Amazon SageMaker Service 2017-07-24
- Client: Aws\SageMaker\SageMakerClient
- Service ID: sagemaker
- Version: 2017-07-24
This page describes the parameters and results for the operations of the Amazon SageMaker Service (2017-07-24), and shows how to use the Aws\SageMaker\SageMakerClient object to call the described operations. This documentation is specific to the 2017-07-24 API version of the service.
Operation Summary
Each of the following operations can be created from a client using
$client->getCommand('CommandName')
, where "CommandName" is the
name of one of the following operations. Note: a command is a value that
encapsulates an operation and the parameters used to create an HTTP request.
You can also create and send a command immediately using the magic methods
available on a client object: $client->commandName(/* parameters */)
.
You can send the command asynchronously (returning a promise) by appending the
word "Async" to the operation name: $client->commandNameAsync(/* parameters */)
.
- AddAssociation ( array $params = [] )
Creates an association between the source and the destination.
- AddTags ( array $params = [] )
Adds or overwrites one or more tags for the specified Amazon SageMaker resource.
- AssociateTrialComponent ( array $params = [] )
Associates a trial component with a trial.
- CreateAction ( array $params = [] )
Creates an action.
- CreateAlgorithm ( array $params = [] )
Create a machine learning algorithm that you can use in Amazon SageMaker and list in the AWS 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.
- CreateCodeRepository ( array $params = [] )
Creates a Git repository as a resource in your Amazon 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 used by Amazon SageMaker Studio.
- 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 Amazon SageMaker hosting services uses to deploy models.
- CreateExperiment ( array $params = [] )
Creates an SageMaker experiment.
- CreateFeatureGroup ( array $params = [] )
Create a new FeatureGroup.
- CreateFlowDefinition ( array $params = [] )
Creates a flow definition.
- 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.
- CreateLabelingJob ( array $params = [] )
Creates a job that uses workers to label the data objects in your input dataset.
- CreateModel ( array $params = [] )
Creates a model in Amazon SageMaker.
- CreateModelBiasJobDefinition ( array $params = [] )
Creates the definition for a model bias 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 Amazon SageMaker models or list on AWS 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 Endoint.
- CreateNotebookInstance ( array $params = [] )
Creates an Amazon SageMaker notebook instance.
- CreateNotebookInstanceLifecycleConfig ( array $params = [] )
Creates a lifecycle configuration that you can associate with a notebook instance.
- CreatePipeline ( array $params = [] )
Creates a pipeline using a JSON pipeline definition.
- CreatePresignedDomainUrl ( array $params = [] )
Creates a URL for a specified UserProfile in a Domain.
- 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.
- CreateTrainingJob ( array $params = [] )
Starts a model training job.
- CreateTransformJob ( array $params = [] )
Starts a transform job.
- CreateTrial ( array $params = [] )
Creates an Amazon 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.
- DeleteCodeRepository ( array $params = [] )
Deletes the specified Git repository from your account.
- 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.
- DeleteEndpoint ( array $params = [] )
Deletes an endpoint.
- DeleteEndpointConfig ( array $params = [] )
Deletes an endpoint configuration.
- DeleteExperiment ( array $params = [] )
Deletes an Amazon 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.
- DeleteHumanTaskUi ( array $params = [] )
Use this operation to delete a human task user interface (worker task template).
- DeleteImage ( array $params = [] )
Deletes a SageMaker image and all versions of the image.
- DeleteImageVersion ( array $params = [] )
Deletes a version of a SageMaker image.
- DeleteModel ( array $params = [] )
Deletes a model.
- DeleteModelBiasJobDefinition ( array $params = [] )
Deletes an Amazon SageMaker model bias job definition.
- 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 Amazon SageMaker notebook instance.
- DeleteNotebookInstanceLifecycleConfig ( array $params = [] )
Deletes a notebook instance lifecycle configuration.
- DeletePipeline ( array $params = [] )
Deletes a pipeline if there are no in-progress executions.
- DeleteProject ( array $params = [] )
Delete the specified project.
- DeleteTags ( array $params = [] )
Deletes the specified tags from an Amazon 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 Amazon SageMaker job.
- 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.
- 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.
- DescribeFlowDefinition ( array $params = [] )
Returns information about the specified flow definition.
- DescribeHumanTaskUi ( array $params = [] )
Returns information about the requested human task user interface (worker task template).
- DescribeHyperParameterTuningJob ( array $params = [] )
Gets a description of a hyperparameter tuning job.
- DescribeImage ( array $params = [] )
Describes a SageMaker image.
- DescribeImageVersion ( array $params = [] )
Describes a version of a SageMaker image.
- DescribeLabelingJob ( array $params = [] )
Gets information about a labeling job.
- 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.
- 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 Amazon SageMaker models or list them on AWS 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.
- 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.
- 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.
- 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.
- GetSearchSuggestions ( array $params = [] )
An auto-complete API for the search functionality in the Amazon SageMaker console.
- ListActions ( array $params = [] )
Lists the actions in your account and their properties.
- ListAlgorithms ( array $params = [] )
Lists the machine learning algorithms that have been created.
- 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.
- 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.
- 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.
- 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.
- ListLabelingJobs ( array $params = [] )
Gets a list of labeling jobs.
- ListLabelingJobsForWorkteam ( array $params = [] )
Gets a list of labeling jobs assigned to a specified work team.
- ListModelBiasJobDefinitions ( array $params = [] )
Lists model bias jobs definitions that satisfy various filters.
- ListModelExplainabilityJobDefinitions ( array $params = [] )
Lists model explainability job definitions that satisfy various filters.
- ListModelPackageGroups ( array $params = [] )
Gets a list of the model groups in your AWS 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.
- 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 Amazon SageMaker notebook instances in the requester's account in an AWS Region.
- 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 AWS account.
- ListSubscribedWorkteams ( array $params = [] )
Gets a list of the work teams that you are subscribed to in the AWS Marketplace.
- ListTags ( array $params = [] )
Returns the tags for the specified Amazon 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 AWS 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.
- RegisterDevices ( array $params = [] )
Register devices.
- RenderUiTemplate ( array $params = [] )
Renders the UI template so that you can preview the worker's experience.
- Search ( array $params = [] )
Finds Amazon SageMaker resources that match a search query.
- 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 the termination of a running job.
- StopCompilationJob ( array $params = [] )
Stops a model compilation job.
- 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.
- StopLabelingJob ( array $params = [] )
Stops a running labeling job.
- StopMonitoringSchedule ( array $params = [] )
Stops a previously started monitoring schedule.
- StopNotebookInstance ( array $params = [] )
Terminates the ML compute instance.
- 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 transform job.
- UpdateAction ( array $params = [] )
Updates an action.
- UpdateAppImageConfig ( array $params = [] )
Updates the properties of an AppImageConfig.
- UpdateArtifact ( array $params = [] )
Updates an artifact.
- 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 new EndpointConfig specified in the request, switches to using newly created endpoint, and then deletes resources provisioned for the endpoint using the previous EndpointConfig (there is no availability loss).
- 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.
- UpdateImage ( array $params = [] )
Updates the properties of a SageMaker image.
- UpdateModelPackage ( array $params = [] )
Updates a versioned model.
- 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.
- UpdateTrainingJob ( array $params = [] )
Update a model training job to request a new Debugger profiling configuration.
- 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, $operationParameters). This client supports the following paginators:
- ListActions
- ListAlgorithms
- ListAppImageConfigs
- ListApps
- ListArtifacts
- ListAssociations
- ListAutoMLJobs
- ListCandidatesForAutoMLJob
- ListCodeRepositories
- ListCompilationJobs
- ListContexts
- ListDataQualityJobDefinitions
- ListDeviceFleets
- ListDevices
- ListDomains
- ListEdgePackagingJobs
- ListEndpointConfigs
- ListEndpoints
- ListExperiments
- ListFeatureGroups
- ListFlowDefinitions
- ListHumanTaskUis
- ListHyperParameterTuningJobs
- ListImageVersions
- ListImages
- ListLabelingJobs
- ListLabelingJobsForWorkteam
- ListModelBiasJobDefinitions
- ListModelExplainabilityJobDefinitions
- ListModelPackageGroups
- ListModelPackages
- ListModelQualityJobDefinitions
- ListModels
- ListMonitoringExecutions
- ListMonitoringSchedules
- ListNotebookInstanceLifecycleConfigs
- ListNotebookInstances
- ListPipelineExecutionSteps
- ListPipelineExecutions
- ListPipelineParametersForExecution
- ListPipelines
- ListProcessingJobs
- ListProjects
- ListSubscribedWorkteams
- ListTags
- ListTrainingJobs
- ListTrainingJobsForHyperParameterTuningJob
- ListTransformJobs
- ListTrialComponents
- ListTrials
- ListUserProfiles
- ListWorkforces
- ListWorkteams
- Search
Waiters
Waiters allow you to poll a resource until it enters into a desired state. A waiter has a name used to describe what it does, and is associated with an API operation. When creating a waiter, you can provide the API operation parameters associated with the corresponding operation. Waiters can be accessed using the getWaiter($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 |
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', '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
Errors
-
Resource being access is not found.
-
You have exceeded an Amazon 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 Amazon SageMaker resource. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints.
Each tag consists of a key and an optional value. Tag keys must be unique per resource. For more information about tags, see For more information, see AWS Tagging Strategies.
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
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 AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS Resources.
Result Syntax
[ 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ]
Result Details
Members
- Tags
-
- Type: Array of Tag structures
A list of tags associated with the Amazon 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
Result Syntax
[ 'TrialArn' => '<string>', 'TrialComponentArn' => '<string>', ]
Result Details
Members
Errors
-
Resource being access is not found.
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
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 AWS 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
Errors
-
You have exceeded an Amazon 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 Amazon SageMaker and list in the AWS Marketplace.
Parameter Syntax
$result = $client->createAlgorithm([ 'AlgorithmDescription' => '<string>', 'AlgorithmName' => '<string>', // REQUIRED 'CertifyForMarketplace' => true || false, 'InferenceSpecification' => [ 'Containers' => [ // REQUIRED [ 'ContainerHostname' => '<string>', 'Image' => '<string>', // REQUIRED 'ImageDigest' => '<string>', 'ModelDataUrl' => '<string>', 'ProductId' => '<string>', ], // ... ], 'SupportedContentTypes' => ['<string>', ...], // REQUIRED 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], // REQUIRED 'SupportedTransformInstanceTypes' => ['<string>', ...], ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'TrainingSpecification' => [ // 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>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'InputMode' => 'Pipe|File', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, // REQUIRED ], ], // ... ], 'OutputDataConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'ResourceConfig' => [ // REQUIRED '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.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', // REQUIRED 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], 'StoppingCondition' => [ // REQUIRED 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TrainingInputMode' => 'Pipe|File', // 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', // 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 AWS 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 AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS Resources.
- TrainingSpecification
-
- Required: Yes
- Type: TrainingSpecification structure
Specifies details about training jobs run by this algorithm, including the following:
-
The Amazon ECR path of the container and the version digest of the algorithm.
-
The hyperparameters that the algorithm supports.
-
The instance types that the algorithm supports for training.
-
Whether the algorithm supports distributed training.
-
The metrics that the algorithm emits to Amazon CloudWatch.
-
Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
-
The input channels that the algorithm supports for training data. For example, an algorithm might support
train
,validation
, andtest
channels.
- ValidationSpecification
-
- Type: AlgorithmValidationSpecification structure
Specifies configurations for one or more training jobs and that Amazon SageMaker runs to test the algorithm's training code and, optionally, one or more batch transform jobs that Amazon SageMaker runs to test the algorithm's inference code.
Result Syntax
[ 'AlgorithmArn' => '<string>', ]
Result Details
Members
Errors
There are no errors described for this operation.
CreateApp
$result = $client->createApp
([/* ... */]); $promise = $client->createAppAsync
([/* ... */]);
Creates a running App for the specified UserProfile. Supported Apps are JupyterServer and KernelGateway. This operation is automatically invoked by Amazon SageMaker Studio upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.
Parameter Syntax
$result = $client->createApp([ 'AppName' => '<string>', // REQUIRED 'AppType' => 'JupyterServer|KernelGateway|TensorBoard', // 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.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.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'UserProfileName' => '<string>', // REQUIRED ]);
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.
- Tags
-
- Type: Array of Tag structures
Each tag consists of a key and an optional value. Tag keys must be unique per resource.
- UserProfileName
-
- Required: Yes
- Type: string
The user profile name.
Result Syntax
[ 'AppArn' => '<string>', ]
Result Details
Errors
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
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 (EFS) storage volume on the image, and a list of the kernels in the image.
Parameter Syntax
$result = $client->createAppImageConfig([ 'AppImageConfigName' => '<string>', // REQUIRED '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.
- KernelGatewayImageConfig
-
- Type: KernelGatewayImageConfig structure
The KernelGatewayImageConfig.
- Tags
-
- Type: Array of Tag structures
A list of tags to apply to the AppImageConfig.
Result Syntax
[ 'AppImageConfigArn' => '<string>', ]
Result Details
Errors
-
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 AWS 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
Errors
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
CreateAutoMLJob
$result = $client->createAutoMLJob
([/* ... */]); $promise = $client->createAutoMLJobAsync
([/* ... */]);
Creates an Autopilot job.
Find the best performing model after you run an Autopilot job by calling . Deploy that model by following the steps described in Step 6.1: Deploy the Model to Amazon SageMaker Hosting Services.
For information about how to use Autopilot, see Automate Model Development with Amazon SageMaker Autopilot.
Parameter Syntax
$result = $client->createAutoMLJob([ 'AutoMLJobConfig' => [ 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'SecurityConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'VolumeKmsKeyId' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], // REQUIRED 'Subnets' => ['<string>', ...], // REQUIRED ], ], ], 'AutoMLJobName' => '<string>', // REQUIRED 'AutoMLJobObjective' => [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC', // REQUIRED ], 'GenerateCandidateDefinitionsOnly' => true || false, 'InputDataConfig' => [ // REQUIRED [ 'CompressionType' => 'None|Gzip', 'DataSource' => [ // REQUIRED 'S3DataSource' => [ // REQUIRED 'S3DataType' => 'ManifestFile|S3Prefix', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'TargetAttributeName' => '<string>', // REQUIRED ], // ... ], 'OutputDataConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'ProblemType' => 'BinaryClassification|MulticlassClassification|Regression', 'RoleArn' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- AutoMLJobConfig
-
- Type: AutoMLJobConfig structure
Contains CompletionCriteria and SecurityConfig.
- AutoMLJobName
-
- Required: Yes
- Type: string
Identifies an Autopilot job. Must be unique to your account and is case-insensitive.
- AutoMLJobObjective
-
- Type: AutoMLJobObjective structure
Defines the objective of a an AutoML job. You provide a AutoMLJobObjective$MetricName and Autopilot infers whether to minimize or maximize it. If a metric is not specified, the most commonly used ObjectiveMetric for problem type is automaically selected.
- GenerateCandidateDefinitionsOnly
-
- Type: boolean
Generates possible candidates without training a model. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
- InputDataConfig
-
- Required: Yes
- Type: Array of AutoMLChannel structures
Similar to InputDataConfig supported by Tuning. Format(s) supported: CSV. Minimum of 500 rows.
- OutputDataConfig
-
- Required: Yes
- Type: AutoMLOutputDataConfig structure
Similar to OutputDataConfig supported by Tuning. Format(s) supported: CSV.
- ProblemType
-
- Type: string
Defines the kind of preprocessing and algorithms intended for the candidates. Options include: BinaryClassification, MulticlassClassification, and Regression.
- RoleArn
-
- Required: Yes
- Type: string
The ARN of the role that is used to access the data.
- Tags
-
- Type: Array of Tag structures
Each tag consists of a key and an optional value. Tag keys must be unique per resource.
Result Syntax
[ 'AutoMLJobArn' => '<string>', ]
Result Details
Errors
-
Resource being accessed is in use.
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
CreateCodeRepository
$result = $client->createCodeRepository
([/* ... */]); $promise = $client->createCodeRepositoryAsync
([/* ... */]);
Creates a Git repository as a resource in your Amazon SageMaker account. You can associate the repository with notebook instances so that you can use Git source control for the notebooks you create. The Git repository is a resource in your Amazon SageMaker account, so it can be associated with more than one notebook instance, and it persists independently from the lifecycle of any notebook instances it is associated with.
The repository can be hosted either in AWS CodeCommit 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 AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS Resources.
Result Syntax
[ 'CodeRepositoryArn' => '<string>', ]
Result Details
Members
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 AWS IoT Greengrass. In that case, deploy them as an ML resource.
In the request body, you provide the following:
-
A name for the compilation job
-
Information about the input model artifacts
-
The output location for the compiled model and the device (target) that the model runs on
-
The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker assumes to perform the model compilation job.
You can also provide a Tag
to track the model compilation job's resource use and costs. The response body contains the CompilationJobArn
for the compiled job.
To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
Parameter Syntax
$result = $client->createCompilationJob([ 'CompilationJobName' => '<string>', // REQUIRED 'InputConfig' => [ // REQUIRED 'DataInputConfig' => '<string>', // REQUIRED 'Framework' => 'TENSORFLOW|KERAS|MXNET|ONNX|PYTORCH|XGBOOST|TFLITE|DARKNET|SKLEARN', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], 'OutputConfig' => [ // REQUIRED 'CompilerOptions' => '<string>', 'KmsKeyId' => '<string>', 'S3OutputLocation' => '<string>', // REQUIRED 'TargetDevice' => 'lambda|ml_m4|ml_m5|ml_c4|ml_c5|ml_p2|ml_p3|ml_g4dn|ml_inf1|jetson_tx1|jetson_tx2|jetson_nano|jetson_xavier|rasp3b|imx8qm|deeplens|rk3399|rk3288|aisage|sbe_c|qcs605|qcs603|sitara_am57x|amba_cv22|x86_win32|x86_win64|coreml|jacinto_tda4vm', 'TargetPlatform' => [ 'Accelerator' => 'INTEL_GRAPHICS|MALI|NVIDIA', 'Arch' => 'X86_64|X86|ARM64|ARM_EABI|ARM_EABIHF', // REQUIRED 'Os' => 'ANDROID|LINUX', // REQUIRED ], ], 'RoleArn' => '<string>', // REQUIRED 'StoppingCondition' => [ // REQUIRED 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- CompilationJobName
-
- Required: Yes
- Type: string
A name for the model compilation job. The name must be unique within the AWS Region and within your AWS account.
- InputConfig
-
- Required: Yes
- 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.
- 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 AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS Resources.
Result Syntax
[ 'CompilationJobArn' => '<string>', ]
Result Details
Members
Errors
-
Resource being accessed is in use.
-
You have exceeded an Amazon 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 AWS 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
Errors
-
You have exceeded an Amazon 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 'EndpointInput' => [ // REQUIRED 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', // REQUIRED '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', // 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 AWS Billing and Cost Management User Guide.
Result Syntax
[ 'JobDefinitionArn' => '<string>', ]
Result Details
Members
Errors
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
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 'OutputConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', '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.
- 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 AWS Internet of Things (IoT).
- Tags
-
- Type: Array of Tag structures
Creates tags for the specified fleet.
Result Syntax
[]
Result Details
Errors
-
Resource being accessed is in use.
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
CreateDomain
$result = $client->createDomain
([/* ... */]); $promise = $client->createDomainAsync
([/* ... */]);
Creates a Domain
used by Amazon SageMaker Studio. A domain consists of an associated Amazon Elastic File System (EFS) volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. An AWS account is limited to one domain per region. Users within a domain can share notebook files and other artifacts with each other.
EFS storage
When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.
SageMaker uses the AWS Key Management Service (AWS KMS) to encrypt the EFS volume attached to the domain with an AWS managed customer master key (CMK) by default. For more control, you can specify a customer managed CMK. For more information, see Protect Data at Rest Using Encryption.
VPC configuration
All SageMaker Studio traffic between the domain and the EFS volume is through the specified VPC and subnets. For other Studio traffic, you can specify the AppNetworkAccessType
parameter. AppNetworkAccessType
corresponds to the network access type that you choose when you onboard to Studio. The following options are available:
-
PublicInternetOnly
- Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value. -
VpcOnly
- All Studio traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.When internet access is disabled, you won't be able to run a Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.
For more information, see Connect SageMaker Studio Notebooks to Resources in a VPC.
Parameter Syntax
$result = $client->createDomain([ 'AppNetworkAccessType' => 'PublicInternetOnly|VpcOnly', 'AuthMode' => 'SSO|IAM', // REQUIRED 'DefaultUserSettings' => [ // REQUIRED 'ExecutionRole' => '<string>', 'JupyterServerAppSettings' => [ '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.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.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionArn' => '<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.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.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'SecurityGroups' => ['<string>', ...], 'SharingSettings' => [ 'NotebookOutputOption' => 'Allowed|Disabled', 'S3KmsKeyId' => '<string>', 'S3OutputPath' => '<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.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.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], ], 'DomainName' => '<string>', // REQUIRED '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 Studio traffic is through the specified VPC and subnets
- AuthMode
-
- Required: Yes
- Type: string
The mode of authentication that members use to access the domain.
- DefaultUserSettings
-
- Required: Yes
- Type: UserSettings structure
The default user settings.
- DomainName
-
- Required: Yes
- Type: string
A name for the domain.
- HomeEfsFileSystemKmsKeyId
-
- Type: string
This member is deprecated and replaced with
KmsKeyId
. - KmsKeyId
-
- Type: string
SageMaker uses AWS KMS to encrypt the EFS volume attached to the domain with an AWS managed customer master key (CMK) by default. For more control, specify a customer managed CMK.
- SubnetIds
-
- Required: Yes
- Type: Array of strings
The VPC subnets that Studio 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.
- VpcId
-
- Required: Yes
- Type: string
The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
Result Syntax
[ 'DomainArn' => '<string>', 'Url' => '<string>', ]
Result Details
Members
Errors
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
Resource being accessed is in use.
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>', '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 CMK to use when encrypting the EBS volume the edge packaging job runs on.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact SageMaker Neo.
- Tags
-
- Type: Array of Tag structures
Creates tags for the packaging job.
Result Syntax
[]
Result Details
Errors
-
You have exceeded an Amazon 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. Amazon SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API.
Use this API to deploy models using Amazon SageMaker hosting services.
For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)).
You must not delete an EndpointConfig
that is in use by an endpoint that is live or while the UpdateEndpoint
or CreateEndpoint
operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig
.
The endpoint name must be unique within an AWS Region in your AWS account.
When it receives the request, Amazon SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads
, the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
When Amazon SageMaker receives the request, it sets the endpoint status to Creating
. After it creates the endpoint, it sets the status to InService
. Amazon SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API.
If any of the models hosted at this endpoint get model data from an Amazon S3 location, Amazon SageMaker uses AWS Security Token Service to download model artifacts from the S3 path you provided. AWS STS is activated in your IAM user account by default. If you previously deactivated AWS STS for a region, you need to reactivate AWS STS for that region. For more information, see Activating and Deactivating AWS STS in an AWS Region in the AWS Identity and Access Management User Guide.
To add the IAM role policies for using this API operation, go to the IAM console, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the role.
-
Option 1: For a full Amazon SageMaker access, search and attach the
AmazonSageMakerFullAccess
policy. -
Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role:
"Action": ["sagemaker:CreateEndpoint", "sagemaker:CreateEndpointConfig"]
"Resource": [
"arn:aws:sagemaker:region:account-id:endpoint/endpointName"
"arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"
]
For more information, see Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference.
Parameter Syntax
$result = $client->createEndpoint([ 'EndpointConfigName' => '<string>', // REQUIRED 'EndpointName' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- 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 AWS Region in your AWS account. The name is case-insensitive in
CreateEndpoint
, but the case is preserved and must be matched in . - Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS Resources.
Result Syntax
[ 'EndpointArn' => '<string>', ]
Result Details
Errors
-
You have exceeded an Amazon 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 Amazon SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel
API, to deploy and the resources that you want Amazon SageMaker to provision. Then you call the CreateEndpoint API.
Use this API if you want to use Amazon SageMaker hosting services to deploy models into production.
In the request, you define a ProductionVariant
, for each model that you want to deploy. Each ProductionVariant
parameter also describes the resources that you want Amazon SageMaker to provision. This includes the number and type of ML compute instances to deploy.
If you are hosting multiple models, you also assign a VariantWeight
to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. Amazon SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.
For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)).
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([ 'DataCaptureConfig' => [ 'CaptureContentTypeHeader' => [ 'CsvContentTypes' => ['<string>', ...], 'JsonContentTypes' => ['<string>', ...], ], 'CaptureOptions' => [ // REQUIRED [ 'CaptureMode' => 'Input|Output', // REQUIRED ], // ... ], 'DestinationS3Uri' => '<string>', // REQUIRED 'EnableCapture' => true || false, 'InitialSamplingPercentage' => <integer>, // REQUIRED 'KmsKeyId' => '<string>', ], 'EndpointConfigName' => '<string>', // REQUIRED 'KmsKeyId' => '<string>', 'ProductionVariants' => [ // REQUIRED [ 'AcceleratorType' => 'ml.eia1.medium|ml.eia1.large|ml.eia1.xlarge|ml.eia2.medium|ml.eia2.large|ml.eia2.xlarge', 'InitialInstanceCount' => <integer>, // REQUIRED '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', // REQUIRED 'ModelName' => '<string>', // REQUIRED 'VariantName' => '<string>', // REQUIRED ], // ... ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- DataCaptureConfig
-
- Type: DataCaptureConfig structure
- EndpointConfigName
-
- Required: Yes
- Type: string
The name of the endpoint configuration. You specify this name in a CreateEndpoint request.
- KmsKeyId
-
- Type: string
The Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.
The KmsKeyId can be any of the following formats:
-
Key ID:
1234abcd-12ab-34cd-56ef-1234567890ab
-
Key ARN:
arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
-
Alias name:
alias/ExampleAlias
-
Alias name ARN:
arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The KMS key policy must grant permission to the IAM role that you specify in your
CreateEndpoint
,UpdateEndpoint
requests. For more information, refer to the AWS Key Management Service section Using Key Policies in AWS KMSCertain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a
KmsKeyId
when using an instance type with local storage. If any of the models that you specify in theProductionVariants
parameter use nitro-based instances with local storage, do not specify a value for theKmsKeyId
parameter. If you specify a value forKmsKeyId
when using any nitro-based instances with local storage, the call toCreateEndpointConfig
fails.For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
- ProductionVariants
-
- Required: Yes
- Type: Array of ProductionVariant structures
An list of
ProductionVariant
objects, one for each model that you want to host at this endpoint. - Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS Resources.
Result Syntax
[ 'EndpointConfigArn' => '<string>', ]
Result Details
Members
Errors
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
CreateExperiment
$result = $client->createExperiment
([/* ... */]); $promise = $client->createExperimentAsync
([/* ... */]);
Creates an SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.
The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.
When you use Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
To add a description to an experiment, specify the optional Description
parameter. To add a description later, or to change the description, call the UpdateExperiment API.
To get a list of all your experiments, call the ListExperiments API. To view an experiment's properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
Parameter Syntax
$result = $client->createExperiment([ 'Description' => '<string>', 'DisplayName' => '<string>', 'ExperimentName' => '<string>', // REQUIRED 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- Description
-
- Type: string
The description of the experiment.
- DisplayName
-
- Type: string
The name of the experiment as displayed. The name doesn't need to be unique. If you don't specify
DisplayName
, the value inExperimentName
is displayed. - ExperimentName
-
- Required: Yes
- Type: string
The name of the experiment. The name must be unique in your AWS 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
Errors
-
You have exceeded an Amazon 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 AWS service quotas to see the FeatureGroup
s quota for your AWS account.
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 [ 'FeatureName' => '<string>', 'FeatureType' => 'Integral|Fractional|String', ], // ... ], 'FeatureGroupName' => '<string>', // REQUIRED 'OfflineStoreConfig' => [ 'DataCatalogConfig' => [ 'Catalog' => '<string>', // REQUIRED 'Database' => '<string>', // REQUIRED 'TableName' => '<string>', // REQUIRED ], 'DisableGlueTableCreation' => true || false, 'S3StorageConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'S3Uri' => '<string>', // REQUIRED ], ], 'OnlineStoreConfig' => [ 'EnableOnlineStore' => true || false, 'SecurityConfig' => [ 'KmsKeyId' => '<string>', ], ], 'RecordIdentifierFeatureName' => '<string>', // REQUIRED 'RoleArn' => '<string>', 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], ]);
Parameter Details
Members
- Description
-
- Type: string
A free-form description of a
FeatureGroup
. - EventTimeFeatureName
-
- Required: Yes
- Type: string
The name of the feature that stores the
EventTime
of aRecord
in aFeatureGroup
.An
EventTime
is a point in time when a new event occurs that corresponds to the creation or update of aRecord
in aFeatureGroup
. AllRecords
in theFeatureGroup
must have a correspondingEventTime
.An
EventTime
can be aString
orFractional
.-
Fractional
:EventTime
feature values must be a Unix timestamp in seconds. -
String
:EventTime
feature values must be an ISO-8601 string in the format. The following formats are supportedyyyy-MM-dd'T'HH:mm:ssZ
andyyyy-MM-dd'T'HH:mm:ss.SSSZ
whereyyyy
,MM
, anddd
represent the year, month, and day respectively andHH
,mm
,ss
, and if applicable,SSS
represent the hour, month, second and milliseconds respsectively.'T'
andZ
are constants.
- FeatureDefinitions
-
- Required: Yes
- Type: Array of FeatureDefinition structures
A list of
Feature
names and types.Name
andType
is compulsory perFeature
.Valid feature
FeatureType
s areIntegral
,Fractional
andString
.FeatureName
s cannot be any of the following:is_deleted
,write_time
,api_invocation_time
You can create up to 2,500
FeatureDefinition
s perFeatureGroup
. - FeatureGroupName
-
- Required: Yes
- Type: string
The name of the
FeatureGroup
. The name must be unique within an AWS Region in an AWS account. The name:-
Must start and end with an alphanumeric character.
-
Can only contain alphanumeric character and hyphens. Spaces are not allowed.
- 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 AWS Glue or AWS Hive data cataolgue.
-
An KMS encryption key to encrypt the Amazon S3 location used for
OfflineStore
.
To learn more about this parameter, see OfflineStoreConfig.
- OnlineStoreConfig
-
- Type: OnlineStoreConfig structure
You can turn the
OnlineStore
on or off by specifyingTrue
for theEnableOnlineStore
flag inOnlineStoreConfig
; the default value isFalse
.You can also include an AWS KMS key ID (
KMSKeyId
) for at-rest encryption of theOnlineStore
. - RecordIdentifierFeatureName
-
- Required: Yes
- Type: string
The name of the
Feature
whose value uniquely identifies aRecord
defined in theFeatureStore
. Only the latest record per identifier value will be stored in theOnlineStore
.RecordIdentifierFeatureName
must be one of feature definitions' names.You use the
RecordIdentifierFeatureName
to access data in aFeatureStore
.This name:
-
Must start and end with an alphanumeric character.
-
Can only contains alphanumeric characters, hyphens, underscores. Spaces are not allowed.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the
OfflineStore
if anOfflineStoreConfig
is provided. - Tags
-
- Type: Array of Tag structures
Tags used to identify
Features
in eachFeatureGroup
.
Result Syntax
[ 'FeatureGroupArn' => '<string>', ]
Result Details
Members
Errors
-
Resource being accessed is in use.
-
You have exceeded an Amazon 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' => [ // REQUIRED '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
-
- Required: Yes
- 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
Errors
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
Resource being accessed is in use.
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
Errors
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
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.
Parameter Syntax
$result = $client->createHyperParameterTuningJob([ 'HyperParameterTuningJobConfig' => [ // REQUIRED 'HyperParameterTuningJobObjective' => [ 'MetricName' => '<string>', // REQUIRED 'Type' => 'Maximize|Minimize', // REQUIRED ], 'ParameterRanges' => [ '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', ], // ... ], ], 'ResourceLimits' => [ // REQUIRED 'MaxNumberOfTrainingJobs' => <integer>, // REQUIRED 'MaxParallelTrainingJobs' => <integer>, // REQUIRED ], 'Strategy' => 'Bayesian|Random', // REQUIRED 'TrainingJobEarlyStoppingType' => 'Off|Auto', 'TuningJobCompletionCriteria' => [ 'TargetObjectiveMetricValue' => <float>, // REQUIRED ], ], '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', // REQUIRED ], 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', // REQUIRED ], 'DefinitionName' => '<string>', 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'HyperParameterRanges' => [ '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', ], // ... ], ], '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>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'InputMode' => 'Pipe|File', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, // REQUIRED ], ], // ... ], 'OutputDataConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'ResourceConfig' => [ // REQUIRED '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.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', // REQUIRED 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], 'RoleArn' => '<string>', // REQUIRED 'StaticHyperParameters' => ['<string>', ...], 'StoppingCondition' => [ // REQUIRED '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', // REQUIRED ], 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', // REQUIRED ], 'DefinitionName' => '<string>', 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'HyperParameterRanges' => [ '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', ], // ... ], ], '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>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'InputMode' => 'Pipe|File', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, // REQUIRED ], ], // ... ], 'OutputDataConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'ResourceConfig' => [ // REQUIRED '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.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', // REQUIRED 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], 'RoleArn' => '<string>', // REQUIRED 'StaticHyperParameters' => ['<string>', ...], 'StoppingCondition' => [ // REQUIRED '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
- 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 AWS account and AWS Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS Resources.
Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.
- TrainingJobDefinition
-
- Type: HyperParameterTrainingJobDefinition structure
The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.
- TrainingJobDefinitions
-
- Type: Array of HyperParameterTrainingJobDefinition structures
A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
- WarmStartConfig
-
- Type: HyperParameterTuningJobWarmStartConfig structure
Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify
IDENTICAL_DATA_AND_ALGORITHM
as theWarmStartType
value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
Result Syntax
[ 'HyperParameterTuningJobArn' => '<string>', ]
Result Details
Members
Errors
-
Resource being accessed is in use.
-
You have exceeded an Amazon 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 Container Registry (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 Amazon Resource Name (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
Errors
-
Resource being accessed is in use.
-
You have exceeded an Amazon 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 Container Registry (ECR) container image specified by BaseImage
.
Parameter Syntax
$result = $client->createImageVersion([ 'BaseImage' => '<string>', // REQUIRED 'ClientToken' => '<string>', // REQUIRED 'ImageName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- 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 Container Registry (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 AWS CLI and AWS SDKs, such as the SDK for Python (Boto3), add a unique value to the call.
- ImageName
-
- Required: Yes
- Type: string
The
ImageName
of theImage
to create a version of.
Result Syntax
[ 'ImageVersionArn' => '<string>', ]
Result Details
Errors
-
Resource being accessed is in use.
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
Resource being access is not found.
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 AWS Marketplace. Vendors provide expertise in specific areas.
-
The Amazon Mechanical Turk workforce. This is the largest workforce, but it should only be used for public data or data that has been stripped of any personally identifiable information.
You can also use automated data labeling to reduce the number of data objects that need to be labeled by a human. Automated data labeling uses active learning to determine if a data object can be labeled by machine or if it needs to be sent to a human worker. For more information, see Using Automated Data Labeling.
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>', ], ], '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.
- 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 name can't end with "-metadata". If you are running a semantic segmentation labeling job, the attribute name must end with "-ref". If you are running any other kind of labeling job, the attribute name must not end with "-ref".
- 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 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"
}
]
}
- 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 AWS 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 AWS Key Management Service key ID for the key used to encrypt the output data, if any.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.
- StoppingConditions
-
- Type: LabelingJobStoppingConditions structure
A set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
- Tags
-
- Type: Array of Tag structures
An array of key/value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.
Result Syntax
[ 'LabelingJobArn' => '<string>', ]
Result Details
Members
Errors
-
Resource being accessed is in use.
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
CreateModel
$result = $client->createModel
([/* ... */]); $promise = $client->createModelAsync
([/* ... */]);
Creates a model in Amazon SageMaker. In the request, you name the model and describe a primary container. For the primary container, you specify the Docker image that contains inference code, artifacts (from prior training), and a custom environment map that the inference code uses when you deploy the model for predictions.
Use this API to create a model if you want to use Amazon SageMaker hosting services or run a batch transform job.
To host your model, you create an endpoint configuration with the CreateEndpointConfig
API, and then create an endpoint with the CreateEndpoint
API. Amazon SageMaker then deploys all of the containers that you defined for the model in the hosting environment.
For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)).
To run a batch transform using your model, you start a job with the CreateTransformJob
API. Amazon SageMaker uses your model and your dataset to get inferences which are then saved to a specified S3 location.
In the CreateModel
request, you must define a container with the PrimaryContainer
parameter.
In the request, you also provide an IAM role that Amazon SageMaker can assume to access model artifacts and docker image for deployment on ML compute hosting instances or for batch transform jobs. In addition, you also use the IAM role to manage permissions the inference code needs. For example, if the inference code access any other AWS resources, you grant necessary permissions via this role.
Parameter Syntax
$result = $client->createModel([ 'Containers' => [ [ 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ImageConfig' => [ 'RepositoryAccessMode' => 'Platform|Vpc', // REQUIRED ], 'Mode' => 'SingleModel|MultiModel', 'ModelDataUrl' => '<string>', 'ModelPackageName' => '<string>', 'MultiModelConfig' => [ 'ModelCacheSetting' => 'Enabled|Disabled', ], ], // ... ], 'EnableNetworkIsolation' => true || false, 'ExecutionRoleArn' => '<string>', // REQUIRED 'ModelName' => '<string>', // REQUIRED 'PrimaryContainer' => [ 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ImageConfig' => [ 'RepositoryAccessMode' => 'Platform|Vpc', // REQUIRED ], 'Mode' => 'SingleModel|MultiModel', '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
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the IAM role that Amazon 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 Amazon SageMaker Roles.
To be able to pass this role to Amazon SageMaker, the caller of this API must have the
iam:PassRole
permission. - 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 AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS 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
Errors
-
You have exceeded an Amazon 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', // REQUIRED 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], ], 'ModelBiasAppSpecification' => [ // REQUIRED 'ConfigUri' => '<string>', // REQUIRED 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', // REQUIRED ], 'ModelBiasBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], ], 'ModelBiasJobInput' => [ // REQUIRED 'EndpointInput' => [ // REQUIRED 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', // REQUIRED '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 AWS Region in the AWS 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 AWS Billing and Cost Management User Guide.
Result Syntax
[ 'JobDefinitionArn' => '<string>', ]
Result Details
Members
Errors
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
Resource being accessed is in use.
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', // REQUIRED 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], ], 'ModelExplainabilityAppSpecification' => [ // REQUIRED 'ConfigUri' => '<string>', // REQUIRED 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', // REQUIRED ], 'ModelExplainabilityBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], ], 'ModelExplainabilityJobInput' => [ // REQUIRED 'EndpointInput' => [ // REQUIRED 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', // REQUIRED '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 AWS Region in the AWS account.
- JobResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources to deploy for a monitoring job.
- ModelExplainabilityAppSpecification
-
- Required: Yes
- Type: ModelExplainabilityAppSpecification structure
Configures the model explainability job to run a specified Docker container image.
- ModelExplainabilityBaselineConfig
-
- Type: ModelExplainabilityBaselineConfig structure
The baseline configuration for a model explainability job.
- ModelExplainabilityJobInput
-
- Required: Yes
- Type: ModelExplainabilityJobInput structure
Inputs for the model explainability job.
- ModelExplainabilityJobOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The output configuration for monitoring jobs.
- NetworkConfig
-
- Type: MonitoringNetworkConfig structure
Networking options for a model explainability job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
A time limit for how long the monitoring job is allowed to run before stopping.
- Tags
-
- Type: Array of Tag structures
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.
Result Syntax
[ 'JobDefinitionArn' => '<string>', ]
Result Details
Members
Errors
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
Resource being accessed is in use.
CreateModelPackage
$result = $client->createModelPackage
([/* ... */]); $promise = $client->createModelPackageAsync
([/* ... */]);
Creates a model package that you can use to create Amazon SageMaker models or list on AWS Marketplace, or a versioned model that is part of a model group. Buyers can subscribe to model packages listed on AWS Marketplace to create models in Amazon SageMaker.
To create a model package by specifying a Docker container that contains your inference code and the Amazon S3 location of your model artifacts, provide values for InferenceSpecification
. To create a model from an algorithm resource that you created or subscribed to in AWS Marketplace, provide a value for SourceAlgorithmSpecification
.
There are two types of model packages:
-
Versioned - a model that is part of a model group in the model registry.
-
Unversioned - a model package that is not part of a model group.
Parameter Syntax
$result = $client->createModelPackage([ 'CertifyForMarketplace' => true || false, 'ClientToken' => '<string>', 'InferenceSpecification' => [ 'Containers' => [ // REQUIRED [ 'ContainerHostname' => '<string>', 'Image' => '<string>', // REQUIRED 'ImageDigest' => '<string>', 'ModelDataUrl' => '<string>', 'ProductId' => '<string>', ], // ... ], 'SupportedContentTypes' => ['<string>', ...], // REQUIRED 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], // REQUIRED 'SupportedTransformInstanceTypes' => ['<string>', ...], ], 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'ModelApprovalStatus' => 'Approved|Rejected|PendingManualApproval', 'ModelMetrics' => [ 'Bias' => [ '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>', 'SourceAlgorithmSpecification' => [ 'SourceAlgorithms' => [ // REQUIRED [ 'AlgorithmName' => '<string>', // REQUIRED 'ModelDataUrl' => '<string>', ], // ... ], ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], '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', // REQUIRED 'VolumeKmsKeyId' => '<string>', ], ], ], // ... ], 'ValidationRole' => '<string>', // REQUIRED ], ]);
Parameter Details
Members
- CertifyForMarketplace
-
- Type: boolean
Whether to certify the model package for listing on AWS 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.
- InferenceSpecification
-
- Type: InferenceSpecification structure
Specifies details about inference jobs that can be run with models based on this model package, including the following:
-
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. - 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 of the model 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.
- SourceAlgorithmSpecification
-
- Type: SourceAlgorithmSpecification structure
Details about the algorithm that was used to create the model package.
- Tags
-
- Type: Array of Tag structures
A list of key value pairs associated with the model. For more information, see Tagging AWS resources in the AWS General Reference Guide.
- ValidationSpecification
-
- Type: ModelPackageValidationSpecification structure
Specifies configurations for one or more transform jobs that Amazon SageMaker runs to test the model package.
Result Syntax
[ 'ModelPackageArn' => '<string>', ]
Result Details
Members
Errors
-
There was a conflict when you attempted to modify an experiment, trial, or trial component.
-
You have exceeded an Amazon 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 AWS resources in the AWS General Reference Guide.
Result Syntax
[ 'ModelPackageGroupArn' => '<string>', ]
Result Details
Members
Errors
-
You have exceeded an Amazon 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', // 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 'EndpointInput' => [ // REQUIRED 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', // REQUIRED '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 AWS Billing and Cost Management User Guide.
Result Syntax
[ 'JobDefinitionArn' => '<string>', ]
Result Details
Members
Errors
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
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 Endoint.
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 [ 'EndpointInput' => [ // REQUIRED 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', // REQUIRED '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', // 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' => [ '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 AWS Region within an AWS account.
- Tags
-
- Type: Array of Tag structures
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.
Result Syntax
[ 'MonitoringScheduleArn' => '<string>', ]
Result Details
Members
Errors
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
Resource being accessed is in use.
CreateNotebookInstance
$result = $client->createNotebookInstance
([/* ... */]); $promise = $client->createNotebookInstanceAsync
([/* ... */]);
Creates an Amazon SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.
In a CreateNotebookInstance
request, specify the type of ML compute instance that you want to run. Amazon SageMaker launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance.
Amazon SageMaker also provides a set of example notebooks. Each notebook demonstrates how to use Amazon SageMaker with a specific algorithm or with a machine learning framework.
After receiving the request, Amazon SageMaker does the following:
-
Creates a network interface in the Amazon SageMaker VPC.
-
(Option) If you specified
SubnetId
, Amazon SageMaker creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, Amazon SageMaker attaches the security group that you specified in the request to the network interface that it creates in your VPC. -
Launches an EC2 instance of the type specified in the request in the Amazon SageMaker VPC. If you specified
SubnetId
of your VPC, Amazon SageMaker specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.
After creating the notebook instance, Amazon SageMaker returns its Amazon Resource Name (ARN). You can't change the name of a notebook instance after you create it.
After Amazon SageMaker creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating Amazon SageMaker endpoints, and validate hosted models.
For more information, see How It Works.
Parameter Syntax
$result = $client->createNotebookInstance([ 'AcceleratorTypes' => ['<string>', ...], 'AdditionalCodeRepositories' => ['<string>', ...], 'DefaultCodeRepository' => '<string>', 'DirectInternetAccess' => 'Enabled|Disabled', '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.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', // REQUIRED 'KmsKeyId' => '<string>', 'LifecycleConfigName' => '<string>', 'NotebookInstanceName' => '<string>', // REQUIRED '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 AWS 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 Amazon 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 AWS 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 Amazon SageMaker Notebook Instances.
- DirectInternetAccess
-
- Type: string
Sets whether Amazon SageMaker provides internet access to the notebook instance. If you set this to
Disabled
this notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker training and endpoint services unless your configure a NAT Gateway in your VPC.For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value of this parameter to
Disabled
only if you set a value for theSubnetId
parameter. - 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 AWS Key Management Service key that Amazon 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 AWS 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.
- RoleArn
-
- Required: Yes
- Type: string
When you send any requests to AWS resources from the notebook instance, Amazon SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so Amazon SageMaker can perform these tasks. The policy must allow the Amazon SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see Amazon SageMaker Roles.
To be able to pass this role to Amazon 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 AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS 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
Errors
-
You have exceeded an Amazon 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 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
Errors
-
You have exceeded an Amazon 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 'PipelineDefinition' => '<string>', // REQUIRED '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.
- PipelineDefinition
-
- Required: Yes
- Type: string
The JSON pipeline definition of the pipeline.
- 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
Errors
-
Resource being access is not found.
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
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 Amazon SageMaker Studio, and granted access to all of the Apps and files associated with the Domain's Amazon Elastic File System (EFS) volume. This operation can only be called when the authentication mode equals IAM.
The URL that you get from a call to CreatePresignedDomainUrl
is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the AWS console sign-in page.
Parameter Syntax
$result = $client->createPresignedDomainUrl([ 'DomainId' => '<string>', // REQUIRED 'SessionExpirationDurationInSeconds' => <integer>, 'UserProfileName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'AuthorizedUrl' => '<string>', ]
Result Details
Errors
-
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 Amazon SageMaker console, when you choose Open
next to a notebook instance, Amazon SageMaker opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.
The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.
You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress
condition operator and the aws:SourceIP
condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.
The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the AWS console sign-in page.
Parameter Syntax
$result = $client->createPresignedNotebookInstanceUrl([ 'NotebookInstanceName' => '<string>', // REQUIRED 'SessionExpirationDurationInSeconds' => <integer>, ]);
Parameter Details
Members
Result Syntax
[ 'AuthorizedUrl' => '<string>', ]
Result Details
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>', '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', // 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
Sets the environment variables 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:
- NetworkConfig
-
- Type: NetworkConfig structure
Networking options for a processing job.
- ProcessingInputs
-
- Type: Array of ProcessingInput structures
List of input configurations for the processing job.
- ProcessingJobName
-
- Required: Yes
- Type: string
The name of the processing job. The name must be unique within an AWS Region in the AWS 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 AWS Billing and Cost Management User Guide.
Result Syntax
[ 'ProcessingJobArn' => '<string>', ]
Result Details
Members
Errors
-
Resource being accessed is in use.
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
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>', // REQUIRED '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. For information, see What is AWS Service Catalog.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs that you want to use to organize and track your AWS resource costs. For more information, see Tagging AWS resources in the AWS General Reference Guide.
Result Syntax
[ 'ProjectArn' => '<string>', 'ProjectId' => '<string>', ]
Result Details
Members
Errors
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
CreateTrainingJob
$result = $client->createTrainingJob
([/* ... */]); $promise = $client->createTrainingJobAsync
([/* ... */]);
Starts a model training job. After training completes, Amazon SageMaker saves the resulting model artifacts to an Amazon S3 location that you specify.
If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts in a machine learning service other than Amazon SageMaker, provided that you know how to use them for inference.
In the request body, you provide the following:
-
AlgorithmSpecification
- Identifies the training algorithm to use. -
HyperParameters
- Specify these algorithm-specific parameters to enable the estimation of model parameters during training. Hyperparameters can be tuned to optimize this learning process. For a list of hyperparameters for each training algorithm provided by Amazon SageMaker, see Algorithms. -
InputDataConfig
- Describes the training dataset and the Amazon S3, EFS, or FSx location where it is stored. -
OutputDataConfig
- Identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of model training. -
ResourceConfig
- Identifies the resources, ML compute instances, and ML storage volumes to deploy for model training. In distributed training, you specify more than one instance. -
EnableManagedSpotTraining
- Optimize the cost of training machine learning models by up to 80% by using Amazon EC2 Spot instances. For more information, see Managed Spot Training. -
RoleArn
- The Amazon Resource Name (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during model training. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete model training. -
StoppingCondition
- To help cap training costs, useMaxRuntimeInSeconds
to set a time limit for training. UseMaxWaitTimeInSeconds
to specify how long you are willing to wait for a managed spot training job to complete.
For more information about Amazon SageMaker, see How It Works.
Parameter Syntax
$result = $client->createTrainingJob([ 'AlgorithmSpecification' => [ // REQUIRED 'AlgorithmName' => '<string>', 'EnableSageMakerMetricsTimeSeries' => true || false, 'MetricDefinitions' => [ [ 'Name' => '<string>', // REQUIRED 'Regex' => '<string>', // REQUIRED ], // ... ], 'TrainingImage' => '<string>', 'TrainingInputMode' => 'Pipe|File', // 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', 'LocalPath' => '<string>', 'RuleConfigurationName' => '<string>', // REQUIRED 'RuleEvaluatorImage' => '<string>', // REQUIRED 'RuleParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', 'VolumeSizeInGB' => <integer>, ], // ... ], 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'HyperParameters' => ['<string>', ...], '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>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', // REQUIRED 'S3Uri' => '<string>', // REQUIRED ], ], 'InputMode' => 'Pipe|File', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, // REQUIRED ], ], // ... ], 'OutputDataConfig' => [ // REQUIRED 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', // REQUIRED ], 'ProfilerConfig' => [ 'ProfilingIntervalInMilliseconds' => <integer>, 'ProfilingParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', // REQUIRED ], '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', 'LocalPath' => '<string>', 'RuleConfigurationName' => '<string>', // REQUIRED 'RuleEvaluatorImage' => '<string>', // REQUIRED 'RuleParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', 'VolumeSizeInGB' => <integer>, ], // ... ], 'ResourceConfig' => [ // REQUIRED '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.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', // REQUIRED 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, // REQUIRED ], 'RoleArn' => '<string>', // REQUIRED 'StoppingCondition' => [ // REQUIRED '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 Amazon 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 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 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, Amazon SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
- 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 Amazon 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
. - InputDataConfig
-
- Type: Array of Channel structures
An array of
Channel
objects. Each channel is a named input source.InputDataConfig
describes the input data and its location.Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels of input data,
training_data
andvalidation_data
. The configuration for each channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.Depending on the input mode that the algorithm supports, Amazon 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 will be made available as input streams. They do not need to be downloaded.
- OutputDataConfig
-
- Required: Yes
- Type: OutputDataConfig structure
Specifies the path to the S3 location where you want to store model artifacts. Amazon SageMaker creates subfolders for the artifacts.
- ProfilerConfig
-
- Type: ProfilerConfig structure
Configuration information for Debugger system monitoring, framework profiling, and storage paths.
- ProfilerRuleConfigurations
-
- Type: Array of ProfilerRuleConfiguration structures
Configuration information for Debugger rules for profiling system and framework metrics.
- 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 Amazon SageMaker to use the ML storage volume to store the training data, choose
File
as theTrainingInputMode
in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1. - 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.
During model training, Amazon 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 Amazon SageMaker Roles.
To be able to pass this role to Amazon SageMaker, the caller of this API must have the
iam:PassRole
permission. - StoppingCondition
-
- Required: Yes
- Type: StoppingCondition structure
Specifies a limit to how long a model training job can run. When the job reaches the time limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, Amazon 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 AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS Resources.
- TensorBoardOutputConfig
-
- Type: TensorBoardOutputConfig structure
Configuration of storage locations for the Debugger TensorBoard output data.
- TrainingJobName
-
- Required: Yes
- Type: string
The name of the training job. The name must be unique within an AWS Region in an AWS 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
Errors
-
Resource being accessed is in use.
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
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 AWS Region in an AWS account. -
ModelName
- Identifies the model to use.ModelName
must be the name of an existing Amazon SageMaker model in the same AWS Region and AWS account. For information on creating a model, see CreateModel. -
TransformInput
- Describes the dataset to be transformed and the Amazon S3 location where it is stored. -
TransformOutput
- Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job. -
TransformResources
- Identifies the ML compute instances for the transform job.
For more information about how batch transformation works, see Batch Transform.
Parameter Syntax
$result = $client->createTransformJob([ 'BatchStrategy' => 'MultiRecord|SingleRecord', 'DataProcessing' => [ 'InputFilter' => '<string>', 'JoinSource' => 'Input|None', 'OutputFilter' => '<string>', ], 'Environment' => ['<string>', ...], 'ExperimentConfig' => [ 'ExperimentName' => '<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', // REQUIRED 'VolumeKmsKeyId' => '<string>', ], ]);
Parameter Details
Members
- BatchStrategy
-
- Type: string
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set the
SplitType
property toLine
,RecordIO
, orTFRecord
.To use only one record when making an HTTP invocation request to a container, set
BatchStrategy
toSingleRecord
andSplitType
toLine
.To fit as many records in a mini-batch as can fit within the
MaxPayloadInMB
limit, setBatchStrategy
toMultiRecord
andSplitType
toLine
. - DataProcessing
-
- Type: DataProcessing structure
The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
- Environment
-
- Type: Associative array of custom strings keys (TransformEnvironmentKey) to strings
The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
- ExperimentConfig
-
- Type: ExperimentConfig structure
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
- MaxConcurrentTransforms
-
- Type: int
The maximum number of parallel requests that can be sent to each instance in a transform job. If
MaxConcurrentTransforms
is set to0
or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is1
. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don't need to set a value forMaxConcurrentTransforms
. - MaxPayloadInMB
-
- Type: int
The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in
MaxPayloadInMB
must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is6
MB.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 AWS Region in an AWS account. - Tags
-
- Type: Array of Tag structures
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS 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 AWS Region in an AWS 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
Errors
-
Resource being accessed is in use.
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
Resource being access is not found.
CreateTrial
$result = $client->createTrial
([/* ... */]); $promise = $client->createTrialAsync
([/* ... */]);
Creates an Amazon SageMaker trial. A trial is a set of steps called trial components that produce a machine learning model. A trial is part of a single Amazon SageMaker experiment.
When you use Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial and then use the Search API to search for the tags.
To get a list of all your trials, call the ListTrials API. To view a trial's properties, call the DescribeTrial API. To create a trial component, call the CreateTrialComponent API.
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 AWS account and is not case-sensitive.
Result Syntax
[ 'TrialArn' => '<string>', ]
Result Details
Errors
-
Resource being access is not found.
-
You have exceeded an Amazon 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 Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial component and then use the Search API to search for the tags.
CreateTrialComponent
can only be invoked from within an Amazon SageMaker managed environment. This includes Amazon SageMaker training jobs, processing jobs, transform jobs, and Amazon SageMaker notebooks. A call to CreateTrialComponent
from outside one of these environments results in an error.
Parameter Syntax
$result = $client->createTrialComponent([ 'DisplayName' => '<string>', 'EndTime' => <integer || string || DateTime>, 'InputArtifacts' => [ '<TrialComponentKey64>' => [ 'MediaType' => '<string>', 'Value' => '<string>', // REQUIRED ], // ... ], 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'OutputArtifacts' => [ '<TrialComponentKey64>' => [ 'MediaType' => '<string>', 'Value' => '<string>', // REQUIRED ], // ... ], 'Parameters' => [ '<TrialComponentKey256>' => [ '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 (TrialComponentKey64) 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 (TrialComponentKey64) 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 (TrialComponentKey256) 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 AWS account and is not case-sensitive.
Result Syntax
[ 'TrialComponentArn' => '<string>', ]
Result Details
Errors
-
You have exceeded an Amazon 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 Amazon SageMaker Studio. If an administrator invites a person by email or imports them from SSO, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user's private Amazon Elastic File System (EFS) home directory.
Parameter Syntax
$result = $client->createUserProfile([ 'DomainId' => '<string>', // REQUIRED 'SingleSignOnUserIdentifier' => '<string>', 'SingleSignOnUserValue' => '<string>', 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'UserProfileName' => '<string>', // REQUIRED 'UserSettings' => [ 'ExecutionRole' => '<string>', 'JupyterServerAppSettings' => [ '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.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.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionArn' => '<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.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.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'SecurityGroups' => ['<string>', ...], 'SharingSettings' => [ 'NotebookOutputOption' => 'Allowed|Disabled', 'S3KmsKeyId' => '<string>', 'S3OutputPath' => '<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.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.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge', 'SageMakerImageArn' => '<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 SSO, this field is required. If the Domain's AuthMode is not SSO, this field cannot be specified.
- SingleSignOnUserValue
-
- Type: string
The username of the associated AWS Single Sign-On User for this UserProfile. If the Domain's AuthMode is SSO, this field is required, and must match a valid username of a user in your directory. If the Domain's AuthMode is not SSO, 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.
- UserProfileName
-
- Required: Yes
- Type: string
A name for the UserProfile.
- UserSettings
-
- Type: UserSettings structure
A collection of settings.
Result Syntax
[ 'UserProfileArn' => '<string>', ]
Result Details
Errors
-
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
-
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 AWS Region that you specify. You can only create one workforce in each AWS Region per AWS account.
If you want to create a new workforce in an AWS Region where a workforce already exists, use the API operation to delete the existing workforce and then use CreateWorkforce
to create a new workforce.
To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig
. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).
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' => [ 'AuthorizationEndpoint' => '<string>', // REQUIRED 'ClientId' => '<string>', // REQUIRED 'ClientSecret' => '<string>', // REQUIRED 'Issuer' => '<string>', // REQUIRED 'JwksUri' => '<string>', // REQUIRED 'LogoutEndpoint' => '<string>', // REQUIRED 'TokenEndpoint' => '<string>', // REQUIRED 'UserInfoEndpoint' => '<string>', // REQUIRED ], 'SourceIpConfig' => [ 'Cidrs' => ['<string>', ...], // REQUIRED ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'WorkforceName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- CognitoConfig
-
- Type: CognitoConfig structure
Use this parameter to configure an Amazon Cognito private workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
Do not use
OidcConfig
if you specify values forCognitoConfig
. - OidcConfig
-
- Type: OidcConfig structure
Use this parameter to configure a private workforce using your own OIDC Identity Provider.
Do not use
CognitoConfig
if you specify values forOidcConfig
. - SourceIpConfig
-
- Type: SourceIpConfig structure
A list of IP address ranges (CIDRs). Used to create an allow list of IP addresses for a private workforce. Workers will only be able to login 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.
Result Syntax
[ 'WorkforceArn' => '<string>', ]
Result Details
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>', ...], // REQUIRED ], ], // ... ], 'NotificationConfiguration' => [ 'NotificationTopicArn' => '<string>', ], 'Tags' => [ [ 'Key' => '<string>', // REQUIRED 'Value' => '<string>', // REQUIRED ], // ... ], 'WorkforceName' => '<string>', 'WorkteamName' => '<string>', // REQUIRED ]);
Parameter Details
Members
- Description
-
- Required: Yes
- Type: string
A description of the work team.
- MemberDefinitions
-
- Required: Yes
- Type: Array of MemberDefinition structures
A list of
MemberDefinition
objects that contains objects that identify the workers that make up the work team.Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use
CognitoMemberDefinition
. For workforces created using your own OIDC identity provider (IdP) useOidcMemberDefinition
. Do not provide input for both of these parameters in a single request.For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the
CognitoMemberDefinition
objects that make up the member definition must have the sameClientId
andUserPool
values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in
OidcMemberDefinition
by listing those groups inGroups
. - NotificationConfiguration
-
- Type: NotificationConfiguration structure
Configures notification of workers regarding available or expiring work items.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs.
For more information, see Resource Tag and Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.
- 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
Errors
-
Resource being accessed is in use.
-
You have exceeded an Amazon 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
Result Syntax
[ 'ActionArn' => '<string>', ]
Result Details
Errors
-
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
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
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|TensorBoard', // REQUIRED 'DomainId' => '<string>', // REQUIRED 'UserProfileName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
-
Resource being accessed is in use.
-
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
Result Syntax
[]
Result Details
Errors
-
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
Errors
-
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
Result Syntax
[ 'DestinationArn' => '<string>', 'SourceArn' => '<string>', ]
Result Details
Members
Errors
-
Resource being access is not found.
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
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteContext
$result = $client->deleteContext
([/* ... */]); $promise = $client->deleteContextAsync
([/* ... */]);
Deletes an context.
Parameter Syntax
$result = $client->deleteContext([ 'ContextName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'ContextArn' => '<string>', ]
Result Details
Errors
-
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
Result Syntax
[]
Result Details
Errors
-
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
Result Syntax
[]
Result Details
Errors
-
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 SSO. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.
Parameter Syntax
$result = $client->deleteDomain([ 'DomainId' => '<string>', // REQUIRED 'RetentionPolicy' => [ 'HomeEfsFileSystem' => 'Retain|Delete', ], ]);
Parameter Details
Members
- DomainId
-
- Required: Yes
- Type: string
The domain ID.
- RetentionPolicy
-
- Type: RetentionPolicy structure
The retention policy for this domain, which specifies whether resources will be retained after the Domain is deleted. By default, all resources are retained (not automatically deleted).
Result Syntax
[]
Result Details
Errors
-
Resource being accessed is in use.
-
Resource being access is not found.
DeleteEndpoint
$result = $client->deleteEndpoint
([/* ... */]); $promise = $client->deleteEndpointAsync
([/* ... */]);
Deletes an endpoint. Amazon SageMaker frees up all of the resources that were deployed when the endpoint was created.
Amazon SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don't need to use the RevokeGrant API call.
Parameter Syntax
$result = $client->deleteEndpoint([ 'EndpointName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteEndpointConfig
$result = $client->deleteEndpointConfig
([/* ... */]); $promise = $client->deleteEndpointConfigAsync
([/* ... */]);
Deletes an endpoint configuration. The DeleteEndpointConfig
API deletes only the specified configuration. It does not delete endpoints created using the configuration.
You must not delete an EndpointConfig
in use by an endpoint that is live or while the UpdateEndpoint
or CreateEndpoint
operations are being performed on the endpoint. If you delete the EndpointConfig
of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
Parameter Syntax
$result = $client->deleteEndpointConfig([ 'EndpointConfigName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteExperiment
$result = $client->deleteExperiment
([/* ... */]); $promise = $client->deleteExperimentAsync
([/* ... */]);
Deletes an Amazon SageMaker experiment. All trials associated with the experiment must be deleted first. Use the ListTrials API to get a list of the trials associated with the experiment.
Parameter Syntax
$result = $client->deleteExperiment([ 'ExperimentName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'ExperimentArn' => '<string>', ]
Result Details
Members
Errors
-
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 AWS Glue database and tables that are automatically created for your OfflineStore
are not deleted.
Parameter Syntax
$result = $client->deleteFeatureGroup([ 'FeatureGroupName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
-
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
Result Syntax
[]
Result Details
Errors
-
Resource being accessed is in use.
-
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 . 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
Result Syntax
[]
Result Details
Errors
-
Resource being access is not found.
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
Result Syntax
[]
Result Details
Errors
-
Resource being accessed is in use.
-
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([ 'ImageName' => '<string>', // REQUIRED 'Version' => <integer>, // REQUIRED ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
-
Resource being accessed is in use.
-
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 Amazon SageMaker when you called the CreateModel API. It does not delete model artifacts, inference code, or the IAM role that you specified when creating the model.
Parameter Syntax
$result = $client->deleteModel([ 'ModelName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteModelBiasJobDefinition
$result = $client->deleteModelBiasJobDefinition
([/* ... */]); $promise = $client->deleteModelBiasJobDefinitionAsync
([/* ... */]);
Deletes an Amazon SageMaker model bias job definition.
Parameter Syntax
$result = $client->deleteModelBiasJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
-
Resource being access is not found.
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
Result Syntax
[]
Result Details
Errors
-
Resource being access is not found.
DeleteModelPackage
$result = $client->deleteModelPackage
([/* ... */]); $promise = $client->deleteModelPackageAsync
([/* ... */]);
Deletes a model package.
A model package is used to create Amazon SageMaker models or list on AWS Marketplace. Buyers can subscribe to model packages listed on AWS Marketplace to create models in Amazon SageMaker.
Parameter Syntax
$result = $client->deleteModelPackage([ 'ModelPackageName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
-
There was a conflict when you attempted to modify an experiment, trial, or trial component.
DeleteModelPackageGroup
$result = $client->deleteModelPackageGroup
([/* ... */]); $promise = $client->deleteModelPackageGroupAsync
([/* ... */]);
Deletes the specified model group.
Parameter Syntax
$result = $client->deleteModelPackageGroup([ 'ModelPackageGroupName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteModelPackageGroupPolicy
$result = $client->deleteModelPackageGroupPolicy
([/* ... */]); $promise = $client->deleteModelPackageGroupPolicyAsync
([/* ... */]);
Deletes a model group resource policy.
Parameter Syntax
$result = $client->deleteModelPackageGroupPolicy([ 'ModelPackageGroupName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteModelQualityJobDefinition
$result = $client->deleteModelQualityJobDefinition
([/* ... */]); $promise = $client->deleteModelQualityJobDefinitionAsync
([/* ... */]);
Deletes the secified model quality monitoring job definition.
Parameter Syntax
$result = $client->deleteModelQualityJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
-
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
Result Syntax
[]
Result Details
Errors
-
Resource being access is not found.
DeleteNotebookInstance
$result = $client->deleteNotebookInstance
([/* ... */]); $promise = $client->deleteNotebookInstanceAsync
([/* ... */]);
Deletes an Amazon SageMaker notebook instance. Before you can delete a notebook instance, you must call the StopNotebookInstance
API.
When you delete a notebook instance, you lose all of your data. Amazon SageMaker removes the ML compute instance, and deletes the ML storage volume and the network interface associated with the notebook instance.
Parameter Syntax
$result = $client->deleteNotebookInstance([ 'NotebookInstanceName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteNotebookInstanceLifecycleConfig
$result = $client->deleteNotebookInstanceLifecycleConfig
([/* ... */]); $promise = $client->deleteNotebookInstanceLifecycleConfigAsync
([/* ... */]);
Deletes a notebook instance lifecycle configuration.
Parameter Syntax
$result = $client->deleteNotebookInstanceLifecycleConfig([ 'NotebookInstanceLifecycleConfigName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeletePipeline
$result = $client->deletePipeline
([/* ... */]); $promise = $client->deletePipelineAsync
([/* ... */]);
Deletes a pipeline if there are no in-progress executions.
Parameter Syntax
$result = $client->deletePipeline([ 'ClientRequestToken' => '<string>', // REQUIRED 'PipelineName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'PipelineArn' => '<string>', ]
Result Details
Errors
-
Resource being access is not found.
DeleteProject
$result = $client->deleteProject
([/* ... */]); $promise = $client->deleteProjectAsync
([/* ... */]);
Delete the specified project.
Parameter Syntax
$result = $client->deleteProject([ 'ProjectName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteTags
$result = $client->deleteTags
([/* ... */]); $promise = $client->deleteTagsAsync
([/* ... */]);
Deletes the specified tags from an Amazon SageMaker resource.
To list a resource's tags, use the ListTags
API.
When you call this API to delete tags from a hyperparameter tuning job, the deleted tags are not removed from training jobs that the hyperparameter tuning job launched before you called this API.
Parameter Syntax
$result = $client->deleteTags([ 'ResourceArn' => '<string>', // REQUIRED 'TagKeys' => ['<string>', ...], // REQUIRED ]);
Parameter Details
Members
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteTrial
$result = $client->deleteTrial
([/* ... */]); $promise = $client->deleteTrialAsync
([/* ... */]);
Deletes the specified trial. All trial components that make up the trial must be deleted first. Use the DescribeTrialComponent API to get the list of trial components.
Parameter Syntax
$result = $client->deleteTrial([ 'TrialName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'TrialArn' => '<string>', ]
Result Details
Errors
-
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
Result Syntax
[ 'TrialComponentArn' => '<string>', ]
Result Details
Members
Errors
-
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
Result Syntax
[]
Result Details
Errors
-
Resource being accessed is in use.
-
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 AWS Region where a workforce already exists, use this operation to delete the existing workforce and then use to create a new workforce.
If a private workforce contains one or more work teams, you must use the operation to delete all work teams before you delete the workforce. If you try to delete a workforce that contains one or more work teams, you will recieve a ResourceInUse
error.
Parameter Syntax
$result = $client->deleteWorkforce([ 'WorkforceName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DeleteWorkteam
$result = $client->deleteWorkteam
([/* ... */]); $promise = $client->deleteWorkteamAsync
([/* ... */]);
Deletes an existing work team. This operation can't be undone.
Parameter Syntax
$result = $client->deleteWorkteam([ 'WorkteamName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'Success' => true || false, ]
Result Details
Members
Errors
-
You have exceeded an Amazon 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
Result Syntax
[]
Result Details
Errors
There are no errors described for this operation.
DescribeAction
$result = $client->describeAction
([/* ... */]); $promise = $client->describeActionAsync
([/* ... */]);
Describes an action.
Parameter Syntax
$result = $client->describeAction([ 'ActionName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'ActionArn' => '<string>', 'ActionName' => '<string>', 'ActionType' => '<string>', 'CreatedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'Description' => '<string>', 'LastModifiedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, '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, or trial component.
- 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, or trial component.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the action was last modified.
- 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
-
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
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' => [ [ 'ContainerHostname' => '<string>', 'Image' => '<string>', 'ImageDigest' => '<string>', 'ModelDataUrl' => '<string>', 'ProductId' => '<string>', ], // ... ], 'SupportedContentTypes' => ['<string>', ...], 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'SupportedTransformInstanceTypes' => ['<string>', ...], ], 'ProductId' => '<string>', 'TrainingSpecification' => [ '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>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'InputMode' => 'Pipe|File', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, ], ], // ... ], 'OutputDataConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'ResourceConfig' => [ '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.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', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TrainingInputMode' => 'Pipe|File', ], 'TransformJobDefinition' => [ 'BatchStrategy' => 'MultiRecord|SingleRecord', 'Environment' => ['<string>', ...], 'MaxConcurrentTransforms' => <integer>, 'MaxPayloadInMB' => <integer>, 'TransformInput' => [ 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'S3DataSource' => [ 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'SplitType' => 'None|Line|RecordIO|TFRecord', ], 'TransformOutput' => [ 'Accept' => '<string>', 'AssembleWith' => 'None|Line', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'TransformResources' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge', 'VolumeKmsKeyId' => '<string>', ], ], ], // ... ], 'ValidationRole' => '<string>', ], ]
Result Details
Members
- AlgorithmArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the algorithm.
- AlgorithmDescription
-
- Type: string
A brief summary about the algorithm.
- AlgorithmName
-
- Required: Yes
- Type: string
The name of the algorithm being described.
- AlgorithmStatus
-
- Required: Yes
- Type: string
The current status of the algorithm.
- AlgorithmStatusDetails
-
- Required: Yes
- Type: AlgorithmStatusDetails structure
Details about the current status of the algorithm.
- CertifyForMarketplace
-
- Type: boolean
Whether the algorithm is certified to be listed in AWS Marketplace.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp specifying when the algorithm was created.
- InferenceSpecification
-
- Type: InferenceSpecification structure
Details about inference jobs that the algorithm runs.
- ProductId
-
- Type: string
The product identifier of the algorithm.
- TrainingSpecification
-
- Required: Yes
- Type: TrainingSpecification structure
Details about training jobs run by this algorithm.
- ValidationSpecification
-
- Type: AlgorithmValidationSpecification structure
Details about configurations for one or more training jobs that Amazon SageMaker runs to test the algorithm.
Errors
There are no errors described for this operation.
DescribeApp
$result = $client->describeApp
([/* ... */]); $promise = $client->describeAppAsync
([/* ... */]);
Describes the app.
Parameter Syntax
$result = $client->describeApp([ 'AppName' => '<string>', // REQUIRED 'AppType' => 'JupyterServer|KernelGateway|TensorBoard', // REQUIRED 'DomainId' => '<string>', // REQUIRED 'UserProfileName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'AppArn' => '<string>', 'AppName' => '<string>', 'AppType' => 'JupyterServer|KernelGateway|TensorBoard', 'CreationTime' => <DateTime>, 'DomainId' => '<string>', 'FailureReason' => '<string>', 'LastHealthCheckTimestamp' => <DateTime>, 'LastUserActivityTimestamp' => <DateTime>, 'ResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.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.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], 'Status' => 'Deleted|Deleting|Failed|InService|Pending', 'UserProfileName' => '<string>', ]
Result Details
Members
- AppArn
-
- Type: string
The Amazon Resource Name (ARN) of the app.
- AppName
-
- Type: string
The name of the app.
- AppType
-
- Type: string
The type of app.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time.
- DomainId
-
- Type: string
The domain ID.
- FailureReason
-
- Type: string
The failure reason.
- LastHealthCheckTimestamp
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of the last health check.
- LastUserActivityTimestamp
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of the last user's activity.
- ResourceSpec
-
- Type: ResourceSpec structure
The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
- Status
-
- Type: string
The status.
- UserProfileName
-
- Type: string
The user profile name.
Errors
-
Resource being access is not found.
DescribeAppImageConfig
$result = $client->describeAppImageConfig
([/* ... */]); $promise = $client->describeAppImageConfigAsync
([/* ... */]);
Describes an AppImageConfig.
Parameter Syntax
$result = $client->describeAppImageConfig([ 'AppImageConfigName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'AppImageConfigArn' => '<string>', 'AppImageConfigName' => '<string>', 'CreationTime' => <DateTime>, 'KernelGatewayImageConfig' => [ 'FileSystemConfig' => [ 'DefaultGid' => <integer>, 'DefaultUid' => <integer>, 'MountPath' => '<string>', ], 'KernelSpecs' => [ [ 'DisplayName' => '<string>', 'Name' => '<string>', ], // ... ], ], 'LastModifiedTime' => <DateTime>, ]
Result Details
Members
- AppImageConfigArn
-
- Type: string
The Amazon Resource Name (ARN) of the AppImageConfig.
- AppImageConfigName
-
- Type: string
The name of the AppImageConfig.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the AppImageConfig was created.
- KernelGatewayImageConfig
-
- Type: KernelGatewayImageConfig structure
The configuration of a KernelGateway app.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the AppImageConfig was last modified.
Errors
-
Resource being access is not found.
DescribeArtifact
$result = $client->describeArtifact
([/* ... */]); $promise = $client->describeArtifactAsync
([/* ... */]);
Describes an artifact.
Parameter Syntax
$result = $client->describeArtifact([ 'ArtifactArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'ArtifactArn' => '<string>', 'ArtifactName' => '<string>', 'ArtifactType' => '<string>', 'CreatedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'LastModifiedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'Properties' => ['<string>', ...], 'Source' => [ 'SourceTypes' => [ [ 'SourceIdType' => 'MD5Hash|S3ETag|S3Version|Custom', 'Value' => '<string>', ], // ... ], 'SourceUri' => '<string>', ], ]
Result Details
Members
- ArtifactArn
-
- Type: string
The Amazon Resource Name (ARN) of the artifact.
- ArtifactName
-
- Type: string
The name of the artifact.
- ArtifactType
-
- Type: string
The type of the artifact.
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, or trial component.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the artifact was created.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, or trial component.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the artifact was last modified.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- Properties
-
- Type: Associative array of custom strings keys (StringParameterValue) to strings
A list of the artifact's properties.
- Source
-
- Type: ArtifactSource structure
The source of the artifact.
Errors
-
Resource being access is not found.
DescribeAutoMLJob
$result = $client->describeAutoMLJob
([/* ... */]); $promise = $client->describeAutoMLJobAsync
([/* ... */]);
Returns information about an Amazon SageMaker job.
Parameter Syntax
$result = $client->describeAutoMLJob([ 'AutoMLJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'AutoMLJobArn' => '<string>', 'AutoMLJobArtifacts' => [ 'CandidateDefinitionNotebookLocation' => '<string>', 'DataExplorationNotebookLocation' => '<string>', ], 'AutoMLJobConfig' => [ 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'SecurityConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'VolumeKmsKeyId' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], ], 'AutoMLJobName' => '<string>', 'AutoMLJobObjective' => [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC', ], 'AutoMLJobSecondaryStatus' => 'Starting|AnalyzingData|FeatureEngineering|ModelTuning|MaxCandidatesReached|Failed|Stopped|MaxAutoMLJobRuntimeReached|Stopping|CandidateDefinitionsGenerated', 'AutoMLJobStatus' => 'Completed|InProgress|Failed|Stopped|Stopping', 'BestCandidate' => [ 'CandidateName' => '<string>', 'CandidateStatus' => 'Completed|InProgress|Failed|Stopped|Stopping', 'CandidateSteps' => [ [ 'CandidateStepArn' => '<string>', 'CandidateStepName' => '<string>', 'CandidateStepType' => 'AWS::SageMaker::TrainingJob|AWS::SageMaker::TransformJob|AWS::SageMaker::ProcessingJob', ], // ... ], 'CreationTime' => <DateTime>, 'EndTime' => <DateTime>, 'FailureReason' => '<string>', 'FinalAutoMLJobObjectiveMetric' => [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC', 'Type' => 'Maximize|Minimize', 'Value' => <float>, ], 'InferenceContainers' => [ [ 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ModelDataUrl' => '<string>', ], // ... ], 'LastModifiedTime' => <DateTime>, 'ObjectiveStatus' => 'Succeeded|Pending|Failed', ], 'CreationTime' => <DateTime>, 'EndTime' => <DateTime>, 'FailureReason' => '<string>', 'GenerateCandidateDefinitionsOnly' => true || false, 'InputDataConfig' => [ [ 'CompressionType' => 'None|Gzip', 'DataSource' => [ 'S3DataSource' => [ 'S3DataType' => 'ManifestFile|S3Prefix', 'S3Uri' => '<string>', ], ], 'TargetAttributeName' => '<string>', ], // ... ], 'LastModifiedTime' => <DateTime>, 'OutputDataConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'ProblemType' => 'BinaryClassification|MulticlassClassification|Regression', 'ResolvedAttributes' => [ 'AutoMLJobObjective' => [ 'MetricName' => 'Accuracy|MSE|F1|F1macro|AUC', ], 'CompletionCriteria' => [ 'MaxAutoMLJobRuntimeInSeconds' => <integer>, 'MaxCandidates' => <integer>, 'MaxRuntimePerTrainingJobInSeconds' => <integer>, ], 'ProblemType' => 'BinaryClassification|MulticlassClassification|Regression', ], 'RoleArn' => '<string>', ]
Result Details
Members
- AutoMLJobArn
-
- Required: Yes
- Type: string
Returns the job's ARN.
- AutoMLJobArtifacts
-
- Type: AutoMLJobArtifacts structure
Returns information on the job's artifacts found in AutoMLJobArtifacts.
- AutoMLJobConfig
-
- Type: AutoMLJobConfig structure
Returns the job's config.
- AutoMLJobName
-
- Required: Yes
- Type: string
Returns the name of a job.
- AutoMLJobObjective
-
- Type: AutoMLJobObjective structure
Returns the job's objective.
- AutoMLJobSecondaryStatus
-
- Required: Yes
- Type: string
Returns the job's AutoMLJobSecondaryStatus.
- AutoMLJobStatus
-
- Required: Yes
- Type: string
Returns the job's AutoMLJobStatus.
- BestCandidate
-
- Type: AutoMLCandidate structure
Returns the job's BestCandidate.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Returns the job's creation time.
- EndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Returns the job's end time.
- FailureReason
-
- Type: string
Returns the job's FailureReason.
- GenerateCandidateDefinitionsOnly
-
- Type: boolean
Returns the job's output from GenerateCandidateDefinitionsOnly.
- InputDataConfig
-
- Required: Yes
- Type: Array of AutoMLChannel structures
Returns the job's input data config.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Returns the job's last modified time.
- OutputDataConfig
-
- Required: Yes
- Type: AutoMLOutputDataConfig structure
Returns the job's output data config.
- ProblemType
-
- Type: string
Returns the job's problem type.
- ResolvedAttributes
-
- Type: ResolvedAttributes structure
This contains ProblemType, AutoMLJobObjective and CompletionCriteria. They're auto-inferred values, if not provided by you. If you do provide them, then they'll be the same as provided.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.
Errors
-
Resource being access is not found.
DescribeCodeRepository
$result = $client->describeCodeRepository
([/* ... */]); $promise = $client->describeCodeRepositoryAsync
([/* ... */]);
Gets details about the specified Git repository.
Parameter Syntax
$result = $client->describeCodeRepository([ 'CodeRepositoryName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'CodeRepositoryArn' => '<string>', 'CodeRepositoryName' => '<string>', 'CreationTime' => <DateTime>, 'GitConfig' => [ 'Branch' => '<string>', 'RepositoryUrl' => '<string>', 'SecretArn' => '<string>', ], 'LastModifiedTime' => <DateTime>, ]
Result Details
Members
- CodeRepositoryArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the Git repository.
- CodeRepositoryName
-
- Required: Yes
- Type: string
The name of the Git repository.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the repository was created.
- GitConfig
-
- Type: GitConfig structure
Configuration details about the repository, including the URL where the repository is located, the default branch, and the Amazon Resource Name (ARN) of the AWS Secrets Manager secret that contains the credentials used to access the repository.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the repository was last changed.
Errors
There are no errors described for this operation.
DescribeCompilationJob
$result = $client->describeCompilationJob
([/* ... */]); $promise = $client->describeCompilationJobAsync
([/* ... */]);
Returns information about a model compilation job.
To create a model compilation job, use CreateCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
Parameter Syntax
$result = $client->describeCompilationJob([ 'CompilationJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'CompilationEndTime' => <DateTime>, 'CompilationJobArn' => '<string>', 'CompilationJobName' => '<string>', 'CompilationJobStatus' => 'INPROGRESS|COMPLETED|FAILED|STARTING|STOPPING|STOPPED', 'CompilationStartTime' => <DateTime>, 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'InputConfig' => [ 'DataInputConfig' => '<string>', 'Framework' => 'TENSORFLOW|KERAS|MXNET|ONNX|PYTORCH|XGBOOST|TFLITE|DARKNET|SKLEARN', 'S3Uri' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'ModelArtifacts' => [ 'S3ModelArtifacts' => '<string>', ], 'ModelDigests' => [ 'ArtifactDigest' => '<string>', ], 'OutputConfig' => [ 'CompilerOptions' => '<string>', 'KmsKeyId' => '<string>', 'S3OutputLocation' => '<string>', 'TargetDevice' => 'lambda|ml_m4|ml_m5|ml_c4|ml_c5|ml_p2|ml_p3|ml_g4dn|ml_inf1|jetson_tx1|jetson_tx2|jetson_nano|jetson_xavier|rasp3b|imx8qm|deeplens|rk3399|rk3288|aisage|sbe_c|qcs605|qcs603|sitara_am57x|amba_cv22|x86_win32|x86_win64|coreml|jacinto_tda4vm', 'TargetPlatform' => [ 'Accelerator' => 'INTEL_GRAPHICS|MALI|NVIDIA', 'Arch' => 'X86_64|X86|ARM64|ARM_EABI|ARM_EABIHF', 'Os' => 'ANDROID|LINUX', ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], ]
Result Details
Members
- CompilationEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the model compilation job on a compilation job instance ended. For a successful or stopped job, this is when the job's model artifacts have finished uploading. For a failed job, this is when Amazon SageMaker detected that the job failed.
- CompilationJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker assumes to perform the model compilation job.
- CompilationJobName
-
- Required: Yes
- Type: string
The name of the model compilation job.
- CompilationJobStatus
-
- Required: Yes
- Type: string
The status of the model compilation job.
- CompilationStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the model compilation job started the
CompilationJob
instances.You are billed for the time between this timestamp and the timestamp in the DescribeCompilationJobResponse$CompilationEndTime field. In Amazon CloudWatch Logs, the start time might be later than this time. That's because it takes time to download the compilation job, which depends on the size of the compilation job container.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the model compilation job was created.
- FailureReason
-
- Required: Yes
- Type: string
If a model compilation job failed, the reason it failed.
- InputConfig
-
- Required: Yes
- Type: InputConfig structure
Information about the location in Amazon S3 of the input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the status of the model compilation job was last modified.
- ModelArtifacts
-
- Required: Yes
- Type: ModelArtifacts structure
Information about the location in Amazon S3 that has been configured for storing the model artifacts used in the compilation job.
- ModelDigests
-
- Type: ModelDigests structure
Provides a BLAKE2 hash value that identifies the compiled model artifacts in Amazon S3.
- OutputConfig
-
- Required: Yes
- Type: OutputConfig structure
Information about the output location for the compiled model and the target device that the model runs on.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model compilation job.
- StoppingCondition
-
- Required: Yes
- Type: StoppingCondition structure
Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker ends the compilation job. Use this API to cap model training costs.
Errors
-
Resource being access is not found.
DescribeContext
$result = $client->describeContext
([/* ... */]); $promise = $client->describeContextAsync
([/* ... */]);
Describes a context.
Parameter Syntax
$result = $client->describeContext([ 'ContextName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'ContextArn' => '<string>', 'ContextName' => '<string>', 'ContextType' => '<string>', 'CreatedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'Description' => '<string>', 'LastModifiedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'Properties' => ['<string>', ...], 'Source' => [ 'SourceId' => '<string>', 'SourceType' => '<string>', 'SourceUri' => '<string>', ], ]
Result Details
Members
- ContextArn
-
- Type: string
The Amazon Resource Name (ARN) of the context.
- ContextName
-
- Type: string
The name of the context.
- ContextType
-
- Type: string
The type of the context.
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, or trial component.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the context was created.
- Description
-
- Type: string
The description of the context.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, or trial component.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the context was last modified.
- Properties
-
- Type: Associative array of custom strings keys (StringParameterValue) to strings
A list of the context's properties.
- Source
-
- Type: ContextSource structure
The source of the context.
Errors
-
Resource being access is not found.
DescribeDataQualityJobDefinition
$result = $client->describeDataQualityJobDefinition
([/* ... */]); $promise = $client->describeDataQualityJobDefinitionAsync
([/* ... */]);
Gets the details of a data quality monitoring job definition.
Parameter Syntax
$result = $client->describeDataQualityJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'CreationTime' => <DateTime>, 'DataQualityAppSpecification' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', 'PostAnalyticsProcessorSourceUri' => '<string>', 'RecordPreprocessorSourceUri' => '<string>', ], 'DataQualityBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], 'StatisticsResource' => [ 'S3Uri' => '<string>', ], ], 'DataQualityJobInput' => [ 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], ], 'DataQualityJobOutputConfig' => [ 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ [ 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'JobDefinitionArn' => '<string>', 'JobDefinitionName' => '<string>', 'JobResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the data quality monitoring job definition was created.
- DataQualityAppSpecification
-
- Required: Yes
- Type: DataQualityAppSpecification structure
Information about the container that runs the data quality monitoring job.
- DataQualityBaselineConfig
-
- Type: DataQualityBaselineConfig structure
The constraints and baselines for the data quality monitoring job definition.
- DataQualityJobInput
-
- Required: Yes
- Type: DataQualityJobInput structure
The list of inputs for the data quality monitoring job. Currently endpoints are supported.
- DataQualityJobOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The output configuration for monitoring jobs.
- JobDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the data quality monitoring job definition.
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the data quality monitoring job definition.
- JobResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources to deploy for a monitoring job.
- NetworkConfig
-
- Type: MonitoringNetworkConfig structure
The networking configuration for the data quality monitoring job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
A time limit for how long the monitoring job is allowed to run before stopping.
Errors
-
Resource being access is not found.
DescribeDevice
$result = $client->describeDevice
([/* ... */]); $promise = $client->describeDeviceAsync
([/* ... */]);
Describes the device.
Parameter Syntax
$result = $client->describeDevice([ 'DeviceFleetName' => '<string>', // REQUIRED 'DeviceName' => '<string>', // REQUIRED 'NextToken' => '<string>', ]);
Parameter Details
Members
Result Syntax
[ 'Description' => '<string>', 'DeviceArn' => '<string>', 'DeviceFleetName' => '<string>', 'DeviceName' => '<string>', 'IotThingName' => '<string>', 'LatestHeartbeat' => <DateTime>, 'MaxModels' => <integer>, 'Models' => [ [ 'LatestInference' => <DateTime>, 'LatestSampleTime' => <DateTime>, 'ModelName' => '<string>', 'ModelVersion' => '<string>', ], // ... ], 'NextToken' => '<string>', 'RegistrationTime' => <DateTime>, ]
Result Details
Members
- Description
-
- Type: string
A description of the device.
- DeviceArn
-
- Type: string
The Amazon Resource Name (ARN) of the device.
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the fleet the device belongs to.
- DeviceName
-
- Required: Yes
- Type: string
The unique identifier of the device.
- IotThingName
-
- Type: string
The AWS Internet of Things (IoT) object thing name associated with the device.
- LatestHeartbeat
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last heartbeat received from the device.
- MaxModels
-
- Type: int
The maximum number of models.
- Models
-
- Type: Array of EdgeModel structures
Models on the device.
- NextToken
-
- Type: string
The response from the last list when returning a list large enough to need tokening.
- RegistrationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of the last registration or de-reregistration.
Errors
-
Resource being access is not found.
DescribeDeviceFleet
$result = $client->describeDeviceFleet
([/* ... */]); $promise = $client->describeDeviceFleetAsync
([/* ... */]);
A description of the fleet the device belongs to.
Parameter Syntax
$result = $client->describeDeviceFleet([ 'DeviceFleetName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'CreationTime' => <DateTime>, 'Description' => '<string>', 'DeviceFleetArn' => '<string>', 'DeviceFleetName' => '<string>', 'IotRoleAlias' => '<string>', 'LastModifiedTime' => <DateTime>, 'OutputConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputLocation' => '<string>', ], 'RoleArn' => '<string>', ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Timestamp of when the device fleet was created.
- Description
-
- Type: string
A description of the fleet.
- DeviceFleetArn
-
- Required: Yes
- Type: string
The The Amazon Resource Name (ARN) of the fleet.
- DeviceFleetName
-
- Required: Yes
- Type: string
The name of the fleet.
- IotRoleAlias
-
- Type: string
The Amazon Resource Name (ARN) alias created in AWS Internet of Things (IoT).
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Timestamp of when the device fleet was last updated.
- OutputConfig
-
- Required: Yes
- Type: EdgeOutputConfig structure
The output configuration for storing sampled data.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) that has access to AWS Internet of Things (IoT).
Errors
-
Resource being access is not found.
DescribeDomain
$result = $client->describeDomain
([/* ... */]); $promise = $client->describeDomainAsync
([/* ... */]);
The description of the domain.
Parameter Syntax
$result = $client->describeDomain([ 'DomainId' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'AppNetworkAccessType' => 'PublicInternetOnly|VpcOnly', 'AuthMode' => 'SSO|IAM', 'CreationTime' => <DateTime>, 'DefaultUserSettings' => [ 'ExecutionRole' => '<string>', 'JupyterServerAppSettings' => [ '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.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.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'KernelGatewayAppSettings' => [ 'CustomImages' => [ [ 'AppImageConfigName' => '<string>', 'ImageName' => '<string>', 'ImageVersionNumber' => <integer>, ], // ... ], 'DefaultResourceSpec' => [ 'InstanceType' => 'system|ml.t3.micro|ml.t3.small|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.8xlarge|ml.m5.12xlarge|ml.m5.16xlarge|ml.m5.24xlarge|ml.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.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], 'SecurityGroups' => ['<string>', ...], 'SharingSettings' => [ 'NotebookOutputOption' => 'Allowed|Disabled', 'S3KmsKeyId' => '<string>', 'S3OutputPath' => '<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.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.g4dn.xlarge|ml.g4dn.2xlarge|ml.g4dn.4xlarge|ml.g4dn.8xlarge|ml.g4dn.12xlarge|ml.g4dn.16xlarge', 'SageMakerImageArn' => '<string>', 'SageMakerImageVersionArn' => '<string>', ], ], ], 'DomainArn' => '<string>', 'DomainId' => '<string>', 'DomainName' => '<string>', 'FailureReason' => '<string>', 'HomeEfsFileSystemId' => '<string>', 'HomeEfsFileSystemKmsKeyId' => '<string>', 'KmsKeyId' => '<string>', 'LastModifiedTime' => <DateTime>, 'SingleSignOnManagedApplicationInstanceId' => '<string>', 'Status' => 'Deleting|Failed|InService|Pending|Updating|Update_Failed|Delete_Failed', 'SubnetIds' => ['<string>', ...], 'Url' => '<string>', 'VpcId' => '<string>', ]
Result Details
Members
- AppNetworkAccessType
-
- Type: string
Specifies the VPC used for non-EFS traffic. The default value is
PublicInternetOnly
.-
PublicInternetOnly
- Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet access -
VpcOnly
- All Studio traffic is through the specified VPC and subnets
- AuthMode
-
- Type: string
The domain's authentication mode.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The creation time.
- DefaultUserSettings
-
- Type: UserSettings structure
Settings which are applied to all UserProfiles in this domain, if settings are not explicitly specified in a given UserProfile.
- DomainArn
-
- Type: string
The domain's Amazon Resource Name (ARN).
- DomainId
-
- Type: string
The domain ID.
- DomainName
-
- Type: string
The domain name.
- FailureReason
-
- Type: string
The failure reason.
- HomeEfsFileSystemId
-
- Type: string
The ID of the Amazon Elastic File System (EFS) managed by this Domain.
- HomeEfsFileSystemKmsKeyId
-
- Type: string
This member is deprecated and replaced with
KmsKeyId
. - KmsKeyId
-
- Type: string
The AWS KMS customer managed CMK used to encrypt the EFS volume attached to the domain.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last modified time.
- SingleSignOnManagedApplicationInstanceId
-
- Type: string
The SSO managed application instance ID.
- Status
-
- Type: string
The status.
- SubnetIds
-
- Type: Array of strings
The VPC subnets that Studio uses for communication.
- Url
-
- Type: string
The domain's URL.
- VpcId
-
- Type: string
The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
Errors
-
Resource being access is not found.
DescribeEdgePackagingJob
$result = $client->describeEdgePackagingJob
([/* ... */]); $promise = $client->describeEdgePackagingJobAsync
([/* ... */]);
A description of edge packaging jobs.
Parameter Syntax
$result = $client->describeEdgePackagingJob([ 'EdgePackagingJobName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'CompilationJobName' => '<string>', 'CreationTime' => <DateTime>, 'EdgePackagingJobArn' => '<string>', 'EdgePackagingJobName' => '<string>', 'EdgePackagingJobStatus' => 'STARTING|INPROGRESS|COMPLETED|FAILED|STOPPING|STOPPED', 'EdgePackagingJobStatusMessage' => '<string>', 'LastModifiedTime' => <DateTime>, 'ModelArtifact' => '<string>', 'ModelName' => '<string>', 'ModelSignature' => '<string>', 'ModelVersion' => '<string>', 'OutputConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputLocation' => '<string>', ], 'ResourceKey' => '<string>', 'RoleArn' => '<string>', ]
Result Details
Members
- CompilationJobName
-
- Type: string
The name of the SageMaker Neo compilation job that is used to locate model artifacts that are being packaged.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of when the packaging job was created.
- EdgePackagingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the edge packaging job.
- EdgePackagingJobName
-
- Required: Yes
- Type: string
The name of the edge packaging job.
- EdgePackagingJobStatus
-
- Required: Yes
- Type: string
The current status of the packaging job.
- EdgePackagingJobStatusMessage
-
- Type: string
Returns a message describing the job status and error messages.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp of when the job was last updated.
- ModelArtifact
-
- Type: string
The Amazon Simple Storage (S3) URI where model artifacts ares stored.
- ModelName
-
- Type: string
The name of the model.
- ModelSignature
-
- Type: string
The signature document of files in the model artifact.
- ModelVersion
-
- Type: string
The version of the model.
- OutputConfig
-
- Type: EdgeOutputConfig structure
The output configuration for the edge packaging job.
- ResourceKey
-
- Type: string
The CMK to use when encrypting the EBS volume the job run on.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact Neo.
Errors
-
Resource being access is not found.
DescribeEndpoint
$result = $client->describeEndpoint
([/* ... */]); $promise = $client->describeEndpointAsync
([/* ... */]);
Returns the description of an endpoint.
Parameter Syntax
$result = $client->describeEndpoint([ 'EndpointName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'CreationTime' => <DateTime>, 'DataCaptureConfig' => [ 'CaptureStatus' => 'Started|Stopped', 'CurrentSamplingPercentage' => <integer>, 'DestinationS3Uri' => '<string>', 'EnableCapture' => true || false, 'KmsKeyId' => '<string>', ], 'EndpointArn' => '<string>', 'EndpointConfigName' => '<string>', 'EndpointName' => '<string>', 'EndpointStatus' => 'OutOfService|Creating|Updating|SystemUpdating|RollingBack|InService|Deleting|Failed', 'FailureReason' => '<string>', 'LastDeploymentConfig' => [ 'AutoRollbackConfiguration' => [ 'Alarms' => [ [ 'AlarmName' => '<string>', ], // ... ], ], 'BlueGreenUpdatePolicy' => [ 'MaximumExecutionTimeoutInSeconds' => <integer>, 'TerminationWaitInSeconds' => <integer>, 'TrafficRoutingConfiguration' => [ 'CanarySize' => [ 'Type' => 'INSTANCE_COUNT|CAPACITY_PERCENT', 'Value' => <integer>, ], 'Type' => 'ALL_AT_ONCE|CANARY', 'WaitIntervalInSeconds' => <integer>, ], ], ], 'LastModifiedTime' => <DateTime>, 'ProductionVariants' => [ [ 'CurrentInstanceCount' => <integer>, 'CurrentWeight' => <float>, 'DeployedImages' => [ [ 'ResolutionTime' => <DateTime>, 'ResolvedImage' => '<string>', 'SpecifiedImage' => '<string>', ], // ... ], 'DesiredInstanceCount' => <integer>, 'DesiredWeight' => <float>, 'VariantName' => '<string>', ], // ... ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the endpoint was created.
- DataCaptureConfig
-
- Type: DataCaptureConfigSummary structure
- EndpointArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the endpoint.
- EndpointConfigName
-
- Required: Yes
- Type: string
The name of the endpoint configuration associated with this endpoint.
- EndpointName
-
- Required: Yes
- Type: string
Name of the endpoint.
- EndpointStatus
-
- Required: Yes
- Type: string
The status of the endpoint.
-
OutOfService
: Endpoint is not available to take incoming requests. -
Creating
: CreateEndpoint is executing. -
Updating
: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing. -
SystemUpdating
: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count. -
RollingBack
: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to anInService
status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly. -
InService
: Endpoint is available to process incoming requests. -
Deleting
: DeleteEndpoint is executing. -
Failed
: Endpoint could not be created, updated, or re-scaled. Use DescribeEndpointOutput$FailureReason for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
- FailureReason
-
- Type: string
If the status of the endpoint is
Failed
, the reason why it failed. - LastDeploymentConfig
-
- Type: DeploymentConfig structure
The most recent deployment configuration for the endpoint.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the endpoint was last modified.
- ProductionVariants
-
- Type: Array of ProductionVariantSummary structures
An array of ProductionVariantSummary objects, one for each model hosted behind this endpoint.
Errors
There are no errors described for this operation.
DescribeEndpointConfig
$result = $client->describeEndpointConfig
([/* ... */]); $promise = $client->describeEndpointConfigAsync
([/* ... */]);
Returns the description of an endpoint configuration created using the CreateEndpointConfig
API.
Parameter Syntax
$result = $client->describeEndpointConfig([ 'EndpointConfigName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'CreationTime' => <DateTime>, 'DataCaptureConfig' => [ 'CaptureContentTypeHeader' => [ 'CsvContentTypes' => ['<string>', ...], 'JsonContentTypes' => ['<string>', ...], ], 'CaptureOptions' => [ [ 'CaptureMode' => 'Input|Output', ], // ... ], 'DestinationS3Uri' => '<string>', 'EnableCapture' => true || false, 'InitialSamplingPercentage' => <integer>, 'KmsKeyId' => '<string>', ], 'EndpointConfigArn' => '<string>', 'EndpointConfigName' => '<string>', 'KmsKeyId' => '<string>', 'ProductionVariants' => [ [ 'AcceleratorType' => 'ml.eia1.medium|ml.eia1.large|ml.eia1.xlarge|ml.eia2.medium|ml.eia2.large|ml.eia2.xlarge', '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', 'ModelName' => '<string>', 'VariantName' => '<string>', ], // ... ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the endpoint configuration was created.
- DataCaptureConfig
-
- Type: DataCaptureConfig structure
- EndpointConfigArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the endpoint configuration.
- EndpointConfigName
-
- Required: Yes
- Type: string
Name of the Amazon SageMaker endpoint configuration.
- KmsKeyId
-
- Type: string
AWS KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
- ProductionVariants
-
- Required: Yes
- Type: Array of ProductionVariant structures
An array of
ProductionVariant
objects, one for each model that you want to host at this endpoint.
Errors
There are no errors described for this operation.
DescribeExperiment
$result = $client->describeExperiment
([/* ... */]); $promise = $client->describeExperimentAsync
([/* ... */]);
Provides a list of an experiment's properties.
Parameter Syntax
$result = $client->describeExperiment([ 'ExperimentName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'CreatedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'Description' => '<string>', 'DisplayName' => '<string>', 'ExperimentArn' => '<string>', 'ExperimentName' => '<string>', 'LastModifiedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'Source' => [ 'SourceArn' => '<string>', 'SourceType' => '<string>', ], ]
Result Details
Members
- CreatedBy
-
- Type: UserContext structure
Who created the experiment.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the experiment was created.
- Description
-
- Type: string
The description of the experiment.
- DisplayName
-
- Type: string
The name of the experiment as displayed. If
DisplayName
isn't specified,ExperimentName
is displayed. - ExperimentArn
-
- Type: string
The Amazon Resource Name (ARN) of the experiment.
- ExperimentName
-
- Type: string
The name of the experiment.
- LastModifiedBy
-
- Type: UserContext structure
Who last modified the experiment.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the experiment was last modified.
- Source
-
- Type: ExperimentSource structure
The ARN of the source and, optionally, the type.
Errors
-
Resource being access is not found.
DescribeFeatureGroup
$result = $client->describeFeatureGroup
([/* ... */]); $promise = $client->describeFeatureGroupAsync
([/* ... */]);
Use this operation to describe a FeatureGroup
. The response includes information on the creation time, FeatureGroup
name, the unique identifier for each FeatureGroup
, and more.
Parameter Syntax
$result = $client->describeFeatureGroup([ 'FeatureGroupName' => '<string>', // REQUIRED 'NextToken' => '<string>', ]);
Parameter Details
Members
Result Syntax
[ 'CreationTime' => <DateTime>, 'Description' => '<string>', 'EventTimeFeatureName' => '<string>', 'FailureReason' => '<string>', 'FeatureDefinitions' => [ [ 'FeatureName' => '<string>', 'FeatureType' => 'Integral|Fractional|String', ], // ... ], 'FeatureGroupArn' => '<string>', 'FeatureGroupName' => '<string>', 'FeatureGroupStatus' => 'Creating|Created|CreateFailed|Deleting|DeleteFailed', 'NextToken' => '<string>', 'OfflineStoreConfig' => [ 'DataCatalogConfig' => [ 'Catalog' => '<string>', 'Database' => '<string>', 'TableName' => '<string>', ], 'DisableGlueTableCreation' => true || false, 'S3StorageConfig' => [ 'KmsKeyId' => '<string>', 'S3Uri' => '<string>', ], ], 'OfflineStoreStatus' => [ 'BlockedReason' => '<string>', 'Status' => 'Active|Blocked|Disabled', ], 'OnlineStoreConfig' => [ 'EnableOnlineStore' => true || false, 'SecurityConfig' => [ 'KmsKeyId' => '<string>', ], ], 'RecordIdentifierFeatureName' => '<string>', 'RoleArn' => '<string>', ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp indicating when SageMaker created the
FeatureGroup
. - Description
-
- Type: string
A free form description of the feature group.
- EventTimeFeatureName
-
- Required: Yes
- Type: string
The name of the feature that stores the
EventTime
of a Record in aFeatureGroup
.An
EventTime
is a point in time when a new event occurs that corresponds to the creation or update of aRecord
in aFeatureGroup
. AllRecords
in theFeatureGroup
have a correspondingEventTime
. - FailureReason
-
- Type: string
The reason that the
FeatureGroup
failed to be replicated in theOfflineStore
. This is failure can occur because:-
The
FeatureGroup
could not be created in theOfflineStore
. -
The
FeatureGroup
could not be deleted from theOfflineStore
.
- FeatureDefinitions
-
- Required: Yes
- Type: Array of FeatureDefinition structures
A list of the
Features
in theFeatureGroup
. Each feature is defined by aFeatureName
andFeatureType
. - FeatureGroupArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the
FeatureGroup
. - FeatureGroupName
-
- Required: Yes
- Type: string
he name of the
FeatureGroup
. - FeatureGroupStatus
-
- Type: string
The status of the feature group.
- NextToken
-
- Required: Yes
- Type: string
A token to resume pagination of the list of
Features
(FeatureDefinitions
). - OfflineStoreConfig
-
- Type: OfflineStoreConfig structure
The configuration of the
OfflineStore
, inducing the S3 location of theOfflineStore
, AWS Glue or AWS Hive data catalogue configurations, and the security configuration. - OfflineStoreStatus
-
- Type: OfflineStoreStatus structure
The status of the
OfflineStore
. Notifies you if replicating data into theOfflineStore
has failed. Returns either:Active
orBlocked
- OnlineStoreConfig
-
- Type: OnlineStoreConfig structure
The configuration for the
OnlineStore
. - RecordIdentifierFeatureName
-
- Required: Yes
- Type: string
The name of the
Feature
used forRecordIdentifier
, whose value uniquely identifies a record stored in the feature store. - RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the
OfflineStore
if anOfflineStoreConfig
is provided.
Errors
-
Resource being access is not found.
DescribeFlowDefinition
$result = $client->describeFlowDefinition
([/* ... */]); $promise = $client->describeFlowDefinitionAsync
([/* ... */]);
Returns information about the specified flow definition.
Parameter Syntax
$result = $client->describeFlowDefinition([ 'FlowDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'FlowDefinitionArn' => '<string>', 'FlowDefinitionName' => '<string>', 'FlowDefinitionStatus' => 'Initializing|Active|Failed|Deleting', 'HumanLoopActivationConfig' => [ 'HumanLoopActivationConditionsConfig' => [ 'HumanLoopActivationConditions' => '<string>', ], ], 'HumanLoopConfig' => [ 'HumanTaskUiArn' => '<string>', 'PublicWorkforceTaskPrice' => [ 'AmountInUsd' => [ 'Cents' => <integer>, 'Dollars' => <integer>, 'TenthFractionsOfACent' => <integer>, ], ], 'TaskAvailabilityLifetimeInSeconds' => <integer>, 'TaskCount' => <integer>, 'TaskDescription' => '<string>', 'TaskKeywords' => ['<string>', ...], 'TaskTimeLimitInSeconds' => <integer>, 'TaskTitle' => '<string>', 'WorkteamArn' => '<string>', ], 'HumanLoopRequestSource' => [ 'AwsManagedHumanLoopRequestSource' => 'AWS/Rekognition/DetectModerationLabels/Image/V3|AWS/Textract/AnalyzeDocument/Forms/V1', ], 'OutputConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'RoleArn' => '<string>', ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp when the flow definition was created.
- FailureReason
-
- Type: string
The reason your flow definition failed.
- FlowDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the flow defintion.
- FlowDefinitionName
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the flow definition.
- FlowDefinitionStatus
-
- Required: Yes
- Type: string
The status of the flow definition. Valid values are listed below.
- HumanLoopActivationConfig
-
- Type: HumanLoopActivationConfig structure
An object containing information about what triggers a human review workflow.
- HumanLoopConfig
-
- Required: Yes
- Type: HumanLoopConfig structure
An object containing information about who works on the task, the workforce task price, and other task details.
- HumanLoopRequestSource
-
- Type: HumanLoopRequestSource structure
Container for configuring the source of human task requests. Used to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
- OutputConfig
-
- Required: Yes
- Type: FlowDefinitionOutputConfig structure
An object containing information about the output file.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) execution role for the flow definition.
Errors
-
Resource being access is not found.
DescribeHumanTaskUi
$result = $client->describeHumanTaskUi
([/* ... */]); $promise = $client->describeHumanTaskUiAsync
([/* ... */]);
Returns information about the requested human task user interface (worker task template).
Parameter Syntax
$result = $client->describeHumanTaskUi([ 'HumanTaskUiName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'CreationTime' => <DateTime>, 'HumanTaskUiArn' => '<string>', 'HumanTaskUiName' => '<string>', 'HumanTaskUiStatus' => 'Active|Deleting', 'UiTemplate' => [ 'ContentSha256' => '<string>', 'Url' => '<string>', ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The timestamp when the human task user interface was created.
- HumanTaskUiArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the human task user interface (worker task template).
- HumanTaskUiName
-
- Required: Yes
- Type: string
The name of the human task user interface (worker task template).
- HumanTaskUiStatus
-
- Type: string
The status of the human task user interface (worker task template). Valid values are listed below.
- UiTemplate
-
- Required: Yes
- Type: UiTemplateInfo structure
Container for user interface template information.
Errors
-
Resource being access is not found.
DescribeHyperParameterTuningJob
$result = $client->describeHyperParameterTuningJob
([/* ... */]); $promise = $client->describeHyperParameterTuningJobAsync
([/* ... */]);
Gets a description of a hyperparameter tuning job.
Parameter Syntax
$result = $client->describeHyperParameterTuningJob([ 'HyperParameterTuningJobName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'BestTrainingJob' => [ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'FinalHyperParameterTuningJobObjectiveMetric' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', 'Value' => <float>, ], 'ObjectiveStatus' => 'Succeeded|Pending|Failed', 'TrainingEndTime' => <DateTime>, 'TrainingJobArn' => '<string>', 'TrainingJobDefinitionName' => '<string>', 'TrainingJobName' => '<string>', 'TrainingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TrainingStartTime' => <DateTime>, 'TunedHyperParameters' => ['<string>', ...], 'TuningJobName' => '<string>', ], 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'HyperParameterTuningEndTime' => <DateTime>, 'HyperParameterTuningJobArn' => '<string>', 'HyperParameterTuningJobConfig' => [ 'HyperParameterTuningJobObjective' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', ], 'ParameterRanges' => [ 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', 'Values' => ['<string>', ...], ], // ... ], 'ContinuousParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], 'IntegerParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], ], 'ResourceLimits' => [ 'MaxNumberOfTrainingJobs' => <integer>, 'MaxParallelTrainingJobs' => <integer>, ], 'Strategy' => 'Bayesian|Random', 'TrainingJobEarlyStoppingType' => 'Off|Auto', 'TuningJobCompletionCriteria' => [ 'TargetObjectiveMetricValue' => <float>, ], ], 'HyperParameterTuningJobName' => '<string>', 'HyperParameterTuningJobStatus' => 'Completed|InProgress|Failed|Stopped|Stopping', 'LastModifiedTime' => <DateTime>, 'ObjectiveStatusCounters' => [ 'Failed' => <integer>, 'Pending' => <integer>, 'Succeeded' => <integer>, ], 'OverallBestTrainingJob' => [ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'FinalHyperParameterTuningJobObjectiveMetric' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', 'Value' => <float>, ], 'ObjectiveStatus' => 'Succeeded|Pending|Failed', 'TrainingEndTime' => <DateTime>, 'TrainingJobArn' => '<string>', 'TrainingJobDefinitionName' => '<string>', 'TrainingJobName' => '<string>', 'TrainingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TrainingStartTime' => <DateTime>, 'TunedHyperParameters' => ['<string>', ...], 'TuningJobName' => '<string>', ], 'TrainingJobDefinition' => [ 'AlgorithmSpecification' => [ 'AlgorithmName' => '<string>', 'MetricDefinitions' => [ [ 'Name' => '<string>', 'Regex' => '<string>', ], // ... ], 'TrainingImage' => '<string>', 'TrainingInputMode' => 'Pipe|File', ], 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', ], 'DefinitionName' => '<string>', 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'HyperParameterRanges' => [ 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', 'Values' => ['<string>', ...], ], // ... ], 'ContinuousParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], 'IntegerParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], ], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', 'FileSystemAccessMode' => 'rw|ro', 'FileSystemId' => '<string>', 'FileSystemType' => 'EFS|FSxLustre', ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'InputMode' => 'Pipe|File', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, ], ], // ... ], 'OutputDataConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'ResourceConfig' => [ '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.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', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'RoleArn' => '<string>', 'StaticHyperParameters' => ['<string>', ...], 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TuningObjective' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'TrainingJobDefinitions' => [ [ 'AlgorithmSpecification' => [ 'AlgorithmName' => '<string>', 'MetricDefinitions' => [ [ 'Name' => '<string>', 'Regex' => '<string>', ], // ... ], 'TrainingImage' => '<string>', 'TrainingInputMode' => 'Pipe|File', ], 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', ], 'DefinitionName' => '<string>', 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'HyperParameterRanges' => [ 'CategoricalParameterRanges' => [ [ 'Name' => '<string>', 'Values' => ['<string>', ...], ], // ... ], 'ContinuousParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], 'IntegerParameterRanges' => [ [ 'MaxValue' => '<string>', 'MinValue' => '<string>', 'Name' => '<string>', 'ScalingType' => 'Auto|Linear|Logarithmic|ReverseLogarithmic', ], // ... ], ], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', 'FileSystemAccessMode' => 'rw|ro', 'FileSystemId' => '<string>', 'FileSystemType' => 'EFS|FSxLustre', ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'InputMode' => 'Pipe|File', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, ], ], // ... ], 'OutputDataConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'ResourceConfig' => [ '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.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', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'RoleArn' => '<string>', 'StaticHyperParameters' => ['<string>', ...], 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TuningObjective' => [ 'MetricName' => '<string>', 'Type' => 'Maximize|Minimize', ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], // ... ], 'TrainingJobStatusCounters' => [ 'Completed' => <integer>, 'InProgress' => <integer>, 'NonRetryableError' => <integer>, 'RetryableError' => <integer>, 'Stopped' => <integer>, ], 'WarmStartConfig' => [ 'ParentHyperParameterTuningJobs' => [ [ 'HyperParameterTuningJobName' => '<string>', ], // ... ], 'WarmStartType' => 'IdenticalDataAndAlgorithm|TransferLearning', ], ]
Result Details
Members
- BestTrainingJob
-
- Type: HyperParameterTrainingJobSummary structure
A TrainingJobSummary object that describes the training job that completed with the best current HyperParameterTuningJobObjective.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the tuning job started.
- FailureReason
-
- Type: string
If the tuning job failed, the reason it failed.
- HyperParameterTuningEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the tuning job ended.
- HyperParameterTuningJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the tuning job.
- HyperParameterTuningJobConfig
-
- Required: Yes
- Type: HyperParameterTuningJobConfig structure
The HyperParameterTuningJobConfig object that specifies the configuration of the tuning job.
- HyperParameterTuningJobName
-
- Required: Yes
- Type: string
The name of the tuning job.
- HyperParameterTuningJobStatus
-
- Required: Yes
- Type: string
The status of the tuning job: InProgress, Completed, Failed, Stopping, or Stopped.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the status of the tuning job was modified.
- ObjectiveStatusCounters
-
- Required: Yes
- Type: ObjectiveStatusCounters structure
The ObjectiveStatusCounters object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.
- OverallBestTrainingJob
-
- Type: HyperParameterTrainingJobSummary structure
If the hyperparameter tuning job is an warm start tuning job with a
WarmStartType
ofIDENTICAL_DATA_AND_ALGORITHM
, this is the TrainingJobSummary for the training job with the best objective metric value of all training jobs launched by this tuning job and all parent jobs specified for the warm start tuning job. - TrainingJobDefinition
-
- Type: HyperParameterTrainingJobDefinition structure
The HyperParameterTrainingJobDefinition object that specifies the definition of the training jobs that this tuning job launches.
- TrainingJobDefinitions
-
- Type: Array of HyperParameterTrainingJobDefinition structures
A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
- TrainingJobStatusCounters
-
- Required: Yes
- Type: TrainingJobStatusCounters structure
The TrainingJobStatusCounters object that specifies the number of training jobs, categorized by status, that this tuning job launched.
- WarmStartConfig
-
- Type: HyperParameterTuningJobWarmStartConfig structure
The configuration for starting the hyperparameter parameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
Errors
-
Resource being access is not found.
DescribeImage
$result = $client->describeImage
([/* ... */]); $promise = $client->describeImageAsync
([/* ... */]);
Describes a SageMaker image.
Parameter Syntax
$result = $client->describeImage([ 'ImageName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'CreationTime' => <DateTime>, 'Description' => '<string>', 'DisplayName' => '<string>', 'FailureReason' => '<string>', 'ImageArn' => '<string>', 'ImageName' => '<string>', 'ImageStatus' => 'CREATING|CREATED|CREATE_FAILED|UPDATING|UPDATE_FAILED|DELETING|DELETE_FAILED', 'LastModifiedTime' => <DateTime>, 'RoleArn' => '<string>', ]
Result Details
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the image was created.
- Description
-
- Type: string
The description of the image.
- DisplayName
-
- Type: string
The name of the image as displayed.
- FailureReason
-
- Type: string
When a create, update, or delete operation fails, the reason for the failure.
- ImageArn
-
- Type: string
The Amazon Resource Name (ARN) of the image.
- ImageName
-
- Type: string
The name of the image.
- ImageStatus
-
- Type: string
The status of the image.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the image was last modified.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM role that enables Amazon SageMaker to perform tasks on your behalf.
Errors
-
Resource being access is not found.
DescribeImageVersion
$result = $client->describeImageVersion
([/* ... */]); $promise = $client->describeImageVersionAsync
([/* ... */]);
Describes a version of a SageMaker image.
Parameter Syntax
$result = $client->describeImageVersion([ 'ImageName' => '<string>', // REQUIRED 'Version' => <integer>, ]);
Parameter Details
Members
Result Syntax
[ 'BaseImage' => '<string>', 'ContainerImage' => '<string>', 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'ImageArn' => '<string>', 'ImageVersionArn' => '<string>', 'ImageVersionStatus' => 'CREATING|CREATED|CREATE_FAILED|DELETING|DELETE_FAILED', 'LastModifiedTime' => <DateTime>, 'Version' => <integer>, ]
Result Details
Members
- BaseImage
-
- Type: string
The registry path of the container image on which this image version is based.
- ContainerImage
-
- Type: string
The registry path of the container image that contains this image version.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the version was created.
- FailureReason
-
- Type: string
When a create or delete operation fails, the reason for the failure.
- ImageArn
-
- Type: string
The Amazon Resource Name (ARN) of the image the version is based on.
- ImageVersionArn
-
- Type: string
The ARN of the version.
- ImageVersionStatus
-
- Type: string
The status of the version.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
When the version was last modified.
- Version
-
- Type: int
The version number.
Errors
-
Resource being access is not found.
DescribeLabelingJob
$result = $client->describeLabelingJob
([/* ... */]); $promise = $client->describeLabelingJobAsync
([/* ... */]);
Gets information about a labeling job.
Parameter Syntax
$result = $client->describeLabelingJob([ 'LabelingJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'CreationTime' => <DateTime>, 'FailureReason' => '<string>', 'HumanTaskConfig' => [ 'AnnotationConsolidationConfig' => [ 'AnnotationConsolidationLambdaArn' => '<string>', ], 'MaxConcurrentTaskCount' => <integer>, 'NumberOfHumanWorkersPerDataObject' => <integer>, 'PreHumanTaskLambdaArn' => '<string>', 'PublicWorkforceTaskPrice' => [ 'AmountInUsd' => [ 'Cents' => <integer>, 'Dollars' => <integer>, 'TenthFractionsOfACent' => <integer>, ], ], 'TaskAvailabilityLifetimeInSeconds' => <integer>, 'TaskDescription' => '<string>', 'TaskKeywords' => ['<string>', ...], 'TaskTimeLimitInSeconds' => <integer>, 'TaskTitle' => '<string>', 'UiConfig' => [ 'HumanTaskUiArn' => '<string>', 'UiTemplateS3Uri' => '<string>', ], 'WorkteamArn' => '<string>', ], 'InputConfig' => [ 'DataAttributes' => [ 'ContentClassifiers' => ['<string>', ...], ], 'DataSource' => [ 'S3DataSource' => [ 'ManifestS3Uri' => '<string>', ], 'SnsDataSource' => [ 'SnsTopicArn' => '<string>', ], ], ], 'JobReferenceCode' => '<string>', 'LabelAttributeName' => '<string>', 'LabelCategoryConfigS3Uri' => '<string>', 'LabelCounters' => [ 'FailedNonRetryableError' => <integer>, 'HumanLabeled' => <integer>, 'MachineLabeled' => <integer>, 'TotalLabeled' => <integer>, 'Unlabeled' => <integer>, ], 'LabelingJobAlgorithmsConfig' => [ 'InitialActiveLearningModelArn' => '<string>', 'LabelingJobAlgorithmSpecificationArn' => '<string>', 'LabelingJobResourceConfig' => [ 'VolumeKmsKeyId' => '<string>', ], ], 'LabelingJobArn' => '<string>', 'LabelingJobName' => '<string>', 'LabelingJobOutput' => [ 'FinalActiveLearningModelArn' => '<string>', 'OutputDatasetS3Uri' => '<string>', ], 'LabelingJobStatus' => 'Initializing|InProgress|Completed|Failed|Stopping|Stopped', 'LastModifiedTime' => <DateTime>, 'OutputConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', 'SnsTopicArn' => '<string>', ], 'RoleArn' => '<string>', 'StoppingConditions' => [ 'MaxHumanLabeledObjectCount' => <integer>, 'MaxPercentageOfInputDatasetLabeled' => <integer>, ], 'Tags' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the labeling job was created.
- FailureReason
-
- Type: string
If the job failed, the reason that it failed.
- HumanTaskConfig
-
- Required: Yes
- Type: HumanTaskConfig structure
Configuration information required for human workers to complete a labeling task.
- InputConfig
-
- Required: Yes
- Type: LabelingJobInputConfig structure
Input configuration information for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
- JobReferenceCode
-
- Required: Yes
- Type: string
A unique identifier for work done as part of a labeling job.
- LabelAttributeName
-
- Type: string
The attribute used as the label in the output manifest file.
- LabelCategoryConfigS3Uri
-
- Type: string
The S3 location of the JSON file that defines the categories used to label data objects. Please note the following label-category limits:
-
Semantic segmentation labeling jobs using automated labeling: 20 labels
-
Box bounding labeling jobs (all): 10 labels
The file is a JSON structure in the following format:
{
"document-version": "2018-11-28"
"labels": [
{
"label": "label 1"
},
{
"label": "label 2"
},
...
{
"label": "label n"
}
]
}
- LabelCounters
-
- Required: Yes
- Type: LabelCounters structure
Provides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn't be labeled, and the total number of objects labeled.
- LabelingJobAlgorithmsConfig
-
- Type: LabelingJobAlgorithmsConfig structure
Configuration information for automated data labeling.
- LabelingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the labeling job.
- LabelingJobName
-
- Required: Yes
- Type: string
The name assigned to the labeling job when it was created.
- LabelingJobOutput
-
- Type: LabelingJobOutput structure
The location of the output produced by the labeling job.
- LabelingJobStatus
-
- Required: Yes
- Type: string
The processing status of the labeling job.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The date and time that the labeling job was last updated.
- OutputConfig
-
- Required: Yes
- Type: LabelingJobOutputConfig structure
The location of the job's output data and the AWS Key Management Service key ID for the key used to encrypt the output data, if any.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling.
- StoppingConditions
-
- Type: LabelingJobStoppingConditions structure
A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped.
- Tags
-
- Type: Array of Tag structures
An array of key-value pairs. You can use tags to categorize your AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS Resources.
Errors
-
Resource being access is not found.
DescribeModel
$result = $client->describeModel
([/* ... */]); $promise = $client->describeModelAsync
([/* ... */]);
Describes a model that you created using the CreateModel
API.
Parameter Syntax
$result = $client->describeModel([ 'ModelName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'Containers' => [ [ 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ImageConfig' => [ 'RepositoryAccessMode' => 'Platform|Vpc', ], 'Mode' => 'SingleModel|MultiModel', 'ModelDataUrl' => '<string>', 'ModelPackageName' => '<string>', 'MultiModelConfig' => [ 'ModelCacheSetting' => 'Enabled|Disabled', ], ], // ... ], 'CreationTime' => <DateTime>, 'EnableNetworkIsolation' => true || false, 'ExecutionRoleArn' => '<string>', 'ModelArn' => '<string>', 'ModelName' => '<string>', 'PrimaryContainer' => [ 'ContainerHostname' => '<string>', 'Environment' => ['<string>', ...], 'Image' => '<string>', 'ImageConfig' => [ 'RepositoryAccessMode' => 'Platform|Vpc', ], 'Mode' => 'SingleModel|MultiModel', 'ModelDataUrl' => '<string>', 'ModelPackageName' => '<string>', 'MultiModelConfig' => [ 'ModelCacheSetting' => 'Enabled|Disabled', ], ], 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ]
Result Details
Members
- Containers
-
- Type: Array of ContainerDefinition structures
The containers in the inference pipeline.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that shows when the model was created.
- EnableNetworkIsolation
-
- Type: boolean
If
True
, no inbound or outbound network calls can be made to or from the model container. - ExecutionRoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
- ModelArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model.
- ModelName
-
- Required: Yes
- Type: string
Name of the Amazon SageMaker model.
- PrimaryContainer
-
- Type: ContainerDefinition structure
The location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production.
- VpcConfig
-
- Type: VpcConfig structure
A VpcConfig object that specifies the VPC that this model has access to. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud
Errors
There are no errors described for this operation.
DescribeModelBiasJobDefinition
$result = $client->describeModelBiasJobDefinition
([/* ... */]); $promise = $client->describeModelBiasJobDefinitionAsync
([/* ... */]);
Returns a description of a model bias job definition.
Parameter Syntax
$result = $client->describeModelBiasJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'CreationTime' => <DateTime>, 'JobDefinitionArn' => '<string>', 'JobDefinitionName' => '<string>', 'JobResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'ModelBiasAppSpecification' => [ 'ConfigUri' => '<string>', 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', ], 'ModelBiasBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], ], 'ModelBiasJobInput' => [ 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'GroundTruthS3Input' => [ 'S3Uri' => '<string>', ], ], 'ModelBiasJobOutputConfig' => [ 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ [ 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the model bias job was created.
- JobDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model bias job.
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the bias job definition. The name must be unique within an AWS Region in the AWS account.
- JobResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources to deploy for a monitoring job.
- ModelBiasAppSpecification
-
- Required: Yes
- Type: ModelBiasAppSpecification structure
Configures the model bias job to run a specified Docker container image.
- ModelBiasBaselineConfig
-
- Type: ModelBiasBaselineConfig structure
The baseline configuration for a model bias job.
- ModelBiasJobInput
-
- Required: Yes
- Type: ModelBiasJobInput structure
Inputs for the model bias job.
- ModelBiasJobOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The output configuration for monitoring jobs.
- NetworkConfig
-
- Type: MonitoringNetworkConfig structure
Networking options for a model bias job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
A time limit for how long the monitoring job is allowed to run before stopping.
Errors
-
Resource being access is not found.
DescribeModelExplainabilityJobDefinition
$result = $client->describeModelExplainabilityJobDefinition
([/* ... */]); $promise = $client->describeModelExplainabilityJobDefinitionAsync
([/* ... */]);
Returns a description of a model explainability job definition.
Parameter Syntax
$result = $client->describeModelExplainabilityJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'CreationTime' => <DateTime>, 'JobDefinitionArn' => '<string>', 'JobDefinitionName' => '<string>', 'JobResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'ModelExplainabilityAppSpecification' => [ 'ConfigUri' => '<string>', 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', ], 'ModelExplainabilityBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], ], 'ModelExplainabilityJobInput' => [ 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], ], 'ModelExplainabilityJobOutputConfig' => [ 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ [ 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the model explainability job was created.
- JobDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model explainability job.
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the explainability job definition. The name must be unique within an AWS Region in the AWS account.
- JobResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources to deploy for a monitoring job.
- ModelExplainabilityAppSpecification
-
- Required: Yes
- Type: ModelExplainabilityAppSpecification structure
Configures the model explainability job to run a specified Docker container image.
- ModelExplainabilityBaselineConfig
-
- Type: ModelExplainabilityBaselineConfig structure
The baseline configuration for a model explainability job.
- ModelExplainabilityJobInput
-
- Required: Yes
- Type: ModelExplainabilityJobInput structure
Inputs for the model explainability job.
- ModelExplainabilityJobOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The output configuration for monitoring jobs.
- NetworkConfig
-
- Type: MonitoringNetworkConfig structure
Networking options for a model explainability job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
A time limit for how long the monitoring job is allowed to run before stopping.
Errors
-
Resource being access is not found.
DescribeModelPackage
$result = $client->describeModelPackage
([/* ... */]); $promise = $client->describeModelPackageAsync
([/* ... */]);
Returns a description of the specified model package, which is used to create Amazon SageMaker models or list them on AWS Marketplace.
To create models in Amazon SageMaker, buyers can subscribe to model packages listed on AWS Marketplace.
Parameter Syntax
$result = $client->describeModelPackage([ 'ModelPackageName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'ApprovalDescription' => '<string>', 'CertifyForMarketplace' => true || false, 'CreatedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'InferenceSpecification' => [ 'Containers' => [ [ 'ContainerHostname' => '<string>', 'Image' => '<string>', 'ImageDigest' => '<string>', 'ModelDataUrl' => '<string>', 'ProductId' => '<string>', ], // ... ], 'SupportedContentTypes' => ['<string>', ...], 'SupportedRealtimeInferenceInstanceTypes' => ['<string>', ...], 'SupportedResponseMIMETypes' => ['<string>', ...], 'SupportedTransformInstanceTypes' => ['<string>', ...], ], 'LastModifiedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'MetadataProperties' => [ 'CommitId' => '<string>', 'GeneratedBy' => '<string>', 'ProjectId' => '<string>', 'Repository' => '<string>', ], 'ModelApprovalStatus' => 'Approved|Rejected|PendingManualApproval', 'ModelMetrics' => [ 'Bias' => [ 'Report' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'Explainability' => [ 'Report' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'ModelDataQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], 'ModelQuality' => [ 'Constraints' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], 'Statistics' => [ 'ContentDigest' => '<string>', 'ContentType' => '<string>', 'S3Uri' => '<string>', ], ], ], 'ModelPackageArn' => '<string>', 'ModelPackageDescription' => '<string>', 'ModelPackageGroupName' => '<string>', 'ModelPackageName' => '<string>', 'ModelPackageStatus' => 'Pending|InProgress|Completed|Failed|Deleting', 'ModelPackageStatusDetails' => [ 'ImageScanStatuses' => [ [ 'FailureReason' => '<string>', 'Name' => '<string>', 'Status' => 'NotStarted|InProgress|Completed|Failed', ], // ... ], 'ValidationStatuses' => [ [ 'FailureReason' => '<string>', 'Name' => '<string>', 'Status' => 'NotStarted|InProgress|Completed|Failed', ], // ... ], ], 'ModelPackageVersion' => <integer>, 'SourceAlgorithmSpecification' => [ 'SourceAlgorithms' => [ [ 'AlgorithmName' => '<string>', 'ModelDataUrl' => '<string>', ], // ... ], ], 'ValidationSpecification' => [ 'ValidationProfiles' => [ [ 'ProfileName' => '<string>', 'TransformJobDefinition' => [ 'BatchStrategy' => 'MultiRecord|SingleRecord', 'Environment' => ['<string>', ...], 'MaxConcurrentTransforms' => <integer>, 'MaxPayloadInMB' => <integer>, 'TransformInput' => [ 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'S3DataSource' => [ 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'SplitType' => 'None|Line|RecordIO|TFRecord', ], 'TransformOutput' => [ 'Accept' => '<string>', 'AssembleWith' => 'None|Line', 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'TransformResources' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge', 'VolumeKmsKeyId' => '<string>', ], ], ], // ... ], 'ValidationRole' => '<string>', ], ]
Result Details
Members
- ApprovalDescription
-
- Type: string
A description provided for the model approval.
- CertifyForMarketplace
-
- Type: boolean
Whether the model package is certified for listing on AWS Marketplace.
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, or trial component.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp specifying when the model package was created.
- InferenceSpecification
-
- Type: InferenceSpecification structure
Details about inference jobs that can be run with models based on this model package.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, or trial component.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The last time the model package was modified.
- MetadataProperties
-
- Type: MetadataProperties structure
Metadata properties of the tracking entity, trial, or trial component.
- ModelApprovalStatus
-
- Type: string
The approval status of the model package.
- ModelMetrics
-
- Type: ModelMetrics structure
Metrics for the model.
- ModelPackageArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model package.
- ModelPackageDescription
-
- Type: string
A brief summary of the model package.
- ModelPackageGroupName
-
- Type: string
If the model is a versioned model, the name of the model group that the versioned model belongs to.
- ModelPackageName
-
- Required: Yes
- Type: string
The name of the model package being described.
- ModelPackageStatus
-
- Required: Yes
- Type: string
The current status of the model package.
- ModelPackageStatusDetails
-
- Required: Yes
- Type: ModelPackageStatusDetails structure
Details about the current status of the model package.
- ModelPackageVersion
-
- Type: int
The version of the model package.
- SourceAlgorithmSpecification
-
- Type: SourceAlgorithmSpecification structure
Details about the algorithm that was used to create the model package.
- ValidationSpecification
-
- Type: ModelPackageValidationSpecification structure
Configurations for one or more transform jobs that Amazon SageMaker runs to test the model package.
Errors
There are no errors described for this operation.
DescribeModelPackageGroup
$result = $client->describeModelPackageGroup
([/* ... */]); $promise = $client->describeModelPackageGroupAsync
([/* ... */]);
Gets a description for the specified model group.
Parameter Syntax
$result = $client->describeModelPackageGroup([ 'ModelPackageGroupName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'CreatedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'ModelPackageGroupArn' => '<string>', 'ModelPackageGroupDescription' => '<string>', 'ModelPackageGroupName' => '<string>', 'ModelPackageGroupStatus' => 'Pending|InProgress|Completed|Failed|Deleting|DeleteFailed', ]
Result Details
Members
- CreatedBy
-
- Required: Yes
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, or trial component.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time that the model group was created.
- ModelPackageGroupArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model group.
- ModelPackageGroupDescription
-
- Type: string
A description of the model group.
- ModelPackageGroupName
-
- Required: Yes
- Type: string
The name of the model group.
- ModelPackageGroupStatus
-
- Required: Yes
- Type: string
The status of the model group.
Errors
There are no errors described for this operation.
DescribeModelQualityJobDefinition
$result = $client->describeModelQualityJobDefinition
([/* ... */]); $promise = $client->describeModelQualityJobDefinitionAsync
([/* ... */]);
Returns a description of a model quality job definition.
Parameter Syntax
$result = $client->describeModelQualityJobDefinition([ 'JobDefinitionName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'CreationTime' => <DateTime>, 'JobDefinitionArn' => '<string>', 'JobDefinitionName' => '<string>', 'JobResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'ModelQualityAppSpecification' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'Environment' => ['<string>', ...], 'ImageUri' => '<string>', 'PostAnalyticsProcessorSourceUri' => '<string>', 'ProblemType' => 'BinaryClassification|MulticlassClassification|Regression', 'RecordPreprocessorSourceUri' => '<string>', ], 'ModelQualityBaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], ], 'ModelQualityJobInput' => [ 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], 'GroundTruthS3Input' => [ 'S3Uri' => '<string>', ], ], 'ModelQualityJobOutputConfig' => [ 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ [ 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the model quality job was created.
- JobDefinitionArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the model quality job.
- JobDefinitionName
-
- Required: Yes
- Type: string
The name of the quality job definition. The name must be unique within an AWS Region in the AWS account.
- JobResources
-
- Required: Yes
- Type: MonitoringResources structure
Identifies the resources to deploy for a monitoring job.
- ModelQualityAppSpecification
-
- Required: Yes
- Type: ModelQualityAppSpecification structure
Configures the model quality job to run a specified Docker container image.
- ModelQualityBaselineConfig
-
- Type: ModelQualityBaselineConfig structure
The baseline configuration for a model quality job.
- ModelQualityJobInput
-
- Required: Yes
- Type: ModelQualityJobInput structure
Inputs for the model quality job.
- ModelQualityJobOutputConfig
-
- Required: Yes
- Type: MonitoringOutputConfig structure
The output configuration for monitoring jobs.
- NetworkConfig
-
- Type: MonitoringNetworkConfig structure
Networking options for a model quality job.
- RoleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- StoppingCondition
-
- Type: MonitoringStoppingCondition structure
A time limit for how long the monitoring job is allowed to run before stopping.
Errors
-
Resource being access is not found.
DescribeMonitoringSchedule
$result = $client->describeMonitoringSchedule
([/* ... */]); $promise = $client->describeMonitoringScheduleAsync
([/* ... */]);
Describes the schedule for a monitoring job.
Parameter Syntax
$result = $client->describeMonitoringSchedule([ 'MonitoringScheduleName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'LastMonitoringExecutionSummary' => [ 'CreationTime' => <DateTime>, 'EndpointName' => '<string>', 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'MonitoringExecutionStatus' => 'Pending|Completed|CompletedWithViolations|InProgress|Failed|Stopping|Stopped', 'MonitoringJobDefinitionName' => '<string>', 'MonitoringScheduleName' => '<string>', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'ProcessingJobArn' => '<string>', 'ScheduledTime' => <DateTime>, ], 'MonitoringScheduleArn' => '<string>', 'MonitoringScheduleConfig' => [ 'MonitoringJobDefinition' => [ 'BaselineConfig' => [ 'BaseliningJobName' => '<string>', 'ConstraintsResource' => [ 'S3Uri' => '<string>', ], 'StatisticsResource' => [ 'S3Uri' => '<string>', ], ], 'Environment' => ['<string>', ...], 'MonitoringAppSpecification' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ImageUri' => '<string>', 'PostAnalyticsProcessorSourceUri' => '<string>', 'RecordPreprocessorSourceUri' => '<string>', ], 'MonitoringInputs' => [ [ 'EndpointInput' => [ 'EndTimeOffset' => '<string>', 'EndpointName' => '<string>', 'FeaturesAttribute' => '<string>', 'InferenceAttribute' => '<string>', 'LocalPath' => '<string>', 'ProbabilityAttribute' => '<string>', 'ProbabilityThresholdAttribute' => <float>, 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3InputMode' => 'Pipe|File', 'StartTimeOffset' => '<string>', ], ], // ... ], 'MonitoringOutputConfig' => [ 'KmsKeyId' => '<string>', 'MonitoringOutputs' => [ [ 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'MonitoringResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], ], 'MonitoringJobDefinitionName' => '<string>', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', 'ScheduleConfig' => [ 'ScheduleExpression' => '<string>', ], ], 'MonitoringScheduleName' => '<string>', 'MonitoringScheduleStatus' => 'Pending|Failed|Scheduled|Stopped', 'MonitoringType' => 'DataQuality|ModelQuality|ModelBias|ModelExplainability', ]
Result Details
Members
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the monitoring job was created.
- EndpointName
-
- Type: string
The name of the endpoint for the monitoring job.
- FailureReason
-
- Type: string
A string, up to one KB in size, that contains the reason a monitoring job failed, if it failed.
- LastModifiedTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the monitoring job was last modified.
- LastMonitoringExecutionSummary
-
- Type: MonitoringExecutionSummary structure
Describes metadata on the last execution to run, if there was one.
- MonitoringScheduleArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the monitoring schedule.
- MonitoringScheduleConfig
-
- Required: Yes
- Type: MonitoringScheduleConfig structure
The configuration object that specifies the monitoring schedule and defines the monitoring job.
- MonitoringScheduleName
-
- Required: Yes
- Type: string
Name of the monitoring schedule.
- MonitoringScheduleStatus
-
- Required: Yes
- Type: string
The status of an monitoring job.
- MonitoringType
-
- Type: string
The type of the monitoring job that this schedule runs. This is one of the following values.
-
DATA_QUALITY
- The schedule is for a data quality monitoring job. -
MODEL_QUALITY
- The schedule is for a model quality monitoring job. -
MODEL_BIAS
- The schedule is for a bias monitoring job. -
MODEL_EXPLAINABILITY
- The schedule is for an explainability monitoring job.
Errors
-
Resource being access is not found.
DescribeNotebookInstance
$result = $client->describeNotebookInstance
([/* ... */]); $promise = $client->describeNotebookInstanceAsync
([/* ... */]);
Returns information about a notebook instance.
Parameter Syntax
$result = $client->describeNotebookInstance([ 'NotebookInstanceName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'AcceleratorTypes' => ['<string>', ...], 'AdditionalCodeRepositories' => ['<string>', ...], 'CreationTime' => <DateTime>, 'DefaultCodeRepository' => '<string>', 'DirectInternetAccess' => 'Enabled|Disabled', 'FailureReason' => '<string>', 'InstanceType' => 'ml.t2.medium|ml.t2.large|ml.t2.xlarge|ml.t2.2xlarge|ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.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', 'KmsKeyId' => '<string>', 'LastModifiedTime' => <DateTime>, 'NetworkInterfaceId' => '<string>', 'NotebookInstanceArn' => '<string>', 'NotebookInstanceLifecycleConfigName' => '<string>', 'NotebookInstanceName' => '<string>', 'NotebookInstanceStatus' => 'Pending|InService|Stopping|Stopped|Failed|Deleting|Updating', 'RoleArn' => '<string>', 'RootAccess' => 'Enabled|Disabled', 'SecurityGroups' => ['<string>', ...], 'SubnetId' => '<string>', 'Url' => '<string>', 'VolumeSizeInGB' => <integer>, ]
Result Details
Members
- AcceleratorTypes
-
- Type: Array of strings
A list of the Elastic Inference (EI) instance types associated with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
- AdditionalCodeRepositories
-
- Type: Array of strings
An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in AWS 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 Amazon SageMaker Notebook Instances.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp. Use this parameter to return the time when the notebook instance was created
- DefaultCodeRepository
-
- Type: string
The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in AWS 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 Amazon SageMaker Notebook Instances.
- DirectInternetAccess
-
- Type: string
Describes whether Amazon SageMaker provides internet access to the notebook instance. If this value is set to Disabled, the notebook instance does not have internet access, and cannot connect to Amazon SageMaker training and endpoint services.
For more information, see Notebook Instances Are Internet-Enabled by Default.
- FailureReason
-
- Type: string
If status is
Failed
, the reason it failed. - InstanceType
-
- Type: string
The type of ML compute instance running on the notebook instance.
- KmsKeyId
-
- Type: string
The AWS KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp. Use this parameter to retrieve the time when the notebook instance was last modified.
- NetworkInterfaceId
-
- Type: string
The network interface IDs that Amazon SageMaker created at the time of creating the instance.
- NotebookInstanceArn
-
- Type: string
The Amazon Resource Name (ARN) of the notebook instance.
- NotebookInstanceLifecycleConfigName
-
- Type: string
Returns the name of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance
- NotebookInstanceName
-
- Type: string
The name of the Amazon SageMaker notebook instance.
- NotebookInstanceStatus
-
- Type: string
The status of the notebook instance.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of the IAM role associated with the instance.
- RootAccess
-
- Type: string
Whether root access is enabled or disabled for users of the notebook instance.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
- SecurityGroups
-
- Type: Array of strings
The IDs of the VPC security groups.
- SubnetId
-
- Type: string
The ID of the VPC subnet.
- Url
-
- Type: string
The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
- VolumeSizeInGB
-
- Type: int
The size, in GB, of the ML storage volume attached to the notebook instance.
Errors
There are no errors described for this operation.
DescribeNotebookInstanceLifecycleConfig
$result = $client->describeNotebookInstanceLifecycleConfig
([/* ... */]); $promise = $client->describeNotebookInstanceLifecycleConfigAsync
([/* ... */]);
Returns a description of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
Parameter Syntax
$result = $client->describeNotebookInstanceLifecycleConfig([ 'NotebookInstanceLifecycleConfigName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'CreationTime' => <DateTime>, 'LastModifiedTime' => <DateTime>, 'NotebookInstanceLifecycleConfigArn' => '<string>', 'NotebookInstanceLifecycleConfigName' => '<string>', 'OnCreate' => [ [ 'Content' => '<string>', ], // ... ], 'OnStart' => [ [ 'Content' => '<string>', ], // ... ], ]
Result Details
Members
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that tells when the lifecycle configuration was created.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that tells when the lifecycle configuration was last modified.
- NotebookInstanceLifecycleConfigArn
-
- Type: string
The Amazon Resource Name (ARN) of the lifecycle configuration.
- NotebookInstanceLifecycleConfigName
-
- Type: string
The name of the lifecycle configuration.
- OnCreate
-
- Type: Array of NotebookInstanceLifecycleHook structures
The shell script that runs only once, when you create a notebook instance.
- OnStart
-
- Type: Array of NotebookInstanceLifecycleHook structures
The shell script that runs every time you start a notebook instance, including when you create the notebook instance.
Errors
There are no errors described for this operation.
DescribePipeline
$result = $client->describePipeline
([/* ... */]); $promise = $client->describePipelineAsync
([/* ... */]);
Describes the details of a pipeline.
Parameter Syntax
$result = $client->describePipeline([ 'PipelineName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'CreatedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'LastModifiedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'LastRunTime' => <DateTime>, 'PipelineArn' => '<string>', 'PipelineDefinition' => '<string>', 'PipelineDescription' => '<string>', 'PipelineDisplayName' => '<string>', 'PipelineName' => '<string>', 'PipelineStatus' => 'Active', 'RoleArn' => '<string>', ]
Result Details
Members
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, or trial component.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the pipeline was created.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, or trial component.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the pipeline was last modified.
- LastRunTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the pipeline was last run.
- PipelineArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline.
- PipelineDefinition
-
- Type: string
The JSON pipeline definition.
- PipelineDescription
-
- Type: string
The description of the pipeline.
- PipelineDisplayName
-
- Type: string
The display name of the pipeline.
- PipelineName
-
- Type: string
The name of the pipeline.
- PipelineStatus
-
- Type: string
The status of the pipeline execution.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) that the pipeline uses to execute.
Errors
-
Resource being access is not found.
DescribePipelineDefinitionForExecution
$result = $client->describePipelineDefinitionForExecution
([/* ... */]); $promise = $client->describePipelineDefinitionForExecutionAsync
([/* ... */]);
Describes the details of an execution's pipeline definition.
Parameter Syntax
$result = $client->describePipelineDefinitionForExecution([ 'PipelineExecutionArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'CreationTime' => <DateTime>, 'PipelineDefinition' => '<string>', ]
Result Details
Members
Errors
-
Resource being access is not found.
DescribePipelineExecution
$result = $client->describePipelineExecution
([/* ... */]); $promise = $client->describePipelineExecutionAsync
([/* ... */]);
Describes the details of a pipeline execution.
Parameter Syntax
$result = $client->describePipelineExecution([ 'PipelineExecutionArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'CreatedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'LastModifiedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'LastModifiedTime' => <DateTime>, 'PipelineArn' => '<string>', 'PipelineExecutionArn' => '<string>', 'PipelineExecutionDescription' => '<string>', 'PipelineExecutionDisplayName' => '<string>', 'PipelineExecutionStatus' => 'Executing|Stopping|Stopped|Failed|Succeeded', ]
Result Details
Members
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, or trial component.
- CreationTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the pipeline execution was created.
- LastModifiedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, or trial component.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the pipeline execution was modified last.
- PipelineArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline.
- PipelineExecutionArn
-
- Type: string
The Amazon Resource Name (ARN) of the pipeline execution.
- PipelineExecutionDescription
-
- Type: string
The description of the pipeline execution.
- PipelineExecutionDisplayName
-
- Type: string
The display name of the pipeline execution.
- PipelineExecutionStatus
-
- Type: string
The status of the pipeline execution.
Errors
-
Resource being access is not found.
DescribeProcessingJob
$result = $client->describeProcessingJob
([/* ... */]); $promise = $client->describeProcessingJobAsync
([/* ... */]);
Returns a description of a processing job.
Parameter Syntax
$result = $client->describeProcessingJob([ 'ProcessingJobName' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'AppSpecification' => [ 'ContainerArguments' => ['<string>', ...], 'ContainerEntrypoint' => ['<string>', ...], 'ImageUri' => '<string>', ], 'AutoMLJobArn' => '<string>', 'CreationTime' => <DateTime>, 'Environment' => ['<string>', ...], 'ExitMessage' => '<string>', 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'FailureReason' => '<string>', 'LastModifiedTime' => <DateTime>, 'MonitoringScheduleArn' => '<string>', 'NetworkConfig' => [ 'EnableInterContainerTrafficEncryption' => true || false, 'EnableNetworkIsolation' => true || false, 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ], 'ProcessingEndTime' => <DateTime>, 'ProcessingInputs' => [ [ 'AppManaged' => true || false, 'DatasetDefinition' => [ 'AthenaDatasetDefinition' => [ 'Catalog' => '<string>', 'Database' => '<string>', 'KmsKeyId' => '<string>', 'OutputCompression' => 'GZIP|SNAPPY|ZLIB', 'OutputFormat' => 'PARQUET|ORC|AVRO|JSON|TEXTFILE', 'OutputS3Uri' => '<string>', 'QueryString' => '<string>', 'WorkGroup' => '<string>', ], 'DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'InputMode' => 'Pipe|File', 'LocalPath' => '<string>', 'RedshiftDatasetDefinition' => [ 'ClusterId' => '<string>', 'ClusterRoleArn' => '<string>', 'Database' => '<string>', 'DbUser' => '<string>', 'KmsKeyId' => '<string>', 'OutputCompression' => 'None|GZIP|BZIP2|ZSTD|SNAPPY', 'OutputFormat' => 'PARQUET|CSV', 'OutputS3Uri' => '<string>', 'QueryString' => '<string>', ], ], 'InputName' => '<string>', 'S3Input' => [ 'LocalPath' => '<string>', 'S3CompressionType' => 'None|Gzip', 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix', 'S3InputMode' => 'Pipe|File', 'S3Uri' => '<string>', ], ], // ... ], 'ProcessingJobArn' => '<string>', 'ProcessingJobName' => '<string>', 'ProcessingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'ProcessingOutputConfig' => [ 'KmsKeyId' => '<string>', 'Outputs' => [ [ 'AppManaged' => true || false, 'FeatureStoreOutput' => [ 'FeatureGroupName' => '<string>', ], 'OutputName' => '<string>', 'S3Output' => [ 'LocalPath' => '<string>', 'S3UploadMode' => 'Continuous|EndOfJob', 'S3Uri' => '<string>', ], ], // ... ], ], 'ProcessingResources' => [ 'ClusterConfig' => [ 'InstanceCount' => <integer>, 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], ], 'ProcessingStartTime' => <DateTime>, 'RoleArn' => '<string>', 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, ], 'TrainingJobArn' => '<string>', ]
Result Details
Members
- AppSpecification
-
- Required: Yes
- Type: AppSpecification structure
Configures the processing job to run a specified container image.
- AutoMLJobArn
-
- Type: string
The ARN of an AutoML job associated with this processing job.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the processing job was created.
- Environment
-
- Type: Associative array of custom strings keys (ProcessingEnvironmentKey) to strings
The environment variables set in the Docker container.
- ExitMessage
-
- Type: string
An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
- ExperimentConfig
-
- Type: ExperimentConfig structure
The configuration information used to create an experiment.
- FailureReason
-
- Type: string
A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the processing job was last modified.
- MonitoringScheduleArn
-
- Type: string
The ARN of a monitoring schedule for an endpoint associated with this processing job.
- NetworkConfig
-
- Type: NetworkConfig structure
Networking options for a processing job.
- ProcessingEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the processing job completed.
- ProcessingInputs
-
- Type: Array of ProcessingInput structures
The inputs for a processing job.
- ProcessingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the processing job.
- ProcessingJobName
-
- Required: Yes
- Type: string
The name of the processing job. The name must be unique within an AWS Region in the AWS account.
- ProcessingJobStatus
-
- Required: Yes
- Type: string
Provides the status of a processing job.
- ProcessingOutputConfig
-
- Type: ProcessingOutputConfig structure
Output configuration for the processing job.
- ProcessingResources
-
- Required: Yes
- Type: ProcessingResources structure
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
- ProcessingStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time at which the processing job started.
- RoleArn
-
- Type: string
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- StoppingCondition
-
- Type: ProcessingStoppingCondition structure
The time limit for how long the processing job is allowed to run.
- TrainingJobArn
-
- Type: string
The ARN of a training job associated with this processing job.
Errors
-
Resource being access is not found.
DescribeProject
$result = $client->describeProject
([/* ... */]); $promise = $client->describeProjectAsync
([/* ... */]);
Describes the details of a project.
Parameter Syntax
$result = $client->describeProject([ 'ProjectName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'CreatedBy' => [ 'DomainId' => '<string>', 'UserProfileArn' => '<string>', 'UserProfileName' => '<string>', ], 'CreationTime' => <DateTime>, 'ProjectArn' => '<string>', 'ProjectDescription' => '<string>', 'ProjectId' => '<string>', 'ProjectName' => '<string>', 'ProjectStatus' => 'Pending|CreateInProgress|CreateCompleted|CreateFailed|DeleteInProgress|DeleteFailed|DeleteCompleted', 'ServiceCatalogProvisionedProductDetails' => [ 'ProvisionedProductId' => '<string>', 'ProvisionedProductStatusMessage' => '<string>', ], 'ServiceCatalogProvisioningDetails' => [ 'PathId' => '<string>', 'ProductId' => '<string>', 'ProvisioningArtifactId' => '<string>', 'ProvisioningParameters' => [ [ 'Key' => '<string>', 'Value' => '<string>', ], // ... ], ], ]
Result Details
Members
- CreatedBy
-
- Type: UserContext structure
Information about the user who created or modified an experiment, trial, or trial component.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
The time when the project was created.
- ProjectArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the project.
- ProjectDescription
-
- Type: string
The description of the project.
- ProjectId
-
- Required: Yes
- Type: string
The ID of the project.
- ProjectName
-
- Required: Yes
- Type: string
The name of the project.
- ProjectStatus
-
- Required: Yes
- Type: string
The status of the project.
- ServiceCatalogProvisionedProductDetails
-
- Type: ServiceCatalogProvisionedProductDetails structure
Information about a provisioned service catalog product.
- ServiceCatalogProvisioningDetails
-
- Required: Yes
- Type: ServiceCatalogProvisioningDetails structure
Information used to provision a service catalog product. For information, see What is AWS Service Catalog.
Errors
There are no errors described for this operation.
DescribeSubscribedWorkteam
$result = $client->describeSubscribedWorkteam
([/* ... */]); $promise = $client->describeSubscribedWorkteamAsync
([/* ... */]);
Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the AWS Marketplace.
Parameter Syntax
$result = $client->describeSubscribedWorkteam([ 'WorkteamArn' => '<string>', // REQUIRED ]);
Parameter Details
Members
Result Syntax
[ 'SubscribedWorkteam' => [ 'ListingId' => '<string>', 'MarketplaceDescription' => '<string>', 'MarketplaceTitle' => '<string>', 'SellerName' => '<string>', 'WorkteamArn' => '<string>', ], ]
Result Details
Members
- SubscribedWorkteam
-
- Required: Yes
- Type: SubscribedWorkteam structure
A
Workteam
instance that contains information about the work team.
Errors
There are no errors described for this operation.
DescribeTrainingJob
$result = $client->describeTrainingJob
([/* ... */]); $promise = $client->describeTrainingJobAsync
([/* ... */]);
Returns information about a training job.
Parameter Syntax
$result = $client->describeTrainingJob([ 'TrainingJobName' => '<string>', // REQUIRED ]);
Parameter Details
Result Syntax
[ 'AlgorithmSpecification' => [ 'AlgorithmName' => '<string>', 'EnableSageMakerMetricsTimeSeries' => true || false, 'MetricDefinitions' => [ [ 'Name' => '<string>', 'Regex' => '<string>', ], // ... ], 'TrainingImage' => '<string>', 'TrainingInputMode' => 'Pipe|File', ], 'AutoMLJobArn' => '<string>', 'BillableTimeInSeconds' => <integer>, 'CheckpointConfig' => [ 'LocalPath' => '<string>', 'S3Uri' => '<string>', ], 'CreationTime' => <DateTime>, 'DebugHookConfig' => [ 'CollectionConfigurations' => [ [ 'CollectionName' => '<string>', 'CollectionParameters' => ['<string>', ...], ], // ... ], 'HookParameters' => ['<string>', ...], 'LocalPath' => '<string>', 'S3OutputPath' => '<string>', ], 'DebugRuleConfigurations' => [ [ 'InstanceType' => 'ml.t3.medium|ml.t3.large|ml.t3.xlarge|ml.t3.2xlarge|ml.m4.xlarge|ml.m4.2xlarge|ml.m4.4xlarge|ml.m4.10xlarge|ml.m4.16xlarge|ml.c4.xlarge|ml.c4.2xlarge|ml.c4.4xlarge|ml.c4.8xlarge|ml.p2.xlarge|ml.p2.8xlarge|ml.p2.16xlarge|ml.p3.2xlarge|ml.p3.8xlarge|ml.p3.16xlarge|ml.c5.xlarge|ml.c5.2xlarge|ml.c5.4xlarge|ml.c5.9xlarge|ml.c5.18xlarge|ml.m5.large|ml.m5.xlarge|ml.m5.2xlarge|ml.m5.4xlarge|ml.m5.12xlarge|ml.m5.24xlarge|ml.r5.large|ml.r5.xlarge|ml.r5.2xlarge|ml.r5.4xlarge|ml.r5.8xlarge|ml.r5.12xlarge|ml.r5.16xlarge|ml.r5.24xlarge', 'LocalPath' => '<string>', 'RuleConfigurationName' => '<string>', 'RuleEvaluatorImage' => '<string>', 'RuleParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', 'VolumeSizeInGB' => <integer>, ], // ... ], 'DebugRuleEvaluationStatuses' => [ [ 'LastModifiedTime' => <DateTime>, 'RuleConfigurationName' => '<string>', 'RuleEvaluationJobArn' => '<string>', 'RuleEvaluationStatus' => 'InProgress|NoIssuesFound|IssuesFound|Error|Stopping|Stopped', 'StatusDetails' => '<string>', ], // ... ], 'EnableInterContainerTrafficEncryption' => true || false, 'EnableManagedSpotTraining' => true || false, 'EnableNetworkIsolation' => true || false, 'ExperimentConfig' => [ 'ExperimentName' => '<string>', 'TrialComponentDisplayName' => '<string>', 'TrialName' => '<string>', ], 'FailureReason' => '<string>', 'FinalMetricDataList' => [ [ 'MetricName' => '<string>', 'Timestamp' => <DateTime>, 'Value' => <float>, ], // ... ], 'HyperParameters' => ['<string>', ...], 'InputDataConfig' => [ [ 'ChannelName' => '<string>', 'CompressionType' => 'None|Gzip', 'ContentType' => '<string>', 'DataSource' => [ 'FileSystemDataSource' => [ 'DirectoryPath' => '<string>', 'FileSystemAccessMode' => 'rw|ro', 'FileSystemId' => '<string>', 'FileSystemType' => 'EFS|FSxLustre', ], 'S3DataSource' => [ 'AttributeNames' => ['<string>', ...], 'S3DataDistributionType' => 'FullyReplicated|ShardedByS3Key', 'S3DataType' => 'ManifestFile|S3Prefix|AugmentedManifestFile', 'S3Uri' => '<string>', ], ], 'InputMode' => 'Pipe|File', 'RecordWrapperType' => 'None|RecordIO', 'ShuffleConfig' => [ 'Seed' => <integer>, ], ], // ... ], 'LabelingJobArn' => '<string>', 'LastModifiedTime' => <DateTime>, 'ModelArtifacts' => [ 'S3ModelArtifacts' => '<string>', ], 'OutputDataConfig' => [ 'KmsKeyId' => '<string>', 'S3OutputPath' => '<string>', ], 'ProfilerConfig' => [ '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', 'LocalPath' => '<string>', 'RuleConfigurationName' => '<string>', 'RuleEvaluatorImage' => '<string>', 'RuleParameters' => ['<string>', ...], 'S3OutputPath' => '<string>', 'VolumeSizeInGB' => <integer>, ], // ... ], 'ProfilerRuleEvaluationStatuses' => [ [ 'LastModifiedTime' => <DateTime>, 'RuleConfigurationName' => '<string>', 'RuleEvaluationJobArn' => '<string>', 'RuleEvaluationStatus' => 'InProgress|NoIssuesFound|IssuesFound|Error|Stopping|Stopped', 'StatusDetails' => '<string>', ], // ... ], 'ProfilingStatus' => 'Enabled|Disabled', 'ResourceConfig' => [ '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.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', 'VolumeKmsKeyId' => '<string>', 'VolumeSizeInGB' => <integer>, ], 'RoleArn' => '<string>', 'SecondaryStatus' => 'Starting|LaunchingMLInstances|PreparingTrainingStack|Downloading|DownloadingTrainingImage|Training|Uploading|Stopping|Stopped|MaxRuntimeExceeded|Completed|Failed|Interrupted|MaxWaitTimeExceeded|Updating', 'SecondaryStatusTransitions' => [ [ 'EndTime' => <DateTime>, 'StartTime' => <DateTime>, 'Status' => 'Starting|LaunchingMLInstances|PreparingTrainingStack|Downloading|DownloadingTrainingImage|Training|Uploading|Stopping|Stopped|MaxRuntimeExceeded|Completed|Failed|Interrupted|MaxWaitTimeExceeded|Updating', 'StatusMessage' => '<string>', ], // ... ], 'StoppingCondition' => [ 'MaxRuntimeInSeconds' => <integer>, 'MaxWaitTimeInSeconds' => <integer>, ], 'TensorBoardOutputConfig' => [ 'LocalPath' => '<string>', 'S3OutputPath' => '<string>', ], 'TrainingEndTime' => <DateTime>, 'TrainingJobArn' => '<string>', 'TrainingJobName' => '<string>', 'TrainingJobStatus' => 'InProgress|Completed|Failed|Stopping|Stopped', 'TrainingStartTime' => <DateTime>, 'TrainingTimeInSeconds' => <integer>, 'TuningJobArn' => '<string>', 'VpcConfig' => [ 'SecurityGroupIds' => ['<string>', ...], 'Subnets' => ['<string>', ...], ], ]
Result Details
Members
- AlgorithmSpecification
-
- Required: Yes
- Type: AlgorithmSpecification structure
Information about the algorithm used for training, and algorithm metadata.
- AutoMLJobArn
-
- Type: string
The Amazon Resource Name (ARN) of an AutoML job.
- BillableTimeInSeconds
-
- Type: int
The billable time in seconds.
You can calculate the savings from using managed spot training using the formula
(1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100
. For example, ifBillableTimeInSeconds
is 100 andTrainingTimeInSeconds
is 500, the savings is 80%. - CheckpointConfig
-
- Type: CheckpointConfig structure
Contains information about the output location for managed spot training checkpoint data.
- CreationTime
-
- Required: Yes
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the training job was created.
- DebugHookConfig
-
- Type: DebugHookConfig structure
Configuration information for the 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 Debugger rules for debugging output tensors.
- DebugRuleEvaluationStatuses
-
- Type: Array of DebugRuleEvaluationStatus structures
Evaluation status of Debugger rules for debugging on a training job.
- EnableInterContainerTrafficEncryption
-
- Type: boolean
To encrypt all communications between ML compute instances in distributed training, choose
True
. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training. - EnableManagedSpotTraining
-
- Type: boolean
A Boolean indicating whether managed spot training is enabled (
True
) or not (False
). - EnableNetworkIsolation
-
- Type: boolean
If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose
True
. If you enable network isolation for training jobs that are configured to use a VPC, Amazon SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access. - ExperimentConfig
-
- Type: ExperimentConfig structure
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
- FailureReason
-
- Type: string
If the training job failed, the reason it failed.
- FinalMetricDataList
-
- Type: Array of MetricData structures
A collection of
MetricData
objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch. - HyperParameters
-
- Type: Associative array of custom strings keys (HyperParameterKey) to strings
Algorithm-specific parameters.
- InputDataConfig
-
- Type: Array of Channel structures
An array of
Channel
objects that describes each data input channel. - LabelingJobArn
-
- Type: string
The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.
- LastModifiedTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
A timestamp that indicates when the status of the training job was last modified.
- ModelArtifacts
-
- Required: Yes
- Type: ModelArtifacts structure
Information about the Amazon S3 location that is configured for storing model artifacts.
- OutputDataConfig
-
- Type: OutputDataConfig structure
The S3 path where model artifacts that you configured when creating the job are stored. Amazon SageMaker creates subfolders for model artifacts.
- ProfilerConfig
-
- Type: ProfilerConfig structure
Configuration information for Debugger system monitoring, framework profiling, and storage paths.
- ProfilerRuleConfigurations
-
- Type: Array of ProfilerRuleConfiguration structures
Configuration information for Debugger rules for profiling system and framework metrics.
- ProfilerRuleEvaluationStatuses
-
- Type: Array of ProfilerRuleEvaluationStatus structures
Evaluation status of Debugger rules for profiling on a training job.
- ProfilingStatus
-
- Type: string
Profiling status of a training job.
- ResourceConfig
-
- Required: Yes
- Type: ResourceConfig structure
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
- RoleArn
-
- Type: string
The AWS Identity and Access Management (IAM) role configured for the training job.
- SecondaryStatus
-
- Required: Yes
- Type: string
Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see
StatusMessage
under SecondaryStatusTransition.Amazon SageMaker provides primary statuses and secondary statuses that apply to each of them:
- InProgress
-
-
Starting
- Starting the training job. -
Downloading
- An optional stage for algorithms that supportFile
training input mode. It indicates that data is being downloaded to the ML storage volumes. -
Training
- Training is in progress. -
Interrupted
- The job stopped because the managed spot training instances were interrupted. -
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
-
- Completed
-
-
Completed
- The training job has completed.
-
- Failed
-
-
Failed
- The training job has failed. The reason for the failure is returned in theFailureReason
field ofDescribeTrainingJobResponse
.
-
- Stopped
-
-
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime. -
MaxWaitTimeExceeded
- The job stopped because it exceeded the maximum allowed wait time. -
Stopped
- The training job has stopped.
-
- Stopping
-
-
Stopping
- Stopping the training job.
-
Valid values for
SecondaryStatus
are subject to change.We no longer support the following secondary statuses:
-
LaunchingMLInstances
-
PreparingTrainingStack
-
DownloadingTrainingImage
- SecondaryStatusTransitions
-
- Type: Array of SecondaryStatusTransition structures
A history of all of the secondary statuses that the training job has transitioned through.
- StoppingCondition
-
- Required: Yes
- Type: StoppingCondition structure
Specifies a limit to how long a model training job can run. It also specifies the maximum time to wait for a spot instance. When the job reaches the time limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, Amazon SageMaker sends the algorithm the
SIGTERM
signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost. - TensorBoardOutputConfig
-
- Type: TensorBoardOutputConfig structure
Configuration of storage locations for the Debugger TensorBoard output data.
- TrainingEndTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of
TrainingStartTime
and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when Amazon SageMaker detects a job failure. - TrainingJobArn
-
- Required: Yes
- Type: string
The Amazon Resource Name (ARN) of the training job.
- TrainingJobName
-
- Required: Yes
- Type: string
Name of the model training job.
- TrainingJobStatus
-
- Required: Yes
- Type: string
The status of the training job.
Amazon SageMaker provides the following training job statuses:
-
InProgress
- The training is in progress. -
Completed
- The training job has completed. -
Failed
- The training job has failed. To see the reason for the failure, see theFailureReason
field in the response to aDescribeTrainingJobResponse
call. -
Stopping
- The training job is stopping. -
Stopped
- The training job has stopped.
For more detailed information, see
SecondaryStatus
. - TrainingStartTime
-
- Type: timestamp (string|DateTime or anything parsable by strtotime)
Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of
TrainingEndTime
. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container. - TrainingTimeInSeconds
-
- Type: int
The training time in seconds.
- <