@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class AbstractAmazonSageMakerAsync extends AbstractAmazonSageMaker implements AmazonSageMakerAsync
AmazonSageMakerAsync
. Convenient method forms pass through to the corresponding
overload that takes a request object and an AsyncHandler
, which throws an
UnsupportedOperationException
.ENDPOINT_PREFIX
addTags, associateTrialComponent, createAlgorithm, createApp, createAutoMLJob, createCodeRepository, createCompilationJob, createDomain, createEndpoint, createEndpointConfig, createExperiment, createFlowDefinition, createHumanTaskUi, createHyperParameterTuningJob, createLabelingJob, createModel, createModelPackage, createMonitoringSchedule, createNotebookInstance, createNotebookInstanceLifecycleConfig, createPresignedDomainUrl, createPresignedNotebookInstanceUrl, createProcessingJob, createTrainingJob, createTransformJob, createTrial, createTrialComponent, createUserProfile, createWorkteam, deleteAlgorithm, deleteApp, deleteCodeRepository, deleteDomain, deleteEndpoint, deleteEndpointConfig, deleteExperiment, deleteFlowDefinition, deleteModel, deleteModelPackage, deleteMonitoringSchedule, deleteNotebookInstance, deleteNotebookInstanceLifecycleConfig, deleteTags, deleteTrial, deleteTrialComponent, deleteUserProfile, deleteWorkteam, describeAlgorithm, describeApp, describeAutoMLJob, describeCodeRepository, describeCompilationJob, describeDomain, describeEndpoint, describeEndpointConfig, describeExperiment, describeFlowDefinition, describeHumanTaskUi, describeHyperParameterTuningJob, describeLabelingJob, describeModel, describeModelPackage, describeMonitoringSchedule, describeNotebookInstance, describeNotebookInstanceLifecycleConfig, describeProcessingJob, describeSubscribedWorkteam, describeTrainingJob, describeTransformJob, describeTrial, describeTrialComponent, describeUserProfile, describeWorkforce, describeWorkteam, disassociateTrialComponent, getCachedResponseMetadata, getSearchSuggestions, listAlgorithms, listApps, listAutoMLJobs, listCandidatesForAutoMLJob, listCodeRepositories, listCompilationJobs, listDomains, listEndpointConfigs, listEndpoints, listExperiments, listFlowDefinitions, listHumanTaskUis, listHyperParameterTuningJobs, listLabelingJobs, listLabelingJobsForWorkteam, listModelPackages, listModels, listMonitoringExecutions, listMonitoringSchedules, listNotebookInstanceLifecycleConfigs, listNotebookInstances, listProcessingJobs, listSubscribedWorkteams, listTags, listTrainingJobs, listTrainingJobsForHyperParameterTuningJob, listTransformJobs, listTrialComponents, listTrials, listUserProfiles, listWorkteams, renderUiTemplate, search, shutdown, startMonitoringSchedule, startNotebookInstance, stopAutoMLJob, stopCompilationJob, stopHyperParameterTuningJob, stopLabelingJob, stopMonitoringSchedule, stopNotebookInstance, stopProcessingJob, stopTrainingJob, stopTransformJob, updateCodeRepository, updateDomain, updateEndpoint, updateEndpointWeightsAndCapacities, updateExperiment, updateMonitoringSchedule, updateNotebookInstance, updateNotebookInstanceLifecycleConfig, updateTrial, updateTrialComponent, updateUserProfile, updateWorkforce, updateWorkteam, waiters
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
addTags, associateTrialComponent, createAlgorithm, createApp, createAutoMLJob, createCodeRepository, createCompilationJob, createDomain, createEndpoint, createEndpointConfig, createExperiment, createFlowDefinition, createHumanTaskUi, createHyperParameterTuningJob, createLabelingJob, createModel, createModelPackage, createMonitoringSchedule, createNotebookInstance, createNotebookInstanceLifecycleConfig, createPresignedDomainUrl, createPresignedNotebookInstanceUrl, createProcessingJob, createTrainingJob, createTransformJob, createTrial, createTrialComponent, createUserProfile, createWorkteam, deleteAlgorithm, deleteApp, deleteCodeRepository, deleteDomain, deleteEndpoint, deleteEndpointConfig, deleteExperiment, deleteFlowDefinition, deleteModel, deleteModelPackage, deleteMonitoringSchedule, deleteNotebookInstance, deleteNotebookInstanceLifecycleConfig, deleteTags, deleteTrial, deleteTrialComponent, deleteUserProfile, deleteWorkteam, describeAlgorithm, describeApp, describeAutoMLJob, describeCodeRepository, describeCompilationJob, describeDomain, describeEndpoint, describeEndpointConfig, describeExperiment, describeFlowDefinition, describeHumanTaskUi, describeHyperParameterTuningJob, describeLabelingJob, describeModel, describeModelPackage, describeMonitoringSchedule, describeNotebookInstance, describeNotebookInstanceLifecycleConfig, describeProcessingJob, describeSubscribedWorkteam, describeTrainingJob, describeTransformJob, describeTrial, describeTrialComponent, describeUserProfile, describeWorkforce, describeWorkteam, disassociateTrialComponent, getCachedResponseMetadata, getSearchSuggestions, listAlgorithms, listApps, listAutoMLJobs, listCandidatesForAutoMLJob, listCodeRepositories, listCompilationJobs, listDomains, listEndpointConfigs, listEndpoints, listExperiments, listFlowDefinitions, listHumanTaskUis, listHyperParameterTuningJobs, listLabelingJobs, listLabelingJobsForWorkteam, listModelPackages, listModels, listMonitoringExecutions, listMonitoringSchedules, listNotebookInstanceLifecycleConfigs, listNotebookInstances, listProcessingJobs, listSubscribedWorkteams, listTags, listTrainingJobs, listTrainingJobsForHyperParameterTuningJob, listTransformJobs, listTrialComponents, listTrials, listUserProfiles, listWorkteams, renderUiTemplate, search, shutdown, startMonitoringSchedule, startNotebookInstance, stopAutoMLJob, stopCompilationJob, stopHyperParameterTuningJob, stopLabelingJob, stopMonitoringSchedule, stopNotebookInstance, stopProcessingJob, stopTrainingJob, stopTransformJob, updateCodeRepository, updateDomain, updateEndpoint, updateEndpointWeightsAndCapacities, updateExperiment, updateMonitoringSchedule, updateNotebookInstance, updateNotebookInstanceLifecycleConfig, updateTrial, updateTrialComponent, updateUserProfile, updateWorkforce, updateWorkteam, waiters
public Future<AddTagsResult> addTagsAsync(AddTagsRequest request)
AmazonSageMakerAsync
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
addTagsAsync
in interface AmazonSageMakerAsync
public Future<AddTagsResult> addTagsAsync(AddTagsRequest request, AsyncHandler<AddTagsRequest,AddTagsResult> asyncHandler)
AmazonSageMakerAsync
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
addTagsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<AssociateTrialComponentResult> associateTrialComponentAsync(AssociateTrialComponentRequest request)
AmazonSageMakerAsync
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.
associateTrialComponentAsync
in interface AmazonSageMakerAsync
public Future<AssociateTrialComponentResult> associateTrialComponentAsync(AssociateTrialComponentRequest request, AsyncHandler<AssociateTrialComponentRequest,AssociateTrialComponentResult> asyncHandler)
AmazonSageMakerAsync
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.
associateTrialComponentAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateAlgorithmResult> createAlgorithmAsync(CreateAlgorithmRequest request)
AmazonSageMakerAsync
Create a machine learning algorithm that you can use in Amazon SageMaker and list in the AWS Marketplace.
createAlgorithmAsync
in interface AmazonSageMakerAsync
public Future<CreateAlgorithmResult> createAlgorithmAsync(CreateAlgorithmRequest request, AsyncHandler<CreateAlgorithmRequest,CreateAlgorithmResult> asyncHandler)
AmazonSageMakerAsync
Create a machine learning algorithm that you can use in Amazon SageMaker and list in the AWS Marketplace.
createAlgorithmAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateAppResult> createAppAsync(CreateAppRequest request)
AmazonSageMakerAsync
Creates a running App for the specified UserProfile. Supported Apps are JupyterServer and KernelGateway. This operation is automatically invoked by Amazon SageMaker Amazon SageMaker Studio (Studio) upon access to the associated Studio Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously. Apps will automatically terminate and be deleted when stopped from within Studio, or when the DeleteApp API is manually called. UserProfiles are limited to 5 concurrently running Apps at a time.
createAppAsync
in interface AmazonSageMakerAsync
public Future<CreateAppResult> createAppAsync(CreateAppRequest request, AsyncHandler<CreateAppRequest,CreateAppResult> asyncHandler)
AmazonSageMakerAsync
Creates a running App for the specified UserProfile. Supported Apps are JupyterServer and KernelGateway. This operation is automatically invoked by Amazon SageMaker Amazon SageMaker Studio (Studio) upon access to the associated Studio Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously. Apps will automatically terminate and be deleted when stopped from within Studio, or when the DeleteApp API is manually called. UserProfiles are limited to 5 concurrently running Apps at a time.
createAppAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateAutoMLJobResult> createAutoMLJobAsync(CreateAutoMLJobRequest request)
AmazonSageMakerAsync
Creates an AutoPilot job.
After you run an AutoPilot job, you can find the best performing model by calling , and then 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 Use AutoPilot to Automate Model Development.
createAutoMLJobAsync
in interface AmazonSageMakerAsync
public Future<CreateAutoMLJobResult> createAutoMLJobAsync(CreateAutoMLJobRequest request, AsyncHandler<CreateAutoMLJobRequest,CreateAutoMLJobResult> asyncHandler)
AmazonSageMakerAsync
Creates an AutoPilot job.
After you run an AutoPilot job, you can find the best performing model by calling , and then 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 Use AutoPilot to Automate Model Development.
createAutoMLJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateCodeRepositoryResult> createCodeRepositoryAsync(CreateCodeRepositoryRequest request)
AmazonSageMakerAsync
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.
createCodeRepositoryAsync
in interface AmazonSageMakerAsync
public Future<CreateCodeRepositoryResult> createCodeRepositoryAsync(CreateCodeRepositoryRequest request, AsyncHandler<CreateCodeRepositoryRequest,CreateCodeRepositoryResult> asyncHandler)
AmazonSageMakerAsync
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.
createCodeRepositoryAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateCompilationJobResult> createCompilationJobAsync(CreateCompilationJobRequest request)
AmazonSageMakerAsync
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.
createCompilationJobAsync
in interface AmazonSageMakerAsync
public Future<CreateCompilationJobResult> createCompilationJobAsync(CreateCompilationJobRequest request, AsyncHandler<CreateCompilationJobRequest,CreateCompilationJobResult> asyncHandler)
AmazonSageMakerAsync
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.
createCompilationJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateDomainResult> createDomainAsync(CreateDomainRequest request)
AmazonSageMakerAsync
Creates a Domain for Amazon SageMaker Amazon SageMaker Studio (Studio), which can be accessed by end-users in a web browser. A Domain has an associated directory, list of authorized users, and a variety of security, application, policies, and Amazon Virtual Private Cloud 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. When a Domain is created, an Amazon Elastic File System (EFS) is also created for use by all of the users within the Domain. Each user receives a private home directory within the EFS for notebooks, Git repositories, and data files.
createDomainAsync
in interface AmazonSageMakerAsync
public Future<CreateDomainResult> createDomainAsync(CreateDomainRequest request, AsyncHandler<CreateDomainRequest,CreateDomainResult> asyncHandler)
AmazonSageMakerAsync
Creates a Domain for Amazon SageMaker Amazon SageMaker Studio (Studio), which can be accessed by end-users in a web browser. A Domain has an associated directory, list of authorized users, and a variety of security, application, policies, and Amazon Virtual Private Cloud 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. When a Domain is created, an Amazon Elastic File System (EFS) is also created for use by all of the users within the Domain. Each user receives a private home directory within the EFS for notebooks, Git repositories, and data files.
createDomainAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateEndpointResult> createEndpointAsync(CreateEndpointRequest request)
AmazonSageMakerAsync
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 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.
createEndpointAsync
in interface AmazonSageMakerAsync
public Future<CreateEndpointResult> createEndpointAsync(CreateEndpointRequest request, AsyncHandler<CreateEndpointRequest,CreateEndpointResult> asyncHandler)
AmazonSageMakerAsync
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 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.
createEndpointAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateEndpointConfigResult> createEndpointConfigAsync(CreateEndpointConfigRequest request)
AmazonSageMakerAsync
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)).
createEndpointConfigAsync
in interface AmazonSageMakerAsync
public Future<CreateEndpointConfigResult> createEndpointConfigAsync(CreateEndpointConfigRequest request, AsyncHandler<CreateEndpointConfigRequest,CreateEndpointConfigResult> asyncHandler)
AmazonSageMakerAsync
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)).
createEndpointConfigAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateExperimentResult> createExperimentAsync(CreateExperimentRequest request)
AmazonSageMakerAsync
Creates an Amazon 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.
createExperimentAsync
in interface AmazonSageMakerAsync
public Future<CreateExperimentResult> createExperimentAsync(CreateExperimentRequest request, AsyncHandler<CreateExperimentRequest,CreateExperimentResult> asyncHandler)
AmazonSageMakerAsync
Creates an Amazon 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.
createExperimentAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateFlowDefinitionResult> createFlowDefinitionAsync(CreateFlowDefinitionRequest request)
AmazonSageMakerAsync
Creates a flow definition.
createFlowDefinitionAsync
in interface AmazonSageMakerAsync
public Future<CreateFlowDefinitionResult> createFlowDefinitionAsync(CreateFlowDefinitionRequest request, AsyncHandler<CreateFlowDefinitionRequest,CreateFlowDefinitionResult> asyncHandler)
AmazonSageMakerAsync
Creates a flow definition.
createFlowDefinitionAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateHumanTaskUiResult> createHumanTaskUiAsync(CreateHumanTaskUiRequest request)
AmazonSageMakerAsync
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.
createHumanTaskUiAsync
in interface AmazonSageMakerAsync
public Future<CreateHumanTaskUiResult> createHumanTaskUiAsync(CreateHumanTaskUiRequest request, AsyncHandler<CreateHumanTaskUiRequest,CreateHumanTaskUiResult> asyncHandler)
AmazonSageMakerAsync
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.
createHumanTaskUiAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateHyperParameterTuningJobResult> createHyperParameterTuningJobAsync(CreateHyperParameterTuningJobRequest request)
AmazonSageMakerAsync
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.
createHyperParameterTuningJobAsync
in interface AmazonSageMakerAsync
public Future<CreateHyperParameterTuningJobResult> createHyperParameterTuningJobAsync(CreateHyperParameterTuningJobRequest request, AsyncHandler<CreateHyperParameterTuningJobRequest,CreateHyperParameterTuningJobResult> asyncHandler)
AmazonSageMakerAsync
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.
createHyperParameterTuningJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateLabelingJobResult> createLabelingJobAsync(CreateLabelingJobRequest request)
AmazonSageMakerAsync
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.
createLabelingJobAsync
in interface AmazonSageMakerAsync
public Future<CreateLabelingJobResult> createLabelingJobAsync(CreateLabelingJobRequest request, AsyncHandler<CreateLabelingJobRequest,CreateLabelingJobResult> asyncHandler)
AmazonSageMakerAsync
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.
createLabelingJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateModelResult> createModelAsync(CreateModelRequest request)
AmazonSageMakerAsync
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.
createModelAsync
in interface AmazonSageMakerAsync
public Future<CreateModelResult> createModelAsync(CreateModelRequest request, AsyncHandler<CreateModelRequest,CreateModelResult> asyncHandler)
AmazonSageMakerAsync
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.
createModelAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateModelPackageResult> createModelPackageAsync(CreateModelPackageRequest request)
AmazonSageMakerAsync
Creates a model package that you can use 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.
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
.
createModelPackageAsync
in interface AmazonSageMakerAsync
public Future<CreateModelPackageResult> createModelPackageAsync(CreateModelPackageRequest request, AsyncHandler<CreateModelPackageRequest,CreateModelPackageResult> asyncHandler)
AmazonSageMakerAsync
Creates a model package that you can use 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.
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
.
createModelPackageAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateMonitoringScheduleResult> createMonitoringScheduleAsync(CreateMonitoringScheduleRequest request)
AmazonSageMakerAsync
Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endoint.
createMonitoringScheduleAsync
in interface AmazonSageMakerAsync
public Future<CreateMonitoringScheduleResult> createMonitoringScheduleAsync(CreateMonitoringScheduleRequest request, AsyncHandler<CreateMonitoringScheduleRequest,CreateMonitoringScheduleResult> asyncHandler)
AmazonSageMakerAsync
Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endoint.
createMonitoringScheduleAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateNotebookInstanceResult> createNotebookInstanceAsync(CreateNotebookInstanceRequest request)
AmazonSageMakerAsync
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.
createNotebookInstanceAsync
in interface AmazonSageMakerAsync
public Future<CreateNotebookInstanceResult> createNotebookInstanceAsync(CreateNotebookInstanceRequest request, AsyncHandler<CreateNotebookInstanceRequest,CreateNotebookInstanceResult> asyncHandler)
AmazonSageMakerAsync
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.
createNotebookInstanceAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateNotebookInstanceLifecycleConfigResult> createNotebookInstanceLifecycleConfigAsync(CreateNotebookInstanceLifecycleConfigRequest request)
AmazonSageMakerAsync
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.
createNotebookInstanceLifecycleConfigAsync
in interface AmazonSageMakerAsync
public Future<CreateNotebookInstanceLifecycleConfigResult> createNotebookInstanceLifecycleConfigAsync(CreateNotebookInstanceLifecycleConfigRequest request, AsyncHandler<CreateNotebookInstanceLifecycleConfigRequest,CreateNotebookInstanceLifecycleConfigResult> asyncHandler)
AmazonSageMakerAsync
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.
createNotebookInstanceLifecycleConfigAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreatePresignedDomainUrlResult> createPresignedDomainUrlAsync(CreatePresignedDomainUrlRequest request)
AmazonSageMakerAsync
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 Amazon SageMaker Studio (Studio), and granted access to all of the Apps and files associated with that Amazon Elastic File System (EFS). This operation can only be called when AuthMode equals IAM.
createPresignedDomainUrlAsync
in interface AmazonSageMakerAsync
public Future<CreatePresignedDomainUrlResult> createPresignedDomainUrlAsync(CreatePresignedDomainUrlRequest request, AsyncHandler<CreatePresignedDomainUrlRequest,CreatePresignedDomainUrlResult> asyncHandler)
AmazonSageMakerAsync
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 Amazon SageMaker Studio (Studio), and granted access to all of the Apps and files associated with that Amazon Elastic File System (EFS). This operation can only be called when AuthMode equals IAM.
createPresignedDomainUrlAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreatePresignedNotebookInstanceUrlResult> createPresignedNotebookInstanceUrlAsync(CreatePresignedNotebookInstanceUrlRequest request)
AmazonSageMakerAsync
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.
IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that
attempts to connect to the notebook instance.For example, 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.
createPresignedNotebookInstanceUrlAsync
in interface AmazonSageMakerAsync
public Future<CreatePresignedNotebookInstanceUrlResult> createPresignedNotebookInstanceUrlAsync(CreatePresignedNotebookInstanceUrlRequest request, AsyncHandler<CreatePresignedNotebookInstanceUrlRequest,CreatePresignedNotebookInstanceUrlResult> asyncHandler)
AmazonSageMakerAsync
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.
IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that
attempts to connect to the notebook instance.For example, 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.
createPresignedNotebookInstanceUrlAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateProcessingJobResult> createProcessingJobAsync(CreateProcessingJobRequest request)
AmazonSageMakerAsync
Creates a processing job.
createProcessingJobAsync
in interface AmazonSageMakerAsync
public Future<CreateProcessingJobResult> createProcessingJobAsync(CreateProcessingJobRequest request, AsyncHandler<CreateProcessingJobRequest,CreateProcessingJobResult> asyncHandler)
AmazonSageMakerAsync
Creates a processing job.
createProcessingJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateTrainingJobResult> createTrainingJobAsync(CreateTrainingJobRequest request)
AmazonSageMakerAsync
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 inferences.
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 Number (ARN) that Amazon SageMaker assumes to perform tasks on your
behalf during model training. You must grant this role the necessary permissions so that Amazon SageMaker can
successfully complete model training.
StoppingCondition
- To help cap training costs, use MaxRuntimeInSeconds
to set a time
limit for training. Use MaxWaitTimeInSeconds
to specify how long you are willing to wait for a
managed spot training job to complete.
For more information about Amazon SageMaker, see How It Works.
createTrainingJobAsync
in interface AmazonSageMakerAsync
public Future<CreateTrainingJobResult> createTrainingJobAsync(CreateTrainingJobRequest request, AsyncHandler<CreateTrainingJobRequest,CreateTrainingJobResult> asyncHandler)
AmazonSageMakerAsync
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 inferences.
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 Number (ARN) that Amazon SageMaker assumes to perform tasks on your
behalf during model training. You must grant this role the necessary permissions so that Amazon SageMaker can
successfully complete model training.
StoppingCondition
- To help cap training costs, use MaxRuntimeInSeconds
to set a time
limit for training. Use MaxWaitTimeInSeconds
to specify how long you are willing to wait for a
managed spot training job to complete.
For more information about Amazon SageMaker, see How It Works.
createTrainingJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateTransformJobResult> createTransformJobAsync(CreateTransformJobRequest request)
AmazonSageMakerAsync
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.
createTransformJobAsync
in interface AmazonSageMakerAsync
public Future<CreateTransformJobResult> createTransformJobAsync(CreateTransformJobRequest request, AsyncHandler<CreateTransformJobRequest,CreateTransformJobResult> asyncHandler)
AmazonSageMakerAsync
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.
createTransformJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateTrialResult> createTrialAsync(CreateTrialRequest request)
AmazonSageMakerAsync
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.
createTrialAsync
in interface AmazonSageMakerAsync
public Future<CreateTrialResult> createTrialAsync(CreateTrialRequest request, AsyncHandler<CreateTrialRequest,CreateTrialResult> asyncHandler)
AmazonSageMakerAsync
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.
createTrialAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateTrialComponentResult> createTrialComponentAsync(CreateTrialComponentRequest request)
AmazonSageMakerAsync
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.
createTrialComponentAsync
in interface AmazonSageMakerAsync
public Future<CreateTrialComponentResult> createTrialComponentAsync(CreateTrialComponentRequest request, AsyncHandler<CreateTrialComponentRequest,CreateTrialComponentResult> asyncHandler)
AmazonSageMakerAsync
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.
createTrialComponentAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateUserProfileResult> createUserProfileAsync(CreateUserProfileRequest request)
AmazonSageMakerAsync
Creates a new 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 during on-boarding. If an administrator invites a person by email or imports them from SSO, a new UserProfile is automatically created. This entity 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.
createUserProfileAsync
in interface AmazonSageMakerAsync
public Future<CreateUserProfileResult> createUserProfileAsync(CreateUserProfileRequest request, AsyncHandler<CreateUserProfileRequest,CreateUserProfileResult> asyncHandler)
AmazonSageMakerAsync
Creates a new 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 during on-boarding. If an administrator invites a person by email or imports them from SSO, a new UserProfile is automatically created. This entity 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.
createUserProfileAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<CreateWorkteamResult> createWorkteamAsync(CreateWorkteamRequest request)
AmazonSageMakerAsync
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.
createWorkteamAsync
in interface AmazonSageMakerAsync
public Future<CreateWorkteamResult> createWorkteamAsync(CreateWorkteamRequest request, AsyncHandler<CreateWorkteamRequest,CreateWorkteamResult> asyncHandler)
AmazonSageMakerAsync
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.
createWorkteamAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteAlgorithmResult> deleteAlgorithmAsync(DeleteAlgorithmRequest request)
AmazonSageMakerAsync
Removes the specified algorithm from your account.
deleteAlgorithmAsync
in interface AmazonSageMakerAsync
public Future<DeleteAlgorithmResult> deleteAlgorithmAsync(DeleteAlgorithmRequest request, AsyncHandler<DeleteAlgorithmRequest,DeleteAlgorithmResult> asyncHandler)
AmazonSageMakerAsync
Removes the specified algorithm from your account.
deleteAlgorithmAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteAppResult> deleteAppAsync(DeleteAppRequest request)
AmazonSageMakerAsync
Used to stop and delete an app.
deleteAppAsync
in interface AmazonSageMakerAsync
public Future<DeleteAppResult> deleteAppAsync(DeleteAppRequest request, AsyncHandler<DeleteAppRequest,DeleteAppResult> asyncHandler)
AmazonSageMakerAsync
Used to stop and delete an app.
deleteAppAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteCodeRepositoryResult> deleteCodeRepositoryAsync(DeleteCodeRepositoryRequest request)
AmazonSageMakerAsync
Deletes the specified Git repository from your account.
deleteCodeRepositoryAsync
in interface AmazonSageMakerAsync
public Future<DeleteCodeRepositoryResult> deleteCodeRepositoryAsync(DeleteCodeRepositoryRequest request, AsyncHandler<DeleteCodeRepositoryRequest,DeleteCodeRepositoryResult> asyncHandler)
AmazonSageMakerAsync
Deletes the specified Git repository from your account.
deleteCodeRepositoryAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteDomainResult> deleteDomainAsync(DeleteDomainRequest request)
AmazonSageMakerAsync
Used to delete a domain. If you on-boarded with IAM mode, you will need to delete your domain to on-board 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.
deleteDomainAsync
in interface AmazonSageMakerAsync
public Future<DeleteDomainResult> deleteDomainAsync(DeleteDomainRequest request, AsyncHandler<DeleteDomainRequest,DeleteDomainResult> asyncHandler)
AmazonSageMakerAsync
Used to delete a domain. If you on-boarded with IAM mode, you will need to delete your domain to on-board 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.
deleteDomainAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteEndpointResult> deleteEndpointAsync(DeleteEndpointRequest request)
AmazonSageMakerAsync
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.
deleteEndpointAsync
in interface AmazonSageMakerAsync
public Future<DeleteEndpointResult> deleteEndpointAsync(DeleteEndpointRequest request, AsyncHandler<DeleteEndpointRequest,DeleteEndpointResult> asyncHandler)
AmazonSageMakerAsync
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.
deleteEndpointAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteEndpointConfigResult> deleteEndpointConfigAsync(DeleteEndpointConfigRequest request)
AmazonSageMakerAsync
Deletes an endpoint configuration. The DeleteEndpointConfig
API deletes only the specified
configuration. It does not delete endpoints created using the configuration.
deleteEndpointConfigAsync
in interface AmazonSageMakerAsync
public Future<DeleteEndpointConfigResult> deleteEndpointConfigAsync(DeleteEndpointConfigRequest request, AsyncHandler<DeleteEndpointConfigRequest,DeleteEndpointConfigResult> asyncHandler)
AmazonSageMakerAsync
Deletes an endpoint configuration. The DeleteEndpointConfig
API deletes only the specified
configuration. It does not delete endpoints created using the configuration.
deleteEndpointConfigAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteExperimentResult> deleteExperimentAsync(DeleteExperimentRequest request)
AmazonSageMakerAsync
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.
deleteExperimentAsync
in interface AmazonSageMakerAsync
public Future<DeleteExperimentResult> deleteExperimentAsync(DeleteExperimentRequest request, AsyncHandler<DeleteExperimentRequest,DeleteExperimentResult> asyncHandler)
AmazonSageMakerAsync
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.
deleteExperimentAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteFlowDefinitionResult> deleteFlowDefinitionAsync(DeleteFlowDefinitionRequest request)
AmazonSageMakerAsync
Deletes the specified flow definition.
deleteFlowDefinitionAsync
in interface AmazonSageMakerAsync
public Future<DeleteFlowDefinitionResult> deleteFlowDefinitionAsync(DeleteFlowDefinitionRequest request, AsyncHandler<DeleteFlowDefinitionRequest,DeleteFlowDefinitionResult> asyncHandler)
AmazonSageMakerAsync
Deletes the specified flow definition.
deleteFlowDefinitionAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteModelResult> deleteModelAsync(DeleteModelRequest request)
AmazonSageMakerAsync
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.
deleteModelAsync
in interface AmazonSageMakerAsync
public Future<DeleteModelResult> deleteModelAsync(DeleteModelRequest request, AsyncHandler<DeleteModelRequest,DeleteModelResult> asyncHandler)
AmazonSageMakerAsync
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.
deleteModelAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteModelPackageResult> deleteModelPackageAsync(DeleteModelPackageRequest request)
AmazonSageMakerAsync
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.
deleteModelPackageAsync
in interface AmazonSageMakerAsync
public Future<DeleteModelPackageResult> deleteModelPackageAsync(DeleteModelPackageRequest request, AsyncHandler<DeleteModelPackageRequest,DeleteModelPackageResult> asyncHandler)
AmazonSageMakerAsync
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.
deleteModelPackageAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteMonitoringScheduleResult> deleteMonitoringScheduleAsync(DeleteMonitoringScheduleRequest request)
AmazonSageMakerAsync
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.
deleteMonitoringScheduleAsync
in interface AmazonSageMakerAsync
public Future<DeleteMonitoringScheduleResult> deleteMonitoringScheduleAsync(DeleteMonitoringScheduleRequest request, AsyncHandler<DeleteMonitoringScheduleRequest,DeleteMonitoringScheduleResult> asyncHandler)
AmazonSageMakerAsync
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.
deleteMonitoringScheduleAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteNotebookInstanceResult> deleteNotebookInstanceAsync(DeleteNotebookInstanceRequest request)
AmazonSageMakerAsync
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.
deleteNotebookInstanceAsync
in interface AmazonSageMakerAsync
public Future<DeleteNotebookInstanceResult> deleteNotebookInstanceAsync(DeleteNotebookInstanceRequest request, AsyncHandler<DeleteNotebookInstanceRequest,DeleteNotebookInstanceResult> asyncHandler)
AmazonSageMakerAsync
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.
deleteNotebookInstanceAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteNotebookInstanceLifecycleConfigResult> deleteNotebookInstanceLifecycleConfigAsync(DeleteNotebookInstanceLifecycleConfigRequest request)
AmazonSageMakerAsync
Deletes a notebook instance lifecycle configuration.
deleteNotebookInstanceLifecycleConfigAsync
in interface AmazonSageMakerAsync
public Future<DeleteNotebookInstanceLifecycleConfigResult> deleteNotebookInstanceLifecycleConfigAsync(DeleteNotebookInstanceLifecycleConfigRequest request, AsyncHandler<DeleteNotebookInstanceLifecycleConfigRequest,DeleteNotebookInstanceLifecycleConfigResult> asyncHandler)
AmazonSageMakerAsync
Deletes a notebook instance lifecycle configuration.
deleteNotebookInstanceLifecycleConfigAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteTagsResult> deleteTagsAsync(DeleteTagsRequest request)
AmazonSageMakerAsync
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.
deleteTagsAsync
in interface AmazonSageMakerAsync
public Future<DeleteTagsResult> deleteTagsAsync(DeleteTagsRequest request, AsyncHandler<DeleteTagsRequest,DeleteTagsResult> asyncHandler)
AmazonSageMakerAsync
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.
deleteTagsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteTrialResult> deleteTrialAsync(DeleteTrialRequest request)
AmazonSageMakerAsync
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.
deleteTrialAsync
in interface AmazonSageMakerAsync
public Future<DeleteTrialResult> deleteTrialAsync(DeleteTrialRequest request, AsyncHandler<DeleteTrialRequest,DeleteTrialResult> asyncHandler)
AmazonSageMakerAsync
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.
deleteTrialAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteTrialComponentResult> deleteTrialComponentAsync(DeleteTrialComponentRequest request)
AmazonSageMakerAsync
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.
deleteTrialComponentAsync
in interface AmazonSageMakerAsync
public Future<DeleteTrialComponentResult> deleteTrialComponentAsync(DeleteTrialComponentRequest request, AsyncHandler<DeleteTrialComponentRequest,DeleteTrialComponentResult> asyncHandler)
AmazonSageMakerAsync
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.
deleteTrialComponentAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteUserProfileResult> deleteUserProfileAsync(DeleteUserProfileRequest request)
AmazonSageMakerAsync
Deletes a user profile.
deleteUserProfileAsync
in interface AmazonSageMakerAsync
public Future<DeleteUserProfileResult> deleteUserProfileAsync(DeleteUserProfileRequest request, AsyncHandler<DeleteUserProfileRequest,DeleteUserProfileResult> asyncHandler)
AmazonSageMakerAsync
Deletes a user profile.
deleteUserProfileAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DeleteWorkteamResult> deleteWorkteamAsync(DeleteWorkteamRequest request)
AmazonSageMakerAsync
Deletes an existing work team. This operation can't be undone.
deleteWorkteamAsync
in interface AmazonSageMakerAsync
public Future<DeleteWorkteamResult> deleteWorkteamAsync(DeleteWorkteamRequest request, AsyncHandler<DeleteWorkteamRequest,DeleteWorkteamResult> asyncHandler)
AmazonSageMakerAsync
Deletes an existing work team. This operation can't be undone.
deleteWorkteamAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeAlgorithmResult> describeAlgorithmAsync(DescribeAlgorithmRequest request)
AmazonSageMakerAsync
Returns a description of the specified algorithm that is in your account.
describeAlgorithmAsync
in interface AmazonSageMakerAsync
public Future<DescribeAlgorithmResult> describeAlgorithmAsync(DescribeAlgorithmRequest request, AsyncHandler<DescribeAlgorithmRequest,DescribeAlgorithmResult> asyncHandler)
AmazonSageMakerAsync
Returns a description of the specified algorithm that is in your account.
describeAlgorithmAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeAppResult> describeAppAsync(DescribeAppRequest request)
AmazonSageMakerAsync
Describes the app.
describeAppAsync
in interface AmazonSageMakerAsync
public Future<DescribeAppResult> describeAppAsync(DescribeAppRequest request, AsyncHandler<DescribeAppRequest,DescribeAppResult> asyncHandler)
AmazonSageMakerAsync
Describes the app.
describeAppAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeAutoMLJobResult> describeAutoMLJobAsync(DescribeAutoMLJobRequest request)
AmazonSageMakerAsync
Returns information about an Amazon SageMaker job.
describeAutoMLJobAsync
in interface AmazonSageMakerAsync
public Future<DescribeAutoMLJobResult> describeAutoMLJobAsync(DescribeAutoMLJobRequest request, AsyncHandler<DescribeAutoMLJobRequest,DescribeAutoMLJobResult> asyncHandler)
AmazonSageMakerAsync
Returns information about an Amazon SageMaker job.
describeAutoMLJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeCodeRepositoryResult> describeCodeRepositoryAsync(DescribeCodeRepositoryRequest request)
AmazonSageMakerAsync
Gets details about the specified Git repository.
describeCodeRepositoryAsync
in interface AmazonSageMakerAsync
public Future<DescribeCodeRepositoryResult> describeCodeRepositoryAsync(DescribeCodeRepositoryRequest request, AsyncHandler<DescribeCodeRepositoryRequest,DescribeCodeRepositoryResult> asyncHandler)
AmazonSageMakerAsync
Gets details about the specified Git repository.
describeCodeRepositoryAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeCompilationJobResult> describeCompilationJobAsync(DescribeCompilationJobRequest request)
AmazonSageMakerAsync
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.
describeCompilationJobAsync
in interface AmazonSageMakerAsync
public Future<DescribeCompilationJobResult> describeCompilationJobAsync(DescribeCompilationJobRequest request, AsyncHandler<DescribeCompilationJobRequest,DescribeCompilationJobResult> asyncHandler)
AmazonSageMakerAsync
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.
describeCompilationJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeDomainResult> describeDomainAsync(DescribeDomainRequest request)
AmazonSageMakerAsync
The desciption of the domain.
describeDomainAsync
in interface AmazonSageMakerAsync
public Future<DescribeDomainResult> describeDomainAsync(DescribeDomainRequest request, AsyncHandler<DescribeDomainRequest,DescribeDomainResult> asyncHandler)
AmazonSageMakerAsync
The desciption of the domain.
describeDomainAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeEndpointResult> describeEndpointAsync(DescribeEndpointRequest request)
AmazonSageMakerAsync
Returns the description of an endpoint.
describeEndpointAsync
in interface AmazonSageMakerAsync
public Future<DescribeEndpointResult> describeEndpointAsync(DescribeEndpointRequest request, AsyncHandler<DescribeEndpointRequest,DescribeEndpointResult> asyncHandler)
AmazonSageMakerAsync
Returns the description of an endpoint.
describeEndpointAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeEndpointConfigResult> describeEndpointConfigAsync(DescribeEndpointConfigRequest request)
AmazonSageMakerAsync
Returns the description of an endpoint configuration created using the CreateEndpointConfig
API.
describeEndpointConfigAsync
in interface AmazonSageMakerAsync
public Future<DescribeEndpointConfigResult> describeEndpointConfigAsync(DescribeEndpointConfigRequest request, AsyncHandler<DescribeEndpointConfigRequest,DescribeEndpointConfigResult> asyncHandler)
AmazonSageMakerAsync
Returns the description of an endpoint configuration created using the CreateEndpointConfig
API.
describeEndpointConfigAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeExperimentResult> describeExperimentAsync(DescribeExperimentRequest request)
AmazonSageMakerAsync
Provides a list of an experiment's properties.
describeExperimentAsync
in interface AmazonSageMakerAsync
public Future<DescribeExperimentResult> describeExperimentAsync(DescribeExperimentRequest request, AsyncHandler<DescribeExperimentRequest,DescribeExperimentResult> asyncHandler)
AmazonSageMakerAsync
Provides a list of an experiment's properties.
describeExperimentAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeFlowDefinitionResult> describeFlowDefinitionAsync(DescribeFlowDefinitionRequest request)
AmazonSageMakerAsync
Returns information about the specified flow definition.
describeFlowDefinitionAsync
in interface AmazonSageMakerAsync
public Future<DescribeFlowDefinitionResult> describeFlowDefinitionAsync(DescribeFlowDefinitionRequest request, AsyncHandler<DescribeFlowDefinitionRequest,DescribeFlowDefinitionResult> asyncHandler)
AmazonSageMakerAsync
Returns information about the specified flow definition.
describeFlowDefinitionAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeHumanTaskUiResult> describeHumanTaskUiAsync(DescribeHumanTaskUiRequest request)
AmazonSageMakerAsync
Returns information about the requested human task user interface.
describeHumanTaskUiAsync
in interface AmazonSageMakerAsync
public Future<DescribeHumanTaskUiResult> describeHumanTaskUiAsync(DescribeHumanTaskUiRequest request, AsyncHandler<DescribeHumanTaskUiRequest,DescribeHumanTaskUiResult> asyncHandler)
AmazonSageMakerAsync
Returns information about the requested human task user interface.
describeHumanTaskUiAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeHyperParameterTuningJobResult> describeHyperParameterTuningJobAsync(DescribeHyperParameterTuningJobRequest request)
AmazonSageMakerAsync
Gets a description of a hyperparameter tuning job.
describeHyperParameterTuningJobAsync
in interface AmazonSageMakerAsync
public Future<DescribeHyperParameterTuningJobResult> describeHyperParameterTuningJobAsync(DescribeHyperParameterTuningJobRequest request, AsyncHandler<DescribeHyperParameterTuningJobRequest,DescribeHyperParameterTuningJobResult> asyncHandler)
AmazonSageMakerAsync
Gets a description of a hyperparameter tuning job.
describeHyperParameterTuningJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeLabelingJobResult> describeLabelingJobAsync(DescribeLabelingJobRequest request)
AmazonSageMakerAsync
Gets information about a labeling job.
describeLabelingJobAsync
in interface AmazonSageMakerAsync
public Future<DescribeLabelingJobResult> describeLabelingJobAsync(DescribeLabelingJobRequest request, AsyncHandler<DescribeLabelingJobRequest,DescribeLabelingJobResult> asyncHandler)
AmazonSageMakerAsync
Gets information about a labeling job.
describeLabelingJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeModelResult> describeModelAsync(DescribeModelRequest request)
AmazonSageMakerAsync
Describes a model that you created using the CreateModel
API.
describeModelAsync
in interface AmazonSageMakerAsync
public Future<DescribeModelResult> describeModelAsync(DescribeModelRequest request, AsyncHandler<DescribeModelRequest,DescribeModelResult> asyncHandler)
AmazonSageMakerAsync
Describes a model that you created using the CreateModel
API.
describeModelAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeModelPackageResult> describeModelPackageAsync(DescribeModelPackageRequest request)
AmazonSageMakerAsync
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.
describeModelPackageAsync
in interface AmazonSageMakerAsync
public Future<DescribeModelPackageResult> describeModelPackageAsync(DescribeModelPackageRequest request, AsyncHandler<DescribeModelPackageRequest,DescribeModelPackageResult> asyncHandler)
AmazonSageMakerAsync
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.
describeModelPackageAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeMonitoringScheduleResult> describeMonitoringScheduleAsync(DescribeMonitoringScheduleRequest request)
AmazonSageMakerAsync
Describes the schedule for a monitoring job.
describeMonitoringScheduleAsync
in interface AmazonSageMakerAsync
public Future<DescribeMonitoringScheduleResult> describeMonitoringScheduleAsync(DescribeMonitoringScheduleRequest request, AsyncHandler<DescribeMonitoringScheduleRequest,DescribeMonitoringScheduleResult> asyncHandler)
AmazonSageMakerAsync
Describes the schedule for a monitoring job.
describeMonitoringScheduleAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeNotebookInstanceResult> describeNotebookInstanceAsync(DescribeNotebookInstanceRequest request)
AmazonSageMakerAsync
Returns information about a notebook instance.
describeNotebookInstanceAsync
in interface AmazonSageMakerAsync
public Future<DescribeNotebookInstanceResult> describeNotebookInstanceAsync(DescribeNotebookInstanceRequest request, AsyncHandler<DescribeNotebookInstanceRequest,DescribeNotebookInstanceResult> asyncHandler)
AmazonSageMakerAsync
Returns information about a notebook instance.
describeNotebookInstanceAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeNotebookInstanceLifecycleConfigResult> describeNotebookInstanceLifecycleConfigAsync(DescribeNotebookInstanceLifecycleConfigRequest request)
AmazonSageMakerAsync
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.
describeNotebookInstanceLifecycleConfigAsync
in interface AmazonSageMakerAsync
public Future<DescribeNotebookInstanceLifecycleConfigResult> describeNotebookInstanceLifecycleConfigAsync(DescribeNotebookInstanceLifecycleConfigRequest request, AsyncHandler<DescribeNotebookInstanceLifecycleConfigRequest,DescribeNotebookInstanceLifecycleConfigResult> asyncHandler)
AmazonSageMakerAsync
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.
describeNotebookInstanceLifecycleConfigAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeProcessingJobResult> describeProcessingJobAsync(DescribeProcessingJobRequest request)
AmazonSageMakerAsync
Returns a description of a processing job.
describeProcessingJobAsync
in interface AmazonSageMakerAsync
public Future<DescribeProcessingJobResult> describeProcessingJobAsync(DescribeProcessingJobRequest request, AsyncHandler<DescribeProcessingJobRequest,DescribeProcessingJobResult> asyncHandler)
AmazonSageMakerAsync
Returns a description of a processing job.
describeProcessingJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeSubscribedWorkteamResult> describeSubscribedWorkteamAsync(DescribeSubscribedWorkteamRequest request)
AmazonSageMakerAsync
Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the AWS Marketplace.
describeSubscribedWorkteamAsync
in interface AmazonSageMakerAsync
public Future<DescribeSubscribedWorkteamResult> describeSubscribedWorkteamAsync(DescribeSubscribedWorkteamRequest request, AsyncHandler<DescribeSubscribedWorkteamRequest,DescribeSubscribedWorkteamResult> asyncHandler)
AmazonSageMakerAsync
Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the AWS Marketplace.
describeSubscribedWorkteamAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeTrainingJobResult> describeTrainingJobAsync(DescribeTrainingJobRequest request)
AmazonSageMakerAsync
Returns information about a training job.
describeTrainingJobAsync
in interface AmazonSageMakerAsync
public Future<DescribeTrainingJobResult> describeTrainingJobAsync(DescribeTrainingJobRequest request, AsyncHandler<DescribeTrainingJobRequest,DescribeTrainingJobResult> asyncHandler)
AmazonSageMakerAsync
Returns information about a training job.
describeTrainingJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeTransformJobResult> describeTransformJobAsync(DescribeTransformJobRequest request)
AmazonSageMakerAsync
Returns information about a transform job.
describeTransformJobAsync
in interface AmazonSageMakerAsync
public Future<DescribeTransformJobResult> describeTransformJobAsync(DescribeTransformJobRequest request, AsyncHandler<DescribeTransformJobRequest,DescribeTransformJobResult> asyncHandler)
AmazonSageMakerAsync
Returns information about a transform job.
describeTransformJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeTrialResult> describeTrialAsync(DescribeTrialRequest request)
AmazonSageMakerAsync
Provides a list of a trial's properties.
describeTrialAsync
in interface AmazonSageMakerAsync
public Future<DescribeTrialResult> describeTrialAsync(DescribeTrialRequest request, AsyncHandler<DescribeTrialRequest,DescribeTrialResult> asyncHandler)
AmazonSageMakerAsync
Provides a list of a trial's properties.
describeTrialAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeTrialComponentResult> describeTrialComponentAsync(DescribeTrialComponentRequest request)
AmazonSageMakerAsync
Provides a list of a trials component's properties.
describeTrialComponentAsync
in interface AmazonSageMakerAsync
public Future<DescribeTrialComponentResult> describeTrialComponentAsync(DescribeTrialComponentRequest request, AsyncHandler<DescribeTrialComponentRequest,DescribeTrialComponentResult> asyncHandler)
AmazonSageMakerAsync
Provides a list of a trials component's properties.
describeTrialComponentAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeUserProfileResult> describeUserProfileAsync(DescribeUserProfileRequest request)
AmazonSageMakerAsync
Describes the user profile.
describeUserProfileAsync
in interface AmazonSageMakerAsync
public Future<DescribeUserProfileResult> describeUserProfileAsync(DescribeUserProfileRequest request, AsyncHandler<DescribeUserProfileRequest,DescribeUserProfileResult> asyncHandler)
AmazonSageMakerAsync
Describes the user profile.
describeUserProfileAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeWorkforceResult> describeWorkforceAsync(DescribeWorkforceRequest request)
AmazonSageMakerAsync
Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs). Allowable IP address ranges are the IP addresses that workers can use to access tasks.
This operation applies only to private workforces.
describeWorkforceAsync
in interface AmazonSageMakerAsync
public Future<DescribeWorkforceResult> describeWorkforceAsync(DescribeWorkforceRequest request, AsyncHandler<DescribeWorkforceRequest,DescribeWorkforceResult> asyncHandler)
AmazonSageMakerAsync
Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs). Allowable IP address ranges are the IP addresses that workers can use to access tasks.
This operation applies only to private workforces.
describeWorkforceAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DescribeWorkteamResult> describeWorkteamAsync(DescribeWorkteamRequest request)
AmazonSageMakerAsync
Gets information about a specific work team. You can see information such as the create date, the last updated date, membership information, and the work team's Amazon Resource Name (ARN).
describeWorkteamAsync
in interface AmazonSageMakerAsync
public Future<DescribeWorkteamResult> describeWorkteamAsync(DescribeWorkteamRequest request, AsyncHandler<DescribeWorkteamRequest,DescribeWorkteamResult> asyncHandler)
AmazonSageMakerAsync
Gets information about a specific work team. You can see information such as the create date, the last updated date, membership information, and the work team's Amazon Resource Name (ARN).
describeWorkteamAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<DisassociateTrialComponentResult> disassociateTrialComponentAsync(DisassociateTrialComponentRequest request)
AmazonSageMakerAsync
Disassociates a trial component from a trial. This doesn't effect other trials the component is associated with. Before you can delete a component, you must disassociate the component from all trials it is associated with. To associate a trial component with a trial, call the AssociateTrialComponent API.
To get a list of the trials a component is associated with, use the Search API. Specify
ExperimentTrialComponent
for the Resource
parameter. The list appears in the response
under Results.TrialComponent.Parents
.
disassociateTrialComponentAsync
in interface AmazonSageMakerAsync
public Future<DisassociateTrialComponentResult> disassociateTrialComponentAsync(DisassociateTrialComponentRequest request, AsyncHandler<DisassociateTrialComponentRequest,DisassociateTrialComponentResult> asyncHandler)
AmazonSageMakerAsync
Disassociates a trial component from a trial. This doesn't effect other trials the component is associated with. Before you can delete a component, you must disassociate the component from all trials it is associated with. To associate a trial component with a trial, call the AssociateTrialComponent API.
To get a list of the trials a component is associated with, use the Search API. Specify
ExperimentTrialComponent
for the Resource
parameter. The list appears in the response
under Results.TrialComponent.Parents
.
disassociateTrialComponentAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<GetSearchSuggestionsResult> getSearchSuggestionsAsync(GetSearchSuggestionsRequest request)
AmazonSageMakerAsync
An auto-complete API for the search functionality in the Amazon SageMaker console. It returns suggestions of
possible matches for the property name to use in Search
queries. Provides suggestions for
HyperParameters
, Tags
, and Metrics
.
getSearchSuggestionsAsync
in interface AmazonSageMakerAsync
public Future<GetSearchSuggestionsResult> getSearchSuggestionsAsync(GetSearchSuggestionsRequest request, AsyncHandler<GetSearchSuggestionsRequest,GetSearchSuggestionsResult> asyncHandler)
AmazonSageMakerAsync
An auto-complete API for the search functionality in the Amazon SageMaker console. It returns suggestions of
possible matches for the property name to use in Search
queries. Provides suggestions for
HyperParameters
, Tags
, and Metrics
.
getSearchSuggestionsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListAlgorithmsResult> listAlgorithmsAsync(ListAlgorithmsRequest request)
AmazonSageMakerAsync
Lists the machine learning algorithms that have been created.
listAlgorithmsAsync
in interface AmazonSageMakerAsync
public Future<ListAlgorithmsResult> listAlgorithmsAsync(ListAlgorithmsRequest request, AsyncHandler<ListAlgorithmsRequest,ListAlgorithmsResult> asyncHandler)
AmazonSageMakerAsync
Lists the machine learning algorithms that have been created.
listAlgorithmsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListAppsResult> listAppsAsync(ListAppsRequest request)
AmazonSageMakerAsync
Lists apps.
listAppsAsync
in interface AmazonSageMakerAsync
public Future<ListAppsResult> listAppsAsync(ListAppsRequest request, AsyncHandler<ListAppsRequest,ListAppsResult> asyncHandler)
AmazonSageMakerAsync
Lists apps.
listAppsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListAutoMLJobsResult> listAutoMLJobsAsync(ListAutoMLJobsRequest request)
AmazonSageMakerAsync
Request a list of jobs.
listAutoMLJobsAsync
in interface AmazonSageMakerAsync
public Future<ListAutoMLJobsResult> listAutoMLJobsAsync(ListAutoMLJobsRequest request, AsyncHandler<ListAutoMLJobsRequest,ListAutoMLJobsResult> asyncHandler)
AmazonSageMakerAsync
Request a list of jobs.
listAutoMLJobsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListCandidatesForAutoMLJobResult> listCandidatesForAutoMLJobAsync(ListCandidatesForAutoMLJobRequest request)
AmazonSageMakerAsync
List the Candidates created for the job.
listCandidatesForAutoMLJobAsync
in interface AmazonSageMakerAsync
public Future<ListCandidatesForAutoMLJobResult> listCandidatesForAutoMLJobAsync(ListCandidatesForAutoMLJobRequest request, AsyncHandler<ListCandidatesForAutoMLJobRequest,ListCandidatesForAutoMLJobResult> asyncHandler)
AmazonSageMakerAsync
List the Candidates created for the job.
listCandidatesForAutoMLJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListCodeRepositoriesResult> listCodeRepositoriesAsync(ListCodeRepositoriesRequest request)
AmazonSageMakerAsync
Gets a list of the Git repositories in your account.
listCodeRepositoriesAsync
in interface AmazonSageMakerAsync
public Future<ListCodeRepositoriesResult> listCodeRepositoriesAsync(ListCodeRepositoriesRequest request, AsyncHandler<ListCodeRepositoriesRequest,ListCodeRepositoriesResult> asyncHandler)
AmazonSageMakerAsync
Gets a list of the Git repositories in your account.
listCodeRepositoriesAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListCompilationJobsResult> listCompilationJobsAsync(ListCompilationJobsRequest request)
AmazonSageMakerAsync
Lists model compilation jobs that satisfy various filters.
To create a model compilation job, use CreateCompilationJob. To get information about a particular model compilation job you have created, use DescribeCompilationJob.
listCompilationJobsAsync
in interface AmazonSageMakerAsync
public Future<ListCompilationJobsResult> listCompilationJobsAsync(ListCompilationJobsRequest request, AsyncHandler<ListCompilationJobsRequest,ListCompilationJobsResult> asyncHandler)
AmazonSageMakerAsync
Lists model compilation jobs that satisfy various filters.
To create a model compilation job, use CreateCompilationJob. To get information about a particular model compilation job you have created, use DescribeCompilationJob.
listCompilationJobsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListDomainsResult> listDomainsAsync(ListDomainsRequest request)
AmazonSageMakerAsync
Lists the domains.
listDomainsAsync
in interface AmazonSageMakerAsync
public Future<ListDomainsResult> listDomainsAsync(ListDomainsRequest request, AsyncHandler<ListDomainsRequest,ListDomainsResult> asyncHandler)
AmazonSageMakerAsync
Lists the domains.
listDomainsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListEndpointConfigsResult> listEndpointConfigsAsync(ListEndpointConfigsRequest request)
AmazonSageMakerAsync
Lists endpoint configurations.
listEndpointConfigsAsync
in interface AmazonSageMakerAsync
public Future<ListEndpointConfigsResult> listEndpointConfigsAsync(ListEndpointConfigsRequest request, AsyncHandler<ListEndpointConfigsRequest,ListEndpointConfigsResult> asyncHandler)
AmazonSageMakerAsync
Lists endpoint configurations.
listEndpointConfigsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListEndpointsResult> listEndpointsAsync(ListEndpointsRequest request)
AmazonSageMakerAsync
Lists endpoints.
listEndpointsAsync
in interface AmazonSageMakerAsync
public Future<ListEndpointsResult> listEndpointsAsync(ListEndpointsRequest request, AsyncHandler<ListEndpointsRequest,ListEndpointsResult> asyncHandler)
AmazonSageMakerAsync
Lists endpoints.
listEndpointsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListExperimentsResult> listExperimentsAsync(ListExperimentsRequest request)
AmazonSageMakerAsync
Lists all the experiments in your account. The list can be filtered to show only experiments that were created in a specific time range. The list can be sorted by experiment name or creation time.
listExperimentsAsync
in interface AmazonSageMakerAsync
public Future<ListExperimentsResult> listExperimentsAsync(ListExperimentsRequest request, AsyncHandler<ListExperimentsRequest,ListExperimentsResult> asyncHandler)
AmazonSageMakerAsync
Lists all the experiments in your account. The list can be filtered to show only experiments that were created in a specific time range. The list can be sorted by experiment name or creation time.
listExperimentsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListFlowDefinitionsResult> listFlowDefinitionsAsync(ListFlowDefinitionsRequest request)
AmazonSageMakerAsync
Returns information about the flow definitions in your account.
listFlowDefinitionsAsync
in interface AmazonSageMakerAsync
public Future<ListFlowDefinitionsResult> listFlowDefinitionsAsync(ListFlowDefinitionsRequest request, AsyncHandler<ListFlowDefinitionsRequest,ListFlowDefinitionsResult> asyncHandler)
AmazonSageMakerAsync
Returns information about the flow definitions in your account.
listFlowDefinitionsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListHumanTaskUisResult> listHumanTaskUisAsync(ListHumanTaskUisRequest request)
AmazonSageMakerAsync
Returns information about the human task user interfaces in your account.
listHumanTaskUisAsync
in interface AmazonSageMakerAsync
public Future<ListHumanTaskUisResult> listHumanTaskUisAsync(ListHumanTaskUisRequest request, AsyncHandler<ListHumanTaskUisRequest,ListHumanTaskUisResult> asyncHandler)
AmazonSageMakerAsync
Returns information about the human task user interfaces in your account.
listHumanTaskUisAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListHyperParameterTuningJobsResult> listHyperParameterTuningJobsAsync(ListHyperParameterTuningJobsRequest request)
AmazonSageMakerAsync
Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.
listHyperParameterTuningJobsAsync
in interface AmazonSageMakerAsync
public Future<ListHyperParameterTuningJobsResult> listHyperParameterTuningJobsAsync(ListHyperParameterTuningJobsRequest request, AsyncHandler<ListHyperParameterTuningJobsRequest,ListHyperParameterTuningJobsResult> asyncHandler)
AmazonSageMakerAsync
Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.
listHyperParameterTuningJobsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListLabelingJobsResult> listLabelingJobsAsync(ListLabelingJobsRequest request)
AmazonSageMakerAsync
Gets a list of labeling jobs.
listLabelingJobsAsync
in interface AmazonSageMakerAsync
public Future<ListLabelingJobsResult> listLabelingJobsAsync(ListLabelingJobsRequest request, AsyncHandler<ListLabelingJobsRequest,ListLabelingJobsResult> asyncHandler)
AmazonSageMakerAsync
Gets a list of labeling jobs.
listLabelingJobsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListLabelingJobsForWorkteamResult> listLabelingJobsForWorkteamAsync(ListLabelingJobsForWorkteamRequest request)
AmazonSageMakerAsync
Gets a list of labeling jobs assigned to a specified work team.
listLabelingJobsForWorkteamAsync
in interface AmazonSageMakerAsync
public Future<ListLabelingJobsForWorkteamResult> listLabelingJobsForWorkteamAsync(ListLabelingJobsForWorkteamRequest request, AsyncHandler<ListLabelingJobsForWorkteamRequest,ListLabelingJobsForWorkteamResult> asyncHandler)
AmazonSageMakerAsync
Gets a list of labeling jobs assigned to a specified work team.
listLabelingJobsForWorkteamAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListModelPackagesResult> listModelPackagesAsync(ListModelPackagesRequest request)
AmazonSageMakerAsync
Lists the model packages that have been created.
listModelPackagesAsync
in interface AmazonSageMakerAsync
public Future<ListModelPackagesResult> listModelPackagesAsync(ListModelPackagesRequest request, AsyncHandler<ListModelPackagesRequest,ListModelPackagesResult> asyncHandler)
AmazonSageMakerAsync
Lists the model packages that have been created.
listModelPackagesAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListModelsResult> listModelsAsync(ListModelsRequest request)
AmazonSageMakerAsync
Lists models created with the CreateModel API.
listModelsAsync
in interface AmazonSageMakerAsync
public Future<ListModelsResult> listModelsAsync(ListModelsRequest request, AsyncHandler<ListModelsRequest,ListModelsResult> asyncHandler)
AmazonSageMakerAsync
Lists models created with the CreateModel API.
listModelsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListMonitoringExecutionsResult> listMonitoringExecutionsAsync(ListMonitoringExecutionsRequest request)
AmazonSageMakerAsync
Returns list of all monitoring job executions.
listMonitoringExecutionsAsync
in interface AmazonSageMakerAsync
public Future<ListMonitoringExecutionsResult> listMonitoringExecutionsAsync(ListMonitoringExecutionsRequest request, AsyncHandler<ListMonitoringExecutionsRequest,ListMonitoringExecutionsResult> asyncHandler)
AmazonSageMakerAsync
Returns list of all monitoring job executions.
listMonitoringExecutionsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListMonitoringSchedulesResult> listMonitoringSchedulesAsync(ListMonitoringSchedulesRequest request)
AmazonSageMakerAsync
Returns list of all monitoring schedules.
listMonitoringSchedulesAsync
in interface AmazonSageMakerAsync
public Future<ListMonitoringSchedulesResult> listMonitoringSchedulesAsync(ListMonitoringSchedulesRequest request, AsyncHandler<ListMonitoringSchedulesRequest,ListMonitoringSchedulesResult> asyncHandler)
AmazonSageMakerAsync
Returns list of all monitoring schedules.
listMonitoringSchedulesAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListNotebookInstanceLifecycleConfigsResult> listNotebookInstanceLifecycleConfigsAsync(ListNotebookInstanceLifecycleConfigsRequest request)
AmazonSageMakerAsync
Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API.
listNotebookInstanceLifecycleConfigsAsync
in interface AmazonSageMakerAsync
public Future<ListNotebookInstanceLifecycleConfigsResult> listNotebookInstanceLifecycleConfigsAsync(ListNotebookInstanceLifecycleConfigsRequest request, AsyncHandler<ListNotebookInstanceLifecycleConfigsRequest,ListNotebookInstanceLifecycleConfigsResult> asyncHandler)
AmazonSageMakerAsync
Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API.
listNotebookInstanceLifecycleConfigsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListNotebookInstancesResult> listNotebookInstancesAsync(ListNotebookInstancesRequest request)
AmazonSageMakerAsync
Returns a list of the Amazon SageMaker notebook instances in the requester's account in an AWS Region.
listNotebookInstancesAsync
in interface AmazonSageMakerAsync
public Future<ListNotebookInstancesResult> listNotebookInstancesAsync(ListNotebookInstancesRequest request, AsyncHandler<ListNotebookInstancesRequest,ListNotebookInstancesResult> asyncHandler)
AmazonSageMakerAsync
Returns a list of the Amazon SageMaker notebook instances in the requester's account in an AWS Region.
listNotebookInstancesAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListProcessingJobsResult> listProcessingJobsAsync(ListProcessingJobsRequest request)
AmazonSageMakerAsync
Lists processing jobs that satisfy various filters.
listProcessingJobsAsync
in interface AmazonSageMakerAsync
public Future<ListProcessingJobsResult> listProcessingJobsAsync(ListProcessingJobsRequest request, AsyncHandler<ListProcessingJobsRequest,ListProcessingJobsResult> asyncHandler)
AmazonSageMakerAsync
Lists processing jobs that satisfy various filters.
listProcessingJobsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListSubscribedWorkteamsResult> listSubscribedWorkteamsAsync(ListSubscribedWorkteamsRequest request)
AmazonSageMakerAsync
Gets a list of the work teams that you are subscribed to in the AWS Marketplace. The list may be empty if no work
team satisfies the filter specified in the NameContains
parameter.
listSubscribedWorkteamsAsync
in interface AmazonSageMakerAsync
public Future<ListSubscribedWorkteamsResult> listSubscribedWorkteamsAsync(ListSubscribedWorkteamsRequest request, AsyncHandler<ListSubscribedWorkteamsRequest,ListSubscribedWorkteamsResult> asyncHandler)
AmazonSageMakerAsync
Gets a list of the work teams that you are subscribed to in the AWS Marketplace. The list may be empty if no work
team satisfies the filter specified in the NameContains
parameter.
listSubscribedWorkteamsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListTagsResult> listTagsAsync(ListTagsRequest request)
AmazonSageMakerAsync
Returns the tags for the specified Amazon SageMaker resource.
listTagsAsync
in interface AmazonSageMakerAsync
public Future<ListTagsResult> listTagsAsync(ListTagsRequest request, AsyncHandler<ListTagsRequest,ListTagsResult> asyncHandler)
AmazonSageMakerAsync
Returns the tags for the specified Amazon SageMaker resource.
listTagsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListTrainingJobsResult> listTrainingJobsAsync(ListTrainingJobsRequest request)
AmazonSageMakerAsync
Lists training jobs.
listTrainingJobsAsync
in interface AmazonSageMakerAsync
public Future<ListTrainingJobsResult> listTrainingJobsAsync(ListTrainingJobsRequest request, AsyncHandler<ListTrainingJobsRequest,ListTrainingJobsResult> asyncHandler)
AmazonSageMakerAsync
Lists training jobs.
listTrainingJobsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListTrainingJobsForHyperParameterTuningJobResult> listTrainingJobsForHyperParameterTuningJobAsync(ListTrainingJobsForHyperParameterTuningJobRequest request)
AmazonSageMakerAsync
Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.
listTrainingJobsForHyperParameterTuningJobAsync
in interface AmazonSageMakerAsync
public Future<ListTrainingJobsForHyperParameterTuningJobResult> listTrainingJobsForHyperParameterTuningJobAsync(ListTrainingJobsForHyperParameterTuningJobRequest request, AsyncHandler<ListTrainingJobsForHyperParameterTuningJobRequest,ListTrainingJobsForHyperParameterTuningJobResult> asyncHandler)
AmazonSageMakerAsync
Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.
listTrainingJobsForHyperParameterTuningJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListTransformJobsResult> listTransformJobsAsync(ListTransformJobsRequest request)
AmazonSageMakerAsync
Lists transform jobs.
listTransformJobsAsync
in interface AmazonSageMakerAsync
public Future<ListTransformJobsResult> listTransformJobsAsync(ListTransformJobsRequest request, AsyncHandler<ListTransformJobsRequest,ListTransformJobsResult> asyncHandler)
AmazonSageMakerAsync
Lists transform jobs.
listTransformJobsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListTrialComponentsResult> listTrialComponentsAsync(ListTrialComponentsRequest request)
AmazonSageMakerAsync
Lists the trial components in your account. You can sort the list by trial component name or creation time. You can filter the list to show only components that were created in a specific time range. You can also filter on one of the following:
ExperimentName
SourceArn
TrialName
listTrialComponentsAsync
in interface AmazonSageMakerAsync
public Future<ListTrialComponentsResult> listTrialComponentsAsync(ListTrialComponentsRequest request, AsyncHandler<ListTrialComponentsRequest,ListTrialComponentsResult> asyncHandler)
AmazonSageMakerAsync
Lists the trial components in your account. You can sort the list by trial component name or creation time. You can filter the list to show only components that were created in a specific time range. You can also filter on one of the following:
ExperimentName
SourceArn
TrialName
listTrialComponentsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListTrialsResult> listTrialsAsync(ListTrialsRequest request)
AmazonSageMakerAsync
Lists the trials in your account. Specify an experiment name to limit the list to the trials that are part of that experiment. Specify a trial component name to limit the list to the trials that associated with that trial component. The list can be filtered to show only trials that were created in a specific time range. The list can be sorted by trial name or creation time.
listTrialsAsync
in interface AmazonSageMakerAsync
public Future<ListTrialsResult> listTrialsAsync(ListTrialsRequest request, AsyncHandler<ListTrialsRequest,ListTrialsResult> asyncHandler)
AmazonSageMakerAsync
Lists the trials in your account. Specify an experiment name to limit the list to the trials that are part of that experiment. Specify a trial component name to limit the list to the trials that associated with that trial component. The list can be filtered to show only trials that were created in a specific time range. The list can be sorted by trial name or creation time.
listTrialsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListUserProfilesResult> listUserProfilesAsync(ListUserProfilesRequest request)
AmazonSageMakerAsync
Lists user profiles.
listUserProfilesAsync
in interface AmazonSageMakerAsync
public Future<ListUserProfilesResult> listUserProfilesAsync(ListUserProfilesRequest request, AsyncHandler<ListUserProfilesRequest,ListUserProfilesResult> asyncHandler)
AmazonSageMakerAsync
Lists user profiles.
listUserProfilesAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<ListWorkteamsResult> listWorkteamsAsync(ListWorkteamsRequest request)
AmazonSageMakerAsync
Gets a list of work teams that you have defined in a region. The list may be empty if no work team satisfies the
filter specified in the NameContains
parameter.
listWorkteamsAsync
in interface AmazonSageMakerAsync
public Future<ListWorkteamsResult> listWorkteamsAsync(ListWorkteamsRequest request, AsyncHandler<ListWorkteamsRequest,ListWorkteamsResult> asyncHandler)
AmazonSageMakerAsync
Gets a list of work teams that you have defined in a region. The list may be empty if no work team satisfies the
filter specified in the NameContains
parameter.
listWorkteamsAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<RenderUiTemplateResult> renderUiTemplateAsync(RenderUiTemplateRequest request)
AmazonSageMakerAsync
Renders the UI template so that you can preview the worker's experience.
renderUiTemplateAsync
in interface AmazonSageMakerAsync
public Future<RenderUiTemplateResult> renderUiTemplateAsync(RenderUiTemplateRequest request, AsyncHandler<RenderUiTemplateRequest,RenderUiTemplateResult> asyncHandler)
AmazonSageMakerAsync
Renders the UI template so that you can preview the worker's experience.
renderUiTemplateAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<SearchResult> searchAsync(SearchRequest request)
AmazonSageMakerAsync
Finds Amazon SageMaker resources that match a search query. Matching resources are returned as a list of
SearchRecord
objects in the response. You can sort the search results by any resource property in a
ascending or descending order.
You can query against the following value types: numeric, text, Boolean, and timestamp.
searchAsync
in interface AmazonSageMakerAsync
public Future<SearchResult> searchAsync(SearchRequest request, AsyncHandler<SearchRequest,SearchResult> asyncHandler)
AmazonSageMakerAsync
Finds Amazon SageMaker resources that match a search query. Matching resources are returned as a list of
SearchRecord
objects in the response. You can sort the search results by any resource property in a
ascending or descending order.
You can query against the following value types: numeric, text, Boolean, and timestamp.
searchAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StartMonitoringScheduleResult> startMonitoringScheduleAsync(StartMonitoringScheduleRequest request)
AmazonSageMakerAsync
Starts a previously stopped monitoring schedule.
New monitoring schedules are immediately started after creation.
startMonitoringScheduleAsync
in interface AmazonSageMakerAsync
public Future<StartMonitoringScheduleResult> startMonitoringScheduleAsync(StartMonitoringScheduleRequest request, AsyncHandler<StartMonitoringScheduleRequest,StartMonitoringScheduleResult> asyncHandler)
AmazonSageMakerAsync
Starts a previously stopped monitoring schedule.
New monitoring schedules are immediately started after creation.
startMonitoringScheduleAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StartNotebookInstanceResult> startNotebookInstanceAsync(StartNotebookInstanceRequest request)
AmazonSageMakerAsync
Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume.
After configuring the notebook instance, Amazon SageMaker sets the notebook instance status to
InService
. A notebook instance's status must be InService
before you can connect to
your Jupyter notebook.
startNotebookInstanceAsync
in interface AmazonSageMakerAsync
public Future<StartNotebookInstanceResult> startNotebookInstanceAsync(StartNotebookInstanceRequest request, AsyncHandler<StartNotebookInstanceRequest,StartNotebookInstanceResult> asyncHandler)
AmazonSageMakerAsync
Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume.
After configuring the notebook instance, Amazon SageMaker sets the notebook instance status to
InService
. A notebook instance's status must be InService
before you can connect to
your Jupyter notebook.
startNotebookInstanceAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StopAutoMLJobResult> stopAutoMLJobAsync(StopAutoMLJobRequest request)
AmazonSageMakerAsync
A method for forcing the termination of a running job.
stopAutoMLJobAsync
in interface AmazonSageMakerAsync
public Future<StopAutoMLJobResult> stopAutoMLJobAsync(StopAutoMLJobRequest request, AsyncHandler<StopAutoMLJobRequest,StopAutoMLJobResult> asyncHandler)
AmazonSageMakerAsync
A method for forcing the termination of a running job.
stopAutoMLJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StopCompilationJobResult> stopCompilationJobAsync(StopCompilationJobRequest request)
AmazonSageMakerAsync
Stops a model compilation job.
To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job hasn't stopped, it sends the SIGKILL signal.
When it receives a StopCompilationJob
request, Amazon SageMaker changes the
CompilationJobSummary$CompilationJobStatus of the job to Stopping
. After Amazon SageMaker
stops the job, it sets the CompilationJobSummary$CompilationJobStatus to Stopped
.
stopCompilationJobAsync
in interface AmazonSageMakerAsync
public Future<StopCompilationJobResult> stopCompilationJobAsync(StopCompilationJobRequest request, AsyncHandler<StopCompilationJobRequest,StopCompilationJobResult> asyncHandler)
AmazonSageMakerAsync
Stops a model compilation job.
To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job hasn't stopped, it sends the SIGKILL signal.
When it receives a StopCompilationJob
request, Amazon SageMaker changes the
CompilationJobSummary$CompilationJobStatus of the job to Stopping
. After Amazon SageMaker
stops the job, it sets the CompilationJobSummary$CompilationJobStatus to Stopped
.
stopCompilationJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StopHyperParameterTuningJobResult> stopHyperParameterTuningJobAsync(StopHyperParameterTuningJobRequest request)
AmazonSageMakerAsync
Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.
All model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3). All
data that the training jobs write to Amazon CloudWatch Logs are still available in CloudWatch. After the tuning
job moves to the Stopped
state, it releases all reserved resources for the tuning job.
stopHyperParameterTuningJobAsync
in interface AmazonSageMakerAsync
public Future<StopHyperParameterTuningJobResult> stopHyperParameterTuningJobAsync(StopHyperParameterTuningJobRequest request, AsyncHandler<StopHyperParameterTuningJobRequest,StopHyperParameterTuningJobResult> asyncHandler)
AmazonSageMakerAsync
Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.
All model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3). All
data that the training jobs write to Amazon CloudWatch Logs are still available in CloudWatch. After the tuning
job moves to the Stopped
state, it releases all reserved resources for the tuning job.
stopHyperParameterTuningJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StopLabelingJobResult> stopLabelingJobAsync(StopLabelingJobRequest request)
AmazonSageMakerAsync
Stops a running labeling job. A job that is stopped cannot be restarted. Any results obtained before the job is stopped are placed in the Amazon S3 output bucket.
stopLabelingJobAsync
in interface AmazonSageMakerAsync
public Future<StopLabelingJobResult> stopLabelingJobAsync(StopLabelingJobRequest request, AsyncHandler<StopLabelingJobRequest,StopLabelingJobResult> asyncHandler)
AmazonSageMakerAsync
Stops a running labeling job. A job that is stopped cannot be restarted. Any results obtained before the job is stopped are placed in the Amazon S3 output bucket.
stopLabelingJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StopMonitoringScheduleResult> stopMonitoringScheduleAsync(StopMonitoringScheduleRequest request)
AmazonSageMakerAsync
Stops a previously started monitoring schedule.
stopMonitoringScheduleAsync
in interface AmazonSageMakerAsync
public Future<StopMonitoringScheduleResult> stopMonitoringScheduleAsync(StopMonitoringScheduleRequest request, AsyncHandler<StopMonitoringScheduleRequest,StopMonitoringScheduleResult> asyncHandler)
AmazonSageMakerAsync
Stops a previously started monitoring schedule.
stopMonitoringScheduleAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StopNotebookInstanceResult> stopNotebookInstanceAsync(StopNotebookInstanceRequest request)
AmazonSageMakerAsync
Terminates the ML compute instance. Before terminating the instance, Amazon SageMaker disconnects the ML storage
volume from it. Amazon SageMaker preserves the ML storage volume. Amazon SageMaker stops charging you for the ML
compute instance when you call StopNotebookInstance
.
To access data on the ML storage volume for a notebook instance that has been terminated, call the
StartNotebookInstance
API. StartNotebookInstance
launches another ML compute instance,
configures it, and attaches the preserved ML storage volume so you can continue your work.
stopNotebookInstanceAsync
in interface AmazonSageMakerAsync
public Future<StopNotebookInstanceResult> stopNotebookInstanceAsync(StopNotebookInstanceRequest request, AsyncHandler<StopNotebookInstanceRequest,StopNotebookInstanceResult> asyncHandler)
AmazonSageMakerAsync
Terminates the ML compute instance. Before terminating the instance, Amazon SageMaker disconnects the ML storage
volume from it. Amazon SageMaker preserves the ML storage volume. Amazon SageMaker stops charging you for the ML
compute instance when you call StopNotebookInstance
.
To access data on the ML storage volume for a notebook instance that has been terminated, call the
StartNotebookInstance
API. StartNotebookInstance
launches another ML compute instance,
configures it, and attaches the preserved ML storage volume so you can continue your work.
stopNotebookInstanceAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StopProcessingJobResult> stopProcessingJobAsync(StopProcessingJobRequest request)
AmazonSageMakerAsync
Stops a processing job.
stopProcessingJobAsync
in interface AmazonSageMakerAsync
public Future<StopProcessingJobResult> stopProcessingJobAsync(StopProcessingJobRequest request, AsyncHandler<StopProcessingJobRequest,StopProcessingJobResult> asyncHandler)
AmazonSageMakerAsync
Stops a processing job.
stopProcessingJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StopTrainingJobResult> stopTrainingJobAsync(StopTrainingJobRequest request)
AmazonSageMakerAsync
Stops a training job. To stop a job, Amazon SageMaker sends the algorithm the SIGTERM
signal, which
delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts,
so the results of the training is not lost.
When it receives a StopTrainingJob
request, Amazon SageMaker changes the status of the job to
Stopping
. After Amazon SageMaker stops the job, it sets the status to Stopped
.
stopTrainingJobAsync
in interface AmazonSageMakerAsync
public Future<StopTrainingJobResult> stopTrainingJobAsync(StopTrainingJobRequest request, AsyncHandler<StopTrainingJobRequest,StopTrainingJobResult> asyncHandler)
AmazonSageMakerAsync
Stops a training job. To stop a job, Amazon SageMaker sends the algorithm the SIGTERM
signal, which
delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts,
so the results of the training is not lost.
When it receives a StopTrainingJob
request, Amazon SageMaker changes the status of the job to
Stopping
. After Amazon SageMaker stops the job, it sets the status to Stopped
.
stopTrainingJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<StopTransformJobResult> stopTransformJobAsync(StopTransformJobRequest request)
AmazonSageMakerAsync
Stops a transform job.
When Amazon SageMaker receives a StopTransformJob
request, the status of the job changes to
Stopping
. After Amazon SageMaker stops the job, the status is set to Stopped
. When you
stop a transform job before it is completed, Amazon SageMaker doesn't store the job's output in Amazon S3.
stopTransformJobAsync
in interface AmazonSageMakerAsync
public Future<StopTransformJobResult> stopTransformJobAsync(StopTransformJobRequest request, AsyncHandler<StopTransformJobRequest,StopTransformJobResult> asyncHandler)
AmazonSageMakerAsync
Stops a transform job.
When Amazon SageMaker receives a StopTransformJob
request, the status of the job changes to
Stopping
. After Amazon SageMaker stops the job, the status is set to Stopped
. When you
stop a transform job before it is completed, Amazon SageMaker doesn't store the job's output in Amazon S3.
stopTransformJobAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateCodeRepositoryResult> updateCodeRepositoryAsync(UpdateCodeRepositoryRequest request)
AmazonSageMakerAsync
Updates the specified Git repository with the specified values.
updateCodeRepositoryAsync
in interface AmazonSageMakerAsync
public Future<UpdateCodeRepositoryResult> updateCodeRepositoryAsync(UpdateCodeRepositoryRequest request, AsyncHandler<UpdateCodeRepositoryRequest,UpdateCodeRepositoryResult> asyncHandler)
AmazonSageMakerAsync
Updates the specified Git repository with the specified values.
updateCodeRepositoryAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateDomainResult> updateDomainAsync(UpdateDomainRequest request)
AmazonSageMakerAsync
Updates a domain. Changes will impact all of the people in the domain.
updateDomainAsync
in interface AmazonSageMakerAsync
public Future<UpdateDomainResult> updateDomainAsync(UpdateDomainRequest request, AsyncHandler<UpdateDomainRequest,UpdateDomainResult> asyncHandler)
AmazonSageMakerAsync
Updates a domain. Changes will impact all of the people in the domain.
updateDomainAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateEndpointResult> updateEndpointAsync(UpdateEndpointRequest request)
AmazonSageMakerAsync
Deploys the new EndpointConfig
specified in the request, switches to using newly created endpoint,
and then deletes resources provisioned for the endpoint using the previous EndpointConfig
(there is
no availability loss).
When Amazon SageMaker receives the request, it sets the endpoint status to Updating
. After updating
the endpoint, it sets the status to InService
. To check the status of an endpoint, use the
DescribeEndpoint API.
You must not delete an EndpointConfig
in use by an endpoint that is live or while the
UpdateEndpoint
or CreateEndpoint
operations are being performed on the endpoint. To
update an endpoint, you must create a new EndpointConfig
.
updateEndpointAsync
in interface AmazonSageMakerAsync
public Future<UpdateEndpointResult> updateEndpointAsync(UpdateEndpointRequest request, AsyncHandler<UpdateEndpointRequest,UpdateEndpointResult> asyncHandler)
AmazonSageMakerAsync
Deploys the new EndpointConfig
specified in the request, switches to using newly created endpoint,
and then deletes resources provisioned for the endpoint using the previous EndpointConfig
(there is
no availability loss).
When Amazon SageMaker receives the request, it sets the endpoint status to Updating
. After updating
the endpoint, it sets the status to InService
. To check the status of an endpoint, use the
DescribeEndpoint API.
You must not delete an EndpointConfig
in use by an endpoint that is live or while the
UpdateEndpoint
or CreateEndpoint
operations are being performed on the endpoint. To
update an endpoint, you must create a new EndpointConfig
.
updateEndpointAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateEndpointWeightsAndCapacitiesResult> updateEndpointWeightsAndCapacitiesAsync(UpdateEndpointWeightsAndCapacitiesRequest request)
AmazonSageMakerAsync
Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant
associated with an existing endpoint. When it receives the request, Amazon SageMaker sets the endpoint status to
Updating
. After updating the endpoint, it sets the status to InService
. To check the
status of an endpoint, use the DescribeEndpoint API.
updateEndpointWeightsAndCapacitiesAsync
in interface AmazonSageMakerAsync
public Future<UpdateEndpointWeightsAndCapacitiesResult> updateEndpointWeightsAndCapacitiesAsync(UpdateEndpointWeightsAndCapacitiesRequest request, AsyncHandler<UpdateEndpointWeightsAndCapacitiesRequest,UpdateEndpointWeightsAndCapacitiesResult> asyncHandler)
AmazonSageMakerAsync
Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant
associated with an existing endpoint. When it receives the request, Amazon SageMaker sets the endpoint status to
Updating
. After updating the endpoint, it sets the status to InService
. To check the
status of an endpoint, use the DescribeEndpoint API.
updateEndpointWeightsAndCapacitiesAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateExperimentResult> updateExperimentAsync(UpdateExperimentRequest request)
AmazonSageMakerAsync
Adds, updates, or removes the description of an experiment. Updates the display name of an experiment.
updateExperimentAsync
in interface AmazonSageMakerAsync
public Future<UpdateExperimentResult> updateExperimentAsync(UpdateExperimentRequest request, AsyncHandler<UpdateExperimentRequest,UpdateExperimentResult> asyncHandler)
AmazonSageMakerAsync
Adds, updates, or removes the description of an experiment. Updates the display name of an experiment.
updateExperimentAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateMonitoringScheduleResult> updateMonitoringScheduleAsync(UpdateMonitoringScheduleRequest request)
AmazonSageMakerAsync
Updates a previously created schedule.
updateMonitoringScheduleAsync
in interface AmazonSageMakerAsync
public Future<UpdateMonitoringScheduleResult> updateMonitoringScheduleAsync(UpdateMonitoringScheduleRequest request, AsyncHandler<UpdateMonitoringScheduleRequest,UpdateMonitoringScheduleResult> asyncHandler)
AmazonSageMakerAsync
Updates a previously created schedule.
updateMonitoringScheduleAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateNotebookInstanceResult> updateNotebookInstanceAsync(UpdateNotebookInstanceRequest request)
AmazonSageMakerAsync
Updates a notebook instance. NotebookInstance updates include upgrading or downgrading the ML compute instance used for your notebook instance to accommodate changes in your workload requirements.
updateNotebookInstanceAsync
in interface AmazonSageMakerAsync
public Future<UpdateNotebookInstanceResult> updateNotebookInstanceAsync(UpdateNotebookInstanceRequest request, AsyncHandler<UpdateNotebookInstanceRequest,UpdateNotebookInstanceResult> asyncHandler)
AmazonSageMakerAsync
Updates a notebook instance. NotebookInstance updates include upgrading or downgrading the ML compute instance used for your notebook instance to accommodate changes in your workload requirements.
updateNotebookInstanceAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateNotebookInstanceLifecycleConfigResult> updateNotebookInstanceLifecycleConfigAsync(UpdateNotebookInstanceLifecycleConfigRequest request)
AmazonSageMakerAsync
Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API.
updateNotebookInstanceLifecycleConfigAsync
in interface AmazonSageMakerAsync
public Future<UpdateNotebookInstanceLifecycleConfigResult> updateNotebookInstanceLifecycleConfigAsync(UpdateNotebookInstanceLifecycleConfigRequest request, AsyncHandler<UpdateNotebookInstanceLifecycleConfigRequest,UpdateNotebookInstanceLifecycleConfigResult> asyncHandler)
AmazonSageMakerAsync
Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API.
updateNotebookInstanceLifecycleConfigAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateTrialResult> updateTrialAsync(UpdateTrialRequest request)
AmazonSageMakerAsync
Updates the display name of a trial.
updateTrialAsync
in interface AmazonSageMakerAsync
public Future<UpdateTrialResult> updateTrialAsync(UpdateTrialRequest request, AsyncHandler<UpdateTrialRequest,UpdateTrialResult> asyncHandler)
AmazonSageMakerAsync
Updates the display name of a trial.
updateTrialAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateTrialComponentResult> updateTrialComponentAsync(UpdateTrialComponentRequest request)
AmazonSageMakerAsync
Updates one or more properties of a trial component.
updateTrialComponentAsync
in interface AmazonSageMakerAsync
public Future<UpdateTrialComponentResult> updateTrialComponentAsync(UpdateTrialComponentRequest request, AsyncHandler<UpdateTrialComponentRequest,UpdateTrialComponentResult> asyncHandler)
AmazonSageMakerAsync
Updates one or more properties of a trial component.
updateTrialComponentAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateUserProfileResult> updateUserProfileAsync(UpdateUserProfileRequest request)
AmazonSageMakerAsync
Updates a user profile.
updateUserProfileAsync
in interface AmazonSageMakerAsync
public Future<UpdateUserProfileResult> updateUserProfileAsync(UpdateUserProfileRequest request, AsyncHandler<UpdateUserProfileRequest,UpdateUserProfileResult> asyncHandler)
AmazonSageMakerAsync
Updates a user profile.
updateUserProfileAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateWorkforceResult> updateWorkforceAsync(UpdateWorkforceRequest request)
AmazonSageMakerAsync
Restricts access to tasks assigned to workers in the specified workforce to those within specific ranges of IP addresses. You specify allowed IP addresses by creating a list of up to four CIDRs.
By default, a workforce isn't restricted to specific IP addresses. If you specify a range of IP addresses,
workers who attempt to access tasks using any IP address outside the specified range are denied access and get a
Not Found
error message on the worker portal. After restricting access with this operation, you can
see the allowed IP values for a private workforce with the operation.
This operation applies only to private workforces.
updateWorkforceAsync
in interface AmazonSageMakerAsync
public Future<UpdateWorkforceResult> updateWorkforceAsync(UpdateWorkforceRequest request, AsyncHandler<UpdateWorkforceRequest,UpdateWorkforceResult> asyncHandler)
AmazonSageMakerAsync
Restricts access to tasks assigned to workers in the specified workforce to those within specific ranges of IP addresses. You specify allowed IP addresses by creating a list of up to four CIDRs.
By default, a workforce isn't restricted to specific IP addresses. If you specify a range of IP addresses,
workers who attempt to access tasks using any IP address outside the specified range are denied access and get a
Not Found
error message on the worker portal. After restricting access with this operation, you can
see the allowed IP values for a private workforce with the operation.
This operation applies only to private workforces.
updateWorkforceAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.public Future<UpdateWorkteamResult> updateWorkteamAsync(UpdateWorkteamRequest request)
AmazonSageMakerAsync
Updates an existing work team with new member definitions or description.
updateWorkteamAsync
in interface AmazonSageMakerAsync
public Future<UpdateWorkteamResult> updateWorkteamAsync(UpdateWorkteamRequest request, AsyncHandler<UpdateWorkteamRequest,UpdateWorkteamResult> asyncHandler)
AmazonSageMakerAsync
Updates an existing work team with new member definitions or description.
updateWorkteamAsync
in interface AmazonSageMakerAsync
asyncHandler
- Asynchronous callback handler for events in the lifecycle of the request. Users can provide an
implementation of the callback methods in this interface to receive notification of successful or
unsuccessful completion of the operation.Copyright © 2013 Amazon Web Services, Inc. All Rights Reserved.