SDK for PHP 3.x

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, and test channels.

ValidationSpecification

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 the ResourceSpec in the CreateApp call overrides the value passed as part of the ResourceSpec configured for the user profile or the domain. If InstanceType is not specified in any of those three ResourceSpec values for a KernelGateway app, the CreateApp 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 the AppImageConfig 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.

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.

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([
    '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
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 in AutoMLProblemTypeConfig (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 an InputConfig object in the request syntax. The presence of both objects in the CreateCompilationJob 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

The results for this operation are always empty.

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>',
            ],
            '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',
            ],
            '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>',
            ],
            '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 when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided. If setting up the domain for use with RStudio, this value must be set to Service.

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 the CreateUserProfile API.

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.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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 KMS

Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a KmsKeyId when using an instance type with local storage. If any of the models that you specify in the ProductionVariants parameter use nitro-based instances with local storage, do not specify a value for the KmsKeyId parameter. If you specify a value for KmsKeyId when using any nitro-based instances with local storage, the call to CreateEndpointConfig fails.

For a list of instance types that support local instance storage, see Instance Store Volumes.

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 on ProductionVariants. If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants.

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 in ExperimentName 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 FeatureGroups 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 a Record in a FeatureGroup.

An EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a FeatureGroup. All Records in the FeatureGroup must have a corresponding EventTime.

An EventTime can be a String or Fractional.

  • Fractional: EventTime feature values must be a Unix timestamp in seconds.

  • String: EventTime feature values must be an ISO-8601 string in the format. The following formats are supported yyyy-MM-dd'T'HH:mm:ssZ and yyyy-MM-dd'T'HH:mm:ss.SSSZ where yyyy, MM, and dd represent the year, month, and day respectively and HH, mm, ss, and if applicable, SSS represent the hour, month, second and milliseconds respsectively. 'T' and Z are constants.

FeatureDefinitions
Required: Yes
Type: Array of FeatureDefinition structures

A list of Feature names and types. Name and Type is compulsory per Feature.

Valid feature FeatureTypes are Integral, Fractional and String.

FeatureNames cannot be any of the following: is_deleted, write_time, api_invocation_time

You can create up to 2,500 FeatureDefinitions per FeatureGroup.

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 specifying True for the EnableOnlineStore flag in OnlineStoreConfig.

You can also include an Amazon Web Services KMS key ID (KMSKeyId) for at-rest encryption of the OnlineStore.

The default value is False.

RecordIdentifierFeatureName
Required: Yes
Type: string

The name of the Feature whose value uniquely identifies a Record defined in the FeatureStore. Only the latest record per identifier value will be stored in the OnlineStore. RecordIdentifierFeatureName must be one of feature definitions' names.

You use the RecordIdentifierFeatureName to access data in a FeatureStore.

This name:

  • Must start 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 an OfflineStoreConfig is provided.

Tags
Type: Array of Tag structures

Tags used to identify Features in each FeatureGroup.

ThroughputConfig
Type: ThroughputConfig structure

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.

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

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

Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.

All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM as the WarmStartType value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.

All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.

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 the Image 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

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 for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3: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 and UpdateEndpoint 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. Each ModelVariantConfig 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 and Advanced to initiate a load test. If left unspecified, Amazon SageMaker Inference Recommender will run an instance recommendation (DEFAULT) job.

OutputConfig

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

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 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 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 an S3DataSource is optional if you use SnsDataSource 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 the LabelAttributeName 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

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 to False. If not specified, AutomaticModelRegistration defaults to False.

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 or Artifact.

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 or Artifact.

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

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 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.

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

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 a tag 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

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 or Artifact.

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:

  1. Creates a network interface in the SageMaker VPC.

  2. (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.

  3. 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 the SubnetId parameter.

InstanceMetadataServiceConfiguration

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

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 or Artifact.

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>', // REQUIRED
                    '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, use MaxRuntimeInSeconds to set a time limit for training. Use MaxWaitTimeInSeconds 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 an InternalServerError.

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 and validation_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 the TrainingInputMode 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 to Line, RecordIO, or TFRecord.

To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.

To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.

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 to 0 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 is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.

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.

The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the MaxConcurrentTransforms 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',
            ],
            '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>',
            ],
            '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 for CognitoConfig.

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 for OidcConfig.

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) use OidcMemberDefinition. 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 same ClientId and UserPool 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 in Groups.

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

The results for this operation are always empty.

Errors

ConflictException:

There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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 or Artifact.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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 or Artifact.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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 or Artifact.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

Errors

ConflictException:

There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.

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

The results for this operation are always empty.

Errors

ConflictException:

There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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 or Artifact.

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

The results for this operation are always empty.

Errors

ConflictException:

There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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

The results for this operation are always empty.

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, returns false.

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

The results for this operation are always empty.

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',