AWS SDK for C++  1.8.95
AWS SDK for C++
Public Types | Public Member Functions | List of all members
Aws::SageMaker::SageMakerClient Class Reference

#include <SageMakerClient.h>

+ Inheritance diagram for Aws::SageMaker::SageMakerClient:

Public Types

typedef Aws::Client::AWSJsonClient BASECLASS
 
- Public Types inherited from Aws::Client::AWSJsonClient
typedef AWSClient BASECLASS
 

Public Member Functions

 SageMakerClient (const Aws::Client::ClientConfiguration &clientConfiguration=Aws::Client::ClientConfiguration())
 
 SageMakerClient (const Aws::Auth::AWSCredentials &credentials, const Aws::Client::ClientConfiguration &clientConfiguration=Aws::Client::ClientConfiguration())
 
 SageMakerClient (const std::shared_ptr< Aws::Auth::AWSCredentialsProvider > &credentialsProvider, const Aws::Client::ClientConfiguration &clientConfiguration=Aws::Client::ClientConfiguration())
 
virtual ~SageMakerClient ()
 
virtual Model::AddTagsOutcome AddTags (const Model::AddTagsRequest &request) const
 
virtual Model::AddTagsOutcomeCallable AddTagsCallable (const Model::AddTagsRequest &request) const
 
virtual void AddTagsAsync (const Model::AddTagsRequest &request, const AddTagsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::AssociateTrialComponentOutcome AssociateTrialComponent (const Model::AssociateTrialComponentRequest &request) const
 
virtual Model::AssociateTrialComponentOutcomeCallable AssociateTrialComponentCallable (const Model::AssociateTrialComponentRequest &request) const
 
virtual void AssociateTrialComponentAsync (const Model::AssociateTrialComponentRequest &request, const AssociateTrialComponentResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateAlgorithmOutcome CreateAlgorithm (const Model::CreateAlgorithmRequest &request) const
 
virtual Model::CreateAlgorithmOutcomeCallable CreateAlgorithmCallable (const Model::CreateAlgorithmRequest &request) const
 
virtual void CreateAlgorithmAsync (const Model::CreateAlgorithmRequest &request, const CreateAlgorithmResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateAppOutcome CreateApp (const Model::CreateAppRequest &request) const
 
virtual Model::CreateAppOutcomeCallable CreateAppCallable (const Model::CreateAppRequest &request) const
 
virtual void CreateAppAsync (const Model::CreateAppRequest &request, const CreateAppResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateAppImageConfigOutcome CreateAppImageConfig (const Model::CreateAppImageConfigRequest &request) const
 
virtual Model::CreateAppImageConfigOutcomeCallable CreateAppImageConfigCallable (const Model::CreateAppImageConfigRequest &request) const
 
virtual void CreateAppImageConfigAsync (const Model::CreateAppImageConfigRequest &request, const CreateAppImageConfigResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateAutoMLJobOutcome CreateAutoMLJob (const Model::CreateAutoMLJobRequest &request) const
 
virtual Model::CreateAutoMLJobOutcomeCallable CreateAutoMLJobCallable (const Model::CreateAutoMLJobRequest &request) const
 
virtual void CreateAutoMLJobAsync (const Model::CreateAutoMLJobRequest &request, const CreateAutoMLJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateCodeRepositoryOutcome CreateCodeRepository (const Model::CreateCodeRepositoryRequest &request) const
 
virtual Model::CreateCodeRepositoryOutcomeCallable CreateCodeRepositoryCallable (const Model::CreateCodeRepositoryRequest &request) const
 
virtual void CreateCodeRepositoryAsync (const Model::CreateCodeRepositoryRequest &request, const CreateCodeRepositoryResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateCompilationJobOutcome CreateCompilationJob (const Model::CreateCompilationJobRequest &request) const
 
virtual Model::CreateCompilationJobOutcomeCallable CreateCompilationJobCallable (const Model::CreateCompilationJobRequest &request) const
 
virtual void CreateCompilationJobAsync (const Model::CreateCompilationJobRequest &request, const CreateCompilationJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateDomainOutcome CreateDomain (const Model::CreateDomainRequest &request) const
 
virtual Model::CreateDomainOutcomeCallable CreateDomainCallable (const Model::CreateDomainRequest &request) const
 
virtual void CreateDomainAsync (const Model::CreateDomainRequest &request, const CreateDomainResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateEndpointOutcome CreateEndpoint (const Model::CreateEndpointRequest &request) const
 
virtual Model::CreateEndpointOutcomeCallable CreateEndpointCallable (const Model::CreateEndpointRequest &request) const
 
virtual void CreateEndpointAsync (const Model::CreateEndpointRequest &request, const CreateEndpointResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateEndpointConfigOutcome CreateEndpointConfig (const Model::CreateEndpointConfigRequest &request) const
 
virtual Model::CreateEndpointConfigOutcomeCallable CreateEndpointConfigCallable (const Model::CreateEndpointConfigRequest &request) const
 
virtual void CreateEndpointConfigAsync (const Model::CreateEndpointConfigRequest &request, const CreateEndpointConfigResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateExperimentOutcome CreateExperiment (const Model::CreateExperimentRequest &request) const
 
virtual Model::CreateExperimentOutcomeCallable CreateExperimentCallable (const Model::CreateExperimentRequest &request) const
 
virtual void CreateExperimentAsync (const Model::CreateExperimentRequest &request, const CreateExperimentResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateFlowDefinitionOutcome CreateFlowDefinition (const Model::CreateFlowDefinitionRequest &request) const
 
virtual Model::CreateFlowDefinitionOutcomeCallable CreateFlowDefinitionCallable (const Model::CreateFlowDefinitionRequest &request) const
 
virtual void CreateFlowDefinitionAsync (const Model::CreateFlowDefinitionRequest &request, const CreateFlowDefinitionResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateHumanTaskUiOutcome CreateHumanTaskUi (const Model::CreateHumanTaskUiRequest &request) const
 
virtual Model::CreateHumanTaskUiOutcomeCallable CreateHumanTaskUiCallable (const Model::CreateHumanTaskUiRequest &request) const
 
virtual void CreateHumanTaskUiAsync (const Model::CreateHumanTaskUiRequest &request, const CreateHumanTaskUiResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateHyperParameterTuningJobOutcome CreateHyperParameterTuningJob (const Model::CreateHyperParameterTuningJobRequest &request) const
 
virtual Model::CreateHyperParameterTuningJobOutcomeCallable CreateHyperParameterTuningJobCallable (const Model::CreateHyperParameterTuningJobRequest &request) const
 
virtual void CreateHyperParameterTuningJobAsync (const Model::CreateHyperParameterTuningJobRequest &request, const CreateHyperParameterTuningJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateImageOutcome CreateImage (const Model::CreateImageRequest &request) const
 
virtual Model::CreateImageOutcomeCallable CreateImageCallable (const Model::CreateImageRequest &request) const
 
virtual void CreateImageAsync (const Model::CreateImageRequest &request, const CreateImageResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateImageVersionOutcome CreateImageVersion (const Model::CreateImageVersionRequest &request) const
 
virtual Model::CreateImageVersionOutcomeCallable CreateImageVersionCallable (const Model::CreateImageVersionRequest &request) const
 
virtual void CreateImageVersionAsync (const Model::CreateImageVersionRequest &request, const CreateImageVersionResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateLabelingJobOutcome CreateLabelingJob (const Model::CreateLabelingJobRequest &request) const
 
virtual Model::CreateLabelingJobOutcomeCallable CreateLabelingJobCallable (const Model::CreateLabelingJobRequest &request) const
 
virtual void CreateLabelingJobAsync (const Model::CreateLabelingJobRequest &request, const CreateLabelingJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateModelOutcome CreateModel (const Model::CreateModelRequest &request) const
 
virtual Model::CreateModelOutcomeCallable CreateModelCallable (const Model::CreateModelRequest &request) const
 
virtual void CreateModelAsync (const Model::CreateModelRequest &request, const CreateModelResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateModelPackageOutcome CreateModelPackage (const Model::CreateModelPackageRequest &request) const
 
virtual Model::CreateModelPackageOutcomeCallable CreateModelPackageCallable (const Model::CreateModelPackageRequest &request) const
 
virtual void CreateModelPackageAsync (const Model::CreateModelPackageRequest &request, const CreateModelPackageResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateMonitoringScheduleOutcome CreateMonitoringSchedule (const Model::CreateMonitoringScheduleRequest &request) const
 
virtual Model::CreateMonitoringScheduleOutcomeCallable CreateMonitoringScheduleCallable (const Model::CreateMonitoringScheduleRequest &request) const
 
virtual void CreateMonitoringScheduleAsync (const Model::CreateMonitoringScheduleRequest &request, const CreateMonitoringScheduleResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateNotebookInstanceOutcome CreateNotebookInstance (const Model::CreateNotebookInstanceRequest &request) const
 
virtual Model::CreateNotebookInstanceOutcomeCallable CreateNotebookInstanceCallable (const Model::CreateNotebookInstanceRequest &request) const
 
virtual void CreateNotebookInstanceAsync (const Model::CreateNotebookInstanceRequest &request, const CreateNotebookInstanceResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateNotebookInstanceLifecycleConfigOutcome CreateNotebookInstanceLifecycleConfig (const Model::CreateNotebookInstanceLifecycleConfigRequest &request) const
 
virtual Model::CreateNotebookInstanceLifecycleConfigOutcomeCallable CreateNotebookInstanceLifecycleConfigCallable (const Model::CreateNotebookInstanceLifecycleConfigRequest &request) const
 
virtual void CreateNotebookInstanceLifecycleConfigAsync (const Model::CreateNotebookInstanceLifecycleConfigRequest &request, const CreateNotebookInstanceLifecycleConfigResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreatePresignedDomainUrlOutcome CreatePresignedDomainUrl (const Model::CreatePresignedDomainUrlRequest &request) const
 
virtual Model::CreatePresignedDomainUrlOutcomeCallable CreatePresignedDomainUrlCallable (const Model::CreatePresignedDomainUrlRequest &request) const
 
virtual void CreatePresignedDomainUrlAsync (const Model::CreatePresignedDomainUrlRequest &request, const CreatePresignedDomainUrlResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreatePresignedNotebookInstanceUrlOutcome CreatePresignedNotebookInstanceUrl (const Model::CreatePresignedNotebookInstanceUrlRequest &request) const
 
virtual Model::CreatePresignedNotebookInstanceUrlOutcomeCallable CreatePresignedNotebookInstanceUrlCallable (const Model::CreatePresignedNotebookInstanceUrlRequest &request) const
 
virtual void CreatePresignedNotebookInstanceUrlAsync (const Model::CreatePresignedNotebookInstanceUrlRequest &request, const CreatePresignedNotebookInstanceUrlResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateProcessingJobOutcome CreateProcessingJob (const Model::CreateProcessingJobRequest &request) const
 
virtual Model::CreateProcessingJobOutcomeCallable CreateProcessingJobCallable (const Model::CreateProcessingJobRequest &request) const
 
virtual void CreateProcessingJobAsync (const Model::CreateProcessingJobRequest &request, const CreateProcessingJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateTrainingJobOutcome CreateTrainingJob (const Model::CreateTrainingJobRequest &request) const
 
virtual Model::CreateTrainingJobOutcomeCallable CreateTrainingJobCallable (const Model::CreateTrainingJobRequest &request) const
 
virtual void CreateTrainingJobAsync (const Model::CreateTrainingJobRequest &request, const CreateTrainingJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateTransformJobOutcome CreateTransformJob (const Model::CreateTransformJobRequest &request) const
 
virtual Model::CreateTransformJobOutcomeCallable CreateTransformJobCallable (const Model::CreateTransformJobRequest &request) const
 
virtual void CreateTransformJobAsync (const Model::CreateTransformJobRequest &request, const CreateTransformJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateTrialOutcome CreateTrial (const Model::CreateTrialRequest &request) const
 
virtual Model::CreateTrialOutcomeCallable CreateTrialCallable (const Model::CreateTrialRequest &request) const
 
virtual void CreateTrialAsync (const Model::CreateTrialRequest &request, const CreateTrialResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateTrialComponentOutcome CreateTrialComponent (const Model::CreateTrialComponentRequest &request) const
 
virtual Model::CreateTrialComponentOutcomeCallable CreateTrialComponentCallable (const Model::CreateTrialComponentRequest &request) const
 
virtual void CreateTrialComponentAsync (const Model::CreateTrialComponentRequest &request, const CreateTrialComponentResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateUserProfileOutcome CreateUserProfile (const Model::CreateUserProfileRequest &request) const
 
virtual Model::CreateUserProfileOutcomeCallable CreateUserProfileCallable (const Model::CreateUserProfileRequest &request) const
 
virtual void CreateUserProfileAsync (const Model::CreateUserProfileRequest &request, const CreateUserProfileResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateWorkforceOutcome CreateWorkforce (const Model::CreateWorkforceRequest &request) const
 
virtual Model::CreateWorkforceOutcomeCallable CreateWorkforceCallable (const Model::CreateWorkforceRequest &request) const
 
virtual void CreateWorkforceAsync (const Model::CreateWorkforceRequest &request, const CreateWorkforceResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::CreateWorkteamOutcome CreateWorkteam (const Model::CreateWorkteamRequest &request) const
 
virtual Model::CreateWorkteamOutcomeCallable CreateWorkteamCallable (const Model::CreateWorkteamRequest &request) const
 
virtual void CreateWorkteamAsync (const Model::CreateWorkteamRequest &request, const CreateWorkteamResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteAlgorithmOutcome DeleteAlgorithm (const Model::DeleteAlgorithmRequest &request) const
 
virtual Model::DeleteAlgorithmOutcomeCallable DeleteAlgorithmCallable (const Model::DeleteAlgorithmRequest &request) const
 
virtual void DeleteAlgorithmAsync (const Model::DeleteAlgorithmRequest &request, const DeleteAlgorithmResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteAppOutcome DeleteApp (const Model::DeleteAppRequest &request) const
 
virtual Model::DeleteAppOutcomeCallable DeleteAppCallable (const Model::DeleteAppRequest &request) const
 
virtual void DeleteAppAsync (const Model::DeleteAppRequest &request, const DeleteAppResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteAppImageConfigOutcome DeleteAppImageConfig (const Model::DeleteAppImageConfigRequest &request) const
 
virtual Model::DeleteAppImageConfigOutcomeCallable DeleteAppImageConfigCallable (const Model::DeleteAppImageConfigRequest &request) const
 
virtual void DeleteAppImageConfigAsync (const Model::DeleteAppImageConfigRequest &request, const DeleteAppImageConfigResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteCodeRepositoryOutcome DeleteCodeRepository (const Model::DeleteCodeRepositoryRequest &request) const
 
virtual Model::DeleteCodeRepositoryOutcomeCallable DeleteCodeRepositoryCallable (const Model::DeleteCodeRepositoryRequest &request) const
 
virtual void DeleteCodeRepositoryAsync (const Model::DeleteCodeRepositoryRequest &request, const DeleteCodeRepositoryResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteDomainOutcome DeleteDomain (const Model::DeleteDomainRequest &request) const
 
virtual Model::DeleteDomainOutcomeCallable DeleteDomainCallable (const Model::DeleteDomainRequest &request) const
 
virtual void DeleteDomainAsync (const Model::DeleteDomainRequest &request, const DeleteDomainResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteEndpointOutcome DeleteEndpoint (const Model::DeleteEndpointRequest &request) const
 
virtual Model::DeleteEndpointOutcomeCallable DeleteEndpointCallable (const Model::DeleteEndpointRequest &request) const
 
virtual void DeleteEndpointAsync (const Model::DeleteEndpointRequest &request, const DeleteEndpointResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteEndpointConfigOutcome DeleteEndpointConfig (const Model::DeleteEndpointConfigRequest &request) const
 
virtual Model::DeleteEndpointConfigOutcomeCallable DeleteEndpointConfigCallable (const Model::DeleteEndpointConfigRequest &request) const
 
virtual void DeleteEndpointConfigAsync (const Model::DeleteEndpointConfigRequest &request, const DeleteEndpointConfigResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteExperimentOutcome DeleteExperiment (const Model::DeleteExperimentRequest &request) const
 
virtual Model::DeleteExperimentOutcomeCallable DeleteExperimentCallable (const Model::DeleteExperimentRequest &request) const
 
virtual void DeleteExperimentAsync (const Model::DeleteExperimentRequest &request, const DeleteExperimentResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteFlowDefinitionOutcome DeleteFlowDefinition (const Model::DeleteFlowDefinitionRequest &request) const
 
virtual Model::DeleteFlowDefinitionOutcomeCallable DeleteFlowDefinitionCallable (const Model::DeleteFlowDefinitionRequest &request) const
 
virtual void DeleteFlowDefinitionAsync (const Model::DeleteFlowDefinitionRequest &request, const DeleteFlowDefinitionResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteHumanTaskUiOutcome DeleteHumanTaskUi (const Model::DeleteHumanTaskUiRequest &request) const
 
virtual Model::DeleteHumanTaskUiOutcomeCallable DeleteHumanTaskUiCallable (const Model::DeleteHumanTaskUiRequest &request) const
 
virtual void DeleteHumanTaskUiAsync (const Model::DeleteHumanTaskUiRequest &request, const DeleteHumanTaskUiResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteImageOutcome DeleteImage (const Model::DeleteImageRequest &request) const
 
virtual Model::DeleteImageOutcomeCallable DeleteImageCallable (const Model::DeleteImageRequest &request) const
 
virtual void DeleteImageAsync (const Model::DeleteImageRequest &request, const DeleteImageResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteImageVersionOutcome DeleteImageVersion (const Model::DeleteImageVersionRequest &request) const
 
virtual Model::DeleteImageVersionOutcomeCallable DeleteImageVersionCallable (const Model::DeleteImageVersionRequest &request) const
 
virtual void DeleteImageVersionAsync (const Model::DeleteImageVersionRequest &request, const DeleteImageVersionResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteModelOutcome DeleteModel (const Model::DeleteModelRequest &request) const
 
virtual Model::DeleteModelOutcomeCallable DeleteModelCallable (const Model::DeleteModelRequest &request) const
 
virtual void DeleteModelAsync (const Model::DeleteModelRequest &request, const DeleteModelResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteModelPackageOutcome DeleteModelPackage (const Model::DeleteModelPackageRequest &request) const
 
virtual Model::DeleteModelPackageOutcomeCallable DeleteModelPackageCallable (const Model::DeleteModelPackageRequest &request) const
 
virtual void DeleteModelPackageAsync (const Model::DeleteModelPackageRequest &request, const DeleteModelPackageResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteMonitoringScheduleOutcome DeleteMonitoringSchedule (const Model::DeleteMonitoringScheduleRequest &request) const
 
virtual Model::DeleteMonitoringScheduleOutcomeCallable DeleteMonitoringScheduleCallable (const Model::DeleteMonitoringScheduleRequest &request) const
 
virtual void DeleteMonitoringScheduleAsync (const Model::DeleteMonitoringScheduleRequest &request, const DeleteMonitoringScheduleResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteNotebookInstanceOutcome DeleteNotebookInstance (const Model::DeleteNotebookInstanceRequest &request) const
 
virtual Model::DeleteNotebookInstanceOutcomeCallable DeleteNotebookInstanceCallable (const Model::DeleteNotebookInstanceRequest &request) const
 
virtual void DeleteNotebookInstanceAsync (const Model::DeleteNotebookInstanceRequest &request, const DeleteNotebookInstanceResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteNotebookInstanceLifecycleConfigOutcome DeleteNotebookInstanceLifecycleConfig (const Model::DeleteNotebookInstanceLifecycleConfigRequest &request) const
 
virtual Model::DeleteNotebookInstanceLifecycleConfigOutcomeCallable DeleteNotebookInstanceLifecycleConfigCallable (const Model::DeleteNotebookInstanceLifecycleConfigRequest &request) const
 
virtual void DeleteNotebookInstanceLifecycleConfigAsync (const Model::DeleteNotebookInstanceLifecycleConfigRequest &request, const DeleteNotebookInstanceLifecycleConfigResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteTagsOutcome DeleteTags (const Model::DeleteTagsRequest &request) const
 
virtual Model::DeleteTagsOutcomeCallable DeleteTagsCallable (const Model::DeleteTagsRequest &request) const
 
virtual void DeleteTagsAsync (const Model::DeleteTagsRequest &request, const DeleteTagsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteTrialOutcome DeleteTrial (const Model::DeleteTrialRequest &request) const
 
virtual Model::DeleteTrialOutcomeCallable DeleteTrialCallable (const Model::DeleteTrialRequest &request) const
 
virtual void DeleteTrialAsync (const Model::DeleteTrialRequest &request, const DeleteTrialResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteTrialComponentOutcome DeleteTrialComponent (const Model::DeleteTrialComponentRequest &request) const
 
virtual Model::DeleteTrialComponentOutcomeCallable DeleteTrialComponentCallable (const Model::DeleteTrialComponentRequest &request) const
 
virtual void DeleteTrialComponentAsync (const Model::DeleteTrialComponentRequest &request, const DeleteTrialComponentResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteUserProfileOutcome DeleteUserProfile (const Model::DeleteUserProfileRequest &request) const
 
virtual Model::DeleteUserProfileOutcomeCallable DeleteUserProfileCallable (const Model::DeleteUserProfileRequest &request) const
 
virtual void DeleteUserProfileAsync (const Model::DeleteUserProfileRequest &request, const DeleteUserProfileResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteWorkforceOutcome DeleteWorkforce (const Model::DeleteWorkforceRequest &request) const
 
virtual Model::DeleteWorkforceOutcomeCallable DeleteWorkforceCallable (const Model::DeleteWorkforceRequest &request) const
 
virtual void DeleteWorkforceAsync (const Model::DeleteWorkforceRequest &request, const DeleteWorkforceResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DeleteWorkteamOutcome DeleteWorkteam (const Model::DeleteWorkteamRequest &request) const
 
virtual Model::DeleteWorkteamOutcomeCallable DeleteWorkteamCallable (const Model::DeleteWorkteamRequest &request) const
 
virtual void DeleteWorkteamAsync (const Model::DeleteWorkteamRequest &request, const DeleteWorkteamResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeAlgorithmOutcome DescribeAlgorithm (const Model::DescribeAlgorithmRequest &request) const
 
virtual Model::DescribeAlgorithmOutcomeCallable DescribeAlgorithmCallable (const Model::DescribeAlgorithmRequest &request) const
 
virtual void DescribeAlgorithmAsync (const Model::DescribeAlgorithmRequest &request, const DescribeAlgorithmResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeAppOutcome DescribeApp (const Model::DescribeAppRequest &request) const
 
virtual Model::DescribeAppOutcomeCallable DescribeAppCallable (const Model::DescribeAppRequest &request) const
 
virtual void DescribeAppAsync (const Model::DescribeAppRequest &request, const DescribeAppResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeAppImageConfigOutcome DescribeAppImageConfig (const Model::DescribeAppImageConfigRequest &request) const
 
virtual Model::DescribeAppImageConfigOutcomeCallable DescribeAppImageConfigCallable (const Model::DescribeAppImageConfigRequest &request) const
 
virtual void DescribeAppImageConfigAsync (const Model::DescribeAppImageConfigRequest &request, const DescribeAppImageConfigResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeAutoMLJobOutcome DescribeAutoMLJob (const Model::DescribeAutoMLJobRequest &request) const
 
virtual Model::DescribeAutoMLJobOutcomeCallable DescribeAutoMLJobCallable (const Model::DescribeAutoMLJobRequest &request) const
 
virtual void DescribeAutoMLJobAsync (const Model::DescribeAutoMLJobRequest &request, const DescribeAutoMLJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeCodeRepositoryOutcome DescribeCodeRepository (const Model::DescribeCodeRepositoryRequest &request) const
 
virtual Model::DescribeCodeRepositoryOutcomeCallable DescribeCodeRepositoryCallable (const Model::DescribeCodeRepositoryRequest &request) const
 
virtual void DescribeCodeRepositoryAsync (const Model::DescribeCodeRepositoryRequest &request, const DescribeCodeRepositoryResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeCompilationJobOutcome DescribeCompilationJob (const Model::DescribeCompilationJobRequest &request) const
 
virtual Model::DescribeCompilationJobOutcomeCallable DescribeCompilationJobCallable (const Model::DescribeCompilationJobRequest &request) const
 
virtual void DescribeCompilationJobAsync (const Model::DescribeCompilationJobRequest &request, const DescribeCompilationJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeDomainOutcome DescribeDomain (const Model::DescribeDomainRequest &request) const
 
virtual Model::DescribeDomainOutcomeCallable DescribeDomainCallable (const Model::DescribeDomainRequest &request) const
 
virtual void DescribeDomainAsync (const Model::DescribeDomainRequest &request, const DescribeDomainResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeEndpointOutcome DescribeEndpoint (const Model::DescribeEndpointRequest &request) const
 
virtual Model::DescribeEndpointOutcomeCallable DescribeEndpointCallable (const Model::DescribeEndpointRequest &request) const
 
virtual void DescribeEndpointAsync (const Model::DescribeEndpointRequest &request, const DescribeEndpointResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeEndpointConfigOutcome DescribeEndpointConfig (const Model::DescribeEndpointConfigRequest &request) const
 
virtual Model::DescribeEndpointConfigOutcomeCallable DescribeEndpointConfigCallable (const Model::DescribeEndpointConfigRequest &request) const
 
virtual void DescribeEndpointConfigAsync (const Model::DescribeEndpointConfigRequest &request, const DescribeEndpointConfigResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeExperimentOutcome DescribeExperiment (const Model::DescribeExperimentRequest &request) const
 
virtual Model::DescribeExperimentOutcomeCallable DescribeExperimentCallable (const Model::DescribeExperimentRequest &request) const
 
virtual void DescribeExperimentAsync (const Model::DescribeExperimentRequest &request, const DescribeExperimentResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeFlowDefinitionOutcome DescribeFlowDefinition (const Model::DescribeFlowDefinitionRequest &request) const
 
virtual Model::DescribeFlowDefinitionOutcomeCallable DescribeFlowDefinitionCallable (const Model::DescribeFlowDefinitionRequest &request) const
 
virtual void DescribeFlowDefinitionAsync (const Model::DescribeFlowDefinitionRequest &request, const DescribeFlowDefinitionResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeHumanTaskUiOutcome DescribeHumanTaskUi (const Model::DescribeHumanTaskUiRequest &request) const
 
virtual Model::DescribeHumanTaskUiOutcomeCallable DescribeHumanTaskUiCallable (const Model::DescribeHumanTaskUiRequest &request) const
 
virtual void DescribeHumanTaskUiAsync (const Model::DescribeHumanTaskUiRequest &request, const DescribeHumanTaskUiResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeHyperParameterTuningJobOutcome DescribeHyperParameterTuningJob (const Model::DescribeHyperParameterTuningJobRequest &request) const
 
virtual Model::DescribeHyperParameterTuningJobOutcomeCallable DescribeHyperParameterTuningJobCallable (const Model::DescribeHyperParameterTuningJobRequest &request) const
 
virtual void DescribeHyperParameterTuningJobAsync (const Model::DescribeHyperParameterTuningJobRequest &request, const DescribeHyperParameterTuningJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeImageOutcome DescribeImage (const Model::DescribeImageRequest &request) const
 
virtual Model::DescribeImageOutcomeCallable DescribeImageCallable (const Model::DescribeImageRequest &request) const
 
virtual void DescribeImageAsync (const Model::DescribeImageRequest &request, const DescribeImageResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeImageVersionOutcome DescribeImageVersion (const Model::DescribeImageVersionRequest &request) const
 
virtual Model::DescribeImageVersionOutcomeCallable DescribeImageVersionCallable (const Model::DescribeImageVersionRequest &request) const
 
virtual void DescribeImageVersionAsync (const Model::DescribeImageVersionRequest &request, const DescribeImageVersionResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeLabelingJobOutcome DescribeLabelingJob (const Model::DescribeLabelingJobRequest &request) const
 
virtual Model::DescribeLabelingJobOutcomeCallable DescribeLabelingJobCallable (const Model::DescribeLabelingJobRequest &request) const
 
virtual void DescribeLabelingJobAsync (const Model::DescribeLabelingJobRequest &request, const DescribeLabelingJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeModelOutcome DescribeModel (const Model::DescribeModelRequest &request) const
 
virtual Model::DescribeModelOutcomeCallable DescribeModelCallable (const Model::DescribeModelRequest &request) const
 
virtual void DescribeModelAsync (const Model::DescribeModelRequest &request, const DescribeModelResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeModelPackageOutcome DescribeModelPackage (const Model::DescribeModelPackageRequest &request) const
 
virtual Model::DescribeModelPackageOutcomeCallable DescribeModelPackageCallable (const Model::DescribeModelPackageRequest &request) const
 
virtual void DescribeModelPackageAsync (const Model::DescribeModelPackageRequest &request, const DescribeModelPackageResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeMonitoringScheduleOutcome DescribeMonitoringSchedule (const Model::DescribeMonitoringScheduleRequest &request) const
 
virtual Model::DescribeMonitoringScheduleOutcomeCallable DescribeMonitoringScheduleCallable (const Model::DescribeMonitoringScheduleRequest &request) const
 
virtual void DescribeMonitoringScheduleAsync (const Model::DescribeMonitoringScheduleRequest &request, const DescribeMonitoringScheduleResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeNotebookInstanceOutcome DescribeNotebookInstance (const Model::DescribeNotebookInstanceRequest &request) const
 
virtual Model::DescribeNotebookInstanceOutcomeCallable DescribeNotebookInstanceCallable (const Model::DescribeNotebookInstanceRequest &request) const
 
virtual void DescribeNotebookInstanceAsync (const Model::DescribeNotebookInstanceRequest &request, const DescribeNotebookInstanceResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeNotebookInstanceLifecycleConfigOutcome DescribeNotebookInstanceLifecycleConfig (const Model::DescribeNotebookInstanceLifecycleConfigRequest &request) const
 
virtual Model::DescribeNotebookInstanceLifecycleConfigOutcomeCallable DescribeNotebookInstanceLifecycleConfigCallable (const Model::DescribeNotebookInstanceLifecycleConfigRequest &request) const
 
virtual void DescribeNotebookInstanceLifecycleConfigAsync (const Model::DescribeNotebookInstanceLifecycleConfigRequest &request, const DescribeNotebookInstanceLifecycleConfigResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeProcessingJobOutcome DescribeProcessingJob (const Model::DescribeProcessingJobRequest &request) const
 
virtual Model::DescribeProcessingJobOutcomeCallable DescribeProcessingJobCallable (const Model::DescribeProcessingJobRequest &request) const
 
virtual void DescribeProcessingJobAsync (const Model::DescribeProcessingJobRequest &request, const DescribeProcessingJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeSubscribedWorkteamOutcome DescribeSubscribedWorkteam (const Model::DescribeSubscribedWorkteamRequest &request) const
 
virtual Model::DescribeSubscribedWorkteamOutcomeCallable DescribeSubscribedWorkteamCallable (const Model::DescribeSubscribedWorkteamRequest &request) const
 
virtual void DescribeSubscribedWorkteamAsync (const Model::DescribeSubscribedWorkteamRequest &request, const DescribeSubscribedWorkteamResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeTrainingJobOutcome DescribeTrainingJob (const Model::DescribeTrainingJobRequest &request) const
 
virtual Model::DescribeTrainingJobOutcomeCallable DescribeTrainingJobCallable (const Model::DescribeTrainingJobRequest &request) const
 
virtual void DescribeTrainingJobAsync (const Model::DescribeTrainingJobRequest &request, const DescribeTrainingJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeTransformJobOutcome DescribeTransformJob (const Model::DescribeTransformJobRequest &request) const
 
virtual Model::DescribeTransformJobOutcomeCallable DescribeTransformJobCallable (const Model::DescribeTransformJobRequest &request) const
 
virtual void DescribeTransformJobAsync (const Model::DescribeTransformJobRequest &request, const DescribeTransformJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeTrialOutcome DescribeTrial (const Model::DescribeTrialRequest &request) const
 
virtual Model::DescribeTrialOutcomeCallable DescribeTrialCallable (const Model::DescribeTrialRequest &request) const
 
virtual void DescribeTrialAsync (const Model::DescribeTrialRequest &request, const DescribeTrialResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeTrialComponentOutcome DescribeTrialComponent (const Model::DescribeTrialComponentRequest &request) const
 
virtual Model::DescribeTrialComponentOutcomeCallable DescribeTrialComponentCallable (const Model::DescribeTrialComponentRequest &request) const
 
virtual void DescribeTrialComponentAsync (const Model::DescribeTrialComponentRequest &request, const DescribeTrialComponentResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeUserProfileOutcome DescribeUserProfile (const Model::DescribeUserProfileRequest &request) const
 
virtual Model::DescribeUserProfileOutcomeCallable DescribeUserProfileCallable (const Model::DescribeUserProfileRequest &request) const
 
virtual void DescribeUserProfileAsync (const Model::DescribeUserProfileRequest &request, const DescribeUserProfileResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeWorkforceOutcome DescribeWorkforce (const Model::DescribeWorkforceRequest &request) const
 
virtual Model::DescribeWorkforceOutcomeCallable DescribeWorkforceCallable (const Model::DescribeWorkforceRequest &request) const
 
virtual void DescribeWorkforceAsync (const Model::DescribeWorkforceRequest &request, const DescribeWorkforceResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DescribeWorkteamOutcome DescribeWorkteam (const Model::DescribeWorkteamRequest &request) const
 
virtual Model::DescribeWorkteamOutcomeCallable DescribeWorkteamCallable (const Model::DescribeWorkteamRequest &request) const
 
virtual void DescribeWorkteamAsync (const Model::DescribeWorkteamRequest &request, const DescribeWorkteamResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::DisassociateTrialComponentOutcome DisassociateTrialComponent (const Model::DisassociateTrialComponentRequest &request) const
 
virtual Model::DisassociateTrialComponentOutcomeCallable DisassociateTrialComponentCallable (const Model::DisassociateTrialComponentRequest &request) const
 
virtual void DisassociateTrialComponentAsync (const Model::DisassociateTrialComponentRequest &request, const DisassociateTrialComponentResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::GetSearchSuggestionsOutcome GetSearchSuggestions (const Model::GetSearchSuggestionsRequest &request) const
 
virtual Model::GetSearchSuggestionsOutcomeCallable GetSearchSuggestionsCallable (const Model::GetSearchSuggestionsRequest &request) const
 
virtual void GetSearchSuggestionsAsync (const Model::GetSearchSuggestionsRequest &request, const GetSearchSuggestionsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListAlgorithmsOutcome ListAlgorithms (const Model::ListAlgorithmsRequest &request) const
 
virtual Model::ListAlgorithmsOutcomeCallable ListAlgorithmsCallable (const Model::ListAlgorithmsRequest &request) const
 
virtual void ListAlgorithmsAsync (const Model::ListAlgorithmsRequest &request, const ListAlgorithmsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListAppImageConfigsOutcome ListAppImageConfigs (const Model::ListAppImageConfigsRequest &request) const
 
virtual Model::ListAppImageConfigsOutcomeCallable ListAppImageConfigsCallable (const Model::ListAppImageConfigsRequest &request) const
 
virtual void ListAppImageConfigsAsync (const Model::ListAppImageConfigsRequest &request, const ListAppImageConfigsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListAppsOutcome ListApps (const Model::ListAppsRequest &request) const
 
virtual Model::ListAppsOutcomeCallable ListAppsCallable (const Model::ListAppsRequest &request) const
 
virtual void ListAppsAsync (const Model::ListAppsRequest &request, const ListAppsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListAutoMLJobsOutcome ListAutoMLJobs (const Model::ListAutoMLJobsRequest &request) const
 
virtual Model::ListAutoMLJobsOutcomeCallable ListAutoMLJobsCallable (const Model::ListAutoMLJobsRequest &request) const
 
virtual void ListAutoMLJobsAsync (const Model::ListAutoMLJobsRequest &request, const ListAutoMLJobsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListCandidatesForAutoMLJobOutcome ListCandidatesForAutoMLJob (const Model::ListCandidatesForAutoMLJobRequest &request) const
 
virtual Model::ListCandidatesForAutoMLJobOutcomeCallable ListCandidatesForAutoMLJobCallable (const Model::ListCandidatesForAutoMLJobRequest &request) const
 
virtual void ListCandidatesForAutoMLJobAsync (const Model::ListCandidatesForAutoMLJobRequest &request, const ListCandidatesForAutoMLJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListCodeRepositoriesOutcome ListCodeRepositories (const Model::ListCodeRepositoriesRequest &request) const
 
virtual Model::ListCodeRepositoriesOutcomeCallable ListCodeRepositoriesCallable (const Model::ListCodeRepositoriesRequest &request) const
 
virtual void ListCodeRepositoriesAsync (const Model::ListCodeRepositoriesRequest &request, const ListCodeRepositoriesResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListCompilationJobsOutcome ListCompilationJobs (const Model::ListCompilationJobsRequest &request) const
 
virtual Model::ListCompilationJobsOutcomeCallable ListCompilationJobsCallable (const Model::ListCompilationJobsRequest &request) const
 
virtual void ListCompilationJobsAsync (const Model::ListCompilationJobsRequest &request, const ListCompilationJobsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListDomainsOutcome ListDomains (const Model::ListDomainsRequest &request) const
 
virtual Model::ListDomainsOutcomeCallable ListDomainsCallable (const Model::ListDomainsRequest &request) const
 
virtual void ListDomainsAsync (const Model::ListDomainsRequest &request, const ListDomainsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListEndpointConfigsOutcome ListEndpointConfigs (const Model::ListEndpointConfigsRequest &request) const
 
virtual Model::ListEndpointConfigsOutcomeCallable ListEndpointConfigsCallable (const Model::ListEndpointConfigsRequest &request) const
 
virtual void ListEndpointConfigsAsync (const Model::ListEndpointConfigsRequest &request, const ListEndpointConfigsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListEndpointsOutcome ListEndpoints (const Model::ListEndpointsRequest &request) const
 
virtual Model::ListEndpointsOutcomeCallable ListEndpointsCallable (const Model::ListEndpointsRequest &request) const
 
virtual void ListEndpointsAsync (const Model::ListEndpointsRequest &request, const ListEndpointsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListExperimentsOutcome ListExperiments (const Model::ListExperimentsRequest &request) const
 
virtual Model::ListExperimentsOutcomeCallable ListExperimentsCallable (const Model::ListExperimentsRequest &request) const
 
virtual void ListExperimentsAsync (const Model::ListExperimentsRequest &request, const ListExperimentsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListFlowDefinitionsOutcome ListFlowDefinitions (const Model::ListFlowDefinitionsRequest &request) const
 
virtual Model::ListFlowDefinitionsOutcomeCallable ListFlowDefinitionsCallable (const Model::ListFlowDefinitionsRequest &request) const
 
virtual void ListFlowDefinitionsAsync (const Model::ListFlowDefinitionsRequest &request, const ListFlowDefinitionsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListHumanTaskUisOutcome ListHumanTaskUis (const Model::ListHumanTaskUisRequest &request) const
 
virtual Model::ListHumanTaskUisOutcomeCallable ListHumanTaskUisCallable (const Model::ListHumanTaskUisRequest &request) const
 
virtual void ListHumanTaskUisAsync (const Model::ListHumanTaskUisRequest &request, const ListHumanTaskUisResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListHyperParameterTuningJobsOutcome ListHyperParameterTuningJobs (const Model::ListHyperParameterTuningJobsRequest &request) const
 
virtual Model::ListHyperParameterTuningJobsOutcomeCallable ListHyperParameterTuningJobsCallable (const Model::ListHyperParameterTuningJobsRequest &request) const
 
virtual void ListHyperParameterTuningJobsAsync (const Model::ListHyperParameterTuningJobsRequest &request, const ListHyperParameterTuningJobsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListImageVersionsOutcome ListImageVersions (const Model::ListImageVersionsRequest &request) const
 
virtual Model::ListImageVersionsOutcomeCallable ListImageVersionsCallable (const Model::ListImageVersionsRequest &request) const
 
virtual void ListImageVersionsAsync (const Model::ListImageVersionsRequest &request, const ListImageVersionsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListImagesOutcome ListImages (const Model::ListImagesRequest &request) const
 
virtual Model::ListImagesOutcomeCallable ListImagesCallable (const Model::ListImagesRequest &request) const
 
virtual void ListImagesAsync (const Model::ListImagesRequest &request, const ListImagesResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListLabelingJobsOutcome ListLabelingJobs (const Model::ListLabelingJobsRequest &request) const
 
virtual Model::ListLabelingJobsOutcomeCallable ListLabelingJobsCallable (const Model::ListLabelingJobsRequest &request) const
 
virtual void ListLabelingJobsAsync (const Model::ListLabelingJobsRequest &request, const ListLabelingJobsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListLabelingJobsForWorkteamOutcome ListLabelingJobsForWorkteam (const Model::ListLabelingJobsForWorkteamRequest &request) const
 
virtual Model::ListLabelingJobsForWorkteamOutcomeCallable ListLabelingJobsForWorkteamCallable (const Model::ListLabelingJobsForWorkteamRequest &request) const
 
virtual void ListLabelingJobsForWorkteamAsync (const Model::ListLabelingJobsForWorkteamRequest &request, const ListLabelingJobsForWorkteamResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListModelPackagesOutcome ListModelPackages (const Model::ListModelPackagesRequest &request) const
 
virtual Model::ListModelPackagesOutcomeCallable ListModelPackagesCallable (const Model::ListModelPackagesRequest &request) const
 
virtual void ListModelPackagesAsync (const Model::ListModelPackagesRequest &request, const ListModelPackagesResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListModelsOutcome ListModels (const Model::ListModelsRequest &request) const
 
virtual Model::ListModelsOutcomeCallable ListModelsCallable (const Model::ListModelsRequest &request) const
 
virtual void ListModelsAsync (const Model::ListModelsRequest &request, const ListModelsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListMonitoringExecutionsOutcome ListMonitoringExecutions (const Model::ListMonitoringExecutionsRequest &request) const
 
virtual Model::ListMonitoringExecutionsOutcomeCallable ListMonitoringExecutionsCallable (const Model::ListMonitoringExecutionsRequest &request) const
 
virtual void ListMonitoringExecutionsAsync (const Model::ListMonitoringExecutionsRequest &request, const ListMonitoringExecutionsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListMonitoringSchedulesOutcome ListMonitoringSchedules (const Model::ListMonitoringSchedulesRequest &request) const
 
virtual Model::ListMonitoringSchedulesOutcomeCallable ListMonitoringSchedulesCallable (const Model::ListMonitoringSchedulesRequest &request) const
 
virtual void ListMonitoringSchedulesAsync (const Model::ListMonitoringSchedulesRequest &request, const ListMonitoringSchedulesResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListNotebookInstanceLifecycleConfigsOutcome ListNotebookInstanceLifecycleConfigs (const Model::ListNotebookInstanceLifecycleConfigsRequest &request) const
 
virtual Model::ListNotebookInstanceLifecycleConfigsOutcomeCallable ListNotebookInstanceLifecycleConfigsCallable (const Model::ListNotebookInstanceLifecycleConfigsRequest &request) const
 
virtual void ListNotebookInstanceLifecycleConfigsAsync (const Model::ListNotebookInstanceLifecycleConfigsRequest &request, const ListNotebookInstanceLifecycleConfigsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListNotebookInstancesOutcome ListNotebookInstances (const Model::ListNotebookInstancesRequest &request) const
 
virtual Model::ListNotebookInstancesOutcomeCallable ListNotebookInstancesCallable (const Model::ListNotebookInstancesRequest &request) const
 
virtual void ListNotebookInstancesAsync (const Model::ListNotebookInstancesRequest &request, const ListNotebookInstancesResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListProcessingJobsOutcome ListProcessingJobs (const Model::ListProcessingJobsRequest &request) const
 
virtual Model::ListProcessingJobsOutcomeCallable ListProcessingJobsCallable (const Model::ListProcessingJobsRequest &request) const
 
virtual void ListProcessingJobsAsync (const Model::ListProcessingJobsRequest &request, const ListProcessingJobsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListSubscribedWorkteamsOutcome ListSubscribedWorkteams (const Model::ListSubscribedWorkteamsRequest &request) const
 
virtual Model::ListSubscribedWorkteamsOutcomeCallable ListSubscribedWorkteamsCallable (const Model::ListSubscribedWorkteamsRequest &request) const
 
virtual void ListSubscribedWorkteamsAsync (const Model::ListSubscribedWorkteamsRequest &request, const ListSubscribedWorkteamsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListTagsOutcome ListTags (const Model::ListTagsRequest &request) const
 
virtual Model::ListTagsOutcomeCallable ListTagsCallable (const Model::ListTagsRequest &request) const
 
virtual void ListTagsAsync (const Model::ListTagsRequest &request, const ListTagsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListTrainingJobsOutcome ListTrainingJobs (const Model::ListTrainingJobsRequest &request) const
 
virtual Model::ListTrainingJobsOutcomeCallable ListTrainingJobsCallable (const Model::ListTrainingJobsRequest &request) const
 
virtual void ListTrainingJobsAsync (const Model::ListTrainingJobsRequest &request, const ListTrainingJobsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListTrainingJobsForHyperParameterTuningJobOutcome ListTrainingJobsForHyperParameterTuningJob (const Model::ListTrainingJobsForHyperParameterTuningJobRequest &request) const
 
virtual Model::ListTrainingJobsForHyperParameterTuningJobOutcomeCallable ListTrainingJobsForHyperParameterTuningJobCallable (const Model::ListTrainingJobsForHyperParameterTuningJobRequest &request) const
 
virtual void ListTrainingJobsForHyperParameterTuningJobAsync (const Model::ListTrainingJobsForHyperParameterTuningJobRequest &request, const ListTrainingJobsForHyperParameterTuningJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListTransformJobsOutcome ListTransformJobs (const Model::ListTransformJobsRequest &request) const
 
virtual Model::ListTransformJobsOutcomeCallable ListTransformJobsCallable (const Model::ListTransformJobsRequest &request) const
 
virtual void ListTransformJobsAsync (const Model::ListTransformJobsRequest &request, const ListTransformJobsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListTrialComponentsOutcome ListTrialComponents (const Model::ListTrialComponentsRequest &request) const
 
virtual Model::ListTrialComponentsOutcomeCallable ListTrialComponentsCallable (const Model::ListTrialComponentsRequest &request) const
 
virtual void ListTrialComponentsAsync (const Model::ListTrialComponentsRequest &request, const ListTrialComponentsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListTrialsOutcome ListTrials (const Model::ListTrialsRequest &request) const
 
virtual Model::ListTrialsOutcomeCallable ListTrialsCallable (const Model::ListTrialsRequest &request) const
 
virtual void ListTrialsAsync (const Model::ListTrialsRequest &request, const ListTrialsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListUserProfilesOutcome ListUserProfiles (const Model::ListUserProfilesRequest &request) const
 
virtual Model::ListUserProfilesOutcomeCallable ListUserProfilesCallable (const Model::ListUserProfilesRequest &request) const
 
virtual void ListUserProfilesAsync (const Model::ListUserProfilesRequest &request, const ListUserProfilesResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListWorkforcesOutcome ListWorkforces (const Model::ListWorkforcesRequest &request) const
 
virtual Model::ListWorkforcesOutcomeCallable ListWorkforcesCallable (const Model::ListWorkforcesRequest &request) const
 
virtual void ListWorkforcesAsync (const Model::ListWorkforcesRequest &request, const ListWorkforcesResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::ListWorkteamsOutcome ListWorkteams (const Model::ListWorkteamsRequest &request) const
 
virtual Model::ListWorkteamsOutcomeCallable ListWorkteamsCallable (const Model::ListWorkteamsRequest &request) const
 
virtual void ListWorkteamsAsync (const Model::ListWorkteamsRequest &request, const ListWorkteamsResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::RenderUiTemplateOutcome RenderUiTemplate (const Model::RenderUiTemplateRequest &request) const
 
virtual Model::RenderUiTemplateOutcomeCallable RenderUiTemplateCallable (const Model::RenderUiTemplateRequest &request) const
 
virtual void RenderUiTemplateAsync (const Model::RenderUiTemplateRequest &request, const RenderUiTemplateResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::SearchOutcome Search (const Model::SearchRequest &request) const
 
virtual Model::SearchOutcomeCallable SearchCallable (const Model::SearchRequest &request) const
 
virtual void SearchAsync (const Model::SearchRequest &request, const SearchResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::StartMonitoringScheduleOutcome StartMonitoringSchedule (const Model::StartMonitoringScheduleRequest &request) const
 
virtual Model::StartMonitoringScheduleOutcomeCallable StartMonitoringScheduleCallable (const Model::StartMonitoringScheduleRequest &request) const
 
virtual void StartMonitoringScheduleAsync (const Model::StartMonitoringScheduleRequest &request, const StartMonitoringScheduleResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::StartNotebookInstanceOutcome StartNotebookInstance (const Model::StartNotebookInstanceRequest &request) const
 
virtual Model::StartNotebookInstanceOutcomeCallable StartNotebookInstanceCallable (const Model::StartNotebookInstanceRequest &request) const
 
virtual void StartNotebookInstanceAsync (const Model::StartNotebookInstanceRequest &request, const StartNotebookInstanceResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::StopAutoMLJobOutcome StopAutoMLJob (const Model::StopAutoMLJobRequest &request) const
 
virtual Model::StopAutoMLJobOutcomeCallable StopAutoMLJobCallable (const Model::StopAutoMLJobRequest &request) const
 
virtual void StopAutoMLJobAsync (const Model::StopAutoMLJobRequest &request, const StopAutoMLJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::StopCompilationJobOutcome StopCompilationJob (const Model::StopCompilationJobRequest &request) const
 
virtual Model::StopCompilationJobOutcomeCallable StopCompilationJobCallable (const Model::StopCompilationJobRequest &request) const
 
virtual void StopCompilationJobAsync (const Model::StopCompilationJobRequest &request, const StopCompilationJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::StopHyperParameterTuningJobOutcome StopHyperParameterTuningJob (const Model::StopHyperParameterTuningJobRequest &request) const
 
virtual Model::StopHyperParameterTuningJobOutcomeCallable StopHyperParameterTuningJobCallable (const Model::StopHyperParameterTuningJobRequest &request) const
 
virtual void StopHyperParameterTuningJobAsync (const Model::StopHyperParameterTuningJobRequest &request, const StopHyperParameterTuningJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::StopLabelingJobOutcome StopLabelingJob (const Model::StopLabelingJobRequest &request) const
 
virtual Model::StopLabelingJobOutcomeCallable StopLabelingJobCallable (const Model::StopLabelingJobRequest &request) const
 
virtual void StopLabelingJobAsync (const Model::StopLabelingJobRequest &request, const StopLabelingJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::StopMonitoringScheduleOutcome StopMonitoringSchedule (const Model::StopMonitoringScheduleRequest &request) const
 
virtual Model::StopMonitoringScheduleOutcomeCallable StopMonitoringScheduleCallable (const Model::StopMonitoringScheduleRequest &request) const
 
virtual void StopMonitoringScheduleAsync (const Model::StopMonitoringScheduleRequest &request, const StopMonitoringScheduleResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::StopNotebookInstanceOutcome StopNotebookInstance (const Model::StopNotebookInstanceRequest &request) const
 
virtual Model::StopNotebookInstanceOutcomeCallable StopNotebookInstanceCallable (const Model::StopNotebookInstanceRequest &request) const
 
virtual void StopNotebookInstanceAsync (const Model::StopNotebookInstanceRequest &request, const StopNotebookInstanceResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::StopProcessingJobOutcome StopProcessingJob (const Model::StopProcessingJobRequest &request) const
 
virtual Model::StopProcessingJobOutcomeCallable StopProcessingJobCallable (const Model::StopProcessingJobRequest &request) const
 
virtual void StopProcessingJobAsync (const Model::StopProcessingJobRequest &request, const StopProcessingJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::StopTrainingJobOutcome StopTrainingJob (const Model::StopTrainingJobRequest &request) const
 
virtual Model::StopTrainingJobOutcomeCallable StopTrainingJobCallable (const Model::StopTrainingJobRequest &request) const
 
virtual void StopTrainingJobAsync (const Model::StopTrainingJobRequest &request, const StopTrainingJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::StopTransformJobOutcome StopTransformJob (const Model::StopTransformJobRequest &request) const
 
virtual Model::StopTransformJobOutcomeCallable StopTransformJobCallable (const Model::StopTransformJobRequest &request) const
 
virtual void StopTransformJobAsync (const Model::StopTransformJobRequest &request, const StopTransformJobResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateAppImageConfigOutcome UpdateAppImageConfig (const Model::UpdateAppImageConfigRequest &request) const
 
virtual Model::UpdateAppImageConfigOutcomeCallable UpdateAppImageConfigCallable (const Model::UpdateAppImageConfigRequest &request) const
 
virtual void UpdateAppImageConfigAsync (const Model::UpdateAppImageConfigRequest &request, const UpdateAppImageConfigResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateCodeRepositoryOutcome UpdateCodeRepository (const Model::UpdateCodeRepositoryRequest &request) const
 
virtual Model::UpdateCodeRepositoryOutcomeCallable UpdateCodeRepositoryCallable (const Model::UpdateCodeRepositoryRequest &request) const
 
virtual void UpdateCodeRepositoryAsync (const Model::UpdateCodeRepositoryRequest &request, const UpdateCodeRepositoryResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateDomainOutcome UpdateDomain (const Model::UpdateDomainRequest &request) const
 
virtual Model::UpdateDomainOutcomeCallable UpdateDomainCallable (const Model::UpdateDomainRequest &request) const
 
virtual void UpdateDomainAsync (const Model::UpdateDomainRequest &request, const UpdateDomainResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateEndpointOutcome UpdateEndpoint (const Model::UpdateEndpointRequest &request) const
 
virtual Model::UpdateEndpointOutcomeCallable UpdateEndpointCallable (const Model::UpdateEndpointRequest &request) const
 
virtual void UpdateEndpointAsync (const Model::UpdateEndpointRequest &request, const UpdateEndpointResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateEndpointWeightsAndCapacitiesOutcome UpdateEndpointWeightsAndCapacities (const Model::UpdateEndpointWeightsAndCapacitiesRequest &request) const
 
virtual Model::UpdateEndpointWeightsAndCapacitiesOutcomeCallable UpdateEndpointWeightsAndCapacitiesCallable (const Model::UpdateEndpointWeightsAndCapacitiesRequest &request) const
 
virtual void UpdateEndpointWeightsAndCapacitiesAsync (const Model::UpdateEndpointWeightsAndCapacitiesRequest &request, const UpdateEndpointWeightsAndCapacitiesResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateExperimentOutcome UpdateExperiment (const Model::UpdateExperimentRequest &request) const
 
virtual Model::UpdateExperimentOutcomeCallable UpdateExperimentCallable (const Model::UpdateExperimentRequest &request) const
 
virtual void UpdateExperimentAsync (const Model::UpdateExperimentRequest &request, const UpdateExperimentResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateImageOutcome UpdateImage (const Model::UpdateImageRequest &request) const
 
virtual Model::UpdateImageOutcomeCallable UpdateImageCallable (const Model::UpdateImageRequest &request) const
 
virtual void UpdateImageAsync (const Model::UpdateImageRequest &request, const UpdateImageResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateMonitoringScheduleOutcome UpdateMonitoringSchedule (const Model::UpdateMonitoringScheduleRequest &request) const
 
virtual Model::UpdateMonitoringScheduleOutcomeCallable UpdateMonitoringScheduleCallable (const Model::UpdateMonitoringScheduleRequest &request) const
 
virtual void UpdateMonitoringScheduleAsync (const Model::UpdateMonitoringScheduleRequest &request, const UpdateMonitoringScheduleResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateNotebookInstanceOutcome UpdateNotebookInstance (const Model::UpdateNotebookInstanceRequest &request) const
 
virtual Model::UpdateNotebookInstanceOutcomeCallable UpdateNotebookInstanceCallable (const Model::UpdateNotebookInstanceRequest &request) const
 
virtual void UpdateNotebookInstanceAsync (const Model::UpdateNotebookInstanceRequest &request, const UpdateNotebookInstanceResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateNotebookInstanceLifecycleConfigOutcome UpdateNotebookInstanceLifecycleConfig (const Model::UpdateNotebookInstanceLifecycleConfigRequest &request) const
 
virtual Model::UpdateNotebookInstanceLifecycleConfigOutcomeCallable UpdateNotebookInstanceLifecycleConfigCallable (const Model::UpdateNotebookInstanceLifecycleConfigRequest &request) const
 
virtual void UpdateNotebookInstanceLifecycleConfigAsync (const Model::UpdateNotebookInstanceLifecycleConfigRequest &request, const UpdateNotebookInstanceLifecycleConfigResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateTrialOutcome UpdateTrial (const Model::UpdateTrialRequest &request) const
 
virtual Model::UpdateTrialOutcomeCallable UpdateTrialCallable (const Model::UpdateTrialRequest &request) const
 
virtual void UpdateTrialAsync (const Model::UpdateTrialRequest &request, const UpdateTrialResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateTrialComponentOutcome UpdateTrialComponent (const Model::UpdateTrialComponentRequest &request) const
 
virtual Model::UpdateTrialComponentOutcomeCallable UpdateTrialComponentCallable (const Model::UpdateTrialComponentRequest &request) const
 
virtual void UpdateTrialComponentAsync (const Model::UpdateTrialComponentRequest &request, const UpdateTrialComponentResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateUserProfileOutcome UpdateUserProfile (const Model::UpdateUserProfileRequest &request) const
 
virtual Model::UpdateUserProfileOutcomeCallable UpdateUserProfileCallable (const Model::UpdateUserProfileRequest &request) const
 
virtual void UpdateUserProfileAsync (const Model::UpdateUserProfileRequest &request, const UpdateUserProfileResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateWorkforceOutcome UpdateWorkforce (const Model::UpdateWorkforceRequest &request) const
 
virtual Model::UpdateWorkforceOutcomeCallable UpdateWorkforceCallable (const Model::UpdateWorkforceRequest &request) const
 
virtual void UpdateWorkforceAsync (const Model::UpdateWorkforceRequest &request, const UpdateWorkforceResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
virtual Model::UpdateWorkteamOutcome UpdateWorkteam (const Model::UpdateWorkteamRequest &request) const
 
virtual Model::UpdateWorkteamOutcomeCallable UpdateWorkteamCallable (const Model::UpdateWorkteamRequest &request) const
 
virtual void UpdateWorkteamAsync (const Model::UpdateWorkteamRequest &request, const UpdateWorkteamResponseReceivedHandler &handler, const std::shared_ptr< const Aws::Client::AsyncCallerContext > &context=nullptr) const
 
void OverrideEndpoint (const Aws::String &endpoint)
 
- Public Member Functions inherited from Aws::Client::AWSJsonClient
 AWSJsonClient (const Aws::Client::ClientConfiguration &configuration, const std::shared_ptr< Aws::Client::AWSAuthSigner > &signer, const std::shared_ptr< AWSErrorMarshaller > &errorMarshaller)
 
 AWSJsonClient (const Aws::Client::ClientConfiguration &configuration, const std::shared_ptr< Aws::Auth::AWSAuthSignerProvider > &signerProvider, const std::shared_ptr< AWSErrorMarshaller > &errorMarshaller)
 
virtual ~AWSJsonClient ()=default
 
- Public Member Functions inherited from Aws::Client::AWSClient
 AWSClient (const Aws::Client::ClientConfiguration &configuration, const std::shared_ptr< Aws::Client::AWSAuthSigner > &signer, const std::shared_ptr< AWSErrorMarshaller > &errorMarshaller)
 
 AWSClient (const Aws::Client::ClientConfiguration &configuration, const std::shared_ptr< Aws::Auth::AWSAuthSignerProvider > &signerProvider, const std::shared_ptr< AWSErrorMarshaller > &errorMarshaller)
 
virtual ~AWSClient ()
 
Aws::String GeneratePresignedUrl (Aws::Http::URI &uri, Aws::Http::HttpMethod method, long long expirationInSeconds=0)
 
Aws::String GeneratePresignedUrl (Aws::Http::URI &uri, Aws::Http::HttpMethod method, const Aws::Http::HeaderValueCollection &customizedHeaders, long long expirationInSeconds=0)
 
Aws::String GeneratePresignedUrl (Aws::Http::URI &uri, Aws::Http::HttpMethod method, const char *region, long long expirationInSeconds=0) const
 
Aws::String GeneratePresignedUrl (Aws::Http::URI &uri, Aws::Http::HttpMethod method, const char *region, const Aws::Http::HeaderValueCollection &customizedHeaders, long long expirationInSeconds=0)
 
Aws::String GeneratePresignedUrl (Aws::Http::URI &uri, Aws::Http::HttpMethod method, const char *region, const char *serviceName, long long expirationInSeconds=0) const
 
Aws::String GeneratePresignedUrl (Aws::Http::URI &uri, Aws::Http::HttpMethod method, const char *region, const char *serviceName, const Aws::Http::HeaderValueCollection &customizedHeaders, long long expirationInSeconds=0)
 
Aws::String GeneratePresignedUrl (const Aws::AmazonWebServiceRequest &request, Aws::Http::URI &uri, Aws::Http::HttpMethod method, const Aws::Http::QueryStringParameterCollection &extraParams=Aws::Http::QueryStringParameterCollection(), long long expirationInSeconds=0) const
 
Aws::String GeneratePresignedUrl (const Aws::AmazonWebServiceRequest &request, Aws::Http::URI &uri, Aws::Http::HttpMethod method, const char *region, const char *serviceName, const Aws::Http::QueryStringParameterCollection &extraParams=Aws::Http::QueryStringParameterCollection(), long long expirationInSeconds=0) const
 
Aws::String GeneratePresignedUrl (const Aws::AmazonWebServiceRequest &request, Aws::Http::URI &uri, Aws::Http::HttpMethod method, const char *region, const Aws::Http::QueryStringParameterCollection &extraParams=Aws::Http::QueryStringParameterCollection(), long long expirationInSeconds=0) const
 
void DisableRequestProcessing ()
 
void EnableRequestProcessing ()
 
virtual const char * GetServiceClientName () const
 
virtual void SetServiceClientName (const Aws::String &name)
 

Additional Inherited Members

- Protected Member Functions inherited from Aws::Client::AWSJsonClient
virtual AWSError< CoreErrorsBuildAWSError (const std::shared_ptr< Aws::Http::HttpResponse > &response) const override
 
JsonOutcome MakeRequest (const Aws::Http::URI &uri, const Aws::AmazonWebServiceRequest &request, Http::HttpMethod method=Http::HttpMethod::HTTP_POST, const char *signerName=Aws::Auth::SIGV4_SIGNER, const char *signerRegionOverride=nullptr, const char *signerServiceNameOverride=nullptr) const
 
JsonOutcome MakeRequest (const Aws::Http::URI &uri, Http::HttpMethod method=Http::HttpMethod::HTTP_POST, const char *signerName=Aws::Auth::SIGV4_SIGNER, const char *requestName="", const char *signerRegionOverride=nullptr, const char *signerServiceNameOverride=nullptr) const
 
JsonOutcome MakeEventStreamRequest (std::shared_ptr< Aws::Http::HttpRequest > &request) const
 
- Protected Member Functions inherited from Aws::Client::AWSClient
HttpResponseOutcome AttemptExhaustively (const Aws::Http::URI &uri, const Aws::AmazonWebServiceRequest &request, Http::HttpMethod httpMethod, const char *signerName, const char *signerRegionOverride=nullptr, const char *signerServiceNameOverride=nullptr) const
 
HttpResponseOutcome AttemptExhaustively (const Aws::Http::URI &uri, Http::HttpMethod httpMethod, const char *signerName, const char *requestName="", const char *signerRegionOverride=nullptr, const char *signerServiceNameOverride=nullptr) const
 
HttpResponseOutcome AttemptOneRequest (const std::shared_ptr< Http::HttpRequest > &httpRequest, const Aws::AmazonWebServiceRequest &request, const char *signerName, const char *signerRegionOverride=nullptr, const char *signerServiceNameOverride=nullptr) const
 
HttpResponseOutcome AttemptOneRequest (const std::shared_ptr< Http::HttpRequest > &httpRequest, const char *signerName, const char *requestName="", const char *signerRegionOverride=nullptr, const char *signerServiceNameOverride=nullptr) const
 
StreamOutcome MakeRequestWithUnparsedResponse (const Aws::Http::URI &uri, const Aws::AmazonWebServiceRequest &request, Http::HttpMethod method=Http::HttpMethod::HTTP_POST, const char *signerName=Aws::Auth::SIGV4_SIGNER, const char *signerRegionOverride=nullptr, const char *signerServiceNameOverride=nullptr) const
 
StreamOutcome MakeRequestWithUnparsedResponse (const Aws::Http::URI &uri, Http::HttpMethod method=Http::HttpMethod::HTTP_POST, const char *signerName=Aws::Auth::SIGV4_SIGNER, const char *requestName="", const char *signerRegionOverride=nullptr, const char *signerServiceNameOverride=nullptr) const
 
virtual void BuildHttpRequest (const Aws::AmazonWebServiceRequest &request, const std::shared_ptr< Aws::Http::HttpRequest > &httpRequest) const
 
const std::shared_ptr< AWSErrorMarshaller > & GetErrorMarshaller () const
 
Aws::Client::AWSAuthSignerGetSignerByName (const char *name) const
 
std::shared_ptr< Aws::Http::HttpRequestBuildAndSignHttpRequest (const Aws::Http::URI &uri, const Aws::AmazonWebServiceRequest &request, Http::HttpMethod method, const char *signerName) const
 
std::shared_ptr< Aws::Http::HttpResponseMakeHttpRequest (std::shared_ptr< Aws::Http::HttpRequest > &request) const
 
- Protected Attributes inherited from Aws::Client::AWSClient
Aws::String m_region
 

Detailed Description

Provides APIs for creating and managing Amazon SageMaker resources.

Other Resources:

Definition at line 800 of file SageMakerClient.h.

Member Typedef Documentation

◆ BASECLASS

Definition at line 803 of file SageMakerClient.h.

Constructor & Destructor Documentation

◆ SageMakerClient() [1/3]

Aws::SageMaker::SageMakerClient::SageMakerClient ( const Aws::Client::ClientConfiguration clientConfiguration = Aws::Client::ClientConfiguration())

Initializes client to use DefaultCredentialProviderChain, with default http client factory, and optional client config. If client config is not specified, it will be initialized to default values.

◆ SageMakerClient() [2/3]

Aws::SageMaker::SageMakerClient::SageMakerClient ( const Aws::Auth::AWSCredentials credentials,
const Aws::Client::ClientConfiguration clientConfiguration = Aws::Client::ClientConfiguration() 
)

Initializes client to use SimpleAWSCredentialsProvider, with default http client factory, and optional client config. If client config is not specified, it will be initialized to default values.

◆ SageMakerClient() [3/3]

Aws::SageMaker::SageMakerClient::SageMakerClient ( const std::shared_ptr< Aws::Auth::AWSCredentialsProvider > &  credentialsProvider,
const Aws::Client::ClientConfiguration clientConfiguration = Aws::Client::ClientConfiguration() 
)

Initializes client to use specified credentials provider with specified client config. If http client factory is not supplied, the default http client factory will be used

◆ ~SageMakerClient()

virtual Aws::SageMaker::SageMakerClient::~SageMakerClient ( )
virtual

Member Function Documentation

◆ AddTags()

virtual Model::AddTagsOutcome Aws::SageMaker::SageMakerClient::AddTags ( const Model::AddTagsRequest request) const
virtual

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

See Also:

AWS API Reference

◆ AddTagsAsync()

virtual void Aws::SageMaker::SageMakerClient::AddTagsAsync ( const Model::AddTagsRequest request,
const AddTagsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ AddTagsCallable()

virtual Model::AddTagsOutcomeCallable Aws::SageMaker::SageMakerClient::AddTagsCallable ( const Model::AddTagsRequest request) const
virtual

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

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ AssociateTrialComponent()

virtual Model::AssociateTrialComponentOutcome Aws::SageMaker::SageMakerClient::AssociateTrialComponent ( const Model::AssociateTrialComponentRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ AssociateTrialComponentAsync()

virtual void Aws::SageMaker::SageMakerClient::AssociateTrialComponentAsync ( const Model::AssociateTrialComponentRequest request,
const AssociateTrialComponentResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ AssociateTrialComponentCallable()

virtual Model::AssociateTrialComponentOutcomeCallable Aws::SageMaker::SageMakerClient::AssociateTrialComponentCallable ( const Model::AssociateTrialComponentRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateAlgorithm()

virtual Model::CreateAlgorithmOutcome Aws::SageMaker::SageMakerClient::CreateAlgorithm ( const Model::CreateAlgorithmRequest request) const
virtual

Create a machine learning algorithm that you can use in Amazon SageMaker and list in the AWS Marketplace.

See Also:

AWS API Reference

◆ CreateAlgorithmAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateAlgorithmAsync ( const Model::CreateAlgorithmRequest request,
const CreateAlgorithmResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Create a machine learning algorithm that you can use in Amazon SageMaker and list in the AWS Marketplace.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateAlgorithmCallable()

virtual Model::CreateAlgorithmOutcomeCallable Aws::SageMaker::SageMakerClient::CreateAlgorithmCallable ( const Model::CreateAlgorithmRequest request) const
virtual

Create a machine learning algorithm that you can use in Amazon SageMaker and list in the AWS Marketplace.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateApp()

virtual Model::CreateAppOutcome Aws::SageMaker::SageMakerClient::CreateApp ( const Model::CreateAppRequest request) const
virtual

Creates a running App for the specified UserProfile. Supported Apps are JupyterServer and KernelGateway. This operation is automatically invoked by Amazon SageMaker Studio upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.

See Also:

AWS API Reference

◆ CreateAppAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateAppAsync ( const Model::CreateAppRequest request,
const CreateAppResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates a running App for the specified UserProfile. Supported Apps are JupyterServer and KernelGateway. This operation is automatically invoked by Amazon SageMaker Studio upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateAppCallable()

virtual Model::CreateAppOutcomeCallable Aws::SageMaker::SageMakerClient::CreateAppCallable ( const Model::CreateAppRequest request) const
virtual

Creates a running App for the specified UserProfile. Supported Apps are JupyterServer and KernelGateway. This operation is automatically invoked by Amazon SageMaker Studio upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateAppImageConfig()

virtual Model::CreateAppImageConfigOutcome Aws::SageMaker::SageMakerClient::CreateAppImageConfig ( const Model::CreateAppImageConfigRequest request) const
virtual

Creates a configuration for running a SageMaker image as a KernelGateway app. The configuration specifies the Amazon Elastic File System (EFS) storage volume on the image, and a list of the kernels in the image.

See Also:

AWS API Reference

◆ CreateAppImageConfigAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateAppImageConfigAsync ( const Model::CreateAppImageConfigRequest request,
const CreateAppImageConfigResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates a configuration for running a SageMaker image as a KernelGateway app. The configuration specifies the Amazon Elastic File System (EFS) storage volume on the image, and a list of the kernels in the image.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateAppImageConfigCallable()

virtual Model::CreateAppImageConfigOutcomeCallable Aws::SageMaker::SageMakerClient::CreateAppImageConfigCallable ( const Model::CreateAppImageConfigRequest request) const
virtual

Creates a configuration for running a SageMaker image as a KernelGateway app. The configuration specifies the Amazon Elastic File System (EFS) storage volume on the image, and a list of the kernels in the image.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateAutoMLJob()

virtual Model::CreateAutoMLJobOutcome Aws::SageMaker::SageMakerClient::CreateAutoMLJob ( const Model::CreateAutoMLJobRequest request) const
virtual

Creates an Autopilot job.

Find the best performing model after you run an Autopilot job by calling . Deploy that model by following the steps described in Step 6.1: Deploy the Model to Amazon SageMaker Hosting Services.

For information about how to use Autopilot, see Automate Model Development with Amazon SageMaker Autopilot.

See Also:

AWS API Reference

◆ CreateAutoMLJobAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateAutoMLJobAsync ( const Model::CreateAutoMLJobRequest request,
const CreateAutoMLJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates an Autopilot job.

Find the best performing model after you run an Autopilot job by calling . Deploy that model by following the steps described in Step 6.1: Deploy the Model to Amazon SageMaker Hosting Services.

For information about how to use Autopilot, see Automate Model Development with Amazon SageMaker Autopilot.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateAutoMLJobCallable()

virtual Model::CreateAutoMLJobOutcomeCallable Aws::SageMaker::SageMakerClient::CreateAutoMLJobCallable ( const Model::CreateAutoMLJobRequest request) const
virtual

Creates an Autopilot job.

Find the best performing model after you run an Autopilot job by calling . Deploy that model by following the steps described in Step 6.1: Deploy the Model to Amazon SageMaker Hosting Services.

For information about how to use Autopilot, see Automate Model Development with Amazon SageMaker Autopilot.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateCodeRepository()

virtual Model::CreateCodeRepositoryOutcome Aws::SageMaker::SageMakerClient::CreateCodeRepository ( const Model::CreateCodeRepositoryRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ CreateCodeRepositoryAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateCodeRepositoryAsync ( const Model::CreateCodeRepositoryRequest request,
const CreateCodeRepositoryResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateCodeRepositoryCallable()

virtual Model::CreateCodeRepositoryOutcomeCallable Aws::SageMaker::SageMakerClient::CreateCodeRepositoryCallable ( const Model::CreateCodeRepositoryRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateCompilationJob()

virtual Model::CreateCompilationJobOutcome Aws::SageMaker::SageMakerClient::CreateCompilationJob ( const Model::CreateCompilationJobRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ CreateCompilationJobAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateCompilationJobAsync ( const Model::CreateCompilationJobRequest request,
const CreateCompilationJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateCompilationJobCallable()

virtual Model::CreateCompilationJobOutcomeCallable Aws::SageMaker::SageMakerClient::CreateCompilationJobCallable ( const Model::CreateCompilationJobRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateDomain()

virtual Model::CreateDomainOutcome Aws::SageMaker::SageMakerClient::CreateDomain ( const Model::CreateDomainRequest request) const
virtual

Creates a Domain used by Amazon SageMaker Studio. A domain consists of an associated Amazon Elastic File System (EFS) volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. An AWS account is limited to one domain per region. Users within a domain can share notebook files and other artifacts with each other.

When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.

VPC configuration

All SageMaker Studio traffic between the domain and the EFS volume is through the specified VPC and subnets. For other Studio traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to Studio. The following options are available:

  • PublicInternetOnly - Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.

  • VpcOnly - All Studio traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.

    When internet access is disabled, you won't be able to run a Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.

For more information, see Connect SageMaker Studio Notebooks to Resources in a VPC.

See Also:

AWS API Reference

◆ CreateDomainAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateDomainAsync ( const Model::CreateDomainRequest request,
const CreateDomainResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates a Domain used by Amazon SageMaker Studio. A domain consists of an associated Amazon Elastic File System (EFS) volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. An AWS account is limited to one domain per region. Users within a domain can share notebook files and other artifacts with each other.

When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.

VPC configuration

All SageMaker Studio traffic between the domain and the EFS volume is through the specified VPC and subnets. For other Studio traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to Studio. The following options are available:

  • PublicInternetOnly - Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.

  • VpcOnly - All Studio traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.

    When internet access is disabled, you won't be able to run a Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.

For more information, see Connect SageMaker Studio Notebooks to Resources in a VPC.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateDomainCallable()

virtual Model::CreateDomainOutcomeCallable Aws::SageMaker::SageMakerClient::CreateDomainCallable ( const Model::CreateDomainRequest request) const
virtual

Creates a Domain used by Amazon SageMaker Studio. A domain consists of an associated Amazon Elastic File System (EFS) volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. An AWS account is limited to one domain per region. Users within a domain can share notebook files and other artifacts with each other.

When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.

VPC configuration

All SageMaker Studio traffic between the domain and the EFS volume is through the specified VPC and subnets. For other Studio traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to Studio. The following options are available:

  • PublicInternetOnly - Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.

  • VpcOnly - All Studio traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.

    When internet access is disabled, you won't be able to run a Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.

For more information, see Connect SageMaker Studio Notebooks to Resources in a VPC.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateEndpoint()

virtual Model::CreateEndpointOutcome Aws::SageMaker::SageMakerClient::CreateEndpoint ( const Model::CreateEndpointRequest request) const
virtual

Creates an endpoint using the endpoint configuration specified in the request. Amazon SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API.

Use this API to deploy models using Amazon SageMaker hosting services.

For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)).

You must not delete an EndpointConfig that is in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig.

The endpoint name must be unique within an AWS Region in your AWS account.

When it receives the request, Amazon SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them.

When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.

When Amazon SageMaker receives the request, it sets the endpoint status to Creating. After it creates the endpoint, it sets the status to InService. Amazon SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API.

If any of the models hosted at this endpoint get model data from an Amazon S3 location, Amazon SageMaker uses AWS Security Token Service to download model artifacts from the S3 path you provided. AWS STS is activated in your IAM user account by default. If you previously deactivated AWS STS for a region, you need to reactivate AWS STS for that region. For more information, see Activating and Deactivating AWS STS in an AWS Region in the AWS Identity and Access Management User Guide.

To add the IAM role policies for using this API operation, go to the IAM console, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the role.

  • Option 1: For a full Amazon SageMaker access, search and attach the AmazonSageMakerFullAccess policy.

  • Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role:

    "Action": ["sagemaker:CreateEndpoint", "sagemaker:CreateEndpointConfig"]

    "Resource": [

    "arn:aws:sagemaker:region:account-id:endpoint/endpointName"

    "arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"

    ]

    For more information, see Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference.

See Also:

AWS API Reference

◆ CreateEndpointAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateEndpointAsync ( const Model::CreateEndpointRequest request,
const CreateEndpointResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates an endpoint using the endpoint configuration specified in the request. Amazon SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API.

Use this API to deploy models using Amazon SageMaker hosting services.

For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)).

You must not delete an EndpointConfig that is in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig.

The endpoint name must be unique within an AWS Region in your AWS account.

When it receives the request, Amazon SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them.

When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.

When Amazon SageMaker receives the request, it sets the endpoint status to Creating. After it creates the endpoint, it sets the status to InService. Amazon SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API.

If any of the models hosted at this endpoint get model data from an Amazon S3 location, Amazon SageMaker uses AWS Security Token Service to download model artifacts from the S3 path you provided. AWS STS is activated in your IAM user account by default. If you previously deactivated AWS STS for a region, you need to reactivate AWS STS for that region. For more information, see Activating and Deactivating AWS STS in an AWS Region in the AWS Identity and Access Management User Guide.

To add the IAM role policies for using this API operation, go to the IAM console, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the role.

  • Option 1: For a full Amazon SageMaker access, search and attach the AmazonSageMakerFullAccess policy.

  • Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role:

    "Action": ["sagemaker:CreateEndpoint", "sagemaker:CreateEndpointConfig"]

    "Resource": [

    "arn:aws:sagemaker:region:account-id:endpoint/endpointName"

    "arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"

    ]

    For more information, see Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateEndpointCallable()

virtual Model::CreateEndpointOutcomeCallable Aws::SageMaker::SageMakerClient::CreateEndpointCallable ( const Model::CreateEndpointRequest request) const
virtual

Creates an endpoint using the endpoint configuration specified in the request. Amazon SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API.

Use this API to deploy models using Amazon SageMaker hosting services.

For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)).

You must not delete an EndpointConfig that is in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig.

The endpoint name must be unique within an AWS Region in your AWS account.

When it receives the request, Amazon SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them.

When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.

When Amazon SageMaker receives the request, it sets the endpoint status to Creating. After it creates the endpoint, it sets the status to InService. Amazon SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API.

If any of the models hosted at this endpoint get model data from an Amazon S3 location, Amazon SageMaker uses AWS Security Token Service to download model artifacts from the S3 path you provided. AWS STS is activated in your IAM user account by default. If you previously deactivated AWS STS for a region, you need to reactivate AWS STS for that region. For more information, see Activating and Deactivating AWS STS in an AWS Region in the AWS Identity and Access Management User Guide.

To add the IAM role policies for using this API operation, go to the IAM console, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the role.

  • Option 1: For a full Amazon SageMaker access, search and attach the AmazonSageMakerFullAccess policy.

  • Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role:

    "Action": ["sagemaker:CreateEndpoint", "sagemaker:CreateEndpointConfig"]

    "Resource": [

    "arn:aws:sagemaker:region:account-id:endpoint/endpointName"

    "arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"

    ]

    For more information, see Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateEndpointConfig()

virtual Model::CreateEndpointConfigOutcome Aws::SageMaker::SageMakerClient::CreateEndpointConfig ( const Model::CreateEndpointConfigRequest request) const
virtual

Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want Amazon SageMaker to provision. Then you call the CreateEndpoint API.

Use this API if you want to use Amazon SageMaker hosting services to deploy models into production.

In the request, you define a ProductionVariant, for each model that you want to deploy. Each ProductionVariant parameter also describes the resources that you want Amazon SageMaker to provision. This includes the number and type of ML compute instances to deploy.

If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. Amazon SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.

For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)).

When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.

See Also:

AWS API Reference

◆ CreateEndpointConfigAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateEndpointConfigAsync ( const Model::CreateEndpointConfigRequest request,
const CreateEndpointConfigResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want Amazon SageMaker to provision. Then you call the CreateEndpoint API.

Use this API if you want to use Amazon SageMaker hosting services to deploy models into production.

In the request, you define a ProductionVariant, for each model that you want to deploy. Each ProductionVariant parameter also describes the resources that you want Amazon SageMaker to provision. This includes the number and type of ML compute instances to deploy.

If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. Amazon SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.

For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)).

When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateEndpointConfigCallable()

virtual Model::CreateEndpointConfigOutcomeCallable Aws::SageMaker::SageMakerClient::CreateEndpointConfigCallable ( const Model::CreateEndpointConfigRequest request) const
virtual

Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want Amazon SageMaker to provision. Then you call the CreateEndpoint API.

Use this API if you want to use Amazon SageMaker hosting services to deploy models into production.

In the request, you define a ProductionVariant, for each model that you want to deploy. Each ProductionVariant parameter also describes the resources that you want Amazon SageMaker to provision. This includes the number and type of ML compute instances to deploy.

If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. Amazon SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.

For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)).

When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateExperiment()

virtual Model::CreateExperimentOutcome Aws::SageMaker::SageMakerClient::CreateExperiment ( const Model::CreateExperimentRequest request) const
virtual

Creates an SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.

The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.

When you use Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK.

You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.

To add a description to an experiment, specify the optional Description parameter. To add a description later, or to change the description, call the UpdateExperiment API.

To get a list of all your experiments, call the ListExperiments API. To view an experiment's properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.

See Also:

AWS API Reference

◆ CreateExperimentAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateExperimentAsync ( const Model::CreateExperimentRequest request,
const CreateExperimentResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates an SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.

The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.

When you use Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK.

You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.

To add a description to an experiment, specify the optional Description parameter. To add a description later, or to change the description, call the UpdateExperiment API.

To get a list of all your experiments, call the ListExperiments API. To view an experiment's properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateExperimentCallable()

virtual Model::CreateExperimentOutcomeCallable Aws::SageMaker::SageMakerClient::CreateExperimentCallable ( const Model::CreateExperimentRequest request) const
virtual

Creates an SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.

The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.

When you use Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK.

You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.

To add a description to an experiment, specify the optional Description parameter. To add a description later, or to change the description, call the UpdateExperiment API.

To get a list of all your experiments, call the ListExperiments API. To view an experiment's properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateFlowDefinition()

virtual Model::CreateFlowDefinitionOutcome Aws::SageMaker::SageMakerClient::CreateFlowDefinition ( const Model::CreateFlowDefinitionRequest request) const
virtual

Creates a flow definition.

See Also:

AWS API Reference

◆ CreateFlowDefinitionAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateFlowDefinitionAsync ( const Model::CreateFlowDefinitionRequest request,
const CreateFlowDefinitionResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates a flow definition.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateFlowDefinitionCallable()

virtual Model::CreateFlowDefinitionOutcomeCallable Aws::SageMaker::SageMakerClient::CreateFlowDefinitionCallable ( const Model::CreateFlowDefinitionRequest request) const
virtual

Creates a flow definition.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateHumanTaskUi()

virtual Model::CreateHumanTaskUiOutcome Aws::SageMaker::SageMakerClient::CreateHumanTaskUi ( const Model::CreateHumanTaskUiRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ CreateHumanTaskUiAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateHumanTaskUiAsync ( const Model::CreateHumanTaskUiRequest request,
const CreateHumanTaskUiResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateHumanTaskUiCallable()

virtual Model::CreateHumanTaskUiOutcomeCallable Aws::SageMaker::SageMakerClient::CreateHumanTaskUiCallable ( const Model::CreateHumanTaskUiRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateHyperParameterTuningJob()

virtual Model::CreateHyperParameterTuningJobOutcome Aws::SageMaker::SageMakerClient::CreateHyperParameterTuningJob ( const Model::CreateHyperParameterTuningJobRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ CreateHyperParameterTuningJobAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateHyperParameterTuningJobAsync ( const Model::CreateHyperParameterTuningJobRequest request,
const CreateHyperParameterTuningJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateHyperParameterTuningJobCallable()

virtual Model::CreateHyperParameterTuningJobOutcomeCallable Aws::SageMaker::SageMakerClient::CreateHyperParameterTuningJobCallable ( const Model::CreateHyperParameterTuningJobRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateImage()

virtual Model::CreateImageOutcome Aws::SageMaker::SageMakerClient::CreateImage ( const Model::CreateImageRequest request) const
virtual

Creates a custom SageMaker image. A SageMaker image is a set of image versions. Each image version represents a container image stored in Amazon Container Registry (ECR). For more information, see Bring your own SageMaker image.

See Also:

AWS API Reference

◆ CreateImageAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateImageAsync ( const Model::CreateImageRequest request,
const CreateImageResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates a custom SageMaker image. A SageMaker image is a set of image versions. Each image version represents a container image stored in Amazon Container Registry (ECR). For more information, see Bring your own SageMaker image.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateImageCallable()

virtual Model::CreateImageOutcomeCallable Aws::SageMaker::SageMakerClient::CreateImageCallable ( const Model::CreateImageRequest request) const
virtual

Creates a custom SageMaker image. A SageMaker image is a set of image versions. Each image version represents a container image stored in Amazon Container Registry (ECR). For more information, see Bring your own SageMaker image.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateImageVersion()

virtual Model::CreateImageVersionOutcome Aws::SageMaker::SageMakerClient::CreateImageVersion ( const Model::CreateImageVersionRequest request) const
virtual

Creates a version of the SageMaker image specified by ImageName. The version represents the Amazon Container Registry (ECR) container image specified by BaseImage.

See Also:

AWS API Reference

◆ CreateImageVersionAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateImageVersionAsync ( const Model::CreateImageVersionRequest request,
const CreateImageVersionResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates a version of the SageMaker image specified by ImageName. The version represents the Amazon Container Registry (ECR) container image specified by BaseImage.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateImageVersionCallable()

virtual Model::CreateImageVersionOutcomeCallable Aws::SageMaker::SageMakerClient::CreateImageVersionCallable ( const Model::CreateImageVersionRequest request) const
virtual

Creates a version of the SageMaker image specified by ImageName. The version represents the Amazon Container Registry (ECR) container image specified by BaseImage.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateLabelingJob()

virtual Model::CreateLabelingJobOutcome Aws::SageMaker::SageMakerClient::CreateLabelingJob ( const Model::CreateLabelingJobRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ CreateLabelingJobAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateLabelingJobAsync ( const Model::CreateLabelingJobRequest request,
const CreateLabelingJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateLabelingJobCallable()

virtual Model::CreateLabelingJobOutcomeCallable Aws::SageMaker::SageMakerClient::CreateLabelingJobCallable ( const Model::CreateLabelingJobRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateModel()

virtual Model::CreateModelOutcome Aws::SageMaker::SageMakerClient::CreateModel ( const Model::CreateModelRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ CreateModelAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateModelAsync ( const Model::CreateModelRequest request,
const CreateModelResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateModelCallable()

virtual Model::CreateModelOutcomeCallable Aws::SageMaker::SageMakerClient::CreateModelCallable ( const Model::CreateModelRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateModelPackage()

virtual Model::CreateModelPackageOutcome Aws::SageMaker::SageMakerClient::CreateModelPackage ( const Model::CreateModelPackageRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ CreateModelPackageAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateModelPackageAsync ( const Model::CreateModelPackageRequest request,
const CreateModelPackageResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateModelPackageCallable()

virtual Model::CreateModelPackageOutcomeCallable Aws::SageMaker::SageMakerClient::CreateModelPackageCallable ( const Model::CreateModelPackageRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateMonitoringSchedule()

virtual Model::CreateMonitoringScheduleOutcome Aws::SageMaker::SageMakerClient::CreateMonitoringSchedule ( const Model::CreateMonitoringScheduleRequest request) const
virtual

Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endoint.

See Also:

AWS API Reference

◆ CreateMonitoringScheduleAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateMonitoringScheduleAsync ( const Model::CreateMonitoringScheduleRequest request,
const CreateMonitoringScheduleResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endoint.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateMonitoringScheduleCallable()

virtual Model::CreateMonitoringScheduleOutcomeCallable Aws::SageMaker::SageMakerClient::CreateMonitoringScheduleCallable ( const Model::CreateMonitoringScheduleRequest request) const
virtual

Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endoint.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateNotebookInstance()

virtual Model::CreateNotebookInstanceOutcome Aws::SageMaker::SageMakerClient::CreateNotebookInstance ( const Model::CreateNotebookInstanceRequest request) const
virtual

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:

  1. Creates a network interface in the Amazon SageMaker VPC.

  2. (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.

  3. 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.

See Also:

AWS API Reference

◆ CreateNotebookInstanceAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateNotebookInstanceAsync ( const Model::CreateNotebookInstanceRequest request,
const CreateNotebookInstanceResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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:

  1. Creates a network interface in the Amazon SageMaker VPC.

  2. (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.

  3. 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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateNotebookInstanceCallable()

virtual Model::CreateNotebookInstanceOutcomeCallable Aws::SageMaker::SageMakerClient::CreateNotebookInstanceCallable ( const Model::CreateNotebookInstanceRequest request) const
virtual

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:

  1. Creates a network interface in the Amazon SageMaker VPC.

  2. (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.

  3. 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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateNotebookInstanceLifecycleConfig()

virtual Model::CreateNotebookInstanceLifecycleConfigOutcome Aws::SageMaker::SageMakerClient::CreateNotebookInstanceLifecycleConfig ( const Model::CreateNotebookInstanceLifecycleConfigRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ CreateNotebookInstanceLifecycleConfigAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateNotebookInstanceLifecycleConfigAsync ( const Model::CreateNotebookInstanceLifecycleConfigRequest request,
const CreateNotebookInstanceLifecycleConfigResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateNotebookInstanceLifecycleConfigCallable()

virtual Model::CreateNotebookInstanceLifecycleConfigOutcomeCallable Aws::SageMaker::SageMakerClient::CreateNotebookInstanceLifecycleConfigCallable ( const Model::CreateNotebookInstanceLifecycleConfigRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreatePresignedDomainUrl()

virtual Model::CreatePresignedDomainUrlOutcome Aws::SageMaker::SageMakerClient::CreatePresignedDomainUrl ( const Model::CreatePresignedDomainUrlRequest request) const
virtual

Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to Amazon SageMaker Studio, and granted access to all of the Apps and files associated with the Domain's Amazon Elastic File System (EFS) volume. This operation can only be called when the authentication mode equals IAM.

The URL that you get from a call to CreatePresignedDomainUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the AWS console sign-in page.

See Also:

AWS API Reference

◆ CreatePresignedDomainUrlAsync()

virtual void Aws::SageMaker::SageMakerClient::CreatePresignedDomainUrlAsync ( const Model::CreatePresignedDomainUrlRequest request,
const CreatePresignedDomainUrlResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to Amazon SageMaker Studio, and granted access to all of the Apps and files associated with the Domain's Amazon Elastic File System (EFS) volume. This operation can only be called when the authentication mode equals IAM.

The URL that you get from a call to CreatePresignedDomainUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the AWS console sign-in page.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreatePresignedDomainUrlCallable()

virtual Model::CreatePresignedDomainUrlOutcomeCallable Aws::SageMaker::SageMakerClient::CreatePresignedDomainUrlCallable ( const Model::CreatePresignedDomainUrlRequest request) const
virtual

Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to Amazon SageMaker Studio, and granted access to all of the Apps and files associated with the Domain's Amazon Elastic File System (EFS) volume. This operation can only be called when the authentication mode equals IAM.

The URL that you get from a call to CreatePresignedDomainUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the AWS console sign-in page.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreatePresignedNotebookInstanceUrl()

virtual Model::CreatePresignedNotebookInstanceUrlOutcome Aws::SageMaker::SageMakerClient::CreatePresignedNotebookInstanceUrl ( const Model::CreatePresignedNotebookInstanceUrlRequest request) const
virtual

Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the Amazon SageMaker console, when you choose Open next to a notebook instance, Amazon SageMaker opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.

The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.

You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress condition operator and the aws:SourceIP condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.

The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the AWS console sign-in page.

See Also:

AWS API Reference

◆ CreatePresignedNotebookInstanceUrlAsync()

virtual void Aws::SageMaker::SageMakerClient::CreatePresignedNotebookInstanceUrlAsync ( const Model::CreatePresignedNotebookInstanceUrlRequest request,
const CreatePresignedNotebookInstanceUrlResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the Amazon SageMaker console, when you choose Open next to a notebook instance, Amazon SageMaker opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.

The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.

You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress condition operator and the aws:SourceIP condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.

The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the AWS console sign-in page.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreatePresignedNotebookInstanceUrlCallable()

virtual Model::CreatePresignedNotebookInstanceUrlOutcomeCallable Aws::SageMaker::SageMakerClient::CreatePresignedNotebookInstanceUrlCallable ( const Model::CreatePresignedNotebookInstanceUrlRequest request) const
virtual

Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the Amazon SageMaker console, when you choose Open next to a notebook instance, Amazon SageMaker opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.

The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.

You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress condition operator and the aws:SourceIP condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.

The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the AWS console sign-in page.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateProcessingJob()

virtual Model::CreateProcessingJobOutcome Aws::SageMaker::SageMakerClient::CreateProcessingJob ( const Model::CreateProcessingJobRequest request) const
virtual

Creates a processing job.

See Also:

AWS API Reference

◆ CreateProcessingJobAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateProcessingJobAsync ( const Model::CreateProcessingJobRequest request,
const CreateProcessingJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates a processing job.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateProcessingJobCallable()

virtual Model::CreateProcessingJobOutcomeCallable Aws::SageMaker::SageMakerClient::CreateProcessingJobCallable ( const Model::CreateProcessingJobRequest request) const
virtual

Creates a processing job.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateTrainingJob()

virtual Model::CreateTrainingJobOutcome Aws::SageMaker::SageMakerClient::CreateTrainingJob ( const Model::CreateTrainingJobRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ CreateTrainingJobAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateTrainingJobAsync ( const Model::CreateTrainingJobRequest request,
const CreateTrainingJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateTrainingJobCallable()

virtual Model::CreateTrainingJobOutcomeCallable Aws::SageMaker::SageMakerClient::CreateTrainingJobCallable ( const Model::CreateTrainingJobRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateTransformJob()

virtual Model::CreateTransformJobOutcome Aws::SageMaker::SageMakerClient::CreateTransformJob ( const Model::CreateTransformJobRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ CreateTransformJobAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateTransformJobAsync ( const Model::CreateTransformJobRequest request,
const CreateTransformJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateTransformJobCallable()

virtual Model::CreateTransformJobOutcomeCallable Aws::SageMaker::SageMakerClient::CreateTransformJobCallable ( const Model::CreateTransformJobRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateTrial()

virtual Model::CreateTrialOutcome Aws::SageMaker::SageMakerClient::CreateTrial ( const Model::CreateTrialRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ CreateTrialAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateTrialAsync ( const Model::CreateTrialRequest request,
const CreateTrialResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateTrialCallable()

virtual Model::CreateTrialOutcomeCallable Aws::SageMaker::SageMakerClient::CreateTrialCallable ( const Model::CreateTrialRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateTrialComponent()

virtual Model::CreateTrialComponentOutcome Aws::SageMaker::SageMakerClient::CreateTrialComponent ( const Model::CreateTrialComponentRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ CreateTrialComponentAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateTrialComponentAsync ( const Model::CreateTrialComponentRequest request,
const CreateTrialComponentResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateTrialComponentCallable()

virtual Model::CreateTrialComponentOutcomeCallable Aws::SageMaker::SageMakerClient::CreateTrialComponentCallable ( const Model::CreateTrialComponentRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateUserProfile()

virtual Model::CreateUserProfileOutcome Aws::SageMaker::SageMakerClient::CreateUserProfile ( const Model::CreateUserProfileRequest request) const
virtual

Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a "person" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to Amazon SageMaker Studio. If an administrator invites a person by email or imports them from SSO, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user's private Amazon Elastic File System (EFS) home directory.

See Also:

AWS API Reference

◆ CreateUserProfileAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateUserProfileAsync ( const Model::CreateUserProfileRequest request,
const CreateUserProfileResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a "person" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to Amazon SageMaker Studio. If an administrator invites a person by email or imports them from SSO, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user's private Amazon Elastic File System (EFS) home directory.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateUserProfileCallable()

virtual Model::CreateUserProfileOutcomeCallable Aws::SageMaker::SageMakerClient::CreateUserProfileCallable ( const Model::CreateUserProfileRequest request) const
virtual

Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a "person" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to Amazon SageMaker Studio. If an administrator invites a person by email or imports them from SSO, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user's private Amazon Elastic File System (EFS) home directory.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateWorkforce()

virtual Model::CreateWorkforceOutcome Aws::SageMaker::SageMakerClient::CreateWorkforce ( const Model::CreateWorkforceRequest request) const
virtual

Use this operation to create a workforce. This operation will return an error if a workforce already exists in the AWS Region that you specify. You can only create one workforce in each AWS Region per AWS account.

If you want to create a new workforce in an AWS Region where a workforce already exists, use the API operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.

To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).

To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig. Your OIDC IdP must support groups because groups are used by Ground Truth and Amazon A2I to create work teams. For more information, see Create a Private Workforce (OIDC IdP).

See Also:

AWS API Reference

◆ CreateWorkforceAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateWorkforceAsync ( const Model::CreateWorkforceRequest request,
const CreateWorkforceResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Use this operation to create a workforce. This operation will return an error if a workforce already exists in the AWS Region that you specify. You can only create one workforce in each AWS Region per AWS account.

If you want to create a new workforce in an AWS Region where a workforce already exists, use the API operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.

To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).

To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig. Your OIDC IdP must support groups because groups are used by Ground Truth and Amazon A2I to create work teams. For more information, see Create a Private Workforce (OIDC IdP).

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateWorkforceCallable()

virtual Model::CreateWorkforceOutcomeCallable Aws::SageMaker::SageMakerClient::CreateWorkforceCallable ( const Model::CreateWorkforceRequest request) const
virtual

Use this operation to create a workforce. This operation will return an error if a workforce already exists in the AWS Region that you specify. You can only create one workforce in each AWS Region per AWS account.

If you want to create a new workforce in an AWS Region where a workforce already exists, use the API operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.

To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).

To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig. Your OIDC IdP must support groups because groups are used by Ground Truth and Amazon A2I to create work teams. For more information, see Create a Private Workforce (OIDC IdP).

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ CreateWorkteam()

virtual Model::CreateWorkteamOutcome Aws::SageMaker::SageMakerClient::CreateWorkteam ( const Model::CreateWorkteamRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ CreateWorkteamAsync()

virtual void Aws::SageMaker::SageMakerClient::CreateWorkteamAsync ( const Model::CreateWorkteamRequest request,
const CreateWorkteamResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ CreateWorkteamCallable()

virtual Model::CreateWorkteamOutcomeCallable Aws::SageMaker::SageMakerClient::CreateWorkteamCallable ( const Model::CreateWorkteamRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteAlgorithm()

virtual Model::DeleteAlgorithmOutcome Aws::SageMaker::SageMakerClient::DeleteAlgorithm ( const Model::DeleteAlgorithmRequest request) const
virtual

Removes the specified algorithm from your account.

See Also:

AWS API Reference

◆ DeleteAlgorithmAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteAlgorithmAsync ( const Model::DeleteAlgorithmRequest request,
const DeleteAlgorithmResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Removes the specified algorithm from your account.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteAlgorithmCallable()

virtual Model::DeleteAlgorithmOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteAlgorithmCallable ( const Model::DeleteAlgorithmRequest request) const
virtual

Removes the specified algorithm from your account.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteApp()

virtual Model::DeleteAppOutcome Aws::SageMaker::SageMakerClient::DeleteApp ( const Model::DeleteAppRequest request) const
virtual

Used to stop and delete an app.

See Also:

AWS API Reference

◆ DeleteAppAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteAppAsync ( const Model::DeleteAppRequest request,
const DeleteAppResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Used to stop and delete an app.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteAppCallable()

virtual Model::DeleteAppOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteAppCallable ( const Model::DeleteAppRequest request) const
virtual

Used to stop and delete an app.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteAppImageConfig()

virtual Model::DeleteAppImageConfigOutcome Aws::SageMaker::SageMakerClient::DeleteAppImageConfig ( const Model::DeleteAppImageConfigRequest request) const
virtual

Deletes an AppImageConfig.

See Also:

AWS API Reference

◆ DeleteAppImageConfigAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteAppImageConfigAsync ( const Model::DeleteAppImageConfigRequest request,
const DeleteAppImageConfigResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Deletes an AppImageConfig.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteAppImageConfigCallable()

virtual Model::DeleteAppImageConfigOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteAppImageConfigCallable ( const Model::DeleteAppImageConfigRequest request) const
virtual

Deletes an AppImageConfig.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteCodeRepository()

virtual Model::DeleteCodeRepositoryOutcome Aws::SageMaker::SageMakerClient::DeleteCodeRepository ( const Model::DeleteCodeRepositoryRequest request) const
virtual

Deletes the specified Git repository from your account.

See Also:

AWS API Reference

◆ DeleteCodeRepositoryAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteCodeRepositoryAsync ( const Model::DeleteCodeRepositoryRequest request,
const DeleteCodeRepositoryResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Deletes the specified Git repository from your account.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteCodeRepositoryCallable()

virtual Model::DeleteCodeRepositoryOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteCodeRepositoryCallable ( const Model::DeleteCodeRepositoryRequest request) const
virtual

Deletes the specified Git repository from your account.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteDomain()

virtual Model::DeleteDomainOutcome Aws::SageMaker::SageMakerClient::DeleteDomain ( const Model::DeleteDomainRequest request) const
virtual

Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using SSO. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.

See Also:

AWS API Reference

◆ DeleteDomainAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteDomainAsync ( const Model::DeleteDomainRequest request,
const DeleteDomainResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using SSO. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteDomainCallable()

virtual Model::DeleteDomainOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteDomainCallable ( const Model::DeleteDomainRequest request) const
virtual

Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using SSO. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteEndpoint()

virtual Model::DeleteEndpointOutcome Aws::SageMaker::SageMakerClient::DeleteEndpoint ( const Model::DeleteEndpointRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DeleteEndpointAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteEndpointAsync ( const Model::DeleteEndpointRequest request,
const DeleteEndpointResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteEndpointCallable()

virtual Model::DeleteEndpointOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteEndpointCallable ( const Model::DeleteEndpointRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteEndpointConfig()

virtual Model::DeleteEndpointConfigOutcome Aws::SageMaker::SageMakerClient::DeleteEndpointConfig ( const Model::DeleteEndpointConfigRequest request) const
virtual

Deletes an endpoint configuration. The DeleteEndpointConfig API deletes only the specified configuration. It does not delete endpoints created using the configuration.

You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.

See Also:

AWS API Reference

◆ DeleteEndpointConfigAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteEndpointConfigAsync ( const Model::DeleteEndpointConfigRequest request,
const DeleteEndpointConfigResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Deletes an endpoint configuration. The DeleteEndpointConfig API deletes only the specified configuration. It does not delete endpoints created using the configuration.

You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteEndpointConfigCallable()

virtual Model::DeleteEndpointConfigOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteEndpointConfigCallable ( const Model::DeleteEndpointConfigRequest request) const
virtual

Deletes an endpoint configuration. The DeleteEndpointConfig API deletes only the specified configuration. It does not delete endpoints created using the configuration.

You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteExperiment()

virtual Model::DeleteExperimentOutcome Aws::SageMaker::SageMakerClient::DeleteExperiment ( const Model::DeleteExperimentRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DeleteExperimentAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteExperimentAsync ( const Model::DeleteExperimentRequest request,
const DeleteExperimentResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteExperimentCallable()

virtual Model::DeleteExperimentOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteExperimentCallable ( const Model::DeleteExperimentRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteFlowDefinition()

virtual Model::DeleteFlowDefinitionOutcome Aws::SageMaker::SageMakerClient::DeleteFlowDefinition ( const Model::DeleteFlowDefinitionRequest request) const
virtual

Deletes the specified flow definition.

See Also:

AWS API Reference

◆ DeleteFlowDefinitionAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteFlowDefinitionAsync ( const Model::DeleteFlowDefinitionRequest request,
const DeleteFlowDefinitionResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Deletes the specified flow definition.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteFlowDefinitionCallable()

virtual Model::DeleteFlowDefinitionOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteFlowDefinitionCallable ( const Model::DeleteFlowDefinitionRequest request) const
virtual

Deletes the specified flow definition.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteHumanTaskUi()

virtual Model::DeleteHumanTaskUiOutcome Aws::SageMaker::SageMakerClient::DeleteHumanTaskUi ( const Model::DeleteHumanTaskUiRequest request) const
virtual

Use this operation to delete a human task user interface (worker task template).

To see a list of human task user interfaces (work task templates) in your account, use . When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.

See Also:

AWS API Reference

◆ DeleteHumanTaskUiAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteHumanTaskUiAsync ( const Model::DeleteHumanTaskUiRequest request,
const DeleteHumanTaskUiResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Use this operation to delete a human task user interface (worker task template).

To see a list of human task user interfaces (work task templates) in your account, use . When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteHumanTaskUiCallable()

virtual Model::DeleteHumanTaskUiOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteHumanTaskUiCallable ( const Model::DeleteHumanTaskUiRequest request) const
virtual

Use this operation to delete a human task user interface (worker task template).

To see a list of human task user interfaces (work task templates) in your account, use . When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteImage()

virtual Model::DeleteImageOutcome Aws::SageMaker::SageMakerClient::DeleteImage ( const Model::DeleteImageRequest request) const
virtual

Deletes a SageMaker image and all versions of the image. The container images aren't deleted.

See Also:

AWS API Reference

◆ DeleteImageAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteImageAsync ( const Model::DeleteImageRequest request,
const DeleteImageResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Deletes a SageMaker image and all versions of the image. The container images aren't deleted.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteImageCallable()

virtual Model::DeleteImageOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteImageCallable ( const Model::DeleteImageRequest request) const
virtual

Deletes a SageMaker image and all versions of the image. The container images aren't deleted.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteImageVersion()

virtual Model::DeleteImageVersionOutcome Aws::SageMaker::SageMakerClient::DeleteImageVersion ( const Model::DeleteImageVersionRequest request) const
virtual

Deletes a version of a SageMaker image. The container image the version represents isn't deleted.

See Also:

AWS API Reference

◆ DeleteImageVersionAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteImageVersionAsync ( const Model::DeleteImageVersionRequest request,
const DeleteImageVersionResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Deletes a version of a SageMaker image. The container image the version represents isn't deleted.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteImageVersionCallable()

virtual Model::DeleteImageVersionOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteImageVersionCallable ( const Model::DeleteImageVersionRequest request) const
virtual

Deletes a version of a SageMaker image. The container image the version represents isn't deleted.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteModel()

virtual Model::DeleteModelOutcome Aws::SageMaker::SageMakerClient::DeleteModel ( const Model::DeleteModelRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DeleteModelAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteModelAsync ( const Model::DeleteModelRequest request,
const DeleteModelResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteModelCallable()

virtual Model::DeleteModelOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteModelCallable ( const Model::DeleteModelRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteModelPackage()

virtual Model::DeleteModelPackageOutcome Aws::SageMaker::SageMakerClient::DeleteModelPackage ( const Model::DeleteModelPackageRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DeleteModelPackageAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteModelPackageAsync ( const Model::DeleteModelPackageRequest request,
const DeleteModelPackageResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteModelPackageCallable()

virtual Model::DeleteModelPackageOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteModelPackageCallable ( const Model::DeleteModelPackageRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteMonitoringSchedule()

virtual Model::DeleteMonitoringScheduleOutcome Aws::SageMaker::SageMakerClient::DeleteMonitoringSchedule ( const Model::DeleteMonitoringScheduleRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DeleteMonitoringScheduleAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteMonitoringScheduleAsync ( const Model::DeleteMonitoringScheduleRequest request,
const DeleteMonitoringScheduleResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteMonitoringScheduleCallable()

virtual Model::DeleteMonitoringScheduleOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteMonitoringScheduleCallable ( const Model::DeleteMonitoringScheduleRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteNotebookInstance()

virtual Model::DeleteNotebookInstanceOutcome Aws::SageMaker::SageMakerClient::DeleteNotebookInstance ( const Model::DeleteNotebookInstanceRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DeleteNotebookInstanceAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteNotebookInstanceAsync ( const Model::DeleteNotebookInstanceRequest request,
const DeleteNotebookInstanceResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteNotebookInstanceCallable()

virtual Model::DeleteNotebookInstanceOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteNotebookInstanceCallable ( const Model::DeleteNotebookInstanceRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteNotebookInstanceLifecycleConfig()

virtual Model::DeleteNotebookInstanceLifecycleConfigOutcome Aws::SageMaker::SageMakerClient::DeleteNotebookInstanceLifecycleConfig ( const Model::DeleteNotebookInstanceLifecycleConfigRequest request) const
virtual

Deletes a notebook instance lifecycle configuration.

See Also:

AWS API Reference

◆ DeleteNotebookInstanceLifecycleConfigAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteNotebookInstanceLifecycleConfigAsync ( const Model::DeleteNotebookInstanceLifecycleConfigRequest request,
const DeleteNotebookInstanceLifecycleConfigResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Deletes a notebook instance lifecycle configuration.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteNotebookInstanceLifecycleConfigCallable()

virtual Model::DeleteNotebookInstanceLifecycleConfigOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteNotebookInstanceLifecycleConfigCallable ( const Model::DeleteNotebookInstanceLifecycleConfigRequest request) const
virtual

Deletes a notebook instance lifecycle configuration.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteTags()

virtual Model::DeleteTagsOutcome Aws::SageMaker::SageMakerClient::DeleteTags ( const Model::DeleteTagsRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DeleteTagsAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteTagsAsync ( const Model::DeleteTagsRequest request,
const DeleteTagsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteTagsCallable()

virtual Model::DeleteTagsOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteTagsCallable ( const Model::DeleteTagsRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteTrial()

virtual Model::DeleteTrialOutcome Aws::SageMaker::SageMakerClient::DeleteTrial ( const Model::DeleteTrialRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DeleteTrialAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteTrialAsync ( const Model::DeleteTrialRequest request,
const DeleteTrialResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteTrialCallable()

virtual Model::DeleteTrialOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteTrialCallable ( const Model::DeleteTrialRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteTrialComponent()

virtual Model::DeleteTrialComponentOutcome Aws::SageMaker::SageMakerClient::DeleteTrialComponent ( const Model::DeleteTrialComponentRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DeleteTrialComponentAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteTrialComponentAsync ( const Model::DeleteTrialComponentRequest request,
const DeleteTrialComponentResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteTrialComponentCallable()

virtual Model::DeleteTrialComponentOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteTrialComponentCallable ( const Model::DeleteTrialComponentRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteUserProfile()

virtual Model::DeleteUserProfileOutcome Aws::SageMaker::SageMakerClient::DeleteUserProfile ( const Model::DeleteUserProfileRequest request) const
virtual

Deletes a user profile. When a user profile is deleted, the user loses access to their EFS volume, including data, notebooks, and other artifacts.

See Also:

AWS API Reference

◆ DeleteUserProfileAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteUserProfileAsync ( const Model::DeleteUserProfileRequest request,
const DeleteUserProfileResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Deletes a user profile. When a user profile is deleted, the user loses access to their EFS volume, including data, notebooks, and other artifacts.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteUserProfileCallable()

virtual Model::DeleteUserProfileOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteUserProfileCallable ( const Model::DeleteUserProfileRequest request) const
virtual

Deletes a user profile. When a user profile is deleted, the user loses access to their EFS volume, including data, notebooks, and other artifacts.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteWorkforce()

virtual Model::DeleteWorkforceOutcome Aws::SageMaker::SageMakerClient::DeleteWorkforce ( const Model::DeleteWorkforceRequest request) const
virtual

Use this operation to delete a workforce.

If you want to create a new workforce in an AWS Region where a workforce already exists, use this operation to delete the existing workforce and then use to create a new workforce.

If a private workforce contains one or more work teams, you must use the operation to delete all work teams before you delete the workforce. If you try to delete a workforce that contains one or more work teams, you will recieve a ResourceInUse error.

See Also:

AWS API Reference

◆ DeleteWorkforceAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteWorkforceAsync ( const Model::DeleteWorkforceRequest request,
const DeleteWorkforceResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Use this operation to delete a workforce.

If you want to create a new workforce in an AWS Region where a workforce already exists, use this operation to delete the existing workforce and then use to create a new workforce.

If a private workforce contains one or more work teams, you must use the operation to delete all work teams before you delete the workforce. If you try to delete a workforce that contains one or more work teams, you will recieve a ResourceInUse error.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteWorkforceCallable()

virtual Model::DeleteWorkforceOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteWorkforceCallable ( const Model::DeleteWorkforceRequest request) const
virtual

Use this operation to delete a workforce.

If you want to create a new workforce in an AWS Region where a workforce already exists, use this operation to delete the existing workforce and then use to create a new workforce.

If a private workforce contains one or more work teams, you must use the operation to delete all work teams before you delete the workforce. If you try to delete a workforce that contains one or more work teams, you will recieve a ResourceInUse error.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DeleteWorkteam()

virtual Model::DeleteWorkteamOutcome Aws::SageMaker::SageMakerClient::DeleteWorkteam ( const Model::DeleteWorkteamRequest request) const
virtual

Deletes an existing work team. This operation can't be undone.

See Also:

AWS API Reference

◆ DeleteWorkteamAsync()

virtual void Aws::SageMaker::SageMakerClient::DeleteWorkteamAsync ( const Model::DeleteWorkteamRequest request,
const DeleteWorkteamResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Deletes an existing work team. This operation can't be undone.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DeleteWorkteamCallable()

virtual Model::DeleteWorkteamOutcomeCallable Aws::SageMaker::SageMakerClient::DeleteWorkteamCallable ( const Model::DeleteWorkteamRequest request) const
virtual

Deletes an existing work team. This operation can't be undone.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeAlgorithm()

virtual Model::DescribeAlgorithmOutcome Aws::SageMaker::SageMakerClient::DescribeAlgorithm ( const Model::DescribeAlgorithmRequest request) const
virtual

Returns a description of the specified algorithm that is in your account.

See Also:

AWS API Reference

◆ DescribeAlgorithmAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeAlgorithmAsync ( const Model::DescribeAlgorithmRequest request,
const DescribeAlgorithmResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Returns a description of the specified algorithm that is in your account.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeAlgorithmCallable()

virtual Model::DescribeAlgorithmOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeAlgorithmCallable ( const Model::DescribeAlgorithmRequest request) const
virtual

Returns a description of the specified algorithm that is in your account.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeApp()

virtual Model::DescribeAppOutcome Aws::SageMaker::SageMakerClient::DescribeApp ( const Model::DescribeAppRequest request) const
virtual

Describes the app.

See Also:

AWS API Reference

◆ DescribeAppAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeAppAsync ( const Model::DescribeAppRequest request,
const DescribeAppResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Describes the app.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeAppCallable()

virtual Model::DescribeAppOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeAppCallable ( const Model::DescribeAppRequest request) const
virtual

Describes the app.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeAppImageConfig()

virtual Model::DescribeAppImageConfigOutcome Aws::SageMaker::SageMakerClient::DescribeAppImageConfig ( const Model::DescribeAppImageConfigRequest request) const
virtual

Describes an AppImageConfig.

See Also:

AWS API Reference

◆ DescribeAppImageConfigAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeAppImageConfigAsync ( const Model::DescribeAppImageConfigRequest request,
const DescribeAppImageConfigResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Describes an AppImageConfig.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeAppImageConfigCallable()

virtual Model::DescribeAppImageConfigOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeAppImageConfigCallable ( const Model::DescribeAppImageConfigRequest request) const
virtual

Describes an AppImageConfig.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeAutoMLJob()

virtual Model::DescribeAutoMLJobOutcome Aws::SageMaker::SageMakerClient::DescribeAutoMLJob ( const Model::DescribeAutoMLJobRequest request) const
virtual

Returns information about an Amazon SageMaker job.

See Also:

AWS API Reference

◆ DescribeAutoMLJobAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeAutoMLJobAsync ( const Model::DescribeAutoMLJobRequest request,
const DescribeAutoMLJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Returns information about an Amazon SageMaker job.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeAutoMLJobCallable()

virtual Model::DescribeAutoMLJobOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeAutoMLJobCallable ( const Model::DescribeAutoMLJobRequest request) const
virtual

Returns information about an Amazon SageMaker job.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeCodeRepository()

virtual Model::DescribeCodeRepositoryOutcome Aws::SageMaker::SageMakerClient::DescribeCodeRepository ( const Model::DescribeCodeRepositoryRequest request) const
virtual

Gets details about the specified Git repository.

See Also:

AWS API Reference

◆ DescribeCodeRepositoryAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeCodeRepositoryAsync ( const Model::DescribeCodeRepositoryRequest request,
const DescribeCodeRepositoryResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Gets details about the specified Git repository.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeCodeRepositoryCallable()

virtual Model::DescribeCodeRepositoryOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeCodeRepositoryCallable ( const Model::DescribeCodeRepositoryRequest request) const
virtual

Gets details about the specified Git repository.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeCompilationJob()

virtual Model::DescribeCompilationJobOutcome Aws::SageMaker::SageMakerClient::DescribeCompilationJob ( const Model::DescribeCompilationJobRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DescribeCompilationJobAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeCompilationJobAsync ( const Model::DescribeCompilationJobRequest request,
const DescribeCompilationJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeCompilationJobCallable()

virtual Model::DescribeCompilationJobOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeCompilationJobCallable ( const Model::DescribeCompilationJobRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeDomain()

virtual Model::DescribeDomainOutcome Aws::SageMaker::SageMakerClient::DescribeDomain ( const Model::DescribeDomainRequest request) const
virtual

The description of the domain.

See Also:

AWS API Reference

◆ DescribeDomainAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeDomainAsync ( const Model::DescribeDomainRequest request,
const DescribeDomainResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

The description of the domain.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeDomainCallable()

virtual Model::DescribeDomainOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeDomainCallable ( const Model::DescribeDomainRequest request) const
virtual

The description of the domain.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeEndpoint()

virtual Model::DescribeEndpointOutcome Aws::SageMaker::SageMakerClient::DescribeEndpoint ( const Model::DescribeEndpointRequest request) const
virtual

Returns the description of an endpoint.

See Also:

AWS API Reference

◆ DescribeEndpointAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeEndpointAsync ( const Model::DescribeEndpointRequest request,
const DescribeEndpointResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Returns the description of an endpoint.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeEndpointCallable()

virtual Model::DescribeEndpointOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeEndpointCallable ( const Model::DescribeEndpointRequest request) const
virtual

Returns the description of an endpoint.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeEndpointConfig()

virtual Model::DescribeEndpointConfigOutcome Aws::SageMaker::SageMakerClient::DescribeEndpointConfig ( const Model::DescribeEndpointConfigRequest request) const
virtual

Returns the description of an endpoint configuration created using the CreateEndpointConfig API.

See Also:

AWS API Reference

◆ DescribeEndpointConfigAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeEndpointConfigAsync ( const Model::DescribeEndpointConfigRequest request,
const DescribeEndpointConfigResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Returns the description of an endpoint configuration created using the CreateEndpointConfig API.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeEndpointConfigCallable()

virtual Model::DescribeEndpointConfigOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeEndpointConfigCallable ( const Model::DescribeEndpointConfigRequest request) const
virtual

Returns the description of an endpoint configuration created using the CreateEndpointConfig API.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeExperiment()

virtual Model::DescribeExperimentOutcome Aws::SageMaker::SageMakerClient::DescribeExperiment ( const Model::DescribeExperimentRequest request) const
virtual

Provides a list of an experiment's properties.

See Also:

AWS API Reference

◆ DescribeExperimentAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeExperimentAsync ( const Model::DescribeExperimentRequest request,
const DescribeExperimentResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Provides a list of an experiment's properties.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeExperimentCallable()

virtual Model::DescribeExperimentOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeExperimentCallable ( const Model::DescribeExperimentRequest request) const
virtual

Provides a list of an experiment's properties.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeFlowDefinition()

virtual Model::DescribeFlowDefinitionOutcome Aws::SageMaker::SageMakerClient::DescribeFlowDefinition ( const Model::DescribeFlowDefinitionRequest request) const
virtual

Returns information about the specified flow definition.

See Also:

AWS API Reference

◆ DescribeFlowDefinitionAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeFlowDefinitionAsync ( const Model::DescribeFlowDefinitionRequest request,
const DescribeFlowDefinitionResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Returns information about the specified flow definition.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeFlowDefinitionCallable()

virtual Model::DescribeFlowDefinitionOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeFlowDefinitionCallable ( const Model::DescribeFlowDefinitionRequest request) const
virtual

Returns information about the specified flow definition.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeHumanTaskUi()

virtual Model::DescribeHumanTaskUiOutcome Aws::SageMaker::SageMakerClient::DescribeHumanTaskUi ( const Model::DescribeHumanTaskUiRequest request) const
virtual

Returns information about the requested human task user interface (worker task template).

See Also:

AWS API Reference

◆ DescribeHumanTaskUiAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeHumanTaskUiAsync ( const Model::DescribeHumanTaskUiRequest request,
const DescribeHumanTaskUiResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Returns information about the requested human task user interface (worker task template).

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeHumanTaskUiCallable()

virtual Model::DescribeHumanTaskUiOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeHumanTaskUiCallable ( const Model::DescribeHumanTaskUiRequest request) const
virtual

Returns information about the requested human task user interface (worker task template).

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeHyperParameterTuningJob()

virtual Model::DescribeHyperParameterTuningJobOutcome Aws::SageMaker::SageMakerClient::DescribeHyperParameterTuningJob ( const Model::DescribeHyperParameterTuningJobRequest request) const
virtual

Gets a description of a hyperparameter tuning job.

See Also:

AWS API Reference

◆ DescribeHyperParameterTuningJobAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeHyperParameterTuningJobAsync ( const Model::DescribeHyperParameterTuningJobRequest request,
const DescribeHyperParameterTuningJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Gets a description of a hyperparameter tuning job.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeHyperParameterTuningJobCallable()

virtual Model::DescribeHyperParameterTuningJobOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeHyperParameterTuningJobCallable ( const Model::DescribeHyperParameterTuningJobRequest request) const
virtual

Gets a description of a hyperparameter tuning job.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeImage()

virtual Model::DescribeImageOutcome Aws::SageMaker::SageMakerClient::DescribeImage ( const Model::DescribeImageRequest request) const
virtual

Describes a SageMaker image.

See Also:

AWS API Reference

◆ DescribeImageAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeImageAsync ( const Model::DescribeImageRequest request,
const DescribeImageResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Describes a SageMaker image.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeImageCallable()

virtual Model::DescribeImageOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeImageCallable ( const Model::DescribeImageRequest request) const
virtual

Describes a SageMaker image.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeImageVersion()

virtual Model::DescribeImageVersionOutcome Aws::SageMaker::SageMakerClient::DescribeImageVersion ( const Model::DescribeImageVersionRequest request) const
virtual

Describes a version of a SageMaker image.

See Also:

AWS API Reference

◆ DescribeImageVersionAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeImageVersionAsync ( const Model::DescribeImageVersionRequest request,
const DescribeImageVersionResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Describes a version of a SageMaker image.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeImageVersionCallable()

virtual Model::DescribeImageVersionOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeImageVersionCallable ( const Model::DescribeImageVersionRequest request) const
virtual

Describes a version of a SageMaker image.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeLabelingJob()

virtual Model::DescribeLabelingJobOutcome Aws::SageMaker::SageMakerClient::DescribeLabelingJob ( const Model::DescribeLabelingJobRequest request) const
virtual

Gets information about a labeling job.

See Also:

AWS API Reference

◆ DescribeLabelingJobAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeLabelingJobAsync ( const Model::DescribeLabelingJobRequest request,
const DescribeLabelingJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Gets information about a labeling job.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeLabelingJobCallable()

virtual Model::DescribeLabelingJobOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeLabelingJobCallable ( const Model::DescribeLabelingJobRequest request) const
virtual

Gets information about a labeling job.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeModel()

virtual Model::DescribeModelOutcome Aws::SageMaker::SageMakerClient::DescribeModel ( const Model::DescribeModelRequest request) const
virtual

Describes a model that you created using the CreateModel API.

See Also:

AWS API Reference

◆ DescribeModelAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeModelAsync ( const Model::DescribeModelRequest request,
const DescribeModelResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Describes a model that you created using the CreateModel API.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeModelCallable()

virtual Model::DescribeModelOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeModelCallable ( const Model::DescribeModelRequest request) const
virtual

Describes a model that you created using the CreateModel API.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeModelPackage()

virtual Model::DescribeModelPackageOutcome Aws::SageMaker::SageMakerClient::DescribeModelPackage ( const Model::DescribeModelPackageRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DescribeModelPackageAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeModelPackageAsync ( const Model::DescribeModelPackageRequest request,
const DescribeModelPackageResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeModelPackageCallable()

virtual Model::DescribeModelPackageOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeModelPackageCallable ( const Model::DescribeModelPackageRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeMonitoringSchedule()

virtual Model::DescribeMonitoringScheduleOutcome Aws::SageMaker::SageMakerClient::DescribeMonitoringSchedule ( const Model::DescribeMonitoringScheduleRequest request) const
virtual

Describes the schedule for a monitoring job.

See Also:

AWS API Reference

◆ DescribeMonitoringScheduleAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeMonitoringScheduleAsync ( const Model::DescribeMonitoringScheduleRequest request,
const DescribeMonitoringScheduleResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Describes the schedule for a monitoring job.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeMonitoringScheduleCallable()

virtual Model::DescribeMonitoringScheduleOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeMonitoringScheduleCallable ( const Model::DescribeMonitoringScheduleRequest request) const
virtual

Describes the schedule for a monitoring job.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeNotebookInstance()

virtual Model::DescribeNotebookInstanceOutcome Aws::SageMaker::SageMakerClient::DescribeNotebookInstance ( const Model::DescribeNotebookInstanceRequest request) const
virtual

Returns information about a notebook instance.

See Also:

AWS API Reference

◆ DescribeNotebookInstanceAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeNotebookInstanceAsync ( const Model::DescribeNotebookInstanceRequest request,
const DescribeNotebookInstanceResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Returns information about a notebook instance.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeNotebookInstanceCallable()

virtual Model::DescribeNotebookInstanceOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeNotebookInstanceCallable ( const Model::DescribeNotebookInstanceRequest request) const
virtual

Returns information about a notebook instance.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeNotebookInstanceLifecycleConfig()

virtual Model::DescribeNotebookInstanceLifecycleConfigOutcome Aws::SageMaker::SageMakerClient::DescribeNotebookInstanceLifecycleConfig ( const Model::DescribeNotebookInstanceLifecycleConfigRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DescribeNotebookInstanceLifecycleConfigAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeNotebookInstanceLifecycleConfigAsync ( const Model::DescribeNotebookInstanceLifecycleConfigRequest request,
const DescribeNotebookInstanceLifecycleConfigResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeNotebookInstanceLifecycleConfigCallable()

virtual Model::DescribeNotebookInstanceLifecycleConfigOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeNotebookInstanceLifecycleConfigCallable ( const Model::DescribeNotebookInstanceLifecycleConfigRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeProcessingJob()

virtual Model::DescribeProcessingJobOutcome Aws::SageMaker::SageMakerClient::DescribeProcessingJob ( const Model::DescribeProcessingJobRequest request) const
virtual

Returns a description of a processing job.

See Also:

AWS API Reference

◆ DescribeProcessingJobAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeProcessingJobAsync ( const Model::DescribeProcessingJobRequest request,
const DescribeProcessingJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Returns a description of a processing job.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeProcessingJobCallable()

virtual Model::DescribeProcessingJobOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeProcessingJobCallable ( const Model::DescribeProcessingJobRequest request) const
virtual

Returns a description of a processing job.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeSubscribedWorkteam()

virtual Model::DescribeSubscribedWorkteamOutcome Aws::SageMaker::SageMakerClient::DescribeSubscribedWorkteam ( const Model::DescribeSubscribedWorkteamRequest request) const
virtual

Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the AWS Marketplace.

See Also:

AWS API Reference

◆ DescribeSubscribedWorkteamAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeSubscribedWorkteamAsync ( const Model::DescribeSubscribedWorkteamRequest request,
const DescribeSubscribedWorkteamResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the AWS Marketplace.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeSubscribedWorkteamCallable()

virtual Model::DescribeSubscribedWorkteamOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeSubscribedWorkteamCallable ( const Model::DescribeSubscribedWorkteamRequest request) const
virtual

Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the AWS Marketplace.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeTrainingJob()

virtual Model::DescribeTrainingJobOutcome Aws::SageMaker::SageMakerClient::DescribeTrainingJob ( const Model::DescribeTrainingJobRequest request) const
virtual

Returns information about a training job.

See Also:

AWS API Reference

◆ DescribeTrainingJobAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeTrainingJobAsync ( const Model::DescribeTrainingJobRequest request,
const DescribeTrainingJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Returns information about a training job.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeTrainingJobCallable()

virtual Model::DescribeTrainingJobOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeTrainingJobCallable ( const Model::DescribeTrainingJobRequest request) const
virtual

Returns information about a training job.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeTransformJob()

virtual Model::DescribeTransformJobOutcome Aws::SageMaker::SageMakerClient::DescribeTransformJob ( const Model::DescribeTransformJobRequest request) const
virtual

Returns information about a transform job.

See Also:

AWS API Reference

◆ DescribeTransformJobAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeTransformJobAsync ( const Model::DescribeTransformJobRequest request,
const DescribeTransformJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Returns information about a transform job.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeTransformJobCallable()

virtual Model::DescribeTransformJobOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeTransformJobCallable ( const Model::DescribeTransformJobRequest request) const
virtual

Returns information about a transform job.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeTrial()

virtual Model::DescribeTrialOutcome Aws::SageMaker::SageMakerClient::DescribeTrial ( const Model::DescribeTrialRequest request) const
virtual

Provides a list of a trial's properties.

See Also:

AWS API Reference

◆ DescribeTrialAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeTrialAsync ( const Model::DescribeTrialRequest request,
const DescribeTrialResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Provides a list of a trial's properties.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeTrialCallable()

virtual Model::DescribeTrialOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeTrialCallable ( const Model::DescribeTrialRequest request) const
virtual

Provides a list of a trial's properties.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeTrialComponent()

virtual Model::DescribeTrialComponentOutcome Aws::SageMaker::SageMakerClient::DescribeTrialComponent ( const Model::DescribeTrialComponentRequest request) const
virtual

Provides a list of a trials component's properties.

See Also:

AWS API Reference

◆ DescribeTrialComponentAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeTrialComponentAsync ( const Model::DescribeTrialComponentRequest request,
const DescribeTrialComponentResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Provides a list of a trials component's properties.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeTrialComponentCallable()

virtual Model::DescribeTrialComponentOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeTrialComponentCallable ( const Model::DescribeTrialComponentRequest request) const
virtual

Provides a list of a trials component's properties.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeUserProfile()

virtual Model::DescribeUserProfileOutcome Aws::SageMaker::SageMakerClient::DescribeUserProfile ( const Model::DescribeUserProfileRequest request) const
virtual

Describes a user profile. For more information, see CreateUserProfile.

See Also:

AWS API Reference

◆ DescribeUserProfileAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeUserProfileAsync ( const Model::DescribeUserProfileRequest request,
const DescribeUserProfileResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Describes a user profile. For more information, see CreateUserProfile.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeUserProfileCallable()

virtual Model::DescribeUserProfileOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeUserProfileCallable ( const Model::DescribeUserProfileRequest request) const
virtual

Describes a user profile. For more information, see CreateUserProfile.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeWorkforce()

virtual Model::DescribeWorkforceOutcome Aws::SageMaker::SageMakerClient::DescribeWorkforce ( const Model::DescribeWorkforceRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DescribeWorkforceAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeWorkforceAsync ( const Model::DescribeWorkforceRequest request,
const DescribeWorkforceResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeWorkforceCallable()

virtual Model::DescribeWorkforceOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeWorkforceCallable ( const Model::DescribeWorkforceRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DescribeWorkteam()

virtual Model::DescribeWorkteamOutcome Aws::SageMaker::SageMakerClient::DescribeWorkteam ( const Model::DescribeWorkteamRequest request) const
virtual

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).

See Also:

AWS API Reference

◆ DescribeWorkteamAsync()

virtual void Aws::SageMaker::SageMakerClient::DescribeWorkteamAsync ( const Model::DescribeWorkteamRequest request,
const DescribeWorkteamResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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).

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DescribeWorkteamCallable()

virtual Model::DescribeWorkteamOutcomeCallable Aws::SageMaker::SageMakerClient::DescribeWorkteamCallable ( const Model::DescribeWorkteamRequest request) const
virtual

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).

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ DisassociateTrialComponent()

virtual Model::DisassociateTrialComponentOutcome Aws::SageMaker::SageMakerClient::DisassociateTrialComponent ( const Model::DisassociateTrialComponentRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ DisassociateTrialComponentAsync()

virtual void Aws::SageMaker::SageMakerClient::DisassociateTrialComponentAsync ( const Model::DisassociateTrialComponentRequest request,
const DisassociateTrialComponentResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ DisassociateTrialComponentCallable()

virtual Model::DisassociateTrialComponentOutcomeCallable Aws::SageMaker::SageMakerClient::DisassociateTrialComponentCallable ( const Model::DisassociateTrialComponentRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ GetSearchSuggestions()

virtual Model::GetSearchSuggestionsOutcome Aws::SageMaker::SageMakerClient::GetSearchSuggestions ( const Model::GetSearchSuggestionsRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ GetSearchSuggestionsAsync()

virtual void Aws::SageMaker::SageMakerClient::GetSearchSuggestionsAsync ( const Model::GetSearchSuggestionsRequest request,
const GetSearchSuggestionsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ GetSearchSuggestionsCallable()

virtual Model::GetSearchSuggestionsOutcomeCallable Aws::SageMaker::SageMakerClient::GetSearchSuggestionsCallable ( const Model::GetSearchSuggestionsRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListAlgorithms()

virtual Model::ListAlgorithmsOutcome Aws::SageMaker::SageMakerClient::ListAlgorithms ( const Model::ListAlgorithmsRequest request) const
virtual

Lists the machine learning algorithms that have been created.

See Also:

AWS API Reference

◆ ListAlgorithmsAsync()

virtual void Aws::SageMaker::SageMakerClient::ListAlgorithmsAsync ( const Model::ListAlgorithmsRequest request,
const ListAlgorithmsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Lists the machine learning algorithms that have been created.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListAlgorithmsCallable()

virtual Model::ListAlgorithmsOutcomeCallable Aws::SageMaker::SageMakerClient::ListAlgorithmsCallable ( const Model::ListAlgorithmsRequest request) const
virtual

Lists the machine learning algorithms that have been created.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListAppImageConfigs()

virtual Model::ListAppImageConfigsOutcome Aws::SageMaker::SageMakerClient::ListAppImageConfigs ( const Model::ListAppImageConfigsRequest request) const
virtual

Lists the AppImageConfigs in your account and their properties. The list can be filtered by creation time or modified time, and whether the AppImageConfig name contains a specified string.

See Also:

AWS API Reference

◆ ListAppImageConfigsAsync()

virtual void Aws::SageMaker::SageMakerClient::ListAppImageConfigsAsync ( const Model::ListAppImageConfigsRequest request,
const ListAppImageConfigsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Lists the AppImageConfigs in your account and their properties. The list can be filtered by creation time or modified time, and whether the AppImageConfig name contains a specified string.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListAppImageConfigsCallable()

virtual Model::ListAppImageConfigsOutcomeCallable Aws::SageMaker::SageMakerClient::ListAppImageConfigsCallable ( const Model::ListAppImageConfigsRequest request) const
virtual

Lists the AppImageConfigs in your account and their properties. The list can be filtered by creation time or modified time, and whether the AppImageConfig name contains a specified string.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListApps()

virtual Model::ListAppsOutcome Aws::SageMaker::SageMakerClient::ListApps ( const Model::ListAppsRequest request) const
virtual

Lists apps.

See Also:

AWS API Reference

◆ ListAppsAsync()

virtual void Aws::SageMaker::SageMakerClient::ListAppsAsync ( const Model::ListAppsRequest request,
const ListAppsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Lists apps.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListAppsCallable()

virtual Model::ListAppsOutcomeCallable Aws::SageMaker::SageMakerClient::ListAppsCallable ( const Model::ListAppsRequest request) const
virtual

Lists apps.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListAutoMLJobs()

virtual Model::ListAutoMLJobsOutcome Aws::SageMaker::SageMakerClient::ListAutoMLJobs ( const Model::ListAutoMLJobsRequest request) const
virtual

Request a list of jobs.

See Also:

AWS API Reference

◆ ListAutoMLJobsAsync()

virtual void Aws::SageMaker::SageMakerClient::ListAutoMLJobsAsync ( const Model::ListAutoMLJobsRequest request,
const ListAutoMLJobsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Request a list of jobs.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListAutoMLJobsCallable()

virtual Model::ListAutoMLJobsOutcomeCallable Aws::SageMaker::SageMakerClient::ListAutoMLJobsCallable ( const Model::ListAutoMLJobsRequest request) const
virtual

Request a list of jobs.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListCandidatesForAutoMLJob()

virtual Model::ListCandidatesForAutoMLJobOutcome Aws::SageMaker::SageMakerClient::ListCandidatesForAutoMLJob ( const Model::ListCandidatesForAutoMLJobRequest request) const
virtual

List the Candidates created for the job.

See Also:

AWS API Reference

◆ ListCandidatesForAutoMLJobAsync()

virtual void Aws::SageMaker::SageMakerClient::ListCandidatesForAutoMLJobAsync ( const Model::ListCandidatesForAutoMLJobRequest request,
const ListCandidatesForAutoMLJobResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

List the Candidates created for the job.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListCandidatesForAutoMLJobCallable()

virtual Model::ListCandidatesForAutoMLJobOutcomeCallable Aws::SageMaker::SageMakerClient::ListCandidatesForAutoMLJobCallable ( const Model::ListCandidatesForAutoMLJobRequest request) const
virtual

List the Candidates created for the job.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListCodeRepositories()

virtual Model::ListCodeRepositoriesOutcome Aws::SageMaker::SageMakerClient::ListCodeRepositories ( const Model::ListCodeRepositoriesRequest request) const
virtual

Gets a list of the Git repositories in your account.

See Also:

AWS API Reference

◆ ListCodeRepositoriesAsync()

virtual void Aws::SageMaker::SageMakerClient::ListCodeRepositoriesAsync ( const Model::ListCodeRepositoriesRequest request,
const ListCodeRepositoriesResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Gets a list of the Git repositories in your account.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListCodeRepositoriesCallable()

virtual Model::ListCodeRepositoriesOutcomeCallable Aws::SageMaker::SageMakerClient::ListCodeRepositoriesCallable ( const Model::ListCodeRepositoriesRequest request) const
virtual

Gets a list of the Git repositories in your account.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListCompilationJobs()

virtual Model::ListCompilationJobsOutcome Aws::SageMaker::SageMakerClient::ListCompilationJobs ( const Model::ListCompilationJobsRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ ListCompilationJobsAsync()

virtual void Aws::SageMaker::SageMakerClient::ListCompilationJobsAsync ( const Model::ListCompilationJobsRequest request,
const ListCompilationJobsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListCompilationJobsCallable()

virtual Model::ListCompilationJobsOutcomeCallable Aws::SageMaker::SageMakerClient::ListCompilationJobsCallable ( const Model::ListCompilationJobsRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListDomains()

virtual Model::ListDomainsOutcome Aws::SageMaker::SageMakerClient::ListDomains ( const Model::ListDomainsRequest request) const
virtual

Lists the domains.

See Also:

AWS API Reference

◆ ListDomainsAsync()

virtual void Aws::SageMaker::SageMakerClient::ListDomainsAsync ( const Model::ListDomainsRequest request,
const ListDomainsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Lists the domains.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListDomainsCallable()

virtual Model::ListDomainsOutcomeCallable Aws::SageMaker::SageMakerClient::ListDomainsCallable ( const Model::ListDomainsRequest request) const
virtual

Lists the domains.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListEndpointConfigs()

virtual Model::ListEndpointConfigsOutcome Aws::SageMaker::SageMakerClient::ListEndpointConfigs ( const Model::ListEndpointConfigsRequest request) const
virtual

Lists endpoint configurations.

See Also:

AWS API Reference

◆ ListEndpointConfigsAsync()

virtual void Aws::SageMaker::SageMakerClient::ListEndpointConfigsAsync ( const Model::ListEndpointConfigsRequest request,
const ListEndpointConfigsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Lists endpoint configurations.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListEndpointConfigsCallable()

virtual Model::ListEndpointConfigsOutcomeCallable Aws::SageMaker::SageMakerClient::ListEndpointConfigsCallable ( const Model::ListEndpointConfigsRequest request) const
virtual

Lists endpoint configurations.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListEndpoints()

virtual Model::ListEndpointsOutcome Aws::SageMaker::SageMakerClient::ListEndpoints ( const Model::ListEndpointsRequest request) const
virtual

Lists endpoints.

See Also:

AWS API Reference

◆ ListEndpointsAsync()

virtual void Aws::SageMaker::SageMakerClient::ListEndpointsAsync ( const Model::ListEndpointsRequest request,
const ListEndpointsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Lists endpoints.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListEndpointsCallable()

virtual Model::ListEndpointsOutcomeCallable Aws::SageMaker::SageMakerClient::ListEndpointsCallable ( const Model::ListEndpointsRequest request) const
virtual

Lists endpoints.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListExperiments()

virtual Model::ListExperimentsOutcome Aws::SageMaker::SageMakerClient::ListExperiments ( const Model::ListExperimentsRequest request) const
virtual

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.

See Also:

AWS API Reference

◆ ListExperimentsAsync()

virtual void Aws::SageMaker::SageMakerClient::ListExperimentsAsync ( const Model::ListExperimentsRequest request,
const ListExperimentsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

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.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListExperimentsCallable()

virtual Model::ListExperimentsOutcomeCallable Aws::SageMaker::SageMakerClient::ListExperimentsCallable ( const Model::ListExperimentsRequest request) const
virtual

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.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListFlowDefinitions()

virtual Model::ListFlowDefinitionsOutcome Aws::SageMaker::SageMakerClient::ListFlowDefinitions ( const Model::ListFlowDefinitionsRequest request) const
virtual

Returns information about the flow definitions in your account.

See Also:

AWS API Reference

◆ ListFlowDefinitionsAsync()

virtual void Aws::SageMaker::SageMakerClient::ListFlowDefinitionsAsync ( const Model::ListFlowDefinitionsRequest request,
const ListFlowDefinitionsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Returns information about the flow definitions in your account.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListFlowDefinitionsCallable()

virtual Model::ListFlowDefinitionsOutcomeCallable Aws::SageMaker::SageMakerClient::ListFlowDefinitionsCallable ( const Model::ListFlowDefinitionsRequest request) const
virtual

Returns information about the flow definitions in your account.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListHumanTaskUis()

virtual Model::ListHumanTaskUisOutcome Aws::SageMaker::SageMakerClient::ListHumanTaskUis ( const Model::ListHumanTaskUisRequest request) const
virtual

Returns information about the human task user interfaces in your account.

See Also:

AWS API Reference

◆ ListHumanTaskUisAsync()

virtual void Aws::SageMaker::SageMakerClient::ListHumanTaskUisAsync ( const Model::ListHumanTaskUisRequest request,
const ListHumanTaskUisResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Returns information about the human task user interfaces in your account.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListHumanTaskUisCallable()

virtual Model::ListHumanTaskUisOutcomeCallable Aws::SageMaker::SageMakerClient::ListHumanTaskUisCallable ( const Model::ListHumanTaskUisRequest request) const
virtual

Returns information about the human task user interfaces in your account.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListHyperParameterTuningJobs()

virtual Model::ListHyperParameterTuningJobsOutcome Aws::SageMaker::SageMakerClient::ListHyperParameterTuningJobs ( const Model::ListHyperParameterTuningJobsRequest request) const
virtual

Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.

See Also:

AWS API Reference

◆ ListHyperParameterTuningJobsAsync()

virtual void Aws::SageMaker::SageMakerClient::ListHyperParameterTuningJobsAsync ( const Model::ListHyperParameterTuningJobsRequest request,
const ListHyperParameterTuningJobsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListHyperParameterTuningJobsCallable()

virtual Model::ListHyperParameterTuningJobsOutcomeCallable Aws::SageMaker::SageMakerClient::ListHyperParameterTuningJobsCallable ( const Model::ListHyperParameterTuningJobsRequest request) const
virtual

Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListImages()

virtual Model::ListImagesOutcome Aws::SageMaker::SageMakerClient::ListImages ( const Model::ListImagesRequest request) const
virtual

Lists the images in your account and their properties. The list can be filtered by creation time or modified time, and whether the image name contains a specified string.

See Also:

AWS API Reference

◆ ListImagesAsync()

virtual void Aws::SageMaker::SageMakerClient::ListImagesAsync ( const Model::ListImagesRequest request,
const ListImagesResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Lists the images in your account and their properties. The list can be filtered by creation time or modified time, and whether the image name contains a specified string.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListImagesCallable()

virtual Model::ListImagesOutcomeCallable Aws::SageMaker::SageMakerClient::ListImagesCallable ( const Model::ListImagesRequest request) const
virtual

Lists the images in your account and their properties. The list can be filtered by creation time or modified time, and whether the image name contains a specified string.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListImageVersions()

virtual Model::ListImageVersionsOutcome Aws::SageMaker::SageMakerClient::ListImageVersions ( const Model::ListImageVersionsRequest request) const
virtual

Lists the versions of a specified image and their properties. The list can be filtered by creation time or modified time.

See Also:

AWS API Reference

◆ ListImageVersionsAsync()

virtual void Aws::SageMaker::SageMakerClient::ListImageVersionsAsync ( const Model::ListImageVersionsRequest request,
const ListImageVersionsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Lists the versions of a specified image and their properties. The list can be filtered by creation time or modified time.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListImageVersionsCallable()

virtual Model::ListImageVersionsOutcomeCallable Aws::SageMaker::SageMakerClient::ListImageVersionsCallable ( const Model::ListImageVersionsRequest request) const
virtual

Lists the versions of a specified image and their properties. The list can be filtered by creation time or modified time.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListLabelingJobs()

virtual Model::ListLabelingJobsOutcome Aws::SageMaker::SageMakerClient::ListLabelingJobs ( const Model::ListLabelingJobsRequest request) const
virtual

Gets a list of labeling jobs.

See Also:

AWS API Reference

◆ ListLabelingJobsAsync()

virtual void Aws::SageMaker::SageMakerClient::ListLabelingJobsAsync ( const Model::ListLabelingJobsRequest request,
const ListLabelingJobsResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Gets a list of labeling jobs.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListLabelingJobsCallable()

virtual Model::ListLabelingJobsOutcomeCallable Aws::SageMaker::SageMakerClient::ListLabelingJobsCallable ( const Model::ListLabelingJobsRequest request) const
virtual

Gets a list of labeling jobs.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListLabelingJobsForWorkteam()

virtual Model::ListLabelingJobsForWorkteamOutcome Aws::SageMaker::SageMakerClient::ListLabelingJobsForWorkteam ( const Model::ListLabelingJobsForWorkteamRequest request) const
virtual

Gets a list of labeling jobs assigned to a specified work team.

See Also:

AWS API Reference

◆ ListLabelingJobsForWorkteamAsync()

virtual void Aws::SageMaker::SageMakerClient::ListLabelingJobsForWorkteamAsync ( const Model::ListLabelingJobsForWorkteamRequest request,
const ListLabelingJobsForWorkteamResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Gets a list of labeling jobs assigned to a specified work team.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListLabelingJobsForWorkteamCallable()

virtual Model::ListLabelingJobsForWorkteamOutcomeCallable Aws::SageMaker::SageMakerClient::ListLabelingJobsForWorkteamCallable ( const Model::ListLabelingJobsForWorkteamRequest request) const
virtual

Gets a list of labeling jobs assigned to a specified work team.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListModelPackages()

virtual Model::ListModelPackagesOutcome Aws::SageMaker::SageMakerClient::ListModelPackages ( const Model::ListModelPackagesRequest request) const
virtual

Lists the model packages that have been created.

See Also:

AWS API Reference

◆ ListModelPackagesAsync()

virtual void Aws::SageMaker::SageMakerClient::ListModelPackagesAsync ( const Model::ListModelPackagesRequest request,
const ListModelPackagesResponseReceivedHandler handler,
const std::shared_ptr< const Aws::Client::AsyncCallerContext > &  context = nullptr 
) const
virtual

Lists the model packages that have been created.

See Also:

AWS API Reference

Queues the request into a thread executor and triggers associated callback when operation has finished.

◆ ListModelPackagesCallable()

virtual Model::ListModelPackagesOutcomeCallable Aws::SageMaker::SageMakerClient::ListModelPackagesCallable ( const Model::ListModelPackagesRequest request) const
virtual

Lists the model packages that have been created.

See Also:

AWS API Reference

returns a future to the operation so that it can be executed in parallel to other requests.

◆ ListModels()

virtual Model::ListModelsOutcome Aws::SageMaker::SageMakerClient::ListModels ( const Model::ListModelsRequest request) const
virtual

Lists models created with the CreateModel API.

See Also:

AWS