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pxz-hos-client-cpp-module/support/aws-sdk-cpp-master/aws-cpp-sdk-sagemaker/include/aws/sagemaker/SageMakerClient.h

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/**
* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
* SPDX-License-Identifier: Apache-2.0.
*/
#pragma once
#include <aws/sagemaker/SageMaker_EXPORTS.h>
#include <aws/sagemaker/SageMakerErrors.h>
#include <aws/core/client/AWSError.h>
#include <aws/core/client/ClientConfiguration.h>
#include <aws/core/client/AWSClient.h>
#include <aws/core/utils/memory/stl/AWSString.h>
#include <aws/core/utils/json/JsonSerializer.h>
#include <aws/sagemaker/model/AddTagsResult.h>
#include <aws/sagemaker/model/AssociateTrialComponentResult.h>
#include <aws/sagemaker/model/CreateAlgorithmResult.h>
#include <aws/sagemaker/model/CreateAppResult.h>
#include <aws/sagemaker/model/CreateAutoMLJobResult.h>
#include <aws/sagemaker/model/CreateCodeRepositoryResult.h>
#include <aws/sagemaker/model/CreateCompilationJobResult.h>
#include <aws/sagemaker/model/CreateDomainResult.h>
#include <aws/sagemaker/model/CreateEndpointResult.h>
#include <aws/sagemaker/model/CreateEndpointConfigResult.h>
#include <aws/sagemaker/model/CreateExperimentResult.h>
#include <aws/sagemaker/model/CreateFlowDefinitionResult.h>
#include <aws/sagemaker/model/CreateHumanTaskUiResult.h>
#include <aws/sagemaker/model/CreateHyperParameterTuningJobResult.h>
#include <aws/sagemaker/model/CreateLabelingJobResult.h>
#include <aws/sagemaker/model/CreateModelResult.h>
#include <aws/sagemaker/model/CreateModelPackageResult.h>
#include <aws/sagemaker/model/CreateMonitoringScheduleResult.h>
#include <aws/sagemaker/model/CreateNotebookInstanceResult.h>
#include <aws/sagemaker/model/CreateNotebookInstanceLifecycleConfigResult.h>
#include <aws/sagemaker/model/CreatePresignedDomainUrlResult.h>
#include <aws/sagemaker/model/CreatePresignedNotebookInstanceUrlResult.h>
#include <aws/sagemaker/model/CreateProcessingJobResult.h>
#include <aws/sagemaker/model/CreateTrainingJobResult.h>
#include <aws/sagemaker/model/CreateTransformJobResult.h>
#include <aws/sagemaker/model/CreateTrialResult.h>
#include <aws/sagemaker/model/CreateTrialComponentResult.h>
#include <aws/sagemaker/model/CreateUserProfileResult.h>
#include <aws/sagemaker/model/CreateWorkforceResult.h>
#include <aws/sagemaker/model/CreateWorkteamResult.h>
#include <aws/sagemaker/model/DeleteExperimentResult.h>
#include <aws/sagemaker/model/DeleteFlowDefinitionResult.h>
#include <aws/sagemaker/model/DeleteHumanTaskUiResult.h>
#include <aws/sagemaker/model/DeleteTagsResult.h>
#include <aws/sagemaker/model/DeleteTrialResult.h>
#include <aws/sagemaker/model/DeleteTrialComponentResult.h>
#include <aws/sagemaker/model/DeleteWorkforceResult.h>
#include <aws/sagemaker/model/DeleteWorkteamResult.h>
#include <aws/sagemaker/model/DescribeAlgorithmResult.h>
#include <aws/sagemaker/model/DescribeAppResult.h>
#include <aws/sagemaker/model/DescribeAutoMLJobResult.h>
#include <aws/sagemaker/model/DescribeCodeRepositoryResult.h>
#include <aws/sagemaker/model/DescribeCompilationJobResult.h>
#include <aws/sagemaker/model/DescribeDomainResult.h>
#include <aws/sagemaker/model/DescribeEndpointResult.h>
#include <aws/sagemaker/model/DescribeEndpointConfigResult.h>
#include <aws/sagemaker/model/DescribeExperimentResult.h>
#include <aws/sagemaker/model/DescribeFlowDefinitionResult.h>
#include <aws/sagemaker/model/DescribeHumanTaskUiResult.h>
#include <aws/sagemaker/model/DescribeHyperParameterTuningJobResult.h>
#include <aws/sagemaker/model/DescribeLabelingJobResult.h>
#include <aws/sagemaker/model/DescribeModelResult.h>
#include <aws/sagemaker/model/DescribeModelPackageResult.h>
#include <aws/sagemaker/model/DescribeMonitoringScheduleResult.h>
#include <aws/sagemaker/model/DescribeNotebookInstanceResult.h>
#include <aws/sagemaker/model/DescribeNotebookInstanceLifecycleConfigResult.h>
#include <aws/sagemaker/model/DescribeProcessingJobResult.h>
#include <aws/sagemaker/model/DescribeSubscribedWorkteamResult.h>
#include <aws/sagemaker/model/DescribeTrainingJobResult.h>
#include <aws/sagemaker/model/DescribeTransformJobResult.h>
#include <aws/sagemaker/model/DescribeTrialResult.h>
#include <aws/sagemaker/model/DescribeTrialComponentResult.h>
#include <aws/sagemaker/model/DescribeUserProfileResult.h>
#include <aws/sagemaker/model/DescribeWorkforceResult.h>
#include <aws/sagemaker/model/DescribeWorkteamResult.h>
#include <aws/sagemaker/model/DisassociateTrialComponentResult.h>
#include <aws/sagemaker/model/GetSearchSuggestionsResult.h>
#include <aws/sagemaker/model/ListAlgorithmsResult.h>
#include <aws/sagemaker/model/ListAppsResult.h>
#include <aws/sagemaker/model/ListAutoMLJobsResult.h>
#include <aws/sagemaker/model/ListCandidatesForAutoMLJobResult.h>
#include <aws/sagemaker/model/ListCodeRepositoriesResult.h>
#include <aws/sagemaker/model/ListCompilationJobsResult.h>
#include <aws/sagemaker/model/ListDomainsResult.h>
#include <aws/sagemaker/model/ListEndpointConfigsResult.h>
#include <aws/sagemaker/model/ListEndpointsResult.h>
#include <aws/sagemaker/model/ListExperimentsResult.h>
#include <aws/sagemaker/model/ListFlowDefinitionsResult.h>
#include <aws/sagemaker/model/ListHumanTaskUisResult.h>
#include <aws/sagemaker/model/ListHyperParameterTuningJobsResult.h>
#include <aws/sagemaker/model/ListLabelingJobsResult.h>
#include <aws/sagemaker/model/ListLabelingJobsForWorkteamResult.h>
#include <aws/sagemaker/model/ListModelPackagesResult.h>
#include <aws/sagemaker/model/ListModelsResult.h>
#include <aws/sagemaker/model/ListMonitoringExecutionsResult.h>
#include <aws/sagemaker/model/ListMonitoringSchedulesResult.h>
#include <aws/sagemaker/model/ListNotebookInstanceLifecycleConfigsResult.h>
#include <aws/sagemaker/model/ListNotebookInstancesResult.h>
#include <aws/sagemaker/model/ListProcessingJobsResult.h>
#include <aws/sagemaker/model/ListSubscribedWorkteamsResult.h>
#include <aws/sagemaker/model/ListTagsResult.h>
#include <aws/sagemaker/model/ListTrainingJobsResult.h>
#include <aws/sagemaker/model/ListTrainingJobsForHyperParameterTuningJobResult.h>
#include <aws/sagemaker/model/ListTransformJobsResult.h>
#include <aws/sagemaker/model/ListTrialComponentsResult.h>
#include <aws/sagemaker/model/ListTrialsResult.h>
#include <aws/sagemaker/model/ListUserProfilesResult.h>
#include <aws/sagemaker/model/ListWorkforcesResult.h>
#include <aws/sagemaker/model/ListWorkteamsResult.h>
#include <aws/sagemaker/model/RenderUiTemplateResult.h>
#include <aws/sagemaker/model/SearchResult.h>
#include <aws/sagemaker/model/UpdateCodeRepositoryResult.h>
#include <aws/sagemaker/model/UpdateDomainResult.h>
#include <aws/sagemaker/model/UpdateEndpointResult.h>
#include <aws/sagemaker/model/UpdateEndpointWeightsAndCapacitiesResult.h>
#include <aws/sagemaker/model/UpdateExperimentResult.h>
#include <aws/sagemaker/model/UpdateMonitoringScheduleResult.h>
#include <aws/sagemaker/model/UpdateNotebookInstanceResult.h>
#include <aws/sagemaker/model/UpdateNotebookInstanceLifecycleConfigResult.h>
#include <aws/sagemaker/model/UpdateTrialResult.h>
#include <aws/sagemaker/model/UpdateTrialComponentResult.h>
#include <aws/sagemaker/model/UpdateUserProfileResult.h>
#include <aws/sagemaker/model/UpdateWorkforceResult.h>
#include <aws/sagemaker/model/UpdateWorkteamResult.h>
#include <aws/core/NoResult.h>
#include <aws/core/client/AsyncCallerContext.h>
#include <aws/core/http/HttpTypes.h>
#include <future>
#include <functional>
namespace Aws
{
namespace Http
{
class HttpClient;
class HttpClientFactory;
} // namespace Http
namespace Utils
{
template< typename R, typename E> class Outcome;
namespace Threading
{
class Executor;
} // namespace Threading
} // namespace Utils
namespace Auth
{
class AWSCredentials;
class AWSCredentialsProvider;
} // namespace Auth
namespace Client
{
class RetryStrategy;
} // namespace Client
namespace SageMaker
{
namespace Model
{
class AddTagsRequest;
class AssociateTrialComponentRequest;
class CreateAlgorithmRequest;
class CreateAppRequest;
class CreateAutoMLJobRequest;
class CreateCodeRepositoryRequest;
class CreateCompilationJobRequest;
class CreateDomainRequest;
class CreateEndpointRequest;
class CreateEndpointConfigRequest;
class CreateExperimentRequest;
class CreateFlowDefinitionRequest;
class CreateHumanTaskUiRequest;
class CreateHyperParameterTuningJobRequest;
class CreateLabelingJobRequest;
class CreateModelRequest;
class CreateModelPackageRequest;
class CreateMonitoringScheduleRequest;
class CreateNotebookInstanceRequest;
class CreateNotebookInstanceLifecycleConfigRequest;
class CreatePresignedDomainUrlRequest;
class CreatePresignedNotebookInstanceUrlRequest;
class CreateProcessingJobRequest;
class CreateTrainingJobRequest;
class CreateTransformJobRequest;
class CreateTrialRequest;
class CreateTrialComponentRequest;
class CreateUserProfileRequest;
class CreateWorkforceRequest;
class CreateWorkteamRequest;
class DeleteAlgorithmRequest;
class DeleteAppRequest;
class DeleteCodeRepositoryRequest;
class DeleteDomainRequest;
class DeleteEndpointRequest;
class DeleteEndpointConfigRequest;
class DeleteExperimentRequest;
class DeleteFlowDefinitionRequest;
class DeleteHumanTaskUiRequest;
class DeleteModelRequest;
class DeleteModelPackageRequest;
class DeleteMonitoringScheduleRequest;
class DeleteNotebookInstanceRequest;
class DeleteNotebookInstanceLifecycleConfigRequest;
class DeleteTagsRequest;
class DeleteTrialRequest;
class DeleteTrialComponentRequest;
class DeleteUserProfileRequest;
class DeleteWorkforceRequest;
class DeleteWorkteamRequest;
class DescribeAlgorithmRequest;
class DescribeAppRequest;
class DescribeAutoMLJobRequest;
class DescribeCodeRepositoryRequest;
class DescribeCompilationJobRequest;
class DescribeDomainRequest;
class DescribeEndpointRequest;
class DescribeEndpointConfigRequest;
class DescribeExperimentRequest;
class DescribeFlowDefinitionRequest;
class DescribeHumanTaskUiRequest;
class DescribeHyperParameterTuningJobRequest;
class DescribeLabelingJobRequest;
class DescribeModelRequest;
class DescribeModelPackageRequest;
class DescribeMonitoringScheduleRequest;
class DescribeNotebookInstanceRequest;
class DescribeNotebookInstanceLifecycleConfigRequest;
class DescribeProcessingJobRequest;
class DescribeSubscribedWorkteamRequest;
class DescribeTrainingJobRequest;
class DescribeTransformJobRequest;
class DescribeTrialRequest;
class DescribeTrialComponentRequest;
class DescribeUserProfileRequest;
class DescribeWorkforceRequest;
class DescribeWorkteamRequest;
class DisassociateTrialComponentRequest;
class GetSearchSuggestionsRequest;
class ListAlgorithmsRequest;
class ListAppsRequest;
class ListAutoMLJobsRequest;
class ListCandidatesForAutoMLJobRequest;
class ListCodeRepositoriesRequest;
class ListCompilationJobsRequest;
class ListDomainsRequest;
class ListEndpointConfigsRequest;
class ListEndpointsRequest;
class ListExperimentsRequest;
class ListFlowDefinitionsRequest;
class ListHumanTaskUisRequest;
class ListHyperParameterTuningJobsRequest;
class ListLabelingJobsRequest;
class ListLabelingJobsForWorkteamRequest;
class ListModelPackagesRequest;
class ListModelsRequest;
class ListMonitoringExecutionsRequest;
class ListMonitoringSchedulesRequest;
class ListNotebookInstanceLifecycleConfigsRequest;
class ListNotebookInstancesRequest;
class ListProcessingJobsRequest;
class ListSubscribedWorkteamsRequest;
class ListTagsRequest;
class ListTrainingJobsRequest;
class ListTrainingJobsForHyperParameterTuningJobRequest;
class ListTransformJobsRequest;
class ListTrialComponentsRequest;
class ListTrialsRequest;
class ListUserProfilesRequest;
class ListWorkforcesRequest;
class ListWorkteamsRequest;
class RenderUiTemplateRequest;
class SearchRequest;
class StartMonitoringScheduleRequest;
class StartNotebookInstanceRequest;
class StopAutoMLJobRequest;
class StopCompilationJobRequest;
class StopHyperParameterTuningJobRequest;
class StopLabelingJobRequest;
class StopMonitoringScheduleRequest;
class StopNotebookInstanceRequest;
class StopProcessingJobRequest;
class StopTrainingJobRequest;
class StopTransformJobRequest;
class UpdateCodeRepositoryRequest;
class UpdateDomainRequest;
class UpdateEndpointRequest;
class UpdateEndpointWeightsAndCapacitiesRequest;
class UpdateExperimentRequest;
class UpdateMonitoringScheduleRequest;
class UpdateNotebookInstanceRequest;
class UpdateNotebookInstanceLifecycleConfigRequest;
class UpdateTrialRequest;
class UpdateTrialComponentRequest;
class UpdateUserProfileRequest;
class UpdateWorkforceRequest;
class UpdateWorkteamRequest;
typedef Aws::Utils::Outcome<AddTagsResult, SageMakerError> AddTagsOutcome;
typedef Aws::Utils::Outcome<AssociateTrialComponentResult, SageMakerError> AssociateTrialComponentOutcome;
typedef Aws::Utils::Outcome<CreateAlgorithmResult, SageMakerError> CreateAlgorithmOutcome;
typedef Aws::Utils::Outcome<CreateAppResult, SageMakerError> CreateAppOutcome;
typedef Aws::Utils::Outcome<CreateAutoMLJobResult, SageMakerError> CreateAutoMLJobOutcome;
typedef Aws::Utils::Outcome<CreateCodeRepositoryResult, SageMakerError> CreateCodeRepositoryOutcome;
typedef Aws::Utils::Outcome<CreateCompilationJobResult, SageMakerError> CreateCompilationJobOutcome;
typedef Aws::Utils::Outcome<CreateDomainResult, SageMakerError> CreateDomainOutcome;
typedef Aws::Utils::Outcome<CreateEndpointResult, SageMakerError> CreateEndpointOutcome;
typedef Aws::Utils::Outcome<CreateEndpointConfigResult, SageMakerError> CreateEndpointConfigOutcome;
typedef Aws::Utils::Outcome<CreateExperimentResult, SageMakerError> CreateExperimentOutcome;
typedef Aws::Utils::Outcome<CreateFlowDefinitionResult, SageMakerError> CreateFlowDefinitionOutcome;
typedef Aws::Utils::Outcome<CreateHumanTaskUiResult, SageMakerError> CreateHumanTaskUiOutcome;
typedef Aws::Utils::Outcome<CreateHyperParameterTuningJobResult, SageMakerError> CreateHyperParameterTuningJobOutcome;
typedef Aws::Utils::Outcome<CreateLabelingJobResult, SageMakerError> CreateLabelingJobOutcome;
typedef Aws::Utils::Outcome<CreateModelResult, SageMakerError> CreateModelOutcome;
typedef Aws::Utils::Outcome<CreateModelPackageResult, SageMakerError> CreateModelPackageOutcome;
typedef Aws::Utils::Outcome<CreateMonitoringScheduleResult, SageMakerError> CreateMonitoringScheduleOutcome;
typedef Aws::Utils::Outcome<CreateNotebookInstanceResult, SageMakerError> CreateNotebookInstanceOutcome;
typedef Aws::Utils::Outcome<CreateNotebookInstanceLifecycleConfigResult, SageMakerError> CreateNotebookInstanceLifecycleConfigOutcome;
typedef Aws::Utils::Outcome<CreatePresignedDomainUrlResult, SageMakerError> CreatePresignedDomainUrlOutcome;
typedef Aws::Utils::Outcome<CreatePresignedNotebookInstanceUrlResult, SageMakerError> CreatePresignedNotebookInstanceUrlOutcome;
typedef Aws::Utils::Outcome<CreateProcessingJobResult, SageMakerError> CreateProcessingJobOutcome;
typedef Aws::Utils::Outcome<CreateTrainingJobResult, SageMakerError> CreateTrainingJobOutcome;
typedef Aws::Utils::Outcome<CreateTransformJobResult, SageMakerError> CreateTransformJobOutcome;
typedef Aws::Utils::Outcome<CreateTrialResult, SageMakerError> CreateTrialOutcome;
typedef Aws::Utils::Outcome<CreateTrialComponentResult, SageMakerError> CreateTrialComponentOutcome;
typedef Aws::Utils::Outcome<CreateUserProfileResult, SageMakerError> CreateUserProfileOutcome;
typedef Aws::Utils::Outcome<CreateWorkforceResult, SageMakerError> CreateWorkforceOutcome;
typedef Aws::Utils::Outcome<CreateWorkteamResult, SageMakerError> CreateWorkteamOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> DeleteAlgorithmOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> DeleteAppOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> DeleteCodeRepositoryOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> DeleteDomainOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> DeleteEndpointOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> DeleteEndpointConfigOutcome;
typedef Aws::Utils::Outcome<DeleteExperimentResult, SageMakerError> DeleteExperimentOutcome;
typedef Aws::Utils::Outcome<DeleteFlowDefinitionResult, SageMakerError> DeleteFlowDefinitionOutcome;
typedef Aws::Utils::Outcome<DeleteHumanTaskUiResult, SageMakerError> DeleteHumanTaskUiOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> DeleteModelOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> DeleteModelPackageOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> DeleteMonitoringScheduleOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> DeleteNotebookInstanceOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> DeleteNotebookInstanceLifecycleConfigOutcome;
typedef Aws::Utils::Outcome<DeleteTagsResult, SageMakerError> DeleteTagsOutcome;
typedef Aws::Utils::Outcome<DeleteTrialResult, SageMakerError> DeleteTrialOutcome;
typedef Aws::Utils::Outcome<DeleteTrialComponentResult, SageMakerError> DeleteTrialComponentOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> DeleteUserProfileOutcome;
typedef Aws::Utils::Outcome<DeleteWorkforceResult, SageMakerError> DeleteWorkforceOutcome;
typedef Aws::Utils::Outcome<DeleteWorkteamResult, SageMakerError> DeleteWorkteamOutcome;
typedef Aws::Utils::Outcome<DescribeAlgorithmResult, SageMakerError> DescribeAlgorithmOutcome;
typedef Aws::Utils::Outcome<DescribeAppResult, SageMakerError> DescribeAppOutcome;
typedef Aws::Utils::Outcome<DescribeAutoMLJobResult, SageMakerError> DescribeAutoMLJobOutcome;
typedef Aws::Utils::Outcome<DescribeCodeRepositoryResult, SageMakerError> DescribeCodeRepositoryOutcome;
typedef Aws::Utils::Outcome<DescribeCompilationJobResult, SageMakerError> DescribeCompilationJobOutcome;
typedef Aws::Utils::Outcome<DescribeDomainResult, SageMakerError> DescribeDomainOutcome;
typedef Aws::Utils::Outcome<DescribeEndpointResult, SageMakerError> DescribeEndpointOutcome;
typedef Aws::Utils::Outcome<DescribeEndpointConfigResult, SageMakerError> DescribeEndpointConfigOutcome;
typedef Aws::Utils::Outcome<DescribeExperimentResult, SageMakerError> DescribeExperimentOutcome;
typedef Aws::Utils::Outcome<DescribeFlowDefinitionResult, SageMakerError> DescribeFlowDefinitionOutcome;
typedef Aws::Utils::Outcome<DescribeHumanTaskUiResult, SageMakerError> DescribeHumanTaskUiOutcome;
typedef Aws::Utils::Outcome<DescribeHyperParameterTuningJobResult, SageMakerError> DescribeHyperParameterTuningJobOutcome;
typedef Aws::Utils::Outcome<DescribeLabelingJobResult, SageMakerError> DescribeLabelingJobOutcome;
typedef Aws::Utils::Outcome<DescribeModelResult, SageMakerError> DescribeModelOutcome;
typedef Aws::Utils::Outcome<DescribeModelPackageResult, SageMakerError> DescribeModelPackageOutcome;
typedef Aws::Utils::Outcome<DescribeMonitoringScheduleResult, SageMakerError> DescribeMonitoringScheduleOutcome;
typedef Aws::Utils::Outcome<DescribeNotebookInstanceResult, SageMakerError> DescribeNotebookInstanceOutcome;
typedef Aws::Utils::Outcome<DescribeNotebookInstanceLifecycleConfigResult, SageMakerError> DescribeNotebookInstanceLifecycleConfigOutcome;
typedef Aws::Utils::Outcome<DescribeProcessingJobResult, SageMakerError> DescribeProcessingJobOutcome;
typedef Aws::Utils::Outcome<DescribeSubscribedWorkteamResult, SageMakerError> DescribeSubscribedWorkteamOutcome;
typedef Aws::Utils::Outcome<DescribeTrainingJobResult, SageMakerError> DescribeTrainingJobOutcome;
typedef Aws::Utils::Outcome<DescribeTransformJobResult, SageMakerError> DescribeTransformJobOutcome;
typedef Aws::Utils::Outcome<DescribeTrialResult, SageMakerError> DescribeTrialOutcome;
typedef Aws::Utils::Outcome<DescribeTrialComponentResult, SageMakerError> DescribeTrialComponentOutcome;
typedef Aws::Utils::Outcome<DescribeUserProfileResult, SageMakerError> DescribeUserProfileOutcome;
typedef Aws::Utils::Outcome<DescribeWorkforceResult, SageMakerError> DescribeWorkforceOutcome;
typedef Aws::Utils::Outcome<DescribeWorkteamResult, SageMakerError> DescribeWorkteamOutcome;
typedef Aws::Utils::Outcome<DisassociateTrialComponentResult, SageMakerError> DisassociateTrialComponentOutcome;
typedef Aws::Utils::Outcome<GetSearchSuggestionsResult, SageMakerError> GetSearchSuggestionsOutcome;
typedef Aws::Utils::Outcome<ListAlgorithmsResult, SageMakerError> ListAlgorithmsOutcome;
typedef Aws::Utils::Outcome<ListAppsResult, SageMakerError> ListAppsOutcome;
typedef Aws::Utils::Outcome<ListAutoMLJobsResult, SageMakerError> ListAutoMLJobsOutcome;
typedef Aws::Utils::Outcome<ListCandidatesForAutoMLJobResult, SageMakerError> ListCandidatesForAutoMLJobOutcome;
typedef Aws::Utils::Outcome<ListCodeRepositoriesResult, SageMakerError> ListCodeRepositoriesOutcome;
typedef Aws::Utils::Outcome<ListCompilationJobsResult, SageMakerError> ListCompilationJobsOutcome;
typedef Aws::Utils::Outcome<ListDomainsResult, SageMakerError> ListDomainsOutcome;
typedef Aws::Utils::Outcome<ListEndpointConfigsResult, SageMakerError> ListEndpointConfigsOutcome;
typedef Aws::Utils::Outcome<ListEndpointsResult, SageMakerError> ListEndpointsOutcome;
typedef Aws::Utils::Outcome<ListExperimentsResult, SageMakerError> ListExperimentsOutcome;
typedef Aws::Utils::Outcome<ListFlowDefinitionsResult, SageMakerError> ListFlowDefinitionsOutcome;
typedef Aws::Utils::Outcome<ListHumanTaskUisResult, SageMakerError> ListHumanTaskUisOutcome;
typedef Aws::Utils::Outcome<ListHyperParameterTuningJobsResult, SageMakerError> ListHyperParameterTuningJobsOutcome;
typedef Aws::Utils::Outcome<ListLabelingJobsResult, SageMakerError> ListLabelingJobsOutcome;
typedef Aws::Utils::Outcome<ListLabelingJobsForWorkteamResult, SageMakerError> ListLabelingJobsForWorkteamOutcome;
typedef Aws::Utils::Outcome<ListModelPackagesResult, SageMakerError> ListModelPackagesOutcome;
typedef Aws::Utils::Outcome<ListModelsResult, SageMakerError> ListModelsOutcome;
typedef Aws::Utils::Outcome<ListMonitoringExecutionsResult, SageMakerError> ListMonitoringExecutionsOutcome;
typedef Aws::Utils::Outcome<ListMonitoringSchedulesResult, SageMakerError> ListMonitoringSchedulesOutcome;
typedef Aws::Utils::Outcome<ListNotebookInstanceLifecycleConfigsResult, SageMakerError> ListNotebookInstanceLifecycleConfigsOutcome;
typedef Aws::Utils::Outcome<ListNotebookInstancesResult, SageMakerError> ListNotebookInstancesOutcome;
typedef Aws::Utils::Outcome<ListProcessingJobsResult, SageMakerError> ListProcessingJobsOutcome;
typedef Aws::Utils::Outcome<ListSubscribedWorkteamsResult, SageMakerError> ListSubscribedWorkteamsOutcome;
typedef Aws::Utils::Outcome<ListTagsResult, SageMakerError> ListTagsOutcome;
typedef Aws::Utils::Outcome<ListTrainingJobsResult, SageMakerError> ListTrainingJobsOutcome;
typedef Aws::Utils::Outcome<ListTrainingJobsForHyperParameterTuningJobResult, SageMakerError> ListTrainingJobsForHyperParameterTuningJobOutcome;
typedef Aws::Utils::Outcome<ListTransformJobsResult, SageMakerError> ListTransformJobsOutcome;
typedef Aws::Utils::Outcome<ListTrialComponentsResult, SageMakerError> ListTrialComponentsOutcome;
typedef Aws::Utils::Outcome<ListTrialsResult, SageMakerError> ListTrialsOutcome;
typedef Aws::Utils::Outcome<ListUserProfilesResult, SageMakerError> ListUserProfilesOutcome;
typedef Aws::Utils::Outcome<ListWorkforcesResult, SageMakerError> ListWorkforcesOutcome;
typedef Aws::Utils::Outcome<ListWorkteamsResult, SageMakerError> ListWorkteamsOutcome;
typedef Aws::Utils::Outcome<RenderUiTemplateResult, SageMakerError> RenderUiTemplateOutcome;
typedef Aws::Utils::Outcome<SearchResult, SageMakerError> SearchOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> StartMonitoringScheduleOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> StartNotebookInstanceOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> StopAutoMLJobOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> StopCompilationJobOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> StopHyperParameterTuningJobOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> StopLabelingJobOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> StopMonitoringScheduleOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> StopNotebookInstanceOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> StopProcessingJobOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> StopTrainingJobOutcome;
typedef Aws::Utils::Outcome<Aws::NoResult, SageMakerError> StopTransformJobOutcome;
typedef Aws::Utils::Outcome<UpdateCodeRepositoryResult, SageMakerError> UpdateCodeRepositoryOutcome;
typedef Aws::Utils::Outcome<UpdateDomainResult, SageMakerError> UpdateDomainOutcome;
typedef Aws::Utils::Outcome<UpdateEndpointResult, SageMakerError> UpdateEndpointOutcome;
typedef Aws::Utils::Outcome<UpdateEndpointWeightsAndCapacitiesResult, SageMakerError> UpdateEndpointWeightsAndCapacitiesOutcome;
typedef Aws::Utils::Outcome<UpdateExperimentResult, SageMakerError> UpdateExperimentOutcome;
typedef Aws::Utils::Outcome<UpdateMonitoringScheduleResult, SageMakerError> UpdateMonitoringScheduleOutcome;
typedef Aws::Utils::Outcome<UpdateNotebookInstanceResult, SageMakerError> UpdateNotebookInstanceOutcome;
typedef Aws::Utils::Outcome<UpdateNotebookInstanceLifecycleConfigResult, SageMakerError> UpdateNotebookInstanceLifecycleConfigOutcome;
typedef Aws::Utils::Outcome<UpdateTrialResult, SageMakerError> UpdateTrialOutcome;
typedef Aws::Utils::Outcome<UpdateTrialComponentResult, SageMakerError> UpdateTrialComponentOutcome;
typedef Aws::Utils::Outcome<UpdateUserProfileResult, SageMakerError> UpdateUserProfileOutcome;
typedef Aws::Utils::Outcome<UpdateWorkforceResult, SageMakerError> UpdateWorkforceOutcome;
typedef Aws::Utils::Outcome<UpdateWorkteamResult, SageMakerError> UpdateWorkteamOutcome;
typedef std::future<AddTagsOutcome> AddTagsOutcomeCallable;
typedef std::future<AssociateTrialComponentOutcome> AssociateTrialComponentOutcomeCallable;
typedef std::future<CreateAlgorithmOutcome> CreateAlgorithmOutcomeCallable;
typedef std::future<CreateAppOutcome> CreateAppOutcomeCallable;
typedef std::future<CreateAutoMLJobOutcome> CreateAutoMLJobOutcomeCallable;
typedef std::future<CreateCodeRepositoryOutcome> CreateCodeRepositoryOutcomeCallable;
typedef std::future<CreateCompilationJobOutcome> CreateCompilationJobOutcomeCallable;
typedef std::future<CreateDomainOutcome> CreateDomainOutcomeCallable;
typedef std::future<CreateEndpointOutcome> CreateEndpointOutcomeCallable;
typedef std::future<CreateEndpointConfigOutcome> CreateEndpointConfigOutcomeCallable;
typedef std::future<CreateExperimentOutcome> CreateExperimentOutcomeCallable;
typedef std::future<CreateFlowDefinitionOutcome> CreateFlowDefinitionOutcomeCallable;
typedef std::future<CreateHumanTaskUiOutcome> CreateHumanTaskUiOutcomeCallable;
typedef std::future<CreateHyperParameterTuningJobOutcome> CreateHyperParameterTuningJobOutcomeCallable;
typedef std::future<CreateLabelingJobOutcome> CreateLabelingJobOutcomeCallable;
typedef std::future<CreateModelOutcome> CreateModelOutcomeCallable;
typedef std::future<CreateModelPackageOutcome> CreateModelPackageOutcomeCallable;
typedef std::future<CreateMonitoringScheduleOutcome> CreateMonitoringScheduleOutcomeCallable;
typedef std::future<CreateNotebookInstanceOutcome> CreateNotebookInstanceOutcomeCallable;
typedef std::future<CreateNotebookInstanceLifecycleConfigOutcome> CreateNotebookInstanceLifecycleConfigOutcomeCallable;
typedef std::future<CreatePresignedDomainUrlOutcome> CreatePresignedDomainUrlOutcomeCallable;
typedef std::future<CreatePresignedNotebookInstanceUrlOutcome> CreatePresignedNotebookInstanceUrlOutcomeCallable;
typedef std::future<CreateProcessingJobOutcome> CreateProcessingJobOutcomeCallable;
typedef std::future<CreateTrainingJobOutcome> CreateTrainingJobOutcomeCallable;
typedef std::future<CreateTransformJobOutcome> CreateTransformJobOutcomeCallable;
typedef std::future<CreateTrialOutcome> CreateTrialOutcomeCallable;
typedef std::future<CreateTrialComponentOutcome> CreateTrialComponentOutcomeCallable;
typedef std::future<CreateUserProfileOutcome> CreateUserProfileOutcomeCallable;
typedef std::future<CreateWorkforceOutcome> CreateWorkforceOutcomeCallable;
typedef std::future<CreateWorkteamOutcome> CreateWorkteamOutcomeCallable;
typedef std::future<DeleteAlgorithmOutcome> DeleteAlgorithmOutcomeCallable;
typedef std::future<DeleteAppOutcome> DeleteAppOutcomeCallable;
typedef std::future<DeleteCodeRepositoryOutcome> DeleteCodeRepositoryOutcomeCallable;
typedef std::future<DeleteDomainOutcome> DeleteDomainOutcomeCallable;
typedef std::future<DeleteEndpointOutcome> DeleteEndpointOutcomeCallable;
typedef std::future<DeleteEndpointConfigOutcome> DeleteEndpointConfigOutcomeCallable;
typedef std::future<DeleteExperimentOutcome> DeleteExperimentOutcomeCallable;
typedef std::future<DeleteFlowDefinitionOutcome> DeleteFlowDefinitionOutcomeCallable;
typedef std::future<DeleteHumanTaskUiOutcome> DeleteHumanTaskUiOutcomeCallable;
typedef std::future<DeleteModelOutcome> DeleteModelOutcomeCallable;
typedef std::future<DeleteModelPackageOutcome> DeleteModelPackageOutcomeCallable;
typedef std::future<DeleteMonitoringScheduleOutcome> DeleteMonitoringScheduleOutcomeCallable;
typedef std::future<DeleteNotebookInstanceOutcome> DeleteNotebookInstanceOutcomeCallable;
typedef std::future<DeleteNotebookInstanceLifecycleConfigOutcome> DeleteNotebookInstanceLifecycleConfigOutcomeCallable;
typedef std::future<DeleteTagsOutcome> DeleteTagsOutcomeCallable;
typedef std::future<DeleteTrialOutcome> DeleteTrialOutcomeCallable;
typedef std::future<DeleteTrialComponentOutcome> DeleteTrialComponentOutcomeCallable;
typedef std::future<DeleteUserProfileOutcome> DeleteUserProfileOutcomeCallable;
typedef std::future<DeleteWorkforceOutcome> DeleteWorkforceOutcomeCallable;
typedef std::future<DeleteWorkteamOutcome> DeleteWorkteamOutcomeCallable;
typedef std::future<DescribeAlgorithmOutcome> DescribeAlgorithmOutcomeCallable;
typedef std::future<DescribeAppOutcome> DescribeAppOutcomeCallable;
typedef std::future<DescribeAutoMLJobOutcome> DescribeAutoMLJobOutcomeCallable;
typedef std::future<DescribeCodeRepositoryOutcome> DescribeCodeRepositoryOutcomeCallable;
typedef std::future<DescribeCompilationJobOutcome> DescribeCompilationJobOutcomeCallable;
typedef std::future<DescribeDomainOutcome> DescribeDomainOutcomeCallable;
typedef std::future<DescribeEndpointOutcome> DescribeEndpointOutcomeCallable;
typedef std::future<DescribeEndpointConfigOutcome> DescribeEndpointConfigOutcomeCallable;
typedef std::future<DescribeExperimentOutcome> DescribeExperimentOutcomeCallable;
typedef std::future<DescribeFlowDefinitionOutcome> DescribeFlowDefinitionOutcomeCallable;
typedef std::future<DescribeHumanTaskUiOutcome> DescribeHumanTaskUiOutcomeCallable;
typedef std::future<DescribeHyperParameterTuningJobOutcome> DescribeHyperParameterTuningJobOutcomeCallable;
typedef std::future<DescribeLabelingJobOutcome> DescribeLabelingJobOutcomeCallable;
typedef std::future<DescribeModelOutcome> DescribeModelOutcomeCallable;
typedef std::future<DescribeModelPackageOutcome> DescribeModelPackageOutcomeCallable;
typedef std::future<DescribeMonitoringScheduleOutcome> DescribeMonitoringScheduleOutcomeCallable;
typedef std::future<DescribeNotebookInstanceOutcome> DescribeNotebookInstanceOutcomeCallable;
typedef std::future<DescribeNotebookInstanceLifecycleConfigOutcome> DescribeNotebookInstanceLifecycleConfigOutcomeCallable;
typedef std::future<DescribeProcessingJobOutcome> DescribeProcessingJobOutcomeCallable;
typedef std::future<DescribeSubscribedWorkteamOutcome> DescribeSubscribedWorkteamOutcomeCallable;
typedef std::future<DescribeTrainingJobOutcome> DescribeTrainingJobOutcomeCallable;
typedef std::future<DescribeTransformJobOutcome> DescribeTransformJobOutcomeCallable;
typedef std::future<DescribeTrialOutcome> DescribeTrialOutcomeCallable;
typedef std::future<DescribeTrialComponentOutcome> DescribeTrialComponentOutcomeCallable;
typedef std::future<DescribeUserProfileOutcome> DescribeUserProfileOutcomeCallable;
typedef std::future<DescribeWorkforceOutcome> DescribeWorkforceOutcomeCallable;
typedef std::future<DescribeWorkteamOutcome> DescribeWorkteamOutcomeCallable;
typedef std::future<DisassociateTrialComponentOutcome> DisassociateTrialComponentOutcomeCallable;
typedef std::future<GetSearchSuggestionsOutcome> GetSearchSuggestionsOutcomeCallable;
typedef std::future<ListAlgorithmsOutcome> ListAlgorithmsOutcomeCallable;
typedef std::future<ListAppsOutcome> ListAppsOutcomeCallable;
typedef std::future<ListAutoMLJobsOutcome> ListAutoMLJobsOutcomeCallable;
typedef std::future<ListCandidatesForAutoMLJobOutcome> ListCandidatesForAutoMLJobOutcomeCallable;
typedef std::future<ListCodeRepositoriesOutcome> ListCodeRepositoriesOutcomeCallable;
typedef std::future<ListCompilationJobsOutcome> ListCompilationJobsOutcomeCallable;
typedef std::future<ListDomainsOutcome> ListDomainsOutcomeCallable;
typedef std::future<ListEndpointConfigsOutcome> ListEndpointConfigsOutcomeCallable;
typedef std::future<ListEndpointsOutcome> ListEndpointsOutcomeCallable;
typedef std::future<ListExperimentsOutcome> ListExperimentsOutcomeCallable;
typedef std::future<ListFlowDefinitionsOutcome> ListFlowDefinitionsOutcomeCallable;
typedef std::future<ListHumanTaskUisOutcome> ListHumanTaskUisOutcomeCallable;
typedef std::future<ListHyperParameterTuningJobsOutcome> ListHyperParameterTuningJobsOutcomeCallable;
typedef std::future<ListLabelingJobsOutcome> ListLabelingJobsOutcomeCallable;
typedef std::future<ListLabelingJobsForWorkteamOutcome> ListLabelingJobsForWorkteamOutcomeCallable;
typedef std::future<ListModelPackagesOutcome> ListModelPackagesOutcomeCallable;
typedef std::future<ListModelsOutcome> ListModelsOutcomeCallable;
typedef std::future<ListMonitoringExecutionsOutcome> ListMonitoringExecutionsOutcomeCallable;
typedef std::future<ListMonitoringSchedulesOutcome> ListMonitoringSchedulesOutcomeCallable;
typedef std::future<ListNotebookInstanceLifecycleConfigsOutcome> ListNotebookInstanceLifecycleConfigsOutcomeCallable;
typedef std::future<ListNotebookInstancesOutcome> ListNotebookInstancesOutcomeCallable;
typedef std::future<ListProcessingJobsOutcome> ListProcessingJobsOutcomeCallable;
typedef std::future<ListSubscribedWorkteamsOutcome> ListSubscribedWorkteamsOutcomeCallable;
typedef std::future<ListTagsOutcome> ListTagsOutcomeCallable;
typedef std::future<ListTrainingJobsOutcome> ListTrainingJobsOutcomeCallable;
typedef std::future<ListTrainingJobsForHyperParameterTuningJobOutcome> ListTrainingJobsForHyperParameterTuningJobOutcomeCallable;
typedef std::future<ListTransformJobsOutcome> ListTransformJobsOutcomeCallable;
typedef std::future<ListTrialComponentsOutcome> ListTrialComponentsOutcomeCallable;
typedef std::future<ListTrialsOutcome> ListTrialsOutcomeCallable;
typedef std::future<ListUserProfilesOutcome> ListUserProfilesOutcomeCallable;
typedef std::future<ListWorkforcesOutcome> ListWorkforcesOutcomeCallable;
typedef std::future<ListWorkteamsOutcome> ListWorkteamsOutcomeCallable;
typedef std::future<RenderUiTemplateOutcome> RenderUiTemplateOutcomeCallable;
typedef std::future<SearchOutcome> SearchOutcomeCallable;
typedef std::future<StartMonitoringScheduleOutcome> StartMonitoringScheduleOutcomeCallable;
typedef std::future<StartNotebookInstanceOutcome> StartNotebookInstanceOutcomeCallable;
typedef std::future<StopAutoMLJobOutcome> StopAutoMLJobOutcomeCallable;
typedef std::future<StopCompilationJobOutcome> StopCompilationJobOutcomeCallable;
typedef std::future<StopHyperParameterTuningJobOutcome> StopHyperParameterTuningJobOutcomeCallable;
typedef std::future<StopLabelingJobOutcome> StopLabelingJobOutcomeCallable;
typedef std::future<StopMonitoringScheduleOutcome> StopMonitoringScheduleOutcomeCallable;
typedef std::future<StopNotebookInstanceOutcome> StopNotebookInstanceOutcomeCallable;
typedef std::future<StopProcessingJobOutcome> StopProcessingJobOutcomeCallable;
typedef std::future<StopTrainingJobOutcome> StopTrainingJobOutcomeCallable;
typedef std::future<StopTransformJobOutcome> StopTransformJobOutcomeCallable;
typedef std::future<UpdateCodeRepositoryOutcome> UpdateCodeRepositoryOutcomeCallable;
typedef std::future<UpdateDomainOutcome> UpdateDomainOutcomeCallable;
typedef std::future<UpdateEndpointOutcome> UpdateEndpointOutcomeCallable;
typedef std::future<UpdateEndpointWeightsAndCapacitiesOutcome> UpdateEndpointWeightsAndCapacitiesOutcomeCallable;
typedef std::future<UpdateExperimentOutcome> UpdateExperimentOutcomeCallable;
typedef std::future<UpdateMonitoringScheduleOutcome> UpdateMonitoringScheduleOutcomeCallable;
typedef std::future<UpdateNotebookInstanceOutcome> UpdateNotebookInstanceOutcomeCallable;
typedef std::future<UpdateNotebookInstanceLifecycleConfigOutcome> UpdateNotebookInstanceLifecycleConfigOutcomeCallable;
typedef std::future<UpdateTrialOutcome> UpdateTrialOutcomeCallable;
typedef std::future<UpdateTrialComponentOutcome> UpdateTrialComponentOutcomeCallable;
typedef std::future<UpdateUserProfileOutcome> UpdateUserProfileOutcomeCallable;
typedef std::future<UpdateWorkforceOutcome> UpdateWorkforceOutcomeCallable;
typedef std::future<UpdateWorkteamOutcome> UpdateWorkteamOutcomeCallable;
} // namespace Model
class SageMakerClient;
typedef std::function<void(const SageMakerClient*, const Model::AddTagsRequest&, const Model::AddTagsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > AddTagsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::AssociateTrialComponentRequest&, const Model::AssociateTrialComponentOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > AssociateTrialComponentResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateAlgorithmRequest&, const Model::CreateAlgorithmOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateAlgorithmResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateAppRequest&, const Model::CreateAppOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateAppResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateAutoMLJobRequest&, const Model::CreateAutoMLJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateAutoMLJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateCodeRepositoryRequest&, const Model::CreateCodeRepositoryOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateCodeRepositoryResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateCompilationJobRequest&, const Model::CreateCompilationJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateCompilationJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateDomainRequest&, const Model::CreateDomainOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateDomainResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateEndpointRequest&, const Model::CreateEndpointOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateEndpointResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateEndpointConfigRequest&, const Model::CreateEndpointConfigOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateEndpointConfigResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateExperimentRequest&, const Model::CreateExperimentOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateExperimentResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateFlowDefinitionRequest&, const Model::CreateFlowDefinitionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateFlowDefinitionResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateHumanTaskUiRequest&, const Model::CreateHumanTaskUiOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateHumanTaskUiResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateHyperParameterTuningJobRequest&, const Model::CreateHyperParameterTuningJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateHyperParameterTuningJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateLabelingJobRequest&, const Model::CreateLabelingJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateLabelingJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateModelRequest&, const Model::CreateModelOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateModelResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateModelPackageRequest&, const Model::CreateModelPackageOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateModelPackageResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateMonitoringScheduleRequest&, const Model::CreateMonitoringScheduleOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateMonitoringScheduleResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateNotebookInstanceRequest&, const Model::CreateNotebookInstanceOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateNotebookInstanceResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateNotebookInstanceLifecycleConfigRequest&, const Model::CreateNotebookInstanceLifecycleConfigOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateNotebookInstanceLifecycleConfigResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreatePresignedDomainUrlRequest&, const Model::CreatePresignedDomainUrlOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreatePresignedDomainUrlResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreatePresignedNotebookInstanceUrlRequest&, const Model::CreatePresignedNotebookInstanceUrlOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreatePresignedNotebookInstanceUrlResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateProcessingJobRequest&, const Model::CreateProcessingJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateProcessingJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateTrainingJobRequest&, const Model::CreateTrainingJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateTrainingJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateTransformJobRequest&, const Model::CreateTransformJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateTransformJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateTrialRequest&, const Model::CreateTrialOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateTrialResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateTrialComponentRequest&, const Model::CreateTrialComponentOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateTrialComponentResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateUserProfileRequest&, const Model::CreateUserProfileOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateUserProfileResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateWorkforceRequest&, const Model::CreateWorkforceOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateWorkforceResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::CreateWorkteamRequest&, const Model::CreateWorkteamOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > CreateWorkteamResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteAlgorithmRequest&, const Model::DeleteAlgorithmOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteAlgorithmResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteAppRequest&, const Model::DeleteAppOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteAppResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteCodeRepositoryRequest&, const Model::DeleteCodeRepositoryOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteCodeRepositoryResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteDomainRequest&, const Model::DeleteDomainOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteDomainResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteEndpointRequest&, const Model::DeleteEndpointOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteEndpointResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteEndpointConfigRequest&, const Model::DeleteEndpointConfigOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteEndpointConfigResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteExperimentRequest&, const Model::DeleteExperimentOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteExperimentResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteFlowDefinitionRequest&, const Model::DeleteFlowDefinitionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteFlowDefinitionResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteHumanTaskUiRequest&, const Model::DeleteHumanTaskUiOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteHumanTaskUiResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteModelRequest&, const Model::DeleteModelOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteModelResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteModelPackageRequest&, const Model::DeleteModelPackageOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteModelPackageResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteMonitoringScheduleRequest&, const Model::DeleteMonitoringScheduleOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteMonitoringScheduleResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteNotebookInstanceRequest&, const Model::DeleteNotebookInstanceOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteNotebookInstanceResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteNotebookInstanceLifecycleConfigRequest&, const Model::DeleteNotebookInstanceLifecycleConfigOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteNotebookInstanceLifecycleConfigResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteTagsRequest&, const Model::DeleteTagsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteTagsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteTrialRequest&, const Model::DeleteTrialOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteTrialResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteTrialComponentRequest&, const Model::DeleteTrialComponentOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteTrialComponentResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteUserProfileRequest&, const Model::DeleteUserProfileOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteUserProfileResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteWorkforceRequest&, const Model::DeleteWorkforceOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteWorkforceResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DeleteWorkteamRequest&, const Model::DeleteWorkteamOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DeleteWorkteamResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeAlgorithmRequest&, const Model::DescribeAlgorithmOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeAlgorithmResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeAppRequest&, const Model::DescribeAppOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeAppResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeAutoMLJobRequest&, const Model::DescribeAutoMLJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeAutoMLJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeCodeRepositoryRequest&, const Model::DescribeCodeRepositoryOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeCodeRepositoryResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeCompilationJobRequest&, const Model::DescribeCompilationJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeCompilationJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeDomainRequest&, const Model::DescribeDomainOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeDomainResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeEndpointRequest&, const Model::DescribeEndpointOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeEndpointResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeEndpointConfigRequest&, const Model::DescribeEndpointConfigOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeEndpointConfigResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeExperimentRequest&, const Model::DescribeExperimentOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeExperimentResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeFlowDefinitionRequest&, const Model::DescribeFlowDefinitionOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeFlowDefinitionResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeHumanTaskUiRequest&, const Model::DescribeHumanTaskUiOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeHumanTaskUiResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeHyperParameterTuningJobRequest&, const Model::DescribeHyperParameterTuningJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeHyperParameterTuningJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeLabelingJobRequest&, const Model::DescribeLabelingJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeLabelingJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeModelRequest&, const Model::DescribeModelOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeModelResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeModelPackageRequest&, const Model::DescribeModelPackageOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeModelPackageResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeMonitoringScheduleRequest&, const Model::DescribeMonitoringScheduleOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeMonitoringScheduleResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeNotebookInstanceRequest&, const Model::DescribeNotebookInstanceOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeNotebookInstanceResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeNotebookInstanceLifecycleConfigRequest&, const Model::DescribeNotebookInstanceLifecycleConfigOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeNotebookInstanceLifecycleConfigResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeProcessingJobRequest&, const Model::DescribeProcessingJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeProcessingJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeSubscribedWorkteamRequest&, const Model::DescribeSubscribedWorkteamOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeSubscribedWorkteamResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeTrainingJobRequest&, const Model::DescribeTrainingJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeTrainingJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeTransformJobRequest&, const Model::DescribeTransformJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeTransformJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeTrialRequest&, const Model::DescribeTrialOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeTrialResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeTrialComponentRequest&, const Model::DescribeTrialComponentOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeTrialComponentResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeUserProfileRequest&, const Model::DescribeUserProfileOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeUserProfileResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeWorkforceRequest&, const Model::DescribeWorkforceOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeWorkforceResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DescribeWorkteamRequest&, const Model::DescribeWorkteamOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DescribeWorkteamResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::DisassociateTrialComponentRequest&, const Model::DisassociateTrialComponentOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > DisassociateTrialComponentResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::GetSearchSuggestionsRequest&, const Model::GetSearchSuggestionsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > GetSearchSuggestionsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListAlgorithmsRequest&, const Model::ListAlgorithmsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListAlgorithmsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListAppsRequest&, const Model::ListAppsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListAppsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListAutoMLJobsRequest&, const Model::ListAutoMLJobsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListAutoMLJobsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListCandidatesForAutoMLJobRequest&, const Model::ListCandidatesForAutoMLJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListCandidatesForAutoMLJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListCodeRepositoriesRequest&, const Model::ListCodeRepositoriesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListCodeRepositoriesResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListCompilationJobsRequest&, const Model::ListCompilationJobsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListCompilationJobsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListDomainsRequest&, const Model::ListDomainsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListDomainsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListEndpointConfigsRequest&, const Model::ListEndpointConfigsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListEndpointConfigsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListEndpointsRequest&, const Model::ListEndpointsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListEndpointsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListExperimentsRequest&, const Model::ListExperimentsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListExperimentsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListFlowDefinitionsRequest&, const Model::ListFlowDefinitionsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListFlowDefinitionsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListHumanTaskUisRequest&, const Model::ListHumanTaskUisOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListHumanTaskUisResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListHyperParameterTuningJobsRequest&, const Model::ListHyperParameterTuningJobsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListHyperParameterTuningJobsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListLabelingJobsRequest&, const Model::ListLabelingJobsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListLabelingJobsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListLabelingJobsForWorkteamRequest&, const Model::ListLabelingJobsForWorkteamOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListLabelingJobsForWorkteamResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListModelPackagesRequest&, const Model::ListModelPackagesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListModelPackagesResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListModelsRequest&, const Model::ListModelsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListModelsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListMonitoringExecutionsRequest&, const Model::ListMonitoringExecutionsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListMonitoringExecutionsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListMonitoringSchedulesRequest&, const Model::ListMonitoringSchedulesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListMonitoringSchedulesResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListNotebookInstanceLifecycleConfigsRequest&, const Model::ListNotebookInstanceLifecycleConfigsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListNotebookInstanceLifecycleConfigsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListNotebookInstancesRequest&, const Model::ListNotebookInstancesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListNotebookInstancesResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListProcessingJobsRequest&, const Model::ListProcessingJobsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListProcessingJobsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListSubscribedWorkteamsRequest&, const Model::ListSubscribedWorkteamsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListSubscribedWorkteamsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListTagsRequest&, const Model::ListTagsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListTagsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListTrainingJobsRequest&, const Model::ListTrainingJobsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListTrainingJobsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListTrainingJobsForHyperParameterTuningJobRequest&, const Model::ListTrainingJobsForHyperParameterTuningJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListTrainingJobsForHyperParameterTuningJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListTransformJobsRequest&, const Model::ListTransformJobsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListTransformJobsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListTrialComponentsRequest&, const Model::ListTrialComponentsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListTrialComponentsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListTrialsRequest&, const Model::ListTrialsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListTrialsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListUserProfilesRequest&, const Model::ListUserProfilesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListUserProfilesResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListWorkforcesRequest&, const Model::ListWorkforcesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListWorkforcesResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::ListWorkteamsRequest&, const Model::ListWorkteamsOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > ListWorkteamsResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::RenderUiTemplateRequest&, const Model::RenderUiTemplateOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > RenderUiTemplateResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::SearchRequest&, const Model::SearchOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > SearchResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::StartMonitoringScheduleRequest&, const Model::StartMonitoringScheduleOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartMonitoringScheduleResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::StartNotebookInstanceRequest&, const Model::StartNotebookInstanceOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StartNotebookInstanceResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::StopAutoMLJobRequest&, const Model::StopAutoMLJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StopAutoMLJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::StopCompilationJobRequest&, const Model::StopCompilationJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StopCompilationJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::StopHyperParameterTuningJobRequest&, const Model::StopHyperParameterTuningJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StopHyperParameterTuningJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::StopLabelingJobRequest&, const Model::StopLabelingJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StopLabelingJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::StopMonitoringScheduleRequest&, const Model::StopMonitoringScheduleOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StopMonitoringScheduleResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::StopNotebookInstanceRequest&, const Model::StopNotebookInstanceOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StopNotebookInstanceResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::StopProcessingJobRequest&, const Model::StopProcessingJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StopProcessingJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::StopTrainingJobRequest&, const Model::StopTrainingJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StopTrainingJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::StopTransformJobRequest&, const Model::StopTransformJobOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > StopTransformJobResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::UpdateCodeRepositoryRequest&, const Model::UpdateCodeRepositoryOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > UpdateCodeRepositoryResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::UpdateDomainRequest&, const Model::UpdateDomainOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > UpdateDomainResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::UpdateEndpointRequest&, const Model::UpdateEndpointOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > UpdateEndpointResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::UpdateEndpointWeightsAndCapacitiesRequest&, const Model::UpdateEndpointWeightsAndCapacitiesOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > UpdateEndpointWeightsAndCapacitiesResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::UpdateExperimentRequest&, const Model::UpdateExperimentOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > UpdateExperimentResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::UpdateMonitoringScheduleRequest&, const Model::UpdateMonitoringScheduleOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > UpdateMonitoringScheduleResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::UpdateNotebookInstanceRequest&, const Model::UpdateNotebookInstanceOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > UpdateNotebookInstanceResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::UpdateNotebookInstanceLifecycleConfigRequest&, const Model::UpdateNotebookInstanceLifecycleConfigOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > UpdateNotebookInstanceLifecycleConfigResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::UpdateTrialRequest&, const Model::UpdateTrialOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > UpdateTrialResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::UpdateTrialComponentRequest&, const Model::UpdateTrialComponentOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > UpdateTrialComponentResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::UpdateUserProfileRequest&, const Model::UpdateUserProfileOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > UpdateUserProfileResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::UpdateWorkforceRequest&, const Model::UpdateWorkforceOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > UpdateWorkforceResponseReceivedHandler;
typedef std::function<void(const SageMakerClient*, const Model::UpdateWorkteamRequest&, const Model::UpdateWorkteamOutcome&, const std::shared_ptr<const Aws::Client::AsyncCallerContext>&) > UpdateWorkteamResponseReceivedHandler;
/**
* <p>Provides APIs for creating and managing Amazon SageMaker resources. </p>
* <p>Other Resources:</p> <ul> <li> <p> <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/whatis.html#first-time-user">Amazon
* SageMaker Developer Guide</a> </p> </li> <li> <p> <a
* href="https://docs.aws.amazon.com/augmented-ai/2019-11-07/APIReference/Welcome.html">Amazon
* Augmented AI Runtime API Reference</a> </p> </li> </ul>
*/
class AWS_SAGEMAKER_API SageMakerClient : public Aws::Client::AWSJsonClient
{
public:
typedef Aws::Client::AWSJsonClient BASECLASS;
/**
* 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(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(const Aws::Auth::AWSCredentials& credentials, 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(const std::shared_ptr<Aws::Auth::AWSCredentialsProvider>& credentialsProvider,
const Aws::Client::ClientConfiguration& clientConfiguration = Aws::Client::ClientConfiguration());
virtual ~SageMakerClient();
/**
* <p>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.</p> <p>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 <a
* href="https://aws.amazon.com/answers/account-management/aws-tagging-strategies/">AWS
* Tagging Strategies</a>.</p> <p>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
* <code>Tags</code> parameter of <a>CreateHyperParameterTuningJob</a> </p>
* <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AddTags">AWS
* API Reference</a></p>
*/
virtual Model::AddTagsOutcome AddTags(const Model::AddTagsRequest& request) const;
/**
* <p>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.</p> <p>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 <a
* href="https://aws.amazon.com/answers/account-management/aws-tagging-strategies/">AWS
* Tagging Strategies</a>.</p> <p>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
* <code>Tags</code> parameter of <a>CreateHyperParameterTuningJob</a> </p>
* <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AddTags">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::AddTagsOutcomeCallable AddTagsCallable(const Model::AddTagsRequest& request) const;
/**
* <p>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.</p> <p>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 <a
* href="https://aws.amazon.com/answers/account-management/aws-tagging-strategies/">AWS
* Tagging Strategies</a>.</p> <p>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
* <code>Tags</code> parameter of <a>CreateHyperParameterTuningJob</a> </p>
* <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AddTags">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void AddTagsAsync(const Model::AddTagsRequest& request, const AddTagsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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 <a>DisassociateTrialComponent</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AssociateTrialComponent">AWS
* API Reference</a></p>
*/
virtual Model::AssociateTrialComponentOutcome AssociateTrialComponent(const Model::AssociateTrialComponentRequest& request) const;
/**
* <p>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 <a>DisassociateTrialComponent</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AssociateTrialComponent">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::AssociateTrialComponentOutcomeCallable AssociateTrialComponentCallable(const Model::AssociateTrialComponentRequest& request) const;
/**
* <p>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 <a>DisassociateTrialComponent</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AssociateTrialComponent">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void AssociateTrialComponentAsync(const Model::AssociateTrialComponentRequest& request, const AssociateTrialComponentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Create a machine learning algorithm that you can use in Amazon SageMaker and
* list in the AWS Marketplace.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAlgorithm">AWS
* API Reference</a></p>
*/
virtual Model::CreateAlgorithmOutcome CreateAlgorithm(const Model::CreateAlgorithmRequest& request) const;
/**
* <p>Create a machine learning algorithm that you can use in Amazon SageMaker and
* list in the AWS Marketplace.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAlgorithm">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateAlgorithmOutcomeCallable CreateAlgorithmCallable(const Model::CreateAlgorithmRequest& request) const;
/**
* <p>Create a machine learning algorithm that you can use in Amazon SageMaker and
* list in the AWS Marketplace.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAlgorithm">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateAlgorithmAsync(const Model::CreateAlgorithmRequest& request, const CreateAlgorithmResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateApp">AWS
* API Reference</a></p>
*/
virtual Model::CreateAppOutcome CreateApp(const Model::CreateAppRequest& request) const;
/**
* <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateApp">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateAppOutcomeCallable CreateAppCallable(const Model::CreateAppRequest& request) const;
/**
* <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateApp">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateAppAsync(const Model::CreateAppRequest& request, const CreateAppResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates an Autopilot job.</p> <p>Find the best performing model after you run
* an Autopilot job by calling . Deploy that model by following the steps described
* in <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html">Step
* 6.1: Deploy the Model to Amazon SageMaker Hosting Services</a>.</p> <p>For
* information about how to use Autopilot, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html">
* Automate Model Development with Amazon SageMaker Autopilot</a>.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAutoMLJob">AWS
* API Reference</a></p>
*/
virtual Model::CreateAutoMLJobOutcome CreateAutoMLJob(const Model::CreateAutoMLJobRequest& request) const;
/**
* <p>Creates an Autopilot job.</p> <p>Find the best performing model after you run
* an Autopilot job by calling . Deploy that model by following the steps described
* in <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html">Step
* 6.1: Deploy the Model to Amazon SageMaker Hosting Services</a>.</p> <p>For
* information about how to use Autopilot, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html">
* Automate Model Development with Amazon SageMaker Autopilot</a>.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAutoMLJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateAutoMLJobOutcomeCallable CreateAutoMLJobCallable(const Model::CreateAutoMLJobRequest& request) const;
/**
* <p>Creates an Autopilot job.</p> <p>Find the best performing model after you run
* an Autopilot job by calling . Deploy that model by following the steps described
* in <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html">Step
* 6.1: Deploy the Model to Amazon SageMaker Hosting Services</a>.</p> <p>For
* information about how to use Autopilot, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html">
* Automate Model Development with Amazon SageMaker Autopilot</a>.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAutoMLJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateAutoMLJobAsync(const Model::CreateAutoMLJobRequest& request, const CreateAutoMLJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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.</p> <p>The repository can be hosted
* either in <a
* href="https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html">AWS
* CodeCommit</a> or in any other Git repository.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateCodeRepository">AWS
* API Reference</a></p>
*/
virtual Model::CreateCodeRepositoryOutcome CreateCodeRepository(const Model::CreateCodeRepositoryRequest& request) const;
/**
* <p>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.</p> <p>The repository can be hosted
* either in <a
* href="https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html">AWS
* CodeCommit</a> or in any other Git repository.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateCodeRepository">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateCodeRepositoryOutcomeCallable CreateCodeRepositoryCallable(const Model::CreateCodeRepositoryRequest& request) const;
/**
* <p>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.</p> <p>The repository can be hosted
* either in <a
* href="https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html">AWS
* CodeCommit</a> or in any other Git repository.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateCodeRepository">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateCodeRepositoryAsync(const Model::CreateCodeRepositoryRequest& request, const CreateCodeRepositoryResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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. </p> <p>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.</p> <p>In the request
* body, you provide the following:</p> <ul> <li> <p>A name for the compilation
* job</p> </li> <li> <p> Information about the input model artifacts </p> </li>
* <li> <p>The output location for the compiled model and the device (target) that
* the model runs on </p> </li> <li> <p>The Amazon Resource Name (ARN) of the IAM
* role that Amazon SageMaker assumes to perform the model compilation job. </p>
* </li> </ul> <p>You can also provide a <code>Tag</code> to track the model
* compilation job's resource use and costs. The response body contains the
* <code>CompilationJobArn</code> for the compiled job.</p> <p>To stop a model
* compilation job, use <a>StopCompilationJob</a>. To get information about a
* particular model compilation job, use <a>DescribeCompilationJob</a>. To get
* information about multiple model compilation jobs, use
* <a>ListCompilationJobs</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateCompilationJob">AWS
* API Reference</a></p>
*/
virtual Model::CreateCompilationJobOutcome CreateCompilationJob(const Model::CreateCompilationJobRequest& request) const;
/**
* <p>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. </p> <p>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.</p> <p>In the request
* body, you provide the following:</p> <ul> <li> <p>A name for the compilation
* job</p> </li> <li> <p> Information about the input model artifacts </p> </li>
* <li> <p>The output location for the compiled model and the device (target) that
* the model runs on </p> </li> <li> <p>The Amazon Resource Name (ARN) of the IAM
* role that Amazon SageMaker assumes to perform the model compilation job. </p>
* </li> </ul> <p>You can also provide a <code>Tag</code> to track the model
* compilation job's resource use and costs. The response body contains the
* <code>CompilationJobArn</code> for the compiled job.</p> <p>To stop a model
* compilation job, use <a>StopCompilationJob</a>. To get information about a
* particular model compilation job, use <a>DescribeCompilationJob</a>. To get
* information about multiple model compilation jobs, use
* <a>ListCompilationJobs</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateCompilationJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateCompilationJobOutcomeCallable CreateCompilationJobCallable(const Model::CreateCompilationJobRequest& request) const;
/**
* <p>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. </p> <p>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.</p> <p>In the request
* body, you provide the following:</p> <ul> <li> <p>A name for the compilation
* job</p> </li> <li> <p> Information about the input model artifacts </p> </li>
* <li> <p>The output location for the compiled model and the device (target) that
* the model runs on </p> </li> <li> <p>The Amazon Resource Name (ARN) of the IAM
* role that Amazon SageMaker assumes to perform the model compilation job. </p>
* </li> </ul> <p>You can also provide a <code>Tag</code> to track the model
* compilation job's resource use and costs. The response body contains the
* <code>CompilationJobArn</code> for the compiled job.</p> <p>To stop a model
* compilation job, use <a>StopCompilationJob</a>. To get information about a
* particular model compilation job, use <a>DescribeCompilationJob</a>. To get
* information about multiple model compilation jobs, use
* <a>ListCompilationJobs</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateCompilationJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateCompilationJobAsync(const Model::CreateCompilationJobRequest& request, const CreateCompilationJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates a <code>Domain</code> used by SageMaker Studio. A domain consists of
* an associated directory, 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.</p> <p>When a domain is
* created, an Amazon Elastic File System (EFS) volume is also created for use by
* all of the users within the domain. Each user receives a private home directory
* within the EFS for notebooks, Git repositories, and data files.</p> <p>All
* traffic between the domain and the EFS volume is communicated through the
* specified subnet IDs. All other traffic goes over the Internet through an Amazon
* SageMaker system VPC. The EFS traffic uses the NFS/TCP protocol over port
* 2049.</p> <p>NFS traffic over TCP on port 2049 needs to be allowed
* in both inbound and outbound rules in order to launch a SageMaker Studio app
* successfully.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateDomain">AWS
* API Reference</a></p>
*/
virtual Model::CreateDomainOutcome CreateDomain(const Model::CreateDomainRequest& request) const;
/**
* <p>Creates a <code>Domain</code> used by SageMaker Studio. A domain consists of
* an associated directory, 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.</p> <p>When a domain is
* created, an Amazon Elastic File System (EFS) volume is also created for use by
* all of the users within the domain. Each user receives a private home directory
* within the EFS for notebooks, Git repositories, and data files.</p> <p>All
* traffic between the domain and the EFS volume is communicated through the
* specified subnet IDs. All other traffic goes over the Internet through an Amazon
* SageMaker system VPC. The EFS traffic uses the NFS/TCP protocol over port
* 2049.</p> <p>NFS traffic over TCP on port 2049 needs to be allowed
* in both inbound and outbound rules in order to launch a SageMaker Studio app
* successfully.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateDomain">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateDomainOutcomeCallable CreateDomainCallable(const Model::CreateDomainRequest& request) const;
/**
* <p>Creates a <code>Domain</code> used by SageMaker Studio. A domain consists of
* an associated directory, 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.</p> <p>When a domain is
* created, an Amazon Elastic File System (EFS) volume is also created for use by
* all of the users within the domain. Each user receives a private home directory
* within the EFS for notebooks, Git repositories, and data files.</p> <p>All
* traffic between the domain and the EFS volume is communicated through the
* specified subnet IDs. All other traffic goes over the Internet through an Amazon
* SageMaker system VPC. The EFS traffic uses the NFS/TCP protocol over port
* 2049.</p> <p>NFS traffic over TCP on port 2049 needs to be allowed
* in both inbound and outbound rules in order to launch a SageMaker Studio app
* successfully.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateDomain">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateDomainAsync(const Model::CreateDomainRequest& request, const CreateDomainResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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
* <a>CreateEndpointConfig</a> API. </p> <p> Use this API to deploy models using
* Amazon SageMaker hosting services. </p> <p>For an example that calls this method
* when deploying a model to Amazon SageMaker hosting services, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto">Deploy
* the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto
* 3)).</a> </p> <p> You must not delete an <code>EndpointConfig</code> that
* is in use by an endpoint that is live or while the <code>UpdateEndpoint</code>
* or <code>CreateEndpoint</code> operations are being performed on the endpoint.
* To update an endpoint, you must create a new <code>EndpointConfig</code>.</p>
* <p>The endpoint name must be unique within an AWS Region in your AWS
* account. </p> <p>When it receives the request, Amazon SageMaker creates the
* endpoint, launches the resources (ML compute instances), and deploys the
* model(s) on them. </p> <p>When you call <a>CreateEndpoint</a>, a load
* call is made to DynamoDB to verify that your endpoint configuration exists. When
* you read data from a DynamoDB table supporting <a
* href="https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadConsistency.html">
* <code>Eventually Consistent Reads</code> </a>, 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
* <a>DescribeEndpointConfig</a> before calling <a>CreateEndpoint</a> to minimize
* the potential impact of a DynamoDB eventually consistent read.</p>
* <p>When Amazon SageMaker receives the request, it sets the endpoint status to
* <code>Creating</code>. After it creates the endpoint, it sets the status to
* <code>InService</code>. Amazon SageMaker can then process incoming requests for
* inferences. To check the status of an endpoint, use the <a>DescribeEndpoint</a>
* API.</p> <p>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 <a
* href="https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html">Activating
* and Deactivating AWS STS in an AWS Region</a> in the <i>AWS Identity and Access
* Management User Guide</i>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEndpoint">AWS
* API Reference</a></p>
*/
virtual Model::CreateEndpointOutcome CreateEndpoint(const Model::CreateEndpointRequest& request) const;
/**
* <p>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
* <a>CreateEndpointConfig</a> API. </p> <p> Use this API to deploy models using
* Amazon SageMaker hosting services. </p> <p>For an example that calls this method
* when deploying a model to Amazon SageMaker hosting services, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto">Deploy
* the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto
* 3)).</a> </p> <p> You must not delete an <code>EndpointConfig</code> that
* is in use by an endpoint that is live or while the <code>UpdateEndpoint</code>
* or <code>CreateEndpoint</code> operations are being performed on the endpoint.
* To update an endpoint, you must create a new <code>EndpointConfig</code>.</p>
* <p>The endpoint name must be unique within an AWS Region in your AWS
* account. </p> <p>When it receives the request, Amazon SageMaker creates the
* endpoint, launches the resources (ML compute instances), and deploys the
* model(s) on them. </p> <p>When you call <a>CreateEndpoint</a>, a load
* call is made to DynamoDB to verify that your endpoint configuration exists. When
* you read data from a DynamoDB table supporting <a
* href="https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadConsistency.html">
* <code>Eventually Consistent Reads</code> </a>, 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
* <a>DescribeEndpointConfig</a> before calling <a>CreateEndpoint</a> to minimize
* the potential impact of a DynamoDB eventually consistent read.</p>
* <p>When Amazon SageMaker receives the request, it sets the endpoint status to
* <code>Creating</code>. After it creates the endpoint, it sets the status to
* <code>InService</code>. Amazon SageMaker can then process incoming requests for
* inferences. To check the status of an endpoint, use the <a>DescribeEndpoint</a>
* API.</p> <p>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 <a
* href="https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html">Activating
* and Deactivating AWS STS in an AWS Region</a> in the <i>AWS Identity and Access
* Management User Guide</i>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEndpoint">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateEndpointOutcomeCallable CreateEndpointCallable(const Model::CreateEndpointRequest& request) const;
/**
* <p>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
* <a>CreateEndpointConfig</a> API. </p> <p> Use this API to deploy models using
* Amazon SageMaker hosting services. </p> <p>For an example that calls this method
* when deploying a model to Amazon SageMaker hosting services, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto">Deploy
* the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto
* 3)).</a> </p> <p> You must not delete an <code>EndpointConfig</code> that
* is in use by an endpoint that is live or while the <code>UpdateEndpoint</code>
* or <code>CreateEndpoint</code> operations are being performed on the endpoint.
* To update an endpoint, you must create a new <code>EndpointConfig</code>.</p>
* <p>The endpoint name must be unique within an AWS Region in your AWS
* account. </p> <p>When it receives the request, Amazon SageMaker creates the
* endpoint, launches the resources (ML compute instances), and deploys the
* model(s) on them. </p> <p>When you call <a>CreateEndpoint</a>, a load
* call is made to DynamoDB to verify that your endpoint configuration exists. When
* you read data from a DynamoDB table supporting <a
* href="https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadConsistency.html">
* <code>Eventually Consistent Reads</code> </a>, 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
* <a>DescribeEndpointConfig</a> before calling <a>CreateEndpoint</a> to minimize
* the potential impact of a DynamoDB eventually consistent read.</p>
* <p>When Amazon SageMaker receives the request, it sets the endpoint status to
* <code>Creating</code>. After it creates the endpoint, it sets the status to
* <code>InService</code>. Amazon SageMaker can then process incoming requests for
* inferences. To check the status of an endpoint, use the <a>DescribeEndpoint</a>
* API.</p> <p>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 <a
* href="https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html">Activating
* and Deactivating AWS STS in an AWS Region</a> in the <i>AWS Identity and Access
* Management User Guide</i>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEndpoint">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateEndpointAsync(const Model::CreateEndpointRequest& request, const CreateEndpointResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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 <code>CreateModel</code> API, to deploy and the resources that you
* want Amazon SageMaker to provision. Then you call the <a>CreateEndpoint</a>
* API.</p> <p> Use this API if you want to use Amazon SageMaker hosting
* services to deploy models into production. </p> <p>In the request, you
* define a <code>ProductionVariant</code>, for each model that you want to deploy.
* Each <code>ProductionVariant</code> parameter also describes the resources that
* you want Amazon SageMaker to provision. This includes the number and type of ML
* compute instances to deploy. </p> <p>If you are hosting multiple models, you
* also assign a <code>VariantWeight</code> 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. </p> <p>For an example that calls this method when deploying a model to
* Amazon SageMaker hosting services, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto">Deploy
* the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto
* 3)).</a> </p> <p>When you call <a>CreateEndpoint</a>, a load call is made
* to DynamoDB to verify that your endpoint configuration exists. When you read
* data from a DynamoDB table supporting <a
* href="https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadConsistency.html">
* <code>Eventually Consistent Reads</code> </a>, 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
* <a>DescribeEndpointConfig</a> before calling <a>CreateEndpoint</a> to minimize
* the potential impact of a DynamoDB eventually consistent read.</p>
* <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEndpointConfig">AWS
* API Reference</a></p>
*/
virtual Model::CreateEndpointConfigOutcome CreateEndpointConfig(const Model::CreateEndpointConfigRequest& request) const;
/**
* <p>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 <code>CreateModel</code> API, to deploy and the resources that you
* want Amazon SageMaker to provision. Then you call the <a>CreateEndpoint</a>
* API.</p> <p> Use this API if you want to use Amazon SageMaker hosting
* services to deploy models into production. </p> <p>In the request, you
* define a <code>ProductionVariant</code>, for each model that you want to deploy.
* Each <code>ProductionVariant</code> parameter also describes the resources that
* you want Amazon SageMaker to provision. This includes the number and type of ML
* compute instances to deploy. </p> <p>If you are hosting multiple models, you
* also assign a <code>VariantWeight</code> 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. </p> <p>For an example that calls this method when deploying a model to
* Amazon SageMaker hosting services, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto">Deploy
* the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto
* 3)).</a> </p> <p>When you call <a>CreateEndpoint</a>, a load call is made
* to DynamoDB to verify that your endpoint configuration exists. When you read
* data from a DynamoDB table supporting <a
* href="https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadConsistency.html">
* <code>Eventually Consistent Reads</code> </a>, 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
* <a>DescribeEndpointConfig</a> before calling <a>CreateEndpoint</a> to minimize
* the potential impact of a DynamoDB eventually consistent read.</p>
* <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEndpointConfig">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateEndpointConfigOutcomeCallable CreateEndpointConfigCallable(const Model::CreateEndpointConfigRequest& request) const;
/**
* <p>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 <code>CreateModel</code> API, to deploy and the resources that you
* want Amazon SageMaker to provision. Then you call the <a>CreateEndpoint</a>
* API.</p> <p> Use this API if you want to use Amazon SageMaker hosting
* services to deploy models into production. </p> <p>In the request, you
* define a <code>ProductionVariant</code>, for each model that you want to deploy.
* Each <code>ProductionVariant</code> parameter also describes the resources that
* you want Amazon SageMaker to provision. This includes the number and type of ML
* compute instances to deploy. </p> <p>If you are hosting multiple models, you
* also assign a <code>VariantWeight</code> 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. </p> <p>For an example that calls this method when deploying a model to
* Amazon SageMaker hosting services, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto">Deploy
* the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto
* 3)).</a> </p> <p>When you call <a>CreateEndpoint</a>, a load call is made
* to DynamoDB to verify that your endpoint configuration exists. When you read
* data from a DynamoDB table supporting <a
* href="https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadConsistency.html">
* <code>Eventually Consistent Reads</code> </a>, 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
* <a>DescribeEndpointConfig</a> before calling <a>CreateEndpoint</a> to minimize
* the potential impact of a DynamoDB eventually consistent read.</p>
* <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEndpointConfig">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateEndpointConfigAsync(const Model::CreateEndpointConfigRequest& request, const CreateEndpointConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates an SageMaker <i>experiment</i>. An experiment is a collection of
* <i>trials</i> that are observed, compared and evaluated as a group. A trial is a
* set of steps, called <i>trial components</i>, that produce a machine learning
* model.</p> <p>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.</p> <p>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.</p> <p>You can add
* tags to experiments, trials, trial components and then use the <a>Search</a> API
* to search for the tags.</p> <p>To add a description to an experiment, specify
* the optional <code>Description</code> parameter. To add a description later, or
* to change the description, call the <a>UpdateExperiment</a> API.</p> <p>To get a
* list of all your experiments, call the <a>ListExperiments</a> API. To view an
* experiment's properties, call the <a>DescribeExperiment</a> API. To get a list
* of all the trials associated with an experiment, call the <a>ListTrials</a> API.
* To create a trial call the <a>CreateTrial</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateExperiment">AWS
* API Reference</a></p>
*/
virtual Model::CreateExperimentOutcome CreateExperiment(const Model::CreateExperimentRequest& request) const;
/**
* <p>Creates an SageMaker <i>experiment</i>. An experiment is a collection of
* <i>trials</i> that are observed, compared and evaluated as a group. A trial is a
* set of steps, called <i>trial components</i>, that produce a machine learning
* model.</p> <p>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.</p> <p>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.</p> <p>You can add
* tags to experiments, trials, trial components and then use the <a>Search</a> API
* to search for the tags.</p> <p>To add a description to an experiment, specify
* the optional <code>Description</code> parameter. To add a description later, or
* to change the description, call the <a>UpdateExperiment</a> API.</p> <p>To get a
* list of all your experiments, call the <a>ListExperiments</a> API. To view an
* experiment's properties, call the <a>DescribeExperiment</a> API. To get a list
* of all the trials associated with an experiment, call the <a>ListTrials</a> API.
* To create a trial call the <a>CreateTrial</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateExperiment">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateExperimentOutcomeCallable CreateExperimentCallable(const Model::CreateExperimentRequest& request) const;
/**
* <p>Creates an SageMaker <i>experiment</i>. An experiment is a collection of
* <i>trials</i> that are observed, compared and evaluated as a group. A trial is a
* set of steps, called <i>trial components</i>, that produce a machine learning
* model.</p> <p>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.</p> <p>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.</p> <p>You can add
* tags to experiments, trials, trial components and then use the <a>Search</a> API
* to search for the tags.</p> <p>To add a description to an experiment, specify
* the optional <code>Description</code> parameter. To add a description later, or
* to change the description, call the <a>UpdateExperiment</a> API.</p> <p>To get a
* list of all your experiments, call the <a>ListExperiments</a> API. To view an
* experiment's properties, call the <a>DescribeExperiment</a> API. To get a list
* of all the trials associated with an experiment, call the <a>ListTrials</a> API.
* To create a trial call the <a>CreateTrial</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateExperiment">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateExperimentAsync(const Model::CreateExperimentRequest& request, const CreateExperimentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates a flow definition.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateFlowDefinition">AWS
* API Reference</a></p>
*/
virtual Model::CreateFlowDefinitionOutcome CreateFlowDefinition(const Model::CreateFlowDefinitionRequest& request) const;
/**
* <p>Creates a flow definition.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateFlowDefinition">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateFlowDefinitionOutcomeCallable CreateFlowDefinitionCallable(const Model::CreateFlowDefinitionRequest& request) const;
/**
* <p>Creates a flow definition.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateFlowDefinition">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateFlowDefinitionAsync(const Model::CreateFlowDefinitionRequest& request, const CreateFlowDefinitionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHumanTaskUi">AWS
* API Reference</a></p>
*/
virtual Model::CreateHumanTaskUiOutcome CreateHumanTaskUi(const Model::CreateHumanTaskUiRequest& request) const;
/**
* <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHumanTaskUi">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateHumanTaskUiOutcomeCallable CreateHumanTaskUiCallable(const Model::CreateHumanTaskUiRequest& request) const;
/**
* <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHumanTaskUi">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateHumanTaskUiAsync(const Model::CreateHumanTaskUiRequest& request, const CreateHumanTaskUiResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHyperParameterTuningJob">AWS
* API Reference</a></p>
*/
virtual Model::CreateHyperParameterTuningJobOutcome CreateHyperParameterTuningJob(const Model::CreateHyperParameterTuningJobRequest& request) const;
/**
* <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHyperParameterTuningJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateHyperParameterTuningJobOutcomeCallable CreateHyperParameterTuningJobCallable(const Model::CreateHyperParameterTuningJobRequest& request) const;
/**
* <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHyperParameterTuningJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateHyperParameterTuningJobAsync(const Model::CreateHyperParameterTuningJobRequest& request, const CreateHyperParameterTuningJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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.</p>
* <p>You can select your workforce from one of three providers:</p> <ul> <li> <p>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.</p> </li> <li> <p>One
* or more vendors that you select from the AWS Marketplace. Vendors provide
* expertise in specific areas. </p> </li> <li> <p>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.</p> </li> </ul> <p>You can also use <i>automated data labeling</i>
* to reduce the number of data objects that need to be labeled by a human.
* Automated data labeling uses <i>active learning</i> 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 <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/sms-automated-labeling.html">Using
* Automated Data Labeling</a>.</p> <p>The data objects to be labeled are contained
* in an Amazon S3 bucket. You create a <i>manifest file</i> that describes the
* location of each object. For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/sms-data.html">Using Input
* and Output Data</a>.</p> <p>The output can be used as the manifest file for
* another labeling job or as training data for your machine learning
* models.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateLabelingJob">AWS
* API Reference</a></p>
*/
virtual Model::CreateLabelingJobOutcome CreateLabelingJob(const Model::CreateLabelingJobRequest& request) const;
/**
* <p>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.</p>
* <p>You can select your workforce from one of three providers:</p> <ul> <li> <p>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.</p> </li> <li> <p>One
* or more vendors that you select from the AWS Marketplace. Vendors provide
* expertise in specific areas. </p> </li> <li> <p>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.</p> </li> </ul> <p>You can also use <i>automated data labeling</i>
* to reduce the number of data objects that need to be labeled by a human.
* Automated data labeling uses <i>active learning</i> 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 <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/sms-automated-labeling.html">Using
* Automated Data Labeling</a>.</p> <p>The data objects to be labeled are contained
* in an Amazon S3 bucket. You create a <i>manifest file</i> that describes the
* location of each object. For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/sms-data.html">Using Input
* and Output Data</a>.</p> <p>The output can be used as the manifest file for
* another labeling job or as training data for your machine learning
* models.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateLabelingJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateLabelingJobOutcomeCallable CreateLabelingJobCallable(const Model::CreateLabelingJobRequest& request) const;
/**
* <p>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.</p>
* <p>You can select your workforce from one of three providers:</p> <ul> <li> <p>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.</p> </li> <li> <p>One
* or more vendors that you select from the AWS Marketplace. Vendors provide
* expertise in specific areas. </p> </li> <li> <p>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.</p> </li> </ul> <p>You can also use <i>automated data labeling</i>
* to reduce the number of data objects that need to be labeled by a human.
* Automated data labeling uses <i>active learning</i> 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 <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/sms-automated-labeling.html">Using
* Automated Data Labeling</a>.</p> <p>The data objects to be labeled are contained
* in an Amazon S3 bucket. You create a <i>manifest file</i> that describes the
* location of each object. For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/sms-data.html">Using Input
* and Output Data</a>.</p> <p>The output can be used as the manifest file for
* another labeling job or as training data for your machine learning
* models.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateLabelingJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateLabelingJobAsync(const Model::CreateLabelingJobRequest& request, const CreateLabelingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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.</p> <p>Use this API to create a model if you want to use Amazon
* SageMaker hosting services or run a batch transform job.</p> <p>To host your
* model, you create an endpoint configuration with the
* <code>CreateEndpointConfig</code> API, and then create an endpoint with the
* <code>CreateEndpoint</code> API. Amazon SageMaker then deploys all of the
* containers that you defined for the model in the hosting environment. </p>
* <p>For an example that calls this method when deploying a model to Amazon
* SageMaker hosting services, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto">Deploy
* the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto
* 3)).</a> </p> <p>To run a batch transform using your model, you start a job with
* the <code>CreateTransformJob</code> API. Amazon SageMaker uses your model and
* your dataset to get inferences which are then saved to a specified S3
* location.</p> <p>In the <code>CreateModel</code> request, you must define a
* container with the <code>PrimaryContainer</code> parameter.</p> <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModel">AWS
* API Reference</a></p>
*/
virtual Model::CreateModelOutcome CreateModel(const Model::CreateModelRequest& request) const;
/**
* <p>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.</p> <p>Use this API to create a model if you want to use Amazon
* SageMaker hosting services or run a batch transform job.</p> <p>To host your
* model, you create an endpoint configuration with the
* <code>CreateEndpointConfig</code> API, and then create an endpoint with the
* <code>CreateEndpoint</code> API. Amazon SageMaker then deploys all of the
* containers that you defined for the model in the hosting environment. </p>
* <p>For an example that calls this method when deploying a model to Amazon
* SageMaker hosting services, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto">Deploy
* the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto
* 3)).</a> </p> <p>To run a batch transform using your model, you start a job with
* the <code>CreateTransformJob</code> API. Amazon SageMaker uses your model and
* your dataset to get inferences which are then saved to a specified S3
* location.</p> <p>In the <code>CreateModel</code> request, you must define a
* container with the <code>PrimaryContainer</code> parameter.</p> <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModel">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateModelOutcomeCallable CreateModelCallable(const Model::CreateModelRequest& request) const;
/**
* <p>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.</p> <p>Use this API to create a model if you want to use Amazon
* SageMaker hosting services or run a batch transform job.</p> <p>To host your
* model, you create an endpoint configuration with the
* <code>CreateEndpointConfig</code> API, and then create an endpoint with the
* <code>CreateEndpoint</code> API. Amazon SageMaker then deploys all of the
* containers that you defined for the model in the hosting environment. </p>
* <p>For an example that calls this method when deploying a model to Amazon
* SageMaker hosting services, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto">Deploy
* the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto
* 3)).</a> </p> <p>To run a batch transform using your model, you start a job with
* the <code>CreateTransformJob</code> API. Amazon SageMaker uses your model and
* your dataset to get inferences which are then saved to a specified S3
* location.</p> <p>In the <code>CreateModel</code> request, you must define a
* container with the <code>PrimaryContainer</code> parameter.</p> <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModel">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateModelAsync(const Model::CreateModelRequest& request, const CreateModelResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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.</p> <p>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
* <code>InferenceSpecification</code>. To create a model from an algorithm
* resource that you created or subscribed to in AWS Marketplace, provide a value
* for <code>SourceAlgorithmSpecification</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelPackage">AWS
* API Reference</a></p>
*/
virtual Model::CreateModelPackageOutcome CreateModelPackage(const Model::CreateModelPackageRequest& request) const;
/**
* <p>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.</p> <p>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
* <code>InferenceSpecification</code>. To create a model from an algorithm
* resource that you created or subscribed to in AWS Marketplace, provide a value
* for <code>SourceAlgorithmSpecification</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelPackage">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateModelPackageOutcomeCallable CreateModelPackageCallable(const Model::CreateModelPackageRequest& request) const;
/**
* <p>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.</p> <p>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
* <code>InferenceSpecification</code>. To create a model from an algorithm
* resource that you created or subscribed to in AWS Marketplace, provide a value
* for <code>SourceAlgorithmSpecification</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelPackage">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateModelPackageAsync(const Model::CreateModelPackageRequest& request, const CreateModelPackageResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to
* monitor the data captured for an Amazon SageMaker Endoint.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateMonitoringSchedule">AWS
* API Reference</a></p>
*/
virtual Model::CreateMonitoringScheduleOutcome CreateMonitoringSchedule(const Model::CreateMonitoringScheduleRequest& request) const;
/**
* <p>Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to
* monitor the data captured for an Amazon SageMaker Endoint.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateMonitoringSchedule">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateMonitoringScheduleOutcomeCallable CreateMonitoringScheduleCallable(const Model::CreateMonitoringScheduleRequest& request) const;
/**
* <p>Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to
* monitor the data captured for an Amazon SageMaker Endoint.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateMonitoringSchedule">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateMonitoringScheduleAsync(const Model::CreateMonitoringScheduleRequest& request, const CreateMonitoringScheduleResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates an Amazon SageMaker notebook instance. A notebook instance is a
* machine learning (ML) compute instance running on a Jupyter notebook. </p> <p>In
* a <code>CreateNotebookInstance</code> 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. </p> <p>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.
* </p> <p>After receiving the request, Amazon SageMaker does the following:</p>
* <ol> <li> <p>Creates a network interface in the Amazon SageMaker VPC.</p> </li>
* <li> <p>(Option) If you specified <code>SubnetId</code>, 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.</p> </li> <li> <p>Launches an EC2
* instance of the type specified in the request in the Amazon SageMaker VPC. If
* you specified <code>SubnetId</code> 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.</p> </li> </ol> <p>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.</p> <p>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. </p> <p>For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works.html">How It
* Works</a>. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateNotebookInstance">AWS
* API Reference</a></p>
*/
virtual Model::CreateNotebookInstanceOutcome CreateNotebookInstance(const Model::CreateNotebookInstanceRequest& request) const;
/**
* <p>Creates an Amazon SageMaker notebook instance. A notebook instance is a
* machine learning (ML) compute instance running on a Jupyter notebook. </p> <p>In
* a <code>CreateNotebookInstance</code> 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. </p> <p>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.
* </p> <p>After receiving the request, Amazon SageMaker does the following:</p>
* <ol> <li> <p>Creates a network interface in the Amazon SageMaker VPC.</p> </li>
* <li> <p>(Option) If you specified <code>SubnetId</code>, 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.</p> </li> <li> <p>Launches an EC2
* instance of the type specified in the request in the Amazon SageMaker VPC. If
* you specified <code>SubnetId</code> 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.</p> </li> </ol> <p>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.</p> <p>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. </p> <p>For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works.html">How It
* Works</a>. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateNotebookInstance">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateNotebookInstanceOutcomeCallable CreateNotebookInstanceCallable(const Model::CreateNotebookInstanceRequest& request) const;
/**
* <p>Creates an Amazon SageMaker notebook instance. A notebook instance is a
* machine learning (ML) compute instance running on a Jupyter notebook. </p> <p>In
* a <code>CreateNotebookInstance</code> 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. </p> <p>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.
* </p> <p>After receiving the request, Amazon SageMaker does the following:</p>
* <ol> <li> <p>Creates a network interface in the Amazon SageMaker VPC.</p> </li>
* <li> <p>(Option) If you specified <code>SubnetId</code>, 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.</p> </li> <li> <p>Launches an EC2
* instance of the type specified in the request in the Amazon SageMaker VPC. If
* you specified <code>SubnetId</code> 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.</p> </li> </ol> <p>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.</p> <p>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. </p> <p>For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works.html">How It
* Works</a>. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateNotebookInstance">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateNotebookInstanceAsync(const Model::CreateNotebookInstanceRequest& request, const CreateNotebookInstanceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates a lifecycle configuration that you can associate with a notebook
* instance. A <i>lifecycle configuration</i> is a collection of shell scripts that
* run when you create or start a notebook instance.</p> <p>Each lifecycle
* configuration script has a limit of 16384 characters.</p> <p>The value of the
* <code>$PATH</code> environment variable that is available to both scripts is
* <code>/sbin:bin:/usr/sbin:/usr/bin</code>.</p> <p>View CloudWatch Logs for
* notebook instance lifecycle configurations in log group
* <code>/aws/sagemaker/NotebookInstances</code> in log stream
* <code>[notebook-instance-name]/[LifecycleConfigHook]</code>.</p> <p>Lifecycle
* configuration scripts cannot run for longer than 5 minutes. If a script runs for
* longer than 5 minutes, it fails and the notebook instance is not created or
* started.</p> <p>For information about notebook instance lifestyle
* configurations, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html">Step
* 2.1: (Optional) Customize a Notebook Instance</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateNotebookInstanceLifecycleConfig">AWS
* API Reference</a></p>
*/
virtual Model::CreateNotebookInstanceLifecycleConfigOutcome CreateNotebookInstanceLifecycleConfig(const Model::CreateNotebookInstanceLifecycleConfigRequest& request) const;
/**
* <p>Creates a lifecycle configuration that you can associate with a notebook
* instance. A <i>lifecycle configuration</i> is a collection of shell scripts that
* run when you create or start a notebook instance.</p> <p>Each lifecycle
* configuration script has a limit of 16384 characters.</p> <p>The value of the
* <code>$PATH</code> environment variable that is available to both scripts is
* <code>/sbin:bin:/usr/sbin:/usr/bin</code>.</p> <p>View CloudWatch Logs for
* notebook instance lifecycle configurations in log group
* <code>/aws/sagemaker/NotebookInstances</code> in log stream
* <code>[notebook-instance-name]/[LifecycleConfigHook]</code>.</p> <p>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.</p> <p>For information about notebook instance lifestyle
* configurations, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html">Step
* 2.1: (Optional) Customize a Notebook Instance</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateNotebookInstanceLifecycleConfig">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateNotebookInstanceLifecycleConfigOutcomeCallable CreateNotebookInstanceLifecycleConfigCallable(const Model::CreateNotebookInstanceLifecycleConfigRequest& request) const;
/**
* <p>Creates a lifecycle configuration that you can associate with a notebook
* instance. A <i>lifecycle configuration</i> is a collection of shell scripts that
* run when you create or start a notebook instance.</p> <p>Each lifecycle
* configuration script has a limit of 16384 characters.</p> <p>The value of the
* <code>$PATH</code> environment variable that is available to both scripts is
* <code>/sbin:bin:/usr/sbin:/usr/bin</code>.</p> <p>View CloudWatch Logs for
* notebook instance lifecycle configurations in log group
* <code>/aws/sagemaker/NotebookInstances</code> in log stream
* <code>[notebook-instance-name]/[LifecycleConfigHook]</code>.</p> <p>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.</p> <p>For information about notebook instance lifestyle
* configurations, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html">Step
* 2.1: (Optional) Customize a Notebook Instance</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateNotebookInstanceLifecycleConfig">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateNotebookInstanceLifecycleConfigAsync(const Model::CreateNotebookInstanceLifecycleConfigRequest& request, const CreateNotebookInstanceLifecycleConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreatePresignedDomainUrl">AWS
* API Reference</a></p>
*/
virtual Model::CreatePresignedDomainUrlOutcome CreatePresignedDomainUrl(const Model::CreatePresignedDomainUrlRequest& request) const;
/**
* <p>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. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreatePresignedDomainUrl">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreatePresignedDomainUrlOutcomeCallable CreatePresignedDomainUrlCallable(const Model::CreatePresignedDomainUrlRequest& request) const;
/**
* <p>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. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreatePresignedDomainUrl">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreatePresignedDomainUrlAsync(const Model::CreatePresignedDomainUrlRequest& request, const CreatePresignedDomainUrlResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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
* <code>Open</code> 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.</p> <p> 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.</p> <p>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
* <code>NotIpAddress</code> condition operator and the <code>aws:SourceIP</code>
* condition context key to specify the list of IP addresses that you want to have
* access to the notebook instance. For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/security_iam_id-based-policy-examples.html#nbi-ip-filter">Limit
* Access to a Notebook Instance by IP Address</a>.</p> <p>The URL that you
* get from a call to <a>CreatePresignedNotebookInstanceUrl</a> 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.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreatePresignedNotebookInstanceUrl">AWS
* API Reference</a></p>
*/
virtual Model::CreatePresignedNotebookInstanceUrlOutcome CreatePresignedNotebookInstanceUrl(const Model::CreatePresignedNotebookInstanceUrlRequest& request) const;
/**
* <p>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
* <code>Open</code> 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.</p> <p> 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.</p> <p>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
* <code>NotIpAddress</code> condition operator and the <code>aws:SourceIP</code>
* condition context key to specify the list of IP addresses that you want to have
* access to the notebook instance. For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/security_iam_id-based-policy-examples.html#nbi-ip-filter">Limit
* Access to a Notebook Instance by IP Address</a>.</p> <p>The URL that you
* get from a call to <a>CreatePresignedNotebookInstanceUrl</a> 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.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreatePresignedNotebookInstanceUrl">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreatePresignedNotebookInstanceUrlOutcomeCallable CreatePresignedNotebookInstanceUrlCallable(const Model::CreatePresignedNotebookInstanceUrlRequest& request) const;
/**
* <p>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
* <code>Open</code> 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.</p> <p> 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.</p> <p>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
* <code>NotIpAddress</code> condition operator and the <code>aws:SourceIP</code>
* condition context key to specify the list of IP addresses that you want to have
* access to the notebook instance. For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/security_iam_id-based-policy-examples.html#nbi-ip-filter">Limit
* Access to a Notebook Instance by IP Address</a>.</p> <p>The URL that you
* get from a call to <a>CreatePresignedNotebookInstanceUrl</a> 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.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreatePresignedNotebookInstanceUrl">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreatePresignedNotebookInstanceUrlAsync(const Model::CreatePresignedNotebookInstanceUrlRequest& request, const CreatePresignedNotebookInstanceUrlResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates a processing job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateProcessingJob">AWS
* API Reference</a></p>
*/
virtual Model::CreateProcessingJobOutcome CreateProcessingJob(const Model::CreateProcessingJobRequest& request) const;
/**
* <p>Creates a processing job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateProcessingJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateProcessingJobOutcomeCallable CreateProcessingJobCallable(const Model::CreateProcessingJobRequest& request) const;
/**
* <p>Creates a processing job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateProcessingJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateProcessingJobAsync(const Model::CreateProcessingJobRequest& request, const CreateProcessingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Starts a model training job. After training completes, Amazon SageMaker saves
* the resulting model artifacts to an Amazon S3 location that you specify. </p>
* <p>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. </p> <p>In the request body, you
* provide the following: </p> <ul> <li> <p> <code>AlgorithmSpecification</code> -
* Identifies the training algorithm to use. </p> </li> <li> <p>
* <code>HyperParameters</code> - 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 <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html">Algorithms</a>.
* </p> </li> <li> <p> <code>InputDataConfig</code> - Describes the training
* dataset and the Amazon S3, EFS, or FSx location where it is stored.</p> </li>
* <li> <p> <code>OutputDataConfig</code> - Identifies the Amazon S3 bucket where
* you want Amazon SageMaker to save the results of model training. </p> <p/> </li>
* <li> <p> <code>ResourceConfig</code> - Identifies the resources, ML compute
* instances, and ML storage volumes to deploy for model training. In distributed
* training, you specify more than one instance. </p> </li> <li> <p>
* <code>EnableManagedSpotTraining</code> - Optimize the cost of training machine
* learning models by up to 80% by using Amazon EC2 Spot instances. For more
* information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.html">Managed
* Spot Training</a>. </p> </li> <li> <p> <code>RoleARN</code> - 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. </p> </li>
* <li> <p> <code>StoppingCondition</code> - To help cap training costs, use
* <code>MaxRuntimeInSeconds</code> to set a time limit for training. Use
* <code>MaxWaitTimeInSeconds</code> to specify how long you are willing to wait
* for a managed spot training job to complete. </p> </li> </ul> <p> For more
* information about Amazon SageMaker, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works.html">How It
* Works</a>. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrainingJob">AWS
* API Reference</a></p>
*/
virtual Model::CreateTrainingJobOutcome CreateTrainingJob(const Model::CreateTrainingJobRequest& request) const;
/**
* <p>Starts a model training job. After training completes, Amazon SageMaker saves
* the resulting model artifacts to an Amazon S3 location that you specify. </p>
* <p>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. </p> <p>In the request body, you
* provide the following: </p> <ul> <li> <p> <code>AlgorithmSpecification</code> -
* Identifies the training algorithm to use. </p> </li> <li> <p>
* <code>HyperParameters</code> - 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 <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html">Algorithms</a>.
* </p> </li> <li> <p> <code>InputDataConfig</code> - Describes the training
* dataset and the Amazon S3, EFS, or FSx location where it is stored.</p> </li>
* <li> <p> <code>OutputDataConfig</code> - Identifies the Amazon S3 bucket where
* you want Amazon SageMaker to save the results of model training. </p> <p/> </li>
* <li> <p> <code>ResourceConfig</code> - Identifies the resources, ML compute
* instances, and ML storage volumes to deploy for model training. In distributed
* training, you specify more than one instance. </p> </li> <li> <p>
* <code>EnableManagedSpotTraining</code> - Optimize the cost of training machine
* learning models by up to 80% by using Amazon EC2 Spot instances. For more
* information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.html">Managed
* Spot Training</a>. </p> </li> <li> <p> <code>RoleARN</code> - 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. </p> </li>
* <li> <p> <code>StoppingCondition</code> - To help cap training costs, use
* <code>MaxRuntimeInSeconds</code> to set a time limit for training. Use
* <code>MaxWaitTimeInSeconds</code> to specify how long you are willing to wait
* for a managed spot training job to complete. </p> </li> </ul> <p> For more
* information about Amazon SageMaker, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works.html">How It
* Works</a>. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrainingJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateTrainingJobOutcomeCallable CreateTrainingJobCallable(const Model::CreateTrainingJobRequest& request) const;
/**
* <p>Starts a model training job. After training completes, Amazon SageMaker saves
* the resulting model artifacts to an Amazon S3 location that you specify. </p>
* <p>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. </p> <p>In the request body, you
* provide the following: </p> <ul> <li> <p> <code>AlgorithmSpecification</code> -
* Identifies the training algorithm to use. </p> </li> <li> <p>
* <code>HyperParameters</code> - 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 <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html">Algorithms</a>.
* </p> </li> <li> <p> <code>InputDataConfig</code> - Describes the training
* dataset and the Amazon S3, EFS, or FSx location where it is stored.</p> </li>
* <li> <p> <code>OutputDataConfig</code> - Identifies the Amazon S3 bucket where
* you want Amazon SageMaker to save the results of model training. </p> <p/> </li>
* <li> <p> <code>ResourceConfig</code> - Identifies the resources, ML compute
* instances, and ML storage volumes to deploy for model training. In distributed
* training, you specify more than one instance. </p> </li> <li> <p>
* <code>EnableManagedSpotTraining</code> - Optimize the cost of training machine
* learning models by up to 80% by using Amazon EC2 Spot instances. For more
* information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.html">Managed
* Spot Training</a>. </p> </li> <li> <p> <code>RoleARN</code> - 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. </p> </li>
* <li> <p> <code>StoppingCondition</code> - To help cap training costs, use
* <code>MaxRuntimeInSeconds</code> to set a time limit for training. Use
* <code>MaxWaitTimeInSeconds</code> to specify how long you are willing to wait
* for a managed spot training job to complete. </p> </li> </ul> <p> For more
* information about Amazon SageMaker, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works.html">How It
* Works</a>. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrainingJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateTrainingJobAsync(const Model::CreateTrainingJobRequest& request, const CreateTrainingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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.</p> <p>To perform batch transformations, you create a transform job
* and use the data that you have readily available.</p> <p>In the request body,
* you provide the following:</p> <ul> <li> <p> <code>TransformJobName</code> -
* Identifies the transform job. The name must be unique within an AWS Region in an
* AWS account.</p> </li> <li> <p> <code>ModelName</code> - Identifies the model to
* use. <code>ModelName</code> 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 <a>CreateModel</a>.</p> </li> <li> <p> <code>TransformInput</code> -
* Describes the dataset to be transformed and the Amazon S3 location where it is
* stored.</p> </li> <li> <p> <code>TransformOutput</code> - Identifies the Amazon
* S3 location where you want Amazon SageMaker to save the results from the
* transform job.</p> </li> <li> <p> <code>TransformResources</code> - Identifies
* the ML compute instances for the transform job.</p> </li> </ul> <p>For more
* information about how batch transformation works, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html">Batch
* Transform</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTransformJob">AWS
* API Reference</a></p>
*/
virtual Model::CreateTransformJobOutcome CreateTransformJob(const Model::CreateTransformJobRequest& request) const;
/**
* <p>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.</p> <p>To perform batch transformations, you create a transform job
* and use the data that you have readily available.</p> <p>In the request body,
* you provide the following:</p> <ul> <li> <p> <code>TransformJobName</code> -
* Identifies the transform job. The name must be unique within an AWS Region in an
* AWS account.</p> </li> <li> <p> <code>ModelName</code> - Identifies the model to
* use. <code>ModelName</code> 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 <a>CreateModel</a>.</p> </li> <li> <p> <code>TransformInput</code> -
* Describes the dataset to be transformed and the Amazon S3 location where it is
* stored.</p> </li> <li> <p> <code>TransformOutput</code> - Identifies the Amazon
* S3 location where you want Amazon SageMaker to save the results from the
* transform job.</p> </li> <li> <p> <code>TransformResources</code> - Identifies
* the ML compute instances for the transform job.</p> </li> </ul> <p>For more
* information about how batch transformation works, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html">Batch
* Transform</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTransformJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateTransformJobOutcomeCallable CreateTransformJobCallable(const Model::CreateTransformJobRequest& request) const;
/**
* <p>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.</p> <p>To perform batch transformations, you create a transform job
* and use the data that you have readily available.</p> <p>In the request body,
* you provide the following:</p> <ul> <li> <p> <code>TransformJobName</code> -
* Identifies the transform job. The name must be unique within an AWS Region in an
* AWS account.</p> </li> <li> <p> <code>ModelName</code> - Identifies the model to
* use. <code>ModelName</code> 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 <a>CreateModel</a>.</p> </li> <li> <p> <code>TransformInput</code> -
* Describes the dataset to be transformed and the Amazon S3 location where it is
* stored.</p> </li> <li> <p> <code>TransformOutput</code> - Identifies the Amazon
* S3 location where you want Amazon SageMaker to save the results from the
* transform job.</p> </li> <li> <p> <code>TransformResources</code> - Identifies
* the ML compute instances for the transform job.</p> </li> </ul> <p>For more
* information about how batch transformation works, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html">Batch
* Transform</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTransformJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateTransformJobAsync(const Model::CreateTransformJobRequest& request, const CreateTransformJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates an Amazon SageMaker <i>trial</i>. A trial is a set of steps called
* <i>trial components</i> that produce a machine learning model. A trial is part
* of a single Amazon SageMaker <i>experiment</i>.</p> <p>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.</p> <p>You can add tags to a trial and then use the <a>Search</a> API to
* search for the tags.</p> <p>To get a list of all your trials, call the
* <a>ListTrials</a> API. To view a trial's properties, call the
* <a>DescribeTrial</a> API. To create a trial component, call the
* <a>CreateTrialComponent</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrial">AWS
* API Reference</a></p>
*/
virtual Model::CreateTrialOutcome CreateTrial(const Model::CreateTrialRequest& request) const;
/**
* <p>Creates an Amazon SageMaker <i>trial</i>. A trial is a set of steps called
* <i>trial components</i> that produce a machine learning model. A trial is part
* of a single Amazon SageMaker <i>experiment</i>.</p> <p>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.</p> <p>You can add tags to a trial and then use the <a>Search</a> API to
* search for the tags.</p> <p>To get a list of all your trials, call the
* <a>ListTrials</a> API. To view a trial's properties, call the
* <a>DescribeTrial</a> API. To create a trial component, call the
* <a>CreateTrialComponent</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrial">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateTrialOutcomeCallable CreateTrialCallable(const Model::CreateTrialRequest& request) const;
/**
* <p>Creates an Amazon SageMaker <i>trial</i>. A trial is a set of steps called
* <i>trial components</i> that produce a machine learning model. A trial is part
* of a single Amazon SageMaker <i>experiment</i>.</p> <p>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.</p> <p>You can add tags to a trial and then use the <a>Search</a> API to
* search for the tags.</p> <p>To get a list of all your trials, call the
* <a>ListTrials</a> API. To view a trial's properties, call the
* <a>DescribeTrial</a> API. To create a trial component, call the
* <a>CreateTrialComponent</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrial">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateTrialAsync(const Model::CreateTrialRequest& request, const CreateTrialResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Creates a <i>trial component</i>, which is a stage of a machine learning
* <i>trial</i>. A trial is composed of one or more trial components. A trial
* component can be used in multiple trials.</p> <p>Trial components include
* pre-processing jobs, training jobs, and batch transform jobs.</p> <p>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.</p> <p>You can add tags to a trial component and then use
* the <a>Search</a> API to search for the tags.</p> <p>
* <code>CreateTrialComponent</code> 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
* <code>CreateTrialComponent</code> from outside one of these environments results
* in an error.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrialComponent">AWS
* API Reference</a></p>
*/
virtual Model::CreateTrialComponentOutcome CreateTrialComponent(const Model::CreateTrialComponentRequest& request) const;
/**
* <p>Creates a <i>trial component</i>, which is a stage of a machine learning
* <i>trial</i>. A trial is composed of one or more trial components. A trial
* component can be used in multiple trials.</p> <p>Trial components include
* pre-processing jobs, training jobs, and batch transform jobs.</p> <p>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.</p> <p>You can add tags to a trial component and then use
* the <a>Search</a> API to search for the tags.</p> <p>
* <code>CreateTrialComponent</code> 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
* <code>CreateTrialComponent</code> from outside one of these environments results
* in an error.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrialComponent">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateTrialComponentOutcomeCallable CreateTrialComponentCallable(const Model::CreateTrialComponentRequest& request) const;
/**
* <p>Creates a <i>trial component</i>, which is a stage of a machine learning
* <i>trial</i>. A trial is composed of one or more trial components. A trial
* component can be used in multiple trials.</p> <p>Trial components include
* pre-processing jobs, training jobs, and batch transform jobs.</p> <p>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.</p> <p>You can add tags to a trial component and then use
* the <a>Search</a> API to search for the tags.</p> <p>
* <code>CreateTrialComponent</code> 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
* <code>CreateTrialComponent</code> from outside one of these environments results
* in an error.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrialComponent">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateTrialComponentAsync(const Model::CreateTrialComponentRequest& request, const CreateTrialComponentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateUserProfile">AWS
* API Reference</a></p>
*/
virtual Model::CreateUserProfileOutcome CreateUserProfile(const Model::CreateUserProfileRequest& request) const;
/**
* <p>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.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateUserProfile">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateUserProfileOutcomeCallable CreateUserProfileCallable(const Model::CreateUserProfileRequest& request) const;
/**
* <p>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.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateUserProfile">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateUserProfileAsync(const Model::CreateUserProfileRequest& request, const CreateUserProfileResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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.</p> <p>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
* <code>CreateWorkforce</code> to create a new workforce.</p> <p>To create a
* private workforce using Amazon Cognito, you must specify a Cognito user pool in
* <code>CognitoConfig</code>. You can also create an Amazon Cognito workforce
* using the Amazon SageMaker console. For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private.html">
* Create a Private Workforce (Amazon Cognito)</a>.</p> <p>To create a private
* workforce using your own OIDC Identity Provider (IdP), specify your IdP
* configuration in <code>OidcConfig</code>. Your OIDC IdP must support
* <i>groups</i> because groups are used by Ground Truth and Amazon A2I to create
* work teams. For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private-oidc.html">
* Create a Private Workforce (OIDC IdP)</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateWorkforce">AWS
* API Reference</a></p>
*/
virtual Model::CreateWorkforceOutcome CreateWorkforce(const Model::CreateWorkforceRequest& request) const;
/**
* <p>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.</p> <p>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
* <code>CreateWorkforce</code> to create a new workforce.</p> <p>To create a
* private workforce using Amazon Cognito, you must specify a Cognito user pool in
* <code>CognitoConfig</code>. You can also create an Amazon Cognito workforce
* using the Amazon SageMaker console. For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private.html">
* Create a Private Workforce (Amazon Cognito)</a>.</p> <p>To create a private
* workforce using your own OIDC Identity Provider (IdP), specify your IdP
* configuration in <code>OidcConfig</code>. Your OIDC IdP must support
* <i>groups</i> because groups are used by Ground Truth and Amazon A2I to create
* work teams. For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private-oidc.html">
* Create a Private Workforce (OIDC IdP)</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateWorkforce">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateWorkforceOutcomeCallable CreateWorkforceCallable(const Model::CreateWorkforceRequest& request) const;
/**
* <p>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.</p> <p>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
* <code>CreateWorkforce</code> to create a new workforce.</p> <p>To create a
* private workforce using Amazon Cognito, you must specify a Cognito user pool in
* <code>CognitoConfig</code>. You can also create an Amazon Cognito workforce
* using the Amazon SageMaker console. For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private.html">
* Create a Private Workforce (Amazon Cognito)</a>.</p> <p>To create a private
* workforce using your own OIDC Identity Provider (IdP), specify your IdP
* configuration in <code>OidcConfig</code>. Your OIDC IdP must support
* <i>groups</i> because groups are used by Ground Truth and Amazon A2I to create
* work teams. For more information, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private-oidc.html">
* Create a Private Workforce (OIDC IdP)</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateWorkforce">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateWorkforceAsync(const Model::CreateWorkforceRequest& request, const CreateWorkforceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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.</p> <p>You cannot create more than 25 work teams in
* an account and region.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateWorkteam">AWS
* API Reference</a></p>
*/
virtual Model::CreateWorkteamOutcome CreateWorkteam(const Model::CreateWorkteamRequest& request) const;
/**
* <p>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.</p> <p>You cannot create more than 25 work teams in
* an account and region.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateWorkteam">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::CreateWorkteamOutcomeCallable CreateWorkteamCallable(const Model::CreateWorkteamRequest& request) const;
/**
* <p>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.</p> <p>You cannot create more than 25 work teams in
* an account and region.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateWorkteam">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void CreateWorkteamAsync(const Model::CreateWorkteamRequest& request, const CreateWorkteamResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Removes the specified algorithm from your account.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteAlgorithm">AWS
* API Reference</a></p>
*/
virtual Model::DeleteAlgorithmOutcome DeleteAlgorithm(const Model::DeleteAlgorithmRequest& request) const;
/**
* <p>Removes the specified algorithm from your account.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteAlgorithm">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteAlgorithmOutcomeCallable DeleteAlgorithmCallable(const Model::DeleteAlgorithmRequest& request) const;
/**
* <p>Removes the specified algorithm from your account.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteAlgorithm">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteAlgorithmAsync(const Model::DeleteAlgorithmRequest& request, const DeleteAlgorithmResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Used to stop and delete an app.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteApp">AWS
* API Reference</a></p>
*/
virtual Model::DeleteAppOutcome DeleteApp(const Model::DeleteAppRequest& request) const;
/**
* <p>Used to stop and delete an app.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteApp">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteAppOutcomeCallable DeleteAppCallable(const Model::DeleteAppRequest& request) const;
/**
* <p>Used to stop and delete an app.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteApp">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteAppAsync(const Model::DeleteAppRequest& request, const DeleteAppResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes the specified Git repository from your account.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteCodeRepository">AWS
* API Reference</a></p>
*/
virtual Model::DeleteCodeRepositoryOutcome DeleteCodeRepository(const Model::DeleteCodeRepositoryRequest& request) const;
/**
* <p>Deletes the specified Git repository from your account.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteCodeRepository">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteCodeRepositoryOutcomeCallable DeleteCodeRepositoryCallable(const Model::DeleteCodeRepositoryRequest& request) const;
/**
* <p>Deletes the specified Git repository from your account.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteCodeRepository">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteCodeRepositoryAsync(const Model::DeleteCodeRepositoryRequest& request, const DeleteCodeRepositoryResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteDomain">AWS
* API Reference</a></p>
*/
virtual Model::DeleteDomainOutcome DeleteDomain(const Model::DeleteDomainRequest& request) const;
/**
* <p>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. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteDomain">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteDomainOutcomeCallable DeleteDomainCallable(const Model::DeleteDomainRequest& request) const;
/**
* <p>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. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteDomain">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteDomainAsync(const Model::DeleteDomainRequest& request, const DeleteDomainResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes an endpoint. Amazon SageMaker frees up all of the resources that were
* deployed when the endpoint was created. </p> <p>Amazon SageMaker retires any
* custom KMS key grants associated with the endpoint, meaning you don't need to
* use the <a
* href="http://docs.aws.amazon.com/kms/latest/APIReference/API_RevokeGrant.html">RevokeGrant</a>
* API call.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteEndpoint">AWS
* API Reference</a></p>
*/
virtual Model::DeleteEndpointOutcome DeleteEndpoint(const Model::DeleteEndpointRequest& request) const;
/**
* <p>Deletes an endpoint. Amazon SageMaker frees up all of the resources that were
* deployed when the endpoint was created. </p> <p>Amazon SageMaker retires any
* custom KMS key grants associated with the endpoint, meaning you don't need to
* use the <a
* href="http://docs.aws.amazon.com/kms/latest/APIReference/API_RevokeGrant.html">RevokeGrant</a>
* API call.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteEndpoint">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteEndpointOutcomeCallable DeleteEndpointCallable(const Model::DeleteEndpointRequest& request) const;
/**
* <p>Deletes an endpoint. Amazon SageMaker frees up all of the resources that were
* deployed when the endpoint was created. </p> <p>Amazon SageMaker retires any
* custom KMS key grants associated with the endpoint, meaning you don't need to
* use the <a
* href="http://docs.aws.amazon.com/kms/latest/APIReference/API_RevokeGrant.html">RevokeGrant</a>
* API call.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteEndpoint">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteEndpointAsync(const Model::DeleteEndpointRequest& request, const DeleteEndpointResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes an endpoint configuration. The <code>DeleteEndpointConfig</code> API
* deletes only the specified configuration. It does not delete endpoints created
* using the configuration. </p> <p>You must not delete an
* <code>EndpointConfig</code> in use by an endpoint that is live or while the
* <code>UpdateEndpoint</code> or <code>CreateEndpoint</code> operations are being
* performed on the endpoint. If you delete the <code>EndpointConfig</code> 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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteEndpointConfig">AWS
* API Reference</a></p>
*/
virtual Model::DeleteEndpointConfigOutcome DeleteEndpointConfig(const Model::DeleteEndpointConfigRequest& request) const;
/**
* <p>Deletes an endpoint configuration. The <code>DeleteEndpointConfig</code> API
* deletes only the specified configuration. It does not delete endpoints created
* using the configuration. </p> <p>You must not delete an
* <code>EndpointConfig</code> in use by an endpoint that is live or while the
* <code>UpdateEndpoint</code> or <code>CreateEndpoint</code> operations are being
* performed on the endpoint. If you delete the <code>EndpointConfig</code> 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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteEndpointConfig">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteEndpointConfigOutcomeCallable DeleteEndpointConfigCallable(const Model::DeleteEndpointConfigRequest& request) const;
/**
* <p>Deletes an endpoint configuration. The <code>DeleteEndpointConfig</code> API
* deletes only the specified configuration. It does not delete endpoints created
* using the configuration. </p> <p>You must not delete an
* <code>EndpointConfig</code> in use by an endpoint that is live or while the
* <code>UpdateEndpoint</code> or <code>CreateEndpoint</code> operations are being
* performed on the endpoint. If you delete the <code>EndpointConfig</code> 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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteEndpointConfig">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteEndpointConfigAsync(const Model::DeleteEndpointConfigRequest& request, const DeleteEndpointConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes an Amazon SageMaker experiment. All trials associated with the
* experiment must be deleted first. Use the <a>ListTrials</a> API to get a list of
* the trials associated with the experiment.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteExperiment">AWS
* API Reference</a></p>
*/
virtual Model::DeleteExperimentOutcome DeleteExperiment(const Model::DeleteExperimentRequest& request) const;
/**
* <p>Deletes an Amazon SageMaker experiment. All trials associated with the
* experiment must be deleted first. Use the <a>ListTrials</a> API to get a list of
* the trials associated with the experiment.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteExperiment">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteExperimentOutcomeCallable DeleteExperimentCallable(const Model::DeleteExperimentRequest& request) const;
/**
* <p>Deletes an Amazon SageMaker experiment. All trials associated with the
* experiment must be deleted first. Use the <a>ListTrials</a> API to get a list of
* the trials associated with the experiment.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteExperiment">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteExperimentAsync(const Model::DeleteExperimentRequest& request, const DeleteExperimentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes the specified flow definition.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteFlowDefinition">AWS
* API Reference</a></p>
*/
virtual Model::DeleteFlowDefinitionOutcome DeleteFlowDefinition(const Model::DeleteFlowDefinitionRequest& request) const;
/**
* <p>Deletes the specified flow definition.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteFlowDefinition">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteFlowDefinitionOutcomeCallable DeleteFlowDefinitionCallable(const Model::DeleteFlowDefinitionRequest& request) const;
/**
* <p>Deletes the specified flow definition.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteFlowDefinition">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteFlowDefinitionAsync(const Model::DeleteFlowDefinitionRequest& request, const DeleteFlowDefinitionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Use this operation to delete a human task user interface (worker task
* template).</p> <p> 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 <code>ListHumanTaskUis</code>.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteHumanTaskUi">AWS
* API Reference</a></p>
*/
virtual Model::DeleteHumanTaskUiOutcome DeleteHumanTaskUi(const Model::DeleteHumanTaskUiRequest& request) const;
/**
* <p>Use this operation to delete a human task user interface (worker task
* template).</p> <p> 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 <code>ListHumanTaskUis</code>.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteHumanTaskUi">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteHumanTaskUiOutcomeCallable DeleteHumanTaskUiCallable(const Model::DeleteHumanTaskUiRequest& request) const;
/**
* <p>Use this operation to delete a human task user interface (worker task
* template).</p> <p> 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 <code>ListHumanTaskUis</code>.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteHumanTaskUi">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteHumanTaskUiAsync(const Model::DeleteHumanTaskUiRequest& request, const DeleteHumanTaskUiResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes a model. The <code>DeleteModel</code> API deletes only the model
* entry that was created in Amazon SageMaker when you called the
* <a>CreateModel</a> API. It does not delete model artifacts, inference code, or
* the IAM role that you specified when creating the model. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModel">AWS
* API Reference</a></p>
*/
virtual Model::DeleteModelOutcome DeleteModel(const Model::DeleteModelRequest& request) const;
/**
* <p>Deletes a model. The <code>DeleteModel</code> API deletes only the model
* entry that was created in Amazon SageMaker when you called the
* <a>CreateModel</a> API. It does not delete model artifacts, inference code, or
* the IAM role that you specified when creating the model. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModel">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteModelOutcomeCallable DeleteModelCallable(const Model::DeleteModelRequest& request) const;
/**
* <p>Deletes a model. The <code>DeleteModel</code> API deletes only the model
* entry that was created in Amazon SageMaker when you called the
* <a>CreateModel</a> API. It does not delete model artifacts, inference code, or
* the IAM role that you specified when creating the model. </p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModel">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteModelAsync(const Model::DeleteModelRequest& request, const DeleteModelResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes a model package.</p> <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModelPackage">AWS
* API Reference</a></p>
*/
virtual Model::DeleteModelPackageOutcome DeleteModelPackage(const Model::DeleteModelPackageRequest& request) const;
/**
* <p>Deletes a model package.</p> <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModelPackage">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteModelPackageOutcomeCallable DeleteModelPackageCallable(const Model::DeleteModelPackageRequest& request) const;
/**
* <p>Deletes a model package.</p> <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModelPackage">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteModelPackageAsync(const Model::DeleteModelPackageRequest& request, const DeleteModelPackageResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteMonitoringSchedule">AWS
* API Reference</a></p>
*/
virtual Model::DeleteMonitoringScheduleOutcome DeleteMonitoringSchedule(const Model::DeleteMonitoringScheduleRequest& request) const;
/**
* <p>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. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteMonitoringSchedule">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteMonitoringScheduleOutcomeCallable DeleteMonitoringScheduleCallable(const Model::DeleteMonitoringScheduleRequest& request) const;
/**
* <p>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. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteMonitoringSchedule">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteMonitoringScheduleAsync(const Model::DeleteMonitoringScheduleRequest& request, const DeleteMonitoringScheduleResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p> Deletes an Amazon SageMaker notebook instance. Before you can delete a
* notebook instance, you must call the <code>StopNotebookInstance</code> API. </p>
* <p>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. </p>
* <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteNotebookInstance">AWS
* API Reference</a></p>
*/
virtual Model::DeleteNotebookInstanceOutcome DeleteNotebookInstance(const Model::DeleteNotebookInstanceRequest& request) const;
/**
* <p> Deletes an Amazon SageMaker notebook instance. Before you can delete a
* notebook instance, you must call the <code>StopNotebookInstance</code> API. </p>
* <p>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. </p>
* <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteNotebookInstance">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteNotebookInstanceOutcomeCallable DeleteNotebookInstanceCallable(const Model::DeleteNotebookInstanceRequest& request) const;
/**
* <p> Deletes an Amazon SageMaker notebook instance. Before you can delete a
* notebook instance, you must call the <code>StopNotebookInstance</code> API. </p>
* <p>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. </p>
* <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteNotebookInstance">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteNotebookInstanceAsync(const Model::DeleteNotebookInstanceRequest& request, const DeleteNotebookInstanceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes a notebook instance lifecycle configuration.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteNotebookInstanceLifecycleConfig">AWS
* API Reference</a></p>
*/
virtual Model::DeleteNotebookInstanceLifecycleConfigOutcome DeleteNotebookInstanceLifecycleConfig(const Model::DeleteNotebookInstanceLifecycleConfigRequest& request) const;
/**
* <p>Deletes a notebook instance lifecycle configuration.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteNotebookInstanceLifecycleConfig">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteNotebookInstanceLifecycleConfigOutcomeCallable DeleteNotebookInstanceLifecycleConfigCallable(const Model::DeleteNotebookInstanceLifecycleConfigRequest& request) const;
/**
* <p>Deletes a notebook instance lifecycle configuration.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteNotebookInstanceLifecycleConfig">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteNotebookInstanceLifecycleConfigAsync(const Model::DeleteNotebookInstanceLifecycleConfigRequest& request, const DeleteNotebookInstanceLifecycleConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes the specified tags from an Amazon SageMaker resource.</p> <p>To list
* a resource's tags, use the <code>ListTags</code> API. </p> <p>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.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTags">AWS
* API Reference</a></p>
*/
virtual Model::DeleteTagsOutcome DeleteTags(const Model::DeleteTagsRequest& request) const;
/**
* <p>Deletes the specified tags from an Amazon SageMaker resource.</p> <p>To list
* a resource's tags, use the <code>ListTags</code> API. </p> <p>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.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTags">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteTagsOutcomeCallable DeleteTagsCallable(const Model::DeleteTagsRequest& request) const;
/**
* <p>Deletes the specified tags from an Amazon SageMaker resource.</p> <p>To list
* a resource's tags, use the <code>ListTags</code> API. </p> <p>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.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTags">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteTagsAsync(const Model::DeleteTagsRequest& request, const DeleteTagsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes the specified trial. All trial components that make up the trial must
* be deleted first. Use the <a>DescribeTrialComponent</a> API to get the list of
* trial components.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTrial">AWS
* API Reference</a></p>
*/
virtual Model::DeleteTrialOutcome DeleteTrial(const Model::DeleteTrialRequest& request) const;
/**
* <p>Deletes the specified trial. All trial components that make up the trial must
* be deleted first. Use the <a>DescribeTrialComponent</a> API to get the list of
* trial components.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTrial">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteTrialOutcomeCallable DeleteTrialCallable(const Model::DeleteTrialRequest& request) const;
/**
* <p>Deletes the specified trial. All trial components that make up the trial must
* be deleted first. Use the <a>DescribeTrialComponent</a> API to get the list of
* trial components.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTrial">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteTrialAsync(const Model::DeleteTrialRequest& request, const DeleteTrialResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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
* <a>DisassociateTrialComponent</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTrialComponent">AWS
* API Reference</a></p>
*/
virtual Model::DeleteTrialComponentOutcome DeleteTrialComponent(const Model::DeleteTrialComponentRequest& request) const;
/**
* <p>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
* <a>DisassociateTrialComponent</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTrialComponent">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteTrialComponentOutcomeCallable DeleteTrialComponentCallable(const Model::DeleteTrialComponentRequest& request) const;
/**
* <p>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
* <a>DisassociateTrialComponent</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTrialComponent">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteTrialComponentAsync(const Model::DeleteTrialComponentRequest& request, const DeleteTrialComponentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes a user profile. When a user profile is deleted, the user loses access
* to their EFS volume, including data, notebooks, and other
* artifacts.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteUserProfile">AWS
* API Reference</a></p>
*/
virtual Model::DeleteUserProfileOutcome DeleteUserProfile(const Model::DeleteUserProfileRequest& request) const;
/**
* <p>Deletes a user profile. When a user profile is deleted, the user loses access
* to their EFS volume, including data, notebooks, and other
* artifacts.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteUserProfile">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteUserProfileOutcomeCallable DeleteUserProfileCallable(const Model::DeleteUserProfileRequest& request) const;
/**
* <p>Deletes a user profile. When a user profile is deleted, the user loses access
* to their EFS volume, including data, notebooks, and other
* artifacts.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteUserProfile">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteUserProfileAsync(const Model::DeleteUserProfileRequest& request, const DeleteUserProfileResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Use this operation to delete a workforce.</p> <p>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.</p>
* <p>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 <code>ResourceInUse</code> error.</p> <p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteWorkforce">AWS
* API Reference</a></p>
*/
virtual Model::DeleteWorkforceOutcome DeleteWorkforce(const Model::DeleteWorkforceRequest& request) const;
/**
* <p>Use this operation to delete a workforce.</p> <p>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.</p>
* <p>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 <code>ResourceInUse</code> error.</p> <p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteWorkforce">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteWorkforceOutcomeCallable DeleteWorkforceCallable(const Model::DeleteWorkforceRequest& request) const;
/**
* <p>Use this operation to delete a workforce.</p> <p>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.</p>
* <p>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 <code>ResourceInUse</code> error.</p> <p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteWorkforce">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteWorkforceAsync(const Model::DeleteWorkforceRequest& request, const DeleteWorkforceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deletes an existing work team. This operation can't be undone.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteWorkteam">AWS
* API Reference</a></p>
*/
virtual Model::DeleteWorkteamOutcome DeleteWorkteam(const Model::DeleteWorkteamRequest& request) const;
/**
* <p>Deletes an existing work team. This operation can't be undone.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteWorkteam">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DeleteWorkteamOutcomeCallable DeleteWorkteamCallable(const Model::DeleteWorkteamRequest& request) const;
/**
* <p>Deletes an existing work team. This operation can't be undone.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteWorkteam">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DeleteWorkteamAsync(const Model::DeleteWorkteamRequest& request, const DeleteWorkteamResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns a description of the specified algorithm that is in your
* account.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAlgorithm">AWS
* API Reference</a></p>
*/
virtual Model::DescribeAlgorithmOutcome DescribeAlgorithm(const Model::DescribeAlgorithmRequest& request) const;
/**
* <p>Returns a description of the specified algorithm that is in your
* account.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAlgorithm">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeAlgorithmOutcomeCallable DescribeAlgorithmCallable(const Model::DescribeAlgorithmRequest& request) const;
/**
* <p>Returns a description of the specified algorithm that is in your
* account.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAlgorithm">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeAlgorithmAsync(const Model::DescribeAlgorithmRequest& request, const DescribeAlgorithmResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Describes the app.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeApp">AWS
* API Reference</a></p>
*/
virtual Model::DescribeAppOutcome DescribeApp(const Model::DescribeAppRequest& request) const;
/**
* <p>Describes the app.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeApp">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeAppOutcomeCallable DescribeAppCallable(const Model::DescribeAppRequest& request) const;
/**
* <p>Describes the app.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeApp">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeAppAsync(const Model::DescribeAppRequest& request, const DescribeAppResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns information about an Amazon SageMaker job.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAutoMLJob">AWS
* API Reference</a></p>
*/
virtual Model::DescribeAutoMLJobOutcome DescribeAutoMLJob(const Model::DescribeAutoMLJobRequest& request) const;
/**
* <p>Returns information about an Amazon SageMaker job.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAutoMLJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeAutoMLJobOutcomeCallable DescribeAutoMLJobCallable(const Model::DescribeAutoMLJobRequest& request) const;
/**
* <p>Returns information about an Amazon SageMaker job.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAutoMLJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeAutoMLJobAsync(const Model::DescribeAutoMLJobRequest& request, const DescribeAutoMLJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets details about the specified Git repository.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeCodeRepository">AWS
* API Reference</a></p>
*/
virtual Model::DescribeCodeRepositoryOutcome DescribeCodeRepository(const Model::DescribeCodeRepositoryRequest& request) const;
/**
* <p>Gets details about the specified Git repository.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeCodeRepository">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeCodeRepositoryOutcomeCallable DescribeCodeRepositoryCallable(const Model::DescribeCodeRepositoryRequest& request) const;
/**
* <p>Gets details about the specified Git repository.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeCodeRepository">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeCodeRepositoryAsync(const Model::DescribeCodeRepositoryRequest& request, const DescribeCodeRepositoryResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns information about a model compilation job.</p> <p>To create a model
* compilation job, use <a>CreateCompilationJob</a>. To get information about
* multiple model compilation jobs, use <a>ListCompilationJobs</a>.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeCompilationJob">AWS
* API Reference</a></p>
*/
virtual Model::DescribeCompilationJobOutcome DescribeCompilationJob(const Model::DescribeCompilationJobRequest& request) const;
/**
* <p>Returns information about a model compilation job.</p> <p>To create a model
* compilation job, use <a>CreateCompilationJob</a>. To get information about
* multiple model compilation jobs, use <a>ListCompilationJobs</a>.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeCompilationJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeCompilationJobOutcomeCallable DescribeCompilationJobCallable(const Model::DescribeCompilationJobRequest& request) const;
/**
* <p>Returns information about a model compilation job.</p> <p>To create a model
* compilation job, use <a>CreateCompilationJob</a>. To get information about
* multiple model compilation jobs, use <a>ListCompilationJobs</a>.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeCompilationJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeCompilationJobAsync(const Model::DescribeCompilationJobRequest& request, const DescribeCompilationJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>The description of the domain.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeDomain">AWS
* API Reference</a></p>
*/
virtual Model::DescribeDomainOutcome DescribeDomain(const Model::DescribeDomainRequest& request) const;
/**
* <p>The description of the domain.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeDomain">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeDomainOutcomeCallable DescribeDomainCallable(const Model::DescribeDomainRequest& request) const;
/**
* <p>The description of the domain.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeDomain">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeDomainAsync(const Model::DescribeDomainRequest& request, const DescribeDomainResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns the description of an endpoint.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEndpoint">AWS
* API Reference</a></p>
*/
virtual Model::DescribeEndpointOutcome DescribeEndpoint(const Model::DescribeEndpointRequest& request) const;
/**
* <p>Returns the description of an endpoint.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEndpoint">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeEndpointOutcomeCallable DescribeEndpointCallable(const Model::DescribeEndpointRequest& request) const;
/**
* <p>Returns the description of an endpoint.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEndpoint">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeEndpointAsync(const Model::DescribeEndpointRequest& request, const DescribeEndpointResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns the description of an endpoint configuration created using the
* <code>CreateEndpointConfig</code> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEndpointConfig">AWS
* API Reference</a></p>
*/
virtual Model::DescribeEndpointConfigOutcome DescribeEndpointConfig(const Model::DescribeEndpointConfigRequest& request) const;
/**
* <p>Returns the description of an endpoint configuration created using the
* <code>CreateEndpointConfig</code> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEndpointConfig">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeEndpointConfigOutcomeCallable DescribeEndpointConfigCallable(const Model::DescribeEndpointConfigRequest& request) const;
/**
* <p>Returns the description of an endpoint configuration created using the
* <code>CreateEndpointConfig</code> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEndpointConfig">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeEndpointConfigAsync(const Model::DescribeEndpointConfigRequest& request, const DescribeEndpointConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Provides a list of an experiment's properties.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeExperiment">AWS
* API Reference</a></p>
*/
virtual Model::DescribeExperimentOutcome DescribeExperiment(const Model::DescribeExperimentRequest& request) const;
/**
* <p>Provides a list of an experiment's properties.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeExperiment">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeExperimentOutcomeCallable DescribeExperimentCallable(const Model::DescribeExperimentRequest& request) const;
/**
* <p>Provides a list of an experiment's properties.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeExperiment">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeExperimentAsync(const Model::DescribeExperimentRequest& request, const DescribeExperimentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns information about the specified flow definition.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeFlowDefinition">AWS
* API Reference</a></p>
*/
virtual Model::DescribeFlowDefinitionOutcome DescribeFlowDefinition(const Model::DescribeFlowDefinitionRequest& request) const;
/**
* <p>Returns information about the specified flow definition.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeFlowDefinition">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeFlowDefinitionOutcomeCallable DescribeFlowDefinitionCallable(const Model::DescribeFlowDefinitionRequest& request) const;
/**
* <p>Returns information about the specified flow definition.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeFlowDefinition">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeFlowDefinitionAsync(const Model::DescribeFlowDefinitionRequest& request, const DescribeFlowDefinitionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns information about the requested human task user interface (worker
* task template).</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHumanTaskUi">AWS
* API Reference</a></p>
*/
virtual Model::DescribeHumanTaskUiOutcome DescribeHumanTaskUi(const Model::DescribeHumanTaskUiRequest& request) const;
/**
* <p>Returns information about the requested human task user interface (worker
* task template).</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHumanTaskUi">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeHumanTaskUiOutcomeCallable DescribeHumanTaskUiCallable(const Model::DescribeHumanTaskUiRequest& request) const;
/**
* <p>Returns information about the requested human task user interface (worker
* task template).</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHumanTaskUi">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeHumanTaskUiAsync(const Model::DescribeHumanTaskUiRequest& request, const DescribeHumanTaskUiResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets a description of a hyperparameter tuning job.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHyperParameterTuningJob">AWS
* API Reference</a></p>
*/
virtual Model::DescribeHyperParameterTuningJobOutcome DescribeHyperParameterTuningJob(const Model::DescribeHyperParameterTuningJobRequest& request) const;
/**
* <p>Gets a description of a hyperparameter tuning job.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHyperParameterTuningJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeHyperParameterTuningJobOutcomeCallable DescribeHyperParameterTuningJobCallable(const Model::DescribeHyperParameterTuningJobRequest& request) const;
/**
* <p>Gets a description of a hyperparameter tuning job.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHyperParameterTuningJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeHyperParameterTuningJobAsync(const Model::DescribeHyperParameterTuningJobRequest& request, const DescribeHyperParameterTuningJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets information about a labeling job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeLabelingJob">AWS
* API Reference</a></p>
*/
virtual Model::DescribeLabelingJobOutcome DescribeLabelingJob(const Model::DescribeLabelingJobRequest& request) const;
/**
* <p>Gets information about a labeling job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeLabelingJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeLabelingJobOutcomeCallable DescribeLabelingJobCallable(const Model::DescribeLabelingJobRequest& request) const;
/**
* <p>Gets information about a labeling job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeLabelingJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeLabelingJobAsync(const Model::DescribeLabelingJobRequest& request, const DescribeLabelingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Describes a model that you created using the <code>CreateModel</code>
* API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModel">AWS
* API Reference</a></p>
*/
virtual Model::DescribeModelOutcome DescribeModel(const Model::DescribeModelRequest& request) const;
/**
* <p>Describes a model that you created using the <code>CreateModel</code>
* API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModel">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeModelOutcomeCallable DescribeModelCallable(const Model::DescribeModelRequest& request) const;
/**
* <p>Describes a model that you created using the <code>CreateModel</code>
* API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModel">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeModelAsync(const Model::DescribeModelRequest& request, const DescribeModelResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns a description of the specified model package, which is used to create
* Amazon SageMaker models or list them on AWS Marketplace.</p> <p>To create models
* in Amazon SageMaker, buyers can subscribe to model packages listed on AWS
* Marketplace.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelPackage">AWS
* API Reference</a></p>
*/
virtual Model::DescribeModelPackageOutcome DescribeModelPackage(const Model::DescribeModelPackageRequest& request) const;
/**
* <p>Returns a description of the specified model package, which is used to create
* Amazon SageMaker models or list them on AWS Marketplace.</p> <p>To create models
* in Amazon SageMaker, buyers can subscribe to model packages listed on AWS
* Marketplace.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelPackage">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeModelPackageOutcomeCallable DescribeModelPackageCallable(const Model::DescribeModelPackageRequest& request) const;
/**
* <p>Returns a description of the specified model package, which is used to create
* Amazon SageMaker models or list them on AWS Marketplace.</p> <p>To create models
* in Amazon SageMaker, buyers can subscribe to model packages listed on AWS
* Marketplace.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelPackage">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeModelPackageAsync(const Model::DescribeModelPackageRequest& request, const DescribeModelPackageResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Describes the schedule for a monitoring job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeMonitoringSchedule">AWS
* API Reference</a></p>
*/
virtual Model::DescribeMonitoringScheduleOutcome DescribeMonitoringSchedule(const Model::DescribeMonitoringScheduleRequest& request) const;
/**
* <p>Describes the schedule for a monitoring job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeMonitoringSchedule">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeMonitoringScheduleOutcomeCallable DescribeMonitoringScheduleCallable(const Model::DescribeMonitoringScheduleRequest& request) const;
/**
* <p>Describes the schedule for a monitoring job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeMonitoringSchedule">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeMonitoringScheduleAsync(const Model::DescribeMonitoringScheduleRequest& request, const DescribeMonitoringScheduleResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns information about a notebook instance.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeNotebookInstance">AWS
* API Reference</a></p>
*/
virtual Model::DescribeNotebookInstanceOutcome DescribeNotebookInstance(const Model::DescribeNotebookInstanceRequest& request) const;
/**
* <p>Returns information about a notebook instance.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeNotebookInstance">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeNotebookInstanceOutcomeCallable DescribeNotebookInstanceCallable(const Model::DescribeNotebookInstanceRequest& request) const;
/**
* <p>Returns information about a notebook instance.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeNotebookInstance">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeNotebookInstanceAsync(const Model::DescribeNotebookInstanceRequest& request, const DescribeNotebookInstanceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns a description of a notebook instance lifecycle configuration.</p>
* <p>For information about notebook instance lifestyle configurations, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html">Step
* 2.1: (Optional) Customize a Notebook Instance</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeNotebookInstanceLifecycleConfig">AWS
* API Reference</a></p>
*/
virtual Model::DescribeNotebookInstanceLifecycleConfigOutcome DescribeNotebookInstanceLifecycleConfig(const Model::DescribeNotebookInstanceLifecycleConfigRequest& request) const;
/**
* <p>Returns a description of a notebook instance lifecycle configuration.</p>
* <p>For information about notebook instance lifestyle configurations, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html">Step
* 2.1: (Optional) Customize a Notebook Instance</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeNotebookInstanceLifecycleConfig">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeNotebookInstanceLifecycleConfigOutcomeCallable DescribeNotebookInstanceLifecycleConfigCallable(const Model::DescribeNotebookInstanceLifecycleConfigRequest& request) const;
/**
* <p>Returns a description of a notebook instance lifecycle configuration.</p>
* <p>For information about notebook instance lifestyle configurations, see <a
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html">Step
* 2.1: (Optional) Customize a Notebook Instance</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeNotebookInstanceLifecycleConfig">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeNotebookInstanceLifecycleConfigAsync(const Model::DescribeNotebookInstanceLifecycleConfigRequest& request, const DescribeNotebookInstanceLifecycleConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns a description of a processing job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeProcessingJob">AWS
* API Reference</a></p>
*/
virtual Model::DescribeProcessingJobOutcome DescribeProcessingJob(const Model::DescribeProcessingJobRequest& request) const;
/**
* <p>Returns a description of a processing job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeProcessingJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeProcessingJobOutcomeCallable DescribeProcessingJobCallable(const Model::DescribeProcessingJobRequest& request) const;
/**
* <p>Returns a description of a processing job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeProcessingJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeProcessingJobAsync(const Model::DescribeProcessingJobRequest& request, const DescribeProcessingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets information about a work team provided by a vendor. It returns details
* about the subscription with a vendor in the AWS Marketplace.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeSubscribedWorkteam">AWS
* API Reference</a></p>
*/
virtual Model::DescribeSubscribedWorkteamOutcome DescribeSubscribedWorkteam(const Model::DescribeSubscribedWorkteamRequest& request) const;
/**
* <p>Gets information about a work team provided by a vendor. It returns details
* about the subscription with a vendor in the AWS Marketplace.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeSubscribedWorkteam">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeSubscribedWorkteamOutcomeCallable DescribeSubscribedWorkteamCallable(const Model::DescribeSubscribedWorkteamRequest& request) const;
/**
* <p>Gets information about a work team provided by a vendor. It returns details
* about the subscription with a vendor in the AWS Marketplace.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeSubscribedWorkteam">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeSubscribedWorkteamAsync(const Model::DescribeSubscribedWorkteamRequest& request, const DescribeSubscribedWorkteamResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns information about a training job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrainingJob">AWS
* API Reference</a></p>
*/
virtual Model::DescribeTrainingJobOutcome DescribeTrainingJob(const Model::DescribeTrainingJobRequest& request) const;
/**
* <p>Returns information about a training job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrainingJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeTrainingJobOutcomeCallable DescribeTrainingJobCallable(const Model::DescribeTrainingJobRequest& request) const;
/**
* <p>Returns information about a training job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrainingJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeTrainingJobAsync(const Model::DescribeTrainingJobRequest& request, const DescribeTrainingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns information about a transform job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTransformJob">AWS
* API Reference</a></p>
*/
virtual Model::DescribeTransformJobOutcome DescribeTransformJob(const Model::DescribeTransformJobRequest& request) const;
/**
* <p>Returns information about a transform job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTransformJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeTransformJobOutcomeCallable DescribeTransformJobCallable(const Model::DescribeTransformJobRequest& request) const;
/**
* <p>Returns information about a transform job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTransformJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeTransformJobAsync(const Model::DescribeTransformJobRequest& request, const DescribeTransformJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Provides a list of a trial's properties.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrial">AWS
* API Reference</a></p>
*/
virtual Model::DescribeTrialOutcome DescribeTrial(const Model::DescribeTrialRequest& request) const;
/**
* <p>Provides a list of a trial's properties.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrial">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeTrialOutcomeCallable DescribeTrialCallable(const Model::DescribeTrialRequest& request) const;
/**
* <p>Provides a list of a trial's properties.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrial">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeTrialAsync(const Model::DescribeTrialRequest& request, const DescribeTrialResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Provides a list of a trials component's properties.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrialComponent">AWS
* API Reference</a></p>
*/
virtual Model::DescribeTrialComponentOutcome DescribeTrialComponent(const Model::DescribeTrialComponentRequest& request) const;
/**
* <p>Provides a list of a trials component's properties.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrialComponent">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeTrialComponentOutcomeCallable DescribeTrialComponentCallable(const Model::DescribeTrialComponentRequest& request) const;
/**
* <p>Provides a list of a trials component's properties.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrialComponent">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeTrialComponentAsync(const Model::DescribeTrialComponentRequest& request, const DescribeTrialComponentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Describes a user profile. For more information, see
* <code>CreateUserProfile</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeUserProfile">AWS
* API Reference</a></p>
*/
virtual Model::DescribeUserProfileOutcome DescribeUserProfile(const Model::DescribeUserProfileRequest& request) const;
/**
* <p>Describes a user profile. For more information, see
* <code>CreateUserProfile</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeUserProfile">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeUserProfileOutcomeCallable DescribeUserProfileCallable(const Model::DescribeUserProfileRequest& request) const;
/**
* <p>Describes a user profile. For more information, see
* <code>CreateUserProfile</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeUserProfile">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeUserProfileAsync(const Model::DescribeUserProfileRequest& request, const DescribeUserProfileResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists private workforce information, including workforce name, Amazon
* Resource Name (ARN), and, if applicable, allowed IP address ranges (<a
* href="https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html">CIDRs</a>).
* Allowable IP address ranges are the IP addresses that workers can use to access
* tasks. </p> <p>This operation applies only to private
* workforces.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeWorkforce">AWS
* API Reference</a></p>
*/
virtual Model::DescribeWorkforceOutcome DescribeWorkforce(const Model::DescribeWorkforceRequest& request) const;
/**
* <p>Lists private workforce information, including workforce name, Amazon
* Resource Name (ARN), and, if applicable, allowed IP address ranges (<a
* href="https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html">CIDRs</a>).
* Allowable IP address ranges are the IP addresses that workers can use to access
* tasks. </p> <p>This operation applies only to private
* workforces.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeWorkforce">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeWorkforceOutcomeCallable DescribeWorkforceCallable(const Model::DescribeWorkforceRequest& request) const;
/**
* <p>Lists private workforce information, including workforce name, Amazon
* Resource Name (ARN), and, if applicable, allowed IP address ranges (<a
* href="https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html">CIDRs</a>).
* Allowable IP address ranges are the IP addresses that workers can use to access
* tasks. </p> <p>This operation applies only to private
* workforces.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeWorkforce">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeWorkforceAsync(const Model::DescribeWorkforceRequest& request, const DescribeWorkforceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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).</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeWorkteam">AWS
* API Reference</a></p>
*/
virtual Model::DescribeWorkteamOutcome DescribeWorkteam(const Model::DescribeWorkteamRequest& request) const;
/**
* <p>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).</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeWorkteam">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DescribeWorkteamOutcomeCallable DescribeWorkteamCallable(const Model::DescribeWorkteamRequest& request) const;
/**
* <p>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).</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeWorkteam">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DescribeWorkteamAsync(const Model::DescribeWorkteamRequest& request, const DescribeWorkteamResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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
* <a>AssociateTrialComponent</a> API.</p> <p>To get a list of the trials a
* component is associated with, use the <a>Search</a> API. Specify
* <code>ExperimentTrialComponent</code> for the <code>Resource</code> parameter.
* The list appears in the response under
* <code>Results.TrialComponent.Parents</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DisassociateTrialComponent">AWS
* API Reference</a></p>
*/
virtual Model::DisassociateTrialComponentOutcome DisassociateTrialComponent(const Model::DisassociateTrialComponentRequest& request) const;
/**
* <p>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
* <a>AssociateTrialComponent</a> API.</p> <p>To get a list of the trials a
* component is associated with, use the <a>Search</a> API. Specify
* <code>ExperimentTrialComponent</code> for the <code>Resource</code> parameter.
* The list appears in the response under
* <code>Results.TrialComponent.Parents</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DisassociateTrialComponent">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::DisassociateTrialComponentOutcomeCallable DisassociateTrialComponentCallable(const Model::DisassociateTrialComponentRequest& request) const;
/**
* <p>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
* <a>AssociateTrialComponent</a> API.</p> <p>To get a list of the trials a
* component is associated with, use the <a>Search</a> API. Specify
* <code>ExperimentTrialComponent</code> for the <code>Resource</code> parameter.
* The list appears in the response under
* <code>Results.TrialComponent.Parents</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DisassociateTrialComponent">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void DisassociateTrialComponentAsync(const Model::DisassociateTrialComponentRequest& request, const DisassociateTrialComponentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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 <code>Search</code> queries. Provides suggestions for
* <code>HyperParameters</code>, <code>Tags</code>, and
* <code>Metrics</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetSearchSuggestions">AWS
* API Reference</a></p>
*/
virtual Model::GetSearchSuggestionsOutcome GetSearchSuggestions(const Model::GetSearchSuggestionsRequest& request) const;
/**
* <p>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 <code>Search</code> queries. Provides suggestions for
* <code>HyperParameters</code>, <code>Tags</code>, and
* <code>Metrics</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetSearchSuggestions">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::GetSearchSuggestionsOutcomeCallable GetSearchSuggestionsCallable(const Model::GetSearchSuggestionsRequest& request) const;
/**
* <p>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 <code>Search</code> queries. Provides suggestions for
* <code>HyperParameters</code>, <code>Tags</code>, and
* <code>Metrics</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetSearchSuggestions">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void GetSearchSuggestionsAsync(const Model::GetSearchSuggestionsRequest& request, const GetSearchSuggestionsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists the machine learning algorithms that have been created.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAlgorithms">AWS
* API Reference</a></p>
*/
virtual Model::ListAlgorithmsOutcome ListAlgorithms(const Model::ListAlgorithmsRequest& request) const;
/**
* <p>Lists the machine learning algorithms that have been created.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAlgorithms">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListAlgorithmsOutcomeCallable ListAlgorithmsCallable(const Model::ListAlgorithmsRequest& request) const;
/**
* <p>Lists the machine learning algorithms that have been created.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAlgorithms">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListAlgorithmsAsync(const Model::ListAlgorithmsRequest& request, const ListAlgorithmsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists apps.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListApps">AWS
* API Reference</a></p>
*/
virtual Model::ListAppsOutcome ListApps(const Model::ListAppsRequest& request) const;
/**
* <p>Lists apps.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListApps">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListAppsOutcomeCallable ListAppsCallable(const Model::ListAppsRequest& request) const;
/**
* <p>Lists apps.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListApps">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListAppsAsync(const Model::ListAppsRequest& request, const ListAppsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Request a list of jobs.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAutoMLJobs">AWS
* API Reference</a></p>
*/
virtual Model::ListAutoMLJobsOutcome ListAutoMLJobs(const Model::ListAutoMLJobsRequest& request) const;
/**
* <p>Request a list of jobs.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAutoMLJobs">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListAutoMLJobsOutcomeCallable ListAutoMLJobsCallable(const Model::ListAutoMLJobsRequest& request) const;
/**
* <p>Request a list of jobs.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAutoMLJobs">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListAutoMLJobsAsync(const Model::ListAutoMLJobsRequest& request, const ListAutoMLJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>List the Candidates created for the job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCandidatesForAutoMLJob">AWS
* API Reference</a></p>
*/
virtual Model::ListCandidatesForAutoMLJobOutcome ListCandidatesForAutoMLJob(const Model::ListCandidatesForAutoMLJobRequest& request) const;
/**
* <p>List the Candidates created for the job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCandidatesForAutoMLJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListCandidatesForAutoMLJobOutcomeCallable ListCandidatesForAutoMLJobCallable(const Model::ListCandidatesForAutoMLJobRequest& request) const;
/**
* <p>List the Candidates created for the job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCandidatesForAutoMLJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListCandidatesForAutoMLJobAsync(const Model::ListCandidatesForAutoMLJobRequest& request, const ListCandidatesForAutoMLJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets a list of the Git repositories in your account.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCodeRepositories">AWS
* API Reference</a></p>
*/
virtual Model::ListCodeRepositoriesOutcome ListCodeRepositories(const Model::ListCodeRepositoriesRequest& request) const;
/**
* <p>Gets a list of the Git repositories in your account.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCodeRepositories">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListCodeRepositoriesOutcomeCallable ListCodeRepositoriesCallable(const Model::ListCodeRepositoriesRequest& request) const;
/**
* <p>Gets a list of the Git repositories in your account.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCodeRepositories">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListCodeRepositoriesAsync(const Model::ListCodeRepositoriesRequest& request, const ListCodeRepositoriesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists model compilation jobs that satisfy various filters.</p> <p>To create a
* model compilation job, use <a>CreateCompilationJob</a>. To get information about
* a particular model compilation job you have created, use
* <a>DescribeCompilationJob</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCompilationJobs">AWS
* API Reference</a></p>
*/
virtual Model::ListCompilationJobsOutcome ListCompilationJobs(const Model::ListCompilationJobsRequest& request) const;
/**
* <p>Lists model compilation jobs that satisfy various filters.</p> <p>To create a
* model compilation job, use <a>CreateCompilationJob</a>. To get information about
* a particular model compilation job you have created, use
* <a>DescribeCompilationJob</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCompilationJobs">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListCompilationJobsOutcomeCallable ListCompilationJobsCallable(const Model::ListCompilationJobsRequest& request) const;
/**
* <p>Lists model compilation jobs that satisfy various filters.</p> <p>To create a
* model compilation job, use <a>CreateCompilationJob</a>. To get information about
* a particular model compilation job you have created, use
* <a>DescribeCompilationJob</a>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCompilationJobs">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListCompilationJobsAsync(const Model::ListCompilationJobsRequest& request, const ListCompilationJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists the domains.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListDomains">AWS
* API Reference</a></p>
*/
virtual Model::ListDomainsOutcome ListDomains(const Model::ListDomainsRequest& request) const;
/**
* <p>Lists the domains.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListDomains">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListDomainsOutcomeCallable ListDomainsCallable(const Model::ListDomainsRequest& request) const;
/**
* <p>Lists the domains.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListDomains">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListDomainsAsync(const Model::ListDomainsRequest& request, const ListDomainsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists endpoint configurations.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEndpointConfigs">AWS
* API Reference</a></p>
*/
virtual Model::ListEndpointConfigsOutcome ListEndpointConfigs(const Model::ListEndpointConfigsRequest& request) const;
/**
* <p>Lists endpoint configurations.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEndpointConfigs">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListEndpointConfigsOutcomeCallable ListEndpointConfigsCallable(const Model::ListEndpointConfigsRequest& request) const;
/**
* <p>Lists endpoint configurations.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEndpointConfigs">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListEndpointConfigsAsync(const Model::ListEndpointConfigsRequest& request, const ListEndpointConfigsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists endpoints.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEndpoints">AWS
* API Reference</a></p>
*/
virtual Model::ListEndpointsOutcome ListEndpoints(const Model::ListEndpointsRequest& request) const;
/**
* <p>Lists endpoints.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEndpoints">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListEndpointsOutcomeCallable ListEndpointsCallable(const Model::ListEndpointsRequest& request) const;
/**
* <p>Lists endpoints.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEndpoints">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListEndpointsAsync(const Model::ListEndpointsRequest& request, const ListEndpointsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListExperiments">AWS
* API Reference</a></p>
*/
virtual Model::ListExperimentsOutcome ListExperiments(const Model::ListExperimentsRequest& request) const;
/**
* <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListExperiments">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListExperimentsOutcomeCallable ListExperimentsCallable(const Model::ListExperimentsRequest& request) const;
/**
* <p>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.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListExperiments">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListExperimentsAsync(const Model::ListExperimentsRequest& request, const ListExperimentsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns information about the flow definitions in your account.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListFlowDefinitions">AWS
* API Reference</a></p>
*/
virtual Model::ListFlowDefinitionsOutcome ListFlowDefinitions(const Model::ListFlowDefinitionsRequest& request) const;
/**
* <p>Returns information about the flow definitions in your account.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListFlowDefinitions">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListFlowDefinitionsOutcomeCallable ListFlowDefinitionsCallable(const Model::ListFlowDefinitionsRequest& request) const;
/**
* <p>Returns information about the flow definitions in your account.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListFlowDefinitions">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListFlowDefinitionsAsync(const Model::ListFlowDefinitionsRequest& request, const ListFlowDefinitionsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns information about the human task user interfaces in your
* account.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHumanTaskUis">AWS
* API Reference</a></p>
*/
virtual Model::ListHumanTaskUisOutcome ListHumanTaskUis(const Model::ListHumanTaskUisRequest& request) const;
/**
* <p>Returns information about the human task user interfaces in your
* account.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHumanTaskUis">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListHumanTaskUisOutcomeCallable ListHumanTaskUisCallable(const Model::ListHumanTaskUisRequest& request) const;
/**
* <p>Returns information about the human task user interfaces in your
* account.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHumanTaskUis">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListHumanTaskUisAsync(const Model::ListHumanTaskUisRequest& request, const ListHumanTaskUisResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets a list of <a>HyperParameterTuningJobSummary</a> objects that describe
* the hyperparameter tuning jobs launched in your account.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHyperParameterTuningJobs">AWS
* API Reference</a></p>
*/
virtual Model::ListHyperParameterTuningJobsOutcome ListHyperParameterTuningJobs(const Model::ListHyperParameterTuningJobsRequest& request) const;
/**
* <p>Gets a list of <a>HyperParameterTuningJobSummary</a> objects that describe
* the hyperparameter tuning jobs launched in your account.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHyperParameterTuningJobs">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListHyperParameterTuningJobsOutcomeCallable ListHyperParameterTuningJobsCallable(const Model::ListHyperParameterTuningJobsRequest& request) const;
/**
* <p>Gets a list of <a>HyperParameterTuningJobSummary</a> objects that describe
* the hyperparameter tuning jobs launched in your account.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHyperParameterTuningJobs">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListHyperParameterTuningJobsAsync(const Model::ListHyperParameterTuningJobsRequest& request, const ListHyperParameterTuningJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets a list of labeling jobs.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListLabelingJobs">AWS
* API Reference</a></p>
*/
virtual Model::ListLabelingJobsOutcome ListLabelingJobs(const Model::ListLabelingJobsRequest& request) const;
/**
* <p>Gets a list of labeling jobs.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListLabelingJobs">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListLabelingJobsOutcomeCallable ListLabelingJobsCallable(const Model::ListLabelingJobsRequest& request) const;
/**
* <p>Gets a list of labeling jobs.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListLabelingJobs">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListLabelingJobsAsync(const Model::ListLabelingJobsRequest& request, const ListLabelingJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets a list of labeling jobs assigned to a specified work team.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListLabelingJobsForWorkteam">AWS
* API Reference</a></p>
*/
virtual Model::ListLabelingJobsForWorkteamOutcome ListLabelingJobsForWorkteam(const Model::ListLabelingJobsForWorkteamRequest& request) const;
/**
* <p>Gets a list of labeling jobs assigned to a specified work team.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListLabelingJobsForWorkteam">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListLabelingJobsForWorkteamOutcomeCallable ListLabelingJobsForWorkteamCallable(const Model::ListLabelingJobsForWorkteamRequest& request) const;
/**
* <p>Gets a list of labeling jobs assigned to a specified work team.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListLabelingJobsForWorkteam">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListLabelingJobsForWorkteamAsync(const Model::ListLabelingJobsForWorkteamRequest& request, const ListLabelingJobsForWorkteamResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists the model packages that have been created.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelPackages">AWS
* API Reference</a></p>
*/
virtual Model::ListModelPackagesOutcome ListModelPackages(const Model::ListModelPackagesRequest& request) const;
/**
* <p>Lists the model packages that have been created.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelPackages">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListModelPackagesOutcomeCallable ListModelPackagesCallable(const Model::ListModelPackagesRequest& request) const;
/**
* <p>Lists the model packages that have been created.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelPackages">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListModelPackagesAsync(const Model::ListModelPackagesRequest& request, const ListModelPackagesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists models created with the <a>CreateModel</a> API.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModels">AWS
* API Reference</a></p>
*/
virtual Model::ListModelsOutcome ListModels(const Model::ListModelsRequest& request) const;
/**
* <p>Lists models created with the <a>CreateModel</a> API.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModels">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListModelsOutcomeCallable ListModelsCallable(const Model::ListModelsRequest& request) const;
/**
* <p>Lists models created with the <a>CreateModel</a> API.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModels">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListModelsAsync(const Model::ListModelsRequest& request, const ListModelsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns list of all monitoring job executions.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringExecutions">AWS
* API Reference</a></p>
*/
virtual Model::ListMonitoringExecutionsOutcome ListMonitoringExecutions(const Model::ListMonitoringExecutionsRequest& request) const;
/**
* <p>Returns list of all monitoring job executions.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringExecutions">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListMonitoringExecutionsOutcomeCallable ListMonitoringExecutionsCallable(const Model::ListMonitoringExecutionsRequest& request) const;
/**
* <p>Returns list of all monitoring job executions.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringExecutions">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListMonitoringExecutionsAsync(const Model::ListMonitoringExecutionsRequest& request, const ListMonitoringExecutionsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns list of all monitoring schedules.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringSchedules">AWS
* API Reference</a></p>
*/
virtual Model::ListMonitoringSchedulesOutcome ListMonitoringSchedules(const Model::ListMonitoringSchedulesRequest& request) const;
/**
* <p>Returns list of all monitoring schedules.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringSchedules">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListMonitoringSchedulesOutcomeCallable ListMonitoringSchedulesCallable(const Model::ListMonitoringSchedulesRequest& request) const;
/**
* <p>Returns list of all monitoring schedules.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringSchedules">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListMonitoringSchedulesAsync(const Model::ListMonitoringSchedulesRequest& request, const ListMonitoringSchedulesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists notebook instance lifestyle configurations created with the
* <a>CreateNotebookInstanceLifecycleConfig</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListNotebookInstanceLifecycleConfigs">AWS
* API Reference</a></p>
*/
virtual Model::ListNotebookInstanceLifecycleConfigsOutcome ListNotebookInstanceLifecycleConfigs(const Model::ListNotebookInstanceLifecycleConfigsRequest& request) const;
/**
* <p>Lists notebook instance lifestyle configurations created with the
* <a>CreateNotebookInstanceLifecycleConfig</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListNotebookInstanceLifecycleConfigs">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListNotebookInstanceLifecycleConfigsOutcomeCallable ListNotebookInstanceLifecycleConfigsCallable(const Model::ListNotebookInstanceLifecycleConfigsRequest& request) const;
/**
* <p>Lists notebook instance lifestyle configurations created with the
* <a>CreateNotebookInstanceLifecycleConfig</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListNotebookInstanceLifecycleConfigs">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListNotebookInstanceLifecycleConfigsAsync(const Model::ListNotebookInstanceLifecycleConfigsRequest& request, const ListNotebookInstanceLifecycleConfigsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns a list of the Amazon SageMaker notebook instances in the requester's
* account in an AWS Region. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListNotebookInstances">AWS
* API Reference</a></p>
*/
virtual Model::ListNotebookInstancesOutcome ListNotebookInstances(const Model::ListNotebookInstancesRequest& request) const;
/**
* <p>Returns a list of the Amazon SageMaker notebook instances in the requester's
* account in an AWS Region. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListNotebookInstances">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListNotebookInstancesOutcomeCallable ListNotebookInstancesCallable(const Model::ListNotebookInstancesRequest& request) const;
/**
* <p>Returns a list of the Amazon SageMaker notebook instances in the requester's
* account in an AWS Region. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListNotebookInstances">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListNotebookInstancesAsync(const Model::ListNotebookInstancesRequest& request, const ListNotebookInstancesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists processing jobs that satisfy various filters.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListProcessingJobs">AWS
* API Reference</a></p>
*/
virtual Model::ListProcessingJobsOutcome ListProcessingJobs(const Model::ListProcessingJobsRequest& request) const;
/**
* <p>Lists processing jobs that satisfy various filters.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListProcessingJobs">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListProcessingJobsOutcomeCallable ListProcessingJobsCallable(const Model::ListProcessingJobsRequest& request) const;
/**
* <p>Lists processing jobs that satisfy various filters.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListProcessingJobs">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListProcessingJobsAsync(const Model::ListProcessingJobsRequest& request, const ListProcessingJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets a list of the work teams that you are subscribed to in the AWS
* Marketplace. The list may be empty if no work team satisfies the filter
* specified in the <code>NameContains</code> parameter.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListSubscribedWorkteams">AWS
* API Reference</a></p>
*/
virtual Model::ListSubscribedWorkteamsOutcome ListSubscribedWorkteams(const Model::ListSubscribedWorkteamsRequest& request) const;
/**
* <p>Gets a list of the work teams that you are subscribed to in the AWS
* Marketplace. The list may be empty if no work team satisfies the filter
* specified in the <code>NameContains</code> parameter.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListSubscribedWorkteams">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListSubscribedWorkteamsOutcomeCallable ListSubscribedWorkteamsCallable(const Model::ListSubscribedWorkteamsRequest& request) const;
/**
* <p>Gets a list of the work teams that you are subscribed to in the AWS
* Marketplace. The list may be empty if no work team satisfies the filter
* specified in the <code>NameContains</code> parameter.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListSubscribedWorkteams">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListSubscribedWorkteamsAsync(const Model::ListSubscribedWorkteamsRequest& request, const ListSubscribedWorkteamsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Returns the tags for the specified Amazon SageMaker resource.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTags">AWS
* API Reference</a></p>
*/
virtual Model::ListTagsOutcome ListTags(const Model::ListTagsRequest& request) const;
/**
* <p>Returns the tags for the specified Amazon SageMaker resource.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTags">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListTagsOutcomeCallable ListTagsCallable(const Model::ListTagsRequest& request) const;
/**
* <p>Returns the tags for the specified Amazon SageMaker resource.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTags">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListTagsAsync(const Model::ListTagsRequest& request, const ListTagsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists training jobs.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrainingJobs">AWS
* API Reference</a></p>
*/
virtual Model::ListTrainingJobsOutcome ListTrainingJobs(const Model::ListTrainingJobsRequest& request) const;
/**
* <p>Lists training jobs.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrainingJobs">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListTrainingJobsOutcomeCallable ListTrainingJobsCallable(const Model::ListTrainingJobsRequest& request) const;
/**
* <p>Lists training jobs.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrainingJobs">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListTrainingJobsAsync(const Model::ListTrainingJobsRequest& request, const ListTrainingJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets a list of <a>TrainingJobSummary</a> objects that describe the training
* jobs that a hyperparameter tuning job launched.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrainingJobsForHyperParameterTuningJob">AWS
* API Reference</a></p>
*/
virtual Model::ListTrainingJobsForHyperParameterTuningJobOutcome ListTrainingJobsForHyperParameterTuningJob(const Model::ListTrainingJobsForHyperParameterTuningJobRequest& request) const;
/**
* <p>Gets a list of <a>TrainingJobSummary</a> objects that describe the training
* jobs that a hyperparameter tuning job launched.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrainingJobsForHyperParameterTuningJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListTrainingJobsForHyperParameterTuningJobOutcomeCallable ListTrainingJobsForHyperParameterTuningJobCallable(const Model::ListTrainingJobsForHyperParameterTuningJobRequest& request) const;
/**
* <p>Gets a list of <a>TrainingJobSummary</a> objects that describe the training
* jobs that a hyperparameter tuning job launched.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrainingJobsForHyperParameterTuningJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListTrainingJobsForHyperParameterTuningJobAsync(const Model::ListTrainingJobsForHyperParameterTuningJobRequest& request, const ListTrainingJobsForHyperParameterTuningJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists transform jobs.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTransformJobs">AWS
* API Reference</a></p>
*/
virtual Model::ListTransformJobsOutcome ListTransformJobs(const Model::ListTransformJobsRequest& request) const;
/**
* <p>Lists transform jobs.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTransformJobs">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListTransformJobsOutcomeCallable ListTransformJobsCallable(const Model::ListTransformJobsRequest& request) const;
/**
* <p>Lists transform jobs.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTransformJobs">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListTransformJobsAsync(const Model::ListTransformJobsRequest& request, const ListTransformJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists the trial components in your account. You can sort the list by trial
* component name or creation time. You can filter the list to show only components
* that were created in a specific time range. You can also filter on one of the
* following:</p> <ul> <li> <p> <code>ExperimentName</code> </p> </li> <li> <p>
* <code>SourceArn</code> </p> </li> <li> <p> <code>TrialName</code> </p> </li>
* </ul><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrialComponents">AWS
* API Reference</a></p>
*/
virtual Model::ListTrialComponentsOutcome ListTrialComponents(const Model::ListTrialComponentsRequest& request) const;
/**
* <p>Lists the trial components in your account. You can sort the list by trial
* component name or creation time. You can filter the list to show only components
* that were created in a specific time range. You can also filter on one of the
* following:</p> <ul> <li> <p> <code>ExperimentName</code> </p> </li> <li> <p>
* <code>SourceArn</code> </p> </li> <li> <p> <code>TrialName</code> </p> </li>
* </ul><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrialComponents">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListTrialComponentsOutcomeCallable ListTrialComponentsCallable(const Model::ListTrialComponentsRequest& request) const;
/**
* <p>Lists the trial components in your account. You can sort the list by trial
* component name or creation time. You can filter the list to show only components
* that were created in a specific time range. You can also filter on one of the
* following:</p> <ul> <li> <p> <code>ExperimentName</code> </p> </li> <li> <p>
* <code>SourceArn</code> </p> </li> <li> <p> <code>TrialName</code> </p> </li>
* </ul><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrialComponents">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListTrialComponentsAsync(const Model::ListTrialComponentsRequest& request, const ListTrialComponentsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists the trials in your account. Specify an experiment name to limit the
* list to the trials that are part of that experiment. Specify a trial component
* name to limit the list to the trials that associated with that trial component.
* The list can be filtered to show only trials that were created in a specific
* time range. The list can be sorted by trial name or creation time.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrials">AWS
* API Reference</a></p>
*/
virtual Model::ListTrialsOutcome ListTrials(const Model::ListTrialsRequest& request) const;
/**
* <p>Lists the trials in your account. Specify an experiment name to limit the
* list to the trials that are part of that experiment. Specify a trial component
* name to limit the list to the trials that associated with that trial component.
* The list can be filtered to show only trials that were created in a specific
* time range. The list can be sorted by trial name or creation time.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrials">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListTrialsOutcomeCallable ListTrialsCallable(const Model::ListTrialsRequest& request) const;
/**
* <p>Lists the trials in your account. Specify an experiment name to limit the
* list to the trials that are part of that experiment. Specify a trial component
* name to limit the list to the trials that associated with that trial component.
* The list can be filtered to show only trials that were created in a specific
* time range. The list can be sorted by trial name or creation time.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrials">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListTrialsAsync(const Model::ListTrialsRequest& request, const ListTrialsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Lists user profiles.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListUserProfiles">AWS
* API Reference</a></p>
*/
virtual Model::ListUserProfilesOutcome ListUserProfiles(const Model::ListUserProfilesRequest& request) const;
/**
* <p>Lists user profiles.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListUserProfiles">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListUserProfilesOutcomeCallable ListUserProfilesCallable(const Model::ListUserProfilesRequest& request) const;
/**
* <p>Lists user profiles.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListUserProfiles">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListUserProfilesAsync(const Model::ListUserProfilesRequest& request, const ListUserProfilesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Use this operation to list all private and vendor workforces in an AWS
* Region. Note that you can only have one private workforce per AWS
* Region.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListWorkforces">AWS
* API Reference</a></p>
*/
virtual Model::ListWorkforcesOutcome ListWorkforces(const Model::ListWorkforcesRequest& request) const;
/**
* <p>Use this operation to list all private and vendor workforces in an AWS
* Region. Note that you can only have one private workforce per AWS
* Region.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListWorkforces">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListWorkforcesOutcomeCallable ListWorkforcesCallable(const Model::ListWorkforcesRequest& request) const;
/**
* <p>Use this operation to list all private and vendor workforces in an AWS
* Region. Note that you can only have one private workforce per AWS
* Region.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListWorkforces">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListWorkforcesAsync(const Model::ListWorkforcesRequest& request, const ListWorkforcesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Gets a list of private work teams that you have defined in a region. The list
* may be empty if no work team satisfies the filter specified in the
* <code>NameContains</code> parameter.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListWorkteams">AWS
* API Reference</a></p>
*/
virtual Model::ListWorkteamsOutcome ListWorkteams(const Model::ListWorkteamsRequest& request) const;
/**
* <p>Gets a list of private work teams that you have defined in a region. The list
* may be empty if no work team satisfies the filter specified in the
* <code>NameContains</code> parameter.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListWorkteams">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::ListWorkteamsOutcomeCallable ListWorkteamsCallable(const Model::ListWorkteamsRequest& request) const;
/**
* <p>Gets a list of private work teams that you have defined in a region. The list
* may be empty if no work team satisfies the filter specified in the
* <code>NameContains</code> parameter.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListWorkteams">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void ListWorkteamsAsync(const Model::ListWorkteamsRequest& request, const ListWorkteamsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Renders the UI template so that you can preview the worker's experience.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RenderUiTemplate">AWS
* API Reference</a></p>
*/
virtual Model::RenderUiTemplateOutcome RenderUiTemplate(const Model::RenderUiTemplateRequest& request) const;
/**
* <p>Renders the UI template so that you can preview the worker's experience.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RenderUiTemplate">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::RenderUiTemplateOutcomeCallable RenderUiTemplateCallable(const Model::RenderUiTemplateRequest& request) const;
/**
* <p>Renders the UI template so that you can preview the worker's experience.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RenderUiTemplate">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void RenderUiTemplateAsync(const Model::RenderUiTemplateRequest& request, const RenderUiTemplateResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Finds Amazon SageMaker resources that match a search query. Matching
* resources are returned as a list of <code>SearchRecord</code> objects in the
* response. You can sort the search results by any resource property in a
* ascending or descending order.</p> <p>You can query against the following value
* types: numeric, text, Boolean, and timestamp.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Search">AWS
* API Reference</a></p>
*/
virtual Model::SearchOutcome Search(const Model::SearchRequest& request) const;
/**
* <p>Finds Amazon SageMaker resources that match a search query. Matching
* resources are returned as a list of <code>SearchRecord</code> objects in the
* response. You can sort the search results by any resource property in a
* ascending or descending order.</p> <p>You can query against the following value
* types: numeric, text, Boolean, and timestamp.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Search">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::SearchOutcomeCallable SearchCallable(const Model::SearchRequest& request) const;
/**
* <p>Finds Amazon SageMaker resources that match a search query. Matching
* resources are returned as a list of <code>SearchRecord</code> objects in the
* response. You can sort the search results by any resource property in a
* ascending or descending order.</p> <p>You can query against the following value
* types: numeric, text, Boolean, and timestamp.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Search">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void SearchAsync(const Model::SearchRequest& request, const SearchResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Starts a previously stopped monitoring schedule.</p> <p>New monitoring
* schedules are immediately started after creation.</p> <p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StartMonitoringSchedule">AWS
* API Reference</a></p>
*/
virtual Model::StartMonitoringScheduleOutcome StartMonitoringSchedule(const Model::StartMonitoringScheduleRequest& request) const;
/**
* <p>Starts a previously stopped monitoring schedule.</p> <p>New monitoring
* schedules are immediately started after creation.</p> <p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StartMonitoringSchedule">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StartMonitoringScheduleOutcomeCallable StartMonitoringScheduleCallable(const Model::StartMonitoringScheduleRequest& request) const;
/**
* <p>Starts a previously stopped monitoring schedule.</p> <p>New monitoring
* schedules are immediately started after creation.</p> <p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StartMonitoringSchedule">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StartMonitoringScheduleAsync(const Model::StartMonitoringScheduleRequest& request, const StartMonitoringScheduleResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Launches an ML compute instance with the latest version of the libraries and
* attaches your ML storage volume. After configuring the notebook instance, Amazon
* SageMaker sets the notebook instance status to <code>InService</code>. A
* notebook instance's status must be <code>InService</code> before you can connect
* to your Jupyter notebook. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StartNotebookInstance">AWS
* API Reference</a></p>
*/
virtual Model::StartNotebookInstanceOutcome StartNotebookInstance(const Model::StartNotebookInstanceRequest& request) const;
/**
* <p>Launches an ML compute instance with the latest version of the libraries and
* attaches your ML storage volume. After configuring the notebook instance, Amazon
* SageMaker sets the notebook instance status to <code>InService</code>. A
* notebook instance's status must be <code>InService</code> before you can connect
* to your Jupyter notebook. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StartNotebookInstance">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StartNotebookInstanceOutcomeCallable StartNotebookInstanceCallable(const Model::StartNotebookInstanceRequest& request) const;
/**
* <p>Launches an ML compute instance with the latest version of the libraries and
* attaches your ML storage volume. After configuring the notebook instance, Amazon
* SageMaker sets the notebook instance status to <code>InService</code>. A
* notebook instance's status must be <code>InService</code> before you can connect
* to your Jupyter notebook. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StartNotebookInstance">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StartNotebookInstanceAsync(const Model::StartNotebookInstanceRequest& request, const StartNotebookInstanceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>A method for forcing the termination of a running job.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopAutoMLJob">AWS
* API Reference</a></p>
*/
virtual Model::StopAutoMLJobOutcome StopAutoMLJob(const Model::StopAutoMLJobRequest& request) const;
/**
* <p>A method for forcing the termination of a running job.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopAutoMLJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StopAutoMLJobOutcomeCallable StopAutoMLJobCallable(const Model::StopAutoMLJobRequest& request) const;
/**
* <p>A method for forcing the termination of a running job.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopAutoMLJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StopAutoMLJobAsync(const Model::StopAutoMLJobRequest& request, const StopAutoMLJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Stops a model compilation job.</p> <p> To stop a job, Amazon SageMaker sends
* the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job
* hasn't stopped, it sends the SIGKILL signal.</p> <p>When it receives a
* <code>StopCompilationJob</code> request, Amazon SageMaker changes the
* <a>CompilationJobSummary$CompilationJobStatus</a> of the job to
* <code>Stopping</code>. After Amazon SageMaker stops the job, it sets the
* <a>CompilationJobSummary$CompilationJobStatus</a> to <code>Stopped</code>.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopCompilationJob">AWS
* API Reference</a></p>
*/
virtual Model::StopCompilationJobOutcome StopCompilationJob(const Model::StopCompilationJobRequest& request) const;
/**
* <p>Stops a model compilation job.</p> <p> To stop a job, Amazon SageMaker sends
* the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job
* hasn't stopped, it sends the SIGKILL signal.</p> <p>When it receives a
* <code>StopCompilationJob</code> request, Amazon SageMaker changes the
* <a>CompilationJobSummary$CompilationJobStatus</a> of the job to
* <code>Stopping</code>. After Amazon SageMaker stops the job, it sets the
* <a>CompilationJobSummary$CompilationJobStatus</a> to <code>Stopped</code>.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopCompilationJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StopCompilationJobOutcomeCallable StopCompilationJobCallable(const Model::StopCompilationJobRequest& request) const;
/**
* <p>Stops a model compilation job.</p> <p> To stop a job, Amazon SageMaker sends
* the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job
* hasn't stopped, it sends the SIGKILL signal.</p> <p>When it receives a
* <code>StopCompilationJob</code> request, Amazon SageMaker changes the
* <a>CompilationJobSummary$CompilationJobStatus</a> of the job to
* <code>Stopping</code>. After Amazon SageMaker stops the job, it sets the
* <a>CompilationJobSummary$CompilationJobStatus</a> to <code>Stopped</code>.
* </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopCompilationJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StopCompilationJobAsync(const Model::StopCompilationJobRequest& request, const StopCompilationJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Stops a running hyperparameter tuning job and all running training jobs that
* the tuning job launched.</p> <p>All model artifacts output from the training
* jobs are stored in Amazon Simple Storage Service (Amazon S3). All data that the
* training jobs write to Amazon CloudWatch Logs are still available in CloudWatch.
* After the tuning job moves to the <code>Stopped</code> state, it releases all
* reserved resources for the tuning job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopHyperParameterTuningJob">AWS
* API Reference</a></p>
*/
virtual Model::StopHyperParameterTuningJobOutcome StopHyperParameterTuningJob(const Model::StopHyperParameterTuningJobRequest& request) const;
/**
* <p>Stops a running hyperparameter tuning job and all running training jobs that
* the tuning job launched.</p> <p>All model artifacts output from the training
* jobs are stored in Amazon Simple Storage Service (Amazon S3). All data that the
* training jobs write to Amazon CloudWatch Logs are still available in CloudWatch.
* After the tuning job moves to the <code>Stopped</code> state, it releases all
* reserved resources for the tuning job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopHyperParameterTuningJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StopHyperParameterTuningJobOutcomeCallable StopHyperParameterTuningJobCallable(const Model::StopHyperParameterTuningJobRequest& request) const;
/**
* <p>Stops a running hyperparameter tuning job and all running training jobs that
* the tuning job launched.</p> <p>All model artifacts output from the training
* jobs are stored in Amazon Simple Storage Service (Amazon S3). All data that the
* training jobs write to Amazon CloudWatch Logs are still available in CloudWatch.
* After the tuning job moves to the <code>Stopped</code> state, it releases all
* reserved resources for the tuning job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopHyperParameterTuningJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StopHyperParameterTuningJobAsync(const Model::StopHyperParameterTuningJobRequest& request, const StopHyperParameterTuningJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Stops a running labeling job. A job that is stopped cannot be restarted. Any
* results obtained before the job is stopped are placed in the Amazon S3 output
* bucket.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopLabelingJob">AWS
* API Reference</a></p>
*/
virtual Model::StopLabelingJobOutcome StopLabelingJob(const Model::StopLabelingJobRequest& request) const;
/**
* <p>Stops a running labeling job. A job that is stopped cannot be restarted. Any
* results obtained before the job is stopped are placed in the Amazon S3 output
* bucket.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopLabelingJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StopLabelingJobOutcomeCallable StopLabelingJobCallable(const Model::StopLabelingJobRequest& request) const;
/**
* <p>Stops a running labeling job. A job that is stopped cannot be restarted. Any
* results obtained before the job is stopped are placed in the Amazon S3 output
* bucket.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopLabelingJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StopLabelingJobAsync(const Model::StopLabelingJobRequest& request, const StopLabelingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Stops a previously started monitoring schedule.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopMonitoringSchedule">AWS
* API Reference</a></p>
*/
virtual Model::StopMonitoringScheduleOutcome StopMonitoringSchedule(const Model::StopMonitoringScheduleRequest& request) const;
/**
* <p>Stops a previously started monitoring schedule.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopMonitoringSchedule">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StopMonitoringScheduleOutcomeCallable StopMonitoringScheduleCallable(const Model::StopMonitoringScheduleRequest& request) const;
/**
* <p>Stops a previously started monitoring schedule.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopMonitoringSchedule">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StopMonitoringScheduleAsync(const Model::StopMonitoringScheduleRequest& request, const StopMonitoringScheduleResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Terminates the ML compute instance. Before terminating the instance, Amazon
* SageMaker disconnects the ML storage volume from it. Amazon SageMaker preserves
* the ML storage volume. Amazon SageMaker stops charging you for the ML compute
* instance when you call <code>StopNotebookInstance</code>.</p> <p>To access data
* on the ML storage volume for a notebook instance that has been terminated, call
* the <code>StartNotebookInstance</code> API. <code>StartNotebookInstance</code>
* launches another ML compute instance, configures it, and attaches the preserved
* ML storage volume so you can continue your work. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopNotebookInstance">AWS
* API Reference</a></p>
*/
virtual Model::StopNotebookInstanceOutcome StopNotebookInstance(const Model::StopNotebookInstanceRequest& request) const;
/**
* <p>Terminates the ML compute instance. Before terminating the instance, Amazon
* SageMaker disconnects the ML storage volume from it. Amazon SageMaker preserves
* the ML storage volume. Amazon SageMaker stops charging you for the ML compute
* instance when you call <code>StopNotebookInstance</code>.</p> <p>To access data
* on the ML storage volume for a notebook instance that has been terminated, call
* the <code>StartNotebookInstance</code> API. <code>StartNotebookInstance</code>
* launches another ML compute instance, configures it, and attaches the preserved
* ML storage volume so you can continue your work. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopNotebookInstance">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StopNotebookInstanceOutcomeCallable StopNotebookInstanceCallable(const Model::StopNotebookInstanceRequest& request) const;
/**
* <p>Terminates the ML compute instance. Before terminating the instance, Amazon
* SageMaker disconnects the ML storage volume from it. Amazon SageMaker preserves
* the ML storage volume. Amazon SageMaker stops charging you for the ML compute
* instance when you call <code>StopNotebookInstance</code>.</p> <p>To access data
* on the ML storage volume for a notebook instance that has been terminated, call
* the <code>StartNotebookInstance</code> API. <code>StartNotebookInstance</code>
* launches another ML compute instance, configures it, and attaches the preserved
* ML storage volume so you can continue your work. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopNotebookInstance">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StopNotebookInstanceAsync(const Model::StopNotebookInstanceRequest& request, const StopNotebookInstanceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Stops a processing job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopProcessingJob">AWS
* API Reference</a></p>
*/
virtual Model::StopProcessingJobOutcome StopProcessingJob(const Model::StopProcessingJobRequest& request) const;
/**
* <p>Stops a processing job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopProcessingJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StopProcessingJobOutcomeCallable StopProcessingJobCallable(const Model::StopProcessingJobRequest& request) const;
/**
* <p>Stops a processing job.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopProcessingJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StopProcessingJobAsync(const Model::StopProcessingJobRequest& request, const StopProcessingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Stops a training job. To stop a job, Amazon SageMaker sends the algorithm the
* <code>SIGTERM</code> signal, which delays job termination for 120 seconds.
* Algorithms might use this 120-second window to save the model artifacts, so the
* results of the training is not lost. </p> <p>When it receives a
* <code>StopTrainingJob</code> request, Amazon SageMaker changes the status of the
* job to <code>Stopping</code>. After Amazon SageMaker stops the job, it sets the
* status to <code>Stopped</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopTrainingJob">AWS
* API Reference</a></p>
*/
virtual Model::StopTrainingJobOutcome StopTrainingJob(const Model::StopTrainingJobRequest& request) const;
/**
* <p>Stops a training job. To stop a job, Amazon SageMaker sends the algorithm the
* <code>SIGTERM</code> signal, which delays job termination for 120 seconds.
* Algorithms might use this 120-second window to save the model artifacts, so the
* results of the training is not lost. </p> <p>When it receives a
* <code>StopTrainingJob</code> request, Amazon SageMaker changes the status of the
* job to <code>Stopping</code>. After Amazon SageMaker stops the job, it sets the
* status to <code>Stopped</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopTrainingJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StopTrainingJobOutcomeCallable StopTrainingJobCallable(const Model::StopTrainingJobRequest& request) const;
/**
* <p>Stops a training job. To stop a job, Amazon SageMaker sends the algorithm the
* <code>SIGTERM</code> signal, which delays job termination for 120 seconds.
* Algorithms might use this 120-second window to save the model artifacts, so the
* results of the training is not lost. </p> <p>When it receives a
* <code>StopTrainingJob</code> request, Amazon SageMaker changes the status of the
* job to <code>Stopping</code>. After Amazon SageMaker stops the job, it sets the
* status to <code>Stopped</code>.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopTrainingJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StopTrainingJobAsync(const Model::StopTrainingJobRequest& request, const StopTrainingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Stops a transform job.</p> <p>When Amazon SageMaker receives a
* <code>StopTransformJob</code> request, the status of the job changes to
* <code>Stopping</code>. After Amazon SageMaker stops the job, the status is set
* to <code>Stopped</code>. When you stop a transform job before it is completed,
* Amazon SageMaker doesn't store the job's output in Amazon S3.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopTransformJob">AWS
* API Reference</a></p>
*/
virtual Model::StopTransformJobOutcome StopTransformJob(const Model::StopTransformJobRequest& request) const;
/**
* <p>Stops a transform job.</p> <p>When Amazon SageMaker receives a
* <code>StopTransformJob</code> request, the status of the job changes to
* <code>Stopping</code>. After Amazon SageMaker stops the job, the status is set
* to <code>Stopped</code>. When you stop a transform job before it is completed,
* Amazon SageMaker doesn't store the job's output in Amazon S3.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopTransformJob">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::StopTransformJobOutcomeCallable StopTransformJobCallable(const Model::StopTransformJobRequest& request) const;
/**
* <p>Stops a transform job.</p> <p>When Amazon SageMaker receives a
* <code>StopTransformJob</code> request, the status of the job changes to
* <code>Stopping</code>. After Amazon SageMaker stops the job, the status is set
* to <code>Stopped</code>. When you stop a transform job before it is completed,
* Amazon SageMaker doesn't store the job's output in Amazon S3.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopTransformJob">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void StopTransformJobAsync(const Model::StopTransformJobRequest& request, const StopTransformJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Updates the specified Git repository with the specified values.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateCodeRepository">AWS
* API Reference</a></p>
*/
virtual Model::UpdateCodeRepositoryOutcome UpdateCodeRepository(const Model::UpdateCodeRepositoryRequest& request) const;
/**
* <p>Updates the specified Git repository with the specified values.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateCodeRepository">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::UpdateCodeRepositoryOutcomeCallable UpdateCodeRepositoryCallable(const Model::UpdateCodeRepositoryRequest& request) const;
/**
* <p>Updates the specified Git repository with the specified values.</p><p><h3>See
* Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateCodeRepository">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void UpdateCodeRepositoryAsync(const Model::UpdateCodeRepositoryRequest& request, const UpdateCodeRepositoryResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Updates the default settings for new user profiles in the
* domain.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateDomain">AWS
* API Reference</a></p>
*/
virtual Model::UpdateDomainOutcome UpdateDomain(const Model::UpdateDomainRequest& request) const;
/**
* <p>Updates the default settings for new user profiles in the
* domain.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateDomain">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::UpdateDomainOutcomeCallable UpdateDomainCallable(const Model::UpdateDomainRequest& request) const;
/**
* <p>Updates the default settings for new user profiles in the
* domain.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateDomain">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void UpdateDomainAsync(const Model::UpdateDomainRequest& request, const UpdateDomainResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Deploys the new <code>EndpointConfig</code> specified in the request,
* switches to using newly created endpoint, and then deletes resources provisioned
* for the endpoint using the previous <code>EndpointConfig</code> (there is no
* availability loss). </p> <p>When Amazon SageMaker receives the request, it sets
* the endpoint status to <code>Updating</code>. After updating the endpoint, it
* sets the status to <code>InService</code>. To check the status of an endpoint,
* use the <a>DescribeEndpoint</a> API. </p> <p>You must not delete an
* <code>EndpointConfig</code> in use by an endpoint that is live or while the
* <code>UpdateEndpoint</code> or <code>CreateEndpoint</code> operations are being
* performed on the endpoint. To update an endpoint, you must create a new
* <code>EndpointConfig</code>.</p> <p>If you delete the
* <code>EndpointConfig</code> 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.</p>
* <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateEndpoint">AWS
* API Reference</a></p>
*/
virtual Model::UpdateEndpointOutcome UpdateEndpoint(const Model::UpdateEndpointRequest& request) const;
/**
* <p>Deploys the new <code>EndpointConfig</code> specified in the request,
* switches to using newly created endpoint, and then deletes resources provisioned
* for the endpoint using the previous <code>EndpointConfig</code> (there is no
* availability loss). </p> <p>When Amazon SageMaker receives the request, it sets
* the endpoint status to <code>Updating</code>. After updating the endpoint, it
* sets the status to <code>InService</code>. To check the status of an endpoint,
* use the <a>DescribeEndpoint</a> API. </p> <p>You must not delete an
* <code>EndpointConfig</code> in use by an endpoint that is live or while the
* <code>UpdateEndpoint</code> or <code>CreateEndpoint</code> operations are being
* performed on the endpoint. To update an endpoint, you must create a new
* <code>EndpointConfig</code>.</p> <p>If you delete the
* <code>EndpointConfig</code> 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.</p>
* <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateEndpoint">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::UpdateEndpointOutcomeCallable UpdateEndpointCallable(const Model::UpdateEndpointRequest& request) const;
/**
* <p>Deploys the new <code>EndpointConfig</code> specified in the request,
* switches to using newly created endpoint, and then deletes resources provisioned
* for the endpoint using the previous <code>EndpointConfig</code> (there is no
* availability loss). </p> <p>When Amazon SageMaker receives the request, it sets
* the endpoint status to <code>Updating</code>. After updating the endpoint, it
* sets the status to <code>InService</code>. To check the status of an endpoint,
* use the <a>DescribeEndpoint</a> API. </p> <p>You must not delete an
* <code>EndpointConfig</code> in use by an endpoint that is live or while the
* <code>UpdateEndpoint</code> or <code>CreateEndpoint</code> operations are being
* performed on the endpoint. To update an endpoint, you must create a new
* <code>EndpointConfig</code>.</p> <p>If you delete the
* <code>EndpointConfig</code> 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.</p>
* <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateEndpoint">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void UpdateEndpointAsync(const Model::UpdateEndpointRequest& request, const UpdateEndpointResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Updates variant weight of one or more variants associated with an existing
* endpoint, or capacity of one variant associated with an existing endpoint. When
* it receives the request, Amazon SageMaker sets the endpoint status to
* <code>Updating</code>. After updating the endpoint, it sets the status to
* <code>InService</code>. To check the status of an endpoint, use the
* <a>DescribeEndpoint</a> API. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateEndpointWeightsAndCapacities">AWS
* API Reference</a></p>
*/
virtual Model::UpdateEndpointWeightsAndCapacitiesOutcome UpdateEndpointWeightsAndCapacities(const Model::UpdateEndpointWeightsAndCapacitiesRequest& request) const;
/**
* <p>Updates variant weight of one or more variants associated with an existing
* endpoint, or capacity of one variant associated with an existing endpoint. When
* it receives the request, Amazon SageMaker sets the endpoint status to
* <code>Updating</code>. After updating the endpoint, it sets the status to
* <code>InService</code>. To check the status of an endpoint, use the
* <a>DescribeEndpoint</a> API. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateEndpointWeightsAndCapacities">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::UpdateEndpointWeightsAndCapacitiesOutcomeCallable UpdateEndpointWeightsAndCapacitiesCallable(const Model::UpdateEndpointWeightsAndCapacitiesRequest& request) const;
/**
* <p>Updates variant weight of one or more variants associated with an existing
* endpoint, or capacity of one variant associated with an existing endpoint. When
* it receives the request, Amazon SageMaker sets the endpoint status to
* <code>Updating</code>. After updating the endpoint, it sets the status to
* <code>InService</code>. To check the status of an endpoint, use the
* <a>DescribeEndpoint</a> API. </p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateEndpointWeightsAndCapacities">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void UpdateEndpointWeightsAndCapacitiesAsync(const Model::UpdateEndpointWeightsAndCapacitiesRequest& request, const UpdateEndpointWeightsAndCapacitiesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Adds, updates, or removes the description of an experiment. Updates the
* display name of an experiment.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateExperiment">AWS
* API Reference</a></p>
*/
virtual Model::UpdateExperimentOutcome UpdateExperiment(const Model::UpdateExperimentRequest& request) const;
/**
* <p>Adds, updates, or removes the description of an experiment. Updates the
* display name of an experiment.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateExperiment">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::UpdateExperimentOutcomeCallable UpdateExperimentCallable(const Model::UpdateExperimentRequest& request) const;
/**
* <p>Adds, updates, or removes the description of an experiment. Updates the
* display name of an experiment.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateExperiment">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void UpdateExperimentAsync(const Model::UpdateExperimentRequest& request, const UpdateExperimentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Updates a previously created schedule.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateMonitoringSchedule">AWS
* API Reference</a></p>
*/
virtual Model::UpdateMonitoringScheduleOutcome UpdateMonitoringSchedule(const Model::UpdateMonitoringScheduleRequest& request) const;
/**
* <p>Updates a previously created schedule.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateMonitoringSchedule">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::UpdateMonitoringScheduleOutcomeCallable UpdateMonitoringScheduleCallable(const Model::UpdateMonitoringScheduleRequest& request) const;
/**
* <p>Updates a previously created schedule.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateMonitoringSchedule">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void UpdateMonitoringScheduleAsync(const Model::UpdateMonitoringScheduleRequest& request, const UpdateMonitoringScheduleResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Updates a notebook instance. NotebookInstance updates include upgrading or
* downgrading the ML compute instance used for your notebook instance to
* accommodate changes in your workload requirements.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateNotebookInstance">AWS
* API Reference</a></p>
*/
virtual Model::UpdateNotebookInstanceOutcome UpdateNotebookInstance(const Model::UpdateNotebookInstanceRequest& request) const;
/**
* <p>Updates a notebook instance. NotebookInstance updates include upgrading or
* downgrading the ML compute instance used for your notebook instance to
* accommodate changes in your workload requirements.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateNotebookInstance">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::UpdateNotebookInstanceOutcomeCallable UpdateNotebookInstanceCallable(const Model::UpdateNotebookInstanceRequest& request) const;
/**
* <p>Updates a notebook instance. NotebookInstance updates include upgrading or
* downgrading the ML compute instance used for your notebook instance to
* accommodate changes in your workload requirements.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateNotebookInstance">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void UpdateNotebookInstanceAsync(const Model::UpdateNotebookInstanceRequest& request, const UpdateNotebookInstanceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Updates a notebook instance lifecycle configuration created with the
* <a>CreateNotebookInstanceLifecycleConfig</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateNotebookInstanceLifecycleConfig">AWS
* API Reference</a></p>
*/
virtual Model::UpdateNotebookInstanceLifecycleConfigOutcome UpdateNotebookInstanceLifecycleConfig(const Model::UpdateNotebookInstanceLifecycleConfigRequest& request) const;
/**
* <p>Updates a notebook instance lifecycle configuration created with the
* <a>CreateNotebookInstanceLifecycleConfig</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateNotebookInstanceLifecycleConfig">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::UpdateNotebookInstanceLifecycleConfigOutcomeCallable UpdateNotebookInstanceLifecycleConfigCallable(const Model::UpdateNotebookInstanceLifecycleConfigRequest& request) const;
/**
* <p>Updates a notebook instance lifecycle configuration created with the
* <a>CreateNotebookInstanceLifecycleConfig</a> API.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateNotebookInstanceLifecycleConfig">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void UpdateNotebookInstanceLifecycleConfigAsync(const Model::UpdateNotebookInstanceLifecycleConfigRequest& request, const UpdateNotebookInstanceLifecycleConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Updates the display name of a trial.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateTrial">AWS
* API Reference</a></p>
*/
virtual Model::UpdateTrialOutcome UpdateTrial(const Model::UpdateTrialRequest& request) const;
/**
* <p>Updates the display name of a trial.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateTrial">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::UpdateTrialOutcomeCallable UpdateTrialCallable(const Model::UpdateTrialRequest& request) const;
/**
* <p>Updates the display name of a trial.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateTrial">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void UpdateTrialAsync(const Model::UpdateTrialRequest& request, const UpdateTrialResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Updates one or more properties of a trial component.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateTrialComponent">AWS
* API Reference</a></p>
*/
virtual Model::UpdateTrialComponentOutcome UpdateTrialComponent(const Model::UpdateTrialComponentRequest& request) const;
/**
* <p>Updates one or more properties of a trial component.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateTrialComponent">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::UpdateTrialComponentOutcomeCallable UpdateTrialComponentCallable(const Model::UpdateTrialComponentRequest& request) const;
/**
* <p>Updates one or more properties of a trial component.</p><p><h3>See Also:</h3>
* <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateTrialComponent">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void UpdateTrialComponentAsync(const Model::UpdateTrialComponentRequest& request, const UpdateTrialComponentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Updates a user profile.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateUserProfile">AWS
* API Reference</a></p>
*/
virtual Model::UpdateUserProfileOutcome UpdateUserProfile(const Model::UpdateUserProfileRequest& request) const;
/**
* <p>Updates a user profile.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateUserProfile">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::UpdateUserProfileOutcomeCallable UpdateUserProfileCallable(const Model::UpdateUserProfileRequest& request) const;
/**
* <p>Updates a user profile.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateUserProfile">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void UpdateUserProfileAsync(const Model::UpdateUserProfileRequest& request, const UpdateUserProfileResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Use this operation to update your workforce. You can use this operation to
* require that workers use specific IP addresses to work on tasks and to update
* your OpenID Connect (OIDC) Identity Provider (IdP) workforce configuration.</p>
* <p> Use <code>SourceIpConfig</code> to restrict worker access to tasks to a
* specific range of IP addresses. You specify allowed IP addresses by creating a
* list of up to ten <a
* href="https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html">CIDRs</a>.
* By default, a workforce isn't restricted to specific IP addresses. If you
* specify a range of IP addresses, workers who attempt to access tasks using any
* IP address outside the specified range are denied and get a <code>Not
* Found</code> error message on the worker portal.</p> <p>Use
* <code>OidcConfig</code> to update the configuration of a workforce created using
* your own OIDC IdP. </p> <p>You can only update your OIDC IdP
* configuration when there are no work teams associated with your workforce. You
* can delete work teams using the operation.</p> <p>After restricting
* access to a range of IP addresses or updating your OIDC IdP configuration with
* this operation, you can view details about your update workforce using the
* operation.</p> <p>This operation only applies to private
* workforces.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateWorkforce">AWS
* API Reference</a></p>
*/
virtual Model::UpdateWorkforceOutcome UpdateWorkforce(const Model::UpdateWorkforceRequest& request) const;
/**
* <p>Use this operation to update your workforce. You can use this operation to
* require that workers use specific IP addresses to work on tasks and to update
* your OpenID Connect (OIDC) Identity Provider (IdP) workforce configuration.</p>
* <p> Use <code>SourceIpConfig</code> to restrict worker access to tasks to a
* specific range of IP addresses. You specify allowed IP addresses by creating a
* list of up to ten <a
* href="https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html">CIDRs</a>.
* By default, a workforce isn't restricted to specific IP addresses. If you
* specify a range of IP addresses, workers who attempt to access tasks using any
* IP address outside the specified range are denied and get a <code>Not
* Found</code> error message on the worker portal.</p> <p>Use
* <code>OidcConfig</code> to update the configuration of a workforce created using
* your own OIDC IdP. </p> <p>You can only update your OIDC IdP
* configuration when there are no work teams associated with your workforce. You
* can delete work teams using the operation.</p> <p>After restricting
* access to a range of IP addresses or updating your OIDC IdP configuration with
* this operation, you can view details about your update workforce using the
* operation.</p> <p>This operation only applies to private
* workforces.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateWorkforce">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::UpdateWorkforceOutcomeCallable UpdateWorkforceCallable(const Model::UpdateWorkforceRequest& request) const;
/**
* <p>Use this operation to update your workforce. You can use this operation to
* require that workers use specific IP addresses to work on tasks and to update
* your OpenID Connect (OIDC) Identity Provider (IdP) workforce configuration.</p>
* <p> Use <code>SourceIpConfig</code> to restrict worker access to tasks to a
* specific range of IP addresses. You specify allowed IP addresses by creating a
* list of up to ten <a
* href="https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html">CIDRs</a>.
* By default, a workforce isn't restricted to specific IP addresses. If you
* specify a range of IP addresses, workers who attempt to access tasks using any
* IP address outside the specified range are denied and get a <code>Not
* Found</code> error message on the worker portal.</p> <p>Use
* <code>OidcConfig</code> to update the configuration of a workforce created using
* your own OIDC IdP. </p> <p>You can only update your OIDC IdP
* configuration when there are no work teams associated with your workforce. You
* can delete work teams using the operation.</p> <p>After restricting
* access to a range of IP addresses or updating your OIDC IdP configuration with
* this operation, you can view details about your update workforce using the
* operation.</p> <p>This operation only applies to private
* workforces.</p> <p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateWorkforce">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
virtual void UpdateWorkforceAsync(const Model::UpdateWorkforceRequest& request, const UpdateWorkforceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context = nullptr) const;
/**
* <p>Updates an existing work team with new member definitions or
* description.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateWorkteam">AWS
* API Reference</a></p>
*/
virtual Model::UpdateWorkteamOutcome UpdateWorkteam(const Model::UpdateWorkteamRequest& request) const;
/**
* <p>Updates an existing work team with new member definitions or
* description.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateWorkteam">AWS
* API Reference</a></p>
*
* returns a future to the operation so that it can be executed in parallel to other requests.
*/
virtual Model::UpdateWorkteamOutcomeCallable UpdateWorkteamCallable(const Model::UpdateWorkteamRequest& request) const;
/**
* <p>Updates an existing work team with new member definitions or
* description.</p><p><h3>See Also:</h3> <a
* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateWorkteam">AWS
* API Reference</a></p>
*
* Queues the request into a thread executor and triggers associated callback when operation has finished.
*/
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);
private:
void init(const Aws::Client::ClientConfiguration& clientConfiguration);
void AddTagsAsyncHelper(const Model::AddTagsRequest& request, const AddTagsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void AssociateTrialComponentAsyncHelper(const Model::AssociateTrialComponentRequest& request, const AssociateTrialComponentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateAlgorithmAsyncHelper(const Model::CreateAlgorithmRequest& request, const CreateAlgorithmResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateAppAsyncHelper(const Model::CreateAppRequest& request, const CreateAppResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateAutoMLJobAsyncHelper(const Model::CreateAutoMLJobRequest& request, const CreateAutoMLJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateCodeRepositoryAsyncHelper(const Model::CreateCodeRepositoryRequest& request, const CreateCodeRepositoryResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateCompilationJobAsyncHelper(const Model::CreateCompilationJobRequest& request, const CreateCompilationJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateDomainAsyncHelper(const Model::CreateDomainRequest& request, const CreateDomainResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateEndpointAsyncHelper(const Model::CreateEndpointRequest& request, const CreateEndpointResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateEndpointConfigAsyncHelper(const Model::CreateEndpointConfigRequest& request, const CreateEndpointConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateExperimentAsyncHelper(const Model::CreateExperimentRequest& request, const CreateExperimentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateFlowDefinitionAsyncHelper(const Model::CreateFlowDefinitionRequest& request, const CreateFlowDefinitionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateHumanTaskUiAsyncHelper(const Model::CreateHumanTaskUiRequest& request, const CreateHumanTaskUiResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateHyperParameterTuningJobAsyncHelper(const Model::CreateHyperParameterTuningJobRequest& request, const CreateHyperParameterTuningJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateLabelingJobAsyncHelper(const Model::CreateLabelingJobRequest& request, const CreateLabelingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateModelAsyncHelper(const Model::CreateModelRequest& request, const CreateModelResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateModelPackageAsyncHelper(const Model::CreateModelPackageRequest& request, const CreateModelPackageResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateMonitoringScheduleAsyncHelper(const Model::CreateMonitoringScheduleRequest& request, const CreateMonitoringScheduleResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateNotebookInstanceAsyncHelper(const Model::CreateNotebookInstanceRequest& request, const CreateNotebookInstanceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateNotebookInstanceLifecycleConfigAsyncHelper(const Model::CreateNotebookInstanceLifecycleConfigRequest& request, const CreateNotebookInstanceLifecycleConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreatePresignedDomainUrlAsyncHelper(const Model::CreatePresignedDomainUrlRequest& request, const CreatePresignedDomainUrlResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreatePresignedNotebookInstanceUrlAsyncHelper(const Model::CreatePresignedNotebookInstanceUrlRequest& request, const CreatePresignedNotebookInstanceUrlResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateProcessingJobAsyncHelper(const Model::CreateProcessingJobRequest& request, const CreateProcessingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateTrainingJobAsyncHelper(const Model::CreateTrainingJobRequest& request, const CreateTrainingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateTransformJobAsyncHelper(const Model::CreateTransformJobRequest& request, const CreateTransformJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateTrialAsyncHelper(const Model::CreateTrialRequest& request, const CreateTrialResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateTrialComponentAsyncHelper(const Model::CreateTrialComponentRequest& request, const CreateTrialComponentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateUserProfileAsyncHelper(const Model::CreateUserProfileRequest& request, const CreateUserProfileResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateWorkforceAsyncHelper(const Model::CreateWorkforceRequest& request, const CreateWorkforceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void CreateWorkteamAsyncHelper(const Model::CreateWorkteamRequest& request, const CreateWorkteamResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteAlgorithmAsyncHelper(const Model::DeleteAlgorithmRequest& request, const DeleteAlgorithmResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteAppAsyncHelper(const Model::DeleteAppRequest& request, const DeleteAppResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteCodeRepositoryAsyncHelper(const Model::DeleteCodeRepositoryRequest& request, const DeleteCodeRepositoryResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteDomainAsyncHelper(const Model::DeleteDomainRequest& request, const DeleteDomainResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteEndpointAsyncHelper(const Model::DeleteEndpointRequest& request, const DeleteEndpointResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteEndpointConfigAsyncHelper(const Model::DeleteEndpointConfigRequest& request, const DeleteEndpointConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteExperimentAsyncHelper(const Model::DeleteExperimentRequest& request, const DeleteExperimentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteFlowDefinitionAsyncHelper(const Model::DeleteFlowDefinitionRequest& request, const DeleteFlowDefinitionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteHumanTaskUiAsyncHelper(const Model::DeleteHumanTaskUiRequest& request, const DeleteHumanTaskUiResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteModelAsyncHelper(const Model::DeleteModelRequest& request, const DeleteModelResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteModelPackageAsyncHelper(const Model::DeleteModelPackageRequest& request, const DeleteModelPackageResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteMonitoringScheduleAsyncHelper(const Model::DeleteMonitoringScheduleRequest& request, const DeleteMonitoringScheduleResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteNotebookInstanceAsyncHelper(const Model::DeleteNotebookInstanceRequest& request, const DeleteNotebookInstanceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteNotebookInstanceLifecycleConfigAsyncHelper(const Model::DeleteNotebookInstanceLifecycleConfigRequest& request, const DeleteNotebookInstanceLifecycleConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteTagsAsyncHelper(const Model::DeleteTagsRequest& request, const DeleteTagsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteTrialAsyncHelper(const Model::DeleteTrialRequest& request, const DeleteTrialResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteTrialComponentAsyncHelper(const Model::DeleteTrialComponentRequest& request, const DeleteTrialComponentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteUserProfileAsyncHelper(const Model::DeleteUserProfileRequest& request, const DeleteUserProfileResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteWorkforceAsyncHelper(const Model::DeleteWorkforceRequest& request, const DeleteWorkforceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DeleteWorkteamAsyncHelper(const Model::DeleteWorkteamRequest& request, const DeleteWorkteamResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeAlgorithmAsyncHelper(const Model::DescribeAlgorithmRequest& request, const DescribeAlgorithmResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeAppAsyncHelper(const Model::DescribeAppRequest& request, const DescribeAppResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeAutoMLJobAsyncHelper(const Model::DescribeAutoMLJobRequest& request, const DescribeAutoMLJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeCodeRepositoryAsyncHelper(const Model::DescribeCodeRepositoryRequest& request, const DescribeCodeRepositoryResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeCompilationJobAsyncHelper(const Model::DescribeCompilationJobRequest& request, const DescribeCompilationJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeDomainAsyncHelper(const Model::DescribeDomainRequest& request, const DescribeDomainResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeEndpointAsyncHelper(const Model::DescribeEndpointRequest& request, const DescribeEndpointResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeEndpointConfigAsyncHelper(const Model::DescribeEndpointConfigRequest& request, const DescribeEndpointConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeExperimentAsyncHelper(const Model::DescribeExperimentRequest& request, const DescribeExperimentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeFlowDefinitionAsyncHelper(const Model::DescribeFlowDefinitionRequest& request, const DescribeFlowDefinitionResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeHumanTaskUiAsyncHelper(const Model::DescribeHumanTaskUiRequest& request, const DescribeHumanTaskUiResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeHyperParameterTuningJobAsyncHelper(const Model::DescribeHyperParameterTuningJobRequest& request, const DescribeHyperParameterTuningJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeLabelingJobAsyncHelper(const Model::DescribeLabelingJobRequest& request, const DescribeLabelingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeModelAsyncHelper(const Model::DescribeModelRequest& request, const DescribeModelResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeModelPackageAsyncHelper(const Model::DescribeModelPackageRequest& request, const DescribeModelPackageResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeMonitoringScheduleAsyncHelper(const Model::DescribeMonitoringScheduleRequest& request, const DescribeMonitoringScheduleResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeNotebookInstanceAsyncHelper(const Model::DescribeNotebookInstanceRequest& request, const DescribeNotebookInstanceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeNotebookInstanceLifecycleConfigAsyncHelper(const Model::DescribeNotebookInstanceLifecycleConfigRequest& request, const DescribeNotebookInstanceLifecycleConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeProcessingJobAsyncHelper(const Model::DescribeProcessingJobRequest& request, const DescribeProcessingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeSubscribedWorkteamAsyncHelper(const Model::DescribeSubscribedWorkteamRequest& request, const DescribeSubscribedWorkteamResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeTrainingJobAsyncHelper(const Model::DescribeTrainingJobRequest& request, const DescribeTrainingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeTransformJobAsyncHelper(const Model::DescribeTransformJobRequest& request, const DescribeTransformJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeTrialAsyncHelper(const Model::DescribeTrialRequest& request, const DescribeTrialResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeTrialComponentAsyncHelper(const Model::DescribeTrialComponentRequest& request, const DescribeTrialComponentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeUserProfileAsyncHelper(const Model::DescribeUserProfileRequest& request, const DescribeUserProfileResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeWorkforceAsyncHelper(const Model::DescribeWorkforceRequest& request, const DescribeWorkforceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DescribeWorkteamAsyncHelper(const Model::DescribeWorkteamRequest& request, const DescribeWorkteamResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void DisassociateTrialComponentAsyncHelper(const Model::DisassociateTrialComponentRequest& request, const DisassociateTrialComponentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void GetSearchSuggestionsAsyncHelper(const Model::GetSearchSuggestionsRequest& request, const GetSearchSuggestionsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListAlgorithmsAsyncHelper(const Model::ListAlgorithmsRequest& request, const ListAlgorithmsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListAppsAsyncHelper(const Model::ListAppsRequest& request, const ListAppsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListAutoMLJobsAsyncHelper(const Model::ListAutoMLJobsRequest& request, const ListAutoMLJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListCandidatesForAutoMLJobAsyncHelper(const Model::ListCandidatesForAutoMLJobRequest& request, const ListCandidatesForAutoMLJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListCodeRepositoriesAsyncHelper(const Model::ListCodeRepositoriesRequest& request, const ListCodeRepositoriesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListCompilationJobsAsyncHelper(const Model::ListCompilationJobsRequest& request, const ListCompilationJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListDomainsAsyncHelper(const Model::ListDomainsRequest& request, const ListDomainsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListEndpointConfigsAsyncHelper(const Model::ListEndpointConfigsRequest& request, const ListEndpointConfigsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListEndpointsAsyncHelper(const Model::ListEndpointsRequest& request, const ListEndpointsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListExperimentsAsyncHelper(const Model::ListExperimentsRequest& request, const ListExperimentsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListFlowDefinitionsAsyncHelper(const Model::ListFlowDefinitionsRequest& request, const ListFlowDefinitionsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListHumanTaskUisAsyncHelper(const Model::ListHumanTaskUisRequest& request, const ListHumanTaskUisResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListHyperParameterTuningJobsAsyncHelper(const Model::ListHyperParameterTuningJobsRequest& request, const ListHyperParameterTuningJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListLabelingJobsAsyncHelper(const Model::ListLabelingJobsRequest& request, const ListLabelingJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListLabelingJobsForWorkteamAsyncHelper(const Model::ListLabelingJobsForWorkteamRequest& request, const ListLabelingJobsForWorkteamResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListModelPackagesAsyncHelper(const Model::ListModelPackagesRequest& request, const ListModelPackagesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListModelsAsyncHelper(const Model::ListModelsRequest& request, const ListModelsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListMonitoringExecutionsAsyncHelper(const Model::ListMonitoringExecutionsRequest& request, const ListMonitoringExecutionsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListMonitoringSchedulesAsyncHelper(const Model::ListMonitoringSchedulesRequest& request, const ListMonitoringSchedulesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListNotebookInstanceLifecycleConfigsAsyncHelper(const Model::ListNotebookInstanceLifecycleConfigsRequest& request, const ListNotebookInstanceLifecycleConfigsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListNotebookInstancesAsyncHelper(const Model::ListNotebookInstancesRequest& request, const ListNotebookInstancesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListProcessingJobsAsyncHelper(const Model::ListProcessingJobsRequest& request, const ListProcessingJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListSubscribedWorkteamsAsyncHelper(const Model::ListSubscribedWorkteamsRequest& request, const ListSubscribedWorkteamsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListTagsAsyncHelper(const Model::ListTagsRequest& request, const ListTagsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListTrainingJobsAsyncHelper(const Model::ListTrainingJobsRequest& request, const ListTrainingJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListTrainingJobsForHyperParameterTuningJobAsyncHelper(const Model::ListTrainingJobsForHyperParameterTuningJobRequest& request, const ListTrainingJobsForHyperParameterTuningJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListTransformJobsAsyncHelper(const Model::ListTransformJobsRequest& request, const ListTransformJobsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListTrialComponentsAsyncHelper(const Model::ListTrialComponentsRequest& request, const ListTrialComponentsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListTrialsAsyncHelper(const Model::ListTrialsRequest& request, const ListTrialsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListUserProfilesAsyncHelper(const Model::ListUserProfilesRequest& request, const ListUserProfilesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListWorkforcesAsyncHelper(const Model::ListWorkforcesRequest& request, const ListWorkforcesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void ListWorkteamsAsyncHelper(const Model::ListWorkteamsRequest& request, const ListWorkteamsResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void RenderUiTemplateAsyncHelper(const Model::RenderUiTemplateRequest& request, const RenderUiTemplateResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void SearchAsyncHelper(const Model::SearchRequest& request, const SearchResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StartMonitoringScheduleAsyncHelper(const Model::StartMonitoringScheduleRequest& request, const StartMonitoringScheduleResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StartNotebookInstanceAsyncHelper(const Model::StartNotebookInstanceRequest& request, const StartNotebookInstanceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StopAutoMLJobAsyncHelper(const Model::StopAutoMLJobRequest& request, const StopAutoMLJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StopCompilationJobAsyncHelper(const Model::StopCompilationJobRequest& request, const StopCompilationJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StopHyperParameterTuningJobAsyncHelper(const Model::StopHyperParameterTuningJobRequest& request, const StopHyperParameterTuningJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StopLabelingJobAsyncHelper(const Model::StopLabelingJobRequest& request, const StopLabelingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StopMonitoringScheduleAsyncHelper(const Model::StopMonitoringScheduleRequest& request, const StopMonitoringScheduleResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StopNotebookInstanceAsyncHelper(const Model::StopNotebookInstanceRequest& request, const StopNotebookInstanceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StopProcessingJobAsyncHelper(const Model::StopProcessingJobRequest& request, const StopProcessingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StopTrainingJobAsyncHelper(const Model::StopTrainingJobRequest& request, const StopTrainingJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void StopTransformJobAsyncHelper(const Model::StopTransformJobRequest& request, const StopTransformJobResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void UpdateCodeRepositoryAsyncHelper(const Model::UpdateCodeRepositoryRequest& request, const UpdateCodeRepositoryResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void UpdateDomainAsyncHelper(const Model::UpdateDomainRequest& request, const UpdateDomainResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void UpdateEndpointAsyncHelper(const Model::UpdateEndpointRequest& request, const UpdateEndpointResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void UpdateEndpointWeightsAndCapacitiesAsyncHelper(const Model::UpdateEndpointWeightsAndCapacitiesRequest& request, const UpdateEndpointWeightsAndCapacitiesResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void UpdateExperimentAsyncHelper(const Model::UpdateExperimentRequest& request, const UpdateExperimentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void UpdateMonitoringScheduleAsyncHelper(const Model::UpdateMonitoringScheduleRequest& request, const UpdateMonitoringScheduleResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void UpdateNotebookInstanceAsyncHelper(const Model::UpdateNotebookInstanceRequest& request, const UpdateNotebookInstanceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void UpdateNotebookInstanceLifecycleConfigAsyncHelper(const Model::UpdateNotebookInstanceLifecycleConfigRequest& request, const UpdateNotebookInstanceLifecycleConfigResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void UpdateTrialAsyncHelper(const Model::UpdateTrialRequest& request, const UpdateTrialResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void UpdateTrialComponentAsyncHelper(const Model::UpdateTrialComponentRequest& request, const UpdateTrialComponentResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void UpdateUserProfileAsyncHelper(const Model::UpdateUserProfileRequest& request, const UpdateUserProfileResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void UpdateWorkforceAsyncHelper(const Model::UpdateWorkforceRequest& request, const UpdateWorkforceResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
void UpdateWorkteamAsyncHelper(const Model::UpdateWorkteamRequest& request, const UpdateWorkteamResponseReceivedHandler& handler, const std::shared_ptr<const Aws::Client::AsyncCallerContext>& context) const;
Aws::String m_uri;
Aws::String m_configScheme;
std::shared_ptr<Aws::Utils::Threading::Executor> m_executor;
};
} // namespace SageMaker
} // namespace Aws