime' => <DateTime>, 'FeatureGroupArn' => '<string>', 'FeatureGroupName' => '<string>', 'FeatureGroupStatus' => 'Creating|Created|CreateFailed|Deleting|DeleteFailed', 'OfflineStoreStatus' => [ 'BlockedReason' => '<string>', 'Status' => 'Active|Blocked|Disabled', ], ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- FeatureGroupSummaries
-
- Required: Yes
- Type: Array of FeatureGroupSummary structures
A summary of feature groups.
- NextToken
-
- Type: string
A token to resume pagination of
ListFeatureGroups
results.
Errors
There are no errors described for this operation.
ListFlowDefinitions
$result = $client->listFlowDefinitions
([/* ... */]); $promise = $client->listFlowDefinitionsAsync
([/* ... */]);
Returns information about the flow definitions in your account.
Parameter Syntax
$result = $client->listFlowDefinitions([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only flow definitions with a creation time greater than or equal to the specified timestamp.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only flow definitions that were created before the specified timestamp.
- MaxResults
-
- Type: int
The total number of items to return. If the total number of available items is more than the value specified in
MaxResults
, then aNextToken
will be provided in the output that you can use to resume pagination. - NextToken
-
- Type: string
A token to resume pagination.
- SortOrder
-
- Type: string
An optional value that specifies whether you want the results sorted in
Ascending
orDescending
order.
Result Syntax
[ 'FlowDefinitionSummaries' => [ [ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'FlowDefinitionArn' => '<string>', 'FlowDefinitionName' => '<string>', 'FlowDefinitionStatus' => 'Initializing|Active|Failed|Deleting', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- FlowDefinitionSummaries
-
- Required: Yes
- Type: Array of FlowDefinitionSummary structures
An array of objects describing the flow definitions.
- NextToken
-
- Type: string
A token to resume pagination.
Errors
There are no errors described for this operation.
ListHubContentVersions
$result = $client->listHubContentVersions
([/* ... */]); $promise = $client->listHubContentVersionsAsync
([/* ... */]);
List hub content versions.
Parameter Syntax
$result = $client->listHubContentVersions([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'HubContentName' => '<string>', // REQUIRED 'HubContentType' => 'Model|Notebook|ModelReference', // REQUIRED 'HubName' => '<string>', // REQUIRED 'MaxResults' => <integer>, 'MaxSchemaVersion' => '<string>', 'MinVersion' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'HubContentName|CreationTime|HubContentStatus', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list hub content versions that were created after the time specified.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list hub content versions that were created before the time specified.
- HubContentName
-
- Required: Yes
- Type: string
The name of the hub content.
- HubContentType
-
- Required: Yes
- Type: string
The type of hub content to list versions of.
- HubName
-
- Required: Yes
- Type: string
The name of the hub to list the content versions of.
- MaxResults
-
- Type: int
The maximum number of hub content versions to list.
- MaxSchemaVersion
-
- Type: string
The upper bound of the hub content schema version.
- MinVersion
-
- Type: string
The lower bound of the hub content versions to list.
- NextToken
-
- Type: string
If the response to a previous
ListHubContentVersions
request was truncated, the response includes aNextToken
. To retrieve the next set of hub content versions, use the token in the next request. - SortBy
-
- Type: string
Sort hub content versions by either name or creation time.
- SortOrder
-
- Type: string
Sort hub content versions by ascending or descending order.
Result Syntax
[ 'HubContentSummaries' => [ [ 'CreationTime' => <DateTime>, 'DocumentSchemaVersion' => '<string>', 'HubContentArn' => '<string>', 'HubContentDescription' => '<string>', 'HubContentDisplayName' => '<string>', 'HubContentName' => '<string>', 'HubContentSearchKeywords' => ['<string>', ...], 'HubContentStatus' => 'Available|Importing|Deleting|ImportFailed|DeleteFailed', 'HubContentType' => 'Model|Notebook|ModelReference', 'HubContentVersion' => '<string>', 'OriginalCreationTime' => <DateTime>, 'SageMakerPublicHubContentArn' => '<string>', 'SupportStatus' => 'Supported|Deprecated', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- HubContentSummaries
-
- Required: Yes
- Type: Array of HubContentInfo structures
The summaries of the listed hub content versions.
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of hub content versions, use it in the subsequent request.
Errors
- ResourceNotFound:
Resource being access is not found.
ListHubContents
$result = $client->listHubContents
([/* ... */]); $promise = $client->listHubContentsAsync
([/* ... */]);
List the contents of a hub.
Parameter Syntax
$result = $client->listHubContents([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'HubContentType' => 'Model|Notebook|ModelReference', // REQUIRED 'HubName' => '<string>', // REQUIRED 'MaxResults' => <integer>, 'MaxSchemaVersion' => '<string>', 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'HubContentName|CreationTime|HubContentStatus', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list hub content that was created after the time specified.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list hub content that was created before the time specified.
- HubContentType
-
- Required: Yes
- Type: string
The type of hub content to list.
- HubName
-
- Required: Yes
- Type: string
The name of the hub to list the contents of.
- MaxResults
-
- Type: int
The maximum amount of hub content to list.
- MaxSchemaVersion
-
- Type: string
The upper bound of the hub content schema verion.
- NameContains
-
- Type: string
Only list hub content if the name contains the specified string.
- NextToken
-
- Type: string
If the response to a previous
ListHubContents
request was truncated, the response includes aNextToken
. To retrieve the next set of hub content, use the token in the next request. - SortBy
-
- Type: string
Sort hub content versions by either name or creation time.
- SortOrder
-
- Type: string
Sort hubs by ascending or descending order.
Result Syntax
[ 'HubContentSummaries' => [ [ 'CreationTime' => <DateTime>, 'DocumentSchemaVersion' => '<string>', 'HubContentArn' => '<string>', 'HubContentDescription' => '<string>', 'HubContentDisplayName' => '<string>', 'HubContentName' => '<string>', 'HubContentSearchKeywords' => ['<string>', ...], 'HubContentStatus' => 'Available|Importing|Deleting|ImportFailed|DeleteFailed', 'HubContentType' => 'Model|Notebook|ModelReference', 'HubContentVersion' => '<string>', 'OriginalCreationTime' => <DateTime>, 'SageMakerPublicHubContentArn' => '<string>', 'SupportStatus' => 'Supported|Deprecated', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- HubContentSummaries
-
- Required: Yes
- Type: Array of HubContentInfo structures
The summaries of the listed hub content.
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of hub content, use it in the subsequent request.
Errors
- ResourceNotFound:
Resource being access is not found.
ListHubs
$result = $client->listHubs
([/* ... */]); $promise = $client->listHubsAsync
([/* ... */]);
List all existing hubs.
Parameter Syntax
$result = $client->listHubs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'HubName|CreationTime|HubStatus|AccountIdOwner', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list hubs that were created after the time specified.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list hubs that were created before the time specified.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list hubs that were last modified after the time specified.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list hubs that were last modified before the time specified.
- MaxResults
-
- Type: int
The maximum number of hubs to list.
- NameContains
-
- Type: string
Only list hubs with names that contain the specified string.
- NextToken
-
- Type: string
If the response to a previous
ListHubs
request was truncated, the response includes aNextToken
. To retrieve the next set of hubs, use the token in the next request. - SortBy
-
- Type: string
Sort hubs by either name or creation time.
- SortOrder
-
- Type: string
Sort hubs by ascending or descending order.
Result Syntax
[ 'HubSummaries' => [ [ 'CreationTime' => <DateTime>, 'HubArn' => '<string>', 'HubDescription' => '<string>', 'HubDisplayName' => '<string>', 'HubName' => '<string>', 'HubSearchKeywords' => ['<string>', ...], 'HubStatus' => 'InService|Creating|Updating|Deleting|CreateFailed|UpdateFailed|DeleteFailed', 'LastModifiedTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- HubSummaries
-
- Required: Yes
- Type: Array of HubInfo structures
The summaries of the listed hubs.
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of hubs, use it in the subsequent request.
Errors
There are no errors described for this operation.
ListHumanTaskUis
$result = $client->listHumanTaskUis
([/* ... */]); $promise = $client->listHumanTaskUisAsync
([/* ... */]);
Returns information about the human task user interfaces in your account.
Parameter Syntax
$result = $client->listHumanTaskUis([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only human task user interfaces with a creation time greater than or equal to the specified timestamp.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only human task user interfaces that were created before the specified timestamp.
- MaxResults
-
- Type: int
The total number of items to return. If the total number of available items is more than the value specified in
MaxResults
, then aNextToken
will be provided in the output that you can use to resume pagination. - NextToken
-
- Type: string
A token to resume pagination.
- SortOrder
-
- Type: string
An optional value that specifies whether you want the results sorted in
Ascending
orDescending
order.
Result Syntax
[ 'HumanTaskUiSummaries' => [ [ 'CreationTime' => <DateTime>, 'HumanTaskUiArn' => '<string>', 'HumanTaskUiName' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- HumanTaskUiSummaries
-
- Required: Yes
- Type: Array of HumanTaskUiSummary structures
An array of objects describing the human task user interfaces.
- NextToken
-
- Type: string
A token to resume pagination.
Errors
There are no errors described for this operation.
ListHyperParameterTuningJobs
$result = $client->listHyperParameterTuningJobs
([/* ... */]); $promise = $client->listHyperParameterTuningJobsAsync
([/* ... */]);
Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.
Parameter Syntax
$result = $client->listHyperParameterTuningJobs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|Status|CreationTime', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'Completed|InProgress|Failed|Stopped|Stopping|Deleting|DeleteFailed', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only tuning jobs that were created after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only tuning jobs that were created before the specified time.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only tuning jobs that were modified after the specified time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only tuning jobs that were modified before the specified time.
- MaxResults
-
- Type: int
The maximum number of tuning jobs to return. The default value is 10.
- NameContains
-
- Type: string
A string in the tuning job name. This filter returns only tuning jobs whose name contains the specified string.
- NextToken
-
- Type: string
If the result of the previous
ListHyperParameterTuningJobs
request was truncated, the response includes aNextToken
. To retrieve the next set of tuning jobs, use the token in the next request. - SortBy
-
- Type: string
The field to sort results by. The default is
Name
. - SortOrder
-
- Type: string
The sort order for results. The default is
Ascending
. - StatusEquals
-
- Type: string
A filter that returns only tuning jobs with the specified status.
Result Syntax
[ 'HyperParameterTuningJobSummaries' => [ [ 'CreationTime' => <DateTime>, 'HyperParameterTuningEndTime' => <DateTime>, 'HyperParameterTuningJobArn' => '<string>', 'HyperParameterTuningJobName' => '<string>', 'HyperParameterTuningJobStatus' => 'Completed|InProgress|Failed|Stopped|Stopping|Deleting|DeleteFailed', 'LastModifiedTime' => <DateTime>, 'ObjectiveStatusCounters' => [ 'Failed' => <integer>, 'Pending' => <integer>, 'Succeeded' => <integer>, ], 'ResourceLimits' => [ 'MaxNumberOfTrainingJobs' => <integer>, 'MaxParallelTrainingJobs' => <integer>, 'MaxRuntimeInSeconds' => <integer>, ], 'Strategy' => 'Bayesian|Random|Hyperband|Grid', 'TrainingJobStatusCounters' => [ 'Completed' => <integer>, 'InProgress' => <integer>, 'NonRetryableError' => <integer>, 'RetryableError' => <integer>, 'Stopped' => <integer>, ], ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- HyperParameterTuningJobSummaries
-
- Required: Yes
- Type: Array of HyperParameterTuningJobSummary structures
A list of HyperParameterTuningJobSummary objects that describe the tuning jobs that the
ListHyperParameterTuningJobs
request returned. - NextToken
-
- Type: string
If the result of this
ListHyperParameterTuningJobs
request was truncated, the response includes aNextToken
. To retrieve the next set of tuning jobs, use the token in the next request.
Errors
There are no errors described for this operation.
ListImageVersions
$result = $client->listImageVersions
([/* ... */]); $promise = $client->listImageVersionsAsync
([/* ... */]);
Lists the versions of a specified image and their properties. The list can be filtered by creation time or modified time.
Parameter Syntax
$result = $client->listImageVersions([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'ImageName' => '<string>', // REQUIRED 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'CREATION_TIME|LAST_MODIFIED_TIME|VERSION', 'SortOrder' => 'ASCENDING|DESCENDING', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only versions created on or after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only versions created on or before the specified time.
- ImageName
-
- Required: Yes
- Type: string
The name of the image to list the versions of.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only versions modified on or after the specified time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only versions modified on or before the specified time.
- MaxResults
-
- Type: int
The maximum number of versions to return in the response. The default value is 10.
- NextToken
-
- Type: string
If the previous call to
ListImageVersions
didn't return the full set of versions, the call returns a token for getting the next set of versions. - SortBy
-
- Type: string
The property used to sort results. The default value is
CREATION_TIME
. - SortOrder
-
- Type: string
The sort order. The default value is
DESCENDING
.
Result Syntax
[ 'ImageVersions' => [ [ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'ImageArn' => '<string>', 'ImageVersionArn' => '<string>', 'ImageVersionStatus' => 'CREATING|CREATED|CREATE_FAILED|DELETING|DELETE_FAILED', 'LastModifiedTime' => <DateTime>, 'Version' => <integer>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- ImageVersions
-
- Type: Array of ImageVersion structures
A list of versions and their properties.
- NextToken
-
- Type: string
A token for getting the next set of versions, if there are any.
Errors
- ResourceNotFound:
Resource being access is not found.
ListImages
$result = $client->listImages
([/* ... */]); $promise = $client->listImagesAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->listImages([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'CREATION_TIME|LAST_MODIFIED_TIME|IMAGE_NAME', 'SortOrder' => 'ASCENDING|DESCENDING', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only images created on or after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only images created on or before the specified time.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only images modified on or after the specified time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only images modified on or before the specified time.
- MaxResults
-
- Type: int
The maximum number of images to return in the response. The default value is 10.
- NameContains
-
- Type: string
A filter that returns only images whose name contains the specified string.
- NextToken
-
- Type: string
If the previous call to
ListImages
didn't return the full set of images, the call returns a token for getting the next set of images. - SortBy
-
- Type: string
The property used to sort results. The default value is
CREATION_TIME
. - SortOrder
-
- Type: string
The sort order. The default value is
DESCENDING
.
Result Syntax
[ 'Images' => [ [ 'CreationTime' => <DateTime>, 'Description' => '<string>', 'DisplayName' => '<string>', 'FailureReason' => '<string>', 'ImageArn' => '<string>', 'ImageName' => '<string>', 'ImageStatus' => 'CREATING|CREATED|CREATE_FAILED|UPDATING|UPDATE_FAILED|DELETING|DELETE_FAILED', 'LastModifiedTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- Images
-
- Type: Array of Image structures
A list of images and their properties.
- NextToken
-
- Type: string
A token for getting the next set of images, if there are any.
Errors
There are no errors described for this operation.
ListInferenceComponents
$result = $client->listInferenceComponents
([/* ... */]); $promise = $client->listInferenceComponentsAsync
([/* ... */]);
Lists the inference components in your account and their properties.
Parameter Syntax
$result = $client->listInferenceComponents([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'EndpointNameEquals' => '<string>', 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'InService|Creating|Updating|Failed|Deleting', 'VariantNameEquals' => '<string>', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filters the results to only those inference components that were created after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filters the results to only those inference components that were created before the specified time.
- EndpointNameEquals
-
- Type: string
An endpoint name to filter the listed inference components. The response includes only those inference components that are hosted at the specified endpoint.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filters the results to only those inference components that were updated after the specified time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filters the results to only those inference components that were updated before the specified time.
- MaxResults
-
- Type: int
The maximum number of inference components to return in the response. This value defaults to 10.
- NameContains
-
- Type: string
Filters the results to only those inference components with a name that contains the specified string.
- NextToken
-
- Type: string
A token that you use to get the next set of results following a truncated response. If the response to the previous request was truncated, that response provides the value for this token.
- SortBy
-
- Type: string
The field by which to sort the inference components in the response. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results. The default is
Descending
. - StatusEquals
-
- Type: string
Filters the results to only those inference components with the specified status.
- VariantNameEquals
-
- Type: string
A production variant name to filter the listed inference components. The response includes only those inference components that are hosted at the specified variant.
Result Syntax
[ 'InferenceComponents' => [ [ 'CreationTime' => <DateTime>, 'EndpointArn' => '<string>', 'EndpointName' => '<string>', 'InferenceComponentArn' => '<string>', 'InferenceComponentName' => '<string>', 'InferenceComponentStatus' => 'InService|Creating|Updating|Failed|Deleting', 'LastModifiedTime' => <DateTime>, 'VariantName' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- InferenceComponents
-
- Required: Yes
- Type: Array of InferenceComponentSummary structures
A list of inference components and their properties that matches any of the filters you specified in the request.
- NextToken
-
- Type: string
The token to use in a subsequent request to get the next set of results following a truncated response.
Errors
There are no errors described for this operation.
ListInferenceExperiments
$result = $client->listInferenceExperiments
([/* ... */]); $promise = $client->listInferenceExperimentsAsync
([/* ... */]);
Returns the list of all inference experiments.
Parameter Syntax
$result = $client->listInferenceExperiments([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'Creating|Created|Updating|Running|Starting|Stopping|Completed|Cancelled', 'Type' => 'ShadowMode', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Selects inference experiments which were created after this timestamp.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Selects inference experiments which were created before this timestamp.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Selects inference experiments which were last modified after this timestamp.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Selects inference experiments which were last modified before this timestamp.
- MaxResults
-
- Type: int
The maximum number of results to select.
- NameContains
-
- Type: string
Selects inference experiments whose names contain this name.
- NextToken
-
- Type: string
The response from the last list when returning a list large enough to need tokening.
- SortBy
-
- Type: string
The column by which to sort the listed inference experiments.
- SortOrder
-
- Type: string
The direction of sorting (ascending or descending).
- StatusEquals
-
- Type: string
Selects inference experiments which are in this status. For the possible statuses, see DescribeInferenceExperiment.
- Type
-
- Type: string
Selects inference experiments of this type. For the possible types of inference experiments, see CreateInferenceExperiment.
Result Syntax
[ 'InferenceExperiments' => [ [ 'CompletionTime' => <DateTime>, 'CreationTime' => <DateTime>, 'Description' => '<string>', 'LastModifiedTime' => <DateTime>, 'Name' => '<string>', 'RoleArn' => '<string>', 'Schedule' => [ 'EndTime' => <DateTime>, 'StartTime' => <DateTime>, ], 'Status' => 'Creating|Created|Updating|Running|Starting|Stopping|Completed|Cancelled', 'StatusReason' => '<string>', 'Type' => 'ShadowMode', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- InferenceExperiments
-
- Type: Array of InferenceExperimentSummary structures
List of inference experiments.
- NextToken
-
- Type: string
The token to use when calling the next page of results.
Errors
There are no errors described for this operation.
ListInferenceRecommendationsJobSteps
$result = $client->listInferenceRecommendationsJobSteps
([/* ... */]); $promise = $client->listInferenceRecommendationsJobStepsAsync
([/* ... */]);
Returns a list of the subtasks for an Inference Recommender job.
The supported subtasks are benchmarks, which evaluate the performance of your model on different instance types.
Parameter Syntax
$result = $client->listInferenceRecommendationsJobSteps([ 'JobName' => '<string>', // REQUIRED 'MaxResults' => <integer>, 'NextToken' => '<string>', 'Status' => 'PENDING|IN_PROGRESS|COMPLETED|FAILED|STOPPING|STOPPED|DELETING|DELETED', 'StepType' => 'BENCHMARK', ]);
Parameter Details
Members
- JobName
-
- Required: Yes
- Type: string
The name for the Inference Recommender job.
- MaxResults
-
- Type: int
The maximum number of results to return.
- NextToken
-
- Type: string
A token that you can specify to return more results from the list. Specify this field if you have a token that was returned from a previous request.
- Status
-
- Type: string
A filter to return benchmarks of a specified status. If this field is left empty, then all benchmarks are returned.
- StepType
-
- Type: string
A filter to return details about the specified type of subtask.
BENCHMARK
: Evaluate the performance of your model on different instance types.
Result Syntax
[ 'NextToken' => '<string>', 'Steps' => [ [ 'InferenceBenchmark' => [ 'EndpointConfiguration' => [ 'EndpointName' => '<string>', 'InitialInstanceCount' => <integer>, 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.12xlarge|ml.m5d.24xlarge|ml.c4.large|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.large|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.12xlarge|ml.r5.24xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.12xlarge|ml.r5d.24xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.dl1.24xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.p4d.24xlarge|ml.c7g.large|ml.c7g.xlarge|ml.c7g.2xlarge|ml.c7g.4xlarge|ml.c7g.8xlarge|ml.c7g.12xlarge|ml.c7g.16xlarge|ml.m6g.large|ml.m6g.xlarge|ml.m6g.2xlarge|ml.m6g.4xlarge|ml.m6g.8xlarge|ml.m6g.12xlarge|ml.m6g.16xlarge|ml.m6gd.large|ml.m6gd.xlarge|ml.m6gd.2xlarge|ml.m6gd.4xlarge|ml.m6gd.8xlarge|ml.m6gd.12xlarge|ml.m6gd.16xlarge|ml.c6g.large|ml.c6g.xlarge|ml.c6g.2xlarge|ml.c6g.4xlarge|ml.c6g.8xlarge|ml.c6g.12xlarge|ml.c6g.16xlarge|ml.c6gd.large|ml.c6gd.xlarge|ml.c6gd.2xlarge|ml.c6gd.4xlarge|ml.c6gd.8xlarge|ml.c6gd.12xlarge|ml.c6gd.16xlarge|ml.c6gn.large|ml.c6gn.xlarge|ml.c6gn.2xlarge|ml.c6gn.4xlarge|ml.c6gn.8xlarge|ml.c6gn.12xlarge|ml.c6gn.16xlarge|ml.r6g.large|ml.r6g.xlarge|ml.r6g.2xlarge|ml.r6g.4xlarge|ml.r6g.8xlarge|ml.r6g.12xlarge|ml.r6g.16xlarge|ml.r6gd.large|ml.r6gd.xlarge|ml.r6gd.2xlarge|ml.r6gd.4xlarge|ml.r6gd.8xlarge|ml.r6gd.12xlarge|ml.r6gd.16xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.p5.48xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge', 'ServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'VariantName' => '<string>', ], 'EndpointMetrics' => [ 'MaxInvocations' => <integer>, 'ModelLatency' => <integer>, ], 'FailureReason' => '<string>', 'InvocationEndTime' => <DateTime>, 'InvocationStartTime' => <DateTime>, 'Metrics' => [ 'CostPerHour' => <float>, 'CostPerInference' => <float>, 'CpuUtilization' => <float>, 'MaxInvocations' => <integer>, 'MemoryUtilization' => <float>, 'ModelLatency' => <integer>, 'ModelSetupTime' => <integer>, ], 'ModelConfiguration' => [ 'CompilationJobName' => '<string>', 'EnvironmentParameters' => [ [ 'Key' => '<string>', 'Value' => '<string>', 'ValueType' => '<string>', ], // ... ], 'InferenceSpecificationName' => '<string>', ], ], 'JobName' => '<string>', 'Status' => 'PENDING|IN_PROGRESS|COMPLETED|FAILED|STOPPING|STOPPED|DELETING|DELETED', 'StepType' => 'BENCHMARK', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
A token that you can specify in your next request to return more results from the list.
- Steps
-
- Type: Array of InferenceRecommendationsJobStep structures
A list of all subtask details in Inference Recommender.
Errors
- ResourceNotFound:
Resource being access is not found.
ListInferenceRecommendationsJobs
$result = $client->listInferenceRecommendationsJobs
([/* ... */]); $promise = $client->listInferenceRecommendationsJobsAsync
([/* ... */]);
Lists recommendation jobs that satisfy various filters.
Parameter Syntax
$result = $client->listInferenceRecommendationsJobs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'ModelNameEquals' => '<string>', 'ModelPackageVersionArnEquals' => '<string>', 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'PENDING|IN_PROGRESS|COMPLETED|FAILED|STOPPING|STOPPED|DELETING|DELETED', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only jobs created after the specified time (timestamp).
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only jobs created before the specified time (timestamp).
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only jobs that were last modified after the specified time (timestamp).
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only jobs that were last modified before the specified time (timestamp).
- MaxResults
-
- Type: int
The maximum number of recommendations to return in the response.
- ModelNameEquals
-
- Type: string
A filter that returns only jobs that were created for this model.
- ModelPackageVersionArnEquals
-
- Type: string
A filter that returns only jobs that were created for this versioned model package.
- NameContains
-
- Type: string
A string in the job name. This filter returns only recommendations whose name contains the specified string.
- NextToken
-
- Type: string
If the response to a previous
ListInferenceRecommendationsJobsRequest
request was truncated, the response includes aNextToken
. To retrieve the next set of recommendations, use the token in the next request. - SortBy
-
- Type: string
The parameter by which to sort the results.
- SortOrder
-
- Type: string
The sort order for the results.
- StatusEquals
-
- Type: string
A filter that retrieves only inference recommendations jobs with a specific status.
Result Syntax
[ 'InferenceRecommendationsJobs' => [ [ 'CompletionTime' => <DateTime>, 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'JobArn' => '<string>', 'JobDescription' => '<string>', 'JobName' => '<string>', 'JobType' => 'Default|Advanced', 'LastModifiedTime' => <DateTime>, 'ModelName' => '<string>', 'ModelPackageVersionArn' => '<string>', 'RoleArn' => '<string>', 'SamplePayloadUrl' => '<string>', 'Status' => 'PENDING|IN_PROGRESS|COMPLETED|FAILED|STOPPING|STOPPED|DELETING|DELETED', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- InferenceRecommendationsJobs
-
- Required: Yes
- Type: Array of InferenceRecommendationsJob structures
The recommendations created from the Amazon SageMaker Inference Recommender job.
- NextToken
-
- Type: string
A token for getting the next set of recommendations, if there are any.
Errors
There are no errors described for this operation.
ListLabelingJobs
$result = $client->listLabelingJobs
([/* ... */]); $promise = $client->listLabelingJobsAsync
([/* ... */]);
Gets a list of labeling jobs.
Parameter Syntax
$result = $client->listLabelingJobs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'Initializing|InProgress|Completed|Failed|Stopping|Stopped', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only labeling jobs created after the specified time (timestamp).
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only labeling jobs created before the specified time (timestamp).
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only labeling jobs modified after the specified time (timestamp).
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only labeling jobs modified before the specified time (timestamp).
- MaxResults
-
- Type: int
The maximum number of labeling jobs to return in each page of the response.
- NameContains
-
- Type: string
A string in the labeling job name. This filter returns only labeling jobs whose name contains the specified string.
- NextToken
-
- Type: string
If the result of the previous
ListLabelingJobs
request was truncated, the response includes aNextToken
. To retrieve the next set of labeling jobs, use the token in the next request. - SortBy
-
- Type: string
The field to sort results by. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results. The default is
Ascending
. - StatusEquals
-
- Type: string
A filter that retrieves only labeling jobs with a specific status.
Result Syntax
[ 'LabelingJobSummaryList' => [ [ 'AnnotationConsolidationLambdaArn' => '<string>', 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'InputConfig' => [ 'DataAttributes' => [ 'ContentClassifiers' => ['<string>', ...], ], 'DataSource' => [ 'S3DataSource' => [ 'ManifestS3Uri' => '<string>', ], 'SnsDataSource' => [ 'SnsTopicArn' => '<string>', ], ], ], 'LabelCounters' => [ 'FailedNonRetryableError' => <integer>, 'HumanLabeled' => <integer>, 'MachineLabeled' => <integer>, 'TotalLabeled' => <integer>, 'Unlabeled' => <integer>, ], 'LabelingJobArn' => '<string>', 'LabelingJobName' => '<string>', 'LabelingJobOutput' => [ 'FinalActiveLearningModelArn' => '<string>', 'OutputDatasetS3Uri' => '<string>', ], 'LabelingJobStatus' => 'Initializing|InProgress|Completed|Failed|Stopping|Stopped', 'LastModifiedTime' => <DateTime>, 'PreHumanTaskLambdaArn' => '<string>', 'WorkteamArn' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- LabelingJobSummaryList
-
- Type: Array of LabelingJobSummary structures
An array of
LabelingJobSummary
objects, each describing a labeling job. - NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
Errors
There are no errors described for this operation.
ListLabelingJobsForWorkteam
$result = $client->listLabelingJobsForWorkteam
([/* ... */]); $promise = $client->listLabelingJobsForWorkteamAsync
([/* ... */]);
Gets a list of labeling jobs assigned to a specified work team.
Parameter Syntax
$result = $client->listLabelingJobsForWorkteam([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'JobReferenceCodeContains' => '<string>', 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'CreationTime', 'SortOrder' => 'Ascending|Descending', 'WorkteamArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only labeling jobs created after the specified time (timestamp).
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only labeling jobs created before the specified time (timestamp).
- JobReferenceCodeContains
-
- Type: string
A filter the limits jobs to only the ones whose job reference code contains the specified string.
- MaxResults
-
- Type: int
The maximum number of labeling jobs to return in each page of the response.
- NextToken
-
- Type: string
If the result of the previous
ListLabelingJobsForWorkteam
request was truncated, the response includes aNextToken
. To retrieve the next set of labeling jobs, use the token in the next request. - SortBy
-
- Type: string
The field to sort results by. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results. The default is
Ascending
. - WorkteamArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the work team for which you want to see labeling jobs for.
Result Syntax
[ 'LabelingJobSummaryList' => [ [ 'CreationTime' => <DateTime>, 'JobReferenceCode' => '<string>', 'LabelCounters' => [ 'HumanLabeled' => <integer>, 'PendingHuman' => <integer>, 'Total' => <integer>, ], 'LabelingJobName' => '<string>', 'NumberOfHumanWorkersPerDataObject' => <integer>, 'WorkRequesterAccountId' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- LabelingJobSummaryList
-
- Required: Yes
- Type: Array of LabelingJobForWorkteamSummary structures
An array of
LabelingJobSummary
objects, each describing a labeling job. - NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
Errors
- ResourceNotFound:
Resource being access is not found.
ListLineageGroups
$result = $client->listLineageGroups
([/* ... */]); $promise = $client->listLineageGroupsAsync
([/* ... */]);
A list of lineage groups shared with your Amazon Web Services account. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
Parameter Syntax
$result = $client->listLineageGroups([ 'CreatedAfter' => <integer || string || DateTime>, 'CreatedBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreatedAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp to filter against lineage groups created after a certain point in time.
- CreatedBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp to filter against lineage groups created before a certain point in time.
- MaxResults
-
- Type: int
The maximum number of endpoints to return in the response. This value defaults to 10.
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
- SortBy
-
- Type: string
The parameter by which to sort the results. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for the results. The default is
Ascending
.
Result Syntax
[ 'LineageGroupSummaries' => [ [ 'CreationTime' => <DateTime>, 'DisplayName' => '<string>', 'LastModifiedTime' => <DateTime>, 'LineageGroupArn' => '<string>', 'LineageGroupName' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- LineageGroupSummaries
-
- Type: Array of LineageGroupSummary structures
A list of lineage groups and their properties.
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
Errors
There are no errors described for this operation.
ListMlflowTrackingServers
$result = $client->listMlflowTrackingServers
([/* ... */]); $promise = $client->listMlflowTrackingServersAsync
([/* ... */]);
Lists all MLflow Tracking Servers.
Parameter Syntax
$result = $client->listMlflowTrackingServers([ 'CreatedAfter' => <integer || string || DateTime>, 'CreatedBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'MlflowVersion' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'TrackingServerStatus' => 'Creating|Created|CreateFailed|Updating|Updated|UpdateFailed|Deleting|DeleteFailed|Stopping|Stopped|StopFailed|Starting|Started|StartFailed|MaintenanceInProgress|MaintenanceComplete|MaintenanceFailed', ]);
Parameter Details
Members
- CreatedAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Use the
CreatedAfter
filter to only list tracking servers created after a specific date and time. Listed tracking servers are shown with a date and time such as"2024-03-16T01:46:56+00:00"
. TheCreatedAfter
parameter takes in a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter. - CreatedBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Use the
CreatedBefore
filter to only list tracking servers created before a specific date and time. Listed tracking servers are shown with a date and time such as"2024-03-16T01:46:56+00:00"
. TheCreatedBefore
parameter takes in a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter. - MaxResults
-
- Type: int
The maximum number of tracking servers to list.
- MlflowVersion
-
- Type: string
Filter for tracking servers using the specified MLflow version.
- NextToken
-
- Type: string
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
- SortBy
-
- Type: string
Filter for trackings servers sorting by name, creation time, or creation status.
- SortOrder
-
- Type: string
Change the order of the listed tracking servers. By default, tracking servers are listed in
Descending
order by creation time. To change the list order, you can specifySortOrder
to beAscending
. - TrackingServerStatus
-
- Type: string
Filter for tracking servers with a specified creation status.
Result Syntax
[ 'NextToken' => '<string>', 'TrackingServerSummaries' => [ [ 'CreationTime' => <DateTime>, 'IsActive' => 'Active|Inactive', 'LastModifiedTime' => <DateTime>, 'MlflowVersion' => '<string>', 'TrackingServerArn' => '<string>', 'TrackingServerName' => '<string>', 'TrackingServerStatus' => 'Creating|Created|CreateFailed|Updating|Updated|UpdateFailed|Deleting|DeleteFailed|Stopping|Stopped|StopFailed|Starting|Started|StartFailed|MaintenanceInProgress|MaintenanceComplete|MaintenanceFailed', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
- TrackingServerSummaries
-
- Type: Array of TrackingServerSummary structures
A list of tracking servers according to chosen filters.
Errors
There are no errors described for this operation.
ListModelBiasJobDefinitions
$result = $client->listModelBiasJobDefinitions
([/* ... */]); $promise = $client->listModelBiasJobDefinitionsAsync
([/* ... */]);
Lists model bias jobs definitions that satisfy various filters.
Parameter Syntax
$result = $client->listModelBiasJobDefinitions([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'EndpointName' => '<string>', 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only model bias jobs created after a specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only model bias jobs created before a specified time.
- EndpointName
-
- Type: string
Name of the endpoint to monitor for model bias.
- MaxResults
-
- Type: int
The maximum number of model bias jobs to return in the response. The default value is 10.
- NameContains
-
- Type: string
Filter for model bias jobs whose name contains a specified string.
- NextToken
-
- Type: string
The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
- SortBy
-
- Type: string
Whether to sort results by the
Name
orCreationTime
field. The default isCreationTime
. - SortOrder
-
- Type: string
Whether to sort the results in
Ascending
orDescending
order. The default isDescending
.
Result Syntax
[ 'JobDefinitionSummaries' => [ [ 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'MonitoringJobDefinitionArn' => '<string>', 'MonitoringJobDefinitionName' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- JobDefinitionSummaries
-
- Required: Yes
- Type: Array of MonitoringJobDefinitionSummary structures
A JSON array in which each element is a summary for a model bias jobs.
- NextToken
-
- Type: string
The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
Errors
There are no errors described for this operation.
ListModelCardExportJobs
$result = $client->listModelCardExportJobs
([/* ... */]); $promise = $client->listModelCardExportJobsAsync
([/* ... */]);
List the export jobs for the Amazon SageMaker Model Card.
Parameter Syntax
$result = $client->listModelCardExportJobs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'ModelCardExportJobNameContains' => '<string>', 'ModelCardName' => '<string>', // REQUIRED 'ModelCardVersion' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'InProgress|Completed|Failed', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list model card export jobs that were created after the time specified.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list model card export jobs that were created before the time specified.
- MaxResults
-
- Type: int
The maximum number of model card export jobs to list.
- ModelCardExportJobNameContains
-
- Type: string
Only list model card export jobs with names that contain the specified string.
- ModelCardName
-
- Required: Yes
- Type: string
List export jobs for the model card with the specified name.
- ModelCardVersion
-
- Type: int
List export jobs for the model card with the specified version.
- NextToken
-
- Type: string
If the response to a previous
ListModelCardExportJobs
request was truncated, the response includes aNextToken
. To retrieve the next set of model card export jobs, use the token in the next request. - SortBy
-
- Type: string
Sort model card export jobs by either name or creation time. Sorts by creation time by default.
- SortOrder
-
- Type: string
Sort model card export jobs by ascending or descending order.
- StatusEquals
-
- Type: string
Only list model card export jobs with the specified status.
Result Syntax
[ 'ModelCardExportJobSummaries' => [ [ 'CreatedAt' => <DateTime>, 'LastModifiedAt' => <DateTime>, 'ModelCardExportJobArn' => '<string>', 'ModelCardExportJobName' => '<string>', 'ModelCardName' => '<string>', 'ModelCardVersion' => <integer>, 'Status' => 'InProgress|Completed|Failed', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- ModelCardExportJobSummaries
-
- Required: Yes
- Type: Array of ModelCardExportJobSummary structures
The summaries of the listed model card export jobs.
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of model card export jobs, use it in the subsequent request.
Errors
There are no errors described for this operation.
ListModelCardVersions
$result = $client->listModelCardVersions
([/* ... */]); $promise = $client->listModelCardVersionsAsync
([/* ... */]);
List existing versions of an Amazon SageMaker Model Card.
Parameter Syntax
$result = $client->listModelCardVersions([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'ModelCardName' => '<string>', // REQUIRED 'ModelCardStatus' => 'Draft|PendingReview|Approved|Archived', 'NextToken' => '<string>', 'SortBy' => 'Version', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list model card versions that were created after the time specified.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list model card versions that were created before the time specified.
- MaxResults
-
- Type: int
The maximum number of model card versions to list.
- ModelCardName
-
- Required: Yes
- Type: string
List model card versions for the model card with the specified name or Amazon Resource Name (ARN).
- ModelCardStatus
-
- Type: string
Only list model card versions with the specified approval status.
- NextToken
-
- Type: string
If the response to a previous
ListModelCardVersions
request was truncated, the response includes aNextToken
. To retrieve the next set of model card versions, use the token in the next request. - SortBy
-
- Type: string
Sort listed model card versions by version. Sorts by version by default.
- SortOrder
-
- Type: string
Sort model card versions by ascending or descending order.
Result Syntax
[ 'ModelCardVersionSummaryList' => [ [ 'CreationTime' => <DateTime>, 'LastModifiedTime' => <DateTime>, 'ModelCardArn' => '<string>', 'ModelCardName' => '<string>', 'ModelCardStatus' => 'Draft|PendingReview|Approved|Archived', 'ModelCardVersion' => <integer>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- ModelCardVersionSummaryList
-
- Required: Yes
- Type: Array of ModelCardVersionSummary structures
The summaries of the listed versions of the model card.
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of model card versions, use it in the subsequent request.
Errors
- ResourceNotFound:
Resource being access is not found.
ListModelCards
$result = $client->listModelCards
([/* ... */]); $promise = $client->listModelCardsAsync
([/* ... */]);
List existing model cards.
Parameter Syntax
$result = $client->listModelCards([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'ModelCardStatus' => 'Draft|PendingReview|Approved|Archived', 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list model cards that were created after the time specified.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Only list model cards that were created before the time specified.
- MaxResults
-
- Type: int
The maximum number of model cards to list.
- ModelCardStatus
-
- Type: string
Only list model cards with the specified approval status.
- NameContains
-
- Type: string
Only list model cards with names that contain the specified string.
- NextToken
-
- Type: string
If the response to a previous
ListModelCards
request was truncated, the response includes aNextToken
. To retrieve the next set of model cards, use the token in the next request. - SortBy
-
- Type: string
Sort model cards by either name or creation time. Sorts by creation time by default.
- SortOrder
-
- Type: string
Sort model cards by ascending or descending order.
Result Syntax
[ 'ModelCardSummaries' => [ [ 'CreationTime' => <DateTime>, 'LastModifiedTime' => <DateTime>, 'ModelCardArn' => '<string>', 'ModelCardName' => '<string>', 'ModelCardStatus' => 'Draft|PendingReview|Approved|Archived', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- ModelCardSummaries
-
- Required: Yes
- Type: Array of ModelCardSummary structures
The summaries of the listed model cards.
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of model cards, use it in the subsequent request.
Errors
There are no errors described for this operation.
ListModelExplainabilityJobDefinitions
$result = $client->listModelExplainabilityJobDefinitions
([/* ... */]); $promise = $client->listModelExplainabilityJobDefinitionsAsync
([/* ... */]);
Lists model explainability job definitions that satisfy various filters.
Parameter Syntax
$result = $client->listModelExplainabilityJobDefinitions([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'EndpointName' => '<string>', 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only model explainability jobs created after a specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only model explainability jobs created before a specified time.
- EndpointName
-
- Type: string
Name of the endpoint to monitor for model explainability.
- MaxResults
-
- Type: int
The maximum number of jobs to return in the response. The default value is 10.
- NameContains
-
- Type: string
Filter for model explainability jobs whose name contains a specified string.
- NextToken
-
- Type: string
The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
- SortBy
-
- Type: string
Whether to sort results by the
Name
orCreationTime
field. The default isCreationTime
. - SortOrder
-
- Type: string
Whether to sort the results in
Ascending
orDescending
order. The default isDescending
.
Result Syntax
[ 'JobDefinitionSummaries' => [ [ 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'MonitoringJobDefinitionArn' => '<string>', 'MonitoringJobDefinitionName' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- JobDefinitionSummaries
-
- Required: Yes
- Type: Array of MonitoringJobDefinitionSummary structures
A JSON array in which each element is a summary for a explainability bias jobs.
- NextToken
-
- Type: string
The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
Errors
There are no errors described for this operation.
ListModelMetadata
$result = $client->listModelMetadata
([/* ... */]); $promise = $client->listModelMetadataAsync
([/* ... */]);
Lists the domain, framework, task, and model name of standard machine learning models found in common model zoos.
Parameter Syntax
$result = $client->listModelMetadata([ 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SearchExpression' => [ 'Filters' => [ [ 'Name' => 'Domain|Framework|Task|FrameworkVersion', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ], ]);
Parameter Details
Members
- MaxResults
-
- Type: int
The maximum number of models to return in the response.
- NextToken
-
- Type: string
If the response to a previous
ListModelMetadataResponse
request was truncated, the response includes a NextToken. To retrieve the next set of model metadata, use the token in the next request. - SearchExpression
-
- Type: ModelMetadataSearchExpression structure
One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression's condition are included in the search results. Specify the Framework, FrameworkVersion, Domain or Task to filter supported. Filter names and values are case-sensitive.
Result Syntax
[ 'ModelMetadataSummaries' => [ [ 'Domain' => '<string>', 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'Model' => '<string>', 'Task' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- ModelMetadataSummaries
-
- Required: Yes
- Type: Array of ModelMetadataSummary structures
A structure that holds model metadata.
- NextToken
-
- Type: string
A token for getting the next set of recommendations, if there are any.
Errors
There are no errors described for this operation.
ListModelPackageGroups
$result = $client->listModelPackageGroups
([/* ... */]); $promise = $client->listModelPackageGroupsAsync
([/* ... */]);
Gets a list of the model groups in your Amazon Web Services account.
Parameter Syntax
$result = $client->listModelPackageGroups([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'CrossAccountFilterOption' => 'SameAccount|CrossAccount', 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only model groups created after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only model groups created before the specified time.
- CrossAccountFilterOption
-
- Type: string
A filter that returns either model groups shared with you or model groups in your own account. When the value is
CrossAccount
, the results show the resources made discoverable to you from other accounts. When the value isSameAccount
ornull
, the results show resources from your account. The default isSameAccount
. - MaxResults
-
- Type: int
The maximum number of results to return in the response.
- NameContains
-
- Type: string
A string in the model group name. This filter returns only model groups whose name contains the specified string.
- NextToken
-
- Type: string
If the result of the previous
ListModelPackageGroups
request was truncated, the response includes aNextToken
. To retrieve the next set of model groups, use the token in the next request. - SortBy
-
- Type: string
The field to sort results by. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results. The default is
Ascending
.
Result Syntax
[ 'ModelPackageGroupSummaryList' => [ [ 'CreationTime' => <DateTime>, 'ModelPackageGroupArn' => '<string>', 'ModelPackageGroupDescription' => '<string>', 'ModelPackageGroupName' => '<string>', 'ModelPackageGroupStatus' => 'Pending|InProgress|Completed|Failed|Deleting|DeleteFailed', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- ModelPackageGroupSummaryList
-
- Required: Yes
- Type: Array of ModelPackageGroupSummary structures
A list of summaries of the model groups in your Amazon Web Services account.
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of model groups, use it in the subsequent request.
Errors
There are no errors described for this operation.
ListModelPackages
$result = $client->listModelPackages
([/* ... */]); $promise = $client->listModelPackagesAsync
([/* ... */]);
Lists the model packages that have been created.
Parameter Syntax
$result = $client->listModelPackages([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'ModelApprovalStatus' => 'Approved|Rejected|PendingManualApproval', 'ModelPackageGroupName' => '<string>', 'ModelPackageType' => 'Versioned|Unversioned|Both', 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only model packages created after the specified time (timestamp).
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only model packages created before the specified time (timestamp).
- MaxResults
-
- Type: int
The maximum number of model packages to return in the response.
- ModelApprovalStatus
-
- Type: string
A filter that returns only the model packages with the specified approval status.
- ModelPackageGroupName
-
- Type: string
A filter that returns only model versions that belong to the specified model group.
- ModelPackageType
-
- Type: string
A filter that returns only the model packages of the specified type. This can be one of the following values.
-
UNVERSIONED
- List only unversioined models. This is the default value if noModelPackageType
is specified. -
VERSIONED
- List only versioned models. -
BOTH
- List both versioned and unversioned models.
- NameContains
-
- Type: string
A string in the model package name. This filter returns only model packages whose name contains the specified string.
- NextToken
-
- Type: string
If the response to a previous
ListModelPackages
request was truncated, the response includes aNextToken
. To retrieve the next set of model packages, use the token in the next request. - SortBy
-
- Type: string
The parameter by which to sort the results. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for the results. The default is
Ascending
.
Result Syntax
[ 'ModelPackageSummaryList' => [ [ 'CreationTime' => <DateTime>, 'ModelApprovalStatus' => 'Approved|Rejected|PendingManualApproval', 'ModelPackageArn' => '<string>', 'ModelPackageDescription' => '<string>', 'ModelPackageGroupName' => '<string>', 'ModelPackageName' => '<string>', 'ModelPackageStatus' => 'Pending|InProgress|Completed|Failed|Deleting', 'ModelPackageVersion' => <integer>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- ModelPackageSummaryList
-
- Required: Yes
- Type: Array of ModelPackageSummary structures
An array of
ModelPackageSummary
objects, each of which lists a model package. - NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of model packages, use it in the subsequent request.
Errors
There are no errors described for this operation.
ListModelQualityJobDefinitions
$result = $client->listModelQualityJobDefinitions
([/* ... */]); $promise = $client->listModelQualityJobDefinitionsAsync
([/* ... */]);
Gets a list of model quality monitoring job definitions in your account.
Parameter Syntax
$result = $client->listModelQualityJobDefinitions([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'EndpointName' => '<string>', 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only model quality monitoring job definitions created after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only model quality monitoring job definitions created before the specified time.
- EndpointName
-
- Type: string
A filter that returns only model quality monitoring job definitions that are associated with the specified endpoint.
- MaxResults
-
- Type: int
The maximum number of results to return in a call to
ListModelQualityJobDefinitions
. - NameContains
-
- Type: string
A string in the transform job name. This filter returns only model quality monitoring job definitions whose name contains the specified string.
- NextToken
-
- Type: string
If the result of the previous
ListModelQualityJobDefinitions
request was truncated, the response includes aNextToken
. To retrieve the next set of model quality monitoring job definitions, use the token in the next request. - SortBy
-
- Type: string
The field to sort results by. The default is
CreationTime
. - SortOrder
-
- Type: string
Whether to sort the results in
Ascending
orDescending
order. The default isDescending
.
Result Syntax
[ 'JobDefinitionSummaries' => [ [ 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'MonitoringJobDefinitionArn' => '<string>', 'MonitoringJobDefinitionName' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- JobDefinitionSummaries
-
- Required: Yes
- Type: Array of MonitoringJobDefinitionSummary structures
A list of summaries of model quality monitoring job definitions.
- NextToken
-
- Type: string
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of model quality monitoring job definitions, use it in the next request.
Errors
There are no errors described for this operation.
ListModels
$result = $client->listModels
([/* ... */]); $promise = $client->listModelsAsync
([/* ... */]);
Lists models created with the CreateModel
API.
Parameter Syntax
$result = $client->listModels([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only models with a creation time greater than or equal to the specified time (timestamp).
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only models created before the specified time (timestamp).
- MaxResults
-
- Type: int
The maximum number of models to return in the response.
- NameContains
-
- Type: string
A string in the model name. This filter returns only models whose name contains the specified string.
- NextToken
-
- Type: string
If the response to a previous
ListModels
request was truncated, the response includes aNextToken
. To retrieve the next set of models, use the token in the next request. - SortBy
-
- Type: string
Sorts the list of results. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results. The default is
Descending
.
Result Syntax
[ 'Models' => [ [ 'CreationTime' => <DateTime>, 'ModelArn' => '<string>', 'ModelName' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- Models
-
- Required: Yes
- Type: Array of ModelSummary structures
An array of
ModelSummary
objects, each of which lists a model. - NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of models, use it in the subsequent request.
Errors
There are no errors described for this operation.
ListMonitoringAlertHistory
$result = $client->listMonitoringAlertHistory
([/* ... */]); $promise = $client->listMonitoringAlertHistoryAsync
([/* ... */]);
Gets a list of past alerts in a model monitoring schedule.
Parameter Syntax
$result = $client->listMonitoringAlertHistory([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'MonitoringAlertName' => '<string>', 'MonitoringScheduleName' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'InAlert|OK', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only alerts created on or after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only alerts created on or before the specified time.
- MaxResults
-
- Type: int
The maximum number of results to display. The default is 100.
- MonitoringAlertName
-
- Type: string
The name of a monitoring alert.
- MonitoringScheduleName
-
- Type: string
The name of a monitoring schedule.
- NextToken
-
- Type: string
If the result of the previous
ListMonitoringAlertHistory
request was truncated, the response includes aNextToken
. To retrieve the next set of alerts in the history, use the token in the next request. - SortBy
-
- Type: string
The field used to sort results. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order, whether
Ascending
orDescending
, of the alert history. The default isDescending
. - StatusEquals
-
- Type: string
A filter that retrieves only alerts with a specific status.
Result Syntax
[ 'MonitoringAlertHistory' => [ [ 'AlertStatus' => 'InAlert|OK', 'CreationTime' => <DateTime>, 'MonitoringAlertName' => '<string>', 'MonitoringScheduleName' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- MonitoringAlertHistory
-
- Type: Array of MonitoringAlertHistorySummary structures
An alert history for a model monitoring schedule.
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
Errors
- ResourceNotFound:
Resource being access is not found.
ListMonitoringAlerts
$result = $client->listMonitoringAlerts
([/* ... */]); $promise = $client->listMonitoringAlertsAsync
([/* ... */]);
Gets the alerts for a single monitoring schedule.
Parameter Syntax
$result = $client->listMonitoringAlerts([ 'MaxResults' => <integer>, 'MonitoringScheduleName' => '<string>', // REQUIRED 'NextToken' => '<string>', ]);
Parameter Details
Members
- MaxResults
-
- Type: int
The maximum number of results to display. The default is 100.
- MonitoringScheduleName
-
- Required: Yes
- Type: string
The name of a monitoring schedule.
- NextToken
-
- Type: string
If the result of the previous
ListMonitoringAlerts
request was truncated, the response includes aNextToken
. To retrieve the next set of alerts in the history, use the token in the next request.
Result Syntax
[ 'MonitoringAlertSummaries' => [ [ 'Actions' => [ 'ModelDashboardIndicator' => [ 'Enabled' => true || false, ], ], 'AlertStatus' => 'InAlert|OK', 'CreationTime' => <DateTime>, 'DatapointsToAlert' => <integer>, 'EvaluationPeriod' => <integer>, 'LastModifiedTime' => <DateTime>, 'MonitoringAlertName' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- MonitoringAlertSummaries
-
- Type: Array of MonitoringAlertSummary structures
A JSON array where each element is a summary for a monitoring alert.
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
Errors
- ResourceNotFound:
Resource being access is not found.
ListMonitoringExecutions
$result = $client->listMonitoringExecutions
([/* ... */]); $promise = $client->listMonitoringExecutionsAsync
([/* ... */]);
Returns list of all monitoring job executions.
Parameter Syntax
$result = $client->listMonitoringExecutions([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'EndpointName' => '<string>', 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'MonitoringJobDefinitionName' => '<string>', 'MonitoringScheduleName' => '<string>', 'MonitoringTypeEquals' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'NextToken' => '<string>', 'ScheduledTimeAfter' => <integer || string || DateTime>, 'ScheduledTimeBefore' => <integer || string || DateTime>, 'SortBy' => 'CreationTime|ScheduledTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'Pending|Completed|CompletedWithViolations|InProgress|Failed|Stopping|Stopped', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only jobs created after a specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only jobs created before a specified time.
- EndpointName
-
- Type: string
Name of a specific endpoint to fetch jobs for.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only jobs modified before a specified time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only jobs modified after a specified time.
- MaxResults
-
- Type: int
The maximum number of jobs to return in the response. The default value is 10.
- MonitoringJobDefinitionName
-
- Type: string
Gets a list of the monitoring job runs of the specified monitoring job definitions.
- MonitoringScheduleName
-
- Type: string
Name of a specific schedule to fetch jobs for.
- MonitoringTypeEquals
-
- Type: string
A filter that returns only the monitoring job runs of the specified monitoring type.
- NextToken
-
- Type: string
The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
- ScheduledTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filter for jobs scheduled after a specified time.
- ScheduledTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filter for jobs scheduled before a specified time.
- SortBy
-
- Type: string
Whether to sort the results by the
Status
,CreationTime
, orScheduledTime
field. The default isCreationTime
. - SortOrder
-
- Type: string
Whether to sort the results in
Ascending
orDescending
order. The default isDescending
. - StatusEquals
-
- Type: string
A filter that retrieves only jobs with a specific status.
Result Syntax
[ 'MonitoringExecutionSummaries' => [ [ 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'MonitoringExecutionStatus' => 'Pending|Completed|CompletedWithViolations|InProgress|Failed|Stopping|Stopped', 'MonitoringJobDefinitionName' => '<string>', 'MonitoringScheduleName' => '<string>', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'ProcessingJobArn' => '<string>', 'ScheduledTime' => <DateTime>, ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- MonitoringExecutionSummaries
-
- Required: Yes
- Type: Array of MonitoringExecutionSummary structures
A JSON array in which each element is a summary for a monitoring execution.
- NextToken
-
- Type: string
The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
Errors
There are no errors described for this operation.
ListMonitoringSchedules
$result = $client->listMonitoringSchedules
([/* ... */]); $promise = $client->listMonitoringSchedulesAsync
([/* ... */]);
Returns list of all monitoring schedules.
Parameter Syntax
$result = $client->listMonitoringSchedules([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'EndpointName' => '<string>', 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'MonitoringJobDefinitionName' => '<string>', 'MonitoringTypeEquals' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'Pending|Failed|Scheduled|Stopped', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only monitoring schedules created after a specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only monitoring schedules created before a specified time.
- EndpointName
-
- Type: string
Name of a specific endpoint to fetch schedules for.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only monitoring schedules modified after a specified time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only monitoring schedules modified before a specified time.
- MaxResults
-
- Type: int
The maximum number of jobs to return in the response. The default value is 10.
- MonitoringJobDefinitionName
-
- Type: string
Gets a list of the monitoring schedules for the specified monitoring job definition.
- MonitoringTypeEquals
-
- Type: string
A filter that returns only the monitoring schedules for the specified monitoring type.
- NameContains
-
- Type: string
Filter for monitoring schedules whose name contains a specified string.
- NextToken
-
- Type: string
The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
- SortBy
-
- Type: string
Whether to sort the results by the
Status
,CreationTime
, orScheduledTime
field. The default isCreationTime
. - SortOrder
-
- Type: string
Whether to sort the results in
Ascending
orDescending
order. The default isDescending
. - StatusEquals
-
- Type: string
A filter that returns only monitoring schedules modified before a specified time.
Result Syntax
[ 'MonitoringScheduleSummaries' => [ [ 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'LastModifiedTime' => <DateTime>, 'MonitoringJobDefinitionName' => '<string>', 'MonitoringScheduleArn' => '<string>', 'MonitoringScheduleName' => '<string>', 'MonitoringScheduleStatus' => 'Pending|Failed|Scheduled|Stopped', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- MonitoringScheduleSummaries
-
- Required: Yes
- Type: Array of MonitoringScheduleSummary structures
A JSON array in which each element is a summary for a monitoring schedule.
- NextToken
-
- Type: string
The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
Errors
There are no errors described for this operation.
ListNotebookInstanceLifecycleConfigs
$result = $client->listNotebookInstanceLifecycleConfigs
([/* ... */]); $promise = $client->listNotebookInstanceLifecycleConfigsAsync
([/* ... */]);
Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API.
Parameter Syntax
$result = $client->listNotebookInstanceLifecycleConfigs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|LastModifiedTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only lifecycle configurations that were created after the specified time (timestamp).
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only lifecycle configurations that were created before the specified time (timestamp).
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only lifecycle configurations that were modified after the specified time (timestamp).
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only lifecycle configurations that were modified before the specified time (timestamp).
- MaxResults
-
- Type: int
The maximum number of lifecycle configurations to return in the response.
- NameContains
-
- Type: string
A string in the lifecycle configuration name. This filter returns only lifecycle configurations whose name contains the specified string.
- NextToken
-
- Type: string
If the result of a
ListNotebookInstanceLifecycleConfigs
request was truncated, the response includes aNextToken
. To get the next set of lifecycle configurations, use the token in the next request. - SortBy
-
- Type: string
Sorts the list of results. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results.
Result Syntax
[ 'NextToken' => '<string>', 'NotebookInstanceLifecycleConfigs' => [ [ 'CreationTime' => <DateTime>, 'LastModifiedTime' => <DateTime>, 'NotebookInstanceLifecycleConfigArn' => '<string>', 'NotebookInstanceLifecycleConfigName' => '<string>', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To get the next set of lifecycle configurations, use it in the next request.
- NotebookInstanceLifecycleConfigs
-
- Type: Array of NotebookInstanceLifecycleConfigSummary structures
An array of
NotebookInstanceLifecycleConfiguration
objects, each listing a lifecycle configuration.
Errors
There are no errors described for this operation.
ListNotebookInstances
$result = $client->listNotebookInstances
([/* ... */]); $promise = $client->listNotebookInstancesAsync
([/* ... */]);
Returns a list of the SageMaker notebook instances in the requester's account in an Amazon Web Services Region.
Parameter Syntax
$result = $client->listNotebookInstances([ 'AdditionalCodeRepositoryEquals' => '<string>', 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'DefaultCodeRepositoryContains' => '<string>', 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'NotebookInstanceLifecycleConfigNameContains' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'Pending|InService|Stopping|Stopped|Failed|Deleting|Updating', ]);
Parameter Details
Members
- AdditionalCodeRepositoryEquals
-
- Type: string
A filter that returns only notebook instances with associated with the specified git repository.
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only notebook instances that were created after the specified time (timestamp).
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only notebook instances that were created before the specified time (timestamp).
- DefaultCodeRepositoryContains
-
- Type: string
A string in the name or URL of a Git repository associated with this notebook instance. This filter returns only notebook instances associated with a git repository with a name that contains the specified string.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only notebook instances that were modified after the specified time (timestamp).
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only notebook instances that were modified before the specified time (timestamp).
- MaxResults
-
- Type: int
The maximum number of notebook instances to return.
- NameContains
-
- Type: string
A string in the notebook instances' name. This filter returns only notebook instances whose name contains the specified string.
- NextToken
-
- Type: string
If the previous call to the
ListNotebookInstances
is truncated, the response includes aNextToken
. You can use this token in your subsequentListNotebookInstances
request to fetch the next set of notebook instances.You might specify a filter or a sort order in your request. When response is truncated, you must use the same values for the filer and sort order in the next request.
- NotebookInstanceLifecycleConfigNameContains
-
- Type: string
A string in the name of a notebook instances lifecycle configuration associated with this notebook instance. This filter returns only notebook instances associated with a lifecycle configuration with a name that contains the specified string.
- SortBy
-
- Type: string
The field to sort results by. The default is
Name
. - SortOrder
-
- Type: string
The sort order for results.
- StatusEquals
-
- Type: string
A filter that returns only notebook instances with the specified status.
Result Syntax
[ 'NextToken' => '<string>', 'NotebookInstances' => [ [ 'AdditionalCodeRepositories' => ['<string>', ...], 'CreationTime' => <DateTime>, 'DefaultCodeRepository' => '<string>', 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge', 'LastModifiedTime' => <DateTime>, 'NotebookInstanceArn' => '<string>', 'NotebookInstanceLifecycleConfigName' => '<string>', 'NotebookInstanceName' => '<string>', 'NotebookInstanceStatus' => 'Pending|InService|Stopping|Stopped|Failed|Deleting|Updating', 'Url' => '<string>', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the response to the previous
ListNotebookInstances
request was truncated, SageMaker returns this token. To retrieve the next set of notebook instances, use the token in the next request. - NotebookInstances
-
- Type: Array of NotebookInstanceSummary structures
An array of
NotebookInstanceSummary
objects, one for each notebook instance.
Errors
There are no errors described for this operation.
ListOptimizationJobs
$result = $client->listOptimizationJobs
([/* ... */]); $promise = $client->listOptimizationJobsAsync
([/* ... */]);
Lists the optimization jobs in your account and their properties.
Parameter Syntax
$result = $client->listOptimizationJobs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'OptimizationContains' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'INPROGRESS|COMPLETED|FAILED|STARTING|STOPPING|STOPPED', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filters the results to only those optimization jobs that were created after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filters the results to only those optimization jobs that were created before the specified time.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filters the results to only those optimization jobs that were updated after the specified time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filters the results to only those optimization jobs that were updated before the specified time.
- MaxResults
-
- Type: int
The maximum number of optimization jobs to return in the response. The default is 50.
- NameContains
-
- Type: string
Filters the results to only those optimization jobs with a name that contains the specified string.
- NextToken
-
- Type: string
A token that you use to get the next set of results following a truncated response. If the response to the previous request was truncated, that response provides the value for this token.
- OptimizationContains
-
- Type: string
Filters the results to only those optimization jobs that apply the specified optimization techniques. You can specify either
Quantization
orCompilation
. - SortBy
-
- Type: string
The field by which to sort the optimization jobs in the response. The default is
CreationTime
- SortOrder
-
- Type: string
The sort order for results. The default is
Ascending
- StatusEquals
-
- Type: string
Filters the results to only those optimization jobs with the specified status.
Result Syntax
[ 'NextToken' => '<string>', 'OptimizationJobSummaries' => [ [ 'CreationTime' => <DateTime>, 'DeploymentInstanceType' => 'ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge', 'LastModifiedTime' => <DateTime>, 'OptimizationEndTime' => <DateTime>, 'OptimizationJobArn' => '<string>', 'OptimizationJobName' => '<string>', 'OptimizationJobStatus' => 'INPROGRESS|COMPLETED|FAILED|STARTING|STOPPING|STOPPED', 'OptimizationStartTime' => <DateTime>, 'OptimizationTypes' => ['<string>', ...], ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
The token to use in a subsequent request to get the next set of results following a truncated response.
- OptimizationJobSummaries
-
- Required: Yes
- Type: Array of OptimizationJobSummary structures
A list of optimization jobs and their properties that matches any of the filters you specified in the request.
Errors
There are no errors described for this operation.
ListPipelineExecutionSteps
$result = $client->listPipelineExecutionSteps
([/* ... */]); $promise = $client->listPipelineExecutionStepsAsync
([/* ... */]);
Gets a list of PipeLineExecutionStep
objects.
Parameter Syntax
$result = $client->listPipelineExecutionSteps([ 'MaxResults' => <integer>, 'NextToken' => '<string>', 'PipelineExecutionArn' => '<string>', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- MaxResults
-
- Type: int
The maximum number of pipeline execution steps to return in the response.
- NextToken
-
- Type: string
If the result of the previous
ListPipelineExecutionSteps
request was truncated, the response includes aNextToken
. To retrieve the next set of pipeline execution steps, use the token in the next request. - PipelineExecutionArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
- SortOrder
-
- Type: string
The field by which to sort results. The default is
CreatedTime
.
Result Syntax
[ 'NextToken' => '<string>', 'PipelineExecutionSteps' => [ [ 'AttemptCount' => <integer>, 'CacheHitResult' => [ 'SourcePipelineExecutionArn' => '<string>', ], 'EndTime' => <DateTime>, 'FailureReason' => '<string>', 'Metadata' => [ 'AutoMLJob' => [ 'Arn' => '<string>', ], 'Callback' => [ 'CallbackToken' => '<string>', 'OutputParameters' => [ [ 'Name' => '<string>', 'Value' => '<string>', ], // ... ], 'SqsQueueUrl' => '<string>', ], 'ClarifyCheck' => [ 'BaselineUsedForDriftCheckConstraints' => '<string>', 'CalculatedBaselineConstraints' => '<string>', 'CheckJobArn' => '<string>', 'CheckType' => '<string>', 'ModelPackageGroupName' => '<string>', 'RegisterNewBaseline' => true || false, 'SkipCheck' => true || false, 'ViolationReport' => '<string>', ], 'Condition' => [ 'Outcome' => 'True|False', ], 'EMR' => [ 'ClusterId' => '<string>', 'LogFilePath' => '<string>', 'StepId' => '<string>', 'StepName' => '<string>', ], 'Endpoint' => [ 'Arn' => '<string>', ], 'EndpointConfig' => [ 'Arn' => '<string>', ], 'Fail' => [ 'ErrorMessage' => '<string>', ], 'Lambda' => [ 'Arn' => '<string>', 'OutputParameters' => [ [ 'Name' => '<string>', 'Value' => '<string>', ], // ... ], ], 'Model' => [ 'Arn' => '<string>', ], 'ProcessingJob' => [ 'Arn' => '<string>', ], 'QualityCheck' => [ 'BaselineUsedForDriftCheckConstraints' => '<string>', 'BaselineUsedForDriftCheckStatistics' => '<string>', 'CalculatedBaselineConstraints' => '<string>', 'CalculatedBaselineStatistics' => '<string>', 'CheckJobArn' => '<string>', 'CheckType' => '<string>', 'ModelPackageGroupName' => '<string>', 'RegisterNewBaseline' => true || false, 'SkipCheck' => true || false, 'ViolationReport' => '<string>', ], 'RegisterModel' => [ 'Arn' => '<string>', ], 'TrainingJob' => [ 'Arn' => '<string>', ], 'TransformJob' => [ 'Arn' => '<string>', ], 'TuningJob' => [ 'Arn' => '<string>', ], ], 'SelectiveExecutionResult' => [ 'SourcePipelineExecutionArn' => '<string>', ], 'StartTime' => <DateTime>, 'StepDescription' => '<string>', 'StepDisplayName' => '<string>', 'StepName' => '<string>', 'StepStatus' => 'Starting|Executing|Stopping|Stopped|Failed|Succeeded', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the result of the previous
ListPipelineExecutionSteps
request was truncated, the response includes aNextToken
. To retrieve the next set of pipeline execution steps, use the token in the next request. - PipelineExecutionSteps
-
- Type: Array of PipelineExecutionStep structures
A list of
PipeLineExecutionStep
objects. EachPipeLineExecutionStep
consists of StepName, StartTime, EndTime, StepStatus, and Metadata. Metadata is an object with properties for each job that contains relevant information about the job created by the step.
Errors
- ResourceNotFound:
Resource being access is not found.
ListPipelineExecutions
$result = $client->listPipelineExecutions
([/* ... */]); $promise = $client->listPipelineExecutionsAsync
([/* ... */]);
Gets a list of the pipeline executions.
Parameter Syntax
$result = $client->listPipelineExecutions([ 'CreatedAfter' => <integer || string || DateTime>, 'CreatedBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NextToken' => '<string>', 'PipelineName' => '<string>', // REQUIRED 'SortBy' => 'CreationTime|PipelineExecutionArn', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreatedAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns the pipeline executions that were created after a specified time.
- CreatedBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns the pipeline executions that were created before a specified time.
- MaxResults
-
- Type: int
The maximum number of pipeline executions to return in the response.
- NextToken
-
- Type: string
If the result of the previous
ListPipelineExecutions
request was truncated, the response includes aNextToken
. To retrieve the next set of pipeline executions, use the token in the next request. - PipelineName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the pipeline.
- SortBy
-
- Type: string
The field by which to sort results. The default is
CreatedTime
. - SortOrder
-
- Type: string
The sort order for results.
Result Syntax
[ 'NextToken' => '<string>', 'PipelineExecutionSummaries' => [ [ 'PipelineExecutionArn' => '<string>', 'PipelineExecutionDescription' => '<string>', 'PipelineExecutionDisplayName' => '<string>', 'PipelineExecutionFailureReason' => '<string>', 'PipelineExecutionStatus' => 'Executing|Stopping|Stopped|Failed|Succeeded', 'StartTime' => <DateTime>, ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the result of the previous
ListPipelineExecutions
request was truncated, the response includes aNextToken
. To retrieve the next set of pipeline executions, use the token in the next request. - PipelineExecutionSummaries
-
- Type: Array of PipelineExecutionSummary structures
Contains a sorted list of pipeline execution summary objects matching the specified filters. Each run summary includes the Amazon Resource Name (ARN) of the pipeline execution, the run date, and the status. This list can be empty.
Errors
- ResourceNotFound:
Resource being access is not found.
ListPipelineParametersForExecution
$result = $client->listPipelineParametersForExecution
([/* ... */]); $promise = $client->listPipelineParametersForExecutionAsync
([/* ... */]);
Gets a list of parameters for a pipeline execution.
Parameter Syntax
$result = $client->listPipelineParametersForExecution([ 'MaxResults' => <integer>, 'NextToken' => '<string>', 'PipelineExecutionArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
- MaxResults
-
- Type: int
The maximum number of parameters to return in the response.
- NextToken
-
- Type: string
If the result of the previous
ListPipelineParametersForExecution
request was truncated, the response includes aNextToken
. To retrieve the next set of parameters, use the token in the next request. - PipelineExecutionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
Result Syntax
[ 'NextToken' => '<string>', 'PipelineParameters' => [ [ 'Name' => '<string>', 'Value' => '<string>', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the result of the previous
ListPipelineParametersForExecution
request was truncated, the response includes aNextToken
. To retrieve the next set of parameters, use the token in the next request. - PipelineParameters
-
- Type: Array of Parameter structures
Contains a list of pipeline parameters. This list can be empty.
Errors
- ResourceNotFound:
Resource being access is not found.
ListPipelines
$result = $client->listPipelines
([/* ... */]); $promise = $client->listPipelinesAsync
([/* ... */]);
Gets a list of pipelines.
Parameter Syntax
$result = $client->listPipelines([ 'CreatedAfter' => <integer || string || DateTime>, 'CreatedBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NextToken' => '<string>', 'PipelineNamePrefix' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreatedAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns the pipelines that were created after a specified time.
- CreatedBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns the pipelines that were created before a specified time.
- MaxResults
-
- Type: int
The maximum number of pipelines to return in the response.
- NextToken
-
- Type: string
If the result of the previous
ListPipelines
request was truncated, the response includes aNextToken
. To retrieve the next set of pipelines, use the token in the next request. - PipelineNamePrefix
-
- Type: string
The prefix of the pipeline name.
- SortBy
-
- Type: string
The field by which to sort results. The default is
CreatedTime
. - SortOrder
-
- Type: string
The sort order for results.
Result Syntax
[ 'NextToken' => '<string>', 'PipelineSummaries' => [ [ 'CreationTime' => <DateTime>, 'LastExecutionTime' => <DateTime>, 'LastModifiedTime' => <DateTime>, 'PipelineArn' => '<string>', 'PipelineDescription' => '<string>', 'PipelineDisplayName' => '<string>', 'PipelineName' => '<string>', 'RoleArn' => '<string>', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the result of the previous
ListPipelines
request was truncated, the response includes aNextToken
. To retrieve the next set of pipelines, use the token in the next request. - PipelineSummaries
-
- Type: Array of PipelineSummary structures
Contains a sorted list of
PipelineSummary
objects matching the specified filters. EachPipelineSummary
consists of PipelineArn, PipelineName, ExperimentName, PipelineDescription, CreationTime, LastModifiedTime, LastRunTime, and RoleArn. This list can be empty.
Errors
There are no errors described for this operation.
ListProcessingJobs
$result = $client->listProcessingJobs
([/* ... */]); $promise = $client->listProcessingJobsAsync
([/* ... */]);
Lists processing jobs that satisfy various filters.
Parameter Syntax
$result = $client->listProcessingJobs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'InProgress|Completed|Failed|Stopping|Stopped', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only processing jobs created after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only processing jobs created after the specified time.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only processing jobs modified after the specified time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only processing jobs modified before the specified time.
- MaxResults
-
- Type: int
The maximum number of processing jobs to return in the response.
- NameContains
-
- Type: string
A string in the processing job name. This filter returns only processing jobs whose name contains the specified string.
- NextToken
-
- Type: string
If the result of the previous
ListProcessingJobs
request was truncated, the response includes aNextToken
. To retrieve the next set of processing jobs, use the token in the next request. - SortBy
-
- Type: string
The field to sort results by. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results. The default is
Ascending
. - StatusEquals
-
- Type: string
A filter that retrieves only processing jobs with a specific status.
Result Syntax
[ 'NextToken' => '<string>', 'ProcessingJobSummaries' => [ [ 'CreationTime' => <DateTime>, 'ExitMessage' => '<string>', 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'ProcessingEndTime' => <DateTime>, 'ProcessingJobArn' => '<string>', 'ProcessingJobName' => '<string>', 'ProcessingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of processing jobs, use it in the subsequent request.
- ProcessingJobSummaries
-
- Required: Yes
- Type: Array of ProcessingJobSummary structures
An array of
ProcessingJobSummary
objects, each listing a processing job.
Errors
There are no errors described for this operation.
ListProjects
$result = $client->listProjects
([/* ... */]); $promise = $client->listProjectsAsync
([/* ... */]);
Gets a list of the projects in an Amazon Web Services account.
Parameter Syntax
$result = $client->listProjects([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns the projects that were created after a specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns the projects that were created before a specified time.
- MaxResults
-
- Type: int
The maximum number of projects to return in the response.
- NameContains
-
- Type: string
A filter that returns the projects whose name contains a specified string.
- NextToken
-
- Type: string
If the result of the previous
ListProjects
request was truncated, the response includes aNextToken
. To retrieve the next set of projects, use the token in the next request. - SortBy
-
- Type: string
The field by which to sort results. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results. The default is
Ascending
.
Result Syntax
[ 'NextToken' => '<string>', 'ProjectSummaryList' => [ [ 'CreationTime' => <DateTime>, 'ProjectArn' => '<string>', 'ProjectDescription' => '<string>', 'ProjectId' => '<string>', 'ProjectName' => '<string>', 'ProjectStatus' => 'Pending|CreateInProgress|CreateCompleted|CreateFailed|DeleteInProgress|DeleteFailed|DeleteCompleted|UpdateInProgress|UpdateCompleted|UpdateFailed', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the result of the previous
ListCompilationJobs
request was truncated, the response includes aNextToken
. To retrieve the next set of model compilation jobs, use the token in the next request. - ProjectSummaryList
-
- Required: Yes
- Type: Array of ProjectSummary structures
A list of summaries of projects.
Errors
There are no errors described for this operation.
ListResourceCatalogs
$result = $client->listResourceCatalogs
([/* ... */]); $promise = $client->listResourceCatalogsAsync
([/* ... */]);
Lists Amazon SageMaker Catalogs based on given filters and orders. The maximum number of ResourceCatalog
s viewable is 1000.
Parameter Syntax
$result = $client->listResourceCatalogs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'CreationTime', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Use this parameter to search for
ResourceCatalog
s created after a specific date and time. - CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Use this parameter to search for
ResourceCatalog
s created before a specific date and time. - MaxResults
-
- Type: int
The maximum number of results returned by
ListResourceCatalogs
. - NameContains
-
- Type: string
A string that partially matches one or more
ResourceCatalog
s names. FiltersResourceCatalog
by name. - NextToken
-
- Type: string
A token to resume pagination of
ListResourceCatalogs
results. - SortBy
-
- Type: string
The value on which the resource catalog list is sorted.
- SortOrder
-
- Type: string
The order in which the resource catalogs are listed.
Result Syntax
[ 'NextToken' => '<string>', 'ResourceCatalogs' => [ [ 'CreationTime' => <DateTime>, 'Description' => '<string>', 'ResourceCatalogArn' => '<string>', 'ResourceCatalogName' => '<string>', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
A token to resume pagination of
ListResourceCatalogs
results. - ResourceCatalogs
-
- Type: Array of ResourceCatalog structures
A list of the requested
ResourceCatalog
s.
Errors
There are no errors described for this operation.
ListSpaces
$result = $client->listSpaces
([/* ... */]); $promise = $client->listSpacesAsync
([/* ... */]);
Lists spaces.
Parameter Syntax
$result = $client->listSpaces([ 'DomainIdEquals' => '<string>', 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'CreationTime|LastModifiedTime', 'SortOrder' => 'Ascending|Descending', 'SpaceNameContains' => '<string>', ]);
Parameter Details
Members
- DomainIdEquals
-
- Type: string
A parameter to search for the domain ID.
- MaxResults
-
- Type: int
This parameter defines the maximum number of results that can be return in a single response. The
MaxResults
parameter is an upper bound, not a target. If there are more results available than the value specified, aNextToken
is provided in the response. TheNextToken
indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value forMaxResults
is 10. - NextToken
-
- Type: string
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
- SortBy
-
- Type: string
The parameter by which to sort the results. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for the results. The default is
Ascending
. - SpaceNameContains
-
- Type: string
A parameter by which to filter the results.
Result Syntax
[ 'NextToken' => '<string>', 'Spaces' => [ [ 'CreationTime' => <DateTime>, 'DomainId' => '<string>', 'LastModifiedTime' => <DateTime>, 'OwnershipSettingsSummary' => [ 'OwnerUserProfileName' => '<string>', ], 'SpaceDisplayName' => '<string>', 'SpaceName' => '<string>', 'SpaceSettingsSummary' => [ 'AppType' => 'JupyterServer|KernelGateway|DetailedProfiler|TensorBoard|CodeEditor|JupyterLab|RStudioServerPro|RSessionGateway|Canvas', 'SpaceStorageSettings' => [ 'EbsStorageSettings' => [ 'EbsVolumeSizeInGb' => <integer>, ], ], ], 'SpaceSharingSettingsSummary' => [ 'SharingType' => 'Private|Shared', ], 'Status' => 'Deleting|Failed|InService|Pending|Updating|Update_Failed|Delete_Failed', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
- Spaces
-
- Type: Array of SpaceDetails structures
The list of spaces.
Errors
There are no errors described for this operation.
ListStageDevices
$result = $client->listStageDevices
([/* ... */]); $promise = $client->listStageDevicesAsync
([/* ... */]);
Lists devices allocated to the stage, containing detailed device information and deployment status.
Parameter Syntax
$result = $client->listStageDevices([ 'EdgeDeploymentPlanName' => '<string>', // REQUIRED 'ExcludeDevicesDeployedInOtherStage' => true || false, 'MaxResults' => <integer>, 'NextToken' => '<string>', 'StageName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- EdgeDeploymentPlanName
-
- Required: Yes
- Type: string
The name of the edge deployment plan.
- ExcludeDevicesDeployedInOtherStage
-
- Type: boolean
Toggle for excluding devices deployed in other stages.
- MaxResults
-
- Type: int
The maximum number of requests to select.
- NextToken
-
- Type: string
The response from the last list when returning a list large enough to neeed tokening.
- StageName
-
- Required: Yes
- Type: string
The name of the stage in the deployment.
Result Syntax
[ 'DeviceDeploymentSummaries' => [ [ 'DeployedStageName' => '<string>', 'DeploymentStartTime' => <DateTime>, 'Description' => '<string>', 'DeviceArn' => '<string>', 'DeviceDeploymentStatus' => 'READYTODEPLOY|INPROGRESS|DEPLOYED|FAILED|STOPPING|STOPPED', 'DeviceDeploymentStatusMessage' => '<string>', 'DeviceFleetName' => '<string>', 'DeviceName' => '<string>', 'EdgeDeploymentPlanArn' => '<string>', 'EdgeDeploymentPlanName' => '<string>', 'StageName' => '<string>', ], // ... ], 'NextToken' => '<string>', ]
Result Details
Members
- DeviceDeploymentSummaries
-
- Required: Yes
- Type: Array of DeviceDeploymentSummary structures
List of summaries of devices allocated to the stage.
- NextToken
-
- Type: string
The token to use when calling the next page of results.
Errors
There are no errors described for this operation.
ListStudioLifecycleConfigs
$result = $client->listStudioLifecycleConfigs
([/* ... */]); $promise = $client->listStudioLifecycleConfigsAsync
([/* ... */]);
Lists the Amazon SageMaker Studio Lifecycle Configurations in your Amazon Web Services Account.
Parameter Syntax
$result = $client->listStudioLifecycleConfigs([ 'AppTypeEquals' => 'JupyterServer|KernelGateway|CodeEditor|JupyterLab', 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'ModifiedTimeAfter' => <integer || string || DateTime>, 'ModifiedTimeBefore' => <integer || string || DateTime>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'CreationTime|LastModifiedTime|Name', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- AppTypeEquals
-
- Type: string
A parameter to search for the App Type to which the Lifecycle Configuration is attached.
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only Lifecycle Configurations created on or after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only Lifecycle Configurations created on or before the specified time.
- MaxResults
-
- Type: int
The total number of items to return in the response. If the total number of items available is more than the value specified, a
NextToken
is provided in the response. To resume pagination, provide theNextToken
value in the as part of a subsequent call. The default value is 10. - ModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only Lifecycle Configurations modified after the specified time.
- ModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only Lifecycle Configurations modified before the specified time.
- NameContains
-
- Type: string
A string in the Lifecycle Configuration name. This filter returns only Lifecycle Configurations whose name contains the specified string.
- NextToken
-
- Type: string
If the previous call to ListStudioLifecycleConfigs didn't return the full set of Lifecycle Configurations, the call returns a token for getting the next set of Lifecycle Configurations.
- SortBy
-
- Type: string
The property used to sort results. The default value is CreationTime.
- SortOrder
-
- Type: string
The sort order. The default value is Descending.
Result Syntax
[ 'NextToken' => '<string>', 'StudioLifecycleConfigs' => [ [ 'CreationTime' => <DateTime>, 'LastModifiedTime' => <DateTime>, 'StudioLifecycleConfigAppType' => 'JupyterServer|KernelGateway|CodeEditor|JupyterLab', 'StudioLifecycleConfigArn' => '<string>', 'StudioLifecycleConfigName' => '<string>', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
- StudioLifecycleConfigs
-
- Type: Array of StudioLifecycleConfigDetails structures
A list of Lifecycle Configurations and their properties.
Errors
- ResourceInUse:
Resource being accessed is in use.
ListSubscribedWorkteams
$result = $client->listSubscribedWorkteams
([/* ... */]); $promise = $client->listSubscribedWorkteamsAsync
([/* ... */]);
Gets a list of the work teams that you are subscribed to in the Amazon Web Services Marketplace. The list may be empty if no work team satisfies the filter specified in the NameContains
parameter.
Parameter Syntax
$result = $client->listSubscribedWorkteams([ 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', ]);
Parameter Details
Members
- MaxResults
-
- Type: int
The maximum number of work teams to return in each page of the response.
- NameContains
-
- Type: string
A string in the work team name. This filter returns only work teams whose name contains the specified string.
- NextToken
-
- Type: string
If the result of the previous
ListSubscribedWorkteams
request was truncated, the response includes aNextToken
. To retrieve the next set of labeling jobs, use the token in the next request.
Result Syntax
[ 'NextToken' => '<string>', 'SubscribedWorkteams' => [ [ 'ListingId' => '<string>', 'MarketplaceDescription' => '<string>', 'MarketplaceTitle' => '<string>', 'SellerName' => '<string>', 'WorkteamArn' => '<string>', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
- SubscribedWorkteams
-
- Required: Yes
- Type: Array of SubscribedWorkteam structures
An array of
Workteam
objects, each describing a work team.
Errors
There are no errors described for this operation.
ListTags
$result = $client->listTags
([/* ... */]); $promise = $client->listTagsAsync
([/* ... */]);
Returns the tags for the specified SageMaker resource.
Parameter Syntax
$result = $client->listTags([ 'MaxResults' => <integer>, 'NextToken' => '<string>', 'ResourceArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
- MaxResults
-
- Type: int
Maximum number of tags to return.
- NextToken
-
- Type: string
If the response to the previous
ListTags
request is truncated, SageMaker returns this token. To retrieve the next set of tags, use it in the subsequent request. - ResourceArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.
Result Syntax
[ 'NextToken' => '<string>', 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If response is truncated, SageMaker includes a token in the response. You can use this token in your subsequent request to fetch next set of tokens.
- Tags
-
- Type: Array of Tag structures
An array of
Tag
objects, each with a tag key and a value.
Errors
There are no errors described for this operation.
ListTrainingJobs
$result = $client->listTrainingJobs
([/* ... */]); $promise = $client->listTrainingJobsAsync
([/* ... */]);
Lists training jobs.
When StatusEquals
and MaxResults
are set at the same time, the MaxResults
number of training jobs are first retrieved ignoring the StatusEquals
parameter and then they are filtered by the StatusEquals
parameter, which is returned as a response.
For example, if ListTrainingJobs
is invoked with the following parameters:
{ ... MaxResults: 100, StatusEquals: InProgress ... }
First, 100 trainings jobs with any status, including those other than InProgress
, are selected (sorted according to the creation time, from the most current to the oldest). Next, those with a status of InProgress
are returned.
You can quickly test the API using the following Amazon Web Services CLI code.
aws sagemaker list-training-jobs --max-results 100 --status-equals InProgress
Parameter Syntax
$result = $client->listTrainingJobs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'InProgress|Completed|Failed|Stopping|Stopped', 'WarmPoolStatusEquals' => 'Available|Terminated|Reused|InUse', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only training jobs created after the specified time (timestamp).
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only training jobs created before the specified time (timestamp).
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only training jobs modified after the specified time (timestamp).
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only training jobs modified before the specified time (timestamp).
- MaxResults
-
- Type: int
The maximum number of training jobs to return in the response.
- NameContains
-
- Type: string
A string in the training job name. This filter returns only training jobs whose name contains the specified string.
- NextToken
-
- Type: string
If the result of the previous
ListTrainingJobs
request was truncated, the response includes aNextToken
. To retrieve the next set of training jobs, use the token in the next request. - SortBy
-
- Type: string
The field to sort results by. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results. The default is
Ascending
. - StatusEquals
-
- Type: string
A filter that retrieves only training jobs with a specific status.
- WarmPoolStatusEquals
-
- Type: string
A filter that retrieves only training jobs with a specific warm pool status.
Result Syntax
[ 'NextToken' => '<string>', 'TrainingJobSummaries' => [ [ 'CreationTime' => <DateTime>, 'LastModifiedTime' => <DateTime>, 'TrainingEndTime' => <DateTime>, 'TrainingJobArn' => '<string>', 'TrainingJobName' => '<string>', 'TrainingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'WarmPoolStatus' => [ 'ResourceRetainedBillableTimeInSeconds' => <integer>, 'ReusedByJob' => '<string>', 'Status' => 'Available|Terminated|Reused|InUse', ], ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
- TrainingJobSummaries
-
- Required: Yes
- Type: Array of TrainingJobSummary structures
An array of
TrainingJobSummary
objects, each listing a training job.
Errors
There are no errors described for this operation.
ListTrainingJobsForHyperParameterTuningJob
$result = $client->listTrainingJobsForHyperParameterTuningJob
([/* ... */]); $promise = $client->listTrainingJobsForHyperParameterTuningJobAsync
([/* ... */]);
Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.
Parameter Syntax
$result = $client->listTrainingJobsForHyperParameterTuningJob([ 'HyperParameterTuningJobName' => '<string>', // REQUIRED 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status|FinalObjectiveMetricValue', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'InProgress|Completed|Failed|Stopping|Stopped', ]);
Parameter Details
Members
- HyperParameterTuningJobName
-
- Required: Yes
- Type: string
The name of the tuning job whose training jobs you want to list.
- MaxResults
-
- Type: int
The maximum number of training jobs to return. The default value is 10.
- NextToken
-
- Type: string
If the result of the previous
ListTrainingJobsForHyperParameterTuningJob
request was truncated, the response includes aNextToken
. To retrieve the next set of training jobs, use the token in the next request. - SortBy
-
- Type: string
The field to sort results by. The default is
Name
.If the value of this field is
FinalObjectiveMetricValue
, any training jobs that did not return an objective metric are not listed. - SortOrder
-
- Type: string
The sort order for results. The default is
Ascending
. - StatusEquals
-
- Type: string
A filter that returns only training jobs with the specified status.
Result Syntax
[ 'NextToken' => '<string>', 'TrainingJobSummaries' => [ [ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'FinalHyperParameterTuningJobObjectiveMetric' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', 'Value' => <float>, ], 'ObjectiveStatus' => 'Succeeded|Pending|Failed', 'TrainingEndTime' => <DateTime>, 'TrainingJobArn' => '<string>', 'TrainingJobDefinitionName' => '<string>', 'TrainingJobName' => '<string>', 'TrainingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TrainingStartTime' => <DateTime>, 'TunedHyperParameters' => ['<string>', ...], 'TuningJobName' => '<string>', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the result of this
ListTrainingJobsForHyperParameterTuningJob
request was truncated, the response includes aNextToken
. To retrieve the next set of training jobs, use the token in the next request. - TrainingJobSummaries
-
- Required: Yes
- Type: Array of HyperParameterTrainingJobSummary structures
A list of TrainingJobSummary objects that describe the training jobs that the
ListTrainingJobsForHyperParameterTuningJob
request returned.
Errors
- ResourceNotFound:
Resource being access is not found.
ListTransformJobs
$result = $client->listTransformJobs
([/* ... */]); $promise = $client->listTransformJobsAsync
([/* ... */]);
Lists transform jobs.
Parameter Syntax
$result = $client->listTransformJobs([ 'CreationTimeAfter' => <integer || string || DateTime>, 'CreationTimeBefore' => <integer || string || DateTime>, 'LastModifiedTimeAfter' => <integer || string || DateTime>, 'LastModifiedTimeBefore' => <integer || string || DateTime>, 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime|Status', 'SortOrder' => 'Ascending|Descending', 'StatusEquals' => 'InProgress|Completed|Failed|Stopping|Stopped', ]);
Parameter Details
Members
- CreationTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only transform jobs created after the specified time.
- CreationTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only transform jobs created before the specified time.
- LastModifiedTimeAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only transform jobs modified after the specified time.
- LastModifiedTimeBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only transform jobs modified before the specified time.
- MaxResults
-
- Type: int
The maximum number of transform jobs to return in the response. The default value is
10
. - NameContains
-
- Type: string
A string in the transform job name. This filter returns only transform jobs whose name contains the specified string.
- NextToken
-
- Type: string
If the result of the previous
ListTransformJobs
request was truncated, the response includes aNextToken
. To retrieve the next set of transform jobs, use the token in the next request. - SortBy
-
- Type: string
The field to sort results by. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results. The default is
Descending
. - StatusEquals
-
- Type: string
A filter that retrieves only transform jobs with a specific status.
Result Syntax
[ 'NextToken' => '<string>', 'TransformJobSummaries' => [ [ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'TransformEndTime' => <DateTime>, 'TransformJobArn' => '<string>', 'TransformJobName' => '<string>', 'TransformJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of transform jobs, use it in the next request.
- TransformJobSummaries
-
- Required: Yes
- Type: Array of TransformJobSummary structures
An array of
TransformJobSummary
objects.
Errors
There are no errors described for this operation.
ListTrialComponents
$result = $client->listTrialComponents
([/* ... */]); $promise = $client->listTrialComponentsAsync
([/* ... */]);
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
Parameter Syntax
$result = $client->listTrialComponents([ 'CreatedAfter' => <integer || string || DateTime>, 'CreatedBefore' => <integer || string || DateTime>, 'ExperimentName' => '<string>', 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', 'SourceArn' => '<string>', 'TrialName' => '<string>', ]);
Parameter Details
Members
- CreatedAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only components created after the specified time.
- CreatedBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only components created before the specified time.
- ExperimentName
-
- Type: string
A filter that returns only components that are part of the specified experiment. If you specify
ExperimentName
, you can't filter bySourceArn
orTrialName
. - MaxResults
-
- Type: int
The maximum number of components to return in the response. The default value is 10.
- NextToken
-
- Type: string
If the previous call to
ListTrialComponents
didn't return the full set of components, the call returns a token for getting the next set of components. - SortBy
-
- Type: string
The property used to sort results. The default value is
CreationTime
. - SortOrder
-
- Type: string
The sort order. The default value is
Descending
. - SourceArn
-
- Type: string
A filter that returns only components that have the specified source Amazon Resource Name (ARN). If you specify
SourceArn
, you can't filter byExperimentName
orTrialName
. - TrialName
-
- Type: string
A filter that returns only components that are part of the specified trial. If you specify
TrialName
, you can't filter byExperimentName
orSourceArn
.
Result Syntax
[ 'NextToken' => '<string>', 'TrialComponentSummaries' => [ [ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'DisplayName' => '<string>', 'EndTime' => <DateTime>, 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'StartTime' => <DateTime>, 'Status' => [ 'Message' => '<string>', 'PrimaryStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', ], 'TrialComponentArn' => '<string>', 'TrialComponentName' => '<string>', 'TrialComponentSource' => [ 'SourceArn' => '<string>', 'SourceType' => '<string>', ], ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
A token for getting the next set of components, if there are any.
- TrialComponentSummaries
-
- Type: Array of TrialComponentSummary structures
A list of the summaries of your trial components.
Errors
- ResourceNotFound:
Resource being access is not found.
ListTrials
$result = $client->listTrials
([/* ... */]); $promise = $client->listTrialsAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->listTrials([ 'CreatedAfter' => <integer || string || DateTime>, 'CreatedBefore' => <integer || string || DateTime>, 'ExperimentName' => '<string>', 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'Name|CreationTime', 'SortOrder' => 'Ascending|Descending', 'TrialComponentName' => '<string>', ]);
Parameter Details
Members
- CreatedAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only trials created after the specified time.
- CreatedBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A filter that returns only trials created before the specified time.
- ExperimentName
-
- Type: string
A filter that returns only trials that are part of the specified experiment.
- MaxResults
-
- Type: int
The maximum number of trials to return in the response. The default value is 10.
- NextToken
-
- Type: string
If the previous call to
ListTrials
didn't return the full set of trials, the call returns a token for getting the next set of trials. - SortBy
-
- Type: string
The property used to sort results. The default value is
CreationTime
. - SortOrder
-
- Type: string
The sort order. The default value is
Descending
. - TrialComponentName
-
- Type: string
A filter that returns only trials that are associated with the specified trial component.
Result Syntax
[ 'NextToken' => '<string>', 'TrialSummaries' => [ [ 'CreationTime' => <DateTime>, 'DisplayName' => '<string>', 'LastModifiedTime' => <DateTime>, 'TrialArn' => '<string>', 'TrialName' => '<string>', 'TrialSource' => [ 'SourceArn' => '<string>', 'SourceType' => '<string>', ], ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
A token for getting the next set of trials, if there are any.
- TrialSummaries
-
- Type: Array of TrialSummary structures
A list of the summaries of your trials.
Errors
- ResourceNotFound:
Resource being access is not found.
ListUserProfiles
$result = $client->listUserProfiles
([/* ... */]); $promise = $client->listUserProfilesAsync
([/* ... */]);
Lists user profiles.
Parameter Syntax
$result = $client->listUserProfiles([ 'DomainIdEquals' => '<string>', 'MaxResults' => <integer>, 'NextToken' => '<string>', 'SortBy' => 'CreationTime|LastModifiedTime', 'SortOrder' => 'Ascending|Descending', 'UserProfileNameContains' => '<string>', ]);
Parameter Details
Members
- DomainIdEquals
-
- Type: string
A parameter by which to filter the results.
- MaxResults
-
- Type: int
This parameter defines the maximum number of results that can be return in a single response. The
MaxResults
parameter is an upper bound, not a target. If there are more results available than the value specified, aNextToken
is provided in the response. TheNextToken
indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value forMaxResults
is 10. - NextToken
-
- Type: string
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
- SortBy
-
- Type: string
The parameter by which to sort the results. The default is CreationTime.
- SortOrder
-
- Type: string
The sort order for the results. The default is Ascending.
- UserProfileNameContains
-
- Type: string
A parameter by which to filter the results.
Result Syntax
[ 'NextToken' => '<string>', 'UserProfiles' => [ [ 'CreationTime' => <DateTime>, 'DomainId' => '<string>', 'LastModifiedTime' => <DateTime>, 'Status' => 'Deleting|Failed|InService|Pending|Updating|Update_Failed|Delete_Failed', 'UserProfileName' => '<string>', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
- UserProfiles
-
- Type: Array of UserProfileDetails structures
The list of user profiles.
Errors
There are no errors described for this operation.
ListWorkforces
$result = $client->listWorkforces
([/* ... */]); $promise = $client->listWorkforcesAsync
([/* ... */]);
Use this operation to list all private and vendor workforces in an Amazon Web Services Region. Note that you can only have one private workforce per Amazon Web Services Region.
Parameter Syntax
$result = $client->listWorkforces([ 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreateDate', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- MaxResults
-
- Type: int
The maximum number of workforces returned in the response.
- NameContains
-
- Type: string
A filter you can use to search for workforces using part of the workforce name.
- NextToken
-
- Type: string
A token to resume pagination.
- SortBy
-
- Type: string
Sort workforces using the workforce name or creation date.
- SortOrder
-
- Type: string
Sort workforces in ascending or descending order.
Result Syntax
[ 'NextToken' => '<string>', 'Workforces' => [ [ 'CognitoConfig' => [ 'ClientId' => '<string>', 'UserPool' => '<string>', ], 'CreateDate' => <DateTime>, 'FailureReason' => '<string>', 'LastUpdatedDate' => <DateTime>, 'OidcConfig' => [ 'AuthenticationRequestExtraParams' => ['<string>', ...], 'AuthorizationEndpoint' => '<string>', 'ClientId' => '<string>', 'Issuer' => '<string>', 'JwksUri' => '<string>', 'LogoutEndpoint' => '<string>', 'Scope' => '<string>', 'TokenEndpoint' => '<string>', 'UserInfoEndpoint' => '<string>', ], 'SourceIpConfig' => [ 'Cidrs' => ['<string>', ...], ], 'Status' => 'Initializing|Updating|Deleting|Failed|Active', 'SubDomain' => '<string>', 'WorkforceArn' => '<string>', 'WorkforceName' => '<string>', 'WorkforceVpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], 'VpcEndpointId' => '<string>', 'VpcId' => '<string>', ], ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
A token to resume pagination.
- Workforces
-
- Required: Yes
- Type: Array of Workforce structures
A list containing information about your workforce.
Errors
There are no errors described for this operation.
ListWorkteams
$result = $client->listWorkteams
([/* ... */]); $promise = $client->listWorkteamsAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->listWorkteams([ 'MaxResults' => <integer>, 'NameContains' => '<string>', 'NextToken' => '<string>', 'SortBy' => 'Name|CreateDate', 'SortOrder' => 'Ascending|Descending', ]);
Parameter Details
Members
- MaxResults
-
- Type: int
The maximum number of work teams to return in each page of the response.
- NameContains
-
- Type: string
A string in the work team's name. This filter returns only work teams whose name contains the specified string.
- NextToken
-
- Type: string
If the result of the previous
ListWorkteams
request was truncated, the response includes aNextToken
. To retrieve the next set of labeling jobs, use the token in the next request. - SortBy
-
- Type: string
The field to sort results by. The default is
CreationTime
. - SortOrder
-
- Type: string
The sort order for results. The default is
Ascending
.
Result Syntax
[ 'NextToken' => '<string>', 'Workteams' => [ [ 'CreateDate' => <DateTime>, 'Description' => '<string>', 'LastUpdatedDate' => <DateTime>, 'MemberDefinitions' => [ [ 'CognitoMemberDefinition' => [ 'ClientId' => '<string>', 'UserGroup' => '<string>', 'UserPool' => '<string>', ], 'OidcMemberDefinition' => [ 'Groups' => ['<string>', ...], ], ], // ... ], 'NotificationConfiguration' => [ 'NotificationTopicArn' => '<string>', ], 'ProductListingIds' => ['<string>', ...], 'SubDomain' => '<string>', 'WorkerAccessConfiguration' => [ 'S3Presign' => [ 'IamPolicyConstraints' => [ 'SourceIp' => 'Enabled|Disabled', 'VpcSourceIp' => 'Enabled|Disabled', ], ], ], 'WorkforceArn' => '<string>', 'WorkteamArn' => '<string>', 'WorkteamName' => '<string>', ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
- Workteams
-
- Required: Yes
- Type: Array of Workteam structures
An array of
Workteam
objects, each describing a work team.
Errors
There are no errors described for this operation.
PutModelPackageGroupPolicy
$result = $client->putModelPackageGroupPolicy
([/* ... */]); $promise = $client->putModelPackageGroupPolicyAsync
([/* ... */]);
Adds a resouce policy to control access to a model group. For information about resoure policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
Parameter Syntax
$result = $client->putModelPackageGroupPolicy([ 'ModelPackageGroupName' => '<string>', // REQUIRED 'ResourcePolicy' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ModelPackageGroupName
-
- Required: Yes
- Type: string
The name of the model group to add a resource policy to.
- ResourcePolicy
-
- Required: Yes
- Type: string
The resource policy for the model group.
Result Syntax
[ 'ModelPackageGroupArn' => '<string>', ]
Result Details
Members
- ModelPackageGroupArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model package group.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
QueryLineage
$result = $client->queryLineage
([/* ... */]); $promise = $client->queryLineageAsync
([/* ... */]);
Use this action to inspect your lineage and discover relationships between entities. For more information, see Querying Lineage Entities in the Amazon SageMaker Developer Guide.
Parameter Syntax
$result = $client->queryLineage([ 'Direction' => 'Both|Ascendants|Descendants', 'Filters' => [ 'CreatedAfter' => <integer || string || DateTime>, 'CreatedBefore' => <integer || string || DateTime>, 'LineageTypes' => ['<string>', ...], 'ModifiedAfter' => <integer || string || DateTime>, 'ModifiedBefore' => <integer || string || DateTime>, 'Properties' => ['<string>', ...], 'Types' => ['<string>', ...], ], 'IncludeEdges' => true || false, 'MaxDepth' => <integer>, 'MaxResults' => <integer>, 'NextToken' => '<string>', 'StartArns' => ['<string>', ...], ]);
Parameter Details
Members
- Direction
-
- Type: string
Associations between lineage entities have a direction. This parameter determines the direction from the StartArn(s) that the query traverses.
- Filters
-
- Type: QueryFilters structure
A set of filtering parameters that allow you to specify which entities should be returned.
-
Properties - Key-value pairs to match on the lineage entities' properties.
-
LineageTypes - A set of lineage entity types to match on. For example:
TrialComponent
,Artifact
, orContext
. -
CreatedBefore - Filter entities created before this date.
-
ModifiedBefore - Filter entities modified before this date.
-
ModifiedAfter - Filter entities modified after this date.
- IncludeEdges
-
- Type: boolean
Setting this value to
True
retrieves not only the entities of interest but also the Associations and lineage entities on the path. Set toFalse
to only return lineage entities that match your query. - MaxDepth
-
- Type: int
The maximum depth in lineage relationships from the
StartArns
that are traversed. Depth is a measure of the number ofAssociations
from theStartArn
entity to the matched results. - MaxResults
-
- Type: int
Limits the number of vertices in the results. Use the
NextToken
in a response to to retrieve the next page of results. - NextToken
-
- Type: string
Limits the number of vertices in the request. Use the
NextToken
in a response to to retrieve the next page of results. - StartArns
-
- Type: Array of strings
A list of resource Amazon Resource Name (ARN) that represent the starting point for your lineage query.
Result Syntax
[ 'Edges' => [ [ 'AssociationType' => 'ContributedTo|AssociatedWith|DerivedFrom|Produced|SameAs', 'DestinationArn' => '<string>', 'SourceArn' => '<string>', ], // ... ], 'NextToken' => '<string>', 'Vertices' => [ [ 'Arn' => '<string>', 'LineageType' => 'TrialComponent|Artifact|Context|Action', 'Type' => '<string>', ], // ... ], ]
Result Details
Members
- Edges
-
- Type: Array of Edge structures
A list of edges that connect vertices in the response.
- NextToken
-
- Type: string
Limits the number of vertices in the response. Use the
NextToken
in a response to to retrieve the next page of results. - Vertices
-
- Type: Array of Vertex structures
A list of vertices connected to the start entity(ies) in the lineage graph.
Errors
- ResourceNotFound:
Resource being access is not found.
RegisterDevices
$result = $client->registerDevices
([/* ... */]); $promise = $client->registerDevicesAsync
([/* ... */]);
Register devices.
Parameter Syntax
$result = $client->registerDevices([ 'DeviceFleetName' => '<string>', // REQUIRED 'Devices' => [ // REQUIRED [ 'Description' => '<string>', 'DeviceName' => '<string>', // REQUIRED 'IotThingName' => '<string>', ], // ... ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
RenderUiTemplate
$result = $client->renderUiTemplate
([/* ... */]); $promise = $client->renderUiTemplateAsync
([/* ... */]);
Renders the UI template so that you can preview the worker's experience.
Parameter Syntax
$result = $client->renderUiTemplate([ 'HumanTaskUiArn' => '<string>', 'RoleArn' => '<string>', // REQUIRED 'Task' => [ // REQUIRED 'Input' => '<string>', // REQUIRED ], 'UiTemplate' => [ 'Content' => '<string>', // REQUIRED ], ]);
Parameter Details
Members
- HumanTaskUiArn
-
- Type: string
The
HumanTaskUiArn
of the worker UI that you want to render. Do not provide aHumanTaskUiArn
if you use theUiTemplate
parameter.See a list of available Human Ui Amazon Resource Names (ARNs) in UiConfig.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) that has access to the S3 objects that are used by the template.
- Task
-
- Required: Yes
- Type: RenderableTask structure
A
RenderableTask
object containing a representative task to render. - UiTemplate
-
- Type: UiTemplate structure
A
Template
object containing the worker UI template to render.
Result Syntax
[ 'Errors' => [ [ 'Code' => '<string>', 'Message' => '<string>', ], // ... ], 'RenderedContent' => '<string>', ]
Result Details
Members
- Errors
-
- Required: Yes
- Type: Array of RenderingError structures
A list of one or more
RenderingError
objects if any were encountered while rendering the template. If there were no errors, the list is empty. - RenderedContent
-
- Required: Yes
- Type: string
A Liquid template that renders the HTML for the worker UI.
Errors
- ResourceNotFound:
Resource being access is not found.
RetryPipelineExecution
$result = $client->retryPipelineExecution
([/* ... */]); $promise = $client->retryPipelineExecutionAsync
([/* ... */]);
Retry the execution of the pipeline.
Parameter Syntax
$result = $client->retryPipelineExecution([ 'ClientRequestToken' => '<string>', // REQUIRED 'ParallelismConfiguration' => [ 'MaxParallelExecutionSteps' => <integer>, // REQUIRED ], 'PipelineExecutionArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ClientRequestToken
-
- Required: Yes
- Type: string
A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
- ParallelismConfiguration
-
- Type: ParallelismConfiguration structure
This configuration, if specified, overrides the parallelism configuration of the parent pipeline.
- PipelineExecutionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
Result Syntax
[ 'PipelineExecutionArn' => '<string>', ]
Result Details
Members
- PipelineExecutionArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
Search
$result = $client->search
([/* ... */]); $promise = $client->searchAsync
([/* ... */]);
Finds 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.
The Search API may provide access to otherwise restricted data. See Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference for more information.
Parameter Syntax
$result = $client->search([ 'CrossAccountFilterOption' => 'SameAccount|CrossAccount', 'MaxResults' => <integer>, 'NextToken' => '<string>', 'Resource' => 'TrainingJob|Experiment|ExperimentTrial|ExperimentTrialComponent|Endpoint|Model|ModelPackage|ModelPackageGroup|Pipeline|PipelineExecution|FeatureGroup|FeatureMetadata|Image|ImageVersion|Project|HyperParameterTuningJob|ModelCard', // REQUIRED 'SearchExpression' => [ 'Filters' => [ [ 'Name' => '<string>', // REQUIRED 'Operator' => 'Equals|NotEquals|GreaterThan|GreaterThanOrEqualTo|LessThan|LessThanOrEqualTo|Contains|Exists|NotExists|In', 'Value' => '<string>', ], // ... ], 'NestedFilters' => [ [ 'Filters' => [ // REQUIRED [ 'Name' => '<string>', // REQUIRED 'Operator' => 'Equals|NotEquals|GreaterThan|GreaterThanOrEqualTo|LessThan|LessThanOrEqualTo|Contains|Exists|NotExists|In', 'Value' => '<string>', ], // ... ], 'NestedPropertyName' => '<string>', // REQUIRED ], // ... ], 'Operator' => 'And|Or', 'SubExpressions' => [ [...], // RECURSIVE // ... ], ], 'SortBy' => '<string>', 'SortOrder' => 'Ascending|Descending', 'VisibilityConditions' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ]);
Parameter Details
Members
- CrossAccountFilterOption
-
- Type: string
A cross account filter option. When the value is
"CrossAccount"
the search results will only include resources made discoverable to you from other accounts. When the value is"SameAccount"
ornull
the search results will only include resources from your account. Default isnull
. For more information on searching for resources made discoverable to your account, see Search discoverable resources in the SageMaker Developer Guide. The maximum number ofResourceCatalog
s viewable is 1000. - MaxResults
-
- Type: int
The maximum number of results to return.
- NextToken
-
- Type: string
If more than
MaxResults
resources match the specifiedSearchExpression
, the response includes aNextToken
. TheNextToken
can be passed to the nextSearchRequest
to continue retrieving results. - Resource
-
- Required: Yes
- Type: string
The name of the SageMaker resource to search for.
- SearchExpression
-
- Type: SearchExpression structure
A Boolean conditional statement. Resources must satisfy this condition to be included in search results. You must provide at least one subexpression, filter, or nested filter. The maximum number of recursive
SubExpressions
,NestedFilters
, andFilters
that can be included in aSearchExpression
object is 50. - SortBy
-
- Type: string
The name of the resource property used to sort the
SearchResults
. The default isLastModifiedTime
. - SortOrder
-
- Type: string
How
SearchResults
are ordered. Valid values areAscending
orDescending
. The default isDescending
. - VisibilityConditions
-
- Type: Array of VisibilityConditions structures
Limits the results of your search request to the resources that you can access.
Result Syntax
[ 'NextToken' => '<string>', 'Results' => [ [ 'Endpoint' => [ 'CreationTime' => <DateTime>, 'DataCaptureConfig' => [ 'CaptureStatus' => 'Started|Stopped', 'CurrentSamplingPercentage' => <integer>, 'DestinationS3Uri' => '<string>', 'EnableCapture' => true || false, 'KmsKeyId' => '<string>', ], 'EndpointArn' => '<string>', 'EndpointConfigName' => '<string>', 'EndpointName' => '<string>', 'EndpointStatus' => 'OutOfService|Creating|Updating|SystemUpdating|RollingBack|InService|Deleting|Failed|UpdateRollbackFailed', 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'MonitoringSchedules' => [ [ 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'LastMonitoringExecutionSummary' => [ 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'MonitoringExecutionStatus' => 'Pending|Completed|CompletedWithViolations|InProgress|Failed|Stopping|Stopped', 'MonitoringJobDefinitionName' => '<string>', 'MonitoringScheduleName' => '<string>', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'ProcessingJobArn' => '<string>', 'ScheduledTime' => <DateTime>, ], 'MonitoringScheduleArn' => '<string>', 'MonitoringScheduleConfig' => [ 'MonitoringJobDefinition' => [ 'BaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], 'StatisticsResource' => [ 'S3Uri' => '<string>', ], ], 'Environment' => ['<string>', ...], 'MonitoringAppSpecification' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ImageUri' => '<string>', 'PostAnalyticsProcessorSourceUri' => '<string>', 'RecordPreprocessorSourceUri' => '<string>', ], 'MonitoringInputs' => [ [ 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', 'DatasetFormat' => [ 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], ], // ... ], 'MonitoringOutputConfig' => [ 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ [ 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'MonitoringResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], ], 'MonitoringJobDefinitionName' => '<string>', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'ScheduleConfig' => [ 'DataAnalysisEndTime' => '<string>', 'DataAnalysisStartTime' => '<string>', 'ScheduleExpression' => '<string>', ], ], 'MonitoringScheduleName' => '<string>', 'MonitoringScheduleStatus' => 'Pending|Failed|Scheduled|Stopped', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], // ... ], 'ProductionVariants' => [ [ 'CurrentInstanceCount' => <integer>, 'CurrentServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'CurrentWeight' => <float>, 'DeployedImages' => [ [ 'ResolutionTime' => <DateTime>, 'ResolvedImage' => '<string>', 'SpecifiedImage' => '<string>', ], // ... ], 'DesiredInstanceCount' => <integer>, 'DesiredServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'DesiredWeight' => <float>, 'ManagedInstanceScaling' => [ 'MaxInstanceCount' => <integer>, 'MinInstanceCount' => <integer>, 'Status' => 'ENABLED|DISABLED', ], 'RoutingConfig' => [ 'RoutingStrategy' => 'LEAST_OUTSTANDING_REQUESTS|RANDOM', ], 'VariantName' => '<string>', 'VariantStatus' => [ [ 'StartTime' => <DateTime>, 'Status' => 'Creating|Updating|Deleting|ActivatingTraffic|Baking', 'StatusMessage' => '<string>', ], // ... ], ], // ... ], 'ShadowProductionVariants' => [ [ 'CurrentInstanceCount' => <integer>, 'CurrentServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'CurrentWeight' => <float>, 'DeployedImages' => [ [ 'ResolutionTime' => <DateTime>, 'ResolvedImage' => '<string>', 'SpecifiedImage' => '<string>', ], // ... ], 'DesiredInstanceCount' => <integer>, 'DesiredServerlessConfig' => [ 'MaxConcurrency' => <integer>, 'MemorySizeInMB' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'DesiredWeight' => <float>, 'ManagedInstanceScaling' => [ 'MaxInstanceCount' => <integer>, 'MinInstanceCount' => <integer>, 'Status' => 'ENABLED|DISABLED', ], 'RoutingConfig' => [ 'RoutingStrategy' => 'LEAST_OUTSTANDING_REQUESTS|RANDOM', ], 'VariantName' => '<string>', 'VariantStatus' => [ [ 'StartTime' => <DateTime>, 'Status' => 'Creating|Updating|Deleting|ActivatingTraffic|Baking', 'StatusMessage' => '<string>', ], // ... ], ], // ... ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], 'Experiment' => [ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'Description' => '<string>', 'DisplayName' => '<string>', 'ExperimentArn' => '<string>', 'ExperimentName' => '<string>', 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'Source' => [ 'SourceArn' => '<string>', 'SourceType' => '<string>', ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], 'FeatureGroup' => [ 'CreationTime' => <DateTime>, 'Description' => '<string>', 'EventTimeFeatureName' => '<string>', 'FailureReason' => '<string>', 'FeatureDefinitions' => [ [ 'CollectionConfig' => [ 'VectorConfig' => [ 'Dimension' => <integer>, ], ], 'CollectionType' => 'List|Set|Vector', 'FeatureName' => '<string>', 'FeatureType' => 'Integral|Fractional|String', ], // ... ], 'FeatureGroupArn' => '<string>', 'FeatureGroupName' => '<string>', 'FeatureGroupStatus' => 'Creating|Created|CreateFailed|Deleting|DeleteFailed', 'LastModifiedTime' => <DateTime>, 'LastUpdateStatus' => [ 'FailureReason' => '<string>', 'Status' => 'Successful|Failed|InProgress', ], 'OfflineStoreConfig' => [ 'DataCatalogConfig' => [ 'Catalog' => '<string>', 'Database' => '<string>', 'TableName' => '<string>', ], 'DisableGlueTableCreation' => true || false, 'S3StorageConfig' => [ 'KmsKeyId' => '<string>', 'ResolvedOutputS3Uri' => '<string>', 'S3Uri' => '<string>', ], 'TableFormat' => 'Default|Glue|Iceberg', ], 'OfflineStoreStatus' => [ 'BlockedReason' => '<string>', 'Status' => 'Active|Blocked|Disabled', ], 'OnlineStoreConfig' => [ 'EnableOnlineStore' => true || false, 'SecurityConfig' => [ 'KmsKeyId' => '<string>', ], 'StorageType' => 'Standard|InMemory', 'TtlDuration' => [ 'Unit' => 'Seconds|Minutes|Hours|Days|Weeks', 'Value' => <integer>, ], ], 'RecordIdentifierFeatureName' => '<string>', 'RoleArn' => '<string>', 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], 'FeatureMetadata' => [ 'CreationTime' => <DateTime>, 'Description' => '<string>', 'FeatureGroupArn' => '<string>', 'FeatureGroupName' => '<string>', 'FeatureName' => '<string>', 'FeatureType' => 'Integral|Fractional|String', 'LastModifiedTime' => <DateTime>, 'Parameters' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], 'HyperParameterTuningJob' => [ 'BestTrainingJob' => [ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'FinalHyperParameterTuningJobObjectiveMetric' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', 'Value' => <float>, ], 'ObjectiveStatus' => 'Succeeded|Pending|Failed', 'TrainingEndTime' => <DateTime>, 'TrainingJobArn' => '<string>', 'TrainingJobDefinitionName' => '<string>', 'TrainingJobName' => '<string>', 'TrainingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TrainingStartTime' => <DateTime>, 'TunedHyperParameters' => ['<string>', ...], 'TuningJobName' => '<string>', ], 'ConsumedResources' => [ 'RuntimeInSeconds' => <integer>, ], 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'HyperParameterTuningEndTime' => <DateTime>, 'HyperParameterTuningJobArn' => '<string>', 'HyperParameterTuningJobConfig' => [ 'HyperParameterTuningJobObjective' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', ], 'ParameterRanges' => [ 'AutoParameters' => [ [ 'Name' => '<string>', 'ValueHint' => '<string>', ], // ... ], 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', 'Values' => ['<string>', ...], ], // ... ], 'ContinuousParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], 'IntegerParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], ], 'RandomSeed' => <integer>, 'ResourceLimits' => [ 'MaxNumberOfTrainingJobs' => <integer>, 'MaxParallelTrainingJobs' => <integer>, 'MaxRuntimeInSeconds' => <integer>, ], 'Strategy' => 'Bayesian|Random|Hyperband|Grid', 'StrategyConfig' => [ 'HyperbandStrategyConfig' => [ 'MaxResource' => <integer>, 'MinResource' => <integer>, ], ], 'TrainingJobEarlyStoppingType' => 'Off|Auto', 'TuningJobCompletionCriteria' => [ 'BestObjectiveNotImproving' => [ 'MaxNumberOfTrainingJobsNotImproving' => <integer>, ], 'ConvergenceDetected' => [ 'CompleteOnConvergence' => 'Disabled|Enabled', ], 'TargetObjectiveMetricValue' => <float>, ], ], 'HyperParameterTuningJobName' => '<string>', 'HyperParameterTuningJobStatus' => 'Completed|InProgress|Failed|Stopped|Stopping|Deleting|DeleteFailed', 'LastModifiedTime' => <DateTime>, 'ObjectiveStatusCounters' => [ 'Failed' => <integer>, 'Pending' => <integer>, 'Succeeded' => <integer>, ], 'OverallBestTrainingJob' => [ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'FinalHyperParameterTuningJobObjectiveMetric' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', 'Value' => <float>, ], 'ObjectiveStatus' => 'Succeeded|Pending|Failed', 'TrainingEndTime' => <DateTime>, 'TrainingJobArn' => '<string>', 'TrainingJobDefinitionName' => '<string>', 'TrainingJobName' => '<string>', 'TrainingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TrainingStartTime' => <DateTime>, 'TunedHyperParameters' => ['<string>', ...], 'TuningJobName' => '<string>', ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], 'TrainingJobDefinition' => [ 'AlgorithmSpecification' => [ 'AlgorithmName' => '<string>', 'MetricDefinitions' => [ [ 'Name' => '<string>', 'Regex' => '<string>', ], // ... ], 'TrainingImage' => '<string>', 'TrainingInputMode' => 'Pipe|File|FastFile', ], 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', ], 'DefinitionName' => '<string>', 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'Environment' => ['<string>', ...], 'HyperParameterRanges' => [ 'AutoParameters' => [ [ 'Name' => '<string>', 'ValueHint' => '<string>', ], // ... ], 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', 'Values' => ['<string>', ...], ], // ... ], 'ContinuousParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], 'IntegerParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], ], 'HyperParameterTuningResourceConfig' => [ 'AllocationStrategy' => 'Prioritized', 'InstanceConfigs' => [ [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeSizeInGB' => <integer>, ], // ... ], 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', 'FileSystemAccessMode' => 'rw|ro', 'FileSystemId' => '<string>', 'FileSystemType' => 'EFS|FSxLustre', ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'InstanceGroupNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'InputMode' => 'Pipe|File|FastFile', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, ], ], // ... ], 'OutputDataConfig' => [ 'CompressionType' => 'GZIP|NONE', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'ResourceConfig' => [ 'InstanceCount' => <integer>, 'InstanceGroups' => [ [ 'InstanceCount' => <integer>, 'InstanceGroupName' => '<string>', 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', ], // ... ], 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'KeepAlivePeriodInSeconds' => <integer>, 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'RetryStrategy' => [ 'MaximumRetryAttempts' => <integer>, ], 'RoleArn' => '<string>', 'StaticHyperParameters' => ['<string>', ...], 'StoppingCondition' => [ 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TuningObjective' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'TrainingJobDefinitions' => [ [ 'AlgorithmSpecification' => [ 'AlgorithmName' => '<string>', 'MetricDefinitions' => [ [ 'Name' => '<string>', 'Regex' => '<string>', ], // ... ], 'TrainingImage' => '<string>', 'TrainingInputMode' => 'Pipe|File|FastFile', ], 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', ], 'DefinitionName' => '<string>', 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'Environment' => ['<string>', ...], 'HyperParameterRanges' => [ 'AutoParameters' => [ [ 'Name' => '<string>', 'ValueHint' => '<string>', ], // ... ], 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', 'Values' => ['<string>', ...], ], // ... ], 'ContinuousParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], 'IntegerParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], ], 'HyperParameterTuningResourceConfig' => [ 'AllocationStrategy' => 'Prioritized', 'InstanceConfigs' => [ [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeSizeInGB' => <integer>, ], // ... ], 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', 'FileSystemAccessMode' => 'rw|ro', 'FileSystemId' => '<string>', 'FileSystemType' => 'EFS|FSxLustre', ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'InstanceGroupNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'InputMode' => 'Pipe|File|FastFile', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, ], ], // ... ], 'OutputDataConfig' => [ 'CompressionType' => 'GZIP|NONE', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'ResourceConfig' => [ 'InstanceCount' => <integer>, 'InstanceGroups' => [ [ 'InstanceCount' => <integer>, 'InstanceGroupName' => '<string>', 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', ], // ... ], 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'KeepAlivePeriodInSeconds' => <integer>, 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'RetryStrategy' => [ 'MaximumRetryAttempts' => <integer>, ], 'RoleArn' => '<string>', 'StaticHyperParameters' => ['<string>', ...], 'StoppingCondition' => [ 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TuningObjective' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], // ... ], 'TrainingJobStatusCounters' => [ 'Completed' => <integer>, 'InProgress' => <integer>, 'NonRetryableError' => <integer>, 'RetryableError' => <integer>, 'Stopped' => <integer>, ], 'TuningJobCompletionDetails' => [ 'ConvergenceDetectedTime' => <DateTime>, 'NumberOfTrainingJobsObjectiveNotImproving' => <integer>, ], 'WarmStartConfig' => [ 'ParentHyperParameterTuningJobs' => [ [ 'HyperParameterTuningJobName' => '<string>', ], // ... ], 'WarmStartType' => 'IdenticalDataAndAlgorithm|TransferLearning', ], ], 'Model' => [ 'Endpoints' => [ [ 'CreationTime' => <DateTime>, 'EndpointArn' => '<string>', 'EndpointName' => '<string>', 'EndpointStatus' => 'OutOfService|Creating|Updating|SystemUpdating|RollingBack|InService|Deleting|Failed|UpdateRollbackFailed', 'LastModifiedTime' => <DateTime>, ], // ... ], 'LastBatchTransformJob' => [ 'AutoMLJobArn' => '<string>', 'BatchStrategy' => 'MultiRecord|SingleRecord', 'CreationTime' => <DateTime>, 'DataCaptureConfig' => [ 'DestinationS3Uri' => '<string>', 'GenerateInferenceId' => true || false, 'KmsKeyId' => '<string>', ], 'DataProcessing' => [ 'InputFilter' => '<string>', 'JoinSource' => 'Input|None', 'OutputFilter' => '<string>', ], 'Environment' => ['<string>', ...], 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'RunName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'FailureReason' => '<string>', 'LabelingJobArn' => '<string>', 'MaxConcurrentTransforms' => <integer>, 'MaxPayloadInMB' => <integer>, 'ModelClientConfig' => [ 'InvocationsMaxRetries' => <integer>, 'InvocationsTimeoutInSeconds' => <integer>, ], 'ModelName' => '<string>', 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], 'TransformEndTime' => <DateTime>, 'TransformInput' => [ 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'S3DataSource' => [ 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'SplitType' => 'None|Line|RecordIO|TFRecord', ], 'TransformJobArn' => '<string>', 'TransformJobName' => '<string>', 'TransformJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TransformOutput' => [ 'Accept' => '<string>', 'AssembleWith' => 'None|Line', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'TransformResources' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge', 'VolumeKmsKeyId' => '<string>', ], 'TransformStartTime' => <DateTime>, ], 'Model' => [ 'Containers' => [ [ 'AdditionalModelDataSources' => [ [ 'ChannelName' => '<string>', 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], // ... ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ImageConfig' => [ 'RepositoryAccessMode' => 'Platform|Vpc', 'RepositoryAuthConfig' => [ 'RepositoryCredentialsProviderArn' => '<string>', ], ], 'InferenceSpecificationName' => '<string>', 'Mode' => 'SingleModel|MultiModel', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], 'ModelDataUrl' => '<string>', 'ModelPackageName' => '<string>', 'MultiModelConfig' => [ 'ModelCacheSetting' => 'Enabled|Disabled', ], ], // ... ], 'CreationTime' => <DateTime>, 'DeploymentRecommendation' => [ 'RealTimeInferenceRecommendations' => [ [ 'Environment' => ['<string>', ...], 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.12xlarge|ml.m5d.24xlarge|ml.c4.large|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.large|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.12xlarge|ml.r5.24xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.12xlarge|ml.r5d.24xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.dl1.24xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.p4d.24xlarge|ml.c7g.large|ml.c7g.xlarge|ml.c7g.2xlarge|ml.c7g.4xlarge|ml.c7g.8xlarge|ml.c7g.12xlarge|ml.c7g.16xlarge|ml.m6g.large|ml.m6g.xlarge|ml.m6g.2xlarge|ml.m6g.4xlarge|ml.m6g.8xlarge|ml.m6g.12xlarge|ml.m6g.16xlarge|ml.m6gd.large|ml.m6gd.xlarge|ml.m6gd.2xlarge|ml.m6gd.4xlarge|ml.m6gd.8xlarge|ml.m6gd.12xlarge|ml.m6gd.16xlarge|ml.c6g.large|ml.c6g.xlarge|ml.c6g.2xlarge|ml.c6g.4xlarge|ml.c6g.8xlarge|ml.c6g.12xlarge|ml.c6g.16xlarge|ml.c6gd.large|ml.c6gd.xlarge|ml.c6gd.2xlarge|ml.c6gd.4xlarge|ml.c6gd.8xlarge|ml.c6gd.12xlarge|ml.c6gd.16xlarge|ml.c6gn.large|ml.c6gn.xlarge|ml.c6gn.2xlarge|ml.c6gn.4xlarge|ml.c6gn.8xlarge|ml.c6gn.12xlarge|ml.c6gn.16xlarge|ml.r6g.large|ml.r6g.xlarge|ml.r6g.2xlarge|ml.r6g.4xlarge|ml.r6g.8xlarge|ml.r6g.12xlarge|ml.r6g.16xlarge|ml.r6gd.large|ml.r6gd.xlarge|ml.r6gd.2xlarge|ml.r6gd.4xlarge|ml.r6gd.8xlarge|ml.r6gd.12xlarge|ml.r6gd.16xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.inf2.xlarge|ml.inf2.8xlarge|ml.inf2.24xlarge|ml.inf2.48xlarge|ml.p5.48xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge', 'RecommendationId' => '<string>', ], // ... ], 'RecommendationStatus' => 'IN_PROGRESS|COMPLETED|FAILED|NOT_APPLICABLE', ], 'EnableNetworkIsolation' => true || false, 'ExecutionRoleArn' => '<string>', 'InferenceExecutionConfig' => [ 'Mode' => 'Serial|Direct', ], 'ModelArn' => '<string>', 'ModelName' => '<string>', 'PrimaryContainer' => [ 'AdditionalModelDataSources' => [ [ 'ChannelName' => '<string>', 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], // ... ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ImageConfig' => [ 'RepositoryAccessMode' => 'Platform|Vpc', 'RepositoryAuthConfig' => [ 'RepositoryCredentialsProviderArn' => '<string>', ], ], 'InferenceSpecificationName' => '<string>', 'Mode' => 'SingleModel|MultiModel', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], 'ModelDataUrl' => '<string>', 'ModelPackageName' => '<string>', 'MultiModelConfig' => [ 'ModelCacheSetting' => 'Enabled|Disabled', ], ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'ModelCard' => [ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'ModelCardArn' => '<string>', 'ModelCardName' => '<string>', 'ModelCardStatus' => 'Draft|PendingReview|Approved|Archived', 'ModelCardVersion' => <integer>, 'ModelId' => '<string>', 'RiskRating' => '<string>', 'SecurityConfig' => [ 'KmsKeyId' => '<string>', ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], 'MonitoringSchedules' => [ [ 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', 'DatasetFormat' => [ 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'LastMonitoringExecutionSummary' => [ 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'MonitoringExecutionStatus' => 'Pending|Completed|CompletedWithViolations|InProgress|Failed|Stopping|Stopped', 'MonitoringJobDefinitionName' => '<string>', 'MonitoringScheduleName' => '<string>', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'ProcessingJobArn' => '<string>', 'ScheduledTime' => <DateTime>, ], 'MonitoringAlertSummaries' => [ [ 'Actions' => [ 'ModelDashboardIndicator' => [ 'Enabled' => true || false, ], ], 'AlertStatus' => 'InAlert|OK', 'CreationTime' => <DateTime>, 'DatapointsToAlert' => <integer>, 'EvaluationPeriod' => <integer>, 'LastModifiedTime' => <DateTime>, 'MonitoringAlertName' => '<string>', ], // ... ], 'MonitoringScheduleArn' => '<string>', 'MonitoringScheduleConfig' => [ 'MonitoringJobDefinition' => [ 'BaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], 'StatisticsResource' => [ 'S3Uri' => '<string>', ], ], 'Environment' => ['<string>', ...], 'MonitoringAppSpecification' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ImageUri' => '<string>', 'PostAnalyticsProcessorSourceUri' => '<string>', 'RecordPreprocessorSourceUri' => '<string>', ], 'MonitoringInputs' => [ [ 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', 'DatasetFormat' => [ 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], ], // ... ], 'MonitoringOutputConfig' => [ 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ [ 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'MonitoringResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], ], 'MonitoringJobDefinitionName' => '<string>', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'ScheduleConfig' => [ 'DataAnalysisEndTime' => '<string>', 'DataAnalysisStartTime' => '<string>', 'ScheduleExpression' => '<string>', ], ], 'MonitoringScheduleName' => '<string>', 'MonitoringScheduleStatus' => 'Pending|Failed|Scheduled|Stopped', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', ], // ... ], ], 'ModelCard' => [ 'Content' => '<string>', 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'ModelCardArn' => '<string>', 'ModelCardName' => '<string>', 'ModelCardStatus' => 'Draft|PendingReview|Approved|Archived', 'ModelCardVersion' => <integer>, 'ModelId' => '<string>', 'ModelPackageGroupName' => '<string>', 'RiskRating' => '<string>', 'SecurityConfig' => [ 'KmsKeyId' => '<string>', ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], 'ModelPackage' => [ 'AdditionalInferenceSpecifications' => [ [ 'Containers' => [ [ 'AdditionalS3DataSource' => [ 'CompressionType' => 'None|Gzip', 'S3DataType' => 'S3Object|S3Prefix', 'S3Uri' => '<string>', ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'Image' => '<string>', 'ImageDigest' => '<string>', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], 'ModelDataUrl' => '<string>', 'ModelInput' => [ 'DataInputConfig' => '<string>', ], 'NearestModelName' => '<string>', 'ProductId' => '<string>', ], // ... ], 'Description' => '<string>', 'Name' => '<string>', 'SupportedContentTypes' => ['<string>', ...], 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'SupportedTransformInstanceTypes' => ['<string>', ...], ], // ... ], 'ApprovalDescription' => '<string>', 'CertifyForMarketplace' => true || false, 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'CustomerMetadataProperties' => ['<string>', ...], 'Domain' => '<string>', 'DriftCheckBaselines' => [ 'Bias' => [ 'ConfigFile' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'PostTrainingConstraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'PreTrainingConstraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'Explainability' => [ 'ConfigFile' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'ModelDataQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'ModelQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], ], 'InferenceSpecification' => [ 'Containers' => [ [ 'AdditionalS3DataSource' => [ 'CompressionType' => 'None|Gzip', 'S3DataType' => 'S3Object|S3Prefix', 'S3Uri' => '<string>', ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'Image' => '<string>', 'ImageDigest' => '<string>', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], 'ModelDataUrl' => '<string>', 'ModelInput' => [ 'DataInputConfig' => '<string>', ], 'NearestModelName' => '<string>', 'ProductId' => '<string>', ], // ... ], 'SupportedContentTypes' => ['<string>', ...], 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'SupportedTransformInstanceTypes' => ['<string>', ...], ], 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'ModelApprovalStatus' => 'Approved|Rejected|PendingManualApproval', 'ModelCard' => [ 'ModelCardContent' => '<string>', 'ModelCardStatus' => 'Draft|PendingReview|Approved|Archived', ], 'ModelMetrics' => [ 'Bias' => [ 'PostTrainingReport' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'PreTrainingReport' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Report' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'Explainability' => [ 'Report' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'ModelDataQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'ModelQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], ], 'ModelPackageArn' => '<string>', 'ModelPackageDescription' => '<string>', 'ModelPackageGroupName' => '<string>', 'ModelPackageName' => '<string>', 'ModelPackageStatus' => 'Pending|InProgress|Completed|Failed|Deleting', 'ModelPackageStatusDetails' => [ 'ImageScanStatuses' => [ [ 'FailureReason' => '<string>', 'Name' => '<string>', 'Status' => 'NotStarted|InProgress|Completed|Failed', ], // ... ], 'ValidationStatuses' => [ [ 'FailureReason' => '<string>', 'Name' => '<string>', 'Status' => 'NotStarted|InProgress|Completed|Failed', ], // ... ], ], 'ModelPackageVersion' => <integer>, 'SamplePayloadUrl' => '<string>', 'SecurityConfig' => [ 'KmsKeyId' => '<string>', ], 'SkipModelValidation' => 'All|None', 'SourceAlgorithmSpecification' => [ 'SourceAlgorithms' => [ [ 'AlgorithmName' => '<string>', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', 'HubAccessConfig' => [ 'HubContentArn' => '<string>', ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, ], 'S3DataType' => 'S3Prefix|S3Object', 'S3Uri' => '<string>', ], ], 'ModelDataUrl' => '<string>', ], // ... ], ], 'SourceUri' => '<string>', 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], 'Task' => '<string>', 'ValidationSpecification' => [ 'ValidationProfiles' => [ [ 'ProfileName' => '<string>', 'TransformJobDefinition' => [ 'BatchStrategy' => 'MultiRecord|SingleRecord', 'Environment' => ['<string>', ...], 'MaxConcurrentTransforms' => <integer>, 'MaxPayloadInMB' => <integer>, 'TransformInput' => [ 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'S3DataSource' => [ 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'SplitType' => 'None|Line|RecordIO|TFRecord', ], 'TransformOutput' => [ 'Accept' => '<string>', 'AssembleWith' => 'None|Line', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'TransformResources' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge', 'VolumeKmsKeyId' => '<string>', ], ], ], // ... ], 'ValidationRole' => '<string>', ], ], 'ModelPackageGroup' => [ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'ModelPackageGroupArn' => '<string>', 'ModelPackageGroupDescription' => '<string>', 'ModelPackageGroupName' => '<string>', 'ModelPackageGroupStatus' => 'Pending|InProgress|Completed|Failed|Deleting|DeleteFailed', 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], 'Pipeline' => [ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'LastRunTime' => <DateTime>, 'ParallelismConfiguration' => [ 'MaxParallelExecutionSteps' => <integer>, ], 'PipelineArn' => '<string>', 'PipelineDescription' => '<string>', 'PipelineDisplayName' => '<string>', 'PipelineName' => '<string>', 'PipelineStatus' => 'Active|Deleting', 'RoleArn' => '<string>', 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], 'PipelineExecution' => [ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'ParallelismConfiguration' => [ 'MaxParallelExecutionSteps' => <integer>, ], 'PipelineArn' => '<string>', 'PipelineExecutionArn' => '<string>', 'PipelineExecutionDescription' => '<string>', 'PipelineExecutionDisplayName' => '<string>', 'PipelineExecutionStatus' => 'Executing|Stopping|Stopped|Failed|Succeeded', 'PipelineExperimentConfig' => [ 'ExperimentName' => '<string>', 'TrialName' => '<string>', ], 'PipelineParameters' => [ [ 'Name' => '<string>', 'Value' => '<string>', ], // ... ], 'SelectiveExecutionConfig' => [ 'SelectedSteps' => [ [ 'StepName' => '<string>', ], // ... ], 'SourcePipelineExecutionArn' => '<string>', ], ], 'Project' => [ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'ProjectArn' => '<string>', 'ProjectDescription' => '<string>', 'ProjectId' => '<string>', 'ProjectName' => '<string>', 'ProjectStatus' => 'Pending|CreateInProgress|CreateCompleted|CreateFailed|DeleteInProgress|DeleteFailed|DeleteCompleted|UpdateInProgress|UpdateCompleted|UpdateFailed', 'ServiceCatalogProvisionedProductDetails' => [ 'ProvisionedProductId' => '<string>', 'ProvisionedProductStatusMessage' => '<string>', ], 'ServiceCatalogProvisioningDetails' => [ 'PathId' => '<string>', 'ProductId' => '<string>', 'ProvisioningArtifactId' => '<string>', 'ProvisioningParameters' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], 'TrainingJob' => [ 'AlgorithmSpecification' => [ 'AlgorithmName' => '<string>', 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'EnableSageMakerMetricsTimeSeries' => true || false, 'MetricDefinitions' => [ [ 'Name' => '<string>', 'Regex' => '<string>', ], // ... ], 'TrainingImage' => '<string>', 'TrainingImageConfig' => [ 'TrainingRepositoryAccessMode' => 'Platform|Vpc', 'TrainingRepositoryAuthConfig' => [ 'TrainingRepositoryCredentialsProviderArn' => '<string>', ], ], 'TrainingInputMode' => 'Pipe|File|FastFile', ], 'AutoMLJobArn' => '<string>', 'BillableTimeInSeconds' => <integer>, 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', ], 'CreationTime' => <DateTime>, 'DebugHookConfig' => [ 'CollectionConfigurations' => [ [ 'CollectionName' => '<string>', 'CollectionParameters' => ['<string>', ...], ], // ... ], 'HookParameters' => ['<string>', ...], 'LocalPath' => '<string>', 'S3OutputPath' => '<string>', ], 'DebugRuleConfigurations' => [ [ 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'LocalPath' => '<string>', 'RuleConfigurationName' => '<string>', 'RuleEvaluatorImage' => '<string>', 'RuleParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', 'VolumeSizeInGB' => <integer>, ], // ... ], 'DebugRuleEvaluationStatuses' => [ [ 'LastModifiedTime' => <DateTime>, 'RuleConfigurationName' => '<string>', 'RuleEvaluationJobArn' => '<string>', 'RuleEvaluationStatus' => 'InProgress|NoIssuesFound|IssuesFound|Error|Stopping|Stopped', 'StatusDetails' => '<string>', ], // ... ], 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'Environment' => ['<string>', ...], 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'RunName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'FailureReason' => '<string>', 'FinalMetricDataList' => [ [ 'MetricName' => '<string>', 'Timestamp' => <DateTime>, 'Value' => <float>, ], // ... ], 'HyperParameters' => ['<string>', ...], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', 'FileSystemAccessMode' => 'rw|ro', 'FileSystemId' => '<string>', 'FileSystemType' => 'EFS|FSxLustre', ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'InstanceGroupNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'InputMode' => 'Pipe|File|FastFile', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, ], ], // ... ], 'LabelingJobArn' => '<string>', 'LastModifiedTime' => <DateTime>, 'ModelArtifacts' => [ 'S3ModelArtifacts' => '<string>', ], 'OutputDataConfig' => [ 'CompressionType' => 'GZIP|NONE', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'ProfilerConfig' => [ 'DisableProfiler' => true || false, 'ProfilingIntervalInMilliseconds' => <integer>, 'ProfilingParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', ], 'ResourceConfig' => [ 'InstanceCount' => <integer>, 'InstanceGroups' => [ [ 'InstanceCount' => <integer>, 'InstanceGroupName' => '<string>', 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', ], // ... ], 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'KeepAlivePeriodInSeconds' => <integer>, 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'RetryStrategy' => [ 'MaximumRetryAttempts' => <integer>, ], 'RoleArn' => '<string>', 'SecondaryStatus' => 'Starting|LaunchingMLInstances|PreparingTrainingStack|Downloading|DownloadingTrainingImage|Training|Uploading|Stopping|Stopped|MaxRuntimeExceeded|Completed|Failed|Interrupted|MaxWaitTimeExceeded|Updating|Restarting|Pending', 'SecondaryStatusTransitions' => [ [ 'EndTime' => <DateTime>, 'StartTime' => <DateTime>, 'Status' => 'Starting|LaunchingMLInstances|PreparingTrainingStack|Downloading|DownloadingTrainingImage|Training|Uploading|Stopping|Stopped|MaxRuntimeExceeded|Completed|Failed|Interrupted|MaxWaitTimeExceeded|Updating|Restarting|Pending', 'StatusMessage' => '<string>', ], // ... ], 'StoppingCondition' => [ 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], 'TensorBoardOutputConfig' => [ 'LocalPath' => '<string>', 'S3OutputPath' => '<string>', ], 'TrainingEndTime' => <DateTime>, 'TrainingJobArn' => '<string>', 'TrainingJobName' => '<string>', 'TrainingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TrainingStartTime' => <DateTime>, 'TrainingTimeInSeconds' => <integer>, 'TuningJobArn' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'Trial' => [ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'DisplayName' => '<string>', 'ExperimentName' => '<string>', 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'Source' => [ 'SourceArn' => '<string>', 'SourceType' => '<string>', ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], 'TrialArn' => '<string>', 'TrialComponentSummaries' => [ [ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'TrialComponentArn' => '<string>', 'TrialComponentName' => '<string>', 'TrialComponentSource' => [ 'SourceArn' => '<string>', 'SourceType' => '<string>', ], ], // ... ], 'TrialName' => '<string>', ], 'TrialComponent' => [ 'CreatedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'DisplayName' => '<string>', 'EndTime' => <DateTime>, 'InputArtifacts' => [ '<TrialComponentKey128>' => [ 'MediaType' => '<string>', 'Value' => '<string>', ], // ... ], 'LastModifiedBy' => [ 'DomainId' => '<string>', 'IamIdentity' => [ 'Arn' => '<string>', 'PrincipalId' => '<string>', 'SourceIdentity' => '<string>', ], 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'LineageGroupArn' => '<string>', 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'Metrics' => [ [ 'Avg' => <float>, 'Count' => <integer>, 'Last' => <float>, 'Max' => <float>, 'MetricName' => '<string>', 'Min' => <float>, 'SourceArn' => '<string>', 'StdDev' => <float>, 'TimeStamp' => <DateTime>, ], // ... ], 'OutputArtifacts' => [ '<TrialComponentKey128>' => [ 'MediaType' => '<string>', 'Value' => '<string>', ], // ... ], 'Parameters' => [ '<TrialComponentKey320>' => [ 'NumberValue' => <float>, 'StringValue' => '<string>', ], // ... ], 'Parents' => [ [ 'ExperimentName' => '<string>', 'TrialName' => '<string>', ], // ... ], 'RunName' => '<string>', 'Source' => [ 'SourceArn' => '<string>', 'SourceType' => '<string>', ], 'SourceDetail' => [ 'ProcessingJob' => [ 'AppSpecification' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ImageUri' => '<string>', ], 'AutoMLJobArn' => '<string>', 'CreationTime' => <DateTime>, 'Environment' => ['<string>', ...], 'ExitMessage' => '<string>', 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'RunName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'MonitoringScheduleArn' => '<string>', 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'ProcessingEndTime' => <DateTime>, 'ProcessingInputs' => [ [ 'AppManaged' => true || false, 'DatasetDefinition' => [ 'AthenaDatasetDefinition' => [ 'Catalog' => '<string>', 'Database' => '<string>', 'KmsKeyId' => '<string>', 'OutputCompression' => 'GZIP|SNAPPY|ZLIB', 'OutputFormat' => 'PARQUET|ORC|AVRO|JSON|TEXTFILE', 'OutputS3Uri' => '<string>', 'QueryString' => '<string>', 'WorkGroup' => '<string>', ], 'DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'InputMode' => 'Pipe|File', 'LocalPath' => '<string>', 'RedshiftDatasetDefinition' => [ 'ClusterId' => '<string>', 'ClusterRoleArn' => '<string>', 'Database' => '<string>', 'DbUser' => '<string>', 'KmsKeyId' => '<string>', 'OutputCompression' => 'None|GZIP|BZIP2|ZSTD|SNAPPY', 'OutputFormat' => 'PARQUET|CSV', 'OutputS3Uri' => '<string>', 'QueryString' => '<string>', ], ], 'InputName' => '<string>', 'S3Input' => [ 'LocalPath' => '<string>', 'S3CompressionType' => 'None|Gzip', 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix', 'S3InputMode' => 'Pipe|File', 'S3Uri' => '<string>', ], ], // ... ], 'ProcessingJobArn' => '<string>', 'ProcessingJobName' => '<string>', 'ProcessingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'ProcessingOutputConfig' => [ 'KmsKeyId' => '<string>', 'Outputs' => [ [ 'AppManaged' => true || false, 'FeatureStoreOutput' => [ 'FeatureGroupName' => '<string>', ], 'OutputName' => '<string>', 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'ProcessingResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'ProcessingStartTime' => <DateTime>, 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], 'TrainingJobArn' => '<string>', ], 'SourceArn' => '<string>', 'TrainingJob' => [ 'AlgorithmSpecification' => [ 'AlgorithmName' => '<string>', 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'EnableSageMakerMetricsTimeSeries' => true || false, 'MetricDefinitions' => [ [ 'Name' => '<string>', 'Regex' => '<string>', ], // ... ], 'TrainingImage' => '<string>', 'TrainingImageConfig' => [ 'TrainingRepositoryAccessMode' => 'Platform|Vpc', 'TrainingRepositoryAuthConfig' => [ 'TrainingRepositoryCredentialsProviderArn' => '<string>', ], ], 'TrainingInputMode' => 'Pipe|File|FastFile', ], 'AutoMLJobArn' => '<string>', 'BillableTimeInSeconds' => <integer>, 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', ], 'CreationTime' => <DateTime>, 'DebugHookConfig' => [ 'CollectionConfigurations' => [ [ 'CollectionName' => '<string>', 'CollectionParameters' => ['<string>', ...], ], // ... ], 'HookParameters' => ['<string>', ...], 'LocalPath' => '<string>', 'S3OutputPath' => '<string>', ], 'DebugRuleConfigurations' => [ [ 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'LocalPath' => '<string>', 'RuleConfigurationName' => '<string>', 'RuleEvaluatorImage' => '<string>', 'RuleParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', 'VolumeSizeInGB' => <integer>, ], // ... ], 'DebugRuleEvaluationStatuses' => [ [ 'LastModifiedTime' => <DateTime>, 'RuleConfigurationName' => '<string>', 'RuleEvaluationJobArn' => '<string>', 'RuleEvaluationStatus' => 'InProgress|NoIssuesFound|IssuesFound|Error|Stopping|Stopped', 'StatusDetails' => '<string>', ], // ... ], 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'Environment' => ['<string>', ...], 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'RunName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'FailureReason' => '<string>', 'FinalMetricDataList' => [ [ 'MetricName' => '<string>', 'Timestamp' => <DateTime>, 'Value' => <float>, ], // ... ], 'HyperParameters' => ['<string>', ...], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', 'FileSystemAccessMode' => 'rw|ro', 'FileSystemId' => '<string>', 'FileSystemType' => 'EFS|FSxLustre', ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'InstanceGroupNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'InputMode' => 'Pipe|File|FastFile', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, ], ], // ... ], 'LabelingJobArn' => '<string>', 'LastModifiedTime' => <DateTime>, 'ModelArtifacts' => [ 'S3ModelArtifacts' => '<string>', ], 'OutputDataConfig' => [ 'CompressionType' => 'GZIP|NONE', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'ProfilerConfig' => [ 'DisableProfiler' => true || false, 'ProfilingIntervalInMilliseconds' => <integer>, 'ProfilingParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', ], 'ResourceConfig' => [ 'InstanceCount' => <integer>, 'InstanceGroups' => [ [ 'InstanceCount' => <integer>, 'InstanceGroupName' => '<string>', 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', ], // ... ], 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5n.xlarge|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.8xlarge|ml.c6i.4xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'KeepAlivePeriodInSeconds' => <integer>, 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'RetryStrategy' => [ 'MaximumRetryAttempts' => <integer>, ], 'RoleArn' => '<string>', 'SecondaryStatus' => 'Starting|LaunchingMLInstances|PreparingTrainingStack|Downloading|DownloadingTrainingImage|Training|Uploading|Stopping|Stopped|MaxRuntimeExceeded|Completed|Failed|Interrupted|MaxWaitTimeExceeded|Updating|Restarting|Pending', 'SecondaryStatusTransitions' => [ [ 'EndTime' => <DateTime>, 'StartTime' => <DateTime>, 'Status' => 'Starting|LaunchingMLInstances|PreparingTrainingStack|Downloading|DownloadingTrainingImage|Training|Uploading|Stopping|Stopped|MaxRuntimeExceeded|Completed|Failed|Interrupted|MaxWaitTimeExceeded|Updating|Restarting|Pending', 'StatusMessage' => '<string>', ], // ... ], 'StoppingCondition' => [ 'MaxPendingTimeInSeconds' => <integer>, 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], 'TensorBoardOutputConfig' => [ 'LocalPath' => '<string>', 'S3OutputPath' => '<string>', ], 'TrainingEndTime' => <DateTime>, 'TrainingJobArn' => '<string>', 'TrainingJobName' => '<string>', 'TrainingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TrainingStartTime' => <DateTime>, 'TrainingTimeInSeconds' => <integer>, 'TuningJobArn' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'TransformJob' => [ 'AutoMLJobArn' => '<string>', 'BatchStrategy' => 'MultiRecord|SingleRecord', 'CreationTime' => <DateTime>, 'DataCaptureConfig' => [ 'DestinationS3Uri' => '<string>', 'GenerateInferenceId' => true || false, 'KmsKeyId' => '<string>', ], 'DataProcessing' => [ 'InputFilter' => '<string>', 'JoinSource' => 'Input|None', 'OutputFilter' => '<string>', ], 'Environment' => ['<string>', ...], 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'RunName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'FailureReason' => '<string>', 'LabelingJobArn' => '<string>', 'MaxConcurrentTransforms' => <integer>, 'MaxPayloadInMB' => <integer>, 'ModelClientConfig' => [ 'InvocationsMaxRetries' => <integer>, 'InvocationsTimeoutInSeconds' => <integer>, ], 'ModelName' => '<string>', 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], 'TransformEndTime' => <DateTime>, 'TransformInput' => [ 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'S3DataSource' => [ 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'SplitType' => 'None|Line|RecordIO|TFRecord', ], 'TransformJobArn' => '<string>', 'TransformJobName' => '<string>', 'TransformJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TransformOutput' => [ 'Accept' => '<string>', 'AssembleWith' => 'None|Line', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'TransformResources' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge', 'VolumeKmsKeyId' => '<string>', ], 'TransformStartTime' => <DateTime>, ], ], 'StartTime' => <DateTime>, 'Status' => [ 'Message' => '<string>', 'PrimaryStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], 'TrialComponentArn' => '<string>', 'TrialComponentName' => '<string>', ], ], // ... ], ]
Result Details
Members
- NextToken
-
- Type: string
If the result of the previous
Search
request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request. - Results
-
- Type: Array of SearchRecord structures
A list of
SearchRecord
objects.
Errors
There are no errors described for this operation.
SendPipelineExecutionStepFailure
$result = $client->sendPipelineExecutionStepFailure
([/* ... */]); $promise = $client->sendPipelineExecutionStepFailureAsync
([/* ... */]);
Notifies the pipeline that the execution of a callback step failed, along with a message describing why. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
Parameter Syntax
$result = $client->sendPipelineExecutionStepFailure([ 'CallbackToken' => '<string>', // REQUIRED 'ClientRequestToken' => '<string>', 'FailureReason' => '<string>', ]);
Parameter Details
Members
- CallbackToken
-
- Required: Yes
- Type: string
The pipeline generated token from the Amazon SQS queue.
- ClientRequestToken
-
- Type: string
A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
- FailureReason
-
- Type: string
A message describing why the step failed.
Result Syntax
[ 'PipelineExecutionArn' => '<string>', ]
Result Details
Members
- PipelineExecutionArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
SendPipelineExecutionStepSuccess
$result = $client->sendPipelineExecutionStepSuccess
([/* ... */]); $promise = $client->sendPipelineExecutionStepSuccessAsync
([/* ... */]);
Notifies the pipeline that the execution of a callback step succeeded and provides a list of the step's output parameters. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
Parameter Syntax
$result = $client->sendPipelineExecutionStepSuccess([ 'CallbackToken' => '<string>', // REQUIRED 'ClientRequestToken' => '<string>', 'OutputParameters' => [ [ 'Name' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- CallbackToken
-
- Required: Yes
- Type: string
The pipeline generated token from the Amazon SQS queue.
- ClientRequestToken
-
- Type: string
A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
- OutputParameters
-
- Type: Array of OutputParameter structures
A list of the output parameters of the callback step.
Result Syntax
[ 'PipelineExecutionArn' => '<string>', ]
Result Details
Members
- PipelineExecutionArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
StartEdgeDeploymentStage
$result = $client->startEdgeDeploymentStage
([/* ... */]); $promise = $client->startEdgeDeploymentStageAsync
([/* ... */]);
Starts a stage in an edge deployment plan.
Parameter Syntax
$result = $client->startEdgeDeploymentStage([ 'EdgeDeploymentPlanName' => '<string>', // REQUIRED 'StageName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- EdgeDeploymentPlanName
-
- Required: Yes
- Type: string
The name of the edge deployment plan to start.
- StageName
-
- Required: Yes
- Type: string
The name of the stage to start.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
StartInferenceExperiment
$result = $client->startInferenceExperiment
([/* ... */]); $promise = $client->startInferenceExperimentAsync
([/* ... */]);
Starts an inference experiment.
Parameter Syntax
$result = $client->startInferenceExperiment([ 'Name' => '<string>', // REQUIRED ]);
Parameter Details
Members
- Name
-
- Required: Yes
- Type: string
The name of the inference experiment to start.
Result Syntax
[ 'InferenceExperimentArn' => '<string>', ]
Result Details
Members
- InferenceExperimentArn
-
- Required: Yes
- Type: string
The ARN of the started inference experiment to start.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.- ResourceNotFound:
Resource being access is not found.
StartMlflowTrackingServer
$result = $client->startMlflowTrackingServer
([/* ... */]); $promise = $client->startMlflowTrackingServerAsync
([/* ... */]);
Programmatically start an MLflow Tracking Server.
Parameter Syntax
$result = $client->startMlflowTrackingServer([ 'TrackingServerName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TrackingServerName
-
- Required: Yes
- Type: string
The name of the tracking server to start.
Result Syntax
[ 'TrackingServerArn' => '<string>', ]
Result Details
Members
- TrackingServerArn
-
- Type: string
The ARN of the started tracking server.
Errors
- ResourceNotFound:
Resource being access is not found.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
StartMonitoringSchedule
$result = $client->startMonitoringSchedule
([/* ... */]); $promise = $client->startMonitoringScheduleAsync
([/* ... */]);
Starts a previously stopped monitoring schedule.
By default, when you successfully create a new schedule, the status of a monitoring schedule is scheduled
.
Parameter Syntax
$result = $client->startMonitoringSchedule([ 'MonitoringScheduleName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- MonitoringScheduleName
-
- Required: Yes
- Type: string
The name of the schedule to start.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
StartNotebookInstance
$result = $client->startNotebookInstance
([/* ... */]); $promise = $client->startNotebookInstanceAsync
([/* ... */]);
Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume. After configuring the notebook instance, SageMaker sets the notebook instance status to InService
. A notebook instance's status must be InService
before you can connect to your Jupyter notebook.
Parameter Syntax
$result = $client->startNotebookInstance([ 'NotebookInstanceName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- NotebookInstanceName
-
- Required: Yes
- Type: string
The name of the notebook instance to start.
Result Syntax
[]
Result Details
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
StartPipelineExecution
$result = $client->startPipelineExecution
([/* ... */]); $promise = $client->startPipelineExecutionAsync
([/* ... */]);
Starts a pipeline execution.
Parameter Syntax
$result = $client->startPipelineExecution([ 'ClientRequestToken' => '<string>', // REQUIRED 'ParallelismConfiguration' => [ 'MaxParallelExecutionSteps' => <integer>, // REQUIRED ], 'PipelineExecutionDescription' => '<string>', 'PipelineExecutionDisplayName' => '<string>', 'PipelineName' => '<string>', // REQUIRED 'PipelineParameters' => [ [ 'Name' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'SelectiveExecutionConfig' => [ 'SelectedSteps' => [ // REQUIRED [ 'StepName' => '<string>', // REQUIRED ], // ... ], 'SourcePipelineExecutionArn' => '<string>', ], ]);
Parameter Details
Members
- ClientRequestToken
-
- Required: Yes
- Type: string
A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
- ParallelismConfiguration
-
- Type: ParallelismConfiguration structure
This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
- PipelineExecutionDescription
-
- Type: string
The description of the pipeline execution.
- PipelineExecutionDisplayName
-
- Type: string
The display name of the pipeline execution.
- PipelineName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the pipeline.
- PipelineParameters
-
- Type: Array of Parameter structures
Contains a list of pipeline parameters. This list can be empty.
- SelectiveExecutionConfig
-
- Type: SelectiveExecutionConfig structure
The selective execution configuration applied to the pipeline run.
Result Syntax
[ 'PipelineExecutionArn' => '<string>', ]
Result Details
Members
- PipelineExecutionArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
StopAutoMLJob
$result = $client->stopAutoMLJob
([/* ... */]); $promise = $client->stopAutoMLJobAsync
([/* ... */]);
A method for forcing a running job to shut down.
Parameter Syntax
$result = $client->stopAutoMLJob([ 'AutoMLJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- AutoMLJobName
-
- Required: Yes
- Type: string
The name of the object you are requesting.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
StopCompilationJob
$result = $client->stopCompilationJob
([/* ... */]); $promise = $client->stopCompilationJobAsync
([/* ... */]);
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 CompilationJobStatus
of the job to Stopping
. After Amazon SageMaker stops the job, it sets the CompilationJobStatus
to Stopped
.
Parameter Syntax
$result = $client->stopCompilationJob([ 'CompilationJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- CompilationJobName
-
- Required: Yes
- Type: string
The name of the model compilation job to stop.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
StopEdgeDeploymentStage
$result = $client->stopEdgeDeploymentStage
([/* ... */]); $promise = $client->stopEdgeDeploymentStageAsync
([/* ... */]);
Stops a stage in an edge deployment plan.
Parameter Syntax
$result = $client->stopEdgeDeploymentStage([ 'EdgeDeploymentPlanName' => '<string>', // REQUIRED 'StageName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- EdgeDeploymentPlanName
-
- Required: Yes
- Type: string
The name of the edge deployment plan to stop.
- StageName
-
- Required: Yes
- Type: string
The name of the stage to stop.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
StopEdgePackagingJob
$result = $client->stopEdgePackagingJob
([/* ... */]); $promise = $client->stopEdgePackagingJobAsync
([/* ... */]);
Request to stop an edge packaging job.
Parameter Syntax
$result = $client->stopEdgePackagingJob([ 'EdgePackagingJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- EdgePackagingJobName
-
- Required: Yes
- Type: string
The name of the edge packaging job.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
StopHyperParameterTuningJob
$result = $client->stopHyperParameterTuningJob
([/* ... */]); $promise = $client->stopHyperParameterTuningJobAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->stopHyperParameterTuningJob([ 'HyperParameterTuningJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- HyperParameterTuningJobName
-
- Required: Yes
- Type: string
The name of the tuning job to stop.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
StopInferenceExperiment
$result = $client->stopInferenceExperiment
([/* ... */]); $promise = $client->stopInferenceExperimentAsync
([/* ... */]);
Stops an inference experiment.
Parameter Syntax
$result = $client->stopInferenceExperiment([ 'DesiredModelVariants' => [ [ 'InfrastructureConfig' => [ // REQUIRED 'InfrastructureType' => 'RealTimeInference', // REQUIRED 'RealTimeInferenceConfig' => [ // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge', // REQUIRED ], ], 'ModelName' => '<string>', // REQUIRED 'VariantName' => '<string>', // REQUIRED ], // ... ], 'DesiredState' => 'Completed|Cancelled', 'ModelVariantActions' => ['<string>', ...], // REQUIRED 'Name' => '<string>', // REQUIRED 'Reason' => '<string>', ]);
Parameter Details
Members
- DesiredModelVariants
-
- Type: Array of ModelVariantConfig structures
An array of
ModelVariantConfig
objects. There is one for each variant that you want to deploy after the inference experiment stops. EachModelVariantConfig
describes the infrastructure configuration for deploying the corresponding variant. - DesiredState
-
- Type: string
The desired state of the experiment after stopping. The possible states are the following:
-
Completed
: The experiment completed successfully -
Cancelled
: The experiment was canceled
- ModelVariantActions
-
- Required: Yes
- Type: Associative array of custom strings keys (ModelVariantName) to strings
Array of key-value pairs, with names of variants mapped to actions. The possible actions are the following:
-
Promote
- Promote the shadow variant to a production variant -
Remove
- Delete the variant -
Retain
- Keep the variant as it is
- Name
-
- Required: Yes
- Type: string
The name of the inference experiment to stop.
- Reason
-
- Type: string
The reason for stopping the experiment.
Result Syntax
[ 'InferenceExperimentArn' => '<string>', ]
Result Details
Members
- InferenceExperimentArn
-
- Required: Yes
- Type: string
The ARN of the stopped inference experiment.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.- ResourceNotFound:
Resource being access is not found.
StopInferenceRecommendationsJob
$result = $client->stopInferenceRecommendationsJob
([/* ... */]); $promise = $client->stopInferenceRecommendationsJobAsync
([/* ... */]);
Stops an Inference Recommender job.
Parameter Syntax
$result = $client->stopInferenceRecommendationsJob([ 'JobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- JobName
-
- Required: Yes
- Type: string
The name of the job you want to stop.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
StopLabelingJob
$result = $client->stopLabelingJob
([/* ... */]); $promise = $client->stopLabelingJobAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->stopLabelingJob([ 'LabelingJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- LabelingJobName
-
- Required: Yes
- Type: string
The name of the labeling job to stop.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
StopMlflowTrackingServer
$result = $client->stopMlflowTrackingServer
([/* ... */]); $promise = $client->stopMlflowTrackingServerAsync
([/* ... */]);
Programmatically stop an MLflow Tracking Server.
Parameter Syntax
$result = $client->stopMlflowTrackingServer([ 'TrackingServerName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TrackingServerName
-
- Required: Yes
- Type: string
The name of the tracking server to stop.
Result Syntax
[ 'TrackingServerArn' => '<string>', ]
Result Details
Members
- TrackingServerArn
-
- Type: string
The ARN of the stopped tracking server.
Errors
- ResourceNotFound:
Resource being access is not found.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
StopMonitoringSchedule
$result = $client->stopMonitoringSchedule
([/* ... */]); $promise = $client->stopMonitoringScheduleAsync
([/* ... */]);
Stops a previously started monitoring schedule.
Parameter Syntax
$result = $client->stopMonitoringSchedule([ 'MonitoringScheduleName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- MonitoringScheduleName
-
- Required: Yes
- Type: string
The name of the schedule to stop.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
StopNotebookInstance
$result = $client->stopNotebookInstance
([/* ... */]); $promise = $client->stopNotebookInstanceAsync
([/* ... */]);
Terminates the ML compute instance. Before terminating the instance, SageMaker disconnects the ML storage volume from it. SageMaker preserves the ML storage volume. 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.
Parameter Syntax
$result = $client->stopNotebookInstance([ 'NotebookInstanceName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- NotebookInstanceName
-
- Required: Yes
- Type: string
The name of the notebook instance to terminate.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
StopOptimizationJob
$result = $client->stopOptimizationJob
([/* ... */]); $promise = $client->stopOptimizationJobAsync
([/* ... */]);
Ends a running inference optimization job.
Parameter Syntax
$result = $client->stopOptimizationJob([ 'OptimizationJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- OptimizationJobName
-
- Required: Yes
- Type: string
The name that you assigned to the optimization job.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
StopPipelineExecution
$result = $client->stopPipelineExecution
([/* ... */]); $promise = $client->stopPipelineExecutionAsync
([/* ... */]);
Stops a pipeline execution.
Callback Step
A pipeline execution won't stop while a callback step is running. When you call StopPipelineExecution
on a pipeline execution with a running callback step, SageMaker Pipelines sends an additional Amazon SQS message to the specified SQS queue. The body of the SQS message contains a "Status" field which is set to "Stopping".
You should add logic to your Amazon SQS message consumer to take any needed action (for example, resource cleanup) upon receipt of the message followed by a call to SendPipelineExecutionStepSuccess
or SendPipelineExecutionStepFailure
.
Only when SageMaker Pipelines receives one of these calls will it stop the pipeline execution.
Lambda Step
A pipeline execution can't be stopped while a lambda step is running because the Lambda function invoked by the lambda step can't be stopped. If you attempt to stop the execution while the Lambda function is running, the pipeline waits for the Lambda function to finish or until the timeout is hit, whichever occurs first, and then stops. If the Lambda function finishes, the pipeline execution status is Stopped
. If the timeout is hit the pipeline execution status is Failed
.
Parameter Syntax
$result = $client->stopPipelineExecution([ 'ClientRequestToken' => '<string>', // REQUIRED 'PipelineExecutionArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ClientRequestToken
-
- Required: Yes
- Type: string
A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
- PipelineExecutionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
Result Syntax
[ 'PipelineExecutionArn' => '<string>', ]
Result Details
Members
- PipelineExecutionArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
Errors
- ResourceNotFound:
Resource being access is not found.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
StopProcessingJob
$result = $client->stopProcessingJob
([/* ... */]); $promise = $client->stopProcessingJobAsync
([/* ... */]);
Stops a processing job.
Parameter Syntax
$result = $client->stopProcessingJob([ 'ProcessingJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ProcessingJobName
-
- Required: Yes
- Type: string
The name of the processing job to stop.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
StopTrainingJob
$result = $client->stopTrainingJob
([/* ... */]); $promise = $client->stopTrainingJobAsync
([/* ... */]);
Stops a training job. To stop a job, 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, SageMaker changes the status of the job to Stopping
. After SageMaker stops the job, it sets the status to Stopped
.
Parameter Syntax
$result = $client->stopTrainingJob([ 'TrainingJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TrainingJobName
-
- Required: Yes
- Type: string
The name of the training job to stop.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
StopTransformJob
$result = $client->stopTransformJob
([/* ... */]); $promise = $client->stopTransformJobAsync
([/* ... */]);
Stops a batch 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 batch transform job before it is completed, Amazon SageMaker doesn't store the job's output in Amazon S3.
Parameter Syntax
$result = $client->stopTransformJob([ 'TransformJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- TransformJobName
-
- Required: Yes
- Type: string
The name of the batch transform job to stop.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
UpdateAction
$result = $client->updateAction
([/* ... */]); $promise = $client->updateActionAsync
([/* ... */]);
Updates an action.
Parameter Syntax
$result = $client->updateAction([ 'ActionName' => '<string>', // REQUIRED 'Description' => '<string>', 'Properties' => ['<string>', ...], 'PropertiesToRemove' => ['<string>', ...], 'Status' => 'Unknown|InProgress|Completed|Failed|Stopping|Stopped', ]);
Parameter Details
Members
- ActionName
-
- Required: Yes
- Type: string
The name of the action to update.
- Description
-
- Type: string
The new description for the action.
- Properties
-
- Type: Associative array of custom strings keys (StringParameterValue) to strings
The new list of properties. Overwrites the current property list.
- PropertiesToRemove
-
- Type: Array of strings
A list of properties to remove.
- Status
-
- Type: string
The new status for the action.
Result Syntax
[ 'ActionArn' => '<string>', ]
Result Details
Members
- ActionArn
-
- Type: string
The Amazon Resource Name (ARN) of the action.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.- ResourceNotFound:
Resource being access is not found.
UpdateAppImageConfig
$result = $client->updateAppImageConfig
([/* ... */]); $promise = $client->updateAppImageConfigAsync
([/* ... */]);
Updates the properties of an AppImageConfig.
Parameter Syntax
$result = $client->updateAppImageConfig([ 'AppImageConfigName' => '<string>', // REQUIRED 'CodeEditorAppImageConfig' => [ 'ContainerConfig' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ContainerEnvironmentVariables' => ['<string>', ...], ], 'FileSystemConfig' => [ 'DefaultGid' => <integer>, 'DefaultUid' => <integer>, 'MountPath' => '<string>', ], ], 'JupyterLabAppImageConfig' => [ 'ContainerConfig' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ContainerEnvironmentVariables' => ['<string>', ...], ], 'FileSystemConfig' => [ 'DefaultGid' => <integer>, 'DefaultUid' => <integer>, 'MountPath' => '<string>', ], ], 'KernelGatewayImageConfig' => [ 'FileSystemConfig' => [ 'DefaultGid' => <integer>, 'DefaultUid' => <integer>, 'MountPath' => '<string>', ], 'KernelSpecs' => [ // REQUIRED [ 'DisplayName' => '<string>', 'Name' => '<string>', // REQUIRED ], // ... ], ], ]);
Parameter Details
Members
- AppImageConfigName
-
- Required: Yes
- Type: string
The name of the AppImageConfig to update.
- CodeEditorAppImageConfig
-
- Type: CodeEditorAppImageConfig structure
The Code Editor app running on the image.
- JupyterLabAppImageConfig
-
- Type: JupyterLabAppImageConfig structure
The JupyterLab app running on the image.
- KernelGatewayImageConfig
-
- Type: KernelGatewayImageConfig structure
The new KernelGateway app to run on the image.
Result Syntax
[ 'AppImageConfigArn' => '<string>', ]
Result Details
Members
- AppImageConfigArn
-
- Type: string
The ARN for the AppImageConfig.
Errors
- ResourceNotFound:
Resource being access is not found.
UpdateArtifact
$result = $client->updateArtifact
([/* ... */]); $promise = $client->updateArtifactAsync
([/* ... */]);
Updates an artifact.
Parameter Syntax
$result = $client->updateArtifact([ 'ArtifactArn' => '<string>', // REQUIRED 'ArtifactName' => '<string>', 'Properties' => ['<string>', ...], 'PropertiesToRemove' => ['<string>', ...], ]);
Parameter Details
Members
- ArtifactArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the artifact to update.
- ArtifactName
-
- Type: string
The new name for the artifact.
- Properties
-
- Type: Associative array of custom strings keys (StringParameterValue) to strings
The new list of properties. Overwrites the current property list.
- PropertiesToRemove
-
- Type: Array of strings
A list of properties to remove.
Result Syntax
[ 'ArtifactArn' => '<string>', ]
Result Details
Members
- ArtifactArn
-
- Type: string
The Amazon Resource Name (ARN) of the artifact.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.- ResourceNotFound:
Resource being access is not found.
UpdateCluster
$result = $client->updateCluster
([/* ... */]); $promise = $client->updateClusterAsync
([/* ... */]);
Updates a SageMaker HyperPod cluster.
Parameter Syntax
$result = $client->updateCluster([ 'ClusterName' => '<string>', // REQUIRED 'InstanceGroups' => [ // REQUIRED [ 'ExecutionRole' => '<string>', // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceGroupName' => '<string>', // REQUIRED 'InstanceStorageConfigs' => [ [ 'EbsVolumeConfig' => [ 'VolumeSizeInGB' => <integer>, // REQUIRED ], ], // ... ], 'InstanceType' => 'ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.12xlarge|ml.g5.16xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.c5n.large|ml.c5n.2xlarge|ml.c5n.4xlarge|ml.c5n.9xlarge|ml.c5n.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge', // REQUIRED 'LifeCycleConfig' => [ // REQUIRED 'OnCreate' => '<string>', // REQUIRED 'SourceS3Uri' => '<string>', // REQUIRED ], 'ThreadsPerCore' => <integer>, ], // ... ], ]);
Parameter Details
Members
- ClusterName
-
- Required: Yes
- Type: string
Specify the name of the SageMaker HyperPod cluster you want to update.
- InstanceGroups
-
- Required: Yes
- Type: Array of ClusterInstanceGroupSpecification structures
Specify the instance groups to update.
Result Syntax
[ 'ClusterArn' => '<string>', ]
Result Details
Members
- ClusterArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the updated SageMaker HyperPod cluster.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceNotFound:
Resource being access is not found.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
UpdateClusterSoftware
$result = $client->updateClusterSoftware
([/* ... */]); $promise = $client->updateClusterSoftwareAsync
([/* ... */]);
Updates the platform software of a SageMaker HyperPod cluster for security patching. To learn how to use this API, see Update the SageMaker HyperPod platform software of a cluster.
Parameter Syntax
$result = $client->updateClusterSoftware([ 'ClusterName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ClusterName
-
- Required: Yes
- Type: string
Specify the name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster you want to update for security patching.
Result Syntax
[ 'ClusterArn' => '<string>', ]
Result Details
Members
- ClusterArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster being updated for security patching.
Errors
- ResourceNotFound:
Resource being access is not found.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
UpdateCodeRepository
$result = $client->updateCodeRepository
([/* ... */]); $promise = $client->updateCodeRepositoryAsync
([/* ... */]);
Updates the specified Git repository with the specified values.
Parameter Syntax
$result = $client->updateCodeRepository([ 'CodeRepositoryName' => '<string>', // REQUIRED 'GitConfig' => [ 'SecretArn' => '<string>', ], ]);
Parameter Details
Members
- CodeRepositoryName
-
- Required: Yes
- Type: string
The name of the Git repository to update.
- GitConfig
-
- Type: GitConfigForUpdate structure
The configuration of the git repository, including the URL and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository. The secret must have a staging label of
AWSCURRENT
and must be in the following format:{"username": UserName, "password": Password}
Result Syntax
[ 'CodeRepositoryArn' => '<string>', ]
Result Details
Members
- CodeRepositoryArn
-
- Required: Yes
- Type: string
The ARN of the Git repository.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
UpdateContext
$result = $client->updateContext
([/* ... */]); $promise = $client->updateContextAsync
([/* ... */]);
Updates a context.
Parameter Syntax
$result = $client->updateContext([ 'ContextName' => '<string>', // REQUIRED 'Description' => '<string>', 'Properties' => ['<string>', ...], 'PropertiesToRemove' => ['<string>', ...], ]);
Parameter Details
Members
- ContextName
-
- Required: Yes
- Type: string
The name of the context to update.
- Description
-
- Type: string
The new description for the context.
- Properties
-
- Type: Associative array of custom strings keys (StringParameterValue) to strings
The new list of properties. Overwrites the current property list.
- PropertiesToRemove
-
- Type: Array of strings
A list of properties to remove.
Result Syntax
[ 'ContextArn' => '<string>', ]
Result Details
Members
- ContextArn
-
- Type: string
The Amazon Resource Name (ARN) of the context.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.- ResourceNotFound:
Resource being access is not found.
UpdateDeviceFleet
$result = $client->updateDeviceFleet
([/* ... */]); $promise = $client->updateDeviceFleetAsync
([/* ... */]);
Updates a fleet of devices.
Parameter Syntax
$result = $client->updateDeviceFleet([ 'Description' => '<string>', 'DeviceFleetName' => '<string>', // REQUIRED 'EnableIotRoleAlias' => true || false, 'OutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'PresetDeploymentConfig' => '<string>', 'PresetDeploymentType' => 'GreengrassV2Component', 'S3OutputLocation' => '<string>', // REQUIRED ], 'RoleArn' => '<string>', ]);
Parameter Details
Members
- Description
-
- Type: string
Description of the fleet.
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the fleet.
- EnableIotRoleAlias
-
- Type: boolean
Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".
For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".
- OutputConfig
-
- Required: Yes
- Type: EdgeOutputConfig structure
Output configuration for storing sample data collected by the fleet.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the device.
Result Syntax
[]
Result Details
Errors
- ResourceInUse:
Resource being accessed is in use.
UpdateDevices
$result = $client->updateDevices
([/* ... */]); $promise = $client->updateDevicesAsync
([/* ... */]);
Updates one or more devices in a fleet.
Parameter Syntax
$result = $client->updateDevices([ 'DeviceFleetName' => '<string>', // REQUIRED 'Devices' => [ // REQUIRED [ 'Description' => '<string>', 'DeviceName' => '<string>', // REQUIRED 'IotThingName' => '<string>', ], // ... ], ]);
Parameter Details
Members
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the fleet the devices belong to.
- Devices
-
- Required: Yes
- Type: Array of Device structures
List of devices to register with Edge Manager agent.
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
UpdateDomain
$result = $client->updateDomain
([/* ... */]); $promise = $client->updateDomainAsync
([/* ... */]);
Updates the default settings for new user profiles in the domain.
Parameter Syntax
$result = $client->updateDomain([ 'AppNetworkAccessType' => 'PublicInternetOnly|VpcOnly', 'AppSecurityGroupManagement' => 'Service|Customer', 'DefaultSpaceSettings' => [ 'CustomFileSystemConfigs' => [ [ 'EFSFileSystemConfig' => [ 'FileSystemId' => '<string>', // REQUIRED 'FileSystemPath' => '<string>', ], ], // ... ], 'CustomPosixUserConfig' => [ 'Gid' => <integer>, // REQUIRED 'Uid' => <integer>, // REQUIRED ], 'ExecutionRole' => '<string>', 'JupyterLabAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'EmrSettings' => [ 'AssumableRoleArns' => ['<string>', ...], 'ExecutionRoleArns' => ['<string>', ...], ], 'LifecycleConfigArns' => ['<string>', ...], ], 'JupyterServerAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'KernelGatewayAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'SecurityGroups' => ['<string>', ...], 'SpaceStorageSettings' => [ 'DefaultEbsStorageSettings' => [ 'DefaultEbsVolumeSizeInGb' => <integer>, // REQUIRED 'MaximumEbsVolumeSizeInGb' => <integer>, // REQUIRED ], ], ], 'DefaultUserSettings' => [ 'CanvasAppSettings' => [ 'DirectDeploySettings' => [ 'Status' => 'ENABLED|DISABLED', ], 'EmrServerlessSettings' => [ 'ExecutionRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'GenerativeAiSettings' => [ 'AmazonBedrockRoleArn' => '<string>', ], 'IdentityProviderOAuthSettings' => [ [ 'DataSourceName' => 'SalesforceGenie|Snowflake', 'SecretArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], // ... ], 'KendraSettings' => [ 'Status' => 'ENABLED|DISABLED', ], 'ModelRegisterSettings' => [ 'CrossAccountModelRegisterRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'TimeSeriesForecastingSettings' => [ 'AmazonForecastRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'WorkspaceSettings' => [ 'S3ArtifactPath' => '<string>', 'S3KmsKeyId' => '<string>', ], ], 'CodeEditorAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'CustomFileSystemConfigs' => [ [ 'EFSFileSystemConfig' => [ 'FileSystemId' => '<string>', // REQUIRED 'FileSystemPath' => '<string>', ], ], // ... ], 'CustomPosixUserConfig' => [ 'Gid' => <integer>, // REQUIRED 'Uid' => <integer>, // REQUIRED ], 'DefaultLandingUri' => '<string>', 'ExecutionRole' => '<string>', 'JupyterLabAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'EmrSettings' => [ 'AssumableRoleArns' => ['<string>', ...], 'ExecutionRoleArns' => ['<string>', ...], ], 'LifecycleConfigArns' => ['<string>', ...], ], 'JupyterServerAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'KernelGatewayAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'RSessionAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'RStudioServerProAppSettings' => [ 'AccessStatus' => 'ENABLED|DISABLED', 'UserGroup' => 'R_STUDIO_ADMIN|R_STUDIO_USER', ], 'SecurityGroups' => ['<string>', ...], 'SharingSettings' => [ 'NotebookOutputOption' => 'Allowed|Disabled', 'S3KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'SpaceStorageSettings' => [ 'DefaultEbsStorageSettings' => [ 'DefaultEbsVolumeSizeInGb' => <integer>, // REQUIRED 'MaximumEbsVolumeSizeInGb' => <integer>, // REQUIRED ], ], 'StudioWebPortal' => 'ENABLED|DISABLED', 'StudioWebPortalSettings' => [ 'HiddenAppTypes' => ['<string>', ...], 'HiddenMlTools' => ['<string>', ...], ], 'TensorBoardAppSettings' => [ 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], ], 'DomainId' => '<string>', // REQUIRED 'DomainSettingsForUpdate' => [ 'AmazonQSettings' => [ 'QProfileArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'DockerSettings' => [ 'EnableDockerAccess' => 'ENABLED|DISABLED', 'VpcOnlyTrustedAccounts' => ['<string>', ...], ], 'ExecutionRoleIdentityConfig' => 'USER_PROFILE_NAME|DISABLED', 'RStudioServerProDomainSettingsForUpdate' => [ 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'DomainExecutionRoleArn' => '<string>', // REQUIRED 'RStudioConnectUrl' => '<string>', 'RStudioPackageManagerUrl' => '<string>', ], 'SecurityGroupIds' => ['<string>', ...], ], 'SubnetIds' => ['<string>', ...], ]);
Parameter Details
Members
- AppNetworkAccessType
-
- Type: string
Specifies the VPC used for non-EFS traffic.
-
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.
This configuration can only be modified if there are no apps in the
InService
,Pending
, orDeleting
state. The configuration cannot be updated ifDomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is already set orDomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is provided as part of the same request. - AppSecurityGroupManagement
-
- Type: string
The entity that creates and manages the required security groups for inter-app communication in
VPCOnly
mode. Required whenCreateDomain.AppNetworkAccessType
isVPCOnly
andDomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn
is provided. If setting up the domain for use with RStudio, this value must be set toService
. - DefaultSpaceSettings
-
- Type: DefaultSpaceSettings structure
The default settings used to create a space within the domain.
- DefaultUserSettings
-
- Type: UserSettings structure
A collection of settings.
- DomainId
-
- Required: Yes
- Type: string
The ID of the domain to be updated.
- DomainSettingsForUpdate
-
- Type: DomainSettingsForUpdate structure
A collection of
DomainSettings
configuration values to update. - SubnetIds
-
- Type: Array of strings
The VPC subnets that Studio uses for communication.
If removing subnets, ensure there are no apps in the
InService
,Pending
, orDeleting
state.
Result Syntax
[ 'DomainArn' => '<string>', ]
Result Details
Members
- DomainArn
-
- Type: string
The Amazon Resource Name (ARN) of the domain.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
UpdateEndpoint
$result = $client->updateEndpoint
([/* ... */]); $promise = $client->updateEndpointAsync
([/* ... */]);
Deploys the EndpointConfig
specified in the request to a new fleet of instances. SageMaker shifts endpoint traffic to the new instances with the updated endpoint configuration and then deletes the old instances using the previous EndpointConfig
(there is no availability loss). For more information about how to control the update and traffic shifting process, see Update models in production.
When 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.
Parameter Syntax
$result = $client->updateEndpoint([ 'DeploymentConfig' => [ 'AutoRollbackConfiguration' => [ 'Alarms' => [ [ 'AlarmName' => '<string>', ], // ... ], ], 'BlueGreenUpdatePolicy' => [ 'MaximumExecutionTimeoutInSeconds' => <integer>, 'TerminationWaitInSeconds' => <integer>, 'TrafficRoutingConfiguration' => [ // REQUIRED 'CanarySize' => [ 'Type' => 'INSTANCE_COUNT|CAPACITY_PERCENT', // REQUIRED 'Value' => <integer>, // REQUIRED ], 'LinearStepSize' => [ 'Type' => 'INSTANCE_COUNT|CAPACITY_PERCENT', // REQUIRED 'Value' => <integer>, // REQUIRED ], 'Type' => 'ALL_AT_ONCE|CANARY|LINEAR', // REQUIRED 'WaitIntervalInSeconds' => <integer>, // REQUIRED ], ], 'RollingUpdatePolicy' => [ 'MaximumBatchSize' => [ // REQUIRED 'Type' => 'INSTANCE_COUNT|CAPACITY_PERCENT', // REQUIRED 'Value' => <integer>, // REQUIRED ], 'MaximumExecutionTimeoutInSeconds' => <integer>, 'RollbackMaximumBatchSize' => [ 'Type' => 'INSTANCE_COUNT|CAPACITY_PERCENT', // REQUIRED 'Value' => <integer>, // REQUIRED ], 'WaitIntervalInSeconds' => <integer>, // REQUIRED ], ], 'EndpointConfigName' => '<string>', // REQUIRED 'EndpointName' => '<string>', // REQUIRED 'ExcludeRetainedVariantProperties' => [ [ 'VariantPropertyType' => 'DesiredInstanceCount|DesiredWeight|DataCaptureConfig', // REQUIRED ], // ... ], 'RetainAllVariantProperties' => true || false, 'RetainDeploymentConfig' => true || false, ]);
Parameter Details
Members
- DeploymentConfig
-
- Type: DeploymentConfig structure
The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
- EndpointConfigName
-
- Required: Yes
- Type: string
The name of the new endpoint configuration.
- EndpointName
-
- Required: Yes
- Type: string
The name of the endpoint whose configuration you want to update.
- ExcludeRetainedVariantProperties
-
- Type: Array of VariantProperty structures
When you are updating endpoint resources with
RetainAllVariantProperties
, whose value is set totrue
,ExcludeRetainedVariantProperties
specifies the list of type VariantProperty to override with the values provided byEndpointConfig
. If you don't specify a value forExcludeRetainedVariantProperties
, no variant properties are overridden. - RetainAllVariantProperties
-
- Type: boolean
When updating endpoint resources, enables or disables the retention of variant properties, such as the instance count or the variant weight. To retain the variant properties of an endpoint when updating it, set
RetainAllVariantProperties
totrue
. To use the variant properties specified in a newEndpointConfig
call when updating an endpoint, setRetainAllVariantProperties
tofalse
. The default isfalse
. - RetainDeploymentConfig
-
- Type: boolean
Specifies whether to reuse the last deployment configuration. The default value is false (the configuration is not reused).
Result Syntax
[ 'EndpointArn' => '<string>', ]
Result Details
Members
- EndpointArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the endpoint.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
UpdateEndpointWeightsAndCapacities
$result = $client->updateEndpointWeightsAndCapacities
([/* ... */]); $promise = $client->updateEndpointWeightsAndCapacitiesAsync
([/* ... */]);
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, 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.
Parameter Syntax
$result = $client->updateEndpointWeightsAndCapacities([ 'DesiredWeightsAndCapacities' => [ // REQUIRED [ 'DesiredInstanceCount' => <integer>, 'DesiredWeight' => <float>, 'ServerlessUpdateConfig' => [ 'MaxConcurrency' => <integer>, 'ProvisionedConcurrency' => <integer>, ], 'VariantName' => '<string>', // REQUIRED ], // ... ], 'EndpointName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DesiredWeightsAndCapacities
-
- Required: Yes
- Type: Array of DesiredWeightAndCapacity structures
An object that provides new capacity and weight values for a variant.
- EndpointName
-
- Required: Yes
- Type: string
The name of an existing SageMaker endpoint.
Result Syntax
[ 'EndpointArn' => '<string>', ]
Result Details
Members
- EndpointArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the updated endpoint.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
UpdateExperiment
$result = $client->updateExperiment
([/* ... */]); $promise = $client->updateExperimentAsync
([/* ... */]);
Adds, updates, or removes the description of an experiment. Updates the display name of an experiment.
Parameter Syntax
$result = $client->updateExperiment([ 'Description' => '<string>', 'DisplayName' => '<string>', 'ExperimentName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- Description
-
- Type: string
The description of the experiment.
- DisplayName
-
- Type: string
The name of the experiment as displayed. The name doesn't need to be unique. If
DisplayName
isn't specified,ExperimentName
is displayed. - ExperimentName
-
- Required: Yes
- Type: string
The name of the experiment to update.
Result Syntax
[ 'ExperimentArn' => '<string>', ]
Result Details
Members
- ExperimentArn
-
- Type: string
The Amazon Resource Name (ARN) of the experiment.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.- ResourceNotFound:
Resource being access is not found.
UpdateFeatureGroup
$result = $client->updateFeatureGroup
([/* ... */]); $promise = $client->updateFeatureGroupAsync
([/* ... */]);
Updates the feature group by either adding features or updating the online store configuration. Use one of the following request parameters at a time while using the UpdateFeatureGroup
API.
You can add features for your feature group using the FeatureAdditions
request parameter. Features cannot be removed from a feature group.
You can update the online store configuration by using the OnlineStoreConfig
request parameter. If a TtlDuration
is specified, the default TtlDuration
applies for all records added to the feature group after the feature group is updated. If a record level TtlDuration
exists from using the PutRecord
API, the record level TtlDuration
applies to that record instead of the default TtlDuration
. To remove the default TtlDuration
from an existing feature group, use the UpdateFeatureGroup
API and set the TtlDuration
Unit
and Value
to null
.
Parameter Syntax
$result = $client->updateFeatureGroup([ 'FeatureAdditions' => [ [ 'CollectionConfig' => [ 'VectorConfig' => [ 'Dimension' => <integer>, // REQUIRED ], ], 'CollectionType' => 'List|Set|Vector', 'FeatureName' => '<string>', // REQUIRED 'FeatureType' => 'Integral|Fractional|String', // REQUIRED ], // ... ], 'FeatureGroupName' => '<string>', // REQUIRED 'OnlineStoreConfig' => [ 'TtlDuration' => [ 'Unit' => 'Seconds|Minutes|Hours|Days|Weeks', 'Value' => <integer>, ], ], 'ThroughputConfig' => [ 'ProvisionedReadCapacityUnits' => <integer>, 'ProvisionedWriteCapacityUnits' => <integer>, 'ThroughputMode' => 'OnDemand|Provisioned', ], ]);
Parameter Details
Members
- FeatureAdditions
-
- Type: Array of FeatureDefinition structures
Updates the feature group. Updating a feature group is an asynchronous operation. When you get an HTTP 200 response, you've made a valid request. It takes some time after you've made a valid request for Feature Store to update the feature group.
- FeatureGroupName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the feature group that you're updating.
- OnlineStoreConfig
-
- Type: OnlineStoreConfigUpdate structure
Updates the feature group online store configuration.
- ThroughputConfig
-
- Type: ThroughputConfigUpdate structure
The new throughput configuration for the feature group. You can switch between on-demand and provisioned modes or update the read / write capacity of provisioned feature groups. You can switch a feature group to on-demand only once in a 24 hour period.
Result Syntax
[ 'FeatureGroupArn' => '<string>', ]
Result Details
Members
- FeatureGroupArn
-
- Required: Yes
- Type: string
The Amazon Resource Number (ARN) of the feature group that you're updating.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
UpdateFeatureMetadata
$result = $client->updateFeatureMetadata
([/* ... */]); $promise = $client->updateFeatureMetadataAsync
([/* ... */]);
Updates the description and parameters of the feature group.
Parameter Syntax
$result = $client->updateFeatureMetadata([ 'Description' => '<string>', 'FeatureGroupName' => '<string>', // REQUIRED 'FeatureName' => '<string>', // REQUIRED 'ParameterAdditions' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], 'ParameterRemovals' => ['<string>', ...], ]);
Parameter Details
Members
- Description
-
- Type: string
A description that you can write to better describe the feature.
- FeatureGroupName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the feature group containing the feature that you're updating.
- FeatureName
-
- Required: Yes
- Type: string
The name of the feature that you're updating.
- ParameterAdditions
-
- Type: Array of FeatureParameter structures
A list of key-value pairs that you can add to better describe the feature.
- ParameterRemovals
-
- Type: Array of strings
A list of parameter keys that you can specify to remove parameters that describe your feature.
Result Syntax
[]
Result Details
Errors
- ResourceNotFound:
Resource being access is not found.
UpdateHub
$result = $client->updateHub
([/* ... */]); $promise = $client->updateHubAsync
([/* ... */]);
Update a hub.
Parameter Syntax
$result = $client->updateHub([ 'HubDescription' => '<string>', 'HubDisplayName' => '<string>', 'HubName' => '<string>', // REQUIRED 'HubSearchKeywords' => ['<string>', ...], ]);
Parameter Details
Members
- HubDescription
-
- Type: string
A description of the updated hub.
- HubDisplayName
-
- Type: string
The display name of the hub.
- HubName
-
- Required: Yes
- Type: string
The name of the hub to update.
- HubSearchKeywords
-
- Type: Array of strings
The searchable keywords for the hub.
Result Syntax
[ 'HubArn' => '<string>', ]
Result Details
Members
- HubArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the updated hub.
Errors
- ResourceNotFound:
Resource being access is not found.
UpdateImage
$result = $client->updateImage
([/* ... */]); $promise = $client->updateImageAsync
([/* ... */]);
Updates the properties of a SageMaker image. To change the image's tags, use the AddTags and DeleteTags APIs.
Parameter Syntax
$result = $client->updateImage([ 'DeleteProperties' => ['<string>', ...], 'Description' => '<string>', 'DisplayName' => '<string>', 'ImageName' => '<string>', // REQUIRED 'RoleArn' => '<string>', ]);
Parameter Details
Members
- DeleteProperties
-
- Type: Array of strings
A list of properties to delete. Only the
Description
andDisplayName
properties can be deleted. - Description
-
- Type: string
The new description for the image.
- DisplayName
-
- Type: string
The new display name for the image.
- ImageName
-
- Required: Yes
- Type: string
The name of the image to update.
- RoleArn
-
- Type: string
The new ARN for the IAM role that enables Amazon SageMaker to perform tasks on your behalf.
Result Syntax
[ 'ImageArn' => '<string>', ]
Result Details
Members
- ImageArn
-
- Type: string
The ARN of the image.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
UpdateImageVersion
$result = $client->updateImageVersion
([/* ... */]); $promise = $client->updateImageVersionAsync
([/* ... */]);
Updates the properties of a SageMaker image version.
Parameter Syntax
$result = $client->updateImageVersion([ 'Alias' => '<string>', 'AliasesToAdd' => ['<string>', ...], 'AliasesToDelete' => ['<string>', ...], 'Horovod' => true || false, 'ImageName' => '<string>', // REQUIRED 'JobType' => 'TRAINING|INFERENCE|NOTEBOOK_KERNEL', 'MLFramework' => '<string>', 'Processor' => 'CPU|GPU', 'ProgrammingLang' => '<string>', 'ReleaseNotes' => '<string>', 'VendorGuidance' => 'NOT_PROVIDED|STABLE|TO_BE_ARCHIVED|ARCHIVED', 'Version' => <integer>, ]);
Parameter Details
Members
- Alias
-
- Type: string
The alias of the image version.
- AliasesToAdd
-
- Type: Array of strings
A list of aliases to add.
- AliasesToDelete
-
- Type: Array of strings
A list of aliases to delete.
- Horovod
-
- Type: boolean
Indicates Horovod compatibility.
- ImageName
-
- Required: Yes
- Type: string
The name of the image.
- JobType
-
- Type: string
Indicates SageMaker job type compatibility.
-
TRAINING
: The image version is compatible with SageMaker training jobs. -
INFERENCE
: The image version is compatible with SageMaker inference jobs. -
NOTEBOOK_KERNEL
: The image version is compatible with SageMaker notebook kernels.
- MLFramework
-
- Type: string
The machine learning framework vended in the image version.
- Processor
-
- Type: string
Indicates CPU or GPU compatibility.
-
CPU
: The image version is compatible with CPU. -
GPU
: The image version is compatible with GPU.
- ProgrammingLang
-
- Type: string
The supported programming language and its version.
- ReleaseNotes
-
- Type: string
The maintainer description of the image version.
- VendorGuidance
-
- Type: string
The availability of the image version specified by the maintainer.
-
NOT_PROVIDED
: The maintainers did not provide a status for image version stability. -
STABLE
: The image version is stable. -
TO_BE_ARCHIVED
: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months. -
ARCHIVED
: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
- Version
-
- Type: int
The version of the image.
Result Syntax
[ 'ImageVersionArn' => '<string>', ]
Result Details
Members
- ImageVersionArn
-
- Type: string
The ARN of the image version.
Errors
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
UpdateInferenceComponent
$result = $client->updateInferenceComponent
([/* ... */]); $promise = $client->updateInferenceComponentAsync
([/* ... */]);
Updates an inference component.
Parameter Syntax
$result = $client->updateInferenceComponent([ 'InferenceComponentName' => '<string>', // REQUIRED 'RuntimeConfig' => [ 'CopyCount' => <integer>, // REQUIRED ], 'Specification' => [ 'ComputeResourceRequirements' => [ // REQUIRED 'MaxMemoryRequiredInMb' => <integer>, 'MinMemoryRequiredInMb' => <integer>, // REQUIRED 'NumberOfAcceleratorDevicesRequired' => <float>, 'NumberOfCpuCoresRequired' => <float>, ], 'Container' => [ 'ArtifactUrl' => '<string>', 'Environment' => ['<string>', ...], 'Image' => '<string>', ], 'ModelName' => '<string>', 'StartupParameters' => [ 'ContainerStartupHealthCheckTimeoutInSeconds' => <integer>, 'ModelDataDownloadTimeoutInSeconds' => <integer>, ], ], ]);
Parameter Details
Members
- InferenceComponentName
-
- Required: Yes
- Type: string
The name of the inference component.
- RuntimeConfig
-
- Type: InferenceComponentRuntimeConfig structure
Runtime settings for a model that is deployed with an inference component.
- Specification
-
- Type: InferenceComponentSpecification structure
Details about the resources to deploy with this inference component, including the model, container, and compute resources.
Result Syntax
[ 'InferenceComponentArn' => '<string>', ]
Result Details
Members
- InferenceComponentArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the inference component.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
UpdateInferenceComponentRuntimeConfig
$result = $client->updateInferenceComponentRuntimeConfig
([/* ... */]); $promise = $client->updateInferenceComponentRuntimeConfigAsync
([/* ... */]);
Runtime settings for a model that is deployed with an inference component.
Parameter Syntax
$result = $client->updateInferenceComponentRuntimeConfig([ 'DesiredRuntimeConfig' => [ // REQUIRED 'CopyCount' => <integer>, // REQUIRED ], 'InferenceComponentName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DesiredRuntimeConfig
-
- Required: Yes
- Type: InferenceComponentRuntimeConfig structure
Runtime settings for a model that is deployed with an inference component.
- InferenceComponentName
-
- Required: Yes
- Type: string
The name of the inference component to update.
Result Syntax
[ 'InferenceComponentArn' => '<string>', ]
Result Details
Members
- InferenceComponentArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the inference component.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
UpdateInferenceExperiment
$result = $client->updateInferenceExperiment
([/* ... */]); $promise = $client->updateInferenceExperimentAsync
([/* ... */]);
Updates an inference experiment that you created. The status of the inference experiment has to be either Created
, Running
. For more information on the status of an inference experiment, see DescribeInferenceExperiment.
Parameter Syntax
$result = $client->updateInferenceExperiment([ 'DataStorageConfig' => [ 'ContentType' => [ 'CsvContentTypes' => ['<string>', ...], 'JsonContentTypes' => ['<string>', ...], ], 'Destination' => '<string>', // REQUIRED 'KmsKey' => '<string>', ], 'Description' => '<string>', 'ModelVariants' => [ [ 'InfrastructureConfig' => [ // REQUIRED 'InfrastructureType' => 'RealTimeInference', // REQUIRED 'RealTimeInferenceConfig' => [ // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge', // REQUIRED ], ], 'ModelName' => '<string>', // REQUIRED 'VariantName' => '<string>', // REQUIRED ], // ... ], 'Name' => '<string>', // REQUIRED 'Schedule' => [ 'EndTime' => <integer || string || DateTime>, 'StartTime' => <integer || string || DateTime>, ], 'ShadowModeConfig' => [ 'ShadowModelVariants' => [ // REQUIRED [ 'SamplingPercentage' => <integer>, // REQUIRED 'ShadowModelVariantName' => '<string>', // REQUIRED ], // ... ], 'SourceModelVariantName' => '<string>', // REQUIRED ], ]);
Parameter Details
Members
- DataStorageConfig
-
- Type: InferenceExperimentDataStorageConfig structure
The Amazon S3 location and configuration for storing inference request and response data.
- Description
-
- Type: string
The description of the inference experiment.
- ModelVariants
-
- Type: Array of ModelVariantConfig structures
An array of
ModelVariantConfig
objects. There is one for each variant, whose infrastructure configuration you want to update. - Name
-
- Required: Yes
- Type: string
The name of the inference experiment to be updated.
- Schedule
-
- Type: InferenceExperimentSchedule structure
The duration for which the inference experiment will run. If the status of the inference experiment is
Created
, then you can update both the start and end dates. If the status of the inference experiment isRunning
, then you can update only the end date. - ShadowModeConfig
-
- Type: ShadowModeConfig structure
The configuration of
ShadowMode
inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.
Result Syntax
[ 'InferenceExperimentArn' => '<string>', ]
Result Details
Members
- InferenceExperimentArn
-
- Required: Yes
- Type: string
The ARN of the updated inference experiment.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.- ResourceNotFound:
Resource being access is not found.
UpdateMlflowTrackingServer
$result = $client->updateMlflowTrackingServer
([/* ... */]); $promise = $client->updateMlflowTrackingServerAsync
([/* ... */]);
Updates properties of an existing MLflow Tracking Server.
Parameter Syntax
$result = $client->updateMlflowTrackingServer([ 'ArtifactStoreUri' => '<string>', 'AutomaticModelRegistration' => true || false, 'TrackingServerName' => '<string>', // REQUIRED 'TrackingServerSize' => 'Small|Medium|Large', 'WeeklyMaintenanceWindowStart' => '<string>', ]);
Parameter Details
Members
- ArtifactStoreUri
-
- Type: string
The new S3 URI for the general purpose bucket to use as the artifact store for the MLflow Tracking Server.
- AutomaticModelRegistration
-
- Type: boolean
Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry. To enable automatic model registration, set this value to
True
. To disable automatic model registration, set this value toFalse
. If not specified,AutomaticModelRegistration
defaults toFalse
- TrackingServerName
-
- Required: Yes
- Type: string
The name of the MLflow Tracking Server to update.
- TrackingServerSize
-
- Type: string
The new size for the MLflow Tracking Server.
- WeeklyMaintenanceWindowStart
-
- Type: string
The new weekly maintenance window start day and time to update. The maintenance window day and time should be in Coordinated Universal Time (UTC) 24-hour standard time. For example: TUE:03:30.
Result Syntax
[ 'TrackingServerArn' => '<string>', ]
Result Details
Members
- TrackingServerArn
-
- Type: string
The ARN of the updated MLflow Tracking Server.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
UpdateModelCard
$result = $client->updateModelCard
([/* ... */]); $promise = $client->updateModelCardAsync
([/* ... */]);
Update an Amazon SageMaker Model Card.
You cannot update both model card content and model card status in a single call.
Parameter Syntax
$result = $client->updateModelCard([ 'Content' => '<string>', 'ModelCardName' => '<string>', // REQUIRED 'ModelCardStatus' => 'Draft|PendingReview|Approved|Archived', ]);
Parameter Details
Members
- Content
-
- Type: string
The updated model card content. Content must be in model card JSON schema and provided as a string.
When updating model card content, be sure to include the full content and not just updated content.
- ModelCardName
-
- Required: Yes
- Type: string
The name or Amazon Resource Name (ARN) of the model card to update.
- ModelCardStatus
-
- Type: string
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
-
Draft
: The model card is a work in progress. -
PendingReview
: The model card is pending review. -
Approved
: The model card is approved. -
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
Result Syntax
[ 'ModelCardArn' => '<string>', ]
Result Details
Members
- ModelCardArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the updated model card.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
UpdateModelPackage
$result = $client->updateModelPackage
([/* ... */]); $promise = $client->updateModelPackageAsync
([/* ... */]);
Updates a versioned model.
Parameter Syntax
$result = $client->updateModelPackage([ 'AdditionalInferenceSpecificationsToAdd' => [ [ 'Containers' => [ // REQUIRED [ 'AdditionalS3DataSource' => [ 'CompressionType' => 'None|Gzip', 'S3DataType' => 'S3Object|S3Prefix', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'Image' => '<string>', // REQUIRED 'ImageDigest' => '<string>', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', // REQUIRED 'HubAccessConfig' => [ 'HubContentArn' => '<string>', // REQUIRED ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, // REQUIRED ], 'S3DataType' => 'S3Prefix|S3Object', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'ModelDataUrl' => '<string>', 'ModelInput' => [ 'DataInputConfig' => '<string>', // REQUIRED ], 'NearestModelName' => '<string>', 'ProductId' => '<string>', ], // ... ], 'Description' => '<string>', 'Name' => '<string>', // REQUIRED 'SupportedContentTypes' => ['<string>', ...], 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'SupportedTransformInstanceTypes' => ['<string>', ...], ], // ... ], 'ApprovalDescription' => '<string>', 'CustomerMetadataProperties' => ['<string>', ...], 'CustomerMetadataPropertiesToRemove' => ['<string>', ...], 'InferenceSpecification' => [ 'Containers' => [ // REQUIRED [ 'AdditionalS3DataSource' => [ 'CompressionType' => 'None|Gzip', 'S3DataType' => 'S3Object|S3Prefix', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Framework' => '<string>', 'FrameworkVersion' => '<string>', 'Image' => '<string>', // REQUIRED 'ImageDigest' => '<string>', 'ModelDataSource' => [ 'S3DataSource' => [ 'CompressionType' => 'None|Gzip', // REQUIRED 'HubAccessConfig' => [ 'HubContentArn' => '<string>', // REQUIRED ], 'ModelAccessConfig' => [ 'AcceptEula' => true || false, // REQUIRED ], 'S3DataType' => 'S3Prefix|S3Object', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'ModelDataUrl' => '<string>', 'ModelInput' => [ 'DataInputConfig' => '<string>', // REQUIRED ], 'NearestModelName' => '<string>', 'ProductId' => '<string>', ], // ... ], 'SupportedContentTypes' => ['<string>', ...], 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'SupportedTransformInstanceTypes' => ['<string>', ...], ], 'ModelApprovalStatus' => 'Approved|Rejected|PendingManualApproval', 'ModelCard' => [ 'ModelCardContent' => '<string>', 'ModelCardStatus' => 'Draft|PendingReview|Approved|Archived', ], 'ModelPackageArn' => '<string>', // REQUIRED 'SourceUri' => '<string>', ]);
Parameter Details
Members
- AdditionalInferenceSpecificationsToAdd
-
- Type: Array of AdditionalInferenceSpecificationDefinition structures
An array of additional Inference Specification objects to be added to the existing array additional Inference Specification. Total number of additional Inference Specifications can not exceed 15. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
- ApprovalDescription
-
- Type: string
A description for the approval status of the model.
- CustomerMetadataProperties
-
- Type: Associative array of custom strings keys (CustomerMetadataKey) to strings
The metadata properties associated with the model package versions.
- CustomerMetadataPropertiesToRemove
-
- Type: Array of strings
The metadata properties associated with the model package versions to remove.
- InferenceSpecification
-
- Type: InferenceSpecification structure
Specifies details about inference jobs that you can run with models based on this model package, including the following information:
-
The Amazon ECR paths of containers that contain the inference code and model artifacts.
-
The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
-
The input and output content formats that the model package supports for inference.
- ModelApprovalStatus
-
- Type: string
The approval status of the model.
- ModelCard
-
- Type: ModelPackageModelCard structure
The model card associated with the model package. Since
ModelPackageModelCard
is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema ofModelCard
. TheModelPackageModelCard
schema does not includemodel_package_details
, andmodel_overview
is composed of themodel_creator
andmodel_artifact
properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version. - ModelPackageArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model package.
- SourceUri
-
- Type: string
The URI of the source for the model package.
Result Syntax
[ 'ModelPackageArn' => '<string>', ]
Result Details
Members
- ModelPackageArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
UpdateMonitoringAlert
$result = $client->updateMonitoringAlert
([/* ... */]); $promise = $client->updateMonitoringAlertAsync
([/* ... */]);
Update the parameters of a model monitor alert.
Parameter Syntax
$result = $client->updateMonitoringAlert([ 'DatapointsToAlert' => <integer>, // REQUIRED 'EvaluationPeriod' => <integer>, // REQUIRED 'MonitoringAlertName' => '<string>', // REQUIRED 'MonitoringScheduleName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DatapointsToAlert
-
- Required: Yes
- Type: int
Within
EvaluationPeriod
, how many execution failures will raise an alert. - EvaluationPeriod
-
- Required: Yes
- Type: int
The number of most recent monitoring executions to consider when evaluating alert status.
- MonitoringAlertName
-
- Required: Yes
- Type: string
The name of a monitoring alert.
- MonitoringScheduleName
-
- Required: Yes
- Type: string
The name of a monitoring schedule.
Result Syntax
[ 'MonitoringAlertName' => '<string>', 'MonitoringScheduleArn' => '<string>', ]
Result Details
Members
- MonitoringAlertName
-
- Type: string
The name of a monitoring alert.
- MonitoringScheduleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the monitoring schedule.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceNotFound:
Resource being access is not found.
UpdateMonitoringSchedule
$result = $client->updateMonitoringSchedule
([/* ... */]); $promise = $client->updateMonitoringScheduleAsync
([/* ... */]);
Updates a previously created schedule.
Parameter Syntax
$result = $client->updateMonitoringSchedule([ 'MonitoringScheduleConfig' => [ // REQUIRED 'MonitoringJobDefinition' => [ 'BaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], 'StatisticsResource' => [ 'S3Uri' => '<string>', ], ], 'Environment' => ['<string>', ...], 'MonitoringAppSpecification' => [ // REQUIRED 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ImageUri' => '<string>', // REQUIRED 'PostAnalyticsProcessorSourceUri' => '<string>', 'RecordPreprocessorSourceUri' => '<string>', ], 'MonitoringInputs' => [ // REQUIRED [ 'BatchTransformInput' => [ 'DataCapturedDestinationS3Uri' => '<string>', // REQUIRED 'DatasetFormat' => [ // REQUIRED 'Csv' => [ 'Header' => true || false, ], 'Json' => [ 'Line' => true || false, ], 'Parquet' => [ ], ], 'EndTimeOffset' => '<string>', 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', // REQUIRED 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', // REQUIRED 'ExcludeFeaturesAttribute' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', // REQUIRED 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], ], // ... ], 'MonitoringOutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ // REQUIRED [ 'S3Output' => [ // REQUIRED 'LocalPath' => '<string>', // REQUIRED 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', // REQUIRED ], ], // ... ], ], 'MonitoringResources' => [ // REQUIRED 'ClusterConfig' => [ // REQUIRED 'InstanceCount' => <integer>, // REQUIRED 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', // REQUIRED 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], 'RoleArn' => '<string>', // REQUIRED 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, // REQUIRED ], ], 'MonitoringJobDefinitionName' => '<string>', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'ScheduleConfig' => [ 'DataAnalysisEndTime' => '<string>', 'DataAnalysisStartTime' => '<string>', 'ScheduleExpression' => '<string>', // REQUIRED ], ], 'MonitoringScheduleName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- MonitoringScheduleConfig
-
- Required: Yes
- Type: MonitoringScheduleConfig structure
The configuration object that specifies the monitoring schedule and defines the monitoring job.
- MonitoringScheduleName
-
- Required: Yes
- Type: string
The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
Result Syntax
[ 'MonitoringScheduleArn' => '<string>', ]
Result Details
Members
- MonitoringScheduleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the monitoring schedule.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceNotFound:
Resource being access is not found.
UpdateNotebookInstance
$result = $client->updateNotebookInstance
([/* ... */]); $promise = $client->updateNotebookInstanceAsync
([/* ... */]);
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.
Parameter Syntax
$result = $client->updateNotebookInstance([ 'AcceleratorTypes' => ['<string>', ...], 'AdditionalCodeRepositories' => ['<string>', ...], 'DefaultCodeRepository' => '<string>', 'DisassociateAcceleratorTypes' => true || false, 'DisassociateAdditionalCodeRepositories' => true || false, 'DisassociateDefaultCodeRepository' => true || false, 'DisassociateLifecycleConfig' => true || false, 'InstanceMetadataServiceConfiguration' => [ 'MinimumInstanceMetadataServiceVersion' => '<string>', // REQUIRED ], 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.c5d.xlarge|ml.c5d.2xlarge|ml.c5d.4xlarge|ml.c5d.9xlarge|ml.c5d.18xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.inf1.xlarge|ml.inf1.2xlarge|ml.inf1.6xlarge|ml.inf1.24xlarge|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge', 'LifecycleConfigName' => '<string>', 'NotebookInstanceName' => '<string>', // REQUIRED 'RoleArn' => '<string>', 'RootAccess' => 'Enabled|Disabled', 'VolumeSizeInGB' => <integer>, ]);
Parameter Details
Members
- AcceleratorTypes
-
- Type: Array of strings
A list of the Elastic Inference (EI) instance types to associate with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
- AdditionalCodeRepositories
-
- Type: Array of strings
An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
- DefaultCodeRepository
-
- Type: string
The Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
- DisassociateAcceleratorTypes
-
- Type: boolean
A list of the Elastic Inference (EI) instance types to remove from this notebook instance. This operation is idempotent. If you specify an accelerator type that is not associated with the notebook instance when you call this method, it does not throw an error.
- DisassociateAdditionalCodeRepositories
-
- Type: boolean
A list of names or URLs of the default Git repositories to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
- DisassociateDefaultCodeRepository
-
- Type: boolean
The name or URL of the default Git repository to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
- DisassociateLifecycleConfig
-
- Type: boolean
Set to
true
to remove the notebook instance lifecycle configuration currently associated with the notebook instance. This operation is idempotent. If you specify a lifecycle configuration that is not associated with the notebook instance when you call this method, it does not throw an error. - InstanceMetadataServiceConfiguration
-
- Type: InstanceMetadataServiceConfiguration structure
Information on the IMDS configuration of the notebook instance
- InstanceType
-
- Type: string
The Amazon ML compute instance type.
- LifecycleConfigName
-
- Type: string
The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
- NotebookInstanceName
-
- Required: Yes
- Type: string
The name of the notebook instance to update.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access the notebook instance. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the
iam:PassRole
permission. - RootAccess
-
- Type: string
Whether root access is enabled or disabled for users of the notebook instance. The default value is
Enabled
.If you set this to
Disabled
, users don't have root access on the notebook instance, but lifecycle configuration scripts still run with root permissions. - VolumeSizeInGB
-
- Type: int
The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. ML storage volumes are encrypted, so SageMaker can't determine the amount of available free space on the volume. Because of this, you can increase the volume size when you update a notebook instance, but you can't decrease the volume size. If you want to decrease the size of the ML storage volume in use, create a new notebook instance with the desired size.
Result Syntax
[]
Result Details
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
UpdateNotebookInstanceLifecycleConfig
$result = $client->updateNotebookInstanceLifecycleConfig
([/* ... */]); $promise = $client->updateNotebookInstanceLifecycleConfigAsync
([/* ... */]);
Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API.
Parameter Syntax
$result = $client->updateNotebookInstanceLifecycleConfig([ 'NotebookInstanceLifecycleConfigName' => '<string>', // REQUIRED 'OnCreate' => [ [ 'Content' => '<string>', ], // ... ], 'OnStart' => [ [ 'Content' => '<string>', ], // ... ], ]);
Parameter Details
Members
- NotebookInstanceLifecycleConfigName
-
- Required: Yes
- Type: string
The name of the lifecycle configuration.
- OnCreate
-
- Type: Array of NotebookInstanceLifecycleHook structures
The shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
- OnStart
-
- Type: Array of NotebookInstanceLifecycleHook structures
The shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
Result Syntax
[]
Result Details
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
UpdatePipeline
$result = $client->updatePipeline
([/* ... */]); $promise = $client->updatePipelineAsync
([/* ... */]);
Updates a pipeline.
Parameter Syntax
$result = $client->updatePipeline([ 'ParallelismConfiguration' => [ 'MaxParallelExecutionSteps' => <integer>, // REQUIRED ], 'PipelineDefinition' => '<string>', 'PipelineDefinitionS3Location' => [ 'Bucket' => '<string>', // REQUIRED 'ObjectKey' => '<string>', // REQUIRED 'VersionId' => '<string>', ], 'PipelineDescription' => '<string>', 'PipelineDisplayName' => '<string>', 'PipelineName' => '<string>', // REQUIRED 'RoleArn' => '<string>', ]);
Parameter Details
Members
- ParallelismConfiguration
-
- Type: ParallelismConfiguration structure
If specified, it applies to all executions of this pipeline by default.
- PipelineDefinition
-
- Type: string
The JSON pipeline definition.
- PipelineDefinitionS3Location
-
- Type: PipelineDefinitionS3Location structure
The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
- PipelineDescription
-
- Type: string
The description of the pipeline.
- PipelineDisplayName
-
- Type: string
The display name of the pipeline.
- PipelineName
-
- Required: Yes
- Type: string
The name of the pipeline to update.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) that the pipeline uses to execute.
Result Syntax
[ 'PipelineArn' => '<string>', ]
Result Details
Members
- PipelineArn
-
- Type: string
The Amazon Resource Name (ARN) of the updated pipeline.
Errors
- ResourceNotFound:
Resource being access is not found.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
UpdatePipelineExecution
$result = $client->updatePipelineExecution
([/* ... */]); $promise = $client->updatePipelineExecutionAsync
([/* ... */]);
Updates a pipeline execution.
Parameter Syntax
$result = $client->updatePipelineExecution([ 'ParallelismConfiguration' => [ 'MaxParallelExecutionSteps' => <integer>, // REQUIRED ], 'PipelineExecutionArn' => '<string>', // REQUIRED 'PipelineExecutionDescription' => '<string>', 'PipelineExecutionDisplayName' => '<string>', ]);
Parameter Details
Members
- ParallelismConfiguration
-
- Type: ParallelismConfiguration structure
This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
- PipelineExecutionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
- PipelineExecutionDescription
-
- Type: string
The description of the pipeline execution.
- PipelineExecutionDisplayName
-
- Type: string
The display name of the pipeline execution.
Result Syntax
[ 'PipelineExecutionArn' => '<string>', ]
Result Details
Members
- PipelineExecutionArn
-
- Type: string
The Amazon Resource Name (ARN) of the updated pipeline execution.
Errors
- ResourceNotFound:
Resource being access is not found.
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
UpdateProject
$result = $client->updateProject
([/* ... */]); $promise = $client->updateProjectAsync
([/* ... */]);
Updates a machine learning (ML) project that is created from a template that sets up an ML pipeline from training to deploying an approved model.
You must not update a project that is in use. If you update the ServiceCatalogProvisioningUpdateDetails
of a project that is active or being created, or updated, you may lose resources already created by the project.
Parameter Syntax
$result = $client->updateProject([ 'ProjectDescription' => '<string>', 'ProjectName' => '<string>', // REQUIRED 'ServiceCatalogProvisioningUpdateDetails' => [ 'ProvisioningArtifactId' => '<string>', 'ProvisioningParameters' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- ProjectDescription
-
- Type: string
The description for the project.
- ProjectName
-
- Required: Yes
- Type: string
The name of the project.
- ServiceCatalogProvisioningUpdateDetails
-
- Type: ServiceCatalogProvisioningUpdateDetails structure
The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources. In addition, the project must have tag update constraints set in order to include this parameter in the request. For more information, see Amazon Web Services Service Catalog Tag Update Constraints.
Result Syntax
[ 'ProjectArn' => '<string>', ]
Result Details
Members
- ProjectArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the project.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
UpdateSpace
$result = $client->updateSpace
([/* ... */]); $promise = $client->updateSpaceAsync
([/* ... */]);
Updates the settings of a space.
Parameter Syntax
$result = $client->updateSpace([ 'DomainId' => '<string>', // REQUIRED 'SpaceDisplayName' => '<string>', 'SpaceName' => '<string>', // REQUIRED 'SpaceSettings' => [ 'AppType' => 'JupyterServer|KernelGateway|DetailedProfiler|TensorBoard|CodeEditor|JupyterLab|RStudioServerPro|RSessionGateway|Canvas', 'CodeEditorAppSettings' => [ 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'CustomFileSystems' => [ [ 'EFSFileSystem' => [ 'FileSystemId' => '<string>', // REQUIRED ], ], // ... ], 'JupyterLabAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'JupyterServerAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'KernelGatewayAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'SpaceStorageSettings' => [ 'EbsStorageSettings' => [ 'EbsVolumeSizeInGb' => <integer>, // REQUIRED ], ], ], ]);
Parameter Details
Members
- DomainId
-
- Required: Yes
- Type: string
The ID of the associated domain.
- SpaceDisplayName
-
- Type: string
The name of the space that appears in the Amazon SageMaker Studio UI.
- SpaceName
-
- Required: Yes
- Type: string
The name of the space.
- SpaceSettings
-
- Type: SpaceSettings structure
A collection of space settings.
Result Syntax
[ 'SpaceArn' => '<string>', ]
Result Details
Members
- SpaceArn
-
- Type: string
The space's Amazon Resource Name (ARN).
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
UpdateTrainingJob
$result = $client->updateTrainingJob
([/* ... */]); $promise = $client->updateTrainingJobAsync
([/* ... */]);
Update a model training job to request a new Debugger profiling configuration or to change warm pool retention length.
Parameter Syntax
$result = $client->updateTrainingJob([ 'ProfilerConfig' => [ 'DisableProfiler' => true || false, 'ProfilingIntervalInMilliseconds' => <integer>, 'ProfilingParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', ], 'ProfilerRuleConfigurations' => [ [ 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.r5d.large|ml.r5d.xlarge|ml.r5d.2xlarge|ml.r5d.4xlarge|ml.r5d.8xlarge|ml.r5d.12xlarge|ml.r5d.16xlarge|ml.r5d.24xlarge', 'LocalPath' => '<string>', 'RuleConfigurationName' => '<string>', // REQUIRED 'RuleEvaluatorImage' => '<string>', // REQUIRED 'RuleParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', 'VolumeSizeInGB' => <integer>, ], // ... ], 'RemoteDebugConfig' => [ 'EnableRemoteDebug' => true || false, ], 'ResourceConfig' => [ 'KeepAlivePeriodInSeconds' => <integer>, // REQUIRED ], 'TrainingJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- ProfilerConfig
-
- Type: ProfilerConfigForUpdate structure
Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
- ProfilerRuleConfigurations
-
- Type: Array of ProfilerRuleConfiguration structures
Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
- RemoteDebugConfig
-
- Type: RemoteDebugConfigForUpdate structure
Configuration for remote debugging while the training job is running. You can update the remote debugging configuration when the
SecondaryStatus
of the job isDownloading
orTraining
.To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging. - ResourceConfig
-
- Type: ResourceConfigForUpdate structure
The training job
ResourceConfig
to update warm pool retention length. - TrainingJobName
-
- Required: Yes
- Type: string
The name of a training job to update the Debugger profiling configuration.
Result Syntax
[ 'TrainingJobArn' => '<string>', ]
Result Details
Members
- TrainingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the training job.
Errors
- ResourceNotFound:
Resource being access is not found.
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
UpdateTrial
$result = $client->updateTrial
([/* ... */]); $promise = $client->updateTrialAsync
([/* ... */]);
Updates the display name of a trial.
Parameter Syntax
$result = $client->updateTrial([ 'DisplayName' => '<string>', 'TrialName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DisplayName
-
- Type: string
The name of the trial as displayed. The name doesn't need to be unique. If
DisplayName
isn't specified,TrialName
is displayed. - TrialName
-
- Required: Yes
- Type: string
The name of the trial to update.
Result Syntax
[ 'TrialArn' => '<string>', ]
Result Details
Members
- TrialArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.- ResourceNotFound:
Resource being access is not found.
UpdateTrialComponent
$result = $client->updateTrialComponent
([/* ... */]); $promise = $client->updateTrialComponentAsync
([/* ... */]);
Updates one or more properties of a trial component.
Parameter Syntax
$result = $client->updateTrialComponent([ 'DisplayName' => '<string>', 'EndTime' => <integer || string || DateTime>, 'InputArtifacts' => [ '<TrialComponentKey128>' => [ 'MediaType' => '<string>', 'Value' => '<string>', // REQUIRED ], // ... ], 'InputArtifactsToRemove' => ['<string>', ...], 'OutputArtifacts' => [ '<TrialComponentKey128>' => [ 'MediaType' => '<string>', 'Value' => '<string>', // REQUIRED ], // ... ], 'OutputArtifactsToRemove' => ['<string>', ...], 'Parameters' => [ '<TrialComponentKey320>' => [ 'NumberValue' => <float>, 'StringValue' => '<string>', ], // ... ], 'ParametersToRemove' => ['<string>', ...], 'StartTime' => <integer || string || DateTime>, 'Status' => [ 'Message' => '<string>', 'PrimaryStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', ], 'TrialComponentName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- DisplayName
-
- Type: string
The name of the component as displayed. The name doesn't need to be unique. If
DisplayName
isn't specified,TrialComponentName
is displayed. - EndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component ended.
- InputArtifacts
-
- Type: Associative array of custom strings keys (TrialComponentKey128) to TrialComponentArtifact structures
Replaces all of the component's input artifacts with the specified artifacts or adds new input artifacts. Existing input artifacts are replaced if the trial component is updated with an identical input artifact key.
- InputArtifactsToRemove
-
- Type: Array of strings
The input artifacts to remove from the component.
- OutputArtifacts
-
- Type: Associative array of custom strings keys (TrialComponentKey128) to TrialComponentArtifact structures
Replaces all of the component's output artifacts with the specified artifacts or adds new output artifacts. Existing output artifacts are replaced if the trial component is updated with an identical output artifact key.
- OutputArtifactsToRemove
-
- Type: Array of strings
The output artifacts to remove from the component.
- Parameters
-
- Type: Associative array of custom strings keys (TrialComponentKey320) to TrialComponentParameterValue structures
Replaces all of the component's hyperparameters with the specified hyperparameters or add new hyperparameters. Existing hyperparameters are replaced if the trial component is updated with an identical hyperparameter key.
- ParametersToRemove
-
- Type: Array of strings
The hyperparameters to remove from the component.
- StartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component started.
- Status
-
- Type: TrialComponentStatus structure
The new status of the component.
- TrialComponentName
-
- Required: Yes
- Type: string
The name of the component to update.
Result Syntax
[ 'TrialComponentArn' => '<string>', ]
Result Details
Members
- TrialComponentArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial component.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.- ResourceNotFound:
Resource being access is not found.
UpdateUserProfile
$result = $client->updateUserProfile
([/* ... */]); $promise = $client->updateUserProfileAsync
([/* ... */]);
Updates a user profile.
Parameter Syntax
$result = $client->updateUserProfile([ 'DomainId' => '<string>', // REQUIRED 'UserProfileName' => '<string>', // REQUIRED 'UserSettings' => [ 'CanvasAppSettings' => [ 'DirectDeploySettings' => [ 'Status' => 'ENABLED|DISABLED', ], 'EmrServerlessSettings' => [ 'ExecutionRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'GenerativeAiSettings' => [ 'AmazonBedrockRoleArn' => '<string>', ], 'IdentityProviderOAuthSettings' => [ [ 'DataSourceName' => 'SalesforceGenie|Snowflake', 'SecretArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], // ... ], 'KendraSettings' => [ 'Status' => 'ENABLED|DISABLED', ], 'ModelRegisterSettings' => [ 'CrossAccountModelRegisterRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'TimeSeriesForecastingSettings' => [ 'AmazonForecastRoleArn' => '<string>', 'Status' => 'ENABLED|DISABLED', ], 'WorkspaceSettings' => [ 'S3ArtifactPath' => '<string>', 'S3KmsKeyId' => '<string>', ], ], 'CodeEditorAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'CustomFileSystemConfigs' => [ [ 'EFSFileSystemConfig' => [ 'FileSystemId' => '<string>', // REQUIRED 'FileSystemPath' => '<string>', ], ], // ... ], 'CustomPosixUserConfig' => [ 'Gid' => <integer>, // REQUIRED 'Uid' => <integer>, // REQUIRED ], 'DefaultLandingUri' => '<string>', 'ExecutionRole' => '<string>', 'JupyterLabAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'EmrSettings' => [ 'AssumableRoleArns' => ['<string>', ...], 'ExecutionRoleArns' => ['<string>', ...], ], 'LifecycleConfigArns' => ['<string>', ...], ], 'JupyterServerAppSettings' => [ 'CodeRepositories' => [ [ 'RepositoryUrl' => '<string>', // REQUIRED ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'KernelGatewayAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'LifecycleConfigArns' => ['<string>', ...], ], 'RSessionAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'RStudioServerProAppSettings' => [ 'AccessStatus' => 'ENABLED|DISABLED', 'UserGroup' => 'R_STUDIO_ADMIN|R_STUDIO_USER', ], 'SecurityGroups' => ['<string>', ...], 'SharingSettings' => [ 'NotebookOutputOption' => 'Allowed|Disabled', 'S3KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'SpaceStorageSettings' => [ 'DefaultEbsStorageSettings' => [ 'DefaultEbsVolumeSizeInGb' => <integer>, // REQUIRED 'MaximumEbsVolumeSizeInGb' => <integer>, // REQUIRED ], ], 'StudioWebPortal' => 'ENABLED|DISABLED', 'StudioWebPortalSettings' => [ 'HiddenAppTypes' => ['<string>', ...], 'HiddenMlTools' => ['<string>', ...], ], 'TensorBoardAppSettings' => [ 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.m5d.large|ml.m5d.xlarge|ml.m5d.2xlarge|ml.m5d.4xlarge|ml.m5d.8xlarge|ml.m5d.12xlarge|ml.m5d.16xlarge|ml.m5d.24xlarge|ml.c5.large|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.12xlarge|ml.c5.18xlarge|ml.c5.24xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.p3dn.24xlarge|ml.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge|ml.g5.xlarge|ml.g5.2xlarge|ml.g5.4xlarge|ml.g5.8xlarge|ml.g5.16xlarge|ml.g5.12xlarge|ml.g5.24xlarge|ml.g5.48xlarge|ml.g6.xlarge|ml.g6.2xlarge|ml.g6.4xlarge|ml.g6.8xlarge|ml.g6.12xlarge|ml.g6.16xlarge|ml.g6.24xlarge|ml.g6.48xlarge|ml.geospatial.interactive|ml.p4d.24xlarge|ml.p4de.24xlarge|ml.trn1.2xlarge|ml.trn1.32xlarge|ml.trn1n.32xlarge|ml.p5.48xlarge|ml.m6i.large|ml.m6i.xlarge|ml.m6i.2xlarge|ml.m6i.4xlarge|ml.m6i.8xlarge|ml.m6i.12xlarge|ml.m6i.16xlarge|ml.m6i.24xlarge|ml.m6i.32xlarge|ml.m7i.large|ml.m7i.xlarge|ml.m7i.2xlarge|ml.m7i.4xlarge|ml.m7i.8xlarge|ml.m7i.12xlarge|ml.m7i.16xlarge|ml.m7i.24xlarge|ml.m7i.48xlarge|ml.c6i.large|ml.c6i.xlarge|ml.c6i.2xlarge|ml.c6i.4xlarge|ml.c6i.8xlarge|ml.c6i.12xlarge|ml.c6i.16xlarge|ml.c6i.24xlarge|ml.c6i.32xlarge|ml.c7i.large|ml.c7i.xlarge|ml.c7i.2xlarge|ml.c7i.4xlarge|ml.c7i.8xlarge|ml.c7i.12xlarge|ml.c7i.16xlarge|ml.c7i.24xlarge|ml.c7i.48xlarge|ml.r6i.large|ml.r6i.xlarge|ml.r6i.2xlarge|ml.r6i.4xlarge|ml.r6i.8xlarge|ml.r6i.12xlarge|ml.r6i.16xlarge|ml.r6i.24xlarge|ml.r6i.32xlarge|ml.r7i.large|ml.r7i.xlarge|ml.r7i.2xlarge|ml.r7i.4xlarge|ml.r7i.8xlarge|ml.r7i.12xlarge|ml.r7i.16xlarge|ml.r7i.24xlarge|ml.r7i.48xlarge|ml.m6id.large|ml.m6id.xlarge|ml.m6id.2xlarge|ml.m6id.4xlarge|ml.m6id.8xlarge|ml.m6id.12xlarge|ml.m6id.16xlarge|ml.m6id.24xlarge|ml.m6id.32xlarge|ml.c6id.large|ml.c6id.xlarge|ml.c6id.2xlarge|ml.c6id.4xlarge|ml.c6id.8xlarge|ml.c6id.12xlarge|ml.c6id.16xlarge|ml.c6id.24xlarge|ml.c6id.32xlarge|ml.r6id.large|ml.r6id.xlarge|ml.r6id.2xlarge|ml.r6id.4xlarge|ml.r6id.8xlarge|ml.r6id.12xlarge|ml.r6id.16xlarge|ml.r6id.24xlarge|ml.r6id.32xlarge', 'LifecycleConfigArn' => '<string>', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionAlias' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], ], ]);
Parameter Details
Members
- DomainId
-
- Required: Yes
- Type: string
The domain ID.
- UserProfileName
-
- Required: Yes
- Type: string
The user profile name.
- UserSettings
-
- Type: UserSettings structure
A collection of settings.
Result Syntax
[ 'UserProfileArn' => '<string>', ]
Result Details
Members
- UserProfileArn
-
- Type: string
The user profile Amazon Resource Name (ARN).
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
- ResourceInUse:
Resource being accessed is in use.
- ResourceNotFound:
Resource being access is not found.
UpdateWorkforce
$result = $client->updateWorkforce
([/* ... */]); $promise = $client->updateWorkforceAsync
([/* ... */]);
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.
The worker portal is now supported in VPC and public internet.
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. 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.
To restrict access to all the workers in public internet, add the SourceIpConfig
CIDR value as "10.0.0.0/16".
Amazon SageMaker does not support Source Ip restriction for worker portals in VPC.
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 DeleteWorkteam 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 DescribeWorkforce operation.
This operation only applies to private workforces.
Parameter Syntax
$result = $client->updateWorkforce([ 'OidcConfig' => [ 'AuthenticationRequestExtraParams' => ['<string>', ...], 'AuthorizationEndpoint' => '<string>', // REQUIRED 'ClientId' => '<string>', // REQUIRED 'ClientSecret' => '<string>', // REQUIRED 'Issuer' => '<string>', // REQUIRED 'JwksUri' => '<string>', // REQUIRED 'LogoutEndpoint' => '<string>', // REQUIRED 'Scope' => '<string>', 'TokenEndpoint' => '<string>', // REQUIRED 'UserInfoEndpoint' => '<string>', // REQUIRED ], 'SourceIpConfig' => [ 'Cidrs' => ['<string>', ...], // REQUIRED ], 'WorkforceName' => '<string>', // REQUIRED 'WorkforceVpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], 'VpcId' => '<string>', ], ]);
Parameter Details
Members
- OidcConfig
-
- Type: OidcConfig structure
Use this parameter to update your OIDC Identity Provider (IdP) configuration for a workforce made using your own IdP.
- SourceIpConfig
-
- Type: SourceIpConfig structure
A list of one to ten worker IP address ranges (CIDRs) that can be used to access tasks assigned to this workforce.
Maximum: Ten CIDR values
- WorkforceName
-
- Required: Yes
- Type: string
The name of the private workforce that you want to update. You can find your workforce name by using the ListWorkforces operation.
- WorkforceVpcConfig
-
- Type: WorkforceVpcConfigRequest structure
Use this parameter to update your VPC configuration for a workforce.
Result Syntax
[ 'Workforce' => [ 'CognitoConfig' => [ 'ClientId' => '<string>', 'UserPool' => '<string>', ], 'CreateDate' => <DateTime>, 'FailureReason' => '<string>', 'LastUpdatedDate' => <DateTime>, 'OidcConfig' => [ 'AuthenticationRequestExtraParams' => ['<string>', ...], 'AuthorizationEndpoint' => '<string>', 'ClientId' => '<string>', 'Issuer' => '<string>', 'JwksUri' => '<string>', 'LogoutEndpoint' => '<string>', 'Scope' => '<string>', 'TokenEndpoint' => '<string>', 'UserInfoEndpoint' => '<string>', ], 'SourceIpConfig' => [ 'Cidrs' => ['<string>', ...], ], 'Status' => 'Initializing|Updating|Deleting|Failed|Active', 'SubDomain' => '<string>', 'WorkforceArn' => '<string>', 'WorkforceName' => '<string>', 'WorkforceVpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], 'VpcEndpointId' => '<string>', 'VpcId' => '<string>', ], ], ]
Result Details
Members
- Workforce
-
- Required: Yes
- Type: Workforce structure
A single private workforce. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
Errors
- ConflictException:
There was a conflict when you attempted to modify a SageMaker entity such as an
Experiment
orArtifact
.
UpdateWorkteam
$result = $client->updateWorkteam
([/* ... */]); $promise = $client->updateWorkteamAsync
([/* ... */]);
Updates an existing work team with new member definitions or description.
Parameter Syntax
$result = $client->updateWorkteam([ 'Description' => '<string>', 'MemberDefinitions' => [ [ 'CognitoMemberDefinition' => [ 'ClientId' => '<string>', // REQUIRED 'UserGroup' => '<string>', // REQUIRED 'UserPool' => '<string>', // REQUIRED ], 'OidcMemberDefinition' => [ 'Groups' => ['<string>', ...], ], ], // ... ], 'NotificationConfiguration' => [ 'NotificationTopicArn' => '<string>', ], 'WorkerAccessConfiguration' => [ 'S3Presign' => [ 'IamPolicyConstraints' => [ 'SourceIp' => 'Enabled|Disabled', 'VpcSourceIp' => 'Enabled|Disabled', ], ], ], 'WorkteamName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- Description
-
- Type: string
An updated description for the work team.
- MemberDefinitions
-
- Type: Array of MemberDefinition structures
A list of
MemberDefinition
objects that contains objects that identify the workers that make up the work team.Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use
CognitoMemberDefinition
. For workforces created using your own OIDC identity provider (IdP) useOidcMemberDefinition
. You should not provide input for both of these parameters in a single request.For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the
CognitoMemberDefinition
objects that make up the member definition must have the sameClientId
andUserPool
values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in
OidcMemberDefinition
by listing those groups inGroups
. Be aware that user groups that are already in the work team must also be listed inGroups
when you make this request to remain on the work team. If you do not include these user groups, they will no longer be associated with the work team you update. - NotificationConfiguration
-
- Type: NotificationConfiguration structure
Configures SNS topic notifications for available or expiring work items
- WorkerAccessConfiguration
-
- Type: WorkerAccessConfiguration structure
Use this optional parameter to constrain access to an Amazon S3 resource based on the IP address using supported IAM global condition keys. The Amazon S3 resource is accessed in the worker portal using a Amazon S3 presigned URL.
- WorkteamName
-
- Required: Yes
- Type: string
The name of the work team to update.
Result Syntax
[ 'Workteam' => [ 'CreateDate' => <DateTime>, 'Description' => '<string>', 'LastUpdatedDate' => <DateTime>, 'MemberDefinitions' => [ [ 'CognitoMemberDefinition' => [ 'ClientId' => '<string>', 'UserGroup' => '<string>', 'UserPool' => '<string>', ], 'OidcMemberDefinition' => [ 'Groups' => ['<string>', ...], ], ], // ... ], 'NotificationConfiguration' => [ 'NotificationTopicArn' => '<string>', ], 'ProductListingIds' => ['<string>', ...], 'SubDomain' => '<string>', 'WorkerAccessConfiguration' => [ 'S3Presign' => [ 'IamPolicyConstraints' => [ 'SourceIp' => 'Enabled|Disabled', 'VpcSourceIp' => 'Enabled|Disabled', ], ], ], 'WorkforceArn' => '<string>', 'WorkteamArn' => '<string>', 'WorkteamName' => '<string>', ], ]
Result Details
Members
- Workteam
-
- Required: Yes
- Type: Workteam structure
A
Workteam
object that describes the updated work team.
Errors
- ResourceLimitExceeded:
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
Shapes
ActionSource
Description
A structure describing the source of an action.
Members
- SourceId
-
- Type: string
The ID of the source.
- SourceType
-
- Type: string
The type of the source.
- SourceUri
-
- Required: Yes
- Type: string
The URI of the source.
ActionSummary
Description
Lists the properties of an action. An action represents an action or activity. Some examples are a workflow step and a model deployment. Generally, an action involves at least one input artifact or output artifact.
Members
- ActionArn
-
- Type: string
The Amazon Resource Name (ARN) of the action.
- ActionName
-
- Type: string
The name of the action.
- ActionType
-
- Type: string
The type of the action.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the action was created.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the action was last modified.
- Source
-
- Type: ActionSource structure
The source of the action.
- Status
-
- Type: string
The status of the action.
AdditionalInferenceSpecificationDefinition
Description
A structure of additional Inference Specification. Additional Inference Specification specifies details about inference jobs that can be run with models based on this model package
Members
- Containers
-
- Required: Yes
- Type: Array of ModelPackageContainerDefinition structures
The Amazon ECR registry path of the Docker image that contains the inference code.
- Description
-
- Type: string
A description of the additional Inference specification
- Name
-
- Required: Yes
- Type: string
A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.
- SupportedContentTypes
-
- Type: Array of strings
The supported MIME types for the input data.
- SupportedRealtimeInferenceInstanceTypes
-
- Type: Array of strings
A list of the instance types that are used to generate inferences in real-time.
- SupportedResponseMIMETypes
-
- Type: Array of strings
The supported MIME types for the output data.
- SupportedTransformInstanceTypes
-
- Type: Array of strings
A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
AdditionalModelDataSource
Description
Data sources that are available to your model in addition to the one that you specify for ModelDataSource
when you use the CreateModel
action.
Members
- ChannelName
-
- Required: Yes
- Type: string
A custom name for this
AdditionalModelDataSource
object. - S3DataSource
-
- Required: Yes
- Type: S3ModelDataSource structure
Specifies the S3 location of ML model data to deploy.
AdditionalS3DataSource
Description
A data source used for training or inference that is in addition to the input dataset or model data.
Members
- CompressionType
-
- Type: string
The type of compression used for an additional data source used in inference or training. Specify
None
if your additional data source is not compressed. - S3DataType
-
- Required: Yes
- Type: string
The data type of the additional data source that you specify for use in inference or training.
- S3Uri
-
- Required: Yes
- Type: string
The uniform resource identifier (URI) used to identify an additional data source used in inference or training.
AgentVersion
Description
Edge Manager agent version.
Members
- AgentCount
-
- Required: Yes
- Type: long (int|float)
The number of Edge Manager agents.
- Version
-
- Required: Yes
- Type: string
Version of the agent.
Alarm
Description
An Amazon CloudWatch alarm configured to monitor metrics on an endpoint.
Members
- AlarmName
-
- Type: string
The name of a CloudWatch alarm in your account.
AlgorithmSpecification
Description
Specifies the training algorithm to use in a CreateTrainingJob request.
For more information about algorithms provided by SageMaker, see Algorithms. For information about using your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
Members
- AlgorithmName
-
- Type: string
The name of the algorithm resource to use for the training job. This must be an algorithm resource that you created or subscribe to on Amazon Web Services Marketplace.
You must specify either the algorithm name to the
AlgorithmName
parameter or the image URI of the algorithm container to theTrainingImage
parameter.Note that the
AlgorithmName
parameter is mutually exclusive with theTrainingImage
parameter. If you specify a value for theAlgorithmName
parameter, you can't specify a value forTrainingImage
, and vice versa.If you specify values for both parameters, the training job might break; if you don't specify any value for both parameters, the training job might raise a
null
error. - ContainerArguments
-
- Type: Array of strings
The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.
- ContainerEntrypoint
-
- Type: Array of strings
The entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See How Amazon SageMaker Runs Your Training Image for more information.
- EnableSageMakerMetricsTimeSeries
-
- Type: boolean
To generate and save time-series metrics during training, set to
true
. The default isfalse
and time-series metrics aren't generated except in the following cases:-
You use one of the SageMaker built-in algorithms
-
You use one of the following Prebuilt SageMaker Docker Images:
-
Tensorflow (version >= 1.15)
-
MXNet (version >= 1.6)
-
PyTorch (version >= 1.3)
-
-
You specify at least one MetricDefinition
- MetricDefinitions
-
- Type: Array of MetricDefinition structures
A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.
- TrainingImage
-
- Type: string
The registry path of the Docker image that contains the training algorithm. For information about docker registry paths for SageMaker built-in algorithms, see Docker Registry Paths and Example Code in the Amazon SageMaker developer guide. SageMaker supports both
registry/repository[:tag]
andregistry/repository[@digest]
image path formats. For more information about using your custom training container, see Using Your Own Algorithms with Amazon SageMaker.You must specify either the algorithm name to the
AlgorithmName
parameter or the image URI of the algorithm container to theTrainingImage
parameter.For more information, see the note in the
AlgorithmName
parameter description. - TrainingImageConfig
-
- Type: TrainingImageConfig structure
The configuration to use an image from a private Docker registry for a training job.
- TrainingInputMode
-
- Required: Yes
- Type: string
The training input mode that the algorithm supports. For more information about input modes, see Algorithms.
Pipe mode
If an algorithm supports
Pipe
mode, Amazon SageMaker streams data directly from Amazon S3 to the container.File mode
If an algorithm supports
File
mode, SageMaker downloads the training data from S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume for the training container.You must provision the ML storage volume with sufficient capacity to accommodate the data downloaded from S3. In addition to the training data, the ML storage volume also stores the output model. The algorithm container uses the ML storage volume to also store intermediate information, if any.
For distributed algorithms, training data is distributed uniformly. Your training duration is predictable if the input data objects sizes are approximately the same. SageMaker does not split the files any further for model training. If the object sizes are skewed, training won't be optimal as the data distribution is also skewed when one host in a training cluster is overloaded, thus becoming a bottleneck in training.
FastFile mode
If an algorithm supports
FastFile
mode, SageMaker streams data directly from S3 to the container with no code changes, and provides file system access to the data. Users can author their training script to interact with these files as if they were stored on disk.FastFile
mode works best when the data is read sequentially. Augmented manifest files aren't supported. The startup time is lower when there are fewer files in the S3 bucket provided.
AlgorithmStatusDetails
Description
Specifies the validation and image scan statuses of the algorithm.
Members
- ImageScanStatuses
-
- Type: Array of AlgorithmStatusItem structures
The status of the scan of the algorithm's Docker image container.
- ValidationStatuses
-
- Type: Array of AlgorithmStatusItem structures
The status of algorithm validation.
AlgorithmStatusItem
Description
Represents the overall status of an algorithm.
Members
- FailureReason
-
- Type: string
if the overall status is
Failed
, the reason for the failure. - Name
-
- Required: Yes
- Type: string
The name of the algorithm for which the overall status is being reported.
- Status
-
- Required: Yes
- Type: string
The current status.
AlgorithmSummary
Description
Provides summary information about an algorithm.
Members
- AlgorithmArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the algorithm.
- AlgorithmDescription
-
- Type: string
A brief description of the algorithm.
- AlgorithmName
-
- Required: Yes
- Type: string
The name of the algorithm that is described by the summary.
- AlgorithmStatus
-
- Required: Yes
- Type: string
The overall status of the algorithm.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the algorithm was created.
AlgorithmValidationProfile
Description
Defines a training job and a batch transform job that SageMaker runs to validate your algorithm.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
Members
- ProfileName
-
- Required: Yes
- Type: string
The name of the profile for the algorithm. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
- TrainingJobDefinition
-
- Required: Yes
- Type: TrainingJobDefinition structure
The
TrainingJobDefinition
object that describes the training job that SageMaker runs to validate your algorithm. - TransformJobDefinition
-
- Type: TransformJobDefinition structure
The
TransformJobDefinition
object that describes the transform job that SageMaker runs to validate your algorithm.
AlgorithmValidationSpecification
Description
Specifies configurations for one or more training jobs that SageMaker runs to test the algorithm.
Members
- ValidationProfiles
-
- Required: Yes
- Type: Array of AlgorithmValidationProfile structures
An array of
AlgorithmValidationProfile
objects, each of which specifies a training job and batch transform job that SageMaker runs to validate your algorithm. - ValidationRole
-
- Required: Yes
- Type: string
The IAM roles that SageMaker uses to run the training jobs.
AmazonQSettings
Description
A collection of settings that configure the Amazon Q experience within the domain.
Members
- QProfileArn
-
- Type: string
The ARN of the Amazon Q profile used within the domain.
- Status
-
- Type: string
Whether Amazon Q has been enabled within the domain.
AnnotationConsolidationConfig
Description
Configures how labels are consolidated across human workers and processes output data.
Members
- AnnotationConsolidationLambdaArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.
This parameter is required for all labeling jobs. For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for
AnnotationConsolidationLambdaArn
. For custom labeling workflows, see Post-annotation Lambda.Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Semantic Segmentation Adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation
Semantic Segmentation Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation
Bounding Box Adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox
Bounding Box Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking
3D Point Cloud Object Detection Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection
3D Point Cloud Object Tracking Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation Adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool.
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation
AppDetails
Description
Details about an Amazon SageMaker app.
Members
- AppName
-
- Type: string
The name of the app.
- AppType
-
- Type: string
The type of app.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time.
- DomainId
-
- Type: string
The domain ID.
- ResourceSpec
-
- Type: ResourceSpec structure
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
- SpaceName
-
- Type: string
The name of the space.
- Status
-
- Type: string
The status.
- UserProfileName
-
- Type: string
The user profile name.
AppImageConfigDetails
Description
The configuration for running a SageMaker image as a KernelGateway app.
Members
- AppImageConfigArn
-
- Type: string
The ARN of the AppImageConfig.
- AppImageConfigName
-
- Type: string
The name of the AppImageConfig. Must be unique to your account.
- CodeEditorAppImageConfig
-
- Type: CodeEditorAppImageConfig structure
The configuration for the file system and the runtime, such as the environment variables and entry point.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the AppImageConfig was created.
- JupyterLabAppImageConfig
-
- Type: JupyterLabAppImageConfig structure
The configuration for the file system and the runtime, such as the environment variables and entry point.
- KernelGatewayImageConfig
-
- Type: KernelGatewayImageConfig structure
The configuration for the file system and kernels in the SageMaker image.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the AppImageConfig was last modified.
AppSpecification
Description
Configuration to run a processing job in a specified container image.
Members
- ContainerArguments
-
- Type: Array of strings
The arguments for a container used to run a processing job.
- ContainerEntrypoint
-
- Type: Array of strings
The entrypoint for a container used to run a processing job.
- ImageUri
-
- Required: Yes
- Type: string
The container image to be run by the processing job.
ArtifactSource
Description
A structure describing the source of an artifact.
Members
- SourceTypes
-
- Type: Array of ArtifactSourceType structures
A list of source types.
- SourceUri
-
- Required: Yes
- Type: string
The URI of the source.
ArtifactSourceType
Description
The ID and ID type of an artifact source.
Members
- SourceIdType
-
- Required: Yes
- Type: string
The type of ID.
- Value
-
- Required: Yes
- Type: string
The ID.
ArtifactSummary
Description
Lists a summary of the properties of an artifact. An artifact represents a URI addressable object or data. Some examples are a dataset and a model.
Members
- ArtifactArn
-
- Type: string
The Amazon Resource Name (ARN) of the artifact.
- ArtifactName
-
- Type: string
The name of the artifact.
- ArtifactType
-
- Type: string
The type of the artifact.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the artifact was created.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the artifact was last modified.
- Source
-
- Type: ArtifactSource structure
The source of the artifact.
AssociationSummary
Description
Lists a summary of the properties of an association. An association is an entity that links other lineage or experiment entities. An example would be an association between a training job and a model.
Members
- AssociationType
-
- Type: string
The type of the association.
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the association was created.
- DestinationArn
-
- Type: string
The Amazon Resource Name (ARN) of the destination.
- DestinationName
-
- Type: string
The name of the destination.
- DestinationType
-
- Type: string
The destination type.
- SourceArn
-
- Type: string
The ARN of the source.
- SourceName
-
- Type: string
The name of the source.
- SourceType
-
- Type: string
The source type.
AsyncInferenceClientConfig
Description
Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
Members
- MaxConcurrentInvocationsPerInstance
-
- Type: int
The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, SageMaker chooses an optimal value.
AsyncInferenceConfig
Description
Specifies configuration for how an endpoint performs asynchronous inference.
Members
- ClientConfig
-
- Type: AsyncInferenceClientConfig structure
Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
- OutputConfig
-
- Required: Yes
- Type: AsyncInferenceOutputConfig structure
Specifies the configuration for asynchronous inference invocation outputs.
AsyncInferenceNotificationConfig
Description
Specifies the configuration for notifications of inference results for asynchronous inference.
Members
- ErrorTopic
-
- Type: string
Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.
- IncludeInferenceResponseIn
-
- Type: Array of strings
The Amazon SNS topics where you want the inference response to be included.
The inference response is included only if the response size is less than or equal to 128 KB.
- SuccessTopic
-
- Type: string
Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.
AsyncInferenceOutputConfig
Description
Specifies the configuration for asynchronous inference invocation outputs.
Members
- KmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the asynchronous inference output in Amazon S3.
- NotificationConfig
-
- Type: AsyncInferenceNotificationConfig structure
Specifies the configuration for notifications of inference results for asynchronous inference.
- S3FailurePath
-
- Type: string
The Amazon S3 location to upload failure inference responses to.
- S3OutputPath
-
- Type: string
The Amazon S3 location to upload inference responses to.
AthenaDatasetDefinition
Description
Configuration for Athena Dataset Definition input.
Members
- Catalog
-
- Required: Yes
- Type: string
The name of the data catalog used in Athena query execution.
- Database
-
- Required: Yes
- Type: string
The name of the database used in the Athena query execution.
- KmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
- OutputCompression
-
- Type: string
The compression used for Athena query results.
- OutputFormat
-
- Required: Yes
- Type: string
The data storage format for Athena query results.
- OutputS3Uri
-
- Required: Yes
- Type: string
The location in Amazon S3 where Athena query results are stored.
- QueryString
-
- Required: Yes
- Type: string
The SQL query statements, to be executed.
- WorkGroup
-
- Type: string
The name of the workgroup in which the Athena query is being started.
AutoMLAlgorithmConfig
Description
The selection of algorithms trained on your dataset to generate the model candidates for an Autopilot job.
Members
- AutoMLAlgorithms
-
- Required: Yes
- Type: Array of strings
The selection of algorithms trained on your dataset to generate the model candidates for an Autopilot job.
-
For the tabular problem type
TabularJobConfig
:Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (
ENSEMBLING
orHYPERPARAMETER_TUNING
). Choose a minimum of 1 algorithm.-
In
ENSEMBLING
mode:-
"catboost"
-
"extra-trees"
-
"fastai"
-
"lightgbm"
-
"linear-learner"
-
"nn-torch"
-
"randomforest"
-
"xgboost"
-
-
In
HYPERPARAMETER_TUNING
mode:-
"linear-learner"
-
"mlp"
-
"xgboost"
-
-
-
For the time-series forecasting problem type
TimeSeriesForecastingJobConfig
:-
Choose your algorithms from this list.
-
"cnn-qr"
-
"deepar"
-
"prophet"
-
"arima"
-
"npts"
-
"ets"
-
-
AutoMLCandidate
Description
Information about a candidate produced by an AutoML training job, including its status, steps, and other properties.
Members
- CandidateName
-
- Required: Yes
- Type: string
The name of the candidate.
- CandidateProperties
-
- Type: CandidateProperties structure
The properties of an AutoML candidate job.
- CandidateStatus
-
- Required: Yes
- Type: string
The candidate's status.
- CandidateSteps
-
- Required: Yes
- Type: Array of AutoMLCandidateStep structures
Information about the candidate's steps.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time.
- EndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The end time.
- FailureReason
-
- Type: string
The failure reason.
- FinalAutoMLJobObjectiveMetric
-
- Type: FinalAutoMLJobObjectiveMetric structure
The best candidate result from an AutoML training job.
- InferenceContainerDefinitions
-
- Type: Associative array of custom strings keys (AutoMLProcessingUnit) to AutoMLContainerDefinition structuress
The mapping of all supported processing unit (CPU, GPU, etc...) to inference container definitions for the candidate. This field is populated for the AutoML jobs V2 (for example, for jobs created by calling
CreateAutoMLJobV2
) related to image or text classification problem types only. - InferenceContainers
-
- Type: Array of AutoMLContainerDefinition structures
Information about the recommended inference container definitions.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last modified time.
- ObjectiveStatus
-
- Required: Yes
- Type: string
The objective's status.
AutoMLCandidateGenerationConfig
Description
Stores the configuration information for how a candidate is generated (optional).
Members
- AlgorithmsConfig
-
- Type: Array of AutoMLAlgorithmConfig structures
Stores the configuration information for the selection of algorithms trained on tabular data.
The list of available algorithms to choose from depends on the training mode set in
TabularJobConfig.Mode
.-
AlgorithmsConfig
should not be set if the training mode is set onAUTO
. -
When
AlgorithmsConfig
is provided, oneAutoMLAlgorithms
attribute must be set and one only.If the list of algorithms provided as values for
AutoMLAlgorithms
is empty,CandidateGenerationConfig
uses the full set of algorithms for the given training mode. -
When
AlgorithmsConfig
is not provided,CandidateGenerationConfig
uses the full set of algorithms for the given training mode.
For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
- FeatureSpecificationS3Uri
-
- Type: string
A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input
FeatureAttributeNames
(optional) in JSON format as shown below:{ "FeatureAttributeNames":["col1", "col2", ...] }
.You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types:
numeric
,categorical
,text
, anddatetime
. In HPO mode, Autopilot can supportnumeric
,categorical
,text
,datetime
, andsequence
.If only
FeatureDataTypes
is provided, the column keys (col1
,col2
,..) should be a subset of the column names in the input data.If both
FeatureDataTypes
andFeatureAttributeNames
are provided, then the column keys should be a subset of the column names provided inFeatureAttributeNames
.The key name
FeatureAttributeNames
is fixed. The values listed in["col1", "col2", ...]
are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
AutoMLCandidateStep
Description
Information about the steps for a candidate and what step it is working on.
Members
- CandidateStepArn
-
- Required: Yes
- Type: string
The ARN for the candidate's step.
- CandidateStepName
-
- Required: Yes
- Type: string
The name for the candidate's step.
- CandidateStepType
-
- Required: Yes
- Type: string
Whether the candidate is at the transform, training, or processing step.
AutoMLChannel
Description
A channel is a named input source that training algorithms can consume. The validation dataset size is limited to less than 2 GB. The training dataset size must be less than 100 GB. For more information, see Channel.
A validation dataset must contain the same headers as the training dataset.
Members
- ChannelType
-
- Type: string
The channel type (optional) is an
enum
string. The default value istraining
. Channels for training and validation must share the sameContentType
andTargetAttributeName
. For information on specifying training and validation channel types, see How to specify training and validation datasets. - CompressionType
-
- Type: string
You can use
Gzip
orNone
. The default value isNone
. - ContentType
-
- Type: string
The content type of the data from the input source. You can use
text/csv;header=present
orx-application/vnd.amazon+parquet
. The default value istext/csv;header=present
. - DataSource
-
- Type: AutoMLDataSource structure
The data source for an AutoML channel.
- SampleWeightAttributeName
-
- Type: string
If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
- TargetAttributeName
-
- Required: Yes
- Type: string
The name of the target variable in supervised learning, usually represented by 'y'.
AutoMLComputeConfig
Description
This data type is intended for use exclusively by SageMaker Canvas and cannot be used in other contexts at the moment.
Specifies the compute configuration for an AutoML job V2.
Members
- EmrServerlessComputeConfig
-
- Type: EmrServerlessComputeConfig structure
The configuration for using EMR Serverless to run the AutoML job V2.
To allow your AutoML job V2 to automatically initiate a remote job on EMR Serverless when additional compute resources are needed to process large datasets, you need to provide an
EmrServerlessComputeConfig
object, which includes anExecutionRoleARN
attribute, to theAutoMLComputeConfig
of the AutoML job V2 input request.By seamlessly transitioning to EMR Serverless when required, the AutoML job can handle datasets that would otherwise exceed the initially provisioned resources, without any manual intervention from you.
EMR Serverless is available for the tabular and time series problem types. We recommend setting up this option for tabular datasets larger than 5 GB and time series datasets larger than 30 GB.
AutoMLContainerDefinition
Description
A list of container definitions that describe the different containers that make up an AutoML candidate. For more information, see ContainerDefinition.
Members
- Environment
-
- Type: Associative array of custom strings keys (EnvironmentKey) to strings
The environment variables to set in the container. For more information, see ContainerDefinition.
- Image
-
- Required: Yes
- Type: string
The Amazon Elastic Container Registry (Amazon ECR) path of the container. For more information, see ContainerDefinition.
- ModelDataUrl
-
- Required: Yes
- Type: string
The location of the model artifacts. For more information, see ContainerDefinition.
AutoMLDataSource
Description
The data source for the Autopilot job.
Members
- S3DataSource
-
- Required: Yes
- Type: AutoMLS3DataSource structure
The Amazon S3 location of the input data.
AutoMLDataSplitConfig
Description
This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob
, the validation dataset must be less than 2 GB in size.
Members
- ValidationFraction
-
- Type: float
The validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation. The default value is 0.2, and values must be greater than 0 and less than 1. We recommend setting this value to be less than 0.5.
AutoMLJobArtifacts
Description
The artifacts that are generated during an AutoML job.
Members
- CandidateDefinitionNotebookLocation
-
- Type: string
The URL of the notebook location.
- DataExplorationNotebookLocation
-
- Type: string
The URL of the notebook location.
AutoMLJobChannel
Description
A channel is a named input source that training algorithms can consume. This channel is used for AutoML jobs V2 (jobs created by calling CreateAutoMLJobV2).
Members
- ChannelType
-
- Type: string
The type of channel. Defines whether the data are used for training or validation. The default value is
training
. Channels fortraining
andvalidation
must share the sameContentType
The type of channel defaults to
training
for the time-series forecasting problem type. - CompressionType
-
- Type: string
The allowed compression types depend on the input format and problem type. We allow the compression type
Gzip
forS3Prefix
inputs on tabular data only. For all other inputs, the compression type should beNone
. If no compression type is provided, we default toNone
. - ContentType
-
- Type: string
The content type of the data from the input source. The following are the allowed content types for different problems:
-
For tabular problem types:
text/csv;header=present
orx-application/vnd.amazon+parquet
. The default value istext/csv;header=present
. -
For image classification:
image/png
,image/jpeg
, orimage/*
. The default value isimage/*
. -
For text classification:
text/csv;header=present
orx-application/vnd.amazon+parquet
. The default value istext/csv;header=present
. -
For time-series forecasting:
text/csv;header=present
orx-application/vnd.amazon+parquet
. The default value istext/csv;header=present
. -
For text generation (LLMs fine-tuning):
text/csv;header=present
orx-application/vnd.amazon+parquet
. The default value istext/csv;header=present
.
- DataSource
-
- Type: AutoMLDataSource structure
The data source for an AutoML channel (Required).
AutoMLJobCompletionCriteria
Description
How long a job is allowed to run, or how many candidates a job is allowed to generate.
Members
- MaxAutoMLJobRuntimeInSeconds
-
- Type: int
The maximum runtime, in seconds, an AutoML job has to complete.
If an AutoML job exceeds the maximum runtime, the job is stopped automatically and its processing is ended gracefully. The AutoML job identifies the best model whose training was completed and marks it as the best-performing model. Any unfinished steps of the job, such as automatic one-click Autopilot model deployment, are not completed.
- MaxCandidates
-
- Type: int
The maximum number of times a training job is allowed to run.
For text and image classification, time-series forecasting, as well as text generation (LLMs fine-tuning) problem types, the supported value is 1. For tabular problem types, the maximum value is 750.
- MaxRuntimePerTrainingJobInSeconds
-
- Type: int
The maximum time, in seconds, that each training job executed inside hyperparameter tuning is allowed to run as part of a hyperparameter tuning job. For more information, see the StoppingCondition used by the CreateHyperParameterTuningJob action.
For job V2s (jobs created by calling
CreateAutoMLJobV2
), this field controls the runtime of the job candidate.For TextGenerationJobConfig problem types, the maximum time defaults to 72 hours (259200 seconds).
AutoMLJobConfig
Description
A collection of settings used for an AutoML job.
Members
- CandidateGenerationConfig
-
- Type: AutoMLCandidateGenerationConfig structure
The configuration for generating a candidate for an AutoML job (optional).
- CompletionCriteria
-
- Type: AutoMLJobCompletionCriteria structure
How long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.
- DataSplitConfig
-
- Type: AutoMLDataSplitConfig structure
The configuration for splitting the input training dataset.
Type: AutoMLDataSplitConfig
- Mode
-
- Type: string
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting
AUTO
. InAUTO
mode, Autopilot choosesENSEMBLING
for datasets smaller than 100 MB, andHYPERPARAMETER_TUNING
for larger ones.The
ENSEMBLING
mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported byENSEMBLING
mode.The
HYPERPARAMETER_TUNING
(HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported byHYPERPARAMETER_TUNING
mode. - SecurityConfig
-
- Type: AutoMLSecurityConfig structure
The security configuration for traffic encryption or Amazon VPC settings.
AutoMLJobObjective
Description
Specifies a metric to minimize or maximize as the objective of an AutoML job.
Members
- MetricName
-
- Required: Yes
- Type: string
The name of the objective metric used to measure the predictive quality of a machine learning system. During training, the model's parameters are updated iteratively to optimize its performance based on the feedback provided by the objective metric when evaluating the model on the validation dataset.
The list of available metrics supported by Autopilot and the default metric applied when you do not specify a metric name explicitly depend on the problem type.
-
For tabular problem types:
-
List of available metrics:
-
Regression:
MAE
,MSE
,R2
,RMSE
-
Binary classification:
Accuracy
,AUC
,BalancedAccuracy
,F1
,Precision
,Recall
-
Multiclass classification:
Accuracy
,BalancedAccuracy
,F1macro
,PrecisionMacro
,RecallMacro
For a description of each metric, see Autopilot metrics for classification and regression.
-
-
Default objective metrics:
-
Regression:
MSE
. -
Binary classification:
F1
. -
Multiclass classification:
Accuracy
.
-
-
-
For image or text classification problem types:
-
List of available metrics:
Accuracy
For a description of each metric, see Autopilot metrics for text and image classification.
-
Default objective metrics:
Accuracy
-
-
For time-series forecasting problem types:
-
List of available metrics:
RMSE
,wQL
,Average wQL
,MASE
,MAPE
,WAPE
For a description of each metric, see Autopilot metrics for time-series forecasting.
-
Default objective metrics:
AverageWeightedQuantileLoss
-
-
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the
AutoMLJobObjective
field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
AutoMLJobStepMetadata
Description
Metadata for an AutoML job step.
Members
- Arn
-
- Type: string
The Amazon Resource Name (ARN) of the AutoML job.
AutoMLJobSummary
Description
Provides a summary about an AutoML job.
Members
- AutoMLJobArn
-
- Required: Yes
- Type: string
The ARN of the AutoML job.
- AutoMLJobName
-
- Required: Yes
- Type: string
The name of the AutoML job you are requesting.
- AutoMLJobSecondaryStatus
-
- Required: Yes
- Type: string
The secondary status of the AutoML job.
- AutoMLJobStatus
-
- Required: Yes
- Type: string
The status of the AutoML job.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the AutoML job was created.
- EndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The end time of an AutoML job.
- FailureReason
-
- Type: string
The failure reason of an AutoML job.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the AutoML job was last modified.
- PartialFailureReasons
-
- Type: Array of AutoMLPartialFailureReason structures
The list of reasons for partial failures within an AutoML job.
AutoMLOutputDataConfig
Description
The output data configuration.
Members
- KmsKeyId
-
- Type: string
The Key Management Service encryption key ID.
- S3OutputPath
-
- Required: Yes
- Type: string
The Amazon S3 output path. Must be 512 characters or less.
AutoMLPartialFailureReason
Description
The reason for a partial failure of an AutoML job.
Members
- PartialFailureMessage
-
- Type: string
The message containing the reason for a partial failure of an AutoML job.
AutoMLProblemTypeConfig
Description
A collection of settings specific to the problem type used to configure an AutoML job V2. There must be one and only one config of the following type.
Members
- ImageClassificationJobConfig
-
- Type: ImageClassificationJobConfig structure
Settings used to configure an AutoML job V2 for the image classification problem type.
- TabularJobConfig
-
- Type: TabularJobConfig structure
Settings used to configure an AutoML job V2 for the tabular problem type (regression, classification).
- TextClassificationJobConfig
-
- Type: TextClassificationJobConfig structure
Settings used to configure an AutoML job V2 for the text classification problem type.
- TextGenerationJobConfig
-
- Type: TextGenerationJobConfig structure
Settings used to configure an AutoML job V2 for the text generation (LLMs fine-tuning) problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
- TimeSeriesForecastingJobConfig
-
- Type: TimeSeriesForecastingJobConfig structure
Settings used to configure an AutoML job V2 for the time-series forecasting problem type.
AutoMLProblemTypeResolvedAttributes
Description
Stores resolved attributes specific to the problem type of an AutoML job V2.
Members
- TabularResolvedAttributes
-
- Type: TabularResolvedAttributes structure
The resolved attributes for the tabular problem type.
- TextGenerationResolvedAttributes
-
- Type: TextGenerationResolvedAttributes structure
The resolved attributes for the text generation problem type.
AutoMLResolvedAttributes
Description
The resolved attributes used to configure an AutoML job V2.
Members
- AutoMLJobObjective
-
- Type: AutoMLJobObjective structure
Specifies a metric to minimize or maximize as the objective of an AutoML job.
- AutoMLProblemTypeResolvedAttributes
-
- Type: AutoMLProblemTypeResolvedAttributes structure
Defines the resolved attributes specific to a problem type.
- CompletionCriteria
-
- Type: AutoMLJobCompletionCriteria structure
How long a job is allowed to run, or how many candidates a job is allowed to generate.
AutoMLS3DataSource
Description
Describes the Amazon S3 data source.
Members
- S3DataType
-
- Required: Yes
- Type: string
The data type.
-
If you choose
S3Prefix
,S3Uri
identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.The
S3Prefix
should have the following format:s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILE
-
If you choose
ManifestFile
,S3Uri
identifies an object that is a manifest file containing a list of object keys that you want SageMaker to use for model training.A
ManifestFile
should have the format shown below:[ {"prefix": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/"},
"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1",
"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2",
... "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N" ]
-
If you choose
AugmentedManifestFile
,S3Uri
identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training.AugmentedManifestFile
is available for V2 API jobs only (for example, for jobs created by callingCreateAutoMLJobV2
).Here is a minimal, single-record example of an
AugmentedManifestFile
:{"source-ref": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/cats/cat.jpg",
"label-metadata": {"class-name": "cat"
}For more information on
AugmentedManifestFile
, see Provide Dataset Metadata to Training Jobs with an Augmented Manifest File.
- S3Uri
-
- Required: Yes
- Type: string
The URL to the Amazon S3 data source. The Uri refers to the Amazon S3 prefix or ManifestFile depending on the data type.
AutoMLSecurityConfig
Description
Security options.
Members
- EnableInterContainerTrafficEncryption
-
- Type: boolean
Whether to use traffic encryption between the container layers.
- VolumeKmsKeyId
-
- Type: string
The key used to encrypt stored data.
- VpcConfig
-
- Type: VpcConfig structure
The VPC configuration.
AutoParameter
Description
The name and an example value of the hyperparameter that you want to use in Autotune. If Automatic model tuning (AMT) determines that your hyperparameter is eligible for Autotune, an optimal hyperparameter range is selected for you.
Members
- Name
-
- Required: Yes
- Type: string
The name of the hyperparameter to optimize using Autotune.
- ValueHint
-
- Required: Yes
- Type: string
An example value of the hyperparameter to optimize using Autotune.
AutoRollbackConfig
Description
Automatic rollback configuration for handling endpoint deployment failures and recovery.
Members
- Alarms
-
- Type: Array of Alarm structures
List of CloudWatch alarms in your account that are configured to monitor metrics on an endpoint. If any alarms are tripped during a deployment, SageMaker rolls back the deployment.
Autotune
Description
A flag to indicate if you want to use Autotune to automatically find optimal values for the following fields:
-
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
-
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
-
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
-
RetryStrategy: The number of times to retry a training job.
-
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
-
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
Members
- Mode
-
- Required: Yes
- Type: string
Set
Mode
toEnabled
if you want to use Autotune.
BatchDataCaptureConfig
Description
Configuration to control how SageMaker captures inference data for batch transform jobs.
Members
- DestinationS3Uri
-
- Required: Yes
- Type: string
The Amazon S3 location being used to capture the data.
- GenerateInferenceId
-
- Type: boolean
Flag that indicates whether to append inference id to the output.
- KmsKeyId
-
- Type: string
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the batch transform job.
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
BatchDescribeModelPackageError
Description
The error code and error description associated with the resource.
Members
- ErrorCode
-
- Required: Yes
- Type: string
- ErrorResponse
-
- Required: Yes
- Type: string
BatchDescribeModelPackageSummary
Description
Provides summary information about the model package.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time of the mortgage package summary.
- InferenceSpecification
-
- Required: Yes
- Type: InferenceSpecification structure
Defines how to perform inference generation after a training job is run.
- ModelApprovalStatus
-
- Type: string
The approval status of the model.
- ModelPackageArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model package.
- ModelPackageDescription
-
- Type: string
The description of the model package.
- ModelPackageGroupName
-
- Required: Yes
- Type: string
The group name for the model package
- ModelPackageStatus
-
- Required: Yes
- Type: string
The status of the mortgage package.
- ModelPackageVersion
-
- Type: int
The version number of a versioned model.
BatchTransformInput
Description
Input object for the batch transform job.
Members
- DataCapturedDestinationS3Uri
-
- Required: Yes
- Type: string
The Amazon S3 location being used to capture the data.
- DatasetFormat
-
- Required: Yes
- Type: MonitoringDatasetFormat structure
The dataset format for your batch transform job.
- EndTimeOffset
-
- Type: string
If specified, monitoring jobs subtract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
- ExcludeFeaturesAttribute
-
- Type: string
The attributes of the input data to exclude from the analysis.
- FeaturesAttribute
-
- Type: string
The attributes of the input data that are the input features.
- InferenceAttribute
-
- Type: string
The attribute of the input data that represents the ground truth label.
- LocalPath
-
- Required: Yes
- Type: string
Path to the filesystem where the batch transform data is available to the container.
- ProbabilityAttribute
-
- Type: string
In a classification problem, the attribute that represents the class probability.
- ProbabilityThresholdAttribute
-
- Type: double
The threshold for the class probability to be evaluated as a positive result.
- S3DataDistributionType
-
- Type: string
Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to
FullyReplicated
- S3InputMode
-
- Type: string
Whether the
Pipe
orFile
is used as the input mode for transferring data for the monitoring job.Pipe
mode is recommended for large datasets.File
mode is useful for small files that fit in memory. Defaults toFile
. - StartTimeOffset
-
- Type: string
If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
BestObjectiveNotImproving
Description
A structure that keeps track of which training jobs launched by your hyperparameter tuning job are not improving model performance as evaluated against an objective function.
Members
- MaxNumberOfTrainingJobsNotImproving
-
- Type: int
The number of training jobs that have failed to improve model performance by 1% or greater over prior training jobs as evaluated against an objective function.
Bias
Description
Contains bias metrics for a model.
Members
- PostTrainingReport
-
- Type: MetricsSource structure
The post-training bias report for a model.
- PreTrainingReport
-
- Type: MetricsSource structure
The pre-training bias report for a model.
- Report
-
- Type: MetricsSource structure
The bias report for a model
BlueGreenUpdatePolicy
Description
Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
Members
- MaximumExecutionTimeoutInSeconds
-
- Type: int
Maximum execution timeout for the deployment. Note that the timeout value should be larger than the total waiting time specified in
TerminationWaitInSeconds
andWaitIntervalInSeconds
. - TerminationWaitInSeconds
-
- Type: int
Additional waiting time in seconds after the completion of an endpoint deployment before terminating the old endpoint fleet. Default is 0.
- TrafficRoutingConfiguration
-
- Required: Yes
- Type: TrafficRoutingConfig structure
Defines the traffic routing strategy to shift traffic from the old fleet to the new fleet during an endpoint deployment.
CacheHitResult
Description
Details on the cache hit of a pipeline execution step.
Members
- SourcePipelineExecutionArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
CallbackStepMetadata
Description
Metadata about a callback step.
Members
- CallbackToken
-
- Type: string
The pipeline generated token from the Amazon SQS queue.
- OutputParameters
-
- Type: Array of OutputParameter structures
A list of the output parameters of the callback step.
- SqsQueueUrl
-
- Type: string
The URL of the Amazon Simple Queue Service (Amazon SQS) queue used by the callback step.
CandidateArtifactLocations
Description
The location of artifacts for an AutoML candidate job.
Members
- BacktestResults
-
- Type: string
The Amazon S3 prefix to the accuracy metrics and the inference results observed over the testing window. Available only for the time-series forecasting problem type.
- Explainability
-
- Required: Yes
- Type: string
The Amazon S3 prefix to the explainability artifacts generated for the AutoML candidate.
- ModelInsights
-
- Type: string
The Amazon S3 prefix to the model insight artifacts generated for the AutoML candidate.
CandidateGenerationConfig
Description
Stores the configuration information for how model candidates are generated using an AutoML job V2.
Members
- AlgorithmsConfig
-
- Type: Array of AutoMLAlgorithmConfig structures
Your Autopilot job trains a default set of algorithms on your dataset. For tabular and time-series data, you can customize the algorithm list by selecting a subset of algorithms for your problem type.
AlgorithmsConfig
stores the customized selection of algorithms to train on your data.-
For the tabular problem type
TabularJobConfig
, the list of available algorithms to choose from depends on the training mode set inAutoMLJobConfig.Mode
.-
AlgorithmsConfig
should not be set when the training modeAutoMLJobConfig.Mode
is set toAUTO
. -
When
AlgorithmsConfig
is provided, oneAutoMLAlgorithms
attribute must be set and one only.If the list of algorithms provided as values for
AutoMLAlgorithms
is empty,CandidateGenerationConfig
uses the full set of algorithms for the given training mode. -
When
AlgorithmsConfig
is not provided,CandidateGenerationConfig
uses the full set of algorithms for the given training mode.
For the list of all algorithms per training mode, see AlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in the Autopilot developer guide.
-
-
For the time-series forecasting problem type
TimeSeriesForecastingJobConfig
, choose your algorithms from the list provided in AlgorithmConfig.For more information on each algorithm, see the Algorithms support for time-series forecasting section in the Autopilot developer guide.
-
When
AlgorithmsConfig
is provided, oneAutoMLAlgorithms
attribute must be set and one only.If the list of algorithms provided as values for
AutoMLAlgorithms
is empty,CandidateGenerationConfig
uses the full set of algorithms for time-series forecasting. -
When
AlgorithmsConfig
is not provided,CandidateGenerationConfig
uses the full set of algorithms for time-series forecasting.
-
CandidateProperties
Description
The properties of an AutoML candidate job.
Members
- CandidateArtifactLocations
-
- Type: CandidateArtifactLocations structure
The Amazon S3 prefix to the artifacts generated for an AutoML candidate.
- CandidateMetrics
-
- Type: Array of MetricDatum structures
Information about the candidate metrics for an AutoML job.
CanvasAppSettings
Description
The SageMaker Canvas application settings.
Members
- DirectDeploySettings
-
- Type: DirectDeploySettings structure
The model deployment settings for the SageMaker Canvas application.
- EmrServerlessSettings
-
- Type: EmrServerlessSettings structure
The settings for running Amazon EMR Serverless data processing jobs in SageMaker Canvas.
- GenerativeAiSettings
-
- Type: GenerativeAiSettings structure
The generative AI settings for the SageMaker Canvas application.
- IdentityProviderOAuthSettings
-
- Type: Array of IdentityProviderOAuthSetting structures
The settings for connecting to an external data source with OAuth.
- KendraSettings
-
- Type: KendraSettings structure
The settings for document querying.
- ModelRegisterSettings
-
- Type: ModelRegisterSettings structure
The model registry settings for the SageMaker Canvas application.
- TimeSeriesForecastingSettings
-
- Type: TimeSeriesForecastingSettings structure
Time series forecast settings for the SageMaker Canvas application.
- WorkspaceSettings
-
- Type: WorkspaceSettings structure
The workspace settings for the SageMaker Canvas application.
CapacitySize
Description
Specifies the type and size of the endpoint capacity to activate for a blue/green deployment, a rolling deployment, or a rollback strategy. You can specify your batches as either instance count or the overall percentage or your fleet.
For a rollback strategy, if you don't specify the fields in this object, or if you set the Value
to 100%, then SageMaker uses a blue/green rollback strategy and rolls all traffic back to the blue fleet.
Members
- Type
-
- Required: Yes
- Type: string
Specifies the endpoint capacity type.
-
INSTANCE_COUNT
: The endpoint activates based on the number of instances. -
CAPACITY_PERCENT
: The endpoint activates based on the specified percentage of capacity.
- Value
-
- Required: Yes
- Type: int
Defines the capacity size, either as a number of instances or a capacity percentage.
CaptureContentTypeHeader
Description
Configuration specifying how to treat different headers. If no headers are specified Amazon SageMaker will by default base64 encode when capturing the data.
Members
- CsvContentTypes
-
- Type: Array of strings
The list of all content type headers that Amazon SageMaker will treat as CSV and capture accordingly.
- JsonContentTypes
-
- Type: Array of strings
The list of all content type headers that SageMaker will treat as JSON and capture accordingly.
CaptureOption
Description
Specifies data Model Monitor will capture.
Members
- CaptureMode
-
- Required: Yes
- Type: string
Specify the boundary of data to capture.
CategoricalParameter
Description
Environment parameters you want to benchmark your load test against.
Members
- Name
-
- Required: Yes
- Type: string
The Name of the environment variable.
- Value
-
- Required: Yes
- Type: Array of strings
The list of values you can pass.
CategoricalParameterRange
Description
A list of categorical hyperparameters to tune.
Members
- Name
-
- Required: Yes
- Type: string
The name of the categorical hyperparameter to tune.
- Values
-
- Required: Yes
- Type: Array of strings
A list of the categories for the hyperparameter.
CategoricalParameterRangeSpecification
Description
Defines the possible values for a categorical hyperparameter.
Members
- Values
-
- Required: Yes
- Type: Array of strings
The allowed categories for the hyperparameter.
Channel
Description
A channel is a named input source that training algorithms can consume.
Members
- ChannelName
-
- Required: Yes
- Type: string
The name of the channel.
- CompressionType
-
- Type: string
If training data is compressed, the compression type. The default value is
None
.CompressionType
is used only in Pipe input mode. In File mode, leave this field unset or set it to None. - ContentType
-
- Type: string
The MIME type of the data.
- DataSource
-
- Required: Yes
- Type: DataSource structure
The location of the channel data.
- InputMode
-
- Type: string
(Optional) The input mode to use for the data channel in a training job. If you don't set a value for
InputMode
, SageMaker uses the value set forTrainingInputMode
. Use this parameter to override theTrainingInputMode
setting in a AlgorithmSpecification request when you have a channel that needs a different input mode from the training job's general setting. To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, useFile
input mode. To stream data directly from Amazon S3 to the container, choosePipe
input mode.To use a model for incremental training, choose
File
input model. - RecordWrapperType
-
- Type: string
Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don't need to set this attribute. For more information, see Create a Dataset Using RecordIO.
In File mode, leave this field unset or set it to None.
- ShuffleConfig
-
- Type: ShuffleConfig structure
A configuration for a shuffle option for input data in a channel. If you use
S3Prefix
forS3DataType
, this shuffles the results of the S3 key prefix matches. If you useManifestFile
, the order of the S3 object references in theManifestFile
is shuffled. If you useAugmentedManifestFile
, the order of the JSON lines in theAugmentedManifestFile
is shuffled. The shuffling order is determined using theSeed
value.For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with
S3DataDistributionType
ofShardedByS3Key
, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
ChannelSpecification
Description
Defines a named input source, called a channel, to be used by an algorithm.
Members
- Description
-
- Type: string
A brief description of the channel.
- IsRequired
-
- Type: boolean
Indicates whether the channel is required by the algorithm.
- Name
-
- Required: Yes
- Type: string
The name of the channel.
- SupportedCompressionTypes
-
- Type: Array of strings
The allowed compression types, if data compression is used.
- SupportedContentTypes
-
- Required: Yes
- Type: Array of strings
The supported MIME types for the data.
- SupportedInputModes
-
- Required: Yes
- Type: Array of strings
The allowed input mode, either FILE or PIPE.
In FILE mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode.
In PIPE mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
CheckpointConfig
Description
Contains information about the output location for managed spot training checkpoint data.
Members
- LocalPath
-
- Type: string
(Optional) The local directory where checkpoints are written. The default directory is
/opt/ml/checkpoints/
. - S3Uri
-
- Required: Yes
- Type: string
Identifies the S3 path where you want SageMaker to store checkpoints. For example,
s3://bucket-name/key-name-prefix
.
ClarifyCheckStepMetadata
Description
The container for the metadata for the ClarifyCheck step. For more information, see the topic on ClarifyCheck step in the Amazon SageMaker Developer Guide.
Members
- BaselineUsedForDriftCheckConstraints
-
- Type: string
The Amazon S3 URI of baseline constraints file to be used for the drift check.
- CalculatedBaselineConstraints
-
- Type: string
The Amazon S3 URI of the newly calculated baseline constraints file.
- CheckJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the check processing job that was run by this step's execution.
- CheckType
-
- Type: string
The type of the Clarify Check step
- ModelPackageGroupName
-
- Type: string
The model package group name.
- RegisterNewBaseline
-
- Type: boolean
This flag indicates if a newly calculated baseline can be accessed through step properties
BaselineUsedForDriftCheckConstraints
andBaselineUsedForDriftCheckStatistics
. If it is set toFalse
, the previous baseline of the configured check type must also be available. These can be accessed through theBaselineUsedForDriftCheckConstraints
property. - SkipCheck
-
- Type: boolean
This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to
False
, the previous baseline of the configured check type must be available. - ViolationReport
-
- Type: string
The Amazon S3 URI of the violation report if violations are detected.
ClarifyExplainerConfig
Description
The configuration parameters for the SageMaker Clarify explainer.
Members
- EnableExplanations
-
- Type: string
A JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See
EnableExplanations
for additional information. - InferenceConfig
-
- Type: ClarifyInferenceConfig structure
The inference configuration parameter for the model container.
- ShapConfig
-
- Required: Yes
- Type: ClarifyShapConfig structure
The configuration for SHAP analysis.
ClarifyInferenceConfig
Description
The inference configuration parameter for the model container.
Members
- ContentTemplate
-
- Type: string
A template string used to format a JSON record into an acceptable model container input. For example, a
ContentTemplate
string'{"myfeatures":$features}'
will format a list of features[1,2,3]
into the record string'{"myfeatures":[1,2,3]}'
. Required only when the model container input is in JSON Lines format. - FeatureHeaders
-
- Type: Array of strings
The names of the features. If provided, these are included in the endpoint response payload to help readability of the
InvokeEndpoint
output. See the Response section under Invoke the endpoint in the Developer Guide for more information. - FeatureTypes
-
- Type: Array of strings
A list of data types of the features (optional). Applicable only to NLP explainability. If provided,
FeatureTypes
must have at least one'text'
string (for example,['text']
). IfFeatureTypes
is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the response section under Invoke the endpoint in the Developer Guide for more information. - FeaturesAttribute
-
- Type: string
Provides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if
FeaturesAttribute
is the JMESPath expression'myfeatures'
, it extracts a list of features[1,2,3]
from request data'{"myfeatures":[1,2,3]}'
. - LabelAttribute
-
- Type: string
A JMESPath expression used to locate the list of label headers in the model container output.
Example: If the model container output of a batch request is
'{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}'
, then setLabelAttribute
to'labels'
to extract the list of label headers["cat","dog","fish"]
- LabelHeaders
-
- Type: Array of strings
For multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the
InvokeEndpoint
API. See the response section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter. - LabelIndex
-
- Type: int
A zero-based index used to extract a label header or list of label headers from model container output in CSV format.
Example for a multiclass model: If the model container output consists of label headers followed by probabilities:
'"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"'
, setLabelIndex
to0
to select the label headers['cat','dog','fish']
. - MaxPayloadInMB
-
- Type: int
The maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to
6
MB. - MaxRecordCount
-
- Type: int
The maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If
MaxRecordCount
is1
, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container's capacity at runtime. - ProbabilityAttribute
-
- Type: string
A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.
Example: If the model container output of a single request is
'{"predicted_label":1,"probability":0.6}'
, then setProbabilityAttribute
to'probability'
. - ProbabilityIndex
-
- Type: int
A zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.
Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability:
'1,0.6'
, setProbabilityIndex
to1
to select the probability value0.6
.Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability:
'"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"'
, setProbabilityIndex
to1
to select the probability values[0.1,0.6,0.3]
.
ClarifyShapBaselineConfig
Description
The configuration for the SHAP baseline (also called the background or reference dataset) of the Kernal SHAP algorithm.
-
The number of records in the baseline data determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
-
ShapBaseline
andShapBaselineUri
are mutually exclusive parameters. One or the either is required to configure a SHAP baseline.
Members
- MimeType
-
- Type: string
The MIME type of the baseline data. Choose from
'text/csv'
or'application/jsonlines'
. Defaults to'text/csv'
. - ShapBaseline
-
- Type: string
The inline SHAP baseline data in string format.
ShapBaseline
can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by theGranularity
of theTextConfig
parameter. The size limit forShapBasline
is 4 KB. Use theShapBaselineUri
parameter if you want to provide more than 4 KB of baseline data. - ShapBaselineUri
-
- Type: string
The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the
ShapBaselineUri
should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to Resources in your Amazon Virtual Private Cloud.
ClarifyShapConfig
Description
The configuration for SHAP analysis using SageMaker Clarify Explainer.
Members
- NumberOfSamples
-
- Type: int
The number of samples to be used for analysis by the Kernal SHAP algorithm.
The number of samples determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
- Seed
-
- Type: int
The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.
- ShapBaselineConfig
-
- Required: Yes
- Type: ClarifyShapBaselineConfig structure
The configuration for the SHAP baseline of the Kernal SHAP algorithm.
- TextConfig
-
- Type: ClarifyTextConfig structure
A parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.
- UseLogit
-
- Type: boolean
A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.
ClarifyTextConfig
Description
A parameter used to configure the SageMaker Clarify explainer to treat text features as text so that explanations are provided for individual units of text. Required only for natural language processing (NLP) explainability.
Members
- Granularity
-
- Required: Yes
- Type: string
The unit of granularity for the analysis of text features. For example, if the unit is
'token'
, then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature. - Language
-
- Required: Yes
- Type: string
ClusterEbsVolumeConfig
Description
Defines the configuration for attaching an additional Amazon Elastic Block Store (EBS) volume to each instance of the SageMaker HyperPod cluster instance group. To learn more, see SageMaker HyperPod release notes: June 20, 2024.
Members
- VolumeSizeInGB
-
- Required: Yes
- Type: int
The size in gigabytes (GB) of the additional EBS volume to be attached to the instances in the SageMaker HyperPod cluster instance group. The additional EBS volume is attached to each instance within the SageMaker HyperPod cluster instance group and mounted to
/opt/sagemaker
.
ClusterInstanceGroupDetails
Description
Details of an instance group in a SageMaker HyperPod cluster.
Members
- CurrentCount
-
- Type: int
The number of instances that are currently in the instance group of a SageMaker HyperPod cluster.
- ExecutionRole
-
- Type: string
The execution role for the instance group to assume.
- InstanceGroupName
-
- Type: string
The name of the instance group of a SageMaker HyperPod cluster.
- InstanceStorageConfigs
-
- Type: Array of ClusterInstanceStorageConfig structures
The additional storage configurations for the instances in the SageMaker HyperPod cluster instance group.
- InstanceType
-
- Type: string
The instance type of the instance group of a SageMaker HyperPod cluster.
- LifeCycleConfig
-
- Type: ClusterLifeCycleConfig structure
Details of LifeCycle configuration for the instance group.
- TargetCount
-
- Type: int
The number of instances you specified to add to the instance group of a SageMaker HyperPod cluster.
- ThreadsPerCore
-
- Type: int
The number you specified to
TreadsPerCore
inCreateCluster
for enabling or disabling multithreading. For instance types that support multithreading, you can specify 1 for disabling multithreading and 2 for enabling multithreading. For more information, see the reference table of CPU cores and threads per CPU core per instance type in the Amazon Elastic Compute Cloud User Guide.
ClusterInstanceGroupSpecification
Description
The specifications of an instance group that you need to define.
Members
- ExecutionRole
-
- Required: Yes
- Type: string
Specifies an IAM execution role to be assumed by the instance group.
- InstanceCount
-
- Required: Yes
- Type: int
Specifies the number of instances to add to the instance group of a SageMaker HyperPod cluster.
- InstanceGroupName
-
- Required: Yes
- Type: string
Specifies the name of the instance group.
- InstanceStorageConfigs
-
- Type: Array of ClusterInstanceStorageConfig structures
Specifies the additional storage configurations for the instances in the SageMaker HyperPod cluster instance group.
- InstanceType
-
- Required: Yes
- Type: string
Specifies the instance type of the instance group.
- LifeCycleConfig
-
- Required: Yes
- Type: ClusterLifeCycleConfig structure
Specifies the LifeCycle configuration for the instance group.
- ThreadsPerCore
-
- Type: int
Specifies the value for Threads per core. For instance types that support multithreading, you can specify
1
for disabling multithreading and2
for enabling multithreading. For instance types that doesn't support multithreading, specify1
. For more information, see the reference table of CPU cores and threads per CPU core per instance type in the Amazon Elastic Compute Cloud User Guide.
ClusterInstancePlacement
Description
Specifies the placement details for the node in the SageMaker HyperPod cluster, including the Availability Zone and the unique identifier (ID) of the Availability Zone.
Members
- AvailabilityZone
-
- Type: string
The Availability Zone where the node in the SageMaker HyperPod cluster is launched.
- AvailabilityZoneId
-
- Type: string
The unique identifier (ID) of the Availability Zone where the node in the SageMaker HyperPod cluster is launched.
ClusterInstanceStatusDetails
Description
Details of an instance in a SageMaker HyperPod cluster.
Members
- Message
-
- Type: string
The message from an instance in a SageMaker HyperPod cluster.
- Status
-
- Required: Yes
- Type: string
The status of an instance in a SageMaker HyperPod cluster.
ClusterInstanceStorageConfig
Description
Defines the configuration for attaching additional storage to the instances in the SageMaker HyperPod cluster instance group. To learn more, see SageMaker HyperPod release notes: June 20, 2024.
Members
- EbsVolumeConfig
-
- Type: ClusterEbsVolumeConfig structure
Defines the configuration for attaching additional Amazon Elastic Block Store (EBS) volumes to the instances in the SageMaker HyperPod cluster instance group. The additional EBS volume is attached to each instance within the SageMaker HyperPod cluster instance group and mounted to
/opt/sagemaker
.
ClusterLifeCycleConfig
Description
The lifecycle configuration for a SageMaker HyperPod cluster.
Members
- OnCreate
-
- Required: Yes
- Type: string
The file name of the entrypoint script of lifecycle scripts under
SourceS3Uri
. This entrypoint script runs during cluster creation. - SourceS3Uri
-
- Required: Yes
- Type: string
An Amazon S3 bucket path where your lifecycle scripts are stored.
Make sure that the S3 bucket path starts with
s3://sagemaker-
. The IAM role for SageMaker HyperPod has the managedAmazonSageMakerClusterInstanceRolePolicy
attached, which allows access to S3 buckets with the specific prefixsagemaker-
.
ClusterNodeDetails
Description
Details of an instance (also called a node interchangeably) in a SageMaker HyperPod cluster.
Members
- InstanceGroupName
-
- Type: string
The instance group name in which the instance is.
- InstanceId
-
- Type: string
The ID of the instance.
- InstanceStatus
-
- Type: ClusterInstanceStatusDetails structure
The status of the instance.
- InstanceStorageConfigs
-
- Type: Array of ClusterInstanceStorageConfig structures
The configurations of additional storage specified to the instance group where the instance (node) is launched.
- InstanceType
-
- Type: string
The type of the instance.
- LaunchTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the instance is launched.
- LifeCycleConfig
-
- Type: ClusterLifeCycleConfig structure
The LifeCycle configuration applied to the instance.
- Placement
-
- Type: ClusterInstancePlacement structure
The placement details of the SageMaker HyperPod cluster node.
- PrivateDnsHostname
-
- Type: string
The private DNS hostname of the SageMaker HyperPod cluster node.
- PrivatePrimaryIp
-
- Type: string
The private primary IP address of the SageMaker HyperPod cluster node.
- ThreadsPerCore
-
- Type: int
The number of threads per CPU core you specified under
CreateCluster
.
ClusterNodeSummary
Description
Lists a summary of the properties of an instance (also called a node interchangeably) of a SageMaker HyperPod cluster.
Members
- InstanceGroupName
-
- Required: Yes
- Type: string
The name of the instance group in which the instance is.
- InstanceId
-
- Required: Yes
- Type: string
The ID of the instance.
- InstanceStatus
-
- Required: Yes
- Type: ClusterInstanceStatusDetails structure
The status of the instance.
- InstanceType
-
- Required: Yes
- Type: string
The type of the instance.
- LaunchTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the instance is launched.
ClusterSummary
Description
Lists a summary of the properties of a SageMaker HyperPod cluster.
Members
- ClusterArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.
- ClusterName
-
- Required: Yes
- Type: string
The name of the SageMaker HyperPod cluster.
- ClusterStatus
-
- Required: Yes
- Type: string
The status of the SageMaker HyperPod cluster.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the SageMaker HyperPod cluster is created.
CodeEditorAppImageConfig
Description
The configuration for the file system and kernels in a SageMaker image running as a Code Editor app. The FileSystemConfig
object is not supported.
Members
- ContainerConfig
-
- Type: ContainerConfig structure
The configuration used to run the application image container.
- FileSystemConfig
-
- Type: FileSystemConfig structure
The Amazon Elastic File System storage configuration for a SageMaker image.
CodeEditorAppSettings
Description
The Code Editor application settings.
For more information about Code Editor, see Get started with Code Editor in Amazon SageMaker.
Members
- CustomImages
-
- Type: Array of CustomImage structures
A list of custom SageMaker images that are configured to run as a Code Editor app.
- DefaultResourceSpec
-
- Type: ResourceSpec structure
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
- LifecycleConfigArns
-
- Type: Array of strings
The Amazon Resource Name (ARN) of the Code Editor application lifecycle configuration.
CodeRepository
Description
A Git repository that SageMaker automatically displays to users for cloning in the JupyterServer application.
Members
- RepositoryUrl
-
- Required: Yes
- Type: string
The URL of the Git repository.
CodeRepositorySummary
Description
Specifies summary information about a Git repository.
Members
- CodeRepositoryArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the Git repository.
- CodeRepositoryName
-
- Required: Yes
- Type: string
The name of the Git repository.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the Git repository was created.
- GitConfig
-
- Type: GitConfig structure
Configuration details for the Git repository, including the URL where it is located and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the Git repository was last modified.
CognitoConfig
Description
Use this parameter to configure your Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
Members
- ClientId
-
- Required: Yes
- Type: string
The client ID for your Amazon Cognito user pool.
- UserPool
-
- Required: Yes
- Type: string
A user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.
CognitoMemberDefinition
Description
Identifies a Amazon Cognito user group. A user group can be used in on or more work teams.
Members
- ClientId
-
- Required: Yes
- Type: string
An identifier for an application client. You must create the app client ID using Amazon Cognito.
- UserGroup
-
- Required: Yes
- Type: string
An identifier for a user group.
- UserPool
-
- Required: Yes
- Type: string
An identifier for a user pool. The user pool must be in the same region as the service that you are calling.
CollectionConfig
Description
Configuration for your collection.
Members
- VectorConfig
-
- Type: VectorConfig structure
Configuration for your vector collection type.
-
Dimension
: The number of elements in your vector.
CollectionConfiguration
Description
Configuration information for the Amazon SageMaker Debugger output tensor collections.
Members
- CollectionName
-
- Type: string
The name of the tensor collection. The name must be unique relative to other rule configuration names.
- CollectionParameters
-
- Type: Associative array of custom strings keys (ConfigKey) to strings
Parameter values for the tensor collection. The allowed parameters are
"name"
,"include_regex"
,"reduction_config"
,"save_config"
,"tensor_names"
, and"save_histogram"
.
CompilationJobSummary
Description
A summary of a model compilation job.
Members
- CompilationEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the model compilation job completed.
- CompilationJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model compilation job.
- CompilationJobName
-
- Required: Yes
- Type: string
The name of the model compilation job that you want a summary for.
- CompilationJobStatus
-
- Required: Yes
- Type: string
The status of the model compilation job.
- CompilationStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the model compilation job started.
- CompilationTargetDevice
-
- Type: string
The type of device that the model will run on after the compilation job has completed.
- CompilationTargetPlatformAccelerator
-
- Type: string
The type of accelerator that the model will run on after the compilation job has completed.
- CompilationTargetPlatformArch
-
- Type: string
The type of architecture that the model will run on after the compilation job has completed.
- CompilationTargetPlatformOs
-
- Type: string
The type of OS that the model will run on after the compilation job has completed.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the model compilation job was created.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the model compilation job was last modified.
ConditionStepMetadata
Description
Metadata for a Condition step.
Members
- Outcome
-
- Type: string
The outcome of the Condition step evaluation.
ConflictException
Description
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment
or Artifact
.
Members
- Message
-
- Type: string
ContainerConfig
Description
The configuration used to run the application image container.
Members
- ContainerArguments
-
- Type: Array of strings
The arguments for the container when you're running the application.
- ContainerEntrypoint
-
- Type: Array of strings
The entrypoint used to run the application in the container.
- ContainerEnvironmentVariables
-
- Type: Associative array of custom strings keys (NonEmptyString256) to strings
The environment variables to set in the container
ContainerDefinition
Description
Describes the container, as part of model definition.
Members
- AdditionalModelDataSources
-
- Type: Array of AdditionalModelDataSource structures
Data sources that are available to your model in addition to the one that you specify for
ModelDataSource
when you use theCreateModel
action. - ContainerHostname
-
- Type: string
This parameter is ignored for models that contain only a
PrimaryContainer
.When a
ContainerDefinition
is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see Use Logs and Metrics to Monitor an Inference Pipeline. If you don't specify a value for this parameter for aContainerDefinition
that is part of an inference pipeline, a unique name is automatically assigned based on the position of theContainerDefinition
in the pipeline. If you specify a value for theContainerHostName
for anyContainerDefinition
that is part of an inference pipeline, you must specify a value for theContainerHostName
parameter of everyContainerDefinition
in that pipeline. - Environment
-
- Type: Associative array of custom strings keys (EnvironmentKey) to strings
The environment variables to set in the Docker container.
The maximum length of each key and value in the
Environment
map is 1024 bytes. The maximum length of all keys and values in the map, combined, is 32 KB. If you pass multiple containers to aCreateModel
request, then the maximum length of all of their maps, combined, is also 32 KB. - Image
-
- Type: string
The path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a Docker registry that is accessible from the same VPC that you configure for your endpoint. If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both
registry/repository[:tag]
andregistry/repository[@digest]
image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
- ImageConfig
-
- Type: ImageConfig structure
Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a private Docker registry, see Use a Private Docker Registry for Real-Time Inference Containers.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
- InferenceSpecificationName
-
- Type: string
The inference specification name in the model package version.
- Mode
-
- Type: string
Whether the container hosts a single model or multiple models.
- ModelDataSource
-
- Type: ModelDataSource structure
Specifies the location of ML model data to deploy.
Currently you cannot use
ModelDataSource
in conjunction with SageMaker batch transform, SageMaker serverless endpoints, SageMaker multi-model endpoints, and SageMaker Marketplace. - ModelDataUrl
-
- Type: string
The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see Common Parameters.
The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.
If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the model artifacts in
ModelDataUrl
. - ModelPackageName
-
- Type: string
The name or Amazon Resource Name (ARN) of the model package to use to create the model.
- MultiModelConfig
-
- Type: MultiModelConfig structure
Specifies additional configuration for multi-model endpoints.
ContextSource
Description
A structure describing the source of a context.
Members
- SourceId
-
- Type: string
The ID of the source.
- SourceType
-
- Type: string
The type of the source.
- SourceUri
-
- Required: Yes
- Type: string
The URI of the source.
ContextSummary
Description
Lists a summary of the properties of a context. A context provides a logical grouping of other entities.
Members
- ContextArn
-
- Type: string
The Amazon Resource Name (ARN) of the context.
- ContextName
-
- Type: string
The name of the context.
- ContextType
-
- Type: string
The type of the context.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the context was created.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the context was last modified.
- Source
-
- Type: ContextSource structure
The source of the context.
ContinuousParameterRange
Description
A list of continuous hyperparameters to tune.
Members
- MaxValue
-
- Required: Yes
- Type: string
The maximum value for the hyperparameter. The tuning job uses floating-point values between
MinValue
value and this value for tuning. - MinValue
-
- Required: Yes
- Type: string
The minimum value for the hyperparameter. The tuning job uses floating-point values between this value and
MaxValue
for tuning. - Name
-
- Required: Yes
- Type: string
The name of the continuous hyperparameter to tune.
- ScalingType
-
- Type: string
The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
- Auto
-
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
- Linear
-
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
- Logarithmic
-
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
- ReverseLogarithmic
-
Hyperparameter tuning searches the values in the hyperparameter range by using a reverse logarithmic scale.
Reverse logarithmic scaling works only for ranges that are entirely within the range 0<=x<1.0.
ContinuousParameterRangeSpecification
Description
Defines the possible values for a continuous hyperparameter.
Members
- MaxValue
-
- Required: Yes
- Type: string
The maximum floating-point value allowed.
- MinValue
-
- Required: Yes
- Type: string
The minimum floating-point value allowed.
ConvergenceDetected
Description
A flag to indicating that automatic model tuning (AMT) has detected model convergence, defined as a lack of significant improvement (1% or less) against an objective metric.
Members
- CompleteOnConvergence
-
- Type: string
A flag to stop a tuning job once AMT has detected that the job has converged.
CustomFileSystem
Description
A file system, created by you, that you assign to a user profile or space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.
Members
- EFSFileSystem
-
- Type: EFSFileSystem structure
A custom file system in Amazon EFS.
CustomFileSystemConfig
Description
The settings for assigning a custom file system to a user profile or space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.
Members
- EFSFileSystemConfig
-
- Type: EFSFileSystemConfig structure
The settings for a custom Amazon EFS file system.
CustomImage
Description
A custom SageMaker image. For more information, see Bring your own SageMaker image.
Members
- AppImageConfigName
-
- Required: Yes
- Type: string
The name of the AppImageConfig.
- ImageName
-
- Required: Yes
- Type: string
The name of the CustomImage. Must be unique to your account.
- ImageVersionNumber
-
- Type: int
The version number of the CustomImage.
CustomPosixUserConfig
Description
Details about the POSIX identity that is used for file system operations.
Members
- Gid
-
- Required: Yes
- Type: long (int|float)
The POSIX group ID.
- Uid
-
- Required: Yes
- Type: long (int|float)
The POSIX user ID.
CustomizedMetricSpecification
Description
A customized metric.
Members
- MetricName
-
- Type: string
The name of the customized metric.
- Namespace
-
- Type: string
The namespace of the customized metric.
- Statistic
-
- Type: string
The statistic of the customized metric.
DataCaptureConfig
Description
Configuration to control how SageMaker captures inference data.
Members
- CaptureContentTypeHeader
-
- Type: CaptureContentTypeHeader structure
Configuration specifying how to treat different headers. If no headers are specified SageMaker will by default base64 encode when capturing the data.
- CaptureOptions
-
- Required: Yes
- Type: Array of CaptureOption structures
Specifies data Model Monitor will capture. You can configure whether to collect only input, only output, or both
- DestinationS3Uri
-
- Required: Yes
- Type: string
The Amazon S3 location used to capture the data.
- EnableCapture
-
- Type: boolean
Whether data capture should be enabled or disabled (defaults to enabled).
- InitialSamplingPercentage
-
- Required: Yes
- Type: int
The percentage of requests SageMaker will capture. A lower value is recommended for Endpoints with high traffic.
- KmsKeyId
-
- Type: string
The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker uses to encrypt the captured data at rest using Amazon S3 server-side encryption.
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
DataCaptureConfigSummary
Description
The currently active data capture configuration used by your Endpoint.
Members
- CaptureStatus
-
- Required: Yes
- Type: string
Whether data capture is currently functional.
- CurrentSamplingPercentage
-
- Required: Yes
- Type: int
The percentage of requests being captured by your Endpoint.
- DestinationS3Uri
-
- Required: Yes
- Type: string
The Amazon S3 location being used to capture the data.
- EnableCapture
-
- Required: Yes
- Type: boolean
Whether data capture is enabled or disabled.
- KmsKeyId
-
- Required: Yes
- Type: string
The KMS key being used to encrypt the data in Amazon S3.
DataCatalogConfig
Description
The meta data of the Glue table which serves as data catalog for the OfflineStore
.
Members
- Catalog
-
- Required: Yes
- Type: string
The name of the Glue table catalog.
- Database
-
- Required: Yes
- Type: string
The name of the Glue table database.
- TableName
-
- Required: Yes
- Type: string
The name of the Glue table.
DataProcessing
Description
The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
Members
- InputFilter
-
- Type: string
A JSONPath expression used to select a portion of the input data to pass to the algorithm. Use the
InputFilter
parameter to exclude fields, such as an ID column, from the input. If you want SageMaker to pass the entire input dataset to the algorithm, accept the default value$
.Examples:
"$"
,"$[1:]"
,"$.features"
- JoinSource
-
- Type: string
Specifies the source of the data to join with the transformed data. The valid values are
None
andInput
. The default value isNone
, which specifies not to join the input with the transformed data. If you want the batch transform job to join the original input data with the transformed data, setJoinSource
toInput
. You can specifyOutputFilter
as an additional filter to select a portion of the joined dataset and store it in the output file.For JSON or JSONLines objects, such as a JSON array, SageMaker adds the transformed data to the input JSON object in an attribute called
SageMakerOutput
. The joined result for JSON must be a key-value pair object. If the input is not a key-value pair object, SageMaker creates a new JSON file. In the new JSON file, and the input data is stored under theSageMakerInput
key and the results are stored inSageMakerOutput
.For CSV data, SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.
For information on how joining in applied, see Workflow for Associating Inferences with Input Records.
- OutputFilter
-
- Type: string
A JSONPath expression used to select a portion of the joined dataset to save in the output file for a batch transform job. If you want SageMaker to store the entire input dataset in the output file, leave the default value,
$
. If you specify indexes that aren't within the dimension size of the joined dataset, you get an error.Examples:
"$"
,"$[0,5:]"
,"$['id','SageMakerOutput']"
DataQualityAppSpecification
Description
Information about the container that a data quality monitoring job runs.
Members
- ContainerArguments
-
- Type: Array of strings
The arguments to send to the container that the monitoring job runs.
- ContainerEntrypoint
-
- Type: Array of strings
The entrypoint for a container used to run a monitoring job.
- Environment
-
- Type: Associative array of custom strings keys (ProcessingEnvironmentKey) to strings
Sets the environment variables in the container that the monitoring job runs.
- ImageUri
-
- Required: Yes
- Type: string
The container image that the data quality monitoring job runs.
- PostAnalyticsProcessorSourceUri
-
- Type: string
An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
- RecordPreprocessorSourceUri
-
- Type: string
An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
DataQualityBaselineConfig
Description
Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
Members
- BaseliningJobName
-
- Type: string
The name of the job that performs baselining for the data quality monitoring job.
- ConstraintsResource
-
- Type: MonitoringConstraintsResource structure
The constraints resource for a monitoring job.
- StatisticsResource
-
- Type: MonitoringStatisticsResource structure
The statistics resource for a monitoring job.
DataQualityJobInput
Description
The input for the data quality monitoring job. Currently endpoints are supported for input.
Members
- BatchTransformInput
-
- Type: BatchTransformInput structure
Input object for the batch transform job.
- EndpointInput
-
- Type: EndpointInput structure
Input object for the endpoint
DataSource
Description
Describes the location of the channel data.
Members
- FileSystemDataSource
-
- Type: FileSystemDataSource structure
The file system that is associated with a channel.
- S3DataSource
-
- Type: S3DataSource structure
The S3 location of the data source that is associated with a channel.
DatasetDefinition
Description
Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition
or RedshiftDatasetDefinition
types.
Members
- AthenaDatasetDefinition
-
- Type: AthenaDatasetDefinition structure
Configuration for Athena Dataset Definition input.
- DataDistributionType
-
- Type: string
Whether the generated dataset is
FullyReplicated
orShardedByS3Key
(default). - InputMode
-
- Type: string
Whether to use
File
orPipe
input mode. InFile
(default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. InPipe
mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume. - LocalPath
-
- Type: string
The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job.
LocalPath
is an absolute path to the input data. This is a required parameter whenAppManaged
isFalse
(default). - RedshiftDatasetDefinition
-
- Type: RedshiftDatasetDefinition structure
Configuration for Redshift Dataset Definition input.
DebugHookConfig
Description
Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Members
- CollectionConfigurations
-
- Type: Array of CollectionConfiguration structures
Configuration information for Amazon SageMaker Debugger tensor collections. To learn more about how to configure the
CollectionConfiguration
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job. - HookParameters
-
- Type: Associative array of custom strings keys (ConfigKey) to strings
Configuration information for the Amazon SageMaker Debugger hook parameters.
- LocalPath
-
- Type: string
Path to local storage location for metrics and tensors. Defaults to
/opt/ml/output/tensors/
. - S3OutputPath
-
- Required: Yes
- Type: string
Path to Amazon S3 storage location for metrics and tensors.
DebugRuleConfiguration
Description
Configuration information for SageMaker Debugger rules for debugging. To learn more about how to configure the DebugRuleConfiguration
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Members
- InstanceType
-
- Type: string
The instance type to deploy a custom rule for debugging a training job.
- LocalPath
-
- Type: string
Path to local storage location for output of rules. Defaults to
/opt/ml/processing/output/rule/
. - RuleConfigurationName
-
- Required: Yes
- Type: string
The name of the rule configuration. It must be unique relative to other rule configuration names.
- RuleEvaluatorImage
-
- Required: Yes
- Type: string
The Amazon Elastic Container (ECR) Image for the managed rule evaluation.
- RuleParameters
-
- Type: Associative array of custom strings keys (ConfigKey) to strings
Runtime configuration for rule container.
- S3OutputPath
-
- Type: string
Path to Amazon S3 storage location for rules.
- VolumeSizeInGB
-
- Type: int
The size, in GB, of the ML storage volume attached to the processing instance.
DebugRuleEvaluationStatus
Description
Information about the status of the rule evaluation.
Members
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Timestamp when the rule evaluation status was last modified.
- RuleConfigurationName
-
- Type: string
The name of the rule configuration.
- RuleEvaluationJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the rule evaluation job.
- RuleEvaluationStatus
-
- Type: string
Status of the rule evaluation.
- StatusDetails
-
- Type: string
Details from the rule evaluation.
DefaultEbsStorageSettings
Description
A collection of default EBS storage settings that apply to spaces created within a domain or user profile.
Members
- DefaultEbsVolumeSizeInGb
-
- Required: Yes
- Type: int
The default size of the EBS storage volume for a space.
- MaximumEbsVolumeSizeInGb
-
- Required: Yes
- Type: int
The maximum size of the EBS storage volume for a space.
DefaultSpaceSettings
Description
A collection of settings that apply to spaces created in the domain.
Members
- CustomFileSystemConfigs
-
- Type: Array of CustomFileSystemConfig structures
The settings for assigning a custom file system to a domain. Permitted users can access this file system in Amazon SageMaker Studio.
- CustomPosixUserConfig
-
- Type: CustomPosixUserConfig structure
Details about the POSIX identity that is used for file system operations.
- ExecutionRole
-
- Type: string
The ARN of the execution role for the space.
- JupyterLabAppSettings
-
- Type: JupyterLabAppSettings structure
The settings for the JupyterLab application.
- JupyterServerAppSettings
-
- Type: JupyterServerAppSettings structure
The JupyterServer app settings.
- KernelGatewayAppSettings
-
- Type: KernelGatewayAppSettings structure
The KernelGateway app settings.
- SecurityGroups
-
- Type: Array of strings
The security group IDs for the Amazon VPC that the space uses for communication.
- SpaceStorageSettings
-
- Type: DefaultSpaceStorageSettings structure
The default storage settings for a space.
DefaultSpaceStorageSettings
Description
The default storage settings for a space.
Members
- DefaultEbsStorageSettings
-
- Type: DefaultEbsStorageSettings structure
The default EBS storage settings for a space.
DeployedImage
Description
Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the registry/repository[:tag]
form to specify the image path of the primary container when you created the model hosted in this ProductionVariant
, the path resolves to a path of the form registry/repository[@digest]
. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
Members
- ResolutionTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time when the image path for the model resolved to the
ResolvedImage
- ResolvedImage
-
- Type: string
The specific digest path of the image hosted in this
ProductionVariant
. - SpecifiedImage
-
- Type: string
The image path you specified when you created the model.
DeploymentConfig
Description
The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
Members
- AutoRollbackConfiguration
-
- Type: AutoRollbackConfig structure
Automatic rollback configuration for handling endpoint deployment failures and recovery.
- BlueGreenUpdatePolicy
-
- Type: BlueGreenUpdatePolicy structure
Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
- RollingUpdatePolicy
-
- Type: RollingUpdatePolicy structure
Specifies a rolling deployment strategy for updating a SageMaker endpoint.
DeploymentRecommendation
Description
A set of recommended deployment configurations for the model. To get more advanced recommendations, see CreateInferenceRecommendationsJob to create an inference recommendation job.
Members
- RealTimeInferenceRecommendations
-
- Type: Array of RealTimeInferenceRecommendation structures
A list of RealTimeInferenceRecommendation items.
- RecommendationStatus
-
- Required: Yes
- Type: string
Status of the deployment recommendation. The status
NOT_APPLICABLE
means that SageMaker is unable to provide a default recommendation for the model using the information provided. If the deployment status isIN_PROGRESS
, retry your API call after a few seconds to get aCOMPLETED
deployment recommendation.
DeploymentStage
Description
Contains information about a stage in an edge deployment plan.
Members
- DeploymentConfig
-
- Type: EdgeDeploymentConfig structure
Configuration of the deployment details.
- DeviceSelectionConfig
-
- Required: Yes
- Type: DeviceSelectionConfig structure
Configuration of the devices in the stage.
- StageName
-
- Required: Yes
- Type: string
The name of the stage.
DeploymentStageStatusSummary
Description
Contains information summarizing the deployment stage results.
Members
- DeploymentConfig
-
- Required: Yes
- Type: EdgeDeploymentConfig structure
Configuration of the deployment details.
- DeploymentStatus
-
- Required: Yes
- Type: EdgeDeploymentStatus structure
General status of the current state.
- DeviceSelectionConfig
-
- Required: Yes
- Type: DeviceSelectionConfig structure
Configuration of the devices in the stage.
- StageName
-
- Required: Yes
- Type: string
The name of the stage.
DerivedInformation
Description
Information that SageMaker Neo automatically derived about the model.
Members
- DerivedDataInputConfig
-
- Type: string
The data input configuration that SageMaker Neo automatically derived for the model. When SageMaker Neo derives this information, you don't need to specify the data input configuration when you create a compilation job.
DesiredWeightAndCapacity
Description
Specifies weight and capacity values for a production variant.
Members
- DesiredInstanceCount
-
- Type: int
The variant's capacity.
- DesiredWeight
-
- Type: float
The variant's weight.
- ServerlessUpdateConfig
-
- Type: ProductionVariantServerlessUpdateConfig structure
Specifies the serverless update concurrency configuration for an endpoint variant.
- VariantName
-
- Required: Yes
- Type: string
The name of the variant to update.
Device
Description
Information of a particular device.
Members
- Description
-
- Type: string
Description of the device.
- DeviceName
-
- Required: Yes
- Type: string
The name of the device.
- IotThingName
-
- Type: string
Amazon Web Services Internet of Things (IoT) object name.
DeviceDeploymentSummary
Description
Contains information summarizing device details and deployment status.
Members
- DeployedStageName
-
- Type: string
The name of the deployed stage.
- DeploymentStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the deployment on the device started.
- Description
-
- Type: string
The description of the device.
- DeviceArn
-
- Required: Yes
- Type: string
The ARN of the device.
- DeviceDeploymentStatus
-
- Type: string
The deployment status of the device.
- DeviceDeploymentStatusMessage
-
- Type: string
The detailed error message for the deployoment status result.
- DeviceFleetName
-
- Type: string
The name of the fleet to which the device belongs to.
- DeviceName
-
- Required: Yes
- Type: string
The name of the device.
- EdgeDeploymentPlanArn
-
- Required: Yes
- Type: string
The ARN of the edge deployment plan.
- EdgeDeploymentPlanName
-
- Required: Yes
- Type: string
The name of the edge deployment plan.
- StageName
-
- Required: Yes
- Type: string
The name of the stage in the edge deployment plan.
DeviceFleetSummary
Description
Summary of the device fleet.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Timestamp of when the device fleet was created.
- DeviceFleetArn
-
- Required: Yes
- Type: string
Amazon Resource Name (ARN) of the device fleet.
- DeviceFleetName
-
- Required: Yes
- Type: string
Name of the device fleet.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Timestamp of when the device fleet was last updated.
DeviceSelectionConfig
Description
Contains information about the configurations of selected devices.
Members
- DeviceNameContains
-
- Type: string
A filter to select devices with names containing this name.
- DeviceNames
-
- Type: Array of strings
List of devices chosen to deploy.
- DeviceSubsetType
-
- Required: Yes
- Type: string
Type of device subsets to deploy to the current stage.
- Percentage
-
- Type: int
Percentage of devices in the fleet to deploy to the current stage.
DeviceStats
Description
Status of devices.
Members
- ConnectedDeviceCount
-
- Required: Yes
- Type: long (int|float)
The number of devices connected with a heartbeat.
- RegisteredDeviceCount
-
- Required: Yes
- Type: long (int|float)
The number of registered devices.
DeviceSummary
Description
Summary of the device.
Members
- AgentVersion
-
- Type: string
Edge Manager agent version.
- Description
-
- Type: string
A description of the device.
- DeviceArn
-
- Required: Yes
- Type: string
Amazon Resource Name (ARN) of the device.
- DeviceFleetName
-
- Type: string
The name of the fleet the device belongs to.
- DeviceName
-
- Required: Yes
- Type: string
The unique identifier of the device.
- IotThingName
-
- Type: string
The Amazon Web Services Internet of Things (IoT) object thing name associated with the device..
- LatestHeartbeat
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last heartbeat received from the device.
- Models
-
- Type: Array of EdgeModelSummary structures
Models on the device.
- RegistrationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of the last registration or de-reregistration.
DirectDeploySettings
Description
The model deployment settings for the SageMaker Canvas application.
In order to enable model deployment for Canvas, the SageMaker Domain's or user profile's Amazon Web Services IAM execution role must have the AmazonSageMakerCanvasDirectDeployAccess
policy attached. You can also turn on model deployment permissions through the SageMaker Domain's or user profile's settings in the SageMaker console.
Members
- Status
-
- Type: string
Describes whether model deployment permissions are enabled or disabled in the Canvas application.
DockerSettings
Description
A collection of settings that configure the domain's Docker interaction.
Members
- EnableDockerAccess
-
- Type: string
Indicates whether the domain can access Docker.
- VpcOnlyTrustedAccounts
-
- Type: Array of strings
The list of Amazon Web Services accounts that are trusted when the domain is created in VPC-only mode.
DomainDetails
Description
The domain's details.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time.
- DomainArn
-
- Type: string
The domain's Amazon Resource Name (ARN).
- DomainId
-
- Type: string
The domain ID.
- DomainName
-
- Type: string
The domain name.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last modified time.
- Status
-
- Type: string
The status.
- Url
-
- Type: string
The domain's URL.
DomainSettings
Description
A collection of settings that apply to the SageMaker Domain
. These settings are specified through the CreateDomain
API call.
Members
- AmazonQSettings
-
- Type: AmazonQSettings structure
A collection of settings that configure the Amazon Q experience within the domain. The
AuthMode
that you use to create the domain must beSSO
. - DockerSettings
-
- Type: DockerSettings structure
A collection of settings that configure the domain's Docker interaction.
- ExecutionRoleIdentityConfig
-
- Type: string
The configuration for attaching a SageMaker user profile name to the execution role as a sts:SourceIdentity key.
- RStudioServerProDomainSettings
-
- Type: RStudioServerProDomainSettings structure
A collection of settings that configure the
RStudioServerPro
Domain-level app. - SecurityGroupIds
-
- Type: Array of strings
The security groups for the Amazon Virtual Private Cloud that the
Domain
uses for communication between Domain-level apps and user apps.
DomainSettingsForUpdate
Description
A collection of Domain
configuration settings to update.
Members
- AmazonQSettings
-
- Type: AmazonQSettings structure
A collection of settings that configure the Amazon Q experience within the domain.
- DockerSettings
-
- Type: DockerSettings structure
A collection of settings that configure the domain's Docker interaction.
- ExecutionRoleIdentityConfig
-
- Type: string
The configuration for attaching a SageMaker user profile name to the execution role as a sts:SourceIdentity key. This configuration can only be modified if there are no apps in the
InService
orPending
state. - RStudioServerProDomainSettingsForUpdate
-
- Type: RStudioServerProDomainSettingsForUpdate structure
A collection of
RStudioServerPro
Domain-level app settings to update. A singleRStudioServerPro
application is created for a domain. - SecurityGroupIds
-
- Type: Array of strings
The security groups for the Amazon Virtual Private Cloud that the
Domain
uses for communication between Domain-level apps and user apps.
DriftCheckBaselines
Description
Represents the drift check baselines that can be used when the model monitor is set using the model package.
Members
- Bias
-
- Type: DriftCheckBias structure
Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
- Explainability
-
- Type: DriftCheckExplainability structure
Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
- ModelDataQuality
-
- Type: DriftCheckModelDataQuality structure
Represents the drift check model data quality baselines that can be used when the model monitor is set using the model package.
- ModelQuality
-
- Type: DriftCheckModelQuality structure
Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
DriftCheckBias
Description
Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
Members
- ConfigFile
-
- Type: FileSource structure
The bias config file for a model.
- PostTrainingConstraints
-
- Type: MetricsSource structure
The post-training constraints.
- PreTrainingConstraints
-
- Type: MetricsSource structure
The pre-training constraints.
DriftCheckExplainability
Description
Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
Members
- ConfigFile
-
- Type: FileSource structure
The explainability config file for the model.
- Constraints
-
- Type: MetricsSource structure
The drift check explainability constraints.
DriftCheckModelDataQuality
Description
Represents the drift check data quality baselines that can be used when the model monitor is set using the model package.
Members
- Constraints
-
- Type: MetricsSource structure
The drift check model data quality constraints.
- Statistics
-
- Type: MetricsSource structure
The drift check model data quality statistics.
DriftCheckModelQuality
Description
Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
Members
- Constraints
-
- Type: MetricsSource structure
The drift check model quality constraints.
- Statistics
-
- Type: MetricsSource structure
The drift check model quality statistics.
DynamicScalingConfiguration
Description
An object with the recommended values for you to specify when creating an autoscaling policy.
Members
- MaxCapacity
-
- Type: int
The recommended maximum capacity to specify for your autoscaling policy.
- MinCapacity
-
- Type: int
The recommended minimum capacity to specify for your autoscaling policy.
- ScaleInCooldown
-
- Type: int
The recommended scale in cooldown time for your autoscaling policy.
- ScaleOutCooldown
-
- Type: int
The recommended scale out cooldown time for your autoscaling policy.
- ScalingPolicies
-
- Type: Array of ScalingPolicy structures
An object of the scaling policies for each metric.
EFSFileSystem
Description
A file system, created by you in Amazon EFS, that you assign to a user profile or space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.
Members
- FileSystemId
-
- Required: Yes
- Type: string
The ID of your Amazon EFS file system.
EFSFileSystemConfig
Description
The settings for assigning a custom Amazon EFS file system to a user profile or space for an Amazon SageMaker Domain.
Members
- FileSystemId
-
- Required: Yes
- Type: string
The ID of your Amazon EFS file system.
- FileSystemPath
-
- Type: string
The path to the file system directory that is accessible in Amazon SageMaker Studio. Permitted users can access only this directory and below.
EMRStepMetadata
Description
The configurations and outcomes of an Amazon EMR step execution.
Members
- ClusterId
-
- Type: string
The identifier of the EMR cluster.
- LogFilePath
-
- Type: string
The path to the log file where the cluster step's failure root cause is recorded.
- StepId
-
- Type: string
The identifier of the EMR cluster step.
- StepName
-
- Type: string
The name of the EMR cluster step.
EbsStorageSettings
Description
A collection of EBS storage settings that apply to both private and shared spaces.
Members
- EbsVolumeSizeInGb
-
- Required: Yes
- Type: int
The size of an EBS storage volume for a space.
Edge
Description
A directed edge connecting two lineage entities.
Members
- AssociationType
-
- Type: string
The type of the Association(Edge) between the source and destination. For example
ContributedTo
,Produced
, orDerivedFrom
. - DestinationArn
-
- Type: string
The Amazon Resource Name (ARN) of the destination lineage entity of the directed edge.
- SourceArn
-
- Type: string
The Amazon Resource Name (ARN) of the source lineage entity of the directed edge.
EdgeDeploymentConfig
Description
Contains information about the configuration of a deployment.
Members
- FailureHandlingPolicy
-
- Required: Yes
- Type: string
Toggle that determines whether to rollback to previous configuration if the current deployment fails. By default this is turned on. You may turn this off if you want to investigate the errors yourself.
EdgeDeploymentModelConfig
Description
Contains information about the configuration of a model in a deployment.
Members
- EdgePackagingJobName
-
- Required: Yes
- Type: string
The edge packaging job associated with this deployment.
- ModelHandle
-
- Required: Yes
- Type: string
The name the device application uses to reference this model.
EdgeDeploymentPlanSummary
Description
Contains information summarizing an edge deployment plan.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the edge deployment plan was created.
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the device fleet used for the deployment.
- EdgeDeploymentFailed
-
- Required: Yes
- Type: int
The number of edge devices that failed the deployment.
- EdgeDeploymentPending
-
- Required: Yes
- Type: int
The number of edge devices yet to pick up the deployment, or in progress.
- EdgeDeploymentPlanArn
-
- Required: Yes
- Type: string
The ARN of the edge deployment plan.
- EdgeDeploymentPlanName
-
- Required: Yes
- Type: string
The name of the edge deployment plan.
- EdgeDeploymentSuccess
-
- Required: Yes
- Type: int
The number of edge devices with the successful deployment.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the edge deployment plan was last updated.
EdgeDeploymentStatus
Description
Contains information summarizing the deployment stage results.
Members
- EdgeDeploymentFailedInStage
-
- Required: Yes
- Type: int
The number of edge devices that failed the deployment in current stage.
- EdgeDeploymentPendingInStage
-
- Required: Yes
- Type: int
The number of edge devices yet to pick up the deployment in current stage, or in progress.
- EdgeDeploymentStageStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the deployment API started.
- EdgeDeploymentStatusMessage
-
- Type: string
A detailed message about deployment status in current stage.
- EdgeDeploymentSuccessInStage
-
- Required: Yes
- Type: int
The number of edge devices with the successful deployment in the current stage.
- StageStatus
-
- Required: Yes
- Type: string
The general status of the current stage.
EdgeModel
Description
The model on the edge device.
Members
- LatestInference
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of the last inference that was made.
- LatestSampleTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of the last data sample taken.
- ModelName
-
- Required: Yes
- Type: string
The name of the model.
- ModelVersion
-
- Required: Yes
- Type: string
The model version.
EdgeModelStat
Description
Status of edge devices with this model.
Members
- ActiveDeviceCount
-
- Required: Yes
- Type: long (int|float)
The number of devices that have this model version, a heart beat, and are currently running.
- ConnectedDeviceCount
-
- Required: Yes
- Type: long (int|float)
The number of devices that have this model version and have a heart beat.
- ModelName
-
- Required: Yes
- Type: string
The name of the model.
- ModelVersion
-
- Required: Yes
- Type: string
The model version.
- OfflineDeviceCount
-
- Required: Yes
- Type: long (int|float)
The number of devices that have this model version and do not have a heart beat.
- SamplingDeviceCount
-
- Required: Yes
- Type: long (int|float)
The number of devices with this model version and are producing sample data.
EdgeModelSummary
Description
Summary of model on edge device.
Members
- ModelName
-
- Required: Yes
- Type: string
The name of the model.
- ModelVersion
-
- Required: Yes
- Type: string
The version model.
EdgeOutputConfig
Description
The output configuration.
Members
- KmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume after compilation job. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account.
- PresetDeploymentConfig
-
- Type: string
The configuration used to create deployment artifacts. Specify configuration options with a JSON string. The available configuration options for each type are:
-
ComponentName
(optional) - Name of the GreenGrass V2 component. If not specified, the default name generated consists of "SagemakerEdgeManager" and the name of your SageMaker Edge Manager packaging job. -
ComponentDescription
(optional) - Description of the component. -
ComponentVersion
(optional) - The version of the component.Amazon Web Services IoT Greengrass uses semantic versions for components. Semantic versions follow a major.minor.patch number system. For example, version 1.0.0 represents the first major release for a component. For more information, see the semantic version specification.
-
PlatformOS
(optional) - The name of the operating system for the platform. Supported platforms include Windows and Linux. -
PlatformArchitecture
(optional) - The processor architecture for the platform.Supported architectures Windows include: Windows32_x86, Windows64_x64.
Supported architectures for Linux include: Linux x86_64, Linux ARMV8.
- PresetDeploymentType
-
- Type: string
The deployment type SageMaker Edge Manager will create. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
- S3OutputLocation
-
- Required: Yes
- Type: string
The Amazon Simple Storage (S3) bucker URI.
EdgePackagingJobSummary
Description
Summary of edge packaging job.
Members
- CompilationJobName
-
- Type: string
The name of the SageMaker Neo compilation job.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of when the job was created.
- EdgePackagingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the edge packaging job.
- EdgePackagingJobName
-
- Required: Yes
- Type: string
The name of the edge packaging job.
- EdgePackagingJobStatus
-
- Required: Yes
- Type: string
The status of the edge packaging job.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of when the edge packaging job was last updated.
- ModelName
-
- Type: string
The name of the model.
- ModelVersion
-
- Type: string
The version of the model.
EdgePresetDeploymentOutput
Description
The output of a SageMaker Edge Manager deployable resource.
Members
- Artifact
-
- Type: string
The Amazon Resource Name (ARN) of the generated deployable resource.
- Status
-
- Type: string
The status of the deployable resource.
- StatusMessage
-
- Type: string
Returns a message describing the status of the deployed resource.
- Type
-
- Required: Yes
- Type: string
The deployment type created by SageMaker Edge Manager. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
EmrServerlessComputeConfig
Description
This data type is intended for use exclusively by SageMaker Canvas and cannot be used in other contexts at the moment.
Specifies the compute configuration for the EMR Serverless job.
Members
- ExecutionRoleARN
-
- Required: Yes
- Type: string
The ARN of the IAM role granting the AutoML job V2 the necessary permissions access policies to list, connect to, or manage EMR Serverless jobs. For detailed information about the required permissions of this role, see "How to configure AutoML to initiate a remote job on EMR Serverless for large datasets" in Create a regression or classification job for tabular data using the AutoML API or Create an AutoML job for time-series forecasting using the API.
EmrServerlessSettings
Description
The settings for running Amazon EMR Serverless jobs in SageMaker Canvas.
Members
- ExecutionRoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the Amazon Web Services IAM role that is assumed for running Amazon EMR Serverless jobs in SageMaker Canvas. This role should have the necessary permissions to read and write data attached and a trust relationship with EMR Serverless.
- Status
-
- Type: string
Describes whether Amazon EMR Serverless job capabilities are enabled or disabled in the SageMaker Canvas application.
EmrSettings
Description
The configuration parameters that specify the IAM roles assumed by the execution role of SageMaker (assumable roles) and the cluster instances or job execution environments (execution roles or runtime roles) to manage and access resources required for running Amazon EMR clusters or Amazon EMR Serverless applications.
Members
- AssumableRoleArns
-
- Type: Array of strings
An array of Amazon Resource Names (ARNs) of the IAM roles that the execution role of SageMaker can assume for performing operations or tasks related to Amazon EMR clusters or Amazon EMR Serverless applications. These roles define the permissions and access policies required when performing Amazon EMR-related operations, such as listing, connecting to, or terminating Amazon EMR clusters or Amazon EMR Serverless applications. They are typically used in cross-account access scenarios, where the Amazon EMR resources (clusters or serverless applications) are located in a different Amazon Web Services account than the SageMaker domain.
- ExecutionRoleArns
-
- Type: Array of strings
An array of Amazon Resource Names (ARNs) of the IAM roles used by the Amazon EMR cluster instances or job execution environments to access other Amazon Web Services services and resources needed during the runtime of your Amazon EMR or Amazon EMR Serverless workloads, such as Amazon S3 for data access, Amazon CloudWatch for logging, or other Amazon Web Services services based on the particular workload requirements.
Endpoint
Description
A hosted endpoint for real-time inference.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the endpoint was created.
- DataCaptureConfig
-
- Type: DataCaptureConfigSummary structure
The currently active data capture configuration used by your Endpoint.
- EndpointArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the endpoint.
- EndpointConfigName
-
- Required: Yes
- Type: string
The endpoint configuration associated with the endpoint.
- EndpointName
-
- Required: Yes
- Type: string
The name of the endpoint.
- EndpointStatus
-
- Required: Yes
- Type: string
The status of the endpoint.
- FailureReason
-
- Type: string
If the endpoint failed, the reason it failed.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last time the endpoint was modified.
- MonitoringSchedules
-
- Type: Array of MonitoringSchedule structures
A list of monitoring schedules for the endpoint. For information about model monitoring, see Amazon SageMaker Model Monitor.
- ProductionVariants
-
- Type: Array of ProductionVariantSummary structures
A list of the production variants hosted on the endpoint. Each production variant is a model.
- ShadowProductionVariants
-
- Type: Array of ProductionVariantSummary structures
A list of the shadow variants hosted on the endpoint. Each shadow variant is a model in shadow mode with production traffic replicated from the production variant.
- Tags
-
- Type: Array of Tag structures
A list of the tags associated with the endpoint. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
EndpointConfigStepMetadata
Description
Metadata for an endpoint configuration step.
Members
- Arn
-
- Type: string
The Amazon Resource Name (ARN) of the endpoint configuration used in the step.
EndpointConfigSummary
Description
Provides summary information for an endpoint configuration.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the endpoint configuration was created.
- EndpointConfigArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the endpoint configuration.
- EndpointConfigName
-
- Required: Yes
- Type: string
The name of the endpoint configuration.
EndpointInfo
Description
Details about a customer endpoint that was compared in an Inference Recommender job.
Members
- EndpointName
-
- Type: string
The name of a customer's endpoint.
EndpointInput
Description
Input object for the endpoint
Members
- EndTimeOffset
-
- Type: string
If specified, monitoring jobs substract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
- EndpointName
-
- Required: Yes
- Type: string
An endpoint in customer's account which has enabled
DataCaptureConfig
enabled. - ExcludeFeaturesAttribute
-
- Type: string
The attributes of the input data to exclude from the analysis.
- FeaturesAttribute
-
- Type: string
The attributes of the input data that are the input features.
- InferenceAttribute
-
- Type: string
The attribute of the input data that represents the ground truth label.
- LocalPath
-
- Required: Yes
- Type: string
Path to the filesystem where the endpoint data is available to the container.
- ProbabilityAttribute
-
- Type: string
In a classification problem, the attribute that represents the class probability.
- ProbabilityThresholdAttribute
-
- Type: double
The threshold for the class probability to be evaluated as a positive result.
- S3DataDistributionType
-
- Type: string
Whether input data distributed in Amazon S3 is fully replicated or sharded by an Amazon S3 key. Defaults to
FullyReplicated
- S3InputMode
-
- Type: string
Whether the
Pipe
orFile
is used as the input mode for transferring data for the monitoring job.Pipe
mode is recommended for large datasets.File
mode is useful for small files that fit in memory. Defaults toFile
. - StartTimeOffset
-
- Type: string
If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
EndpointInputConfiguration
Description
The endpoint configuration for the load test.
Members
- EnvironmentParameterRanges
-
- Type: EnvironmentParameterRanges structure
The parameter you want to benchmark against.
- InferenceSpecificationName
-
- Type: string
The inference specification name in the model package version.
- InstanceType
-
- Type: string
The instance types to use for the load test.
- ServerlessConfig
-
- Type: ProductionVariantServerlessConfig structure
Specifies the serverless configuration for an endpoint variant.
EndpointMetadata
Description
The metadata of the endpoint.
Members
- EndpointConfigName
-
- Type: string
The name of the endpoint configuration.
- EndpointName
-
- Required: Yes
- Type: string
The name of the endpoint.
- EndpointStatus
-
- Type: string
The status of the endpoint. For possible values of the status of an endpoint, see EndpointSummary.
- FailureReason
-
- Type: string
If the status of the endpoint is
Failed
, or the status isInService
but update operation fails, this provides the reason why it failed.
EndpointOutputConfiguration
Description
The endpoint configuration made by Inference Recommender during a recommendation job.
Members
- EndpointName
-
- Required: Yes
- Type: string
The name of the endpoint made during a recommendation job.
- InitialInstanceCount
-
- Type: int
The number of instances recommended to launch initially.
- InstanceType
-
- Type: string
The instance type recommended by Amazon SageMaker Inference Recommender.
- ServerlessConfig
-
- Type: ProductionVariantServerlessConfig structure
Specifies the serverless configuration for an endpoint variant.
- VariantName
-
- Required: Yes
- Type: string
The name of the production variant (deployed model) made during a recommendation job.
EndpointPerformance
Description
The performance results from running an Inference Recommender job on an existing endpoint.
Members
- EndpointInfo
-
- Required: Yes
- Type: EndpointInfo structure
Details about a customer endpoint that was compared in an Inference Recommender job.
- Metrics
-
- Required: Yes
- Type: InferenceMetrics structure
The metrics for an existing endpoint.
EndpointStepMetadata
Description
Metadata for an endpoint step.
Members
- Arn
-
- Type: string
The Amazon Resource Name (ARN) of the endpoint in the step.
EndpointSummary
Description
Provides summary information for an endpoint.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the endpoint was created.
- EndpointArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the endpoint.
- EndpointName
-
- Required: Yes
- Type: string
The name of the endpoint.
- EndpointStatus
-
- Required: Yes
- Type: string
The status of the endpoint.
-
OutOfService
: Endpoint is not available to take incoming requests. -
Creating
: CreateEndpoint is executing. -
Updating
: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing. -
SystemUpdating
: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count. -
RollingBack
: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to anInService
status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly. -
InService
: Endpoint is available to process incoming requests. -
Deleting
: DeleteEndpoint is executing. -
Failed
: Endpoint could not be created, updated, or re-scaled. UseDescribeEndpointOutput$FailureReason
for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
To get a list of endpoints with a specified status, use the
StatusEquals
filter with a call to ListEndpoints. - LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the endpoint was last modified.
EnvironmentParameter
Description
A list of environment parameters suggested by the Amazon SageMaker Inference Recommender.
Members
- Key
-
- Required: Yes
- Type: string
The environment key suggested by the Amazon SageMaker Inference Recommender.
- Value
-
- Required: Yes
- Type: string
The value suggested by the Amazon SageMaker Inference Recommender.
- ValueType
-
- Required: Yes
- Type: string
The value type suggested by the Amazon SageMaker Inference Recommender.
EnvironmentParameterRanges
Description
Specifies the range of environment parameters
Members
- CategoricalParameterRanges
-
- Type: Array of CategoricalParameter structures
Specified a list of parameters for each category.
Experiment
Description
The properties of an experiment as returned by the Search API.
Members
- CreatedBy
-
- Type: UserContext structure
Who created the experiment.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the experiment was created.
- Description
-
- Type: string
The description of the experiment.
- DisplayName
-
- Type: string
The name of the experiment as displayed. If
DisplayName
isn't specified,ExperimentName
is displayed. - ExperimentArn
-
- Type: string
The Amazon Resource Name (ARN) of the experiment.
- ExperimentName
-
- Type: string
The name of the experiment.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the experiment was last modified.
- Source
-
- Type: ExperimentSource structure
The source of the experiment.
- Tags
-
- Type: Array of Tag structures
The list of tags that are associated with the experiment. You can use Search API to search on the tags.
ExperimentConfig
Description
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
Members
- ExperimentName
-
- Type: string
The name of an existing experiment to associate with the trial component.
- RunName
-
- Type: string
The name of the experiment run to associate with the trial component.
- TrialComponentDisplayName
-
- Type: string
The display name for the trial component. If this key isn't specified, the display name is the trial component name.
- TrialName
-
- Type: string
The name of an existing trial to associate the trial component with. If not specified, a new trial is created.
ExperimentSource
Description
The source of the experiment.
Members
- SourceArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the source.
- SourceType
-
- Type: string
The source type.
ExperimentSummary
Description
A summary of the properties of an experiment. To get the complete set of properties, call the DescribeExperiment API and provide the ExperimentName
.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the experiment was created.
- DisplayName
-
- Type: string
The name of the experiment as displayed. If
DisplayName
isn't specified,ExperimentName
is displayed. - ExperimentArn
-
- Type: string
The Amazon Resource Name (ARN) of the experiment.
- ExperimentName
-
- Type: string
The name of the experiment.
- ExperimentSource
-
- Type: ExperimentSource structure
The source of the experiment.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the experiment was last modified.
Explainability
Description
Contains explainability metrics for a model.
Members
- Report
-
- Type: MetricsSource structure
The explainability report for a model.
ExplainerConfig
Description
A parameter to activate explainers.
Members
- ClarifyExplainerConfig
-
- Type: ClarifyExplainerConfig structure
A member of
ExplainerConfig
that contains configuration parameters for the SageMaker Clarify explainer.
FailStepMetadata
Description
The container for the metadata for Fail step.
Members
- ErrorMessage
-
- Type: string
A message that you define and then is processed and rendered by the Fail step when the error occurs.
FeatureDefinition
Description
A list of features. You must include FeatureName
and FeatureType
. Valid feature FeatureType
s are Integral
, Fractional
and String
.
Members
- CollectionConfig
-
- Type: CollectionConfig structure
Configuration for your collection.
- CollectionType
-
- Type: string
A grouping of elements where each element within the collection must have the same feature type (
String
,Integral
, orFractional
).-
List
: An ordered collection of elements. -
Set
: An unordered collection of unique elements. -
Vector
: A specialized list that represents a fixed-size array of elements. The vector dimension is determined by you. Must have elements with fractional feature types.
- FeatureName
-
- Required: Yes
- Type: string
The name of a feature. The type must be a string.
FeatureName
cannot be any of the following:is_deleted
,write_time
,api_invocation_time
.The name:
-
Must start with an alphanumeric character.
-
Can only include alphanumeric characters, underscores, and hyphens. Spaces are not allowed.
- FeatureType
-
- Required: Yes
- Type: string
The value type of a feature. Valid values are Integral, Fractional, or String.
FeatureGroup
Description
Amazon SageMaker Feature Store stores features in a collection called Feature Group. A Feature Group can be visualized as a table which has rows, with a unique identifier for each row where each column in the table is a feature. In principle, a Feature Group is composed of features and values per features.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time a
FeatureGroup
was created. - Description
-
- Type: string
A free form description of a
FeatureGroup
. - EventTimeFeatureName
-
- Type: string
The name of the feature that stores the
EventTime
of a Record in aFeatureGroup
.A
EventTime
is point in time when a new event occurs that corresponds to the creation or update of aRecord
inFeatureGroup
. AllRecords
in theFeatureGroup
must have a correspondingEventTime
. - FailureReason
-
- Type: string
The reason that the
FeatureGroup
failed to be replicated in theOfflineStore
. This is failure may be due to a failure to create aFeatureGroup
in or delete aFeatureGroup
from theOfflineStore
. - FeatureDefinitions
-
- Type: Array of FeatureDefinition structures
A list of
Feature
s. EachFeature
must include aFeatureName
and aFeatureType
.Valid
FeatureType
s areIntegral
,Fractional
andString
.FeatureName
s cannot be any of the following:is_deleted
,write_time
,api_invocation_time
.You can create up to 2,500
FeatureDefinition
s perFeatureGroup
. - FeatureGroupArn
-
- Type: string
The Amazon Resource Name (ARN) of a
FeatureGroup
. - FeatureGroupName
-
- Type: string
The name of the
FeatureGroup
. - FeatureGroupStatus
-
- Type: string
A
FeatureGroup
status. - LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp indicating the last time you updated the feature group.
- LastUpdateStatus
-
- Type: LastUpdateStatus structure
A value that indicates whether the feature group was updated successfully.
- OfflineStoreConfig
-
- Type: OfflineStoreConfig structure
The configuration of an
OfflineStore
.Provide an
OfflineStoreConfig
in a request toCreateFeatureGroup
to create anOfflineStore
.To encrypt an
OfflineStore
using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, orKMSKeyId
, inS3StorageConfig
. - OfflineStoreStatus
-
- Type: OfflineStoreStatus structure
The status of
OfflineStore
. - OnlineStoreConfig
-
- Type: OnlineStoreConfig structure
Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or
KMSKeyId
, for at rest data encryption. You can turnOnlineStore
on or off by specifying theEnableOnlineStore
flag at General Assembly.The default value is
False
. - RecordIdentifierFeatureName
-
- Type: string
The name of the
Feature
whose value uniquely identifies aRecord
defined in theFeatureGroup
FeatureDefinitions
. - RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM execution role used to create the feature group.
- Tags
-
- Type: Array of Tag structures
Tags used to define a
FeatureGroup
.
FeatureGroupSummary
Description
The name, ARN, CreationTime
, FeatureGroup
values, LastUpdatedTime
and EnableOnlineStorage
status of a FeatureGroup
.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp indicating the time of creation time of the
FeatureGroup
. - FeatureGroupArn
-
- Required: Yes
- Type: string
Unique identifier for the
FeatureGroup
. - FeatureGroupName
-
- Required: Yes
- Type: string
The name of
FeatureGroup
. - FeatureGroupStatus
-
- Type: string
The status of a FeatureGroup. The status can be any of the following:
Creating
,Created
,CreateFail
,Deleting
orDetailFail
. - OfflineStoreStatus
-
- Type: OfflineStoreStatus structure
Notifies you if replicating data into the
OfflineStore
has failed. Returns either:Active
orBlocked
.
FeatureMetadata
Description
The metadata for a feature. It can either be metadata that you specify, or metadata that is updated automatically.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp indicating when the feature was created.
- Description
-
- Type: string
An optional description that you specify to better describe the feature.
- FeatureGroupArn
-
- Type: string
The Amazon Resource Number (ARN) of the feature group.
- FeatureGroupName
-
- Type: string
The name of the feature group containing the feature.
- FeatureName
-
- Type: string
The name of feature.
- FeatureType
-
- Type: string
The data type of the feature.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp indicating when the feature was last modified.
- Parameters
-
- Type: Array of FeatureParameter structures
Optional key-value pairs that you specify to better describe the feature.
FeatureParameter
Description
A key-value pair that you specify to describe the feature.
Members
- Key
-
- Type: string
A key that must contain a value to describe the feature.
- Value
-
- Type: string
The value that belongs to a key.
FileSource
Description
Contains details regarding the file source.
Members
- ContentDigest
-
- Type: string
The digest of the file source.
- ContentType
-
- Type: string
The type of content stored in the file source.
- S3Uri
-
- Required: Yes
- Type: string
The Amazon S3 URI for the file source.
FileSystemConfig
Description
The Amazon Elastic File System storage configuration for a SageMaker image.
Members
- DefaultGid
-
- Type: int
The default POSIX group ID (GID). If not specified, defaults to
100
. - DefaultUid
-
- Type: int
The default POSIX user ID (UID). If not specified, defaults to
1000
. - MountPath
-
- Type: string
The path within the image to mount the user's EFS home directory. The directory should be empty. If not specified, defaults to /home/sagemaker-user.
FileSystemDataSource
Description
Specifies a file system data source for a channel.
Members
- DirectoryPath
-
- Required: Yes
- Type: string
The full path to the directory to associate with the channel.
- FileSystemAccessMode
-
- Required: Yes
- Type: string
The access mode of the mount of the directory associated with the channel. A directory can be mounted either in
ro
(read-only) orrw
(read-write) mode. - FileSystemId
-
- Required: Yes
- Type: string
The file system id.
- FileSystemType
-
- Required: Yes
- Type: string
The file system type.
Filter
Description
A conditional statement for a search expression that includes a resource property, a Boolean operator, and a value. Resources that match the statement are returned in the results from the Search API.
If you specify a Value
, but not an Operator
, SageMaker uses the equals operator.
In search, there are several property types:
- Metrics
-
To define a metric filter, enter a value using the form
"Metrics.<name>"
, where<name>
is a metric name. For example, the following filter searches for training jobs with an"accuracy"
metric greater than"0.9"
:{
"Name": "Metrics.accuracy",
"Operator": "GreaterThan",
"Value": "0.9"
}
- HyperParameters
-
To define a hyperparameter filter, enter a value with the form
"HyperParameters.<name>"
. Decimal hyperparameter values are treated as a decimal in a comparison if the specifiedValue
is also a decimal value. If the specifiedValue
is an integer, the decimal hyperparameter values are treated as integers. For example, the following filter is satisfied by training jobs with a"learning_rate"
hyperparameter that is less than"0.5"
:{
"Name": "HyperParameters.learning_rate",
"Operator": "LessThan",
"Value": "0.5"
}
- Tags
-
To define a tag filter, enter a value with the form
Tags.<key>
.
Members
- Name
-
- Required: Yes
- Type: string
A resource property name. For example,
TrainingJobName
. For valid property names, see SearchRecord. You must specify a valid property for the resource. - Operator
-
- Type: string
A Boolean binary operator that is used to evaluate the filter. The operator field contains one of the following values:
- Equals
-
The value of
Name
equalsValue
. - NotEquals
-
The value of
Name
doesn't equalValue
. - Exists
-
The
Name
property exists. - NotExists
-
The
Name
property does not exist. - GreaterThan
-
The value of
Name
is greater thanValue
. Not supported for text properties. - GreaterThanOrEqualTo
-
The value of
Name
is greater than or equal toValue
. Not supported for text properties. - LessThan
-
The value of
Name
is less thanValue
. Not supported for text properties. - LessThanOrEqualTo
-
The value of
Name
is less than or equal toValue
. Not supported for text properties. - In
-
The value of
Name
is one of the comma delimited strings inValue
. Only supported for text properties. - Contains
-
The value of
Name
contains the stringValue
. Only supported for text properties.A
SearchExpression
can include theContains
operator multiple times when the value ofName
is one of the following:-
Experiment.DisplayName
-
Experiment.ExperimentName
-
Experiment.Tags
-
Trial.DisplayName
-
Trial.TrialName
-
Trial.Tags
-
TrialComponent.DisplayName
-
TrialComponent.TrialComponentName
-
TrialComponent.Tags
-
TrialComponent.InputArtifacts
-
TrialComponent.OutputArtifacts
A
SearchExpression
can include only oneContains
operator for all other values ofName
. In these cases, if you include multipleContains
operators in theSearchExpression
, the result is the following error message: "'CONTAINS' operator usage limit of 1 exceeded.
" -
- Value
-
- Type: string
A value used with
Name
andOperator
to determine which resources satisfy the filter's condition. For numerical properties,Value
must be an integer or floating-point decimal. For timestamp properties,Value
must be an ISO 8601 date-time string of the following format:YYYY-mm-dd'T'HH:MM:SS
.
FinalAutoMLJobObjectiveMetric
Description
The best candidate result from an AutoML training job.
Members
- MetricName
-
- Required: Yes
- Type: string
The name of the metric with the best result. For a description of the possible objective metrics, see AutoMLJobObjective$MetricName.
- StandardMetricName
-
- Type: string
The name of the standard metric. For a description of the standard metrics, see Autopilot candidate metrics.
- Type
-
- Type: string
The type of metric with the best result.
- Value
-
- Required: Yes
- Type: float
The value of the metric with the best result.
FinalHyperParameterTuningJobObjectiveMetric
Description
Shows the latest objective metric emitted by a training job that was launched by a hyperparameter tuning job. You define the objective metric in the HyperParameterTuningJobObjective
parameter of HyperParameterTuningJobConfig.
Members
- MetricName
-
- Required: Yes
- Type: string
The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm. See the metrics for XGBoost as an example. You can also use a custom algorithm for training and define your own metrics. For more information, see Define metrics and environment variables.
- Type
-
- Type: string
Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
- Value
-
- Required: Yes
- Type: float
The value of the objective metric.
FlowDefinitionOutputConfig
Description
Contains information about where human output will be stored.
Members
- KmsKeyId
-
- Type: string
The Amazon Key Management Service (KMS) key ID for server-side encryption.
- S3OutputPath
-
- Required: Yes
- Type: string
The Amazon S3 path where the object containing human output will be made available.
To learn more about the format of Amazon A2I output data, see Amazon A2I Output Data.
FlowDefinitionSummary
Description
Contains summary information about the flow definition.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp when SageMaker created the flow definition.
- FailureReason
-
- Type: string
The reason why the flow definition creation failed. A failure reason is returned only when the flow definition status is
Failed
. - FlowDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the flow definition.
- FlowDefinitionName
-
- Required: Yes
- Type: string
The name of the flow definition.
- FlowDefinitionStatus
-
- Required: Yes
- Type: string
The status of the flow definition. Valid values:
GenerativeAiSettings
Description
The generative AI settings for the SageMaker Canvas application.
Configure these settings for Canvas users starting chats with generative AI foundation models. For more information, see Use generative AI with foundation models.
Members
- AmazonBedrockRoleArn
-
- Type: string
The ARN of an Amazon Web Services IAM role that allows fine-tuning of large language models (LLMs) in Amazon Bedrock. The IAM role should have Amazon S3 read and write permissions, as well as a trust relationship that establishes
bedrock.amazonaws.com
as a service principal.
GitConfig
Description
Specifies configuration details for a Git repository in your Amazon Web Services account.
Members
- Branch
-
- Type: string
The default branch for the Git repository.
- RepositoryUrl
-
- Required: Yes
- Type: string
The URL where the Git repository is located.
- SecretArn
-
- Type: string
The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of
AWSCURRENT
and must be in the following format:{"username": UserName, "password": Password}
GitConfigForUpdate
Description
Specifies configuration details for a Git repository when the repository is updated.
Members
- SecretArn
-
- Type: string
The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of
AWSCURRENT
and must be in the following format:{"username": UserName, "password": Password}
HolidayConfigAttributes
Description
Stores the holiday featurization attributes applicable to each item of time-series datasets during the training of a forecasting model. This allows the model to identify patterns associated with specific holidays.
Members
- CountryCode
-
- Type: string
The country code for the holiday calendar.
For the list of public holiday calendars supported by AutoML job V2, see Country Codes. Use the country code corresponding to the country of your choice.
HubContentDependency
Description
Any dependencies related to hub content, such as scripts, model artifacts, datasets, or notebooks.
Members
- DependencyCopyPath
-
- Type: string
The hub content dependency copy path.
- DependencyOriginPath
-
- Type: string
The hub content dependency origin path.
HubContentInfo
Description
Information about hub content.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the hub content was created.
- DocumentSchemaVersion
-
- Required: Yes
- Type: string
The version of the hub content document schema.
- HubContentArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the hub content.
- HubContentDescription
-
- Type: string
A description of the hub content.
- HubContentDisplayName
-
- Type: string
The display name of the hub content.
- HubContentName
-
- Required: Yes
- Type: string
The name of the hub content.
- HubContentSearchKeywords
-
- Type: Array of strings
The searchable keywords for the hub content.
- HubContentStatus
-
- Required: Yes
- Type: string
The status of the hub content.
- HubContentType
-
- Required: Yes
- Type: string
The type of hub content.
- HubContentVersion
-
- Required: Yes
- Type: string
The version of the hub content.
- OriginalCreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time when the hub content was originally created, before any updates or revisions.
- SageMakerPublicHubContentArn
-
- Type: string
The ARN of the public hub content.
- SupportStatus
-
- Type: string
The support status of the hub content.
HubInfo
Description
Information about a hub.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the hub was created.
- HubArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the hub.
- HubDescription
-
- Type: string
A description of the hub.
- HubDisplayName
-
- Type: string
The display name of the hub.
- HubName
-
- Required: Yes
- Type: string
The name of the hub.
- HubSearchKeywords
-
- Type: Array of strings
The searchable keywords for the hub.
- HubStatus
-
- Required: Yes
- Type: string
The status of the hub.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the hub was last modified.
HubS3StorageConfig
Description
The Amazon S3 storage configuration of a hub.
Members
- S3OutputPath
-
- Type: string
The Amazon S3 bucket prefix for hosting hub content.
HumanLoopActivationConditionsConfig
Description
Defines under what conditions SageMaker creates a human loop. Used within CreateFlowDefinition. See HumanLoopActivationConditionsConfig for the required format of activation conditions.
Members
- HumanLoopActivationConditions
-
- Required: Yes
- Type: string (string|number|array|map or anything parsable by json_encode)
JSON expressing use-case specific conditions declaratively. If any condition is matched, atomic tasks are created against the configured work team. The set of conditions is different for Rekognition and Textract. For more information about how to structure the JSON, see JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI in the Amazon SageMaker Developer Guide.
HumanLoopActivationConfig
Description
Provides information about how and under what conditions SageMaker creates a human loop. If HumanLoopActivationConfig
is not given, then all requests go to humans.
Members
- HumanLoopActivationConditionsConfig
-
- Required: Yes
- Type: HumanLoopActivationConditionsConfig structure
Container structure for defining under what conditions SageMaker creates a human loop.
HumanLoopConfig
Description
Describes the work to be performed by human workers.
Members
- HumanTaskUiArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the human task user interface.
You can use standard HTML and Crowd HTML Elements to create a custom worker task template. You use this template to create a human task UI.
To learn how to create a custom HTML template, see Create Custom Worker Task Template.
To learn how to create a human task UI, which is a worker task template that can be used in a flow definition, see Create and Delete a Worker Task Templates.
- PublicWorkforceTaskPrice
-
- Type: PublicWorkforceTaskPrice structure
Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
Use one of the following prices for bounding box tasks. Prices are in US dollars and should be based on the complexity of the task; the longer it takes in your initial testing, the more you should offer.
-
0.036
-
0.048
-
0.060
-
0.072
-
0.120
-
0.240
-
0.360
-
0.480
-
0.600
-
0.720
-
0.840
-
0.960
-
1.080
-
1.200
Use one of the following prices for image classification, text classification, and custom tasks. Prices are in US dollars.
-
0.012
-
0.024
-
0.036
-
0.048
-
0.060
-
0.072
-
0.120
-
0.240
-
0.360
-
0.480
-
0.600
-
0.720
-
0.840
-
0.960
-
1.080
-
1.200
Use one of the following prices for semantic segmentation tasks. Prices are in US dollars.
-
0.840
-
0.960
-
1.080
-
1.200
Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI review tasks. Prices are in US dollars.
-
2.400
-
2.280
-
2.160
-
2.040
-
1.920
-
1.800
-
1.680
-
1.560
-
1.440
-
1.320
-
1.200
-
1.080
-
0.960
-
0.840
-
0.720
-
0.600
-
0.480
-
0.360
-
0.240
-
0.120
-
0.072
-
0.060
-
0.048
-
0.036
-
0.024
-
0.012
Use one of the following prices for Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are in US dollars.
-
1.200
-
1.080
-
0.960
-
0.840
-
0.720
-
0.600
-
0.480
-
0.360
-
0.240
-
0.120
-
0.072
-
0.060
-
0.048
-
0.036
-
0.024
-
0.012
Use one of the following prices for Amazon Augmented AI custom human review tasks. Prices are in US dollars.
-
1.200
-
1.080
-
0.960
-
0.840
-
0.720
-
0.600
-
0.480
-
0.360
-
0.240
-
0.120
-
0.072
-
0.060
-
0.048
-
0.036
-
0.024
-
0.012
- TaskAvailabilityLifetimeInSeconds
-
- Type: int
The length of time that a task remains available for review by human workers.
- TaskCount
-
- Required: Yes
- Type: int
The number of distinct workers who will perform the same task on each object. For example, if
TaskCount
is set to3
for an image classification labeling job, three workers will classify each input image. IncreasingTaskCount
can improve label accuracy. - TaskDescription
-
- Required: Yes
- Type: string
A description for the human worker task.
- TaskKeywords
-
- Type: Array of strings
Keywords used to describe the task so that workers can discover the task.
- TaskTimeLimitInSeconds
-
- Type: int
The amount of time that a worker has to complete a task. The default value is 3,600 seconds (1 hour).
- TaskTitle
-
- Required: Yes
- Type: string
A title for the human worker task.
- WorkteamArn
-
- Required: Yes
- Type: string
Amazon Resource Name (ARN) of a team of workers. To learn more about the types of workforces and work teams you can create and use with Amazon A2I, see Create and Manage Workforces.
HumanLoopRequestSource
Description
Container for configuring the source of human task requests.
Members
- AwsManagedHumanLoopRequestSource
-
- Required: Yes
- Type: string
Specifies whether Amazon Rekognition or Amazon Textract are used as the integration source. The default field settings and JSON parsing rules are different based on the integration source. Valid values:
HumanTaskConfig
Description
Information required for human workers to complete a labeling task.
Members
- AnnotationConsolidationConfig
-
- Required: Yes
- Type: AnnotationConsolidationConfig structure
Configures how labels are consolidated across human workers.
- MaxConcurrentTaskCount
-
- Type: int
Defines the maximum number of data objects that can be labeled by human workers at the same time. Also referred to as batch size. Each object may have more than one worker at one time. The default value is 1000 objects. To increase the maximum value to 5000 objects, contact Amazon Web Services Support.
- NumberOfHumanWorkersPerDataObject
-
- Required: Yes
- Type: int
The number of human workers that will label an object.
- PreHumanTaskLambdaArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of a Lambda function that is run before a data object is sent to a human worker. Use this function to provide input to a custom labeling job.
For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for
PreHumanTaskLambdaArn
. For custom labeling workflows, see Pre-annotation Lambda.Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking
3D Point Cloud Modalities
Use the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See 3D Point Cloud Task types to learn more.
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBox
Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox
Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation
Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking
3D point cloud object detection adjustment - Adjust 3D cuboids in a point cloud frame.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection
3D point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of point cloud frames.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
3D point cloud semantic segmentation adjustment - Adjust semantic segmentation masks in a 3D point cloud.
-
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation
-
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation
- PublicWorkforceTaskPrice
-
- Type: PublicWorkforceTaskPrice structure
The price that you pay for each task performed by an Amazon Mechanical Turk worker.
- TaskAvailabilityLifetimeInSeconds
-
- Type: int
The length of time that a task remains available for labeling by human workers. The default and maximum values for this parameter depend on the type of workforce you use.
-
If you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours (43,200 seconds). The default is 6 hours (21,600 seconds).
-
If you choose a private or vendor workforce, the default value is 30 days (2592,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
- TaskDescription
-
- Required: Yes
- Type: string
A description of the task for your human workers.
- TaskKeywords
-
- Type: Array of strings
Keywords used to describe the task so that workers on Amazon Mechanical Turk can discover the task.
- TaskTimeLimitInSeconds
-
- Required: Yes
- Type: int
The amount of time that a worker has to complete a task.
If you create a custom labeling job, the maximum value for this parameter is 8 hours (28,800 seconds).
If you create a labeling job using a built-in task type the maximum for this parameter depends on the task type you use:
-
For image and text labeling jobs, the maximum is 8 hours (28,800 seconds).
-
For 3D point cloud and video frame labeling jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
- TaskTitle
-
- Required: Yes
- Type: string
A title for the task for your human workers.
- UiConfig
-
- Required: Yes
- Type: UiConfig structure
Information about the user interface that workers use to complete the labeling task.
- WorkteamArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the work team assigned to complete the tasks.
HumanTaskUiSummary
Description
Container for human task user interface information.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp when SageMaker created the human task user interface.
- HumanTaskUiArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the human task user interface.
- HumanTaskUiName
-
- Required: Yes
- Type: string
The name of the human task user interface.
HyperParameterAlgorithmSpecification
Description
Specifies which training algorithm to use for training jobs that a hyperparameter tuning job launches and the metrics to monitor.
Members
- AlgorithmName
-
- Type: string
The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for
TrainingImage
. - MetricDefinitions
-
- Type: Array of MetricDefinition structures
An array of MetricDefinition objects that specify the metrics that the algorithm emits.
- TrainingImage
-
- Type: string
The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see Algorithms Provided by Amazon SageMaker: Common Parameters. SageMaker supports both
registry/repository[:tag]
andregistry/repository[@digest]
image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker. - TrainingInputMode
-
- Required: Yes
- Type: string
The training input mode that the algorithm supports. For more information about input modes, see Algorithms.
Pipe mode
If an algorithm supports
Pipe
mode, Amazon SageMaker streams data directly from Amazon S3 to the container.File mode
If an algorithm supports
File
mode, SageMaker downloads the training data from S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume for the training container.You must provision the ML storage volume with sufficient capacity to accommodate the data downloaded from S3. In addition to the training data, the ML storage volume also stores the output model. The algorithm container uses the ML storage volume to also store intermediate information, if any.
For distributed algorithms, training data is distributed uniformly. Your training duration is predictable if the input data objects sizes are approximately the same. SageMaker does not split the files any further for model training. If the object sizes are skewed, training won't be optimal as the data distribution is also skewed when one host in a training cluster is overloaded, thus becoming a bottleneck in training.
FastFile mode
If an algorithm supports
FastFile
mode, SageMaker streams data directly from S3 to the container with no code changes, and provides file system access to the data. Users can author their training script to interact with these files as if they were stored on disk.FastFile
mode works best when the data is read sequentially. Augmented manifest files aren't supported. The startup time is lower when there are fewer files in the S3 bucket provided.
HyperParameterSpecification
Description
Defines a hyperparameter to be used by an algorithm.
Members
- DefaultValue
-
- Type: string
The default value for this hyperparameter. If a default value is specified, a hyperparameter cannot be required.
- Description
-
- Type: string
A brief description of the hyperparameter.
- IsRequired
-
- Type: boolean
Indicates whether this hyperparameter is required.
- IsTunable
-
- Type: boolean
Indicates whether this hyperparameter is tunable in a hyperparameter tuning job.
- Name
-
- Required: Yes
- Type: string
The name of this hyperparameter. The name must be unique.
- Range
-
- Type: ParameterRange structure
The allowed range for this hyperparameter.
- Type
-
- Required: Yes
- Type: string
The type of this hyperparameter. The valid types are
Integer
,Continuous
,Categorical
, andFreeText
.
HyperParameterTrainingJobDefinition
Description
Defines the training jobs launched by a hyperparameter tuning job.
Members
- AlgorithmSpecification
-
- Required: Yes
- Type: HyperParameterAlgorithmSpecification structure
The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.
- CheckpointConfig
-
- Type: CheckpointConfig structure
Contains information about the output location for managed spot training checkpoint data.
- DefinitionName
-
- Type: string
The job definition name.
- EnableInterContainerTrafficEncryption
-
- Type: boolean
To encrypt all communications between ML compute instances in distributed training, choose
True
. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training. - EnableManagedSpotTraining
-
- Type: boolean
A Boolean indicating whether managed spot training is enabled (
True
) or not (False
). - EnableNetworkIsolation
-
- Type: boolean
Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
- Environment
-
- Type: Associative array of custom strings keys (HyperParameterTrainingJobEnvironmentKey) to strings
An environment variable that you can pass into the SageMaker CreateTrainingJob API. You can use an existing environment variable from the training container or use your own. See Define metrics and variables for more information.
The maximum number of items specified for
Map Entries
refers to the maximum number of environment variables for eachTrainingJobDefinition
and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of environment variables for all the training job definitions can't exceed the maximum number specified. - HyperParameterRanges
-
- Type: ParameterRanges structure
Specifies ranges of integer, continuous, and categorical hyperparameters that a hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs with hyperparameter values within these ranges to find the combination of values that result in the training job with the best performance as measured by the objective metric of the hyperparameter tuning job.
The maximum number of items specified for
Array Members
refers to the maximum number of hyperparameters for each range and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of hyperparameters for all the ranges can't exceed the maximum number specified. - HyperParameterTuningResourceConfig
-
- Type: HyperParameterTuningResourceConfig structure
The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose
File
forTrainingInputMode
in theAlgorithmSpecification
parameter to additionally store training data in the storage volume (optional). - InputDataConfig
-
- Type: Array of Channel structures
An array of Channel objects that specify the input for the training jobs that the tuning job launches.
- OutputDataConfig
-
- Required: Yes
- Type: OutputDataConfig structure
Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
- ResourceConfig
-
- Type: ResourceConfig structure
The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose
File
as theTrainingInputMode
in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.If you want to use hyperparameter optimization with instance type flexibility, use
HyperParameterTuningResourceConfig
instead. - RetryStrategy
-
- Type: RetryStrategy structure
The number of times to retry the job when the job fails due to an
InternalServerError
. - RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
- StaticHyperParameters
-
- Type: Associative array of custom strings keys (HyperParameterKey) to strings
Specifies the values of hyperparameters that do not change for the tuning job.
- StoppingCondition
-
- Required: Yes
- Type: StoppingCondition structure
Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
- TuningObjective
-
- Type: HyperParameterTuningJobObjective structure
Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning uses the value of this metric to evaluate the training jobs it launches, and returns the training job that results in either the highest or lowest value for this metric, depending on the value you specify for the
Type
parameter. If you want to define a custom objective metric, see Define metrics and environment variables. - VpcConfig
-
- Type: VpcConfig structure
The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
HyperParameterTrainingJobSummary
Description
The container for the summary information about a training job.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the training job was created.
- FailureReason
-
- Type: string
The reason that the training job failed.
- FinalHyperParameterTuningJobObjectiveMetric
-
- Type: FinalHyperParameterTuningJobObjectiveMetric structure
The FinalHyperParameterTuningJobObjectiveMetric object that specifies the value of the objective metric of the tuning job that launched this training job.
- ObjectiveStatus
-
- Type: string
The status of the objective metric for the training job:
-
Succeeded: The final objective metric for the training job was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
-
Pending: The training job is in progress and evaluation of its final objective metric is pending.
-
Failed: The final objective metric for the training job was not evaluated, and was not used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
- TrainingEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Specifies the time when the training job ends on training instances. You are billed for the time interval between the value of
TrainingStartTime
and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure. - TrainingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the training job.
- TrainingJobDefinitionName
-
- Type: string
The training job definition name.
- TrainingJobName
-
- Required: Yes
- Type: string
The name of the training job.
- TrainingJobStatus
-
- Required: Yes
- Type: string
The status of the training job.
- TrainingStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the training job started.
- TunedHyperParameters
-
- Required: Yes
- Type: Associative array of custom strings keys (HyperParameterKey) to strings
A list of the hyperparameters for which you specified ranges to search.
- TuningJobName
-
- Type: string
The HyperParameter tuning job that launched the training job.
HyperParameterTuningInstanceConfig
Description
The configuration for hyperparameter tuning resources for use in training jobs launched by the tuning job. These resources include compute instances and storage volumes. Specify one or more compute instance configurations and allocation strategies to select resources (optional).
Members
- InstanceCount
-
- Required: Yes
- Type: int
The number of instances of the type specified by
InstanceType
. Choose an instance count larger than 1 for distributed training algorithms. See Step 2: Launch a SageMaker Distributed Training Job Using the SageMaker Python SDK for more information. - InstanceType
-
- Required: Yes
- Type: string
The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs) instance types: ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance type descriptions.
- VolumeSizeInGB
-
- Required: Yes
- Type: int
The volume size in GB of the data to be processed for hyperparameter optimization (optional).
HyperParameterTuningJobCompletionDetails
Description
A structure that contains runtime information about both current and completed hyperparameter tuning jobs.
Members
- ConvergenceDetectedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time in timestamp format that AMT detected model convergence, as defined by a lack of significant improvement over time based on criteria developed over a wide range of diverse benchmarking tests.
- NumberOfTrainingJobsObjectiveNotImproving
-
- Type: int
The number of training jobs launched by a tuning job that are not improving (1% or less) as measured by model performance evaluated against an objective function.
HyperParameterTuningJobConfig
Description
Configures a hyperparameter tuning job.
Members
- HyperParameterTuningJobObjective
-
- Type: HyperParameterTuningJobObjective structure
The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.
- ParameterRanges
-
- Type: ParameterRanges structure
The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.
- RandomSeed
-
- Type: int
A value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.
- ResourceLimits
-
- Required: Yes
- Type: ResourceLimits structure
The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.
- Strategy
-
- Required: Yes
- Type: string
Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see How Hyperparameter Tuning Works.
- StrategyConfig
-
- Type: HyperParameterTuningJobStrategyConfig structure
The configuration for the
Hyperband
optimization strategy. This parameter should be provided only ifHyperband
is selected as the strategy forHyperParameterTuningJobConfig
. - TrainingJobEarlyStoppingType
-
- Type: string
Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the
Hyperband
strategy has its own advanced internal early stopping mechanism,TrainingJobEarlyStoppingType
must beOFF
to useHyperband
. This parameter can take on one of the following values (the default value isOFF
):- OFF
-
Training jobs launched by the hyperparameter tuning job do not use early stopping.
- AUTO
-
SageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see Stop Training Jobs Early.
- TuningJobCompletionCriteria
-
- Type: TuningJobCompletionCriteria structure
The tuning job's completion criteria.
HyperParameterTuningJobConsumedResources
Description
The total resources consumed by your hyperparameter tuning job.
Members
- RuntimeInSeconds
-
- Type: int
The wall clock runtime in seconds used by your hyperparameter tuning job.
HyperParameterTuningJobObjective
Description
Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning uses the value of this metric to evaluate the training jobs it launches, and returns the training job that results in either the highest or lowest value for this metric, depending on the value you specify for the Type
parameter. If you want to define a custom objective metric, see Define metrics and environment variables.
Members
- MetricName
-
- Required: Yes
- Type: string
The name of the metric to use for the objective metric.
- Type
-
- Required: Yes
- Type: string
Whether to minimize or maximize the objective metric.
HyperParameterTuningJobSearchEntity
Description
An entity returned by the SearchRecord API containing the properties of a hyperparameter tuning job.
Members
- BestTrainingJob
-
- Type: HyperParameterTrainingJobSummary structure
The container for the summary information about a training job.
- ConsumedResources
-
- Type: HyperParameterTuningJobConsumedResources structure
The total amount of resources consumed by a hyperparameter tuning job.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that a hyperparameter tuning job was created.
- FailureReason
-
- Type: string
The error that was created when a hyperparameter tuning job failed.
- HyperParameterTuningEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that a hyperparameter tuning job ended.
- HyperParameterTuningJobArn
-
- Type: string
The Amazon Resource Name (ARN) of a hyperparameter tuning job.
- HyperParameterTuningJobConfig
-
- Type: HyperParameterTuningJobConfig structure
Configures a hyperparameter tuning job.
- HyperParameterTuningJobName
-
- Type: string
The name of a hyperparameter tuning job.
- HyperParameterTuningJobStatus
-
- Type: string
The status of a hyperparameter tuning job.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that a hyperparameter tuning job was last modified.
- ObjectiveStatusCounters
-
- Type: ObjectiveStatusCounters structure
Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.
- OverallBestTrainingJob
-
- Type: HyperParameterTrainingJobSummary structure
The container for the summary information about a training job.
- Tags
-
- Type: Array of Tag structures
The tags associated with a hyperparameter tuning job. For more information see Tagging Amazon Web Services resources.
- TrainingJobDefinition
-
- Type: HyperParameterTrainingJobDefinition structure
Defines the training jobs launched by a hyperparameter tuning job.
- TrainingJobDefinitions
-
- Type: Array of HyperParameterTrainingJobDefinition structures
The job definitions included in a hyperparameter tuning job.
- TrainingJobStatusCounters
-
- Type: TrainingJobStatusCounters structure
The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.
- TuningJobCompletionDetails
-
- Type: HyperParameterTuningJobCompletionDetails structure
Information about either a current or completed hyperparameter tuning job.
- WarmStartConfig
-
- Type: HyperParameterTuningJobWarmStartConfig structure
Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter 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, and the training job that performs the best 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.
HyperParameterTuningJobStrategyConfig
Description
The configuration for a training job launched by a hyperparameter tuning job. Choose Bayesian
for Bayesian optimization, and Random
for random search optimization. For more advanced use cases, use Hyperband
, which evaluates objective metrics for training jobs after every epoch. For more information about strategies, see How Hyperparameter Tuning Works.
Members
- HyperbandStrategyConfig
-
- Type: HyperbandStrategyConfig structure
The configuration for the object that specifies the
Hyperband
strategy. This parameter is only supported for theHyperband
selection forStrategy
within theHyperParameterTuningJobConfig
API.
HyperParameterTuningJobSummary
Description
Provides summary information about a hyperparameter tuning job.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the tuning job was created.
- HyperParameterTuningEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the tuning job ended.
- HyperParameterTuningJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the tuning job.
- HyperParameterTuningJobName
-
- Required: Yes
- Type: string
The name of the tuning job.
- HyperParameterTuningJobStatus
-
- Required: Yes
- Type: string
The status of the tuning job.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the tuning job was modified.
- ObjectiveStatusCounters
-
- Required: Yes
- Type: ObjectiveStatusCounters structure
The ObjectiveStatusCounters object that specifies the numbers of training jobs, categorized by objective metric status, that this tuning job launched.
- ResourceLimits
-
- Type: ResourceLimits structure
The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs allowed for this tuning job.
- Strategy
-
- Required: Yes
- Type: string
Specifies the search strategy hyperparameter tuning uses to choose which hyperparameters to evaluate at each iteration.
- TrainingJobStatusCounters
-
- Required: Yes
- Type: TrainingJobStatusCounters structure
The TrainingJobStatusCounters object that specifies the numbers of training jobs, categorized by status, that this tuning job launched.
HyperParameterTuningJobWarmStartConfig
Description
Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter 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, and the training job that performs the best 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.
Members
- ParentHyperParameterTuningJobs
-
- Required: Yes
- Type: Array of ParentHyperParameterTuningJob structures
An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.
Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.
- WarmStartType
-
- Required: Yes
- Type: string
Specifies one of the following:
- IDENTICAL_DATA_AND_ALGORITHM
-
The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
- TRANSFER_LEARNING
-
The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
HyperParameterTuningResourceConfig
Description
The configuration of resources, including compute instances and storage volumes for use in training jobs launched by hyperparameter tuning jobs. HyperParameterTuningResourceConfig
is similar to ResourceConfig
, but has the additional InstanceConfigs
and AllocationStrategy
fields to allow for flexible instance management. Specify one or more instance types, count, and the allocation strategy for instance selection.
HyperParameterTuningResourceConfig
supports the capabilities of ResourceConfig
with the exception of KeepAlivePeriodInSeconds
. Hyperparameter tuning jobs use warm pools by default, which reuse clusters between training jobs.
Members
- AllocationStrategy
-
- Type: string
The strategy that determines the order of preference for resources specified in
InstanceConfigs
used in hyperparameter optimization. - InstanceConfigs
-
- Type: Array of HyperParameterTuningInstanceConfig structures
A list containing the configuration(s) for one or more resources for processing hyperparameter jobs. These resources include compute instances and storage volumes to use in model training jobs launched by hyperparameter tuning jobs. The
AllocationStrategy
controls the order in which multiple configurations provided inInstanceConfigs
are used.If you only want to use a single instance configuration inside the
HyperParameterTuningResourceConfig
API, do not provide a value forInstanceConfigs
. Instead, useInstanceType
,VolumeSizeInGB
andInstanceCount
. If you useInstanceConfigs
, do not provide values forInstanceType
,VolumeSizeInGB
orInstanceCount
. - InstanceCount
-
- Type: int
The number of compute instances of type
InstanceType
to use. For distributed training, select a value greater than 1. - InstanceType
-
- Type: string
The instance type used to run hyperparameter optimization tuning jobs. See descriptions of instance types for more information.
- VolumeKmsKeyId
-
- Type: string
A key used by Amazon Web Services Key Management Service to encrypt data on the storage volume attached to the compute instances used to run the training job. You can use either of the following formats to specify a key.
KMS Key ID:
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS key:
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
Some instances use local storage, which use a hardware module to encrypt storage volumes. If you choose one of these instance types, you cannot request a
VolumeKmsKeyId
. For a list of instance types that use local storage, see instance store volumes. For more information about Amazon Web Services Key Management Service, see KMS encryption for more information. - VolumeSizeInGB
-
- Type: int
The volume size in GB for the storage volume to be used in processing hyperparameter optimization jobs (optional). These volumes store model artifacts, incremental states and optionally, scratch space for training algorithms. Do not provide a value for this parameter if a value for
InstanceConfigs
is also specified.Some instance types have a fixed total local storage size. If you select one of these instances for training,
VolumeSizeInGB
cannot be greater than this total size. For a list of instance types with local instance storage and their sizes, see instance store volumes.SageMaker supports only the General Purpose SSD (gp2) storage volume type.
HyperbandStrategyConfig
Description
The configuration for Hyperband
, a multi-fidelity based hyperparameter tuning strategy. Hyperband
uses the final and intermediate results of a training job to dynamically allocate resources to utilized hyperparameter configurations while automatically stopping under-performing configurations. This parameter should be provided only if Hyperband
is selected as the StrategyConfig
under the HyperParameterTuningJobConfig
API.
Members
- MaxResource
-
- Type: int
The maximum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. Once a job reaches the
MaxResource
value, it is stopped. If a value forMaxResource
is not provided, andHyperband
is selected as the hyperparameter tuning strategy,HyperbandTraining
attempts to inferMaxResource
from the following keys (if present) in StaticsHyperParameters:-
epochs
-
numepochs
-
n-epochs
-
n_epochs
-
num_epochs
If
HyperbandStrategyConfig
is unable to infer a value forMaxResource
, it generates a validation error. The maximum value is 20,000 epochs. All metrics that correspond to an objective metric are used to derive early stopping decisions. For distributed training jobs, ensure that duplicate metrics are not printed in the logs across the individual nodes in a training job. If multiple nodes are publishing duplicate or incorrect metrics, training jobs may make an incorrect stopping decision and stop the job prematurely. - MinResource
-
- Type: int
The minimum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. If the value for
MinResource
has not been reached, the training job is not stopped byHyperband
.
IamIdentity
Description
The IAM Identity details associated with the user. These details are associated with model package groups, model packages and project entities only.
Members
- Arn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM identity.
- PrincipalId
-
- Type: string
The ID of the principal that assumes the IAM identity.
- SourceIdentity
-
- Type: string
The person or application which assumes the IAM identity.
IamPolicyConstraints
Description
Use this parameter to specify a supported global condition key that is added to the IAM policy.
Members
- SourceIp
-
- Type: string
When
SourceIp
isEnabled
the worker's IP address when a task is rendered in the worker portal is added to the IAM policy as aCondition
used to generate the Amazon S3 presigned URL. This IP address is checked by Amazon S3 and must match in order for the Amazon S3 resource to be rendered in the worker portal. - VpcSourceIp
-
- Type: string
When
VpcSourceIp
isEnabled
the worker's IP address when a task is rendered in private worker portal inside the VPC is added to the IAM policy as aCondition
used to generate the Amazon S3 presigned URL. To render the task successfully Amazon S3 checks that the presigned URL is being accessed over an Amazon S3 VPC Endpoint, and that the worker's IP address matches the IP address in the IAM policy. To learn more about configuring private worker portal, see Use Amazon VPC mode from a private worker portal.
IdentityProviderOAuthSetting
Description
The Amazon SageMaker Canvas application setting where you configure OAuth for connecting to an external data source, such as Snowflake.
Members
- DataSourceName
-
- Type: string
The name of the data source that you're connecting to. Canvas currently supports OAuth for Snowflake and Salesforce Data Cloud.
- SecretArn
-
- Type: string
The ARN of an Amazon Web Services Secrets Manager secret that stores the credentials from your identity provider, such as the client ID and secret, authorization URL, and token URL.
- Status
-
- Type: string
Describes whether OAuth for a data source is enabled or disabled in the Canvas application.
Image
Description
A SageMaker image. A SageMaker image represents a set of container images that are derived from a common base container image. Each of these container images is represented by a SageMaker ImageVersion
.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the image was created.
- Description
-
- Type: string
The description of the image.
- DisplayName
-
- Type: string
The name of the image as displayed.
- FailureReason
-
- Type: string
When a create, update, or delete operation fails, the reason for the failure.
- ImageArn
-
- Required: Yes
- Type: string
The ARN of the image.
- ImageName
-
- Required: Yes
- Type: string
The name of the image.
- ImageStatus
-
- Required: Yes
- Type: string
The status of the image.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the image was last modified.
ImageClassificationJobConfig
Description
The collection of settings used by an AutoML job V2 for the image classification problem type.
Members
- CompletionCriteria
-
- Type: AutoMLJobCompletionCriteria structure
How long a job is allowed to run, or how many candidates a job is allowed to generate.
ImageConfig
Description
Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).
Members
- RepositoryAccessMode
-
- Required: Yes
- Type: string
Set this to one of the following values:
-
Platform
- The model image is hosted in Amazon ECR. -
Vpc
- The model image is hosted in a private Docker registry in your VPC.
- RepositoryAuthConfig
-
- Type: RepositoryAuthConfig structure
(Optional) Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified
Vpc
as the value for theRepositoryAccessMode
field, and the private Docker registry where the model image is hosted requires authentication.
ImageVersion
Description
A version of a SageMaker Image
. A version represents an existing container image.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the version was created.
- FailureReason
-
- Type: string
When a create or delete operation fails, the reason for the failure.
- ImageArn
-
- Required: Yes
- Type: string
The ARN of the image the version is based on.
- ImageVersionArn
-
- Required: Yes
- Type: string
The ARN of the version.
- ImageVersionStatus
-
- Required: Yes
- Type: string
The status of the version.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the version was last modified.
- Version
-
- Required: Yes
- Type: int
The version number.
InferenceComponentComputeResourceRequirements
Description
Defines the compute resources to allocate to run a model that you assign to an inference component. These resources include CPU cores, accelerators, and memory.
Members
- MaxMemoryRequiredInMb
-
- Type: int
The maximum MB of memory to allocate to run a model that you assign to an inference component.
- MinMemoryRequiredInMb
-
- Required: Yes
- Type: int
The minimum MB of memory to allocate to run a model that you assign to an inference component.
- NumberOfAcceleratorDevicesRequired
-
- Type: float
The number of accelerators to allocate to run a model that you assign to an inference component. Accelerators include GPUs and Amazon Web Services Inferentia.
- NumberOfCpuCoresRequired
-
- Type: float
The number of CPU cores to allocate to run a model that you assign to an inference component.
InferenceComponentContainerSpecification
Description
Defines a container that provides the runtime environment for a model that you deploy with an inference component.
Members
- ArtifactUrl
-
- Type: string
The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
- Environment
-
- Type: Associative array of custom strings keys (EnvironmentKey) to strings
The environment variables to set in the Docker container. Each key and value in the Environment string-to-string map can have length of up to 1024. We support up to 16 entries in the map.
- Image
-
- Type: string
The Amazon Elastic Container Registry (Amazon ECR) path where the Docker image for the model is stored.
InferenceComponentContainerSpecificationSummary
Description
Details about the resources that are deployed with this inference component.
Members
- ArtifactUrl
-
- Type: string
The Amazon S3 path where the model artifacts are stored.
- DeployedImage
-
- Type: DeployedImage structure
Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the
registry/repository[:tag]
form to specify the image path of the primary container when you created the model hosted in thisProductionVariant
, the path resolves to a path of the formregistry/repository[@digest]
. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide. - Environment
-
- Type: Associative array of custom strings keys (EnvironmentKey) to strings
The environment variables to set in the Docker container.
InferenceComponentRuntimeConfig
Description
Runtime settings for a model that is deployed with an inference component.
Members
- CopyCount
-
- Required: Yes
- Type: int
The number of runtime copies of the model container to deploy with the inference component. Each copy can serve inference requests.
InferenceComponentRuntimeConfigSummary
Description
Details about the runtime settings for the model that is deployed with the inference component.
Members
- CurrentCopyCount
-
- Type: int
The number of runtime copies of the model container that are currently deployed.
- DesiredCopyCount
-
- Type: int
The number of runtime copies of the model container that you requested to deploy with the inference component.
InferenceComponentSpecification
Description
Details about the resources to deploy with this inference component, including the model, container, and compute resources.
Members
- ComputeResourceRequirements
-
- Required: Yes
- Type: InferenceComponentComputeResourceRequirements structure
The compute resources allocated to run the model assigned to the inference component.
- Container
-
- Type: InferenceComponentContainerSpecification structure
Defines a container that provides the runtime environment for a model that you deploy with an inference component.
- ModelName
-
- Type: string
The name of an existing SageMaker model object in your account that you want to deploy with the inference component.
- StartupParameters
-
- Type: InferenceComponentStartupParameters structure
Settings that take effect while the model container starts up.
InferenceComponentSpecificationSummary
Description
Details about the resources that are deployed with this inference component.
Members
- ComputeResourceRequirements
-
- Type: InferenceComponentComputeResourceRequirements structure
The compute resources allocated to run the model assigned to the inference component.
- Container
-
- Type: InferenceComponentContainerSpecificationSummary structure
Details about the container that provides the runtime environment for the model that is deployed with the inference component.
- ModelName
-
- Type: string
The name of the SageMaker model object that is deployed with the inference component.
- StartupParameters
-
- Type: InferenceComponentStartupParameters structure
Settings that take effect while the model container starts up.
InferenceComponentStartupParameters
Description
Settings that take effect while the model container starts up.
Members
- ContainerStartupHealthCheckTimeoutInSeconds
-
- Type: int
The timeout value, in seconds, for your inference container to pass health check by Amazon S3 Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
- ModelDataDownloadTimeoutInSeconds
-
- Type: int
The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this inference component.
InferenceComponentSummary
Description
A summary of the properties of an inference component.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the inference component was created.
- EndpointArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the endpoint that hosts the inference component.
- EndpointName
-
- Required: Yes
- Type: string
The name of the endpoint that hosts the inference component.
- InferenceComponentArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the inference component.
- InferenceComponentName
-
- Required: Yes
- Type: string
The name of the inference component.
- InferenceComponentStatus
-
- Type: string
The status of the inference component.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the inference component was last updated.
- VariantName
-
- Required: Yes
- Type: string
The name of the production variant that hosts the inference component.
InferenceExecutionConfig
Description
Specifies details about how containers in a multi-container endpoint are run.
Members
- Mode
-
- Required: Yes
- Type: string
How containers in a multi-container are run. The following values are valid.
-
SERIAL
- Containers run as a serial pipeline. -
DIRECT
- Only the individual container that you specify is run.
InferenceExperimentDataStorageConfig
Description
The Amazon S3 location and configuration for storing inference request and response data.
Members
- ContentType
-
- Type: CaptureContentTypeHeader structure
Configuration specifying how to treat different headers. If no headers are specified Amazon SageMaker will by default base64 encode when capturing the data.
- Destination
-
- Required: Yes
- Type: string
The Amazon S3 bucket where the inference request and response data is stored.
- KmsKey
-
- Type: string
The Amazon Web Services Key Management Service key that Amazon SageMaker uses to encrypt captured data at rest using Amazon S3 server-side encryption.
InferenceExperimentSchedule
Description
The start and end times of an inference experiment.
The maximum duration that you can set for an inference experiment is 30 days.
Members
- EndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp at which the inference experiment ended or will end.
- StartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp at which the inference experiment started or will start.
InferenceExperimentSummary
Description
Lists a summary of properties of an inference experiment.
Members
- CompletionTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp at which the inference experiment was completed.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp at which the inference experiment was created.
- Description
-
- Type: string
The description of the inference experiment.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp when you last modified the inference experiment.
- Name
-
- Required: Yes
- Type: string
The name of the inference experiment.
- RoleArn
-
- Type: string
The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
- Schedule
-
- Type: InferenceExperimentSchedule structure
The duration for which the inference experiment ran or will run.
The maximum duration that you can set for an inference experiment is 30 days.
- Status
-
- Required: Yes
- Type: string
The status of the inference experiment.
- StatusReason
-
- Type: string
The error message for the inference experiment status result.
- Type
-
- Required: Yes
- Type: string
The type of the inference experiment.
InferenceHubAccessConfig
Description
Configuration information specifying which hub contents have accessible deployment options.
Members
- HubContentArn
-
- Required: Yes
- Type: string
The ARN of the hub content for which deployment access is allowed.
InferenceMetrics
Description
The metrics for an existing endpoint compared in an Inference Recommender job.
Members
- MaxInvocations
-
- Required: Yes
- Type: int
The expected maximum number of requests per minute for the instance.
- ModelLatency
-
- Required: Yes
- Type: int
The expected model latency at maximum invocations per minute for the instance.
InferenceRecommendation
Description
A list of recommendations made by Amazon SageMaker Inference Recommender.
Members
- EndpointConfiguration
-
- Required: Yes
- Type: EndpointOutputConfiguration structure
Defines the endpoint configuration parameters.
- InvocationEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the benchmark completed.
- InvocationStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the benchmark started.
- Metrics
-
- Type: RecommendationMetrics structure
The metrics used to decide what recommendation to make.
- ModelConfiguration
-
- Required: Yes
- Type: ModelConfiguration structure
Defines the model configuration.
- RecommendationId
-
- Type: string
The recommendation ID which uniquely identifies each recommendation.
InferenceRecommendationsJob
Description
A structure that contains a list of recommendation jobs.
Members
- CompletionTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the job completed.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the job was created.
- FailureReason
-
- Type: string
If the job fails, provides information why the job failed.
- JobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the recommendation job.
- JobDescription
-
- Required: Yes
- Type: string
The job description.
- JobName
-
- Required: Yes
- Type: string
The name of the job.
- JobType
-
- Required: Yes
- Type: string
The recommendation job type.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the job was last modified.
- ModelName
-
- Type: string
The name of the created model.
- ModelPackageVersionArn
-
- Type: string
The Amazon Resource Name (ARN) of a versioned model package.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
- SamplePayloadUrl
-
- Type: string
The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
- Status
-
- Required: Yes
- Type: string
The status of the job.
InferenceRecommendationsJobStep
Description
A returned array object for the Steps
response field in the ListInferenceRecommendationsJobSteps API command.
Members
- InferenceBenchmark
-
- Type: RecommendationJobInferenceBenchmark structure
The details for a specific benchmark.
- JobName
-
- Required: Yes
- Type: string
The name of the Inference Recommender job.
- Status
-
- Required: Yes
- Type: string
The current status of the benchmark.
- StepType
-
- Required: Yes
- Type: string
The type of the subtask.
BENCHMARK
: Evaluate the performance of your model on different instance types.
InferenceSpecification
Description
Defines how to perform inference generation after a training job is run.
Members
- Containers
-
- Required: Yes
- Type: Array of ModelPackageContainerDefinition structures
The Amazon ECR registry path of the Docker image that contains the inference code.
- SupportedContentTypes
-
- Type: Array of strings
The supported MIME types for the input data.
- SupportedRealtimeInferenceInstanceTypes
-
- Type: Array of strings
A list of the instance types that are used to generate inferences in real-time.
This parameter is required for unversioned models, and optional for versioned models.
- SupportedResponseMIMETypes
-
- Type: Array of strings
The supported MIME types for the output data.
- SupportedTransformInstanceTypes
-
- Type: Array of strings
A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
This parameter is required for unversioned models, and optional for versioned models.
InfraCheckConfig
Description
Configuration information for the infrastructure health check of a training job. A SageMaker-provided health check tests the health of instance hardware and cluster network connectivity.
Members
- EnableInfraCheck
-
- Type: boolean
Enables an infrastructure health check.
InputConfig
Description
Contains 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.
Members
- DataInputConfig
-
- Type: string
Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. The data inputs are
Framework
specific.-
TensorFlow
: You must specify the name and shape (NHWC format) of the expected data inputs using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.-
Examples for one input:
-
If using the console,
{"input":[1,1024,1024,3]}
-
If using the CLI,
{\"input\":[1,1024,1024,3]}
-
-
Examples for two inputs:
-
If using the console,
{"data1": [1,28,28,1], "data2":[1,28,28,1]}
-
If using the CLI,
{\"data1\": [1,28,28,1], \"data2\":[1,28,28,1]}
-
-
-
KERAS
: You must specify the name and shape (NCHW format) of expected data inputs using a dictionary format for your trained model. Note that while Keras model artifacts should be uploaded in NHWC (channel-last) format,DataInputConfig
should be specified in NCHW (channel-first) format. The dictionary formats required for the console and CLI are different.-
Examples for one input:
-
If using the console,
{"input_1":[1,3,224,224]}
-
If using the CLI,
{\"input_1\":[1,3,224,224]}
-
-
Examples for two inputs:
-
If using the console,
{"input_1": [1,3,224,224], "input_2":[1,3,224,224]}
-
If using the CLI,
{\"input_1\": [1,3,224,224], \"input_2\":[1,3,224,224]}
-
-
-
MXNET/ONNX/DARKNET
: You must specify the name and shape (NCHW format) of the expected data inputs in order using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.-
Examples for one input:
-
If using the console,
{"data":[1,3,1024,1024]}
-
If using the CLI,
{\"data\":[1,3,1024,1024]}
-
-
Examples for two inputs:
-
If using the console,
{"var1": [1,1,28,28], "var2":[1,1,28,28]}
-
If using the CLI,
{\"var1\": [1,1,28,28], \"var2\":[1,1,28,28]}
-
-
-
PyTorch
: You can either specify the name and shape (NCHW format) of expected data inputs in order using a dictionary format for your trained model or you can specify the shape only using a list format. The dictionary formats required for the console and CLI are different. The list formats for the console and CLI are the same.-
Examples for one input in dictionary format:
-
If using the console,
{"input0":[1,3,224,224]}
-
If using the CLI,
{\"input0\":[1,3,224,224]}
-
-
Example for one input in list format:
[[1,3,224,224]]
-
Examples for two inputs in dictionary format:
-
If using the console,
{"input0":[1,3,224,224], "input1":[1,3,224,224]}
-
If using the CLI,
{\"input0\":[1,3,224,224], \"input1\":[1,3,224,224]}
-
-
Example for two inputs in list format:
[[1,3,224,224], [1,3,224,224]]
-
-
XGBOOST
: input data name and shape are not needed.
DataInputConfig
supports the following parameters forCoreML
TargetDevice
(ML Model format):-
shape
: Input shape, for example{"input_1": {"shape": [1,224,224,3]}}
. In addition to static input shapes, CoreML converter supports Flexible input shapes:-
Range Dimension. You can use the Range Dimension feature if you know the input shape will be within some specific interval in that dimension, for example:
{"input_1": {"shape": ["1..10", 224, 224, 3]}}
-
Enumerated shapes. Sometimes, the models are trained to work only on a select set of inputs. You can enumerate all supported input shapes, for example:
{"input_1": {"shape": [[1, 224, 224, 3], [1, 160, 160, 3]]}}
-
-
default_shape
: Default input shape. You can set a default shape during conversion for both Range Dimension and Enumerated Shapes. For example{"input_1": {"shape": ["1..10", 224, 224, 3], "default_shape": [1, 224, 224, 3]}}
-
type
: Input type. Allowed values:Image
andTensor
. By default, the converter generates an ML Model with inputs of type Tensor (MultiArray). User can set input type to be Image. Image input type requires additional input parameters such asbias
andscale
. -
bias
: If the input type is an Image, you need to provide the bias vector. -
scale
: If the input type is an Image, you need to provide a scale factor.
CoreML
ClassifierConfig
parameters can be specified using OutputConfigCompilerOptions
. CoreML converter supports Tensorflow and PyTorch models. CoreML conversion examples:-
Tensor type input:
-
"DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3]}}
-
-
Tensor type input without input name (PyTorch):
-
"DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224]}]
-
-
Image type input:
-
"DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}}
-
"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}
-
-
Image type input without input name (PyTorch):
-
"DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}]
-
"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}
-
Depending on the model format,
DataInputConfig
requires the following parameters forml_eia2
OutputConfig:TargetDevice.-
For TensorFlow models saved in the SavedModel format, specify the input names from
signature_def_key
and the input model shapes forDataInputConfig
. Specify thesignature_def_key
inOutputConfig:CompilerOptions
if the model does not use TensorFlow's default signature def key. For example:-
"DataInputConfig": {"inputs": [1, 224, 224, 3]}
-
"CompilerOptions": {"signature_def_key": "serving_custom"}
-
-
For TensorFlow models saved as a frozen graph, specify the input tensor names and shapes in
DataInputConfig
and the output tensor names foroutput_names
inOutputConfig:CompilerOptions
. For example:-
"DataInputConfig": {"input_tensor:0": [1, 224, 224, 3]}
-
"CompilerOptions": {"output_names": ["output_tensor:0"]}
-
- Framework
-
- Required: Yes
- Type: string
Identifies the framework in which the model was trained. For example: TENSORFLOW.
- FrameworkVersion
-
- Type: string
Specifies the framework version to use. This API field is only supported for the MXNet, PyTorch, TensorFlow and TensorFlow Lite frameworks.
For information about framework versions supported for cloud targets and edge devices, see Cloud Supported Instance Types and Frameworks and Edge Supported Frameworks.
- S3Uri
-
- Required: Yes
- Type: string
The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
InstanceGroup
Description
Defines an instance group for heterogeneous cluster training. When requesting a training job using the CreateTrainingJob API, you can configure multiple instance groups .
Members
- InstanceCount
-
- Required: Yes
- Type: int
Specifies the number of instances of the instance group.
- InstanceGroupName
-
- Required: Yes
- Type: string
Specifies the name of the instance group.
- InstanceType
-
- Required: Yes
- Type: string
Specifies the instance type of the instance group.
InstanceMetadataServiceConfiguration
Description
Information on the IMDS configuration of the notebook instance
Members
- MinimumInstanceMetadataServiceVersion
-
- Required: Yes
- Type: string
Indicates the minimum IMDS version that the notebook instance supports. When passed as part of
CreateNotebookInstance
, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part ofUpdateNotebookInstance
, there is no default.
IntegerParameterRange
Description
For a hyperparameter of the integer type, specifies the range that a hyperparameter tuning job searches.
Members
- MaxValue
-
- Required: Yes
- Type: string
The maximum value of the hyperparameter to search.
- MinValue
-
- Required: Yes
- Type: string
The minimum value of the hyperparameter to search.
- Name
-
- Required: Yes
- Type: string
The name of the hyperparameter to search.
- ScalingType
-
- Type: string
The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
- Auto
-
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
- Linear
-
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
- Logarithmic
-
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
IntegerParameterRangeSpecification
Description
Defines the possible values for an integer hyperparameter.
Members
- MaxValue
-
- Required: Yes
- Type: string
The maximum integer value allowed.
- MinValue
-
- Required: Yes
- Type: string
The minimum integer value allowed.
JupyterLabAppImageConfig
Description
The configuration for the file system and kernels in a SageMaker image running as a JupyterLab app. The FileSystemConfig
object is not supported.
Members
- ContainerConfig
-
- Type: ContainerConfig structure
The configuration used to run the application image container.
- FileSystemConfig
-
- Type: FileSystemConfig structure
The Amazon Elastic File System storage configuration for a SageMaker image.
JupyterLabAppSettings
Description
The settings for the JupyterLab application.
Members
- CodeRepositories
-
- Type: Array of CodeRepository structures
A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterLab application.
- CustomImages
-
- Type: Array of CustomImage structures
A list of custom SageMaker images that are configured to run as a JupyterLab app.
- DefaultResourceSpec
-
- Type: ResourceSpec structure
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
- EmrSettings
-
- Type: EmrSettings structure
The configuration parameters that specify the IAM roles assumed by the execution role of SageMaker (assumable roles) and the cluster instances or job execution environments (execution roles or runtime roles) to manage and access resources required for running Amazon EMR clusters or Amazon EMR Serverless applications.
- LifecycleConfigArns
-
- Type: Array of strings
The Amazon Resource Name (ARN) of the lifecycle configurations attached to the user profile or domain. To remove a lifecycle config, you must set
LifecycleConfigArns
to an empty list.
JupyterServerAppSettings
Description
The JupyterServer app settings.
Members
- CodeRepositories
-
- Type: Array of CodeRepository structures
A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterServer application.
- DefaultResourceSpec
-
- Type: ResourceSpec structure
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the
LifecycleConfigArns
parameter, then this parameter is also required. - LifecycleConfigArns
-
- Type: Array of strings
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the
DefaultResourceSpec
parameter is also required.To remove a Lifecycle Config, you must set
LifecycleConfigArns
to an empty list.
KendraSettings
Description
The Amazon SageMaker Canvas application setting where you configure document querying.
Members
- Status
-
- Type: string
Describes whether the document querying feature is enabled or disabled in the Canvas application.
KernelGatewayAppSettings
Description
The KernelGateway app settings.
Members
- CustomImages
-
- Type: Array of CustomImage structures
A list of custom SageMaker images that are configured to run as a KernelGateway app.
- DefaultResourceSpec
-
- Type: ResourceSpec structure
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.
The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the CLI or CloudFormation and the instance type parameter value is not passed.
- LifecycleConfigArns
-
- Type: Array of strings
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
To remove a Lifecycle Config, you must set
LifecycleConfigArns
to an empty list.
KernelGatewayImageConfig
Description
The configuration for the file system and kernels in a SageMaker image running as a KernelGateway app.
Members
- FileSystemConfig
-
- Type: FileSystemConfig structure
The Amazon Elastic File System storage configuration for a SageMaker image.
- KernelSpecs
-
- Required: Yes
- Type: Array of KernelSpec structures
The specification of the Jupyter kernels in the image.
KernelSpec
Description
The specification of a Jupyter kernel.
Members
- DisplayName
-
- Type: string
The display name of the kernel.
- Name
-
- Required: Yes
- Type: string
The name of the Jupyter kernel in the image. This value is case sensitive.
LabelCounters
Description
Provides a breakdown of the number of objects labeled.
Members
- FailedNonRetryableError
-
- Type: int
The total number of objects that could not be labeled due to an error.
- HumanLabeled
-
- Type: int
The total number of objects labeled by a human worker.
- MachineLabeled
-
- Type: int
The total number of objects labeled by automated data labeling.
- TotalLabeled
-
- Type: int
The total number of objects labeled.
- Unlabeled
-
- Type: int
The total number of objects not yet labeled.
LabelCountersForWorkteam
Description
Provides counts for human-labeled tasks in the labeling job.
Members
- HumanLabeled
-
- Type: int
The total number of data objects labeled by a human worker.
- PendingHuman
-
- Type: int
The total number of data objects that need to be labeled by a human worker.
- Total
-
- Type: int
The total number of tasks in the labeling job.
LabelingJobAlgorithmsConfig
Description
Provides configuration information for auto-labeling of your data objects. A LabelingJobAlgorithmsConfig
object must be supplied in order to use auto-labeling.
Members
- InitialActiveLearningModelArn
-
- Type: string
At the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.
- LabelingJobAlgorithmSpecificationArn
-
- Required: Yes
- Type: string
Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:
-
Image classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification
-
Text classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification
-
Object detection
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection
-
Semantic Segmentation
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation
- LabelingJobResourceConfig
-
- Type: LabelingJobResourceConfig structure
Provides configuration information for a labeling job.
LabelingJobDataAttributes
Description
Attributes of the data specified by the customer. Use these to describe the data to be labeled.
Members
- ContentClassifiers
-
- Type: Array of strings
Declares that your content is free of personally identifiable information or adult content. SageMaker may restrict the Amazon Mechanical Turk workers that can view your task based on this information.
LabelingJobDataSource
Description
Provides information about the location of input data.
You must specify at least one of the following: S3DataSource
or SnsDataSource
.
Use SnsDataSource
to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job.
Use S3DataSource
to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource
is optional if you use SnsDataSource
to create a streaming labeling job.
Members
- S3DataSource
-
- Type: LabelingJobS3DataSource structure
The Amazon S3 location of the input data objects.
- SnsDataSource
-
- Type: LabelingJobSnsDataSource structure
An Amazon SNS data source used for streaming labeling jobs. To learn more, see Send Data to a Streaming Labeling Job.
LabelingJobForWorkteamSummary
Description
Provides summary information for a work team.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the labeling job was created.
- JobReferenceCode
-
- Required: Yes
- Type: string
A unique identifier for a labeling job. You can use this to refer to a specific labeling job.
- LabelCounters
-
- Type: LabelCountersForWorkteam structure
Provides information about the progress of a labeling job.
- LabelingJobName
-
- Type: string
The name of the labeling job that the work team is assigned to.
- NumberOfHumanWorkersPerDataObject
-
- Type: int
The configured number of workers per data object.
- WorkRequesterAccountId
-
- Required: Yes
- Type: string
The Amazon Web Services account ID of the account used to start the labeling job.
LabelingJobInputConfig
Description
Input configuration information for a labeling job.
Members
- DataAttributes
-
- Type: LabelingJobDataAttributes structure
Attributes of the data specified by the customer.
- DataSource
-
- Required: Yes
- Type: LabelingJobDataSource structure
The location of the input data.
LabelingJobOutput
Description
Specifies the location of the output produced by the labeling job.
Members
- FinalActiveLearningModelArn
-
- Type: string
The Amazon Resource Name (ARN) for the most recent SageMaker model trained as part of automated data labeling.
- OutputDatasetS3Uri
-
- Required: Yes
- Type: string
The Amazon S3 bucket location of the manifest file for labeled data.
LabelingJobOutputConfig
Description
Output configuration information for a labeling job.
Members
- KmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service ID of the key used to encrypt the output data, if any.
If you provide your own KMS key ID, you must add the required permissions to your KMS key described in Encrypt Output Data and Storage Volume with Amazon Web Services KMS.
If you don't provide a KMS key ID, Amazon SageMaker uses the default Amazon Web Services KMS key for Amazon S3 for your role's account to encrypt your output data.
If you use a bucket policy with an
s3:PutObject
permission that only allows objects with server-side encryption, set the condition key ofs3:x-amz-server-side-encryption
to"aws:kms"
. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide. - S3OutputPath
-
- Required: Yes
- Type: string
The Amazon S3 location to write output data.
- SnsTopicArn
-
- Type: string
An Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a
SnsTopicArn
if you want to do real time chaining to another streaming job and receive an Amazon SNS notifications each time a data object is submitted by a worker.If you provide an
SnsTopicArn
inOutputConfig
, when workers complete labeling tasks, Ground Truth will send labeling task output data to the SNS output topic you specify here.To learn more, see Receive Output Data from a Streaming Labeling Job.
LabelingJobResourceConfig
Description
Configure encryption on the storage volume attached to the ML compute instance used to run automated data labeling model training and inference.
Members
- VolumeKmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training and inference jobs used for automated data labeling.
You can only specify a
VolumeKmsKeyId
when you create a labeling job with automated data labeling enabled using the API operationCreateLabelingJob
. You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for automated data labeling model training and inference when you create a labeling job using the console. To learn more, see Output Data and Storage Volume Encryption.The
VolumeKmsKeyId
can be any of the following formats:-
KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
-
Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
- VpcConfig
-
- Type: VpcConfig structure
Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
LabelingJobS3DataSource
Description
The Amazon S3 location of the input data objects.
Members
- ManifestS3Uri
-
- Required: Yes
- Type: string
The Amazon S3 location of the manifest file that describes the input data objects.
The input manifest file referenced in
ManifestS3Uri
must contain one of the following keys:source-ref
orsource
. The value of the keys are interpreted as follows:-
source-ref
: The source of the object is the Amazon S3 object specified in the value. Use this value when the object is a binary object, such as an image. -
source
: The source of the object is the value. Use this value when the object is a text value.
If you are a new user of Ground Truth, it is recommended you review Use an Input Manifest File in the Amazon SageMaker Developer Guide to learn how to create an input manifest file.
LabelingJobSnsDataSource
Description
An Amazon SNS data source used for streaming labeling jobs.
Members
- SnsTopicArn
-
- Required: Yes
- Type: string
The Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the input topic you will use to send new data objects to a streaming labeling job.
LabelingJobStoppingConditions
Description
A set of conditions for stopping a 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.
Labeling jobs fail after 30 days with an appropriate client error message.
Members
- MaxHumanLabeledObjectCount
-
- Type: int
The maximum number of objects that can be labeled by human workers.
- MaxPercentageOfInputDatasetLabeled
-
- Type: int
The maximum number of input data objects that should be labeled.
LabelingJobSummary
Description
Provides summary information about a labeling job.
Members
- AnnotationConsolidationLambdaArn
-
- Type: string
The Amazon Resource Name (ARN) of the Lambda function used to consolidate the annotations from individual workers into a label for a data object. For more information, see Annotation Consolidation.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the job was created (timestamp).
- FailureReason
-
- Type: string
If the
LabelingJobStatus
field isFailed
, this field contains a description of the error. - InputConfig
-
- Type: LabelingJobInputConfig structure
Input configuration for the labeling job.
- LabelCounters
-
- Required: Yes
- Type: LabelCounters structure
Counts showing the progress of the labeling job.
- LabelingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) assigned to the labeling job when it was created.
- LabelingJobName
-
- Required: Yes
- Type: string
The name of the labeling job.
- LabelingJobOutput
-
- Type: LabelingJobOutput structure
The location of the output produced by the labeling job.
- LabelingJobStatus
-
- Required: Yes
- Type: string
The current status of the labeling job.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the job was last modified (timestamp).
- PreHumanTaskLambdaArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of a Lambda function. The function is run before each data object is sent to a worker.
- WorkteamArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the work team assigned to the job.
LambdaStepMetadata
Description
Metadata for a Lambda step.
Members
- Arn
-
- Type: string
The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution.
- OutputParameters
-
- Type: Array of OutputParameter structures
A list of the output parameters of the Lambda step.
LastUpdateStatus
Description
A value that indicates whether the update was successful.
Members
- FailureReason
-
- Type: string
If the update wasn't successful, indicates the reason why it failed.
- Status
-
- Required: Yes
- Type: string
A value that indicates whether the update was made successful.
LineageGroupSummary
Description
Lists a summary of the properties of a lineage group. A lineage group provides a group of shareable lineage entity resources.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time of the lineage group summary.
- DisplayName
-
- Type: string
The display name of the lineage group summary.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last modified time of the lineage group summary.
- LineageGroupArn
-
- Type: string
The Amazon Resource Name (ARN) of the lineage group resource.
- LineageGroupName
-
- Type: string
The name or Amazon Resource Name (ARN) of the lineage group.
MemberDefinition
Description
Defines an Amazon Cognito or your own OIDC IdP user group that is part of a work team.
Members
- CognitoMemberDefinition
-
- Type: CognitoMemberDefinition structure
The Amazon Cognito user group that is part of the work team.
- OidcMemberDefinition
-
- Type: OidcMemberDefinition structure
A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of
Groups
, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
MetadataProperties
Description
Metadata properties of the tracking entity, trial, or trial component.
Members
- CommitId
-
- Type: string
The commit ID.
- GeneratedBy
-
- Type: string
The entity this entity was generated by.
- ProjectId
-
- Type: string
The project ID.
- Repository
-
- Type: string
The repository.
MetricData
Description
The name, value, and date and time of a metric that was emitted to Amazon CloudWatch.
Members
- MetricName
-
- Type: string
The name of the metric.
- Timestamp
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the algorithm emitted the metric.
- Value
-
- Type: float
The value of the metric.
MetricDatum
Description
Information about the metric for a candidate produced by an AutoML job.
Members
- MetricName
-
- Type: string
The name of the metric.
- Set
-
- Type: string
The dataset split from which the AutoML job produced the metric.
- StandardMetricName
-
- Type: string
The name of the standard metric.
For definitions of the standard metrics, see
Autopilot candidate metrics
. - Value
-
- Type: float
The value of the metric.
MetricDefinition
Description
Specifies a metric that the training algorithm writes to stderr
or stdout
. You can view these logs to understand how your training job performs and check for any errors encountered during training. SageMaker hyperparameter tuning captures all defined metrics. Specify one of the defined metrics to use as an objective metric using the TuningObjective parameter in the HyperParameterTrainingJobDefinition
API to evaluate job performance during hyperparameter tuning.
Members
- Name
-
- Required: Yes
- Type: string
The name of the metric.
- Regex
-
- Required: Yes
- Type: string
A regular expression that searches the output of a training job and gets the value of the metric. For more information about using regular expressions to define metrics, see Defining metrics and environment variables.
MetricSpecification
Description
An object containing information about a metric.
Members
- Customized
-
- Type: CustomizedMetricSpecification structure
Information about a customized metric.
- Predefined
-
- Type: PredefinedMetricSpecification structure
Information about a predefined metric.
MetricsSource
Description
Details about the metrics source.
Members
- ContentDigest
-
- Type: string
The hash key used for the metrics source.
- ContentType
-
- Required: Yes
- Type: string
The metric source content type.
- S3Uri
-
- Required: Yes
- Type: string
The S3 URI for the metrics source.
Model
Description
The properties of a model as returned by the Search API.
Members
- Containers
-
- Type: Array of ContainerDefinition structures
The containers in the inference pipeline.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the model was created.
- DeploymentRecommendation
-
- Type: DeploymentRecommendation structure
A set of recommended deployment configurations for the model.
- EnableNetworkIsolation
-
- Type: boolean
Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
- ExecutionRoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
- InferenceExecutionConfig
-
- Type: InferenceExecutionConfig structure
Specifies details about how containers in a multi-container endpoint are run.
- ModelArn
-
- Type: string
The Amazon Resource Name (ARN) of the model.
- ModelName
-
- Type: string
The name of the model.
- PrimaryContainer
-
- Type: ContainerDefinition structure
Describes the container, as part of model definition.
- Tags
-
- Type: Array of Tag structures
A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
- VpcConfig
-
- Type: VpcConfig structure
Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
ModelAccessConfig
Description
The access configuration file to control access to the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig
.
-
If you are a Jumpstart user, see the End-user license agreements section for more details on accepting the EULA.
-
If you are an AutoML user, see the Optional Parameters section of Create an AutoML job to fine-tune text generation models using the API for details on How to set the EULA acceptance when fine-tuning a model using the AutoML API.
Members
- AcceptEula
-
- Required: Yes
- Type: boolean
Specifies agreement to the model end-user license agreement (EULA). The
AcceptEula
value must be explicitly defined asTrue
in order to accept the EULA that this model requires. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
ModelArtifacts
Description
Provides information about the location that is configured for storing model artifacts.
Model artifacts are outputs that result from training a model. They typically consist of trained parameters, a model definition that describes how to compute inferences, and other metadata. A SageMaker container stores your trained model artifacts in the /opt/ml/model
directory. After training has completed, by default, these artifacts are uploaded to your Amazon S3 bucket as compressed files.
Members
- S3ModelArtifacts
-
- Required: Yes
- Type: string
The path of the S3 object that contains the model artifacts. For example,
s3://bucket-name/keynameprefix/model.tar.gz
.
ModelBiasAppSpecification
Description
Docker container image configuration object for the model bias job.
Members
- ConfigUri
-
- Required: Yes
- Type: string
JSON formatted S3 file that defines bias parameters. For more information on this JSON configuration file, see Configure bias parameters.
- Environment
-
- Type: Associative array of custom strings keys (ProcessingEnvironmentKey) to strings
Sets the environment variables in the Docker container.
- ImageUri
-
- Required: Yes
- Type: string
The container image to be run by the model bias job.
ModelBiasBaselineConfig
Description
The configuration for a baseline model bias job.
Members
- BaseliningJobName
-
- Type: string
The name of the baseline model bias job.
- ConstraintsResource
-
- Type: MonitoringConstraintsResource structure
The constraints resource for a monitoring job.
ModelBiasJobInput
Description
Inputs for the model bias job.
Members
- BatchTransformInput
-
- Type: BatchTransformInput structure
Input object for the batch transform job.
- EndpointInput
-
- Type: EndpointInput structure
Input object for the endpoint
- GroundTruthS3Input
-
- Required: Yes
- Type: MonitoringGroundTruthS3Input structure
Location of ground truth labels to use in model bias job.
ModelCard
Description
An Amazon SageMaker Model Card.
Members
- Content
-
- Type: string
The content of the model card. Content uses the model card JSON schema and provided as a string.
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the model card was created.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the model card was last modified.
- ModelCardArn
-
- Type: string
The Amazon Resource Name (ARN) of the model card.
- ModelCardName
-
- Type: string
The unique name of the model card.
- ModelCardStatus
-
- Type: string
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
-
Draft
: The model card is a work in progress. -
PendingReview
: The model card is pending review. -
Approved
: The model card is approved. -
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
- ModelCardVersion
-
- Type: int
The version of the model card.
- ModelId
-
- Type: string
The unique name (ID) of the model.
- ModelPackageGroupName
-
- Type: string
The model package group that contains the model package. Only relevant for model cards created for model packages in the Amazon SageMaker Model Registry.
- RiskRating
-
- Type: string
The risk rating of the model. Different organizations might have different criteria for model card risk ratings. For more information, see Risk ratings.
- SecurityConfig
-
- Type: ModelCardSecurityConfig structure
The security configuration used to protect model card data.
- Tags
-
- Type: Array of Tag structures
Key-value pairs used to manage metadata for the model card.
ModelCardExportArtifacts
Description
The artifacts of the model card export job.
Members
- S3ExportArtifacts
-
- Required: Yes
- Type: string
The Amazon S3 URI of the exported model artifacts.
ModelCardExportJobSummary
Description
The summary of the Amazon SageMaker Model Card export job.
Members
- CreatedAt
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the model card export job was created.
- LastModifiedAt
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the model card export job was last modified..
- ModelCardExportJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model card export job.
- ModelCardExportJobName
-
- Required: Yes
- Type: string
The name of the model card export job.
- ModelCardName
-
- Required: Yes
- Type: string
The name of the model card that the export job exports.
- ModelCardVersion
-
- Required: Yes
- Type: int
The version of the model card that the export job exports.
- Status
-
- Required: Yes
- Type: string
The completion status of the model card export job.
ModelCardExportOutputConfig
Description
Configure the export output details for an Amazon SageMaker Model Card.
Members
- S3OutputPath
-
- Required: Yes
- Type: string
The Amazon S3 output path to export your model card PDF.
ModelCardSecurityConfig
Description
Configure the security settings to protect model card data.
Members
- KmsKeyId
-
- Type: string
A Key Management Service key ID to use for encrypting a model card.
ModelCardSummary
Description
A summary of the model card.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the model card was created.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the model card was last modified.
- ModelCardArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model card.
- ModelCardName
-
- Required: Yes
- Type: string
The name of the model card.
- ModelCardStatus
-
- Required: Yes
- Type: string
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
-
Draft
: The model card is a work in progress. -
PendingReview
: The model card is pending review. -
Approved
: The model card is approved. -
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
ModelCardVersionSummary
Description
A summary of a specific version of the model card.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the model card version was created.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time date and time that the model card version was last modified.
- ModelCardArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model card.
- ModelCardName
-
- Required: Yes
- Type: string
The name of the model card.
- ModelCardStatus
-
- Required: Yes
- Type: string
The approval status of the model card version within your organization. Different organizations might have different criteria for model card review and approval.
-
Draft
: The model card is a work in progress. -
PendingReview
: The model card is pending review. -
Approved
: The model card is approved. -
Archived
: The model card is archived. No more updates should be made to the model card, but it can still be exported.
- ModelCardVersion
-
- Required: Yes
- Type: int
A version of the model card.
ModelClientConfig
Description
Configures the timeout and maximum number of retries for processing a transform job invocation.
Members
- InvocationsMaxRetries
-
- Type: int
The maximum number of retries when invocation requests are failing. The default value is 3.
- InvocationsTimeoutInSeconds
-
- Type: int
The timeout value in seconds for an invocation request. The default value is 600.
ModelCompilationConfig
Description
Settings for the model compilation technique that's applied by a model optimization job.
Members
- Image
-
- Type: string
The URI of an LMI DLC in Amazon ECR. SageMaker uses this image to run the optimization.
- OverrideEnvironment
-
- Type: Associative array of custom strings keys (NonEmptyString256) to strings
Environment variables that override the default ones in the model container.
ModelConfiguration
Description
Defines the model configuration. Includes the specification name and environment parameters.
Members
- CompilationJobName
-
- Type: string
The name of the compilation job used to create the recommended model artifacts.
- EnvironmentParameters
-
- Type: Array of EnvironmentParameter structures
Defines the environment parameters that includes key, value types, and values.
- InferenceSpecificationName
-
- Type: string
The inference specification name in the model package version.
ModelDashboardEndpoint
Description
An endpoint that hosts a model displayed in the Amazon SageMaker Model Dashboard.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the endpoint was created.
- EndpointArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the endpoint.
- EndpointName
-
- Required: Yes
- Type: string
The endpoint name.
- EndpointStatus
-
- Required: Yes
- Type: string
The endpoint status.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last time the endpoint was modified.
ModelDashboardIndicatorAction
Description
An alert action taken to light up an icon on the Amazon SageMaker Model Dashboard when an alert goes into InAlert
status.
Members
- Enabled
-
- Type: boolean
Indicates whether the alert action is turned on.
ModelDashboardModel
Description
A model displayed in the Amazon SageMaker Model Dashboard.
Members
- Endpoints
-
- Type: Array of ModelDashboardEndpoint structures
The endpoints that host a model.
- LastBatchTransformJob
-
- Type: TransformJob structure
A batch transform job. For information about SageMaker batch transform, see Use Batch Transform.
- Model
-
- Type: Model structure
A model displayed in the Model Dashboard.
- ModelCard
-
- Type: ModelDashboardModelCard structure
The model card for a model.
- MonitoringSchedules
-
- Type: Array of ModelDashboardMonitoringSchedule structures
The monitoring schedules for a model.
ModelDashboardModelCard
Description
The model card for a model displayed in the Amazon SageMaker Model Dashboard.
Members
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the model card was created.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the model card was last updated.
- ModelCardArn
-
- Type: string
The Amazon Resource Name (ARN) for a model card.
- ModelCardName
-
- Type: string
The name of a model card.
- ModelCardStatus
-
- Type: string
The model card status.
- ModelCardVersion
-
- Type: int
The model card version.
- ModelId
-
- Type: string
For models created in SageMaker, this is the model ARN. For models created outside of SageMaker, this is a user-customized string.
- RiskRating
-
- Type: string
A model card's risk rating. Can be low, medium, or high.
- SecurityConfig
-
- Type: ModelCardSecurityConfig structure
The KMS Key ID (
KMSKeyId
) for encryption of model card information. - Tags
-
- Type: Array of Tag structures
The tags associated with a model card.
ModelDashboardMonitoringSchedule
Description
A monitoring schedule for a model displayed in the Amazon SageMaker Model Dashboard.
Members
- BatchTransformInput
-
- Type: BatchTransformInput structure
Input object for the batch transform job.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the monitoring schedule was created.
- EndpointName
-
- Type: string
The endpoint which is monitored.
- FailureReason
-
- Type: string
If a monitoring job failed, provides the reason.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the monitoring schedule was last updated.
- LastMonitoringExecutionSummary
-
- Type: MonitoringExecutionSummary structure
Summary of information about the last monitoring job to run.
- MonitoringAlertSummaries
-
- Type: Array of MonitoringAlertSummary structures
A JSON array where each element is a summary for a monitoring alert.
- MonitoringScheduleArn
-
- Type: string
The Amazon Resource Name (ARN) of a monitoring schedule.
- MonitoringScheduleConfig
-
- Type: MonitoringScheduleConfig structure
Configures the monitoring schedule and defines the monitoring job.
- MonitoringScheduleName
-
- Type: string
The name of a monitoring schedule.
- MonitoringScheduleStatus
-
- Type: string
The status of the monitoring schedule.
- MonitoringType
-
- Type: string
The monitor type of a model monitor.
ModelDataQuality
Description
Data quality constraints and statistics for a model.
Members
- Constraints
-
- Type: MetricsSource structure
Data quality constraints for a model.
- Statistics
-
- Type: MetricsSource structure
Data quality statistics for a model.
ModelDataSource
Description
Specifies the location of ML model data to deploy. If specified, you must specify one and only one of the available data sources.
Members
- S3DataSource
-
- Type: S3ModelDataSource structure
Specifies the S3 location of ML model data to deploy.
ModelDeployConfig
Description
Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
Members
- AutoGenerateEndpointName
-
- Type: boolean
Set to
True
to automatically generate an endpoint name for a one-click Autopilot model deployment; set toFalse
otherwise. The default value isFalse
.If you set
AutoGenerateEndpointName
toTrue
, do not specify theEndpointName
; otherwise a 400 error is thrown. - EndpointName
-
- Type: string
Specifies the endpoint name to use for a one-click Autopilot model deployment if the endpoint name is not generated automatically.
Specify the
EndpointName
if and only if you setAutoGenerateEndpointName
toFalse
; otherwise a 400 error is thrown.
ModelDeployResult
Description
Provides information about the endpoint of the model deployment.
Members
- EndpointName
-
- Type: string
The name of the endpoint to which the model has been deployed.
If model deployment fails, this field is omitted from the response.
ModelDigests
Description
Provides information to verify the integrity of stored model artifacts.
Members
- ArtifactDigest
-
- Type: string
Provides a hash value that uniquely identifies the stored model artifacts.
ModelExplainabilityAppSpecification
Description
Docker container image configuration object for the model explainability job.
Members
- ConfigUri
-
- Required: Yes
- Type: string
JSON formatted Amazon S3 file that defines explainability parameters. For more information on this JSON configuration file, see Configure model explainability parameters.
- Environment
-
- Type: Associative array of custom strings keys (ProcessingEnvironmentKey) to strings
Sets the environment variables in the Docker container.
- ImageUri
-
- Required: Yes
- Type: string
The container image to be run by the model explainability job.
ModelExplainabilityBaselineConfig
Description
The configuration for a baseline model explainability job.
Members
- BaseliningJobName
-
- Type: string
The name of the baseline model explainability job.
- ConstraintsResource
-
- Type: MonitoringConstraintsResource structure
The constraints resource for a monitoring job.
ModelExplainabilityJobInput
Description
Inputs for the model explainability job.
Members
- BatchTransformInput
-
- Type: BatchTransformInput structure
Input object for the batch transform job.
- EndpointInput
-
- Type: EndpointInput structure
Input object for the endpoint
ModelInfrastructureConfig
Description
The configuration for the infrastructure that the model will be deployed to.
Members
- InfrastructureType
-
- Required: Yes
- Type: string
The inference option to which to deploy your model. Possible values are the following:
-
RealTime
: Deploy to real-time inference.
- RealTimeInferenceConfig
-
- Required: Yes
- Type: RealTimeInferenceConfig structure
The infrastructure configuration for deploying the model to real-time inference.
ModelInput
Description
Input object for the model.
Members
- DataInputConfig
-
- Required: Yes
- Type: string
The input configuration object for the model.
ModelLatencyThreshold
Description
The model latency threshold.
Members
- Percentile
-
- Type: string
The model latency percentile threshold. Acceptable values are
P95
andP99
. For custom load tests, specify the value asP95
. - ValueInMilliseconds
-
- Type: int
The model latency percentile value in milliseconds.
ModelMetadataFilter
Description
Part of the search expression. You can specify the name and value (domain, task, framework, framework version, task, and model).
Members
- Name
-
- Required: Yes
- Type: string
The name of the of the model to filter by.
- Value
-
- Required: Yes
- Type: string
The value to filter the model metadata.
ModelMetadataSearchExpression
Description
One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression's condition are included in the search results
Members
- Filters
-
- Type: Array of ModelMetadataFilter structures
A list of filter objects.
ModelMetadataSummary
Description
A summary of the model metadata.
Members
- Domain
-
- Required: Yes
- Type: string
The machine learning domain of the model.
- Framework
-
- Required: Yes
- Type: string
The machine learning framework of the model.
- FrameworkVersion
-
- Required: Yes
- Type: string
The framework version of the model.
- Model
-
- Required: Yes
- Type: string
The name of the model.
- Task
-
- Required: Yes
- Type: string
The machine learning task of the model.
ModelMetrics
Description
Contains metrics captured from a model.
Members
- Bias
-
- Type: Bias structure
Metrics that measure bias in a model.
- Explainability
-
- Type: Explainability structure
Metrics that help explain a model.
- ModelDataQuality
-
- Type: ModelDataQuality structure
Metrics that measure the quality of the input data for a model.
- ModelQuality
-
- Type: ModelQuality structure
Metrics that measure the quality of a model.
ModelPackage
Description
A versioned model that can be deployed for SageMaker inference.
Members
- AdditionalInferenceSpecifications
-
- Type: Array of AdditionalInferenceSpecificationDefinition structures
An array of additional Inference Specification objects.
- ApprovalDescription
-
- Type: string
A description provided when the model approval is set.
- CertifyForMarketplace
-
- Type: boolean
Whether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see List Your Algorithm or Model Package on Amazon Web Services Marketplace.
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the model package was created.
- CustomerMetadataProperties
-
- Type: Associative array of custom strings keys (CustomerMetadataKey) to strings
The metadata properties for the model package.
- Domain
-
- Type: string
The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
- DriftCheckBaselines
-
- Type: DriftCheckBaselines structure
Represents the drift check baselines that can be used when the model monitor is set using the model package.
- InferenceSpecification
-
- Type: InferenceSpecification structure
Defines how to perform inference generation after a training job is run.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last time the model package was modified.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- ModelApprovalStatus
-
- Type: string
The approval status of the model. This can be one of the following values.
-
APPROVED
- The model is approved -
REJECTED
- The model is rejected. -
PENDING_MANUAL_APPROVAL
- The model is waiting for manual approval.
- ModelCard
-
- Type: ModelPackageModelCard structure
The model card associated with the model package. Since
ModelPackageModelCard
is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema ofModelCard
. TheModelPackageModelCard
schema does not includemodel_package_details
, andmodel_overview
is composed of themodel_creator
andmodel_artifact
properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version. - ModelMetrics
-
- Type: ModelMetrics structure
Metrics for the model.
- ModelPackageArn
-
- Type: string
The Amazon Resource Name (ARN) of the model package.
- ModelPackageDescription
-
- Type: string
The description of the model package.
- ModelPackageGroupName
-
- Type: string
The model group to which the model belongs.
- ModelPackageName
-
- Type: string
The name of the model.
- ModelPackageStatus
-
- Type: string
The status of the model package. This can be one of the following values.
-
PENDING
- The model package is pending being created. -
IN_PROGRESS
- The model package is in the process of being created. -
COMPLETED
- The model package was successfully created. -
FAILED
- The model package failed. -
DELETING
- The model package is in the process of being deleted.
- ModelPackageStatusDetails
-
- Type: ModelPackageStatusDetails structure
Specifies the validation and image scan statuses of the model package.
- ModelPackageVersion
-
- Type: int
The version number of a versioned model.
- SamplePayloadUrl
-
- Type: string
The Amazon Simple Storage Service path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
- SecurityConfig
-
- Type: ModelPackageSecurityConfig structure
An optional Key Management Service key to encrypt, decrypt, and re-encrypt model package information for regulated workloads with highly sensitive data.
- SkipModelValidation
-
- Type: string
Indicates if you want to skip model validation.
- SourceAlgorithmSpecification
-
- Type: SourceAlgorithmSpecification structure
A list of algorithms that were used to create a model package.
- SourceUri
-
- Type: string
The URI of the source for the model package.
- Tags
-
- Type: Array of Tag structures
A list of the tags associated with the model package. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
- Task
-
- Type: string
The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
- ValidationSpecification
-
- Type: ModelPackageValidationSpecification structure
Specifies batch transform jobs that SageMaker runs to validate your model package.
ModelPackageContainerDefinition
Description
Describes the Docker container for the model package.
Members
- AdditionalS3DataSource
-
- Type: AdditionalS3DataSource structure
The additional data source that is used during inference in the Docker container for your model package.
- ContainerHostname
-
- Type: string
The DNS host name for the Docker container.
- Environment
-
- Type: Associative array of custom strings keys (EnvironmentKey) to strings
The environment variables to set in the Docker container. Each key and value in the
Environment
string to string map can have length of up to 1024. We support up to 16 entries in the map. - Framework
-
- Type: string
The machine learning framework of the model package container image.
- FrameworkVersion
-
- Type: string
The framework version of the Model Package Container Image.
- Image
-
- Required: Yes
- Type: string
The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both
registry/repository[:tag]
andregistry/repository[@digest]
image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker. - ImageDigest
-
- Type: string
An MD5 hash of the training algorithm that identifies the Docker image used for training.
- ModelDataSource
-
- Type: ModelDataSource structure
Specifies the location of ML model data to deploy during endpoint creation.
- ModelDataUrl
-
- Type: string
The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single
gzip
compressed tar archive (.tar.gz
suffix).The model artifacts must be in an S3 bucket that is in the same region as the model package.
- ModelInput
-
- Type: ModelInput structure
A structure with Model Input details.
- NearestModelName
-
- Type: string
The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model. You can find a list of benchmarked models by calling
ListModelMetadata
. - ProductId
-
- Type: string
The Amazon Web Services Marketplace product ID of the model package.
ModelPackageGroup
Description
A group of versioned models in the model registry.
Members
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the model group was created.
- ModelPackageGroupArn
-
- Type: string
The Amazon Resource Name (ARN) of the model group.
- ModelPackageGroupDescription
-
- Type: string
The description for the model group.
- ModelPackageGroupName
-
- Type: string
The name of the model group.
- ModelPackageGroupStatus
-
- Type: string
The status of the model group. This can be one of the following values.
-
PENDING
- The model group is pending being created. -
IN_PROGRESS
- The model group is in the process of being created. -
COMPLETED
- The model group was successfully created. -
FAILED
- The model group failed. -
DELETING
- The model group is in the process of being deleted. -
DELETE_FAILED
- SageMaker failed to delete the model group.
- Tags
-
- Type: Array of Tag structures
A list of the tags associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
ModelPackageGroupSummary
Description
Summary information about a model group.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the model group was created.
- ModelPackageGroupArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model group.
- ModelPackageGroupDescription
-
- Type: string
A description of the model group.
- ModelPackageGroupName
-
- Required: Yes
- Type: string
The name of the model group.
- ModelPackageGroupStatus
-
- Required: Yes
- Type: string
The status of the model group.
ModelPackageModelCard
Description
The model card associated with the model package. Since ModelPackageModelCard
is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema of ModelCard
. The ModelPackageModelCard
schema does not include model_package_details
, and model_overview
is composed of the model_creator
and model_artifact
properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version.
Members
- ModelCardContent
-
- Type: string
The content of the model card. The content must follow the schema described in Model Package Model Card Schema.
- ModelCardStatus
-
- Type: string
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
-
Draft
: The model card is a work in progress. -
PendingReview
: The model card is pending review. -
Approved
: The model card is approved. -
Archived
: The model card is archived. No more updates can be made to the model card content. If you try to update the model card content, you will receive the messageModel Card is in Archived state
.
ModelPackageSecurityConfig
Description
An optional Key Management Service key to encrypt, decrypt, and re-encrypt model package information for regulated workloads with highly sensitive data.
Members
- KmsKeyId
-
- Required: Yes
- Type: string
The KMS Key ID (
KMSKeyId
) used for encryption of model package information.
ModelPackageStatusDetails
Description
Specifies the validation and image scan statuses of the model package.
Members
- ImageScanStatuses
-
- Type: Array of ModelPackageStatusItem structures
The status of the scan of the Docker image container for the model package.
- ValidationStatuses
-
- Required: Yes
- Type: Array of ModelPackageStatusItem structures
The validation status of the model package.
ModelPackageStatusItem
Description
Represents the overall status of a model package.
Members
- FailureReason
-
- Type: string
if the overall status is
Failed
, the reason for the failure. - Name
-
- Required: Yes
- Type: string
The name of the model package for which the overall status is being reported.
- Status
-
- Required: Yes
- Type: string
The current status.
ModelPackageSummary
Description
Provides summary information about a model package.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the model package was created.
- ModelApprovalStatus
-
- Type: string
The approval status of the model. This can be one of the following values.
-
APPROVED
- The model is approved -
REJECTED
- The model is rejected. -
PENDING_MANUAL_APPROVAL
- The model is waiting for manual approval.
- ModelPackageArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model package.
- ModelPackageDescription
-
- Type: string
A brief description of the model package.
- ModelPackageGroupName
-
- Type: string
If the model package is a versioned model, the model group that the versioned model belongs to.
- ModelPackageName
-
- Type: string
The name of the model package.
- ModelPackageStatus
-
- Required: Yes
- Type: string
The overall status of the model package.
- ModelPackageVersion
-
- Type: int
If the model package is a versioned model, the version of the model.
ModelPackageValidationProfile
Description
Contains data, such as the inputs and targeted instance types that are used in the process of validating the model package.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
Members
- ProfileName
-
- Required: Yes
- Type: string
The name of the profile for the model package.
- TransformJobDefinition
-
- Required: Yes
- Type: TransformJobDefinition structure
The
TransformJobDefinition
object that describes the transform job used for the validation of the model package.
ModelPackageValidationSpecification
Description
Specifies batch transform jobs that SageMaker runs to validate your model package.
Members
- ValidationProfiles
-
- Required: Yes
- Type: Array of ModelPackageValidationProfile structures
An array of
ModelPackageValidationProfile
objects, each of which specifies a batch transform job that SageMaker runs to validate your model package. - ValidationRole
-
- Required: Yes
- Type: string
The IAM roles to be used for the validation of the model package.
ModelQuality
Description
Model quality statistics and constraints.
Members
- Constraints
-
- Type: MetricsSource structure
Model quality constraints.
- Statistics
-
- Type: MetricsSource structure
Model quality statistics.
ModelQualityAppSpecification
Description
Container image configuration object for the monitoring job.
Members
- ContainerArguments
-
- Type: Array of strings
An array of arguments for the container used to run the monitoring job.
- ContainerEntrypoint
-
- Type: Array of strings
Specifies the entrypoint for a container that the monitoring job runs.
- Environment
-
- Type: Associative array of custom strings keys (ProcessingEnvironmentKey) to strings
Sets the environment variables in the container that the monitoring job runs.
- ImageUri
-
- Required: Yes
- Type: string
The address of the container image that the monitoring job runs.
- PostAnalyticsProcessorSourceUri
-
- Type: string
An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
- ProblemType
-
- Type: string
The machine learning problem type of the model that the monitoring job monitors.
- RecordPreprocessorSourceUri
-
- Type: string
An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
ModelQualityBaselineConfig
Description
Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
Members
- BaseliningJobName
-
- Type: string
The name of the job that performs baselining for the monitoring job.
- ConstraintsResource
-
- Type: MonitoringConstraintsResource structure
The constraints resource for a monitoring job.
ModelQualityJobInput
Description
The input for the model quality monitoring job. Currently endpoints are supported for input for model quality monitoring jobs.
Members
- BatchTransformInput
-
- Type: BatchTransformInput structure
Input object for the batch transform job.
- EndpointInput
-
- Type: EndpointInput structure
Input object for the endpoint
- GroundTruthS3Input
-
- Required: Yes
- Type: MonitoringGroundTruthS3Input structure
The ground truth label provided for the model.
ModelQuantizationConfig
Description
Settings for the model quantization technique that's applied by a model optimization job.
Members
- Image
-
- Type: string
The URI of an LMI DLC in Amazon ECR. SageMaker uses this image to run the optimization.
- OverrideEnvironment
-
- Type: Associative array of custom strings keys (NonEmptyString256) to strings
Environment variables that override the default ones in the model container.
ModelRegisterSettings
Description
The model registry settings for the SageMaker Canvas application.
Members
- CrossAccountModelRegisterRoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the SageMaker model registry account. Required only to register model versions created by a different SageMaker Canvas Amazon Web Services account than the Amazon Web Services account in which SageMaker model registry is set up.
- Status
-
- Type: string
Describes whether the integration to the model registry is enabled or disabled in the Canvas application.
ModelStepMetadata
Description
Metadata for Model steps.
Members
- Arn
-
- Type: string
The Amazon Resource Name (ARN) of the created model.
ModelSummary
Description
Provides summary information about a model.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the model was created.
- ModelArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model.
- ModelName
-
- Required: Yes
- Type: string
The name of the model that you want a summary for.
ModelVariantConfig
Description
Contains information about the deployment options of a model.
Members
- InfrastructureConfig
-
- Required: Yes
- Type: ModelInfrastructureConfig structure
The configuration for the infrastructure that the model will be deployed to.
- ModelName
-
- Required: Yes
- Type: string
The name of the Amazon SageMaker Model entity.
- VariantName
-
- Required: Yes
- Type: string
The name of the variant.
ModelVariantConfigSummary
Description
Summary of the deployment configuration of a model.
Members
- InfrastructureConfig
-
- Required: Yes
- Type: ModelInfrastructureConfig structure
The configuration of the infrastructure that the model has been deployed to.
- ModelName
-
- Required: Yes
- Type: string
The name of the Amazon SageMaker Model entity.
- Status
-
- Required: Yes
- Type: string
The status of deployment for the model variant on the hosted inference endpoint.
-
Creating
- Amazon SageMaker is preparing the model variant on the hosted inference endpoint. -
InService
- The model variant is running on the hosted inference endpoint. -
Updating
- Amazon SageMaker is updating the model variant on the hosted inference endpoint. -
Deleting
- Amazon SageMaker is deleting the model variant on the hosted inference endpoint. -
Deleted
- The model variant has been deleted on the hosted inference endpoint. This can only happen after stopping the experiment.
- VariantName
-
- Required: Yes
- Type: string
The name of the variant.
MonitoringAlertActions
Description
A list of alert actions taken in response to an alert going into InAlert
status.
Members
- ModelDashboardIndicator
-
- Type: ModelDashboardIndicatorAction structure
An alert action taken to light up an icon on the Model Dashboard when an alert goes into
InAlert
status.
MonitoringAlertHistorySummary
Description
Provides summary information of an alert's history.
Members
- AlertStatus
-
- Required: Yes
- Type: string
The current alert status of an alert.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the first alert transition occurred in an alert history. An alert transition can be from status
InAlert
toOK
, or fromOK
toInAlert
. - MonitoringAlertName
-
- Required: Yes
- Type: string
The name of a monitoring alert.
- MonitoringScheduleName
-
- Required: Yes
- Type: string
The name of a monitoring schedule.
MonitoringAlertSummary
Description
Provides summary information about a monitor alert.
Members
- Actions
-
- Required: Yes
- Type: MonitoringAlertActions structure
A list of alert actions taken in response to an alert going into
InAlert
status. - AlertStatus
-
- Required: Yes
- Type: string
The current status of an alert.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when a monitor alert was created.
- DatapointsToAlert
-
- Required: Yes
- Type: int
Within
EvaluationPeriod
, how many execution failures will raise an alert. - EvaluationPeriod
-
- Required: Yes
- Type: int
The number of most recent monitoring executions to consider when evaluating alert status.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when a monitor alert was last updated.
- MonitoringAlertName
-
- Required: Yes
- Type: string
The name of a monitoring alert.
MonitoringAppSpecification
Description
Container image configuration object for the monitoring job.
Members
- ContainerArguments
-
- Type: Array of strings
An array of arguments for the container used to run the monitoring job.
- ContainerEntrypoint
-
- Type: Array of strings
Specifies the entrypoint for a container used to run the monitoring job.
- ImageUri
-
- Required: Yes
- Type: string
The container image to be run by the monitoring job.
- PostAnalyticsProcessorSourceUri
-
- Type: string
An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
- RecordPreprocessorSourceUri
-
- Type: string
An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
MonitoringBaselineConfig
Description
Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
Members
- BaseliningJobName
-
- Type: string
The name of the job that performs baselining for the monitoring job.
- ConstraintsResource
-
- Type: MonitoringConstraintsResource structure
The baseline constraint file in Amazon S3 that the current monitoring job should validated against.
- StatisticsResource
-
- Type: MonitoringStatisticsResource structure
The baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
MonitoringClusterConfig
Description
Configuration for the cluster used to run model monitoring jobs.
Members
- InstanceCount
-
- Required: Yes
- Type: int
The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
- InstanceType
-
- Required: Yes
- Type: string
The ML compute instance type for the processing job.
- VolumeKmsKeyId
-
- Type: string
The Key Management Service (KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
- VolumeSizeInGB
-
- Required: Yes
- Type: int
The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
MonitoringConstraintsResource
Description
The constraints resource for a monitoring job.
Members
- S3Uri
-
- Type: string
The Amazon S3 URI for the constraints resource.
MonitoringCsvDatasetFormat
Description
Represents the CSV dataset format used when running a monitoring job.
Members
- Header
-
- Type: boolean
Indicates if the CSV data has a header.
MonitoringDatasetFormat
Description
Represents the dataset format used when running a monitoring job.
Members
- Csv
-
- Type: MonitoringCsvDatasetFormat structure
The CSV dataset used in the monitoring job.
- Json
-
- Type: MonitoringJsonDatasetFormat structure
The JSON dataset used in the monitoring job
- Parquet
-
- Type: MonitoringParquetDatasetFormat structure
The Parquet dataset used in the monitoring job
MonitoringExecutionSummary
Description
Summary of information about the last monitoring job to run.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the monitoring job was created.
- EndpointName
-
- Type: string
The name of the endpoint used to run the monitoring job.
- FailureReason
-
- Type: string
Contains the reason a monitoring job failed, if it failed.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates the last time the monitoring job was modified.
- MonitoringExecutionStatus
-
- Required: Yes
- Type: string
The status of the monitoring job.
- MonitoringJobDefinitionName
-
- Type: string
The name of the monitoring job.
- MonitoringScheduleName
-
- Required: Yes
- Type: string
The name of the monitoring schedule.
- MonitoringType
-
- Type: string
The type of the monitoring job.
- ProcessingJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the monitoring job.
- ScheduledTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time the monitoring job was scheduled.
MonitoringGroundTruthS3Input
Description
The ground truth labels for the dataset used for the monitoring job.
Members
- S3Uri
-
- Type: string
The address of the Amazon S3 location of the ground truth labels.
MonitoringInput
Description
The inputs for a monitoring job.
Members
- BatchTransformInput
-
- Type: BatchTransformInput structure
Input object for the batch transform job.
- EndpointInput
-
- Type: EndpointInput structure
The endpoint for a monitoring job.
MonitoringJobDefinition
Description
Defines the monitoring job.
Members
- BaselineConfig
-
- Type: MonitoringBaselineConfig structure
Baseline configuration used to validate that the data conforms to the specified constraints and statistics
- Environment
-
- Type: Associative array of custom strings keys (ProcessingEnvironmentKey) to strings
Sets the environment variables in the Docker container.
- MonitoringAppSpecification
-
- Required: Yes
- Type: MonitoringAppSpecification structure
Configures the monitoring job to run a specified Docker container image.
- MonitoringInputs
-
- Required: Yes
- Type: Array of MonitoringInput structures
The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
- MonitoringOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The array of outputs from the monitoring job to be uploaded to Amazon S3.
- MonitoringResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.
- NetworkConfig
-
- Type: NetworkConfig structure
Specifies networking options for an monitoring job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
Specifies a time limit for how long the monitoring job is allowed to run.
MonitoringJobDefinitionSummary
Description
Summary information about a monitoring job.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the monitoring job was created.
- EndpointName
-
- Required: Yes
- Type: string
The name of the endpoint that the job monitors.
- MonitoringJobDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the monitoring job.
- MonitoringJobDefinitionName
-
- Required: Yes
- Type: string
The name of the monitoring job.
MonitoringJsonDatasetFormat
Description
Represents the JSON dataset format used when running a monitoring job.
Members
- Line
-
- Type: boolean
Indicates if the file should be read as a JSON object per line.
MonitoringNetworkConfig
Description
The networking configuration for the monitoring job.
Members
- EnableInterContainerTrafficEncryption
-
- Type: boolean
Whether to encrypt all communications between the instances used for the monitoring jobs. Choose
True
to encrypt communications. Encryption provides greater security for distributed jobs, but the processing might take longer. - EnableNetworkIsolation
-
- Type: boolean
Whether to allow inbound and outbound network calls to and from the containers used for the monitoring job.
- VpcConfig
-
- Type: VpcConfig structure
Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
MonitoringOutput
Description
The output object for a monitoring job.
Members
- S3Output
-
- Required: Yes
- Type: MonitoringS3Output structure
The Amazon S3 storage location where the results of a monitoring job are saved.
MonitoringOutputConfig
Description
The output configuration for monitoring jobs.
Members
- KmsKeyId
-
- Type: string
The Key Management Service (KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
- MonitoringOutputs
-
- Required: Yes
- Type: Array of MonitoringOutput structures
Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
MonitoringParquetDatasetFormat
Description
Represents the Parquet dataset format used when running a monitoring job.
Members
MonitoringResources
Description
Identifies the resources to deploy for a monitoring job.
Members
- ClusterConfig
-
- Required: Yes
- Type: MonitoringClusterConfig structure
The configuration for the cluster resources used to run the processing job.
MonitoringS3Output
Description
Information about where and how you want to store the results of a monitoring job.
Members
- LocalPath
-
- Required: Yes
- Type: string
The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
- S3UploadMode
-
- Type: string
Whether to upload the results of the monitoring job continuously or after the job completes.
- S3Uri
-
- Required: Yes
- Type: string
A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
MonitoringSchedule
Description
A schedule for a model monitoring job. For information about model monitor, see Amazon SageMaker Model Monitor.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the monitoring schedule was created.
- EndpointName
-
- Type: string
The endpoint that hosts the model being monitored.
- FailureReason
-
- Type: string
If the monitoring schedule failed, the reason it failed.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last time the monitoring schedule was changed.
- LastMonitoringExecutionSummary
-
- Type: MonitoringExecutionSummary structure
Summary of information about the last monitoring job to run.
- MonitoringScheduleArn
-
- Type: string
The Amazon Resource Name (ARN) of the monitoring schedule.
- MonitoringScheduleConfig
-
- Type: MonitoringScheduleConfig structure
Configures the monitoring schedule and defines the monitoring job.
- MonitoringScheduleName
-
- Type: string
The name of the monitoring schedule.
- MonitoringScheduleStatus
-
- Type: string
The status of the monitoring schedule. This can be one of the following values.
-
PENDING
- The schedule is pending being created. -
FAILED
- The schedule failed. -
SCHEDULED
- The schedule was successfully created. -
STOPPED
- The schedule was stopped.
- MonitoringType
-
- Type: string
The type of the monitoring job definition to schedule.
- Tags
-
- Type: Array of Tag structures
A list of the tags associated with the monitoring schedlue. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
MonitoringScheduleConfig
Description
Configures the monitoring schedule and defines the monitoring job.
Members
- MonitoringJobDefinition
-
- Type: MonitoringJobDefinition structure
Defines the monitoring job.
- MonitoringJobDefinitionName
-
- Type: string
The name of the monitoring job definition to schedule.
- MonitoringType
-
- Type: string
The type of the monitoring job definition to schedule.
- ScheduleConfig
-
- Type: ScheduleConfig structure
Configures the monitoring schedule.
MonitoringScheduleSummary
Description
Summarizes the monitoring schedule.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time of the monitoring schedule.
- EndpointName
-
- Type: string
The name of the endpoint using the monitoring schedule.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last time the monitoring schedule was modified.
- MonitoringJobDefinitionName
-
- Type: string
The name of the monitoring job definition that the schedule is for.
- MonitoringScheduleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the monitoring schedule.
- MonitoringScheduleName
-
- Required: Yes
- Type: string
The name of the monitoring schedule.
- MonitoringScheduleStatus
-
- Required: Yes
- Type: string
The status of the monitoring schedule.
- MonitoringType
-
- Type: string
The type of the monitoring job definition that the schedule is for.
MonitoringStatisticsResource
Description
The statistics resource for a monitoring job.
Members
- S3Uri
-
- Type: string
The Amazon S3 URI for the statistics resource.
MonitoringStoppingCondition
Description
A time limit for how long the monitoring job is allowed to run before stopping.
Members
- MaxRuntimeInSeconds
-
- Required: Yes
- Type: int
The maximum runtime allowed in seconds.
The
MaxRuntimeInSeconds
cannot exceed the frequency of the job. For data quality and model explainability, this can be up to 3600 seconds for an hourly schedule. For model bias and model quality hourly schedules, this can be up to 1800 seconds.
MultiModelConfig
Description
Specifies additional configuration for hosting multi-model endpoints.
Members
- ModelCacheSetting
-
- Type: string
Whether to cache models for a multi-model endpoint. By default, multi-model endpoints cache models so that a model does not have to be loaded into memory each time it is invoked. Some use cases do not benefit from model caching. For example, if an endpoint hosts a large number of models that are each invoked infrequently, the endpoint might perform better if you disable model caching. To disable model caching, set the value of this parameter to
Disabled
.
NeoVpcConfig
Description
The VpcConfig configuration object that specifies the VPC that you want the compilation jobs to connect to. For more information on controlling access to your Amazon S3 buckets used for compilation job, see Give Amazon SageMaker Compilation Jobs Access to Resources in Your Amazon VPC.
Members
- SecurityGroupIds
-
- Required: Yes
- Type: Array of strings
The VPC security group IDs. IDs have the form of
sg-xxxxxxxx
. Specify the security groups for the VPC that is specified in theSubnets
field. - Subnets
-
- Required: Yes
- Type: Array of strings
The ID of the subnets in the VPC that you want to connect the compilation job to for accessing the model in Amazon S3.
NestedFilters
Description
A list of nested Filter objects. A resource must satisfy the conditions of all filters to be included in the results returned from the Search API.
For example, to filter on a training job's InputDataConfig
property with a specific channel name and S3Uri
prefix, define the following filters:
-
'{Name:"InputDataConfig.ChannelName", "Operator":"Equals", "Value":"train"}',
-
'{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri", "Operator":"Contains", "Value":"mybucket/catdata"}'
Members
- Filters
-
- Required: Yes
- Type: Array of Filter structures
A list of filters. Each filter acts on a property. Filters must contain at least one
Filters
value. For example, aNestedFilters
call might include a filter on thePropertyName
parameter of theInputDataConfig
property:InputDataConfig.DataSource.S3DataSource.S3Uri
. - NestedPropertyName
-
- Required: Yes
- Type: string
The name of the property to use in the nested filters. The value must match a listed property name, such as
InputDataConfig
.
NetworkConfig
Description
Networking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.
Members
- EnableInterContainerTrafficEncryption
-
- Type: boolean
Whether to encrypt all communications between distributed processing jobs. Choose
True
to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer. - EnableNetworkIsolation
-
- Type: boolean
Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
- VpcConfig
-
- Type: VpcConfig structure
Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
NotebookInstanceLifecycleConfigSummary
Description
Provides a summary of a notebook instance lifecycle configuration.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that tells when the lifecycle configuration was created.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that tells when the lifecycle configuration was last modified.
- NotebookInstanceLifecycleConfigArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the lifecycle configuration.
- NotebookInstanceLifecycleConfigName
-
- Required: Yes
- Type: string
The name of the lifecycle configuration.
NotebookInstanceLifecycleHook
Description
Contains the notebook instance lifecycle configuration script.
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 Amazon 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.
Members
- Content
-
- Type: string
A base64-encoded string that contains a shell script for a notebook instance lifecycle configuration.
NotebookInstanceSummary
Description
Provides summary information for an SageMaker notebook instance.
Members
- AdditionalCodeRepositories
-
- Type: Array of strings
An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the notebook instance was created.
- DefaultCodeRepository
-
- Type: string
The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
- InstanceType
-
- Type: string
The type of ML compute instance that the notebook instance is running on.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the notebook instance was last modified.
- NotebookInstanceArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the notebook instance.
- NotebookInstanceLifecycleConfigName
-
- Type: string
The name of a notebook instance lifecycle configuration associated with this notebook instance.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
- NotebookInstanceName
-
- Required: Yes
- Type: string
The name of the notebook instance that you want a summary for.
- NotebookInstanceStatus
-
- Type: string
The status of the notebook instance.
- Url
-
- Type: string
The URL that you use to connect to the Jupyter notebook running in your notebook instance.
NotificationConfiguration
Description
Configures Amazon SNS notifications of available or expiring work items for work teams.
Members
- NotificationTopicArn
-
- Type: string
The ARN for the Amazon SNS topic to which notifications should be published.
ObjectiveStatusCounters
Description
Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.
Members
- Failed
-
- Type: int
The number of training jobs whose final objective metric was not evaluated and used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
- Pending
-
- Type: int
The number of training jobs that are in progress and pending evaluation of their final objective metric.
- Succeeded
-
- Type: int
The number of training jobs whose final objective metric was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
OfflineStoreConfig
Description
The configuration of an OfflineStore
.
Provide an OfflineStoreConfig
in a request to CreateFeatureGroup
to create an OfflineStore
.
To encrypt an OfflineStore
using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId
, in S3StorageConfig
.
Members
- DataCatalogConfig
-
- Type: DataCatalogConfig structure
The meta data of the Glue table that is autogenerated when an
OfflineStore
is created. - DisableGlueTableCreation
-
- Type: boolean
Set to
True
to disable the automatic creation of an Amazon Web Services Glue table when configuring anOfflineStore
. If set toFalse
, Feature Store will name theOfflineStore
Glue table following Athena's naming recommendations.The default value is
False
. - S3StorageConfig
-
- Required: Yes
- Type: S3StorageConfig structure
The Amazon Simple Storage (Amazon S3) location of
OfflineStore
. - TableFormat
-
- Type: string
Format for the offline store table. Supported formats are Glue (Default) and Apache Iceberg.
OfflineStoreStatus
Description
The status of OfflineStore
.
Members
- BlockedReason
-
- Type: string
The justification for why the OfflineStoreStatus is Blocked (if applicable).
- Status
-
- Required: Yes
- Type: string
An
OfflineStore
status.
OidcConfig
Description
Use this parameter to configure your OIDC Identity Provider (IdP).
Members
- AuthenticationRequestExtraParams
-
- Type: Associative array of custom strings keys (AuthenticationRequestExtraParamsKey) to strings
A string to string map of identifiers specific to the custom identity provider (IdP) being used.
- AuthorizationEndpoint
-
- Required: Yes
- Type: string
The OIDC IdP authorization endpoint used to configure your private workforce.
- ClientId
-
- Required: Yes
- Type: string
The OIDC IdP client ID used to configure your private workforce.
- ClientSecret
-
- Required: Yes
- Type: string
The OIDC IdP client secret used to configure your private workforce.
- Issuer
-
- Required: Yes
- Type: string
The OIDC IdP issuer used to configure your private workforce.
- JwksUri
-
- Required: Yes
- Type: string
The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.
- LogoutEndpoint
-
- Required: Yes
- Type: string
The OIDC IdP logout endpoint used to configure your private workforce.
- Scope
-
- Type: string
An array of string identifiers used to refer to the specific pieces of user data or claims that the client application wants to access.
- TokenEndpoint
-
- Required: Yes
- Type: string
The OIDC IdP token endpoint used to configure your private workforce.
- UserInfoEndpoint
-
- Required: Yes
- Type: string
The OIDC IdP user information endpoint used to configure your private workforce.
OidcConfigForResponse
Description
Your OIDC IdP workforce configuration.
Members
- AuthenticationRequestExtraParams
-
- Type: Associative array of custom strings keys (AuthenticationRequestExtraParamsKey) to strings
A string to string map of identifiers specific to the custom identity provider (IdP) being used.
- AuthorizationEndpoint
-
- Type: string
The OIDC IdP authorization endpoint used to configure your private workforce.
- ClientId
-
- Type: string
The OIDC IdP client ID used to configure your private workforce.
- Issuer
-
- Type: string
The OIDC IdP issuer used to configure your private workforce.
- JwksUri
-
- Type: string
The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.
- LogoutEndpoint
-
- Type: string
The OIDC IdP logout endpoint used to configure your private workforce.
- Scope
-
- Type: string
An array of string identifiers used to refer to the specific pieces of user data or claims that the client application wants to access.
- TokenEndpoint
-
- Type: string
The OIDC IdP token endpoint used to configure your private workforce.
- UserInfoEndpoint
-
- Type: string
The OIDC IdP user information endpoint used to configure your private workforce.
OidcMemberDefinition
Description
A list of user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups
, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
Members
- Groups
-
- Type: Array of strings
A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.
OnlineStoreConfig
Description
Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or KMSKeyId
, for at rest data encryption. You can turn OnlineStore
on or off by specifying the EnableOnlineStore
flag at General Assembly.
The default value is False
.
Members
- EnableOnlineStore
-
- Type: boolean
Turn
OnlineStore
off by specifyingFalse
for theEnableOnlineStore
flag. TurnOnlineStore
on by specifyingTrue
for theEnableOnlineStore
flag.The default value is
False
. - SecurityConfig
-
- Type: OnlineStoreSecurityConfig structure
Use to specify KMS Key ID (
KMSKeyId
) for at-rest encryption of yourOnlineStore
. - StorageType
-
- Type: string
Option for different tiers of low latency storage for real-time data retrieval.
-
Standard
: A managed low latency data store for feature groups. -
InMemory
: A managed data store for feature groups that supports very low latency retrieval.
- TtlDuration
-
- Type: TtlDuration structure
Time to live duration, where the record is hard deleted after the expiration time is reached;
ExpiresAt
=EventTime
+TtlDuration
. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
OnlineStoreConfigUpdate
Description
Updates the feature group online store configuration.
Members
- TtlDuration
-
- Type: TtlDuration structure
Time to live duration, where the record is hard deleted after the expiration time is reached;
ExpiresAt
=EventTime
+TtlDuration
. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
OnlineStoreSecurityConfig
Description
The security configuration for OnlineStore
.
Members
- KmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (KMS) key ARN that SageMaker Feature Store uses to encrypt the Amazon S3 objects at rest using Amazon S3 server-side encryption.
The caller (either user or IAM role) of
CreateFeatureGroup
must have below permissions to theOnlineStore
KmsKeyId
:-
"kms:Encrypt"
-
"kms:Decrypt"
-
"kms:DescribeKey"
-
"kms:CreateGrant"
-
"kms:RetireGrant"
-
"kms:ReEncryptFrom"
-
"kms:ReEncryptTo"
-
"kms:GenerateDataKey"
-
"kms:ListAliases"
-
"kms:ListGrants"
-
"kms:RevokeGrant"
The caller (either user or IAM role) to all DataPlane operations (
PutRecord
,GetRecord
,DeleteRecord
) must have the following permissions to theKmsKeyId
:-
"kms:Decrypt"
OptimizationConfig
Description
Settings for an optimization technique that you apply with a model optimization job.
Members
- ModelCompilationConfig
-
- Type: ModelCompilationConfig structure
Settings for the model compilation technique that's applied by a model optimization job.
- ModelQuantizationConfig
-
- Type: ModelQuantizationConfig structure
Settings for the model quantization technique that's applied by a model optimization job.
OptimizationJobModelSource
Description
The location of the source model to optimize with an optimization job.
Members
- S3
-
- Type: OptimizationJobModelSourceS3 structure
The Amazon S3 location of a source model to optimize with an optimization job.
OptimizationJobModelSourceS3
Description
The Amazon S3 location of a source model to optimize with an optimization job.
Members
- ModelAccessConfig
-
- Type: OptimizationModelAccessConfig structure
The access configuration settings for the source ML model for an optimization job, where you can accept the model end-user license agreement (EULA).
- S3Uri
-
- Type: string
An Amazon S3 URI that locates a source model to optimize with an optimization job.
OptimizationJobOutputConfig
Description
Details for where to store the optimized model that you create with the optimization job.
Members
- KmsKeyId
-
- Type: string
The Amazon Resource Name (ARN) of a key in Amazon Web Services KMS. SageMaker uses they key to encrypt the artifacts of the optimized model when SageMaker uploads the model to Amazon S3.
- S3OutputLocation
-
- Required: Yes
- Type: string
The Amazon S3 URI for where to store the optimized model that you create with an optimization job.
OptimizationJobSummary
Description
Summarizes an optimization job by providing some of its key properties.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when you created the optimization job.
- DeploymentInstanceType
-
- Required: Yes
- Type: string
The type of instance that hosts the optimized model that you create with the optimization job.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the optimization job was last updated.
- OptimizationEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the optimization job finished processing.
- OptimizationJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the optimization job.
- OptimizationJobName
-
- Required: Yes
- Type: string
The name that you assigned to the optimization job.
- OptimizationJobStatus
-
- Required: Yes
- Type: string
The current status of the optimization job.
- OptimizationStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the optimization job started.
- OptimizationTypes
-
- Required: Yes
- Type: Array of strings
The optimization techniques that are applied by the optimization job.
OptimizationModelAccessConfig
Description
The access configuration settings for the source ML model for an optimization job, where you can accept the model end-user license agreement (EULA).
Members
- AcceptEula
-
- Required: Yes
- Type: boolean
Specifies agreement to the model end-user license agreement (EULA). The
AcceptEula
value must be explicitly defined asTrue
in order to accept the EULA that this model requires. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
OptimizationOutput
Description
Output values produced by an optimization job.
Members
- RecommendedInferenceImage
-
- Type: string
The image that SageMaker recommends that you use to host the optimized model that you created with an optimization job.
OptimizationVpcConfig
Description
A VPC in Amazon VPC that's accessible to an optimized that you create with an optimization job. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
Members
- SecurityGroupIds
-
- Required: Yes
- Type: Array of strings
The VPC security group IDs, in the form
sg-xxxxxxxx
. Specify the security groups for the VPC that is specified in theSubnets
field. - Subnets
-
- Required: Yes
- Type: Array of strings
The ID of the subnets in the VPC to which you want to connect your optimized model.
OutputConfig
Description
Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice
and TargetPlatform
are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice
list, use TargetPlatform
to describe the platform of your edge device and CompilerOptions
if there are specific settings that are required or recommended to use for particular TargetPlatform.
Members
- CompilerOptions
-
- Type: string
Specifies additional parameters for compiler options in JSON format. The compiler options are
TargetPlatform
specific. It is required for NVIDIA accelerators and highly recommended for CPU compilations. For any other cases, it is optional to specifyCompilerOptions.
-
DTYPE
: Specifies the data type for the input. When compiling forml_*
(except forml_inf
) instances using PyTorch framework, provide the data type (dtype) of the model's input."float32"
is used if"DTYPE"
is not specified. Options for data type are:-
float32: Use either
"float"
or"float32"
. -
int64: Use either
"int64"
or"long"
.
For example,
{"dtype" : "float32"}
. -
-
CPU
: Compilation for CPU supports the following compiler options.-
mcpu
: CPU micro-architecture. For example,{'mcpu': 'skylake-avx512'}
-
mattr
: CPU flags. For example,{'mattr': ['+neon', '+vfpv4']}
-
-
ARM
: Details of ARM CPU compilations.-
NEON
: NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors.For example, add
{'mattr': ['+neon']}
to the compiler options if compiling for ARM 32-bit platform with the NEON support.
-
-
NVIDIA
: Compilation for NVIDIA GPU supports the following compiler options.-
gpu_code
: Specifies the targeted architecture. -
trt-ver
: Specifies the TensorRT versions in x.y.z. format. -
cuda-ver
: Specifies the CUDA version in x.y format.
For example,
{'gpu-code': 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver': '10.1'}
-
-
ANDROID
: Compilation for the Android OS supports the following compiler options:-
ANDROID_PLATFORM
: Specifies the Android API levels. Available levels range from 21 to 29. For example,{'ANDROID_PLATFORM': 28}
. -
mattr
: Add{'mattr': ['+neon']}
to compiler options if compiling for ARM 32-bit platform with NEON support.
-
-
INFERENTIA
: Compilation for target ml_inf1 uses compiler options passed in as a JSON string. For example,"CompilerOptions": "\"--verbose 1 --num-neuroncores 2 -O2\""
.For information about supported compiler options, see Neuron Compiler CLI Reference Guide.
-
CoreML
: Compilation for the CoreML OutputConfigTargetDevice
supports the following compiler options:-
class_labels
: Specifies the classification labels file name inside input tar.gz file. For example,{"class_labels": "imagenet_labels_1000.txt"}
. Labels inside the txt file should be separated by newlines.
-
-
EIA
: Compilation for the Elastic Inference Accelerator supports the following compiler options:-
precision_mode
: Specifies the precision of compiled artifacts. Supported values are"FP16"
and"FP32"
. Default is"FP32"
. -
signature_def_key
: Specifies the signature to use for models in SavedModel format. Defaults is TensorFlow's default signature def key. -
output_names
: Specifies a list of output tensor names for models in FrozenGraph format. Set at most one API field, either:signature_def_key
oroutput_names
.
For example:
{"precision_mode": "FP32", "output_names": ["output:0"]}
-
- KmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker uses to encrypt your output models with Amazon S3 server-side encryption after compilation job. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
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
- S3OutputLocation
-
- Required: Yes
- Type: string
Identifies the S3 bucket where you want Amazon SageMaker to store the model artifacts. For example,
s3://bucket-name/key-name-prefix
. - TargetDevice
-
- Type: string
Identifies the target device or the machine learning instance that you want to run your model on after the compilation has completed. Alternatively, you can specify OS, architecture, and accelerator using TargetPlatform fields. It can be used instead of
TargetPlatform
.Currently
ml_trn1
is available only in US East (N. Virginia) Region, andml_inf2
is available only in US East (Ohio) Region. - TargetPlatform
-
- Type: TargetPlatform structure
Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of
TargetDevice
.The following examples show how to configure the
TargetPlatform
andCompilerOptions
JSON strings for popular target platforms:-
Raspberry Pi 3 Model B+
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM_EABIHF"},
"CompilerOptions": {'mattr': ['+neon']}
-
Jetson TX2
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "NVIDIA"},
"CompilerOptions": {'gpu-code': 'sm_62', 'trt-ver': '6.0.1', 'cuda-ver': '10.0'}
-
EC2 m5.2xlarge instance OS
"TargetPlatform": {"Os": "LINUX", "Arch": "X86_64", "Accelerator": "NVIDIA"},
"CompilerOptions": {'mcpu': 'skylake-avx512'}
-
RK3399
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "MALI"}
-
ARMv7 phone (CPU)
"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM_EABI"},
"CompilerOptions": {'ANDROID_PLATFORM': 25, 'mattr': ['+neon']}
-
ARMv8 phone (CPU)
"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM64"},
"CompilerOptions": {'ANDROID_PLATFORM': 29}
OutputDataConfig
Description
Provides information about how to store model training results (model artifacts).
Members
- CompressionType
-
- Type: string
The model output compression type. Select
None
to output an uncompressed model, recommended for large model outputs. Defaults to gzip. - KmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The
KmsKeyId
can be any of the following formats:-
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
-
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
-
// KMS Key Alias
"alias/ExampleAlias"
-
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call
kms:Encrypt
. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide. If the output data is stored in Amazon S3 Express One Zone, it is encrypted with server-side encryption with Amazon S3 managed keys (SSE-S3). KMS key is not supported for Amazon S3 Express One ZoneThe KMS key policy must grant permission to the IAM role that you specify in your
CreateTrainingJob
,CreateTransformJob
, orCreateHyperParameterTuningJob
requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide. - S3OutputPath
-
- Required: Yes
- Type: string
Identifies the S3 path where you want SageMaker to store the model artifacts. For example,
s3://bucket-name/key-name-prefix
.
OutputParameter
Description
An output parameter of a pipeline step.
Members
- Name
-
- Required: Yes
- Type: string
The name of the output parameter.
- Value
-
- Required: Yes
- Type: string
The value of the output parameter.
OwnershipSettings
Description
The collection of ownership settings for a space.
Members
- OwnerUserProfileName
-
- Required: Yes
- Type: string
The user profile who is the owner of the space.
OwnershipSettingsSummary
Description
Specifies summary information about the ownership settings.
Members
- OwnerUserProfileName
-
- Type: string
The user profile who is the owner of the space.
ParallelismConfiguration
Description
Configuration that controls the parallelism of the pipeline. By default, the parallelism configuration specified applies to all executions of the pipeline unless overridden.
Members
- MaxParallelExecutionSteps
-
- Required: Yes
- Type: int
The max number of steps that can be executed in parallel.
Parameter
Description
Assigns a value to a named Pipeline parameter.
Members
- Name
-
- Required: Yes
- Type: string
The name of the parameter to assign a value to. This parameter name must match a named parameter in the pipeline definition.
- Value
-
- Required: Yes
- Type: string
The literal value for the parameter.
ParameterRange
Description
Defines the possible values for categorical, continuous, and integer hyperparameters to be used by an algorithm.
Members
- CategoricalParameterRangeSpecification
-
- Type: CategoricalParameterRangeSpecification structure
A
CategoricalParameterRangeSpecification
object that defines the possible values for a categorical hyperparameter. - ContinuousParameterRangeSpecification
-
- Type: ContinuousParameterRangeSpecification structure
A
ContinuousParameterRangeSpecification
object that defines the possible values for a continuous hyperparameter. - IntegerParameterRangeSpecification
-
- Type: IntegerParameterRangeSpecification structure
A
IntegerParameterRangeSpecification
object that defines the possible values for an integer hyperparameter.
ParameterRanges
Description
Specifies ranges of integer, continuous, and categorical hyperparameters that a hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs with hyperparameter values within these ranges to find the combination of values that result in the training job with the best performance as measured by the objective metric of the hyperparameter tuning job.
The maximum number of items specified for Array Members
refers to the maximum number of hyperparameters for each range and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of hyperparameters for all the ranges can't exceed the maximum number specified.
Members
- AutoParameters
-
- Type: Array of AutoParameter structures
A list containing hyperparameter names and example values to be used by Autotune to determine optimal ranges for your tuning job.
- CategoricalParameterRanges
-
- Type: Array of CategoricalParameterRange structures
The array of CategoricalParameterRange objects that specify ranges of categorical hyperparameters that a hyperparameter tuning job searches.
- ContinuousParameterRanges
-
- Type: Array of ContinuousParameterRange structures
The array of ContinuousParameterRange objects that specify ranges of continuous hyperparameters that a hyperparameter tuning job searches.
- IntegerParameterRanges
-
- Type: Array of IntegerParameterRange structures
The array of IntegerParameterRange objects that specify ranges of integer hyperparameters that a hyperparameter tuning job searches.
Parent
Description
The trial that a trial component is associated with and the experiment the trial is part of. A component might not be associated with a trial. A component can be associated with multiple trials.
Members
- ExperimentName
-
- Type: string
The name of the experiment.
- TrialName
-
- Type: string
The name of the trial.
ParentHyperParameterTuningJob
Description
A previously completed or stopped hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
Members
- HyperParameterTuningJobName
-
- Type: string
The name of the hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
PendingDeploymentSummary
Description
The summary of an in-progress deployment when an endpoint is creating or updating with a new endpoint configuration.
Members
- EndpointConfigName
-
- Required: Yes
- Type: string
The name of the endpoint configuration used in the deployment.
- ProductionVariants
-
- Type: Array of PendingProductionVariantSummary structures
An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint for the in-progress deployment.
- ShadowProductionVariants
-
- Type: Array of PendingProductionVariantSummary structures
An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint in shadow mode with production traffic replicated from the model specified on
ProductionVariants
for the in-progress deployment. - StartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The start time of the deployment.
PendingProductionVariantSummary
Description
The production variant summary for a deployment when an endpoint is creating or updating with the CreateEndpoint or UpdateEndpoint operations. Describes the VariantStatus
, weight and capacity for a production variant associated with an endpoint.
Members
- AcceleratorType
-
- Type: string
The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
- CurrentInstanceCount
-
- Type: int
The number of instances associated with the variant.
- CurrentServerlessConfig
-
- Type: ProductionVariantServerlessConfig structure
The serverless configuration for the endpoint.
- CurrentWeight
-
- Type: float
The weight associated with the variant.
- DeployedImages
-
- Type: Array of DeployedImage structures
An array of
DeployedImage
objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of thisProductionVariant
. - DesiredInstanceCount
-
- Type: int
The number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
- DesiredServerlessConfig
-
- Type: ProductionVariantServerlessConfig structure
The serverless configuration requested for this deployment, as specified in the endpoint configuration for the endpoint.
- DesiredWeight
-
- Type: float
The requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
- InstanceType
-
- Type: string
The type of instances associated with the variant.
- ManagedInstanceScaling
-
- Type: ProductionVariantManagedInstanceScaling structure
Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
- RoutingConfig
-
- Type: ProductionVariantRoutingConfig structure
Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
- VariantName
-
- Required: Yes
- Type: string
The name of the variant.
- VariantStatus
-
- Type: Array of ProductionVariantStatus structures
The endpoint variant status which describes the current deployment stage status or operational status.
Phase
Description
Defines the traffic pattern.
Members
- DurationInSeconds
-
- Type: int
Specifies how long a traffic phase should be. For custom load tests, the value should be between 120 and 3600. This value should not exceed
JobDurationInSeconds
. - InitialNumberOfUsers
-
- Type: int
Specifies how many concurrent users to start with. The value should be between 1 and 3.
- SpawnRate
-
- Type: int
Specified how many new users to spawn in a minute.
Pipeline
Description
A SageMaker Model Building Pipeline instance.
Members
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time of the pipeline.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the pipeline was last modified.
- LastRunTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the pipeline was last run.
- ParallelismConfiguration
-
- Type: ParallelismConfiguration structure
The parallelism configuration applied to the pipeline.
- PipelineArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline.
- PipelineDescription
-
- Type: string
The description of the pipeline.
- PipelineDisplayName
-
- Type: string
The display name of the pipeline.
- PipelineName
-
- Type: string
The name of the pipeline.
- PipelineStatus
-
- Type: string
The status of the pipeline.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the role that created the pipeline.
- Tags
-
- Type: Array of Tag structures
A list of tags that apply to the pipeline.
PipelineDefinitionS3Location
Description
The location of the pipeline definition stored in Amazon S3.
Members
- Bucket
-
- Required: Yes
- Type: string
Name of the S3 bucket.
- ObjectKey
-
- Required: Yes
- Type: string
The object key (or key name) uniquely identifies the object in an S3 bucket.
- VersionId
-
- Type: string
Version Id of the pipeline definition file. If not specified, Amazon SageMaker will retrieve the latest version.
PipelineExecution
Description
An execution of a pipeline.
Members
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time of the pipeline execution.
- FailureReason
-
- Type: string
If the execution failed, a message describing why.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the pipeline execution was last modified.
- ParallelismConfiguration
-
- Type: ParallelismConfiguration structure
The parallelism configuration applied to the pipeline execution.
- PipelineArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline that was executed.
- PipelineExecutionArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
- PipelineExecutionDescription
-
- Type: string
The description of the pipeline execution.
- PipelineExecutionDisplayName
-
- Type: string
The display name of the pipeline execution.
- PipelineExecutionStatus
-
- Type: string
The status of the pipeline status.
- PipelineExperimentConfig
-
- Type: PipelineExperimentConfig structure
Specifies the names of the experiment and trial created by a pipeline.
- PipelineParameters
-
- Type: Array of Parameter structures
Contains a list of pipeline parameters. This list can be empty.
- SelectiveExecutionConfig
-
- Type: SelectiveExecutionConfig structure
The selective execution configuration applied to the pipeline run.
PipelineExecutionStep
Description
An execution of a step in a pipeline.
Members
- AttemptCount
-
- Type: int
The current attempt of the execution step. For more information, see Retry Policy for SageMaker Pipelines steps.
- CacheHitResult
-
- Type: CacheHitResult structure
If this pipeline execution step was cached, details on the cache hit.
- EndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the step stopped executing.
- FailureReason
-
- Type: string
The reason why the step failed execution. This is only returned if the step failed its execution.
- Metadata
-
- Type: PipelineExecutionStepMetadata structure
Metadata to run the pipeline step.
- SelectiveExecutionResult
-
- Type: SelectiveExecutionResult structure
The ARN from an execution of the current pipeline from which results are reused for this step.
- StartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the step started executing.
- StepDescription
-
- Type: string
The description of the step.
- StepDisplayName
-
- Type: string
The display name of the step.
- StepName
-
- Type: string
The name of the step that is executed.
- StepStatus
-
- Type: string
The status of the step execution.
PipelineExecutionStepMetadata
Description
Metadata for a step execution.
Members
- AutoMLJob
-
- Type: AutoMLJobStepMetadata structure
The Amazon Resource Name (ARN) of the AutoML job that was run by this step.
- Callback
-
- Type: CallbackStepMetadata structure
The URL of the Amazon SQS queue used by this step execution, the pipeline generated token, and a list of output parameters.
- ClarifyCheck
-
- Type: ClarifyCheckStepMetadata structure
Container for the metadata for a Clarify check step. The configurations and outcomes of the check step execution. This includes:
-
The type of the check conducted,
-
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
-
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
-
The model package group name provided.
-
The Amazon S3 URI of the violation report if violations detected.
-
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
-
The boolean flags indicating if the drift check is skipped.
-
If step property
BaselineUsedForDriftCheck
is set the same asCalculatedBaseline
.
- Condition
-
- Type: ConditionStepMetadata structure
The outcome of the condition evaluation that was run by this step execution.
- EMR
-
- Type: EMRStepMetadata structure
The configurations and outcomes of an Amazon EMR step execution.
- Endpoint
-
- Type: EndpointStepMetadata structure
The endpoint that was invoked during this step execution.
- EndpointConfig
-
- Type: EndpointConfigStepMetadata structure
The endpoint configuration used to create an endpoint during this step execution.
- Fail
-
- Type: FailStepMetadata structure
The configurations and outcomes of a Fail step execution.
- Lambda
-
- Type: LambdaStepMetadata structure
The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution and a list of output parameters.
- Model
-
- Type: ModelStepMetadata structure
The Amazon Resource Name (ARN) of the model that was created by this step execution.
- ProcessingJob
-
- Type: ProcessingJobStepMetadata structure
The Amazon Resource Name (ARN) of the processing job that was run by this step execution.
- QualityCheck
-
- Type: QualityCheckStepMetadata structure
The configurations and outcomes of the check step execution. This includes:
-
The type of the check conducted.
-
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
-
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
-
The model package group name provided.
-
The Amazon S3 URI of the violation report if violations detected.
-
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
-
The Boolean flags indicating if the drift check is skipped.
-
If step property
BaselineUsedForDriftCheck
is set the same asCalculatedBaseline
.
- RegisterModel
-
- Type: RegisterModelStepMetadata structure
The Amazon Resource Name (ARN) of the model package that the model was registered to by this step execution.
- TrainingJob
-
- Type: TrainingJobStepMetadata structure
The Amazon Resource Name (ARN) of the training job that was run by this step execution.
- TransformJob
-
- Type: TransformJobStepMetadata structure
The Amazon Resource Name (ARN) of the transform job that was run by this step execution.
- TuningJob
-
- Type: TuningJobStepMetaData structure
The Amazon Resource Name (ARN) of the tuning job that was run by this step execution.
PipelineExecutionSummary
Description
A pipeline execution summary.
Members
- PipelineExecutionArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
- PipelineExecutionDescription
-
- Type: string
The description of the pipeline execution.
- PipelineExecutionDisplayName
-
- Type: string
The display name of the pipeline execution.
- PipelineExecutionFailureReason
-
- Type: string
A message generated by SageMaker Pipelines describing why the pipeline execution failed.
- PipelineExecutionStatus
-
- Type: string
The status of the pipeline execution.
- StartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The start time of the pipeline execution.
PipelineExperimentConfig
Description
Specifies the names of the experiment and trial created by a pipeline.
Members
- ExperimentName
-
- Type: string
The name of the experiment.
- TrialName
-
- Type: string
The name of the trial.
PipelineSummary
Description
A summary of a pipeline.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time of the pipeline.
- LastExecutionTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last time that a pipeline execution began.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the pipeline was last modified.
- PipelineArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline.
- PipelineDescription
-
- Type: string
The description of the pipeline.
- PipelineDisplayName
-
- Type: string
The display name of the pipeline.
- PipelineName
-
- Type: string
The name of the pipeline.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) that the pipeline used to execute.
PredefinedMetricSpecification
Description
A specification for a predefined metric.
Members
- PredefinedMetricType
-
- Type: string
The metric type. You can only apply SageMaker metric types to SageMaker endpoints.
ProcessingClusterConfig
Description
Configuration for the cluster used to run a processing job.
Members
- InstanceCount
-
- Required: Yes
- Type: int
The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
- InstanceType
-
- Required: Yes
- Type: string
The ML compute instance type for the processing job.
- VolumeKmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job.
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
VolumeKmsKeyId
when using an instance type with local storage.For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
- VolumeSizeInGB
-
- Required: Yes
- Type: int
The size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario.
Certain Nitro-based instances include local storage with a fixed total size, dependent on the instance type. When using these instances for processing, Amazon SageMaker mounts the local instance storage instead of Amazon EBS gp2 storage. You can't request a
VolumeSizeInGB
greater than the total size of the local instance storage.For a list of instance types that support local instance storage, including the total size per instance type, see Instance Store Volumes.
ProcessingFeatureStoreOutput
Description
Configuration for processing job outputs in Amazon SageMaker Feature Store.
Members
- FeatureGroupName
-
- Required: Yes
- Type: string
The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.
ProcessingInput
Description
The inputs for a processing job. The processing input must specify exactly one of either S3Input
or DatasetDefinition
types.
Members
- AppManaged
-
- Type: boolean
When
True
, input operations such as data download are managed natively by the processing job application. WhenFalse
(default), input operations are managed by Amazon SageMaker. - DatasetDefinition
-
- Type: DatasetDefinition structure
Configuration for a Dataset Definition input.
- InputName
-
- Required: Yes
- Type: string
The name for the processing job input.
- S3Input
-
- Type: ProcessingS3Input structure
Configuration for downloading input data from Amazon S3 into the processing container.
ProcessingJob
Description
An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see Process Data and Evaluate Models.
Members
- AppSpecification
-
- Type: AppSpecification structure
Configuration to run a processing job in a specified container image.
- AutoMLJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the AutoML job associated with this processing job.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time the processing job was created.
- Environment
-
- Type: Associative array of custom strings keys (ProcessingEnvironmentKey) to strings
Sets the environment variables in the Docker container.
- ExitMessage
-
- Type: string
A string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
- ExperimentConfig
-
- Type: ExperimentConfig structure
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
- FailureReason
-
- Type: string
A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time the processing job was last modified.
- MonitoringScheduleArn
-
- Type: string
The ARN of a monitoring schedule for an endpoint associated with this processing job.
- NetworkConfig
-
- Type: NetworkConfig structure
Networking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.
- ProcessingEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the processing job ended.
- ProcessingInputs
-
- Type: Array of ProcessingInput structures
List of input configurations for the processing job.
- ProcessingJobArn
-
- Type: string
The ARN of the processing job.
- ProcessingJobName
-
- Type: string
The name of the processing job.
- ProcessingJobStatus
-
- Type: string
The status of the processing job.
- ProcessingOutputConfig
-
- Type: ProcessingOutputConfig structure
Configuration for uploading output from the processing container.
- ProcessingResources
-
- Type: ProcessingResources structure
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
- ProcessingStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the processing job started.
- RoleArn
-
- Type: string
The ARN of the role used to create the processing job.
- StoppingCondition
-
- Type: ProcessingStoppingCondition structure
Configures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
- TrainingJobArn
-
- Type: string
The ARN of the training job associated with this processing job.
ProcessingJobStepMetadata
Description
Metadata for a processing job step.
Members
- Arn
-
- Type: string
The Amazon Resource Name (ARN) of the processing job.
ProcessingJobSummary
Description
Summary of information about a processing job.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the processing job was created.
- ExitMessage
-
- Type: string
An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
- FailureReason
-
- Type: string
A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates the last time the processing job was modified.
- ProcessingEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the processing job completed.
- ProcessingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the processing job..
- ProcessingJobName
-
- Required: Yes
- Type: string
The name of the processing job.
- ProcessingJobStatus
-
- Required: Yes
- Type: string
The status of the processing job.
ProcessingOutput
Description
Describes the results of a processing job. The processing output must specify exactly one of either S3Output
or FeatureStoreOutput
types.
Members
- AppManaged
-
- Type: boolean
When
True
, output operations such as data upload are managed natively by the processing job application. WhenFalse
(default), output operations are managed by Amazon SageMaker. - FeatureStoreOutput
-
- Type: ProcessingFeatureStoreOutput structure
Configuration for processing job outputs in Amazon SageMaker Feature Store. This processing output type is only supported when
AppManaged
is specified. - OutputName
-
- Required: Yes
- Type: string
The name for the processing job output.
- S3Output
-
- Type: ProcessingS3Output structure
Configuration for processing job outputs in Amazon S3.
ProcessingOutputConfig
Description
Configuration for uploading output from the processing container.
Members
- KmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the processing job output.
KmsKeyId
can be an ID of a KMS key, ARN of a KMS key, alias of a KMS key, or alias of a KMS key. TheKmsKeyId
is applied to all outputs. - Outputs
-
- Required: Yes
- Type: Array of ProcessingOutput structures
An array of outputs configuring the data to upload from the processing container.
ProcessingResources
Description
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
Members
- ClusterConfig
-
- Required: Yes
- Type: ProcessingClusterConfig structure
The configuration for the resources in a cluster used to run the processing job.
ProcessingS3Input
Description
Configuration for downloading input data from Amazon S3 into the processing container.
Members
- LocalPath
-
- Type: string
The local path in your container where you want Amazon SageMaker to write input data to.
LocalPath
is an absolute path to the input data and must begin with/opt/ml/processing/
.LocalPath
is a required parameter whenAppManaged
isFalse
(default). - S3CompressionType
-
- Type: string
Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container.
Gzip
can only be used whenPipe
mode is specified as theS3InputMode
. InPipe
mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume. - S3DataDistributionType
-
- Type: string
Whether to distribute the data from Amazon S3 to all processing instances with
FullyReplicated
, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance. - S3DataType
-
- Required: Yes
- Type: string
Whether you use an
S3Prefix
or aManifestFile
for the data type. If you chooseS3Prefix
,S3Uri
identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you chooseManifestFile
,S3Uri
identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job. - S3InputMode
-
- Type: string
Whether to use
File
orPipe
input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. InPipe
mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume. - S3Uri
-
- Required: Yes
- Type: string
The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.
ProcessingS3Output
Description
Configuration for uploading output data to Amazon S3 from the processing container.
Members
- LocalPath
-
- Type: string
The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3.
LocalPath
is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container's entrypoint is invoked. - S3UploadMode
-
- Required: Yes
- Type: string
Whether to upload the results of the processing job continuously or after the job completes.
- S3Uri
-
- Required: Yes
- Type: string
A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.
ProcessingStoppingCondition
Description
Configures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.
Members
- MaxRuntimeInSeconds
-
- Required: Yes
- Type: int
Specifies the maximum runtime in seconds.
ProductionVariant
Description
Identifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic among the models by specifying variant weights. For more information on production variants, check Production variants.
Members
- AcceleratorType
-
- Type: string
The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
- ContainerStartupHealthCheckTimeoutInSeconds
-
- Type: int
The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
- CoreDumpConfig
-
- Type: ProductionVariantCoreDumpConfig structure
Specifies configuration for a core dump from the model container when the process crashes.
- EnableSSMAccess
-
- Type: boolean
You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoint. You can turn on or turn off SSM access for a production variant behind an existing endpoint by creating a new endpoint configuration and calling
UpdateEndpoint
. - InferenceAmiVersion
-
- Type: string
Specifies an option from a collection of preconfigured Amazon Machine Image (AMI) images. Each image is configured by Amazon Web Services with a set of software and driver versions. Amazon Web Services optimizes these configurations for different machine learning workloads.
By selecting an AMI version, you can ensure that your inference environment is compatible with specific software requirements, such as CUDA driver versions, Linux kernel versions, or Amazon Web Services Neuron driver versions.
The AMI version names, and their configurations, are the following:
- al2-ami-sagemaker-inference-gpu-2
-
-
Accelerator: GPU
-
NVIDIA driver version: 535.54.03
-
CUDA driver version: 12.2
-
Supported instance types: ml.g4dn.*, ml.g5.*, ml.g6.*, ml.p3.*, ml.p4d.*, ml.p4de.*, ml.p5.*
-
- InitialInstanceCount
-
- Type: int
Number of instances to launch initially.
- InitialVariantWeight
-
- Type: float
Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the
VariantWeight
to the sum of allVariantWeight
values across all ProductionVariants. If unspecified, it defaults to 1.0. - InstanceType
-
- Type: string
The ML compute instance type.
- ManagedInstanceScaling
-
- Type: ProductionVariantManagedInstanceScaling structure
Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
- ModelDataDownloadTimeoutInSeconds
-
- Type: int
The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.
- ModelName
-
- Type: string
The name of the model that you want to host. This is the name that you specified when creating the model.
- RoutingConfig
-
- Type: ProductionVariantRoutingConfig structure
Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
- ServerlessConfig
-
- Type: ProductionVariantServerlessConfig structure
The serverless configuration for an endpoint. Specifies a serverless endpoint configuration instead of an instance-based endpoint configuration.
- VariantName
-
- Required: Yes
- Type: string
The name of the production variant.
- VolumeSizeInGB
-
- Type: int
The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currently only Amazon EBS gp2 storage volumes are supported.
ProductionVariantCoreDumpConfig
Description
Specifies configuration for a core dump from the model container when the process crashes.
Members
- DestinationS3Uri
-
- Required: Yes
- Type: string
The Amazon S3 bucket to send the core dump to.
- KmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The
KmsKeyId
can be any of the following formats:-
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
-
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
-
// KMS Key Alias
"alias/ExampleAlias"
-
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call
kms:Encrypt
. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side encryption with KMS-managed keys forOutputDataConfig
. If you use a bucket policy with ans3:PutObject
permission that only allows objects with server-side encryption, set the condition key ofs3:x-amz-server-side-encryption
to"aws:kms"
. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your
CreateEndpoint
andUpdateEndpoint
requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
ProductionVariantManagedInstanceScaling
Description
Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
Members
- MaxInstanceCount
-
- Type: int
The maximum number of instances that the endpoint can provision when it scales up to accommodate an increase in traffic.
- MinInstanceCount
-
- Type: int
The minimum number of instances that the endpoint must retain when it scales down to accommodate a decrease in traffic.
- Status
-
- Type: string
Indicates whether managed instance scaling is enabled.
ProductionVariantRoutingConfig
Description
Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
Members
- RoutingStrategy
-
- Required: Yes
- Type: string
Sets how the endpoint routes incoming traffic:
-
LEAST_OUTSTANDING_REQUESTS
: The endpoint routes requests to the specific instances that have more capacity to process them. -
RANDOM
: The endpoint routes each request to a randomly chosen instance.
ProductionVariantServerlessConfig
Description
Specifies the serverless configuration for an endpoint variant.
Members
- MaxConcurrency
-
- Required: Yes
- Type: int
The maximum number of concurrent invocations your serverless endpoint can process.
- MemorySizeInMB
-
- Required: Yes
- Type: int
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
- ProvisionedConcurrency
-
- Type: int
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to
MaxConcurrency
.This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
ProductionVariantServerlessUpdateConfig
Description
Specifies the serverless update concurrency configuration for an endpoint variant.
Members
- MaxConcurrency
-
- Type: int
The updated maximum number of concurrent invocations your serverless endpoint can process.
- ProvisionedConcurrency
-
- Type: int
The updated amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to
MaxConcurrency
.
ProductionVariantStatus
Description
Describes the status of the production variant.
Members
- StartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The start time of the current status change.
- Status
-
- Required: Yes
- Type: string
The endpoint variant status which describes the current deployment stage status or operational status.
-
Creating
: Creating inference resources for the production variant. -
Deleting
: Terminating inference resources for the production variant. -
Updating
: Updating capacity for the production variant. -
ActivatingTraffic
: Turning on traffic for the production variant. -
Baking
: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.
- StatusMessage
-
- Type: string
A message that describes the status of the production variant.
ProductionVariantSummary
Description
Describes weight and capacities for a production variant associated with an endpoint. If you sent a request to the UpdateEndpointWeightsAndCapacities
API and the endpoint status is Updating
, you get different desired and current values.
Members
- CurrentInstanceCount
-
- Type: int
The number of instances associated with the variant.
- CurrentServerlessConfig
-
- Type: ProductionVariantServerlessConfig structure
The serverless configuration for the endpoint.
- CurrentWeight
-
- Type: float
The weight associated with the variant.
- DeployedImages
-
- Type: Array of DeployedImage structures
An array of
DeployedImage
objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of thisProductionVariant
. - DesiredInstanceCount
-
- Type: int
The number of instances requested in the
UpdateEndpointWeightsAndCapacities
request. - DesiredServerlessConfig
-
- Type: ProductionVariantServerlessConfig structure
The serverless configuration requested for the endpoint update.
- DesiredWeight
-
- Type: float
The requested weight, as specified in the
UpdateEndpointWeightsAndCapacities
request. - ManagedInstanceScaling
-
- Type: ProductionVariantManagedInstanceScaling structure
Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
- RoutingConfig
-
- Type: ProductionVariantRoutingConfig structure
Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
- VariantName
-
- Required: Yes
- Type: string
The name of the variant.
- VariantStatus
-
- Type: Array of ProductionVariantStatus structures
The endpoint variant status which describes the current deployment stage status or operational status.
ProfilerConfig
Description
Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
Members
- DisableProfiler
-
- Type: boolean
Configuration to turn off Amazon SageMaker Debugger's system monitoring and profiling functionality. To turn it off, set to
True
. - ProfilingIntervalInMilliseconds
-
- Type: long (int|float)
A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
- ProfilingParameters
-
- Type: Associative array of custom strings keys (ConfigKey) to strings
Configuration information for capturing framework metrics. Available key strings for different profiling options are
DetailedProfilingConfig
,PythonProfilingConfig
, andDataLoaderProfilingConfig
. The following codes are configuration structures for theProfilingParameters
parameter. To learn more about how to configure theProfilingParameters
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job. - S3OutputPath
-
- Type: string
Path to Amazon S3 storage location for system and framework metrics.
ProfilerConfigForUpdate
Description
Configuration information for updating the Amazon SageMaker Debugger profile parameters, system and framework metrics configurations, and storage paths.
Members
- DisableProfiler
-
- Type: boolean
To turn off Amazon SageMaker Debugger monitoring and profiling while a training job is in progress, set to
True
. - ProfilingIntervalInMilliseconds
-
- Type: long (int|float)
A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
- ProfilingParameters
-
- Type: Associative array of custom strings keys (ConfigKey) to strings
Configuration information for capturing framework metrics. Available key strings for different profiling options are
DetailedProfilingConfig
,PythonProfilingConfig
, andDataLoaderProfilingConfig
. The following codes are configuration structures for theProfilingParameters
parameter. To learn more about how to configure theProfilingParameters
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job. - S3OutputPath
-
- Type: string
Path to Amazon S3 storage location for system and framework metrics.
ProfilerRuleConfiguration
Description
Configuration information for profiling rules.
Members
- InstanceType
-
- Type: string
The instance type to deploy a custom rule for profiling a training job.
- LocalPath
-
- Type: string
Path to local storage location for output of rules. Defaults to
/opt/ml/processing/output/rule/
. - RuleConfigurationName
-
- Required: Yes
- Type: string
The name of the rule configuration. It must be unique relative to other rule configuration names.
- RuleEvaluatorImage
-
- Required: Yes
- Type: string
The Amazon Elastic Container Registry Image for the managed rule evaluation.
- RuleParameters
-
- Type: Associative array of custom strings keys (ConfigKey) to strings
Runtime configuration for rule container.
- S3OutputPath
-
- Type: string
Path to Amazon S3 storage location for rules.
- VolumeSizeInGB
-
- Type: int
The size, in GB, of the ML storage volume attached to the processing instance.
ProfilerRuleEvaluationStatus
Description
Information about the status of the rule evaluation.
Members
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Timestamp when the rule evaluation status was last modified.
- RuleConfigurationName
-
- Type: string
The name of the rule configuration.
- RuleEvaluationJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the rule evaluation job.
- RuleEvaluationStatus
-
- Type: string
Status of the rule evaluation.
- StatusDetails
-
- Type: string
Details from the rule evaluation.
Project
Description
The properties of a project as returned by the Search API.
Members
- CreatedBy
-
- Type: UserContext structure
Who created the project.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp specifying when the project was created.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp container for when the project was last modified.
- ProjectArn
-
- Type: string
The Amazon Resource Name (ARN) of the project.
- ProjectDescription
-
- Type: string
The description of the project.
- ProjectId
-
- Type: string
The ID of the project.
- ProjectName
-
- Type: string
The name of the project.
- ProjectStatus
-
- Type: string
The status of the project.
- ServiceCatalogProvisionedProductDetails
-
- Type: ServiceCatalogProvisionedProductDetails structure
Details of a provisioned service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
- ServiceCatalogProvisioningDetails
-
- Type: ServiceCatalogProvisioningDetails structure
Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
ProjectSummary
Description
Information about a project.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the project was created.
- ProjectArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the project.
- ProjectDescription
-
- Type: string
The description of the project.
- ProjectId
-
- Required: Yes
- Type: string
The ID of the project.
- ProjectName
-
- Required: Yes
- Type: string
The name of the project.
- ProjectStatus
-
- Required: Yes
- Type: string
The status of the project.
PropertyNameQuery
Description
Part of the SuggestionQuery
type. Specifies a hint for retrieving property names that begin with the specified text.
Members
- PropertyNameHint
-
- Required: Yes
- Type: string
Text that begins a property's name.
PropertyNameSuggestion
Description
A property name returned from a GetSearchSuggestions
call that specifies a value in the PropertyNameQuery
field.
Members
- PropertyName
-
- Type: string
A suggested property name based on what you entered in the search textbox in the SageMaker console.
ProvisioningParameter
Description
A key value pair used when you provision a project as a service catalog product. For information, see What is Amazon Web Services Service Catalog.
Members
- Key
-
- Type: string
The key that identifies a provisioning parameter.
- Value
-
- Type: string
The value of the provisioning parameter.
PublicWorkforceTaskPrice
Description
Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
Use one of the following prices for bounding box tasks. Prices are in US dollars and should be based on the complexity of the task; the longer it takes in your initial testing, the more you should offer.
-
0.036
-
0.048
-
0.060
-
0.072
-
0.120
-
0.240
-
0.360
-
0.480
-
0.600
-
0.720
-
0.840
-
0.960
-
1.080
-
1.200
Use one of the following prices for image classification, text classification, and custom tasks. Prices are in US dollars.
-
0.012
-
0.024
-
0.036
-
0.048
-
0.060
-
0.072
-
0.120
-
0.240
-
0.360
-
0.480
-
0.600
-
0.720
-
0.840
-
0.960
-
1.080
-
1.200
Use one of the following prices for semantic segmentation tasks. Prices are in US dollars.
-
0.840
-
0.960
-
1.080
-
1.200
Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI review tasks. Prices are in US dollars.
-
2.400
-
2.280
-
2.160
-
2.040
-
1.920
-
1.800
-
1.680
-
1.560
-
1.440
-
1.320
-
1.200
-
1.080
-
0.960
-
0.840
-
0.720
-
0.600
-
0.480
-
0.360
-
0.240
-
0.120
-
0.072
-
0.060
-
0.048
-
0.036
-
0.024
-
0.012
Use one of the following prices for Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are in US dollars.
-
1.200
-
1.080
-
0.960
-
0.840
-
0.720
-
0.600
-
0.480
-
0.360
-
0.240
-
0.120
-
0.072
-
0.060
-
0.048
-
0.036
-
0.024
-
0.012
Use one of the following prices for Amazon Augmented AI custom human review tasks. Prices are in US dollars.
-
1.200
-
1.080
-
0.960
-
0.840
-
0.720
-
0.600
-
0.480
-
0.360
-
0.240
-
0.120
-
0.072
-
0.060
-
0.048
-
0.036
-
0.024
-
0.012
Members
- AmountInUsd
-
- Type: USD structure
Defines the amount of money paid to an Amazon Mechanical Turk worker in United States dollars.
QualityCheckStepMetadata
Description
Container for the metadata for a Quality check step. For more information, see the topic on QualityCheck step in the Amazon SageMaker Developer Guide.
Members
- BaselineUsedForDriftCheckConstraints
-
- Type: string
The Amazon S3 URI of the baseline constraints file used for the drift check.
- BaselineUsedForDriftCheckStatistics
-
- Type: string
The Amazon S3 URI of the baseline statistics file used for the drift check.
- CalculatedBaselineConstraints
-
- Type: string
The Amazon S3 URI of the newly calculated baseline constraints file.
- CalculatedBaselineStatistics
-
- Type: string
The Amazon S3 URI of the newly calculated baseline statistics file.
- CheckJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the Quality check processing job that was run by this step execution.
- CheckType
-
- Type: string
The type of the Quality check step.
- ModelPackageGroupName
-
- Type: string
The model package group name.
- RegisterNewBaseline
-
- Type: boolean
This flag indicates if a newly calculated baseline can be accessed through step properties
BaselineUsedForDriftCheckConstraints
andBaselineUsedForDriftCheckStatistics
. If it is set toFalse
, the previous baseline of the configured check type must also be available. These can be accessed through theBaselineUsedForDriftCheckConstraints
andBaselineUsedForDriftCheckStatistics
properties. - SkipCheck
-
- Type: boolean
This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to
False
, the previous baseline of the configured check type must be available. - ViolationReport
-
- Type: string
The Amazon S3 URI of violation report if violations are detected.
QueryFilters
Description
A set of filters to narrow the set of lineage entities connected to the StartArn
(s) returned by the QueryLineage
API action.
Members
- CreatedAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filter the lineage entities connected to the
StartArn
(s) after the create date. - CreatedBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filter the lineage entities connected to the
StartArn
(s) by created date. - LineageTypes
-
- Type: Array of strings
Filter the lineage entities connected to the
StartArn
(s) by the type of the lineage entity. - ModifiedAfter
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filter the lineage entities connected to the
StartArn
(s) after the last modified date. - ModifiedBefore
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Filter the lineage entities connected to the
StartArn
(s) before the last modified date. - Properties
-
- Type: Associative array of custom strings keys (String256) to strings
Filter the lineage entities connected to the
StartArn
(s) by a set if property key value pairs. If multiple pairs are provided, an entity is included in the results if it matches any of the provided pairs. - Types
-
- Type: Array of strings
Filter the lineage entities connected to the
StartArn
by type. For example:DataSet
,Model
,Endpoint
, orModelDeployment
.
RSessionAppSettings
Description
A collection of settings that apply to an RSessionGateway
app.
Members
- CustomImages
-
- Type: Array of CustomImage structures
A list of custom SageMaker images that are configured to run as a RSession app.
- DefaultResourceSpec
-
- Type: ResourceSpec structure
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
RStudioServerProAppSettings
Description
A collection of settings that configure user interaction with the RStudioServerPro
app.
Members
- AccessStatus
-
- Type: string
Indicates whether the current user has access to the
RStudioServerPro
app. - UserGroup
-
- Type: string
The level of permissions that the user has within the
RStudioServerPro
app. This value defaults to `User`. The `Admin` value allows the user access to the RStudio Administrative Dashboard.
RStudioServerProDomainSettings
Description
A collection of settings that configure the RStudioServerPro
Domain-level app.
Members
- DefaultResourceSpec
-
- Type: ResourceSpec structure
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
- DomainExecutionRoleArn
-
- Required: Yes
- Type: string
The ARN of the execution role for the
RStudioServerPro
Domain-level app. - RStudioConnectUrl
-
- Type: string
A URL pointing to an RStudio Connect server.
- RStudioPackageManagerUrl
-
- Type: string
A URL pointing to an RStudio Package Manager server.
RStudioServerProDomainSettingsForUpdate
Description
A collection of settings that update the current configuration for the RStudioServerPro
Domain-level app.
Members
- DefaultResourceSpec
-
- Type: ResourceSpec structure
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
- DomainExecutionRoleArn
-
- Required: Yes
- Type: string
The execution role for the
RStudioServerPro
Domain-level app. - RStudioConnectUrl
-
- Type: string
A URL pointing to an RStudio Connect server.
- RStudioPackageManagerUrl
-
- Type: string
A URL pointing to an RStudio Package Manager server.
RealTimeInferenceConfig
Description
The infrastructure configuration for deploying the model to a real-time inference endpoint.
Members
- InstanceCount
-
- Required: Yes
- Type: int
The number of instances of the type specified by
InstanceType
. - InstanceType
-
- Required: Yes
- Type: string
The instance type the model is deployed to.
RealTimeInferenceRecommendation
Description
The recommended configuration to use for Real-Time Inference.
Members
- Environment
-
- Type: Associative array of custom strings keys (EnvironmentKey) to strings
The recommended environment variables to set in the model container for Real-Time Inference.
- InstanceType
-
- Required: Yes
- Type: string
The recommended instance type for Real-Time Inference.
- RecommendationId
-
- Required: Yes
- Type: string
The recommendation ID which uniquely identifies each recommendation.
RecommendationJobCompiledOutputConfig
Description
Provides information about the output configuration for the compiled model.
Members
- S3OutputUri
-
- Type: string
Identifies the Amazon S3 bucket where you want SageMaker to store the compiled model artifacts.
RecommendationJobContainerConfig
Description
Specifies mandatory fields for running an Inference Recommender job directly in the CreateInferenceRecommendationsJob API. The fields specified in ContainerConfig
override the corresponding fields in the model package. Use ContainerConfig
if you want to specify these fields for the recommendation job but don't want to edit them in your model package.
Members
- DataInputConfig
-
- Type: string
Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. This field is used for optimizing your model using SageMaker Neo. For more information, see DataInputConfig.
- Domain
-
- Type: string
The machine learning domain of the model and its components.
Valid Values:
COMPUTER_VISION | NATURAL_LANGUAGE_PROCESSING | MACHINE_LEARNING
- Framework
-
- Type: string
The machine learning framework of the container image.
Valid Values:
TENSORFLOW | PYTORCH | XGBOOST | SAGEMAKER-SCIKIT-LEARN
- FrameworkVersion
-
- Type: string
The framework version of the container image.
- NearestModelName
-
- Type: string
The name of a pre-trained machine learning model benchmarked by Amazon SageMaker Inference Recommender that matches your model.
Valid Values:
efficientnetb7 | unet | xgboost | faster-rcnn-resnet101 | nasnetlarge | vgg16 | inception-v3 | mask-rcnn | sagemaker-scikit-learn | densenet201-gluon | resnet18v2-gluon | xception | densenet201 | yolov4 | resnet152 | bert-base-cased | xceptionV1-keras | resnet50 | retinanet
- PayloadConfig
-
- Type: RecommendationJobPayloadConfig structure
Specifies the
SamplePayloadUrl
and all other sample payload-related fields. - SupportedEndpointType
-
- Type: string
The endpoint type to receive recommendations for. By default this is null, and the results of the inference recommendation job return a combined list of both real-time and serverless benchmarks. By specifying a value for this field, you can receive a longer list of benchmarks for the desired endpoint type.
- SupportedInstanceTypes
-
- Type: Array of strings
A list of the instance types that are used to generate inferences in real-time.
- SupportedResponseMIMETypes
-
- Type: Array of strings
The supported MIME types for the output data.
- Task
-
- Type: string
The machine learning task that the model accomplishes.
Valid Values:
IMAGE_CLASSIFICATION | OBJECT_DETECTION | TEXT_GENERATION | IMAGE_SEGMENTATION | FILL_MASK | CLASSIFICATION | REGRESSION | OTHER
RecommendationJobInferenceBenchmark
Description
The details for a specific benchmark from an Inference Recommender job.
Members
- EndpointConfiguration
-
- Type: EndpointOutputConfiguration structure
The endpoint configuration made by Inference Recommender during a recommendation job.
- EndpointMetrics
-
- Type: InferenceMetrics structure
The metrics for an existing endpoint compared in an Inference Recommender job.
- FailureReason
-
- Type: string
The reason why a benchmark failed.
- InvocationEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the benchmark completed.
- InvocationStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the benchmark started.
- Metrics
-
- Type: RecommendationMetrics structure
The metrics of recommendations.
- ModelConfiguration
-
- Required: Yes
- Type: ModelConfiguration structure
Defines the model configuration. Includes the specification name and environment parameters.
RecommendationJobInputConfig
Description
The input configuration of the recommendation job.
Members
- ContainerConfig
-
- Type: RecommendationJobContainerConfig structure
Specifies mandatory fields for running an Inference Recommender job. The fields specified in
ContainerConfig
override the corresponding fields in the model package. - EndpointConfigurations
-
- Type: Array of EndpointInputConfiguration structures
Specifies the endpoint configuration to use for a job.
- Endpoints
-
- Type: Array of EndpointInfo structures
Existing customer endpoints on which to run an Inference Recommender job.
- JobDurationInSeconds
-
- Type: int
Specifies the maximum duration of the job, in seconds. The maximum value is 18,000 seconds.
- ModelName
-
- Type: string
The name of the created model.
- ModelPackageVersionArn
-
- Type: string
The Amazon Resource Name (ARN) of a versioned model package.
- ResourceLimit
-
- Type: RecommendationJobResourceLimit structure
Defines the resource limit of the job.
- TrafficPattern
-
- Type: TrafficPattern structure
Specifies the traffic pattern of the job.
- VolumeKmsKeyId
-
- Type: string
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. This key will be passed to SageMaker Hosting for endpoint creation.
The SageMaker execution role must have
kms:CreateGrant
permission in order to encrypt data on the storage volume of the endpoints created for inference recommendation. The inference recommendation job will fail asynchronously during endpoint configuration creation if the role passed does not havekms:CreateGrant
permission.The
KmsKeyId
can be any of the following formats:-
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
-
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"
-
// KMS Key Alias
"alias/ExampleAlias"
-
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
- VpcConfig
-
- Type: RecommendationJobVpcConfig structure
Inference Recommender provisions SageMaker endpoints with access to VPC in the inference recommendation job.
RecommendationJobOutputConfig
Description
Provides information about the output configuration for the compiled model.
Members
- CompiledOutputConfig
-
- Type: RecommendationJobCompiledOutputConfig structure
Provides information about the output configuration for the compiled model.
- KmsKeyId
-
- Type: string
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt your output artifacts with Amazon S3 server-side encryption. The SageMaker execution role must have
kms:GenerateDataKey
permission.The
KmsKeyId
can be any of the following formats:-
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
-
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"
-
// KMS Key Alias
"alias/ExampleAlias"
-
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
RecommendationJobPayloadConfig
Description
The configuration for the payload for a recommendation job.
Members
- SamplePayloadUrl
-
- Type: string
The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
- SupportedContentTypes
-
- Type: Array of strings
The supported MIME types for the input data.
RecommendationJobResourceLimit
Description
Specifies the maximum number of jobs that can run in parallel and the maximum number of jobs that can run.
Members
- MaxNumberOfTests
-
- Type: int
Defines the maximum number of load tests.
- MaxParallelOfTests
-
- Type: int
Defines the maximum number of parallel load tests.
RecommendationJobStoppingConditions
Description
Specifies conditions for stopping a job. When a job reaches a stopping condition limit, SageMaker ends the job.
Members
- FlatInvocations
-
- Type: string
Stops a load test when the number of invocations (TPS) peaks and flattens, which means that the instance has reached capacity. The default value is
Stop
. If you want the load test to continue after invocations have flattened, set the value toContinue
. - MaxInvocations
-
- Type: int
The maximum number of requests per minute expected for the endpoint.
- ModelLatencyThresholds
-
- Type: Array of ModelLatencyThreshold structures
The interval of time taken by a model to respond as viewed from SageMaker. The interval includes the local communication time taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
RecommendationJobVpcConfig
Description
Inference Recommender provisions SageMaker endpoints with access to VPC in the inference recommendation job.
Members
- SecurityGroupIds
-
- Required: Yes
- Type: Array of strings
The VPC security group IDs. IDs have the form of
sg-xxxxxxxx
. Specify the security groups for the VPC that is specified in theSubnets
field. - Subnets
-
- Required: Yes
- Type: Array of strings
The ID of the subnets in the VPC to which you want to connect your model.
RecommendationMetrics
Description
The metrics of recommendations.
Members
- CostPerHour
-
- Type: float
Defines the cost per hour for the instance.
- CostPerInference
-
- Type: float
Defines the cost per inference for the instance .
- CpuUtilization
-
- Type: float
The expected CPU utilization at maximum invocations per minute for the instance.
NaN
indicates that the value is not available. - MaxInvocations
-
- Type: int
The expected maximum number of requests per minute for the instance.
- MemoryUtilization
-
- Type: float
The expected memory utilization at maximum invocations per minute for the instance.
NaN
indicates that the value is not available. - ModelLatency
-
- Type: int
The expected model latency at maximum invocation per minute for the instance.
- ModelSetupTime
-
- Type: int
The time it takes to launch new compute resources for a serverless endpoint. The time can vary depending on the model size, how long it takes to download the model, and the start-up time of the container.
NaN
indicates that the value is not available.
RedshiftDatasetDefinition
Description
Configuration for Redshift Dataset Definition input.
Members
- ClusterId
-
- Required: Yes
- Type: string
The Redshift cluster Identifier.
- ClusterRoleArn
-
- Required: Yes
- Type: string
The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
- Database
-
- Required: Yes
- Type: string
The name of the Redshift database used in Redshift query execution.
- DbUser
-
- Required: Yes
- Type: string
The database user name used in Redshift query execution.
- KmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
- OutputCompression
-
- Type: string
The compression used for Redshift query results.
- OutputFormat
-
- Required: Yes
- Type: string
The data storage format for Redshift query results.
- OutputS3Uri
-
- Required: Yes
- Type: string
The location in Amazon S3 where the Redshift query results are stored.
- QueryString
-
- Required: Yes
- Type: string
The SQL query statements to be executed.
RegisterModelStepMetadata
Description
Metadata for a register model job step.
Members
- Arn
-
- Type: string
The Amazon Resource Name (ARN) of the model package.
RemoteDebugConfig
Description
Configuration for remote debugging for the CreateTrainingJob API. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
Members
- EnableRemoteDebug
-
- Type: boolean
If set to True, enables remote debugging.
RemoteDebugConfigForUpdate
Description
Configuration for remote debugging for the UpdateTrainingJob API. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
Members
- EnableRemoteDebug
-
- Type: boolean
If set to True, enables remote debugging.
RenderableTask
Description
Contains input values for a task.
Members
- Input
-
- Required: Yes
- Type: string
A JSON object that contains values for the variables defined in the template. It is made available to the template under the substitution variable
task.input
. For example, if you define a variabletask.input.text
in your template, you can supply the variable in the JSON object as"text": "sample text"
.
RenderingError
Description
A description of an error that occurred while rendering the template.
Members
- Code
-
- Required: Yes
- Type: string
A unique identifier for a specific class of errors.
- Message
-
- Required: Yes
- Type: string
A human-readable message describing the error.
RepositoryAuthConfig
Description
Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc
as the value for the RepositoryAccessMode
field of the ImageConfig
object that you passed to a call to CreateModel
and the private Docker registry where the model image is hosted requires authentication.
Members
- RepositoryCredentialsProviderArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides credentials to authenticate to the private Docker registry where your model image is hosted. For information about how to create an Amazon Web Services Lambda function, see Create a Lambda function with the console in the Amazon Web Services Lambda Developer Guide.
ResolvedAttributes
Description
The resolved attributes.
Members
- AutoMLJobObjective
-
- Type: AutoMLJobObjective structure
Specifies a metric to minimize or maximize as the objective of an AutoML job.
- CompletionCriteria
-
- Type: AutoMLJobCompletionCriteria structure
How long a job is allowed to run, or how many candidates a job is allowed to generate.
- ProblemType
-
- Type: string
The problem type.
ResourceCatalog
Description
A resource catalog containing all of the resources of a specific resource type within a resource owner account. For an example on sharing the Amazon SageMaker Feature Store DefaultFeatureGroupCatalog
, see Share Amazon SageMaker Catalog resource type in the Amazon SageMaker Developer Guide.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time the
ResourceCatalog
was created. - Description
-
- Required: Yes
- Type: string
A free form description of the
ResourceCatalog
. - ResourceCatalogArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the
ResourceCatalog
. - ResourceCatalogName
-
- Required: Yes
- Type: string
The name of the
ResourceCatalog
.
ResourceConfig
Description
Describes the resources, including machine learning (ML) compute instances and ML storage volumes, to use for model training.
Members
- InstanceCount
-
- Type: int
The number of ML compute instances to use. For distributed training, provide a value greater than 1.
- InstanceGroups
-
- Type: Array of InstanceGroup structures
The configuration of a heterogeneous cluster in JSON format.
- InstanceType
-
- Type: string
The ML compute instance type.
SageMaker Training on Amazon Elastic Compute Cloud (EC2) P4de instances is in preview release starting December 9th, 2022.
Amazon EC2 P4de instances (currently in preview) are powered by 8 NVIDIA A100 GPUs with 80GB high-performance HBM2e GPU memory, which accelerate the speed of training ML models that need to be trained on large datasets of high-resolution data. In this preview release, Amazon SageMaker supports ML training jobs on P4de instances (
ml.p4de.24xlarge
) to reduce model training time. Theml.p4de.24xlarge
instances are available in the following Amazon Web Services Regions.-
US East (N. Virginia) (us-east-1)
-
US West (Oregon) (us-west-2)
To request quota limit increase and start using P4de instances, contact the SageMaker Training service team through your account team.
- KeepAlivePeriodInSeconds
-
- Type: int
The duration of time in seconds to retain configured resources in a warm pool for subsequent training jobs.
- VolumeKmsKeyId
-
- Type: string
The Amazon Web Services KMS key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job.
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
VolumeKmsKeyId
when using an instance type with local storage.For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The
VolumeKmsKeyId
can be in any of the following formats:-
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
-
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
- VolumeSizeInGB
-
- Required: Yes
- Type: int
The size of the ML storage volume that you want to provision.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use the ML storage volume for scratch space. If you want to store the training data in the ML storage volume, choose
File
as theTrainingInputMode
in the algorithm specification.When using an ML instance with NVMe SSD volumes, SageMaker doesn't provision Amazon EBS General Purpose SSD (gp2) storage. Available storage is fixed to the NVMe-type instance's storage capacity. SageMaker configures storage paths for training datasets, checkpoints, model artifacts, and outputs to use the entire capacity of the instance storage. For example, ML instance families with the NVMe-type instance storage include
ml.p4d
,ml.g4dn
, andml.g5
.When using an ML instance with the EBS-only storage option and without instance storage, you must define the size of EBS volume through
VolumeSizeInGB
in theResourceConfig
API. For example, ML instance families that use EBS volumes includeml.c5
andml.p2
.To look up instance types and their instance storage types and volumes, see Amazon EC2 Instance Types.
To find the default local paths defined by the SageMaker training platform, see Amazon SageMaker Training Storage Folders for Training Datasets, Checkpoints, Model Artifacts, and Outputs.
ResourceConfigForUpdate
Description
The ResourceConfig
to update KeepAlivePeriodInSeconds
. Other fields in the ResourceConfig
cannot be updated.
Members
- KeepAlivePeriodInSeconds
-
- Required: Yes
- Type: int
The
KeepAlivePeriodInSeconds
value specified in theResourceConfig
to update.
ResourceInUse
Description
Resource being accessed is in use.
Members
- Message
-
- Type: string
ResourceLimitExceeded
Description
You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
Members
- Message
-
- Type: string
ResourceLimits
Description
Specifies the maximum number of training jobs and parallel training jobs that a hyperparameter tuning job can launch.
Members
- MaxNumberOfTrainingJobs
-
- Type: int
The maximum number of training jobs that a hyperparameter tuning job can launch.
- MaxParallelTrainingJobs
-
- Required: Yes
- Type: int
The maximum number of concurrent training jobs that a hyperparameter tuning job can launch.
- MaxRuntimeInSeconds
-
- Type: int
The maximum time in seconds that a hyperparameter tuning job can run.
ResourceNotFound
Description
Resource being access is not found.
Members
- Message
-
- Type: string
ResourceSpec
Description
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
Members
- InstanceType
-
- Type: string
The instance type that the image version runs on.
JupyterServer apps only support the
system
value.For KernelGateway apps, the
system
value is translated toml.t3.medium
. KernelGateway apps also support all other values for available instance types. - LifecycleConfigArn
-
- Type: string
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
- SageMakerImageArn
-
- Type: string
The ARN of the SageMaker image that the image version belongs to.
- SageMakerImageVersionAlias
-
- Type: string
The SageMakerImageVersionAlias of the image to launch with. This value is in SemVer 2.0.0 versioning format.
- SageMakerImageVersionArn
-
- Type: string
The ARN of the image version created on the instance.
RetentionPolicy
Description
The retention policy for data stored on an Amazon Elastic File System volume.
Members
- HomeEfsFileSystem
-
- Type: string
The default is
Retain
, which specifies to keep the data stored on the Amazon EFS volume.Specify
Delete
to delete the data stored on the Amazon EFS volume.
RetryStrategy
Description
The retry strategy to use when a training job fails due to an InternalServerError
. RetryStrategy
is specified as part of the CreateTrainingJob
and CreateHyperParameterTuningJob
requests. You can add the StoppingCondition
parameter to the request to limit the training time for the complete job.
Members
- MaximumRetryAttempts
-
- Required: Yes
- Type: int
The number of times to retry the job. When the job is retried, it's
SecondaryStatus
is changed toSTARTING
.
RollingUpdatePolicy
Description
Specifies a rolling deployment strategy for updating a SageMaker endpoint.
Members
- MaximumBatchSize
-
- Required: Yes
- Type: CapacitySize structure
Batch size for each rolling step to provision capacity and turn on traffic on the new endpoint fleet, and terminate capacity on the old endpoint fleet. Value must be between 5% to 50% of the variant's total instance count.
- MaximumExecutionTimeoutInSeconds
-
- Type: int
The time limit for the total deployment. Exceeding this limit causes a timeout.
- RollbackMaximumBatchSize
-
- Type: CapacitySize structure
Batch size for rollback to the old endpoint fleet. Each rolling step to provision capacity and turn on traffic on the old endpoint fleet, and terminate capacity on the new endpoint fleet. If this field is absent, the default value will be set to 100% of total capacity which means to bring up the whole capacity of the old fleet at once during rollback.
- WaitIntervalInSeconds
-
- Required: Yes
- Type: int
The length of the baking period, during which SageMaker monitors alarms for each batch on the new fleet.
S3DataSource
Description
Describes the S3 data source.
Your input bucket must be in the same Amazon Web Services region as your training job.
Members
- AttributeNames
-
- Type: Array of strings
A list of one or more attribute names to use that are found in a specified augmented manifest file.
- InstanceGroupNames
-
- Type: Array of strings
A list of names of instance groups that get data from the S3 data source.
- S3DataDistributionType
-
- Type: string
If you want SageMaker to replicate the entire dataset on each ML compute instance that is launched for model training, specify
FullyReplicated
.If you want SageMaker to replicate a subset of data on each ML compute instance that is launched for model training, specify
ShardedByS3Key
. If there are n ML compute instances launched for a training job, each instance gets approximately 1/n of the number of S3 objects. In this case, model training on each machine uses only the subset of training data.Don't choose more ML compute instances for training than available S3 objects. If you do, some nodes won't get any data and you will pay for nodes that aren't getting any training data. This applies in both File and Pipe modes. Keep this in mind when developing algorithms.
In distributed training, where you use multiple ML compute EC2 instances, you might choose
ShardedByS3Key
. If the algorithm requires copying training data to the ML storage volume (whenTrainingInputMode
is set toFile
), this copies 1/n of the number of objects. - S3DataType
-
- Required: Yes
- Type: string
If you choose
S3Prefix
,S3Uri
identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.If you choose
ManifestFile
,S3Uri
identifies an object that is a manifest file containing a list of object keys that you want SageMaker to use for model training.If you choose
AugmentedManifestFile
, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training.AugmentedManifestFile
can only be used if the Channel's input mode isPipe
. - S3Uri
-
- Required: Yes
- Type: string
Depending on the value specified for the
S3DataType
, identifies either a key name prefix or a manifest. For example:-
A key name prefix might look like this:
s3://bucketname/exampleprefix/
-
A manifest might look like this:
s3://bucketname/example.manifest
A manifest is an S3 object which is a JSON file consisting of an array of elements. The first element is a prefix which is followed by one or more suffixes. SageMaker appends the suffix elements to the prefix to get a full set of
S3Uri
. Note that the prefix must be a valid non-emptyS3Uri
that precludes users from specifying a manifest whose individualS3Uri
is sourced from different S3 buckets.The following code example shows a valid manifest format:
[ {"prefix": "s3://customer_bucket/some/prefix/"},
"relative/path/to/custdata-1",
"relative/path/custdata-2",
...
"relative/path/custdata-N"
]
This JSON is equivalent to the following
S3Uri
list:s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of
S3Uri
in this manifest is the input data for the channel for this data source. The object that eachS3Uri
points to must be readable by the IAM role that SageMaker uses to perform tasks on your behalf.
Your input bucket must be located in same Amazon Web Services region as your training job.
S3ModelDataSource
Description
Specifies the S3 location of ML model data to deploy.
Members
- CompressionType
-
- Required: Yes
- Type: string
Specifies how the ML model data is prepared.
If you choose
Gzip
and chooseS3Object
as the value ofS3DataType
,S3Uri
identifies an object that is a gzip-compressed TAR archive. SageMaker will attempt to decompress and untar the object during model deployment.If you choose
None
and choooseS3Object
as the value ofS3DataType
,S3Uri
identifies an object that represents an uncompressed ML model to deploy.If you choose None and choose
S3Prefix
as the value ofS3DataType
,S3Uri
identifies a key name prefix, under which all objects represents the uncompressed ML model to deploy.If you choose None, then SageMaker will follow rules below when creating model data files under /opt/ml/model directory for use by your inference code:
-
If you choose
S3Object
as the value ofS3DataType
, then SageMaker will split the key of the S3 object referenced byS3Uri
by slash (/), and use the last part as the filename of the file holding the content of the S3 object. -
If you choose
S3Prefix
as the value ofS3DataType
, then for each S3 object under the key name pefix referenced byS3Uri
, SageMaker will trim its key by the prefix, and use the remainder as the path (relative to/opt/ml/model
) of the file holding the content of the S3 object. SageMaker will split the remainder by slash (/), using intermediate parts as directory names and the last part as filename of the file holding the content of the S3 object. -
Do not use any of the following as file names or directory names:
-
An empty or blank string
-
A string which contains null bytes
-
A string longer than 255 bytes
-
A single dot (
.
) -
A double dot (
..
)
-
-
Ambiguous file names will result in model deployment failure. For example, if your uncompressed ML model consists of two S3 objects
s3://mybucket/model/weights
ands3://mybucket/model/weights/part1
and you specifys3://mybucket/model/
as the value ofS3Uri
andS3Prefix
as the value ofS3DataType
, then it will result in name clash between/opt/ml/model/weights
(a regular file) and/opt/ml/model/weights/
(a directory). -
Do not organize the model artifacts in S3 console using folders. When you create a folder in S3 console, S3 creates a 0-byte object with a key set to the folder name you provide. They key of the 0-byte object ends with a slash (/) which violates SageMaker restrictions on model artifact file names, leading to model deployment failure.
- HubAccessConfig
-
- Type: InferenceHubAccessConfig structure
Configuration information for hub access.
- ModelAccessConfig
-
- Type: ModelAccessConfig structure
Specifies the access configuration file for the ML model. You can explicitly accept the model end-user license agreement (EULA) within the
ModelAccessConfig
. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model. - S3DataType
-
- Required: Yes
- Type: string
Specifies the type of ML model data to deploy.
If you choose
S3Prefix
,S3Uri
identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix as part of the ML model data to deploy. A valid key name prefix identified byS3Uri
always ends with a forward slash (/).If you choose
S3Object
,S3Uri
identifies an object that is the ML model data to deploy. - S3Uri
-
- Required: Yes
- Type: string
Specifies the S3 path of ML model data to deploy.
S3Presign
Description
This object defines the access restrictions to Amazon S3 resources that are included in custom worker task templates using the Liquid filter, grant_read_access
.
To learn more about how custom templates are created, see Create custom worker task templates.
Members
- IamPolicyConstraints
-
- Type: IamPolicyConstraints structure
Use this parameter to specify the allowed request source. Possible sources are either
SourceIp
orVpcSourceIp
.
S3StorageConfig
Description
The Amazon Simple Storage (Amazon S3) location and security configuration for OfflineStore
.
Members
- KmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (KMS) key ARN of the key used to encrypt any objects written into the
OfflineStore
S3 location.The IAM
roleARN
that is passed as a parameter toCreateFeatureGroup
must have below permissions to theKmsKeyId
:-
"kms:GenerateDataKey"
- ResolvedOutputS3Uri
-
- Type: string
The S3 path where offline records are written.
- S3Uri
-
- Required: Yes
- Type: string
The S3 URI, or location in Amazon S3, of
OfflineStore
.S3 URIs have a format similar to the following:
s3://example-bucket/prefix/
.
ScalingPolicy
Description
An object containing a recommended scaling policy.
Members
- TargetTracking
-
- Type: TargetTrackingScalingPolicyConfiguration structure
A target tracking scaling policy. Includes support for predefined or customized metrics.
ScalingPolicyMetric
Description
The metric for a scaling policy.
Members
- InvocationsPerInstance
-
- Type: int
The number of invocations sent to a model, normalized by
InstanceCount
in each ProductionVariant.1/numberOfInstances
is sent as the value on each request, wherenumberOfInstances
is the number of active instances for the ProductionVariant behind the endpoint at the time of the request. - ModelLatency
-
- Type: int
The interval of time taken by a model to respond as viewed from SageMaker. This interval includes the local communication times taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
ScalingPolicyObjective
Description
An object where you specify the anticipated traffic pattern for an endpoint.
Members
- MaxInvocationsPerMinute
-
- Type: int
The maximum number of expected requests to your endpoint per minute.
- MinInvocationsPerMinute
-
- Type: int
The minimum number of expected requests to your endpoint per minute.
ScheduleConfig
Description
Configuration details about the monitoring schedule.
Members
- DataAnalysisEndTime
-
- Type: string
Sets the end time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the
ScheduleExpression
parameter. Specify this offset in ISO 8601 duration format. For example, if you want to end the window one hour before the start of each monitoring job, you would specify:"-PT1H"
.The end time that you specify must not follow the start time that you specify by more than 24 hours. You specify the start time with the
DataAnalysisStartTime
parameter.If you set
ScheduleExpression
toNOW
, this parameter is required. - DataAnalysisStartTime
-
- Type: string
Sets the start time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the
ScheduleExpression
parameter. Specify this offset in ISO 8601 duration format. For example, if you want to monitor the five hours of data in your dataset that precede the start of each monitoring job, you would specify:"-PT5H"
.The start time that you specify must not precede the end time that you specify by more than 24 hours. You specify the end time with the
DataAnalysisEndTime
parameter.If you set
ScheduleExpression
toNOW
, this parameter is required. - ScheduleExpression
-
- Required: Yes
- Type: string
A cron expression that describes details about the monitoring schedule.
The supported cron expressions are:
-
If you want to set the job to start every hour, use the following:
Hourly: cron(0 * ? * * *)
-
If you want to start the job daily:
cron(0 [00-23] ? * * *)
-
If you want to run the job one time, immediately, use the following keyword:
NOW
For example, the following are valid cron expressions:
-
Daily at noon UTC:
cron(0 12 ? * * *)
-
Daily at midnight UTC:
cron(0 0 ? * * *)
To support running every 6, 12 hours, the following are also supported:
cron(0 [00-23]/[01-24] ? * * *)
For example, the following are valid cron expressions:
-
Every 12 hours, starting at 5pm UTC:
cron(0 17/12 ? * * *)
-
Every two hours starting at midnight:
cron(0 0/2 ? * * *)
-
Even though the cron expression is set to start at 5PM UTC, note that there could be a delay of 0-20 minutes from the actual requested time to run the execution.
-
We recommend that if you would like a daily schedule, you do not provide this parameter. Amazon SageMaker will pick a time for running every day.
You can also specify the keyword
NOW
to run the monitoring job immediately, one time, without recurring.
SearchExpression
Description
A multi-expression that searches for the specified resource or resources in a search. All resource objects that satisfy the expression's condition are included in the search results. You must specify at least one subexpression, filter, or nested filter. A SearchExpression
can contain up to twenty elements.
A SearchExpression
contains the following components:
-
A list of
Filter
objects. Each filter defines a simple Boolean expression comprised of a resource property name, Boolean operator, and value. -
A list of
NestedFilter
objects. Each nested filter defines a list of Boolean expressions using a list of resource properties. A nested filter is satisfied if a single object in the list satisfies all Boolean expressions. -
A list of
SearchExpression
objects. A search expression object can be nested in a list of search expression objects. -
A Boolean operator:
And
orOr
.
Members
- Filters
-
- Type: Array of Filter structures
A list of filter objects.
- NestedFilters
-
- Type: Array of NestedFilters structures
A list of nested filter objects.
- Operator
-
- Type: string
A Boolean operator used to evaluate the search expression. If you want every conditional statement in all lists to be satisfied for the entire search expression to be true, specify
And
. If only a single conditional statement needs to be true for the entire search expression to be true, specifyOr
. The default value isAnd
. - SubExpressions
-
- Type: Array of SearchExpression structures
A list of search expression objects.
SearchRecord
Description
A single resource returned as part of the Search API response.
Members
- Endpoint
-
- Type: Endpoint structure
A hosted endpoint for real-time inference.
- Experiment
-
- Type: Experiment structure
The properties of an experiment.
- FeatureGroup
-
- Type: FeatureGroup structure
Amazon SageMaker Feature Store stores features in a collection called Feature Group. A Feature Group can be visualized as a table which has rows, with a unique identifier for each row where each column in the table is a feature. In principle, a Feature Group is composed of features and values per features.
- FeatureMetadata
-
- Type: FeatureMetadata structure
The feature metadata used to search through the features.
- HyperParameterTuningJob
-
- Type: HyperParameterTuningJobSearchEntity structure
The properties of a hyperparameter tuning job.
- Model
-
- Type: ModelDashboardModel structure
A model displayed in the Amazon SageMaker Model Dashboard.
- ModelCard
-
- Type: ModelCard structure
An Amazon SageMaker Model Card that documents details about a machine learning model.
- ModelPackage
-
- Type: ModelPackage structure
A versioned model that can be deployed for SageMaker inference.
- ModelPackageGroup
-
- Type: ModelPackageGroup structure
A group of versioned models in the model registry.
- Pipeline
-
- Type: Pipeline structure
A SageMaker Model Building Pipeline instance.
- PipelineExecution
-
- Type: PipelineExecution structure
An execution of a pipeline.
- Project
-
- Type: Project structure
The properties of a project.
- TrainingJob
-
- Type: TrainingJob structure
The properties of a training job.
- Trial
-
- Type: Trial structure
The properties of a trial.
- TrialComponent
-
- Type: TrialComponent structure
The properties of a trial component.
SecondaryStatusTransition
Description
An array element of SecondaryStatusTransitions
for DescribeTrainingJob. It provides additional details about a status that the training job has transitioned through. A training job can be in one of several states, for example, starting, downloading, training, or uploading. Within each state, there are a number of intermediate states. For example, within the starting state, SageMaker could be starting the training job or launching the ML instances. These transitional states are referred to as the job's secondary status.
Members
- EndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the training job transitioned out of this secondary status state into another secondary status state or when the training job has ended.
- StartTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the training job transitioned to the current secondary status state.
- Status
-
- Required: Yes
- Type: string
Contains a secondary status information from a training job.
Status might be one of the following secondary statuses:
- InProgress
-
-
Starting
- Starting the training job. -
Downloading
- An optional stage for algorithms that supportFile
training input mode. It indicates that data is being downloaded to the ML storage volumes. -
Training
- Training is in progress. -
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
-
- Completed
-
-
Completed
- The training job has completed.
-
- Failed
-
-
Failed
- The training job has failed. The reason for the failure is returned in theFailureReason
field ofDescribeTrainingJobResponse
.
-
- Stopped
-
-
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime. -
Stopped
- The training job has stopped.
-
- Stopping
-
-
Stopping
- Stopping the training job.
-
We no longer support the following secondary statuses:
-
LaunchingMLInstances
-
PreparingTrainingStack
-
DownloadingTrainingImage
- StatusMessage
-
- Type: string
A detailed description of the progress within a secondary status.
SageMaker provides secondary statuses and status messages that apply to each of them:
- Starting
-
-
Starting the training job.
-
Launching requested ML instances.
-
Insufficient capacity error from EC2 while launching instances, retrying!
-
Launched instance was unhealthy, replacing it!
-
Preparing the instances for training.
-
- Training
-
-
Training image download completed. Training in progress.
-
Status messages are subject to change. Therefore, we recommend not including them in code that programmatically initiates actions. For examples, don't use status messages in if statements.
To have an overview of your training job's progress, view
TrainingJobStatus
andSecondaryStatus
in DescribeTrainingJob, andStatusMessage
together. For example, at the start of a training job, you might see the following:-
TrainingJobStatus
- InProgress -
SecondaryStatus
- Training -
StatusMessage
- Downloading the training image
SelectedStep
Description
A step selected to run in selective execution mode.
Members
- StepName
-
- Required: Yes
- Type: string
The name of the pipeline step.
SelectiveExecutionConfig
Description
The selective execution configuration applied to the pipeline run.
Members
- SelectedSteps
-
- Required: Yes
- Type: Array of SelectedStep structures
A list of pipeline steps to run. All step(s) in all path(s) between two selected steps should be included.
- SourcePipelineExecutionArn
-
- Type: string
The ARN from a reference execution of the current pipeline. Used to copy input collaterals needed for the selected steps to run. The execution status of the pipeline can be either
Failed
orSuccess
.This field is required if the steps you specify for
SelectedSteps
depend on output collaterals from any non-specified pipeline steps. For more information, see Selective Execution for Pipeline Steps.
SelectiveExecutionResult
Description
The ARN from an execution of the current pipeline.
Members
- SourcePipelineExecutionArn
-
- Type: string
The ARN from an execution of the current pipeline.
ServiceCatalogProvisionedProductDetails
Description
Details of a provisioned service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
Members
- ProvisionedProductId
-
- Type: string
The ID of the provisioned product.
- ProvisionedProductStatusMessage
-
- Type: string
The current status of the product.
-
AVAILABLE
- Stable state, ready to perform any operation. The most recent operation succeeded and completed. -
UNDER_CHANGE
- Transitive state. Operations performed might not have valid results. Wait for an AVAILABLE status before performing operations. -
TAINTED
- Stable state, ready to perform any operation. The stack has completed the requested operation but is not exactly what was requested. For example, a request to update to a new version failed and the stack rolled back to the current version. -
ERROR
- An unexpected error occurred. The provisioned product exists but the stack is not running. For example, CloudFormation received a parameter value that was not valid and could not launch the stack. -
PLAN_IN_PROGRESS
- Transitive state. The plan operations were performed to provision a new product, but resources have not yet been created. After reviewing the list of resources to be created, execute the plan. Wait for an AVAILABLE status before performing operations.
ServiceCatalogProvisioningDetails
Description
Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
Members
- PathId
-
- Type: string
The path identifier of the product. This value is optional if the product has a default path, and required if the product has more than one path.
- ProductId
-
- Required: Yes
- Type: string
The ID of the product to provision.
- ProvisioningArtifactId
-
- Type: string
The ID of the provisioning artifact.
- ProvisioningParameters
-
- Type: Array of ProvisioningParameter structures
A list of key value pairs that you specify when you provision a product.
ServiceCatalogProvisioningUpdateDetails
Description
Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
Members
- ProvisioningArtifactId
-
- Type: string
The ID of the provisioning artifact.
- ProvisioningParameters
-
- Type: Array of ProvisioningParameter structures
A list of key value pairs that you specify when you provision a product.
SessionChainingConfig
Description
Contains information about attribute-based access control (ABAC) for a training job. The session chaining configuration uses Amazon Security Token Service (STS) for your training job to request temporary, limited-privilege credentials to tenants. For more information, see Attribute-based access control (ABAC) for multi-tenancy training.
Members
- EnableSessionTagChaining
-
- Type: boolean
Set to
True
to allow SageMaker to extract session tags from a training job creation role and reuse these tags when assuming the training job execution role.
ShadowModeConfig
Description
The configuration of ShadowMode
inference experiment type, which specifies a production variant to take all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also specifies the percentage of requests that Amazon SageMaker replicates.
Members
- ShadowModelVariants
-
- Required: Yes
- Type: Array of ShadowModelVariantConfig structures
List of shadow variant configurations.
- SourceModelVariantName
-
- Required: Yes
- Type: string
The name of the production variant, which takes all the inference requests.
ShadowModelVariantConfig
Description
The name and sampling percentage of a shadow variant.
Members
- SamplingPercentage
-
- Required: Yes
- Type: int
The percentage of inference requests that Amazon SageMaker replicates from the production variant to the shadow variant.
- ShadowModelVariantName
-
- Required: Yes
- Type: string
The name of the shadow variant.
SharingSettings
Description
Specifies options for sharing Amazon SageMaker Studio notebooks. These settings are specified as part of DefaultUserSettings
when the CreateDomain
API is called, and as part of UserSettings
when the CreateUserProfile
API is called. When SharingSettings
is not specified, notebook sharing isn't allowed.
Members
- NotebookOutputOption
-
- Type: string
Whether to include the notebook cell output when sharing the notebook. The default is
Disabled
. - S3KmsKeyId
-
- Type: string
When
NotebookOutputOption
isAllowed
, the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket. - S3OutputPath
-
- Type: string
When
NotebookOutputOption
isAllowed
, the Amazon S3 bucket used to store the shared notebook snapshots.
ShuffleConfig
Description
A configuration for a shuffle option for input data in a channel. If you use S3Prefix
for S3DataType
, the results of the S3 key prefix matches are shuffled. If you use ManifestFile
, the order of the S3 object references in the ManifestFile
is shuffled. If you use AugmentedManifestFile
, the order of the JSON lines in the AugmentedManifestFile
is shuffled. The shuffling order is determined using the Seed
value.
For Pipe input mode, when ShuffleConfig
is specified shuffling is done at the start of every epoch. With large datasets, this ensures that the order of the training data is different for each epoch, and it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig
is combined with S3DataDistributionType
of ShardedByS3Key
, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
Members
- Seed
-
- Required: Yes
- Type: long (int|float)
Determines the shuffling order in
ShuffleConfig
value.
SourceAlgorithm
Description
Specifies an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
Members
- AlgorithmName
-
- Required: Yes
- Type: string
The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
- ModelDataSource
-
- Type: ModelDataSource structure
Specifies the location of ML model data to deploy during endpoint creation.
- ModelDataUrl
-
- Type: string
The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single
gzip
compressed tar archive (.tar.gz
suffix).The model artifacts must be in an S3 bucket that is in the same Amazon Web Services region as the algorithm.
SourceAlgorithmSpecification
Description
A list of algorithms that were used to create a model package.
Members
- SourceAlgorithms
-
- Required: Yes
- Type: Array of SourceAlgorithm structures
A list of the algorithms that were used to create a model package.
SourceIpConfig
Description
A list of IP address ranges (CIDRs). Used to create an allow list of IP addresses for a private workforce. Workers will only be able to log in to their worker portal from an IP address within this range. By default, a workforce isn't restricted to specific IP addresses.
Members
- Cidrs
-
- Required: Yes
- Type: Array of strings
A list of one to ten Classless Inter-Domain Routing (CIDR) values.
Maximum: Ten CIDR values
The following Length Constraints apply to individual CIDR values in the CIDR value list.
SpaceCodeEditorAppSettings
Description
The application settings for a Code Editor space.
Members
- DefaultResourceSpec
-
- Type: ResourceSpec structure
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
SpaceDetails
Description
The space's details.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time.
- DomainId
-
- Type: string
The ID of the associated domain.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last modified time.
- OwnershipSettingsSummary
-
- Type: OwnershipSettingsSummary structure
Specifies summary information about the ownership settings.
- SpaceDisplayName
-
- Type: string
The name of the space that appears in the Studio UI.
- SpaceName
-
- Type: string
The name of the space.
- SpaceSettingsSummary
-
- Type: SpaceSettingsSummary structure
Specifies summary information about the space settings.
- SpaceSharingSettingsSummary
-
- Type: SpaceSharingSettingsSummary structure
Specifies summary information about the space sharing settings.
- Status
-
- Type: string
The status.
SpaceJupyterLabAppSettings
Description
The settings for the JupyterLab application within a space.
Members
- CodeRepositories
-
- Type: Array of CodeRepository structures
A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterLab application.
- DefaultResourceSpec
-
- Type: ResourceSpec structure
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
SpaceSettings
Description
A collection of space settings.
Members
- AppType
-
- Type: string
The type of app created within the space.
- CodeEditorAppSettings
-
- Type: SpaceCodeEditorAppSettings structure
The Code Editor application settings.
- CustomFileSystems
-
- Type: Array of CustomFileSystem structures
A file system, created by you, that you assign to a space for an Amazon SageMaker Domain. Permitted users can access this file system in Amazon SageMaker Studio.
- JupyterLabAppSettings
-
- Type: SpaceJupyterLabAppSettings structure
The settings for the JupyterLab application.
- JupyterServerAppSettings
-
- Type: JupyterServerAppSettings structure
The JupyterServer app settings.
- KernelGatewayAppSettings
-
- Type: KernelGatewayAppSettings structure
The KernelGateway app settings.
- SpaceStorageSettings
-
- Type: SpaceStorageSettings structure
The storage settings for a space.
SpaceSettingsSummary
Description
Specifies summary information about the space settings.
Members
- AppType
-
- Type: string
The type of app created within the space.
- SpaceStorageSettings
-
- Type: SpaceStorageSettings structure
The storage settings for a space.
SpaceSharingSettings
Description
A collection of space sharing settings.
Members
- SharingType
-
- Required: Yes
- Type: string
Specifies the sharing type of the space.
SpaceSharingSettingsSummary
Description
Specifies summary information about the space sharing settings.
Members
- SharingType
-
- Type: string
Specifies the sharing type of the space.
SpaceStorageSettings
Description
The storage settings for a space.
Members
- EbsStorageSettings
-
- Type: EbsStorageSettings structure
A collection of EBS storage settings for a space.
Stairs
Description
Defines the stairs traffic pattern for an Inference Recommender load test. This pattern type consists of multiple steps where the number of users increases at each step.
Specify either the stairs or phases traffic pattern.
Members
- DurationInSeconds
-
- Type: int
Defines how long each traffic step should be.
- NumberOfSteps
-
- Type: int
Specifies how many steps to perform during traffic.
- UsersPerStep
-
- Type: int
Specifies how many new users to spawn in each step.
StoppingCondition
Description
Specifies a limit to how long a job can run. When the job reaches the time limit, SageMaker ends the job. Use this API to cap costs.
To stop a training job, SageMaker sends the algorithm the SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with CreateModel
.
The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.
Members
- MaxPendingTimeInSeconds
-
- Type: int
The maximum length of time, in seconds, that a training or compilation job can be pending before it is stopped.
- MaxRuntimeInSeconds
-
- Type: int
The maximum length of time, in seconds, that a training or compilation job can run before it is stopped.
For compilation jobs, if the job does not complete during this time, a
TimeOut
error is generated. We recommend starting with 900 seconds and increasing as necessary based on your model.For all other jobs, if the job does not complete during this time, SageMaker ends the job. When
RetryStrategy
is specified in the job request,MaxRuntimeInSeconds
specifies the maximum time for all of the attempts in total, not each individual attempt. The default value is 1 day. The maximum value is 28 days.The maximum time that a
TrainingJob
can run in total, including any time spent publishing metrics or archiving and uploading models after it has been stopped, is 30 days. - MaxWaitTimeInSeconds
-
- Type: int
The maximum length of time, in seconds, that a managed Spot training job has to complete. It is the amount of time spent waiting for Spot capacity plus the amount of time the job can run. It must be equal to or greater than
MaxRuntimeInSeconds
. If the job does not complete during this time, SageMaker ends the job.When
RetryStrategy
is specified in the job request,MaxWaitTimeInSeconds
specifies the maximum time for all of the attempts in total, not each individual attempt.
StudioLifecycleConfigDetails
Description
Details of the Amazon SageMaker Studio Lifecycle Configuration.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time of the Amazon SageMaker Studio Lifecycle Configuration.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
This value is equivalent to CreationTime because Amazon SageMaker Studio Lifecycle Configurations are immutable.
- StudioLifecycleConfigAppType
-
- Type: string
The App type to which the Lifecycle Configuration is attached.
- StudioLifecycleConfigArn
-
- Type: string
The Amazon Resource Name (ARN) of the Lifecycle Configuration.
- StudioLifecycleConfigName
-
- Type: string
The name of the Amazon SageMaker Studio Lifecycle Configuration.
StudioWebPortalSettings
Description
Studio settings. If these settings are applied on a user level, they take priority over the settings applied on a domain level.
Members
- HiddenAppTypes
-
- Type: Array of strings
The Applications supported in Studio that are hidden from the Studio left navigation pane.
- HiddenMlTools
-
- Type: Array of strings
The machine learning tools that are hidden from the Studio left navigation pane.
SubscribedWorkteam
Description
Describes a work team of a vendor that does the labelling job.
Members
- ListingId
-
- Type: string
Marketplace product listing ID.
- MarketplaceDescription
-
- Type: string
The description of the vendor from the Amazon Marketplace.
- MarketplaceTitle
-
- Type: string
The title of the service provided by the vendor in the Amazon Marketplace.
- SellerName
-
- Type: string
The name of the vendor in the Amazon Marketplace.
- WorkteamArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the vendor that you have subscribed.
SuggestionQuery
Description
Specified in the GetSearchSuggestions request. Limits the property names that are included in the response.
Members
- PropertyNameQuery
-
- Type: PropertyNameQuery structure
Defines a property name hint. Only property names that begin with the specified hint are included in the response.
TabularJobConfig
Description
The collection of settings used by an AutoML job V2 for the tabular problem type.
Members
- CandidateGenerationConfig
-
- Type: CandidateGenerationConfig structure
The configuration information of how model candidates are generated.
- CompletionCriteria
-
- Type: AutoMLJobCompletionCriteria structure
How long a job is allowed to run, or how many candidates a job is allowed to generate.
- FeatureSpecificationS3Uri
-
- Type: string
A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job V2. You can input
FeatureAttributeNames
(optional) in JSON format as shown below:{ "FeatureAttributeNames":["col1", "col2", ...] }
.You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types:
numeric
,categorical
,text
, anddatetime
. In HPO mode, Autopilot can supportnumeric
,categorical
,text
,datetime
, andsequence
.If only
FeatureDataTypes
is provided, the column keys (col1
,col2
,..) should be a subset of the column names in the input data.If both
FeatureDataTypes
andFeatureAttributeNames
are provided, then the column keys should be a subset of the column names provided inFeatureAttributeNames
.The key name
FeatureAttributeNames
is fixed. The values listed in["col1", "col2", ...]
are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column. - GenerateCandidateDefinitionsOnly
-
- Type: boolean
Generates possible candidates without training the models. A model candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
- Mode
-
- Type: string
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting
AUTO
. InAUTO
mode, Autopilot choosesENSEMBLING
for datasets smaller than 100 MB, andHYPERPARAMETER_TUNING
for larger ones.The
ENSEMBLING
mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported byENSEMBLING
mode.The
HYPERPARAMETER_TUNING
(HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported byHYPERPARAMETER_TUNING
mode. - ProblemType
-
- Type: string
The type of supervised learning problem available for the model candidates of the AutoML job V2. For more information, see SageMaker Autopilot problem types.
You must either specify the type of supervised learning problem in
ProblemType
and provide the AutoMLJobObjective metric, or none at all. - SampleWeightAttributeName
-
- Type: string
If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
- TargetAttributeName
-
- Required: Yes
- Type: string
The name of the target variable in supervised learning, usually represented by 'y'.
TabularResolvedAttributes
Description
The resolved attributes specific to the tabular problem type.
Members
- ProblemType
-
- Type: string
The type of supervised learning problem available for the model candidates of the AutoML job V2 (Binary Classification, Multiclass Classification, Regression). For more information, see SageMaker Autopilot problem types.
Tag
Description
A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.
You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.
For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.
Members
- Key
-
- Required: Yes
- Type: string
The tag key. Tag keys must be unique per resource.
- Value
-
- Required: Yes
- Type: string
The tag value.
TargetPlatform
Description
Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice
.
Members
- Accelerator
-
- Type: string
Specifies a target platform accelerator (optional).
-
NVIDIA
: Nvidia graphics processing unit. It also requiresgpu-code
,trt-ver
,cuda-ver
compiler options -
MALI
: ARM Mali graphics processor -
INTEL_GRAPHICS
: Integrated Intel graphics
- Arch
-
- Required: Yes
- Type: string
Specifies a target platform architecture.
-
X86_64
: 64-bit version of the x86 instruction set. -
X86
: 32-bit version of the x86 instruction set. -
ARM64
: ARMv8 64-bit CPU. -
ARM_EABIHF
: ARMv7 32-bit, Hard Float. -
ARM_EABI
: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM platform.
- Os
-
- Required: Yes
- Type: string
Specifies a target platform OS.
-
LINUX
: Linux-based operating systems. -
ANDROID
: Android operating systems. Android API level can be specified using theANDROID_PLATFORM
compiler option. For example,"CompilerOptions": {'ANDROID_PLATFORM': 28}
TargetTrackingScalingPolicyConfiguration
Description
A target tracking scaling policy. Includes support for predefined or customized metrics.
When using the PutScalingPolicy API, this parameter is required when you are creating a policy with the policy type TargetTrackingScaling
.
Members
- MetricSpecification
-
- Type: MetricSpecification structure
An object containing information about a metric.
- TargetValue
-
- Type: double
The recommended target value to specify for the metric when creating a scaling policy.
TensorBoardAppSettings
Description
The TensorBoard app settings.
Members
- DefaultResourceSpec
-
- Type: ResourceSpec structure
The default instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
TensorBoardOutputConfig
Description
Configuration of storage locations for the Amazon SageMaker Debugger TensorBoard output data.
Members
- LocalPath
-
- Type: string
Path to local storage location for tensorBoard output. Defaults to
/opt/ml/output/tensorboard
. - S3OutputPath
-
- Required: Yes
- Type: string
Path to Amazon S3 storage location for TensorBoard output.
TextClassificationJobConfig
Description
The collection of settings used by an AutoML job V2 for the text classification problem type.
Members
- CompletionCriteria
-
- Type: AutoMLJobCompletionCriteria structure
How long a job is allowed to run, or how many candidates a job is allowed to generate.
- ContentColumn
-
- Required: Yes
- Type: string
The name of the column used to provide the sentences to be classified. It should not be the same as the target column.
- TargetLabelColumn
-
- Required: Yes
- Type: string
The name of the column used to provide the class labels. It should not be same as the content column.
TextGenerationJobConfig
Description
The collection of settings used by an AutoML job V2 for the text generation problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
Members
- BaseModelName
-
- Type: string
The name of the base model to fine-tune. Autopilot supports fine-tuning a variety of large language models. For information on the list of supported models, see Text generation models supporting fine-tuning in Autopilot. If no
BaseModelName
is provided, the default model used is Falcon7BInstruct. - CompletionCriteria
-
- Type: AutoMLJobCompletionCriteria structure
How long a fine-tuning job is allowed to run. For
TextGenerationJobConfig
problem types, theMaxRuntimePerTrainingJobInSeconds
attribute ofAutoMLJobCompletionCriteria
defaults to 72h (259200s). - ModelAccessConfig
-
- Type: ModelAccessConfig structure
The access configuration file to control access to the ML model. You can explicitly accept the model end-user license agreement (EULA) within the
ModelAccessConfig
.-
If you are a Jumpstart user, see the End-user license agreements section for more details on accepting the EULA.
-
If you are an AutoML user, see the Optional Parameters section of Create an AutoML job to fine-tune text generation models using the API for details on How to set the EULA acceptance when fine-tuning a model using the AutoML API.
- TextGenerationHyperParameters
-
- Type: Associative array of custom strings keys (TextGenerationHyperParameterKey) to strings
The hyperparameters used to configure and optimize the learning process of the base model. You can set any combination of the following hyperparameters for all base models. For more information on each supported hyperparameter, see Optimize the learning process of your text generation models with hyperparameters.
-
"epochCount"
: The number of times the model goes through the entire training dataset. Its value should be a string containing an integer value within the range of "1" to "10". -
"batchSize"
: The number of data samples used in each iteration of training. Its value should be a string containing an integer value within the range of "1" to "64". -
"learningRate"
: The step size at which a model's parameters are updated during training. Its value should be a string containing a floating-point value within the range of "0" to "1". -
"learningRateWarmupSteps"
: The number of training steps during which the learning rate gradually increases before reaching its target or maximum value. Its value should be a string containing an integer value within the range of "0" to "250".
Here is an example where all four hyperparameters are configured.
{ "epochCount":"5", "learningRate":"0.5", "batchSize": "32", "learningRateWarmupSteps": "10" }
TextGenerationResolvedAttributes
Description
The resolved attributes specific to the text generation problem type.
Members
- BaseModelName
-
- Type: string
The name of the base model to fine-tune.
ThroughputConfig
Description
Used to set feature group throughput configuration. There are two modes: ON_DEMAND
and PROVISIONED
. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED
throughput mode is supported only for feature groups that are offline-only, or use the Standard
tier online store.
Members
- ProvisionedReadCapacityUnits
-
- Type: int
For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
- ProvisionedWriteCapacityUnits
-
- Type: int
For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
- ThroughputMode
-
- Required: Yes
- Type: string
The mode used for your feature group throughput:
ON_DEMAND
orPROVISIONED
.
ThroughputConfigDescription
Description
Active throughput configuration of the feature group. There are two modes: ON_DEMAND
and PROVISIONED
. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED
throughput mode is supported only for feature groups that are offline-only, or use the Standard
tier online store.
Members
- ProvisionedReadCapacityUnits
-
- Type: int
For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
- ProvisionedWriteCapacityUnits
-
- Type: int
For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
- ThroughputMode
-
- Required: Yes
- Type: string
The mode used for your feature group throughput:
ON_DEMAND
orPROVISIONED
.
ThroughputConfigUpdate
Description
The new throughput configuration for the feature group. You can switch between on-demand and provisioned modes or update the read / write capacity of provisioned feature groups. You can switch a feature group to on-demand only once in a 24 hour period.
Members
- ProvisionedReadCapacityUnits
-
- Type: int
For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
- ProvisionedWriteCapacityUnits
-
- Type: int
For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
- ThroughputMode
-
- Type: string
Target throughput mode of the feature group. Throughput update is an asynchronous operation, and the outcome should be monitored by polling
LastUpdateStatus
field inDescribeFeatureGroup
response. You cannot update a feature group's throughput while another update is in progress.
TimeSeriesConfig
Description
The collection of components that defines the time-series.
Members
- GroupingAttributeNames
-
- Type: Array of strings
A set of columns names that can be grouped with the item identifier column to create a composite key for which a target value is predicted.
- ItemIdentifierAttributeName
-
- Required: Yes
- Type: string
The name of the column that represents the set of item identifiers for which you want to predict the target value.
- TargetAttributeName
-
- Required: Yes
- Type: string
The name of the column representing the target variable that you want to predict for each item in your dataset. The data type of the target variable must be numerical.
- TimestampAttributeName
-
- Required: Yes
- Type: string
The name of the column indicating a point in time at which the target value of a given item is recorded.
TimeSeriesForecastingJobConfig
Description
The collection of settings used by an AutoML job V2 for the time-series forecasting problem type.
Members
- CandidateGenerationConfig
-
- Type: CandidateGenerationConfig structure
Stores the configuration information for how model candidates are generated using an AutoML job V2.
- CompletionCriteria
-
- Type: AutoMLJobCompletionCriteria structure
How long a job is allowed to run, or how many candidates a job is allowed to generate.
- FeatureSpecificationS3Uri
-
- Type: string
A URL to the Amazon S3 data source containing additional selected features that complement the target, itemID, timestamp, and grouped columns set in
TimeSeriesConfig
. When not provided, the AutoML job V2 includes all the columns from the original dataset that are not already declared inTimeSeriesConfig
. If provided, the AutoML job V2 only considers these additional columns as a complement to the ones declared inTimeSeriesConfig
.You can input
FeatureAttributeNames
(optional) in JSON format as shown below:{ "FeatureAttributeNames":["col1", "col2", ...] }
.You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
Autopilot supports the following data types:
numeric
,categorical
,text
, anddatetime
.These column keys must not include any column set in
TimeSeriesConfig
. - ForecastFrequency
-
- Required: Yes
- Type: string
The frequency of predictions in a forecast.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example,
1D
indicates every day and15min
indicates every 15 minutes. The value of a frequency must not overlap with the next larger frequency. For example, you must use a frequency of1H
instead of60min
.The valid values for each frequency are the following:
-
Minute - 1-59
-
Hour - 1-23
-
Day - 1-6
-
Week - 1-4
-
Month - 1-11
-
Year - 1
- ForecastHorizon
-
- Required: Yes
- Type: int
The number of time-steps that the model predicts. The forecast horizon is also called the prediction length. The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the time-steps in the dataset.
- ForecastQuantiles
-
- Type: Array of strings
The quantiles used to train the model for forecasts at a specified quantile. You can specify quantiles from
0.01
(p1) to0.99
(p99), by increments of 0.01 or higher. Up to five forecast quantiles can be specified. WhenForecastQuantiles
is not provided, the AutoML job uses the quantiles p10, p50, and p90 as default. - HolidayConfig
-
- Type: Array of HolidayConfigAttributes structures
The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.
- TimeSeriesConfig
-
- Required: Yes
- Type: TimeSeriesConfig structure
The collection of components that defines the time-series.
- Transformations
-
- Type: TimeSeriesTransformations structure
The transformations modifying specific attributes of the time-series, such as filling strategies for missing values.
TimeSeriesForecastingSettings
Description
Time series forecast settings for the SageMaker Canvas application.
Members
- AmazonForecastRoleArn
-
- Type: string
The IAM role that Canvas passes to Amazon Forecast for time series forecasting. By default, Canvas uses the execution role specified in the
UserProfile
that launches the Canvas application. If an execution role is not specified in theUserProfile
, Canvas uses the execution role specified in the Domain that owns theUserProfile
. To allow time series forecasting, this IAM role should have the AmazonSageMakerCanvasForecastAccess policy attached andforecast.amazonaws.com
added in the trust relationship as a service principal. - Status
-
- Type: string
Describes whether time series forecasting is enabled or disabled in the Canvas application.
TimeSeriesTransformations
Description
Transformations allowed on the dataset. Supported transformations are Filling
and Aggregation
. Filling
specifies how to add values to missing values in the dataset. Aggregation
defines how to aggregate data that does not align with forecast frequency.
Members
- Aggregation
-
- Type: Associative array of custom strings keys (TransformationAttributeName) to strings
A key value pair defining the aggregation method for a column, where the key is the column name and the value is the aggregation method.
The supported aggregation methods are
sum
(default),avg
,first
,min
,max
.Aggregation is only supported for the target column.
- Filling
-
- Type: Associative array of custom strings keys (TransformationAttributeName) to stringss
A key value pair defining the filling method for a column, where the key is the column name and the value is an object which defines the filling logic. You can specify multiple filling methods for a single column.
The supported filling methods and their corresponding options are:
-
frontfill
:none
(Supported only for target column) -
middlefill
:zero
,value
,median
,mean
,min
,max
-
backfill
:zero
,value
,median
,mean
,min
,max
-
futurefill
:zero
,value
,median
,mean
,min
,max
To set a filling method to a specific value, set the fill parameter to the chosen filling method value (for example
"backfill" : "value"
), and define the filling value in an additional parameter prefixed with "_value". For example, to setbackfill
to a value of2
, you must include two parameters:"backfill": "value"
and"backfill_value":"2"
.
TrackingServerSummary
Description
The summary of the tracking server to list.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time of a listed tracking server.
- IsActive
-
- Type: string
The activity status of a listed tracking server.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last modified time of a listed tracking server.
- MlflowVersion
-
- Type: string
The MLflow version used for a listed tracking server.
- TrackingServerArn
-
- Type: string
The ARN of a listed tracking server.
- TrackingServerName
-
- Type: string
The name of a listed tracking server.
- TrackingServerStatus
-
- Type: string
The creation status of a listed tracking server.
TrafficPattern
TrafficRoutingConfig
Description
Defines the traffic routing strategy during an endpoint deployment to shift traffic from the old fleet to the new fleet.
Members
- CanarySize
-
- Type: CapacitySize structure
Batch size for the first step to turn on traffic on the new endpoint fleet.
Value
must be less than or equal to 50% of the variant's total instance count. - LinearStepSize
-
- Type: CapacitySize structure
Batch size for each step to turn on traffic on the new endpoint fleet.
Value
must be 10-50% of the variant's total instance count. - Type
-
- Required: Yes
- Type: string
Traffic routing strategy type.
-
ALL_AT_ONCE
: Endpoint traffic shifts to the new fleet in a single step. -
CANARY
: Endpoint traffic shifts to the new fleet in two steps. The first step is the canary, which is a small portion of the traffic. The second step is the remainder of the traffic. -
LINEAR
: Endpoint traffic shifts to the new fleet in n steps of a configurable size.
- WaitIntervalInSeconds
-
- Required: Yes
- Type: int
The waiting time (in seconds) between incremental steps to turn on traffic on the new endpoint fleet.
TrainingImageConfig
Description
The configuration to use an image from a private Docker registry for a training job.
Members
- TrainingRepositoryAccessMode
-
- Required: Yes
- Type: string
The method that your training job will use to gain access to the images in your private Docker registry. For access to an image in a private Docker registry, set to
Vpc
. - TrainingRepositoryAuthConfig
-
- Type: TrainingRepositoryAuthConfig structure
An object containing authentication information for a private Docker registry containing your training images.
TrainingJob
Description
Contains information about a training job.
Members
- AlgorithmSpecification
-
- Type: AlgorithmSpecification structure
Information about the algorithm used for training, and algorithm metadata.
- AutoMLJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the job.
- BillableTimeInSeconds
-
- Type: int
The billable time in seconds.
- CheckpointConfig
-
- Type: CheckpointConfig structure
Contains information about the output location for managed spot training checkpoint data.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the training job was created.
- DebugHookConfig
-
- Type: DebugHookConfig structure
Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the
DebugHookConfig
parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job. - DebugRuleConfigurations
-
- Type: Array of DebugRuleConfiguration structures
Information about the debug rule configuration.
- DebugRuleEvaluationStatuses
-
- Type: Array of DebugRuleEvaluationStatus structures
Information about the evaluation status of the rules for the training job.
- EnableInterContainerTrafficEncryption
-
- Type: boolean
To encrypt all communications between ML compute instances in distributed training, choose
True
. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training. - EnableManagedSpotTraining
-
- Type: boolean
When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.
- EnableNetworkIsolation
-
- Type: boolean
If the
TrainingJob
was created with network isolation, the value is set totrue
. If network isolation is enabled, nodes can't communicate beyond the VPC they run in. - Environment
-
- Type: Associative array of custom strings keys (TrainingEnvironmentKey) to strings
The environment variables to set in the Docker container.
- ExperimentConfig
-
- Type: ExperimentConfig structure
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
- FailureReason
-
- Type: string
If the training job failed, the reason it failed.
- FinalMetricDataList
-
- Type: Array of MetricData structures
A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.
- HyperParameters
-
- Type: Associative array of custom strings keys (HyperParameterKey) to strings
Algorithm-specific parameters.
- InputDataConfig
-
- Type: Array of Channel structures
An array of
Channel
objects that describes each data input channel.Your input must be in the same Amazon Web Services region as your training job.
- LabelingJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the labeling job.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the status of the training job was last modified.
- ModelArtifacts
-
- Type: ModelArtifacts structure
Information about the Amazon S3 location that is configured for storing model artifacts.
- OutputDataConfig
-
- Type: OutputDataConfig structure
The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
- ProfilerConfig
-
- Type: ProfilerConfig structure
Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
- ResourceConfig
-
- Type: ResourceConfig structure
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
- RetryStrategy
-
- Type: RetryStrategy structure
The number of times to retry the job when the job fails due to an
InternalServerError
. - RoleArn
-
- Type: string
The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
- SecondaryStatus
-
- Type: string
Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see
StatusMessage
under SecondaryStatusTransition.SageMaker provides primary statuses and secondary statuses that apply to each of them:
- InProgress
-
-
Starting
- Starting the training job. -
Downloading
- An optional stage for algorithms that supportFile
training input mode. It indicates that data is being downloaded to the ML storage volumes. -
Training
- Training is in progress. -
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
-
- Completed
-
-
Completed
- The training job has completed.
-
- Failed
-
-
Failed
- The training job has failed. The reason for the failure is returned in theFailureReason
field ofDescribeTrainingJobResponse
.
-
- Stopped
-
-
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime. -
Stopped
- The training job has stopped.
-
- Stopping
-
-
Stopping
- Stopping the training job.
-
Valid values for
SecondaryStatus
are subject to change.We no longer support the following secondary statuses:
-
LaunchingMLInstances
-
PreparingTrainingStack
-
DownloadingTrainingImage
- SecondaryStatusTransitions
-
- Type: Array of SecondaryStatusTransition structures
A history of all of the secondary statuses that the training job has transitioned through.
- StoppingCondition
-
- Type: StoppingCondition structure
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the
SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost. - Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
- TensorBoardOutputConfig
-
- Type: TensorBoardOutputConfig structure
Configuration of storage locations for the Amazon SageMaker Debugger TensorBoard output data.
- TrainingEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of
TrainingStartTime
and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure. - TrainingJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the training job.
- TrainingJobName
-
- Type: string
The name of the training job.
- TrainingJobStatus
-
- Type: string
The status of the training job.
Training job statuses are:
-
InProgress
- The training is in progress. -
Completed
- The training job has completed. -
Failed
- The training job has failed. To see the reason for the failure, see theFailureReason
field in the response to aDescribeTrainingJobResponse
call. -
Stopping
- The training job is stopping. -
Stopped
- The training job has stopped.
For more detailed information, see
SecondaryStatus
. - TrainingStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of
TrainingEndTime
. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container. - TrainingTimeInSeconds
-
- Type: int
The training time in seconds.
- TuningJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
- VpcConfig
-
- Type: VpcConfig structure
A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
TrainingJobDefinition
Description
Defines the input needed to run a training job using the algorithm.
Members
- HyperParameters
-
- Type: Associative array of custom strings keys (HyperParameterKey) to strings
The hyperparameters used for the training job.
- InputDataConfig
-
- Required: Yes
- Type: Array of Channel structures
An array of
Channel
objects, each of which specifies an input source. - OutputDataConfig
-
- Required: Yes
- Type: OutputDataConfig structure
the path to the S3 bucket where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
- ResourceConfig
-
- Required: Yes
- Type: ResourceConfig structure
The resources, including the ML compute instances and ML storage volumes, to use for model training.
- StoppingCondition
-
- Required: Yes
- Type: StoppingCondition structure
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.
- TrainingInputMode
-
- Required: Yes
- Type: string
The training input mode that the algorithm supports. For more information about input modes, see Algorithms.
Pipe mode
If an algorithm supports
Pipe
mode, Amazon SageMaker streams data directly from Amazon S3 to the container.File mode
If an algorithm supports
File
mode, SageMaker downloads the training data from S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume for the training container.You must provision the ML storage volume with sufficient capacity to accommodate the data downloaded from S3. In addition to the training data, the ML storage volume also stores the output model. The algorithm container uses the ML storage volume to also store intermediate information, if any.
For distributed algorithms, training data is distributed uniformly. Your training duration is predictable if the input data objects sizes are approximately the same. SageMaker does not split the files any further for model training. If the object sizes are skewed, training won't be optimal as the data distribution is also skewed when one host in a training cluster is overloaded, thus becoming a bottleneck in training.
FastFile mode
If an algorithm supports
FastFile
mode, SageMaker streams data directly from S3 to the container with no code changes, and provides file system access to the data. Users can author their training script to interact with these files as if they were stored on disk.FastFile
mode works best when the data is read sequentially. Augmented manifest files aren't supported. The startup time is lower when there are fewer files in the S3 bucket provided.
TrainingJobStatusCounters
Description
The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.
Members
- Completed
-
- Type: int
The number of completed training jobs launched by the hyperparameter tuning job.
- InProgress
-
- Type: int
The number of in-progress training jobs launched by a hyperparameter tuning job.
- NonRetryableError
-
- Type: int
The number of training jobs that failed and can't be retried. A failed training job can't be retried if it failed because a client error occurred.
- RetryableError
-
- Type: int
The number of training jobs that failed, but can be retried. A failed training job can be retried only if it failed because an internal service error occurred.
- Stopped
-
- Type: int
The number of training jobs launched by a hyperparameter tuning job that were manually stopped.
TrainingJobStepMetadata
Description
Metadata for a training job step.
Members
- Arn
-
- Type: string
The Amazon Resource Name (ARN) of the training job that was run by this step execution.
TrainingJobSummary
Description
Provides summary information about a training job.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the training job was created.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Timestamp when the training job was last modified.
- TrainingEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the training job ended. This field is set only if the training job has one of the terminal statuses (
Completed
,Failed
, orStopped
). - TrainingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the training job.
- TrainingJobName
-
- Required: Yes
- Type: string
The name of the training job that you want a summary for.
- TrainingJobStatus
-
- Required: Yes
- Type: string
The status of the training job.
- WarmPoolStatus
-
- Type: WarmPoolStatus structure
The status of the warm pool associated with the training job.
TrainingRepositoryAuthConfig
Description
An object containing authentication information for a private Docker registry.
Members
- TrainingRepositoryCredentialsProviderArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function used to give SageMaker access credentials to your private Docker registry.
TrainingSpecification
Description
Defines how the algorithm is used for a training job.
Members
- AdditionalS3DataSource
-
- Type: AdditionalS3DataSource structure
The additional data source used during the training job.
- MetricDefinitions
-
- Type: Array of MetricDefinition structures
A list of
MetricDefinition
objects, which are used for parsing metrics generated by the algorithm. - SupportedHyperParameters
-
- Type: Array of HyperParameterSpecification structures
A list of the
HyperParameterSpecification
objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.> - SupportedTrainingInstanceTypes
-
- Required: Yes
- Type: Array of strings
A list of the instance types that this algorithm can use for training.
- SupportedTuningJobObjectiveMetrics
-
- Type: Array of HyperParameterTuningJobObjective structures
A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
- SupportsDistributedTraining
-
- Type: boolean
Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.
- TrainingChannels
-
- Required: Yes
- Type: Array of ChannelSpecification structures
A list of
ChannelSpecification
objects, which specify the input sources to be used by the algorithm. - TrainingImage
-
- Required: Yes
- Type: string
The Amazon ECR registry path of the Docker image that contains the training algorithm.
- TrainingImageDigest
-
- Type: string
An MD5 hash of the training algorithm that identifies the Docker image used for training.
TransformDataSource
Description
Describes the location of the channel data.
Members
- S3DataSource
-
- Required: Yes
- Type: TransformS3DataSource structure
The S3 location of the data source that is associated with a channel.
TransformInput
Description
Describes the input source of a transform job and the way the transform job consumes it.
Members
- CompressionType
-
- Type: string
If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is
None
. - ContentType
-
- Type: string
The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
- DataSource
-
- Required: Yes
- Type: TransformDataSource structure
Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
- SplitType
-
- Type: string
The method to use to split the transform job's data files into smaller batches. Splitting is necessary when the total size of each object is too large to fit in a single request. You can also use data splitting to improve performance by processing multiple concurrent mini-batches. The default value for
SplitType
isNone
, which indicates that input data files are not split, and request payloads contain the entire contents of an input object. Set the value of this parameter toLine
to split records on a newline character boundary.SplitType
also supports a number of record-oriented binary data formats. Currently, the supported record formats are:-
RecordIO
-
TFRecord
When splitting is enabled, the size of a mini-batch depends on the values of the
BatchStrategy
andMaxPayloadInMB
parameters. When the value ofBatchStrategy
isMultiRecord
, Amazon SageMaker sends the maximum number of records in each request, up to theMaxPayloadInMB
limit. If the value ofBatchStrategy
isSingleRecord
, Amazon SageMaker sends individual records in each request.Some data formats represent a record as a binary payload wrapped with extra padding bytes. When splitting is applied to a binary data format, padding is removed if the value of
BatchStrategy
is set toSingleRecord
. Padding is not removed if the value ofBatchStrategy
is set toMultiRecord
.For more information about
RecordIO
, see Create a Dataset Using RecordIO in the MXNet documentation. For more information aboutTFRecord
, see Consuming TFRecord data in the TensorFlow documentation.
TransformJob
Description
A batch transform job. For information about SageMaker batch transform, see Use Batch Transform.
Members
- AutoMLJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the AutoML job that created the transform job.
- BatchStrategy
-
- Type: string
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the transform Job was created.
- DataCaptureConfig
-
- Type: BatchDataCaptureConfig structure
Configuration to control how SageMaker captures inference data for batch transform jobs.
- DataProcessing
-
- Type: DataProcessing structure
The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
- Environment
-
- Type: Associative array of custom strings keys (TransformEnvironmentKey) to strings
The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
- ExperimentConfig
-
- Type: ExperimentConfig structure
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
- FailureReason
-
- Type: string
If the transform job failed, the reason it failed.
- LabelingJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the labeling job that created the transform job.
- MaxConcurrentTransforms
-
- Type: int
The maximum number of parallel requests that can be sent to each instance in a transform job. If
MaxConcurrentTransforms
is set to 0 or left unset, SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For built-in algorithms, you don't need to set a value forMaxConcurrentTransforms
. - MaxPayloadInMB
-
- Type: int
The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in
MaxPayloadInMB
must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in algorithms do not support HTTP chunked encoding. - ModelClientConfig
-
- Type: ModelClientConfig structure
Configures the timeout and maximum number of retries for processing a transform job invocation.
- ModelName
-
- Type: string
The name of the model associated with the transform job.
- Tags
-
- Type: Array of Tag structures
A list of tags associated with the transform job.
- TransformEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of
TransformStartTime
. - TransformInput
-
- Type: TransformInput structure
Describes the input source of a transform job and the way the transform job consumes it.
- TransformJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the transform job.
- TransformJobName
-
- Type: string
The name of the transform job.
- TransformJobStatus
-
- Type: string
The status of the transform job.
Transform job statuses are:
-
InProgress
- The job is in progress. -
Completed
- The job has completed. -
Failed
- The transform job has failed. To see the reason for the failure, see theFailureReason
field in the response to aDescribeTransformJob
call. -
Stopping
- The transform job is stopping. -
Stopped
- The transform job has stopped.
- TransformOutput
-
- Type: TransformOutput structure
Describes the results of a transform job.
- TransformResources
-
- Type: TransformResources structure
Describes the resources, including ML instance types and ML instance count, to use for transform job.
- TransformStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of
TransformEndTime
.
TransformJobDefinition
Description
Defines the input needed to run a transform job using the inference specification specified in the algorithm.
Members
- BatchStrategy
-
- Type: string
A string that determines the number of records included in a single mini-batch.
SingleRecord
means only one record is used per mini-batch.MultiRecord
means a mini-batch is set to contain as many records that can fit within theMaxPayloadInMB
limit. - Environment
-
- Type: Associative array of custom strings keys (TransformEnvironmentKey) to strings
The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
- MaxConcurrentTransforms
-
- Type: int
The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.
- MaxPayloadInMB
-
- Type: int
The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).
- TransformInput
-
- Required: Yes
- Type: TransformInput structure
A description of the input source and the way the transform job consumes it.
- TransformOutput
-
- Required: Yes
- Type: TransformOutput structure
Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
- TransformResources
-
- Required: Yes
- Type: TransformResources structure
Identifies the ML compute instances for the transform job.
TransformJobStepMetadata
Description
Metadata for a transform job step.
Members
- Arn
-
- Type: string
The Amazon Resource Name (ARN) of the transform job that was run by this step execution.
TransformJobSummary
Description
Provides a summary of a transform job. Multiple TransformJobSummary
objects are returned as a list after in response to a ListTransformJobs call.
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the transform Job was created.
- FailureReason
-
- Type: string
If the transform job failed, the reason it failed.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Indicates when the transform job was last modified.
- TransformEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Indicates when the transform job ends on compute instances. For successful jobs and stopped jobs, this is the exact time recorded after the results are uploaded. For failed jobs, this is when Amazon SageMaker detected that the job failed.
- TransformJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the transform job.
- TransformJobName
-
- Required: Yes
- Type: string
The name of the transform job.
- TransformJobStatus
-
- Required: Yes
- Type: string
The status of the transform job.
TransformOutput
Description
Describes the results of a transform job.
Members
- Accept
-
- Type: string
The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
- AssembleWith
-
- Type: string
Defines how to assemble the results of the transform job as a single S3 object. Choose a format that is most convenient to you. To concatenate the results in binary format, specify
None
. To add a newline character at the end of every transformed record, specifyLine
. - KmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. 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
If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateModel request. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
- S3OutputPath
-
- Required: Yes
- Type: string
The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For example,
s3://bucket-name/key-name-prefix
.For every S3 object used as input for the transform job, batch transform stores the transformed data with an .
out
suffix in a corresponding subfolder in the location in the output prefix. For example, for the input data stored ats3://bucket-name/input-name-prefix/dataset01/data.csv
, batch transform stores the transformed data ats3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out
. Batch transform doesn't upload partially processed objects. For an input S3 object that contains multiple records, it creates an .out
file only if the transform job succeeds on the entire file. When the input contains multiple S3 objects, the batch transform job processes the listed S3 objects and uploads only the output for successfully processed objects. If any object fails in the transform job batch transform marks the job as failed to prompt investigation.
TransformResources
Description
Describes the resources, including ML instance types and ML instance count, to use for transform job.
Members
- InstanceCount
-
- Required: Yes
- Type: int
The number of ML compute instances to use in the transform job. The default value is
1
, and the maximum is100
. For distributed transform jobs, specify a value greater than1
. - InstanceType
-
- Required: Yes
- Type: string
The ML compute instance type for the transform job. If you are using built-in algorithms to transform moderately sized datasets, we recommend using ml.m4.xlarge or
ml.m5.large
instance types. - VolumeKmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.
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
VolumeKmsKeyId
when using an instance type with local storage.For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The
VolumeKmsKeyId
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
TransformS3DataSource
Description
Describes the S3 data source.
Members
- S3DataType
-
- Required: Yes
- Type: string
If you choose
S3Prefix
,S3Uri
identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for batch transform.If you choose
ManifestFile
,S3Uri
identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for batch transform.The following values are compatible:
ManifestFile
,S3Prefix
The following value is not compatible:
AugmentedManifestFile
- S3Uri
-
- Required: Yes
- Type: string
Depending on the value specified for the
S3DataType
, identifies either a key name prefix or a manifest. For example:-
A key name prefix might look like this:
s3://bucketname/exampleprefix/
. -
A manifest might look like this:
s3://bucketname/example.manifest
The manifest is an S3 object which is a JSON file with the following format:
[ {"prefix": "s3://customer_bucket/some/prefix/"},
"relative/path/to/custdata-1",
"relative/path/custdata-2",
...
"relative/path/custdata-N"
]
The preceding JSON matches the following
S3Uris
:s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of
S3Uris
in this manifest constitutes the input data for the channel for this datasource. The object that eachS3Uris
points to must be readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf.
Trial
Description
The properties of a trial as returned by the Search API.
Members
- CreatedBy
-
- Type: UserContext structure
Who created the trial.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the trial was created.
- DisplayName
-
- Type: string
The name of the trial as displayed. If
DisplayName
isn't specified,TrialName
is displayed. - ExperimentName
-
- Type: string
The name of the experiment the trial is part of.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Who last modified the trial.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- Source
-
- Type: TrialSource structure
The source of the trial.
- Tags
-
- Type: Array of Tag structures
The list of tags that are associated with the trial. You can use Search API to search on the tags.
- TrialArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial.
- TrialComponentSummaries
-
- Type: Array of TrialComponentSimpleSummary structures
A list of the components associated with the trial. For each component, a summary of the component's properties is included.
- TrialName
-
- Type: string
The name of the trial.
TrialComponent
Description
The properties of a trial component as returned by the Search API.
Members
- CreatedBy
-
- Type: UserContext structure
Who created the trial component.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component was created.
- DisplayName
-
- Type: string
The name of the component as displayed. If
DisplayName
isn't specified,TrialComponentName
is displayed. - EndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component ended.
- InputArtifacts
-
- Type: Associative array of custom strings keys (TrialComponentKey128) to TrialComponentArtifact structures
The input artifacts of the component.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component was last modified.
- LineageGroupArn
-
- Type: string
The Amazon Resource Name (ARN) of the lineage group resource.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- Metrics
-
- Type: Array of TrialComponentMetricSummary structures
The metrics for the component.
- OutputArtifacts
-
- Type: Associative array of custom strings keys (TrialComponentKey128) to TrialComponentArtifact structures
The output artifacts of the component.
- Parameters
-
- Type: Associative array of custom strings keys (TrialComponentKey320) to TrialComponentParameterValue structures
The hyperparameters of the component.
- Parents
-
- Type: Array of Parent structures
An array of the parents of the component. A parent is a trial the component is associated with and the experiment the trial is part of. A component might not have any parents.
- RunName
-
- Type: string
The name of the experiment run.
- Source
-
- Type: TrialComponentSource structure
The Amazon Resource Name (ARN) and job type of the source of the component.
- SourceDetail
-
- Type: TrialComponentSourceDetail structure
Details of the source of the component.
- StartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component started.
- Status
-
- Type: TrialComponentStatus structure
The status of the trial component.
- Tags
-
- Type: Array of Tag structures
The list of tags that are associated with the component. You can use Search API to search on the tags.
- TrialComponentArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial component.
- TrialComponentName
-
- Type: string
The name of the trial component.
TrialComponentArtifact
Description
Represents an input or output artifact of a trial component. You specify TrialComponentArtifact
as part of the InputArtifacts
and OutputArtifacts
parameters in the CreateTrialComponent request.
Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types. Examples of output artifacts are metrics, snapshots, logs, and images.
Members
- MediaType
-
- Type: string
The media type of the artifact, which indicates the type of data in the artifact file. The media type consists of a type and a subtype concatenated with a slash (/) character, for example, text/csv, image/jpeg, and s3/uri. The type specifies the category of the media. The subtype specifies the kind of data.
- Value
-
- Required: Yes
- Type: string
The location of the artifact.
TrialComponentMetricSummary
Description
A summary of the metrics of a trial component.
Members
- Avg
-
- Type: double
The average value of the metric.
- Count
-
- Type: int
The number of samples used to generate the metric.
- Last
-
- Type: double
The most recent value of the metric.
- Max
-
- Type: double
The maximum value of the metric.
- MetricName
-
- Type: string
The name of the metric.
- Min
-
- Type: double
The minimum value of the metric.
- SourceArn
-
- Type: string
The Amazon Resource Name (ARN) of the source.
- StdDev
-
- Type: double
The standard deviation of the metric.
- TimeStamp
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the metric was last updated.
TrialComponentParameterValue
Description
The value of a hyperparameter. Only one of NumberValue
or StringValue
can be specified.
This object is specified in the CreateTrialComponent request.
Members
- NumberValue
-
- Type: double
The numeric value of a numeric hyperparameter. If you specify a value for this parameter, you can't specify the
StringValue
parameter. - StringValue
-
- Type: string
The string value of a categorical hyperparameter. If you specify a value for this parameter, you can't specify the
NumberValue
parameter.
TrialComponentSimpleSummary
Description
A short summary of a trial component.
Members
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component was created.
- TrialComponentArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial component.
- TrialComponentName
-
- Type: string
The name of the trial component.
- TrialComponentSource
-
- Type: TrialComponentSource structure
The Amazon Resource Name (ARN) and job type of the source of a trial component.
TrialComponentSource
Description
The Amazon Resource Name (ARN) and job type of the source of a trial component.
Members
- SourceArn
-
- Required: Yes
- Type: string
The source Amazon Resource Name (ARN).
- SourceType
-
- Type: string
The source job type.
TrialComponentSourceDetail
Description
Detailed information about the source of a trial component. Either ProcessingJob
or TrainingJob
is returned.
Members
- ProcessingJob
-
- Type: ProcessingJob structure
Information about a processing job that's the source of a trial component.
- SourceArn
-
- Type: string
The Amazon Resource Name (ARN) of the source.
- TrainingJob
-
- Type: TrainingJob structure
Information about a training job that's the source of a trial component.
- TransformJob
-
- Type: TransformJob structure
Information about a transform job that's the source of a trial component.
TrialComponentStatus
Description
The status of the trial component.
Members
- Message
-
- Type: string
If the component failed, a message describing why.
- PrimaryStatus
-
- Type: string
The status of the trial component.
TrialComponentSummary
Description
A summary of the properties of a trial component. To get all the properties, call the DescribeTrialComponent API and provide the TrialComponentName
.
Members
- CreatedBy
-
- Type: UserContext structure
Who created the trial component.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component was created.
- DisplayName
-
- Type: string
The name of the component as displayed. If
DisplayName
isn't specified,TrialComponentName
is displayed. - EndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component ended.
- LastModifiedBy
-
- Type: UserContext structure
Who last modified the component.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component was last modified.
- StartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the component started.
- Status
-
- Type: TrialComponentStatus structure
The status of the component. States include:
-
InProgress
-
Completed
-
Failed
- TrialComponentArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial component.
- TrialComponentName
-
- Type: string
The name of the trial component.
- TrialComponentSource
-
- Type: TrialComponentSource structure
The Amazon Resource Name (ARN) and job type of the source of a trial component.
TrialSource
Description
The source of the trial.
Members
- SourceArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the source.
- SourceType
-
- Type: string
The source job type.
TrialSummary
Description
A summary of the properties of a trial. To get the complete set of properties, call the DescribeTrial API and provide the TrialName
.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the trial was created.
- DisplayName
-
- Type: string
The name of the trial as displayed. If
DisplayName
isn't specified,TrialName
is displayed. - LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the trial was last modified.
- TrialArn
-
- Type: string
The Amazon Resource Name (ARN) of the trial.
- TrialName
-
- Type: string
The name of the trial.
- TrialSource
-
- Type: TrialSource structure
The source of the trial.
TtlDuration
Description
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt
= EventTime
+ TtlDuration
. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Members
- Unit
-
- Type: string
TtlDuration
time unit. - Value
-
- Type: int
TtlDuration
time value.
TuningJobCompletionCriteria
Description
The job completion criteria.
Members
- BestObjectiveNotImproving
-
- Type: BestObjectiveNotImproving structure
A flag to stop your hyperparameter tuning job if model performance fails to improve as evaluated against an objective function.
- ConvergenceDetected
-
- Type: ConvergenceDetected structure
A flag to top your hyperparameter tuning job if automatic model tuning (AMT) has detected that your model has converged as evaluated against your objective function.
- TargetObjectiveMetricValue
-
- Type: float
The value of the objective metric.
TuningJobStepMetaData
Description
Metadata for a tuning step.
Members
- Arn
-
- Type: string
The Amazon Resource Name (ARN) of the tuning job that was run by this step execution.
USD
Description
Represents an amount of money in United States dollars.
Members
- Cents
-
- Type: int
The fractional portion, in cents, of the amount.
- Dollars
-
- Type: int
The whole number of dollars in the amount.
- TenthFractionsOfACent
-
- Type: int
Fractions of a cent, in tenths.
UiConfig
Description
Provided configuration information for the worker UI for a labeling job. Provide either HumanTaskUiArn
or UiTemplateS3Uri
.
For named entity recognition, 3D point cloud and video frame labeling jobs, use HumanTaskUiArn
.
For all other Ground Truth built-in task types and custom task types, use UiTemplateS3Uri
to specify the location of a worker task template in Amazon S3.
Members
- HumanTaskUiArn
-
- Type: string
The ARN of the worker task template used to render the worker UI and tools for labeling job tasks.
Use this parameter when you are creating a labeling job for named entity recognition, 3D point cloud and video frame labeling jobs. Use your labeling job task type to select one of the following ARNs and use it with this parameter when you create a labeling job. Replace
aws-region
with the Amazon Web Services Region you are creating your labeling job in. For example, replaceaws-region
withus-west-1
if you create a labeling job in US West (N. California).Named Entity Recognition
Use the following
HumanTaskUiArn
for named entity recognition labeling jobs:arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition
3D Point Cloud HumanTaskUiArns
Use this
HumanTaskUiArn
for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs.-
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection
Use this
HumanTaskUiArn
for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs.-
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking
Use this
HumanTaskUiArn
for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs.-
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation
Video Frame HumanTaskUiArns
Use this
HumanTaskUiArn
for video frame object detection and video frame object detection adjustment labeling jobs.-
arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection
Use this
HumanTaskUiArn
for video frame object tracking and video frame object tracking adjustment labeling jobs.-
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking
- UiTemplateS3Uri
-
- Type: string
The Amazon S3 bucket location of the UI template, or worker task template. This is the template used to render the worker UI and tools for labeling job tasks. For more information about the contents of a UI template, see Creating Your Custom Labeling Task Template.
UiTemplate
Description
The Liquid template for the worker user interface.
Members
- Content
-
- Required: Yes
- Type: string
The content of the Liquid template for the worker user interface.
UiTemplateInfo
Description
Container for user interface template information.
Members
- ContentSha256
-
- Type: string
The SHA-256 digest of the contents of the template.
- Url
-
- Type: string
The URL for the user interface template.
UserContext
Description
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
Members
- DomainId
-
- Type: string
The domain associated with the user.
- IamIdentity
-
- Type: IamIdentity structure
The IAM Identity details associated with the user. These details are associated with model package groups, model packages, and project entities only.
- UserProfileArn
-
- Type: string
The Amazon Resource Name (ARN) of the user's profile.
- UserProfileName
-
- Type: string
The name of the user's profile.
UserProfileDetails
Description
The user profile details.
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time.
- DomainId
-
- Type: string
The domain ID.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last modified time.
- Status
-
- Type: string
The status.
- UserProfileName
-
- Type: string
The user profile name.
UserSettings
Description
A collection of settings that apply to users in a domain. These settings are specified when the CreateUserProfile
API is called, and as DefaultUserSettings
when the CreateDomain
API is called.
SecurityGroups
is aggregated when specified in both calls. For all other settings in UserSettings
, the values specified in CreateUserProfile
take precedence over those specified in CreateDomain
.
Members
- CanvasAppSettings
-
- Type: CanvasAppSettings structure
The Canvas app settings.
- CodeEditorAppSettings
-
- Type: CodeEditorAppSettings structure
The Code Editor application settings.
- CustomFileSystemConfigs
-
- Type: Array of CustomFileSystemConfig structures
The settings for assigning a custom file system to a user profile. Permitted users can access this file system in Amazon SageMaker Studio.
- CustomPosixUserConfig
-
- Type: CustomPosixUserConfig structure
Details about the POSIX identity that is used for file system operations.
- DefaultLandingUri
-
- Type: string
The default experience that the user is directed to when accessing the domain. The supported values are:
-
studio::
: Indicates that Studio is the default experience. This value can only be passed ifStudioWebPortal
is set toENABLED
. -
app:JupyterServer:
: Indicates that Studio Classic is the default experience.
- ExecutionRole
-
- Type: string
The execution role for the user.
- JupyterLabAppSettings
-
- Type: JupyterLabAppSettings structure
The settings for the JupyterLab application.
- JupyterServerAppSettings
-
- Type: JupyterServerAppSettings structure
The Jupyter server's app settings.
- KernelGatewayAppSettings
-
- Type: KernelGatewayAppSettings structure
The kernel gateway app settings.
- RSessionAppSettings
-
- Type: RSessionAppSettings structure
A collection of settings that configure the
RSessionGateway
app. - RStudioServerProAppSettings
-
- Type: RStudioServerProAppSettings structure
A collection of settings that configure user interaction with the
RStudioServerPro
app. - SecurityGroups
-
- Type: Array of strings
The security groups for the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.
Optional when the
CreateDomain.AppNetworkAccessType
parameter is set toPublicInternetOnly
.Required when the
CreateDomain.AppNetworkAccessType
parameter is set toVpcOnly
, unless specified as part of theDefaultUserSettings
for the domain.Amazon SageMaker adds a security group to allow NFS traffic from Amazon SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.
- SharingSettings
-
- Type: SharingSettings structure
Specifies options for sharing Amazon SageMaker Studio notebooks.
- SpaceStorageSettings
-
- Type: DefaultSpaceStorageSettings structure
The storage settings for a space.
- StudioWebPortal
-
- Type: string
Whether the user can access Studio. If this value is set to
DISABLED
, the user cannot access Studio, even if that is the default experience for the domain. - StudioWebPortalSettings
-
- Type: StudioWebPortalSettings structure
Studio settings. If these settings are applied on a user level, they take priority over the settings applied on a domain level.
- TensorBoardAppSettings
-
- Type: TensorBoardAppSettings structure
The TensorBoard app settings.
VariantProperty
Description
Specifies a production variant property type for an Endpoint.
If you are updating an endpoint with the RetainAllVariantProperties
option of UpdateEndpointInput set to true
, the VariantProperty
objects listed in the ExcludeRetainedVariantProperties
parameter of UpdateEndpointInput override the existing variant properties of the endpoint.
Members
- VariantPropertyType
-
- Required: Yes
- Type: string
The type of variant property. The supported values are:
-
DesiredInstanceCount
: Overrides the existing variant instance counts using theInitialInstanceCount
values in theProductionVariants
of CreateEndpointConfig. -
DesiredWeight
: Overrides the existing variant weights using theInitialVariantWeight
values in theProductionVariants
of CreateEndpointConfig. -
DataCaptureConfig
: (Not currently supported.)
VectorConfig
Description
Configuration for your vector collection type.
Members
- Dimension
-
- Required: Yes
- Type: int
The number of elements in your vector.
Vertex
Description
A lineage entity connected to the starting entity(ies).
Members
- Arn
-
- Type: string
The Amazon Resource Name (ARN) of the lineage entity resource.
- LineageType
-
- Type: string
The type of resource of the lineage entity.
- Type
-
- Type: string
The type of the lineage entity resource. For example:
DataSet
,Model
,Endpoint
, etc...
VisibilityConditions
Description
The list of key-value pairs used to filter your search results. If a search result contains a key from your list, it is included in the final search response if the value associated with the key in the result matches the value you specified. If the value doesn't match, the result is excluded from the search response. Any resources that don't have a key from the list that you've provided will also be included in the search response.
Members
- Key
-
- Type: string
The key that specifies the tag that you're using to filter the search results. It must be in the following format:
Tags.<key>
. - Value
-
- Type: string
The value for the tag that you're using to filter the search results.
VpcConfig
Description
Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
Members
- SecurityGroupIds
-
- Required: Yes
- Type: Array of strings
The VPC security group IDs, in the form
sg-xxxxxxxx
. Specify the security groups for the VPC that is specified in theSubnets
field. - Subnets
-
- Required: Yes
- Type: Array of strings
The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see Supported Instance Types and Availability Zones.
WarmPoolStatus
Description
Status and billing information about the warm pool.
Members
- ResourceRetainedBillableTimeInSeconds
-
- Type: int
The billable time in seconds used by the warm pool. Billable time refers to the absolute wall-clock time.
Multiply
ResourceRetainedBillableTimeInSeconds
by the number of instances (InstanceCount
) in your training cluster to get the total compute time SageMaker bills you if you run warm pool training. The formula is as follows:ResourceRetainedBillableTimeInSeconds * InstanceCount
. - ReusedByJob
-
- Type: string
The name of the matching training job that reused the warm pool.
- Status
-
- Required: Yes
- Type: string
The status of the warm pool.
-
InUse
: The warm pool is in use for the training job. -
Available
: The warm pool is available to reuse for a matching training job. -
Reused
: The warm pool moved to a matching training job for reuse. -
Terminated
: The warm pool is no longer available. Warm pools are unavailable if they are terminated by a user, terminated for a patch update, or terminated for exceeding the specifiedKeepAlivePeriodInSeconds
.
WorkerAccessConfiguration
Description
Use this optional parameter to constrain access to an Amazon S3 resource based on the IP address using supported IAM global condition keys. The Amazon S3 resource is accessed in the worker portal using a Amazon S3 presigned URL.
Members
- S3Presign
-
- Type: S3Presign structure
Defines any Amazon S3 resource constraints.
Workforce
Description
A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
Members
- CognitoConfig
-
- Type: CognitoConfig structure
The configuration of an Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
- CreateDate
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date that the workforce is created.
- FailureReason
-
- Type: string
The reason your workforce failed.
- LastUpdatedDate
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The most recent date that UpdateWorkforce was used to successfully add one or more IP address ranges (CIDRs) to a private workforce's allow list.
- OidcConfig
-
- Type: OidcConfigForResponse structure
The configuration of an OIDC Identity Provider (IdP) private workforce.
- SourceIpConfig
-
- Type: SourceIpConfig structure
A list of one to ten IP address ranges (CIDRs) to be added to the workforce allow list. By default, a workforce isn't restricted to specific IP addresses.
- Status
-
- Type: string
The status of your workforce.
- SubDomain
-
- Type: string
The subdomain for your OIDC Identity Provider.
- WorkforceArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the private workforce.
- WorkforceName
-
- Required: Yes
- Type: string
The name of the private workforce.
- WorkforceVpcConfig
-
- Type: WorkforceVpcConfigResponse structure
The configuration of a VPC workforce.
WorkforceVpcConfigRequest
Description
The VPC object you use to create or update a workforce.
Members
- SecurityGroupIds
-
- Type: Array of strings
The VPC security group IDs, in the form
sg-xxxxxxxx
. The security groups must be for the same VPC as specified in the subnet. - Subnets
-
- Type: Array of strings
The ID of the subnets in the VPC that you want to connect.
- VpcId
-
- Type: string
The ID of the VPC that the workforce uses for communication.
WorkforceVpcConfigResponse
Description
A VpcConfig object that specifies the VPC that you want your workforce to connect to.
Members
- SecurityGroupIds
-
- Required: Yes
- Type: Array of strings
The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
- Subnets
-
- Required: Yes
- Type: Array of strings
The ID of the subnets in the VPC that you want to connect.
- VpcEndpointId
-
- Type: string
The IDs for the VPC service endpoints of your VPC workforce when it is created and updated.
- VpcId
-
- Required: Yes
- Type: string
The ID of the VPC that the workforce uses for communication.
WorkspaceSettings
Description
The workspace settings for the SageMaker Canvas application.
Members
- S3ArtifactPath
-
- Type: string
The Amazon S3 bucket used to store artifacts generated by Canvas. Updating the Amazon S3 location impacts existing configuration settings, and Canvas users no longer have access to their artifacts. Canvas users must log out and log back in to apply the new location.
- S3KmsKeyId
-
- Type: string
The Amazon Web Services Key Management Service (KMS) encryption key ID that is used to encrypt artifacts generated by Canvas in the Amazon S3 bucket.
Workteam
Description
Provides details about a labeling work team.
Members
- CreateDate
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the work team was created (timestamp).
- Description
-
- Required: Yes
- Type: string
A description of the work team.
- LastUpdatedDate
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the work team was last updated (timestamp).
- MemberDefinitions
-
- Required: Yes
- Type: Array of MemberDefinition structures
A list of
MemberDefinition
objects that contains objects that identify the workers that make up the work team.Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use
CognitoMemberDefinition
. For workforces created using your own OIDC identity provider (IdP) useOidcMemberDefinition
. - NotificationConfiguration
-
- Type: NotificationConfiguration structure
Configures SNS notifications of available or expiring work items for work teams.
- ProductListingIds
-
- Type: Array of strings
The Amazon Marketplace identifier for a vendor's work team.
- SubDomain
-
- Type: string
The URI of the labeling job's user interface. Workers open this URI to start labeling your data objects.
- WorkerAccessConfiguration
-
- Type: WorkerAccessConfiguration structure
Describes any access constraints that have been defined for Amazon S3 resources.
- WorkforceArn
-
- Type: string
The Amazon Resource Name (ARN) of the workforce.
- WorkteamArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) that identifies the work team.
- WorkteamName
-
- Required: Yes
- Type: string
The name of the work team.