/*
* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License").
* You may not use this file except in compliance with the License.
* A copy of the License is located at
*
* http://aws.amazon.com/apache2.0
*
* or in the "license" file accompanying this file. This file is distributed
* on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
* express or implied. See the License for the specific language governing
* permissions and limitations under the License.
*/
/*
* Do not modify this file. This file is generated from the sagemaker-2017-07-24.normal.json service model.
*/
using System;
using System.Runtime.ExceptionServices;
using System.Threading;
using System.Threading.Tasks;
using System.Collections.Generic;
using System.Net;
using Amazon.SageMaker.Model;
using Amazon.SageMaker.Model.Internal.MarshallTransformations;
using Amazon.SageMaker.Internal;
using Amazon.Runtime;
using Amazon.Runtime.Internal;
using Amazon.Runtime.Internal.Auth;
using Amazon.Runtime.Internal.Transform;
namespace Amazon.SageMaker
{
///
/// Implementation for accessing SageMaker
///
/// Provides APIs for creating and managing SageMaker resources.
///
///
///
/// Other Resources:
///
///
///
public partial class AmazonSageMakerClient : AmazonServiceClient, IAmazonSageMaker
{
private static IServiceMetadata serviceMetadata = new AmazonSageMakerMetadata();
#region Constructors
///
/// Constructs AmazonSageMakerClient with the credentials loaded from the application's
/// default configuration, and if unsuccessful from the Instance Profile service on an EC2 instance.
///
/// Example App.config with credentials set.
///
/// <?xml version="1.0" encoding="utf-8" ?>
/// <configuration>
/// <appSettings>
/// <add key="AWSProfileName" value="AWS Default"/>
/// </appSettings>
/// </configuration>
///
///
///
public AmazonSageMakerClient()
: base(FallbackCredentialsFactory.GetCredentials(), new AmazonSageMakerConfig()) { }
///
/// Constructs AmazonSageMakerClient with the credentials loaded from the application's
/// default configuration, and if unsuccessful from the Instance Profile service on an EC2 instance.
///
/// Example App.config with credentials set.
///
/// <?xml version="1.0" encoding="utf-8" ?>
/// <configuration>
/// <appSettings>
/// <add key="AWSProfileName" value="AWS Default"/>
/// </appSettings>
/// </configuration>
///
///
///
/// The region to connect.
public AmazonSageMakerClient(RegionEndpoint region)
: base(FallbackCredentialsFactory.GetCredentials(), new AmazonSageMakerConfig{RegionEndpoint = region}) { }
///
/// Constructs AmazonSageMakerClient with the credentials loaded from the application's
/// default configuration, and if unsuccessful from the Instance Profile service on an EC2 instance.
///
/// Example App.config with credentials set.
///
/// <?xml version="1.0" encoding="utf-8" ?>
/// <configuration>
/// <appSettings>
/// <add key="AWSProfileName" value="AWS Default"/>
/// </appSettings>
/// </configuration>
///
///
///
/// The AmazonSageMakerClient Configuration Object
public AmazonSageMakerClient(AmazonSageMakerConfig config)
: base(FallbackCredentialsFactory.GetCredentials(config), config){}
///
/// Constructs AmazonSageMakerClient with AWS Credentials
///
/// AWS Credentials
public AmazonSageMakerClient(AWSCredentials credentials)
: this(credentials, new AmazonSageMakerConfig())
{
}
///
/// Constructs AmazonSageMakerClient with AWS Credentials
///
/// AWS Credentials
/// The region to connect.
public AmazonSageMakerClient(AWSCredentials credentials, RegionEndpoint region)
: this(credentials, new AmazonSageMakerConfig{RegionEndpoint = region})
{
}
///
/// Constructs AmazonSageMakerClient with AWS Credentials and an
/// AmazonSageMakerClient Configuration object.
///
/// AWS Credentials
/// The AmazonSageMakerClient Configuration Object
public AmazonSageMakerClient(AWSCredentials credentials, AmazonSageMakerConfig clientConfig)
: base(credentials, clientConfig)
{
}
///
/// Constructs AmazonSageMakerClient with AWS Access Key ID and AWS Secret Key
///
/// AWS Access Key ID
/// AWS Secret Access Key
public AmazonSageMakerClient(string awsAccessKeyId, string awsSecretAccessKey)
: this(awsAccessKeyId, awsSecretAccessKey, new AmazonSageMakerConfig())
{
}
///
/// Constructs AmazonSageMakerClient with AWS Access Key ID and AWS Secret Key
///
/// AWS Access Key ID
/// AWS Secret Access Key
/// The region to connect.
public AmazonSageMakerClient(string awsAccessKeyId, string awsSecretAccessKey, RegionEndpoint region)
: this(awsAccessKeyId, awsSecretAccessKey, new AmazonSageMakerConfig() {RegionEndpoint=region})
{
}
///
/// Constructs AmazonSageMakerClient with AWS Access Key ID, AWS Secret Key and an
/// AmazonSageMakerClient Configuration object.
///
/// AWS Access Key ID
/// AWS Secret Access Key
/// The AmazonSageMakerClient Configuration Object
public AmazonSageMakerClient(string awsAccessKeyId, string awsSecretAccessKey, AmazonSageMakerConfig clientConfig)
: base(awsAccessKeyId, awsSecretAccessKey, clientConfig)
{
}
///
/// Constructs AmazonSageMakerClient with AWS Access Key ID and AWS Secret Key
///
/// AWS Access Key ID
/// AWS Secret Access Key
/// AWS Session Token
public AmazonSageMakerClient(string awsAccessKeyId, string awsSecretAccessKey, string awsSessionToken)
: this(awsAccessKeyId, awsSecretAccessKey, awsSessionToken, new AmazonSageMakerConfig())
{
}
///
/// Constructs AmazonSageMakerClient with AWS Access Key ID and AWS Secret Key
///
/// AWS Access Key ID
/// AWS Secret Access Key
/// AWS Session Token
/// The region to connect.
public AmazonSageMakerClient(string awsAccessKeyId, string awsSecretAccessKey, string awsSessionToken, RegionEndpoint region)
: this(awsAccessKeyId, awsSecretAccessKey, awsSessionToken, new AmazonSageMakerConfig{RegionEndpoint = region})
{
}
///
/// Constructs AmazonSageMakerClient with AWS Access Key ID, AWS Secret Key and an
/// AmazonSageMakerClient Configuration object.
///
/// AWS Access Key ID
/// AWS Secret Access Key
/// AWS Session Token
/// The AmazonSageMakerClient Configuration Object
public AmazonSageMakerClient(string awsAccessKeyId, string awsSecretAccessKey, string awsSessionToken, AmazonSageMakerConfig clientConfig)
: base(awsAccessKeyId, awsSecretAccessKey, awsSessionToken, clientConfig)
{
}
#endregion
#if AWS_ASYNC_ENUMERABLES_API
private ISageMakerPaginatorFactory _paginators;
///
/// Paginators for the service
///
public ISageMakerPaginatorFactory Paginators
{
get
{
if (this._paginators == null)
{
this._paginators = new SageMakerPaginatorFactory(this);
}
return this._paginators;
}
}
#endif
#region Overrides
///
/// Creates the signer for the service.
///
protected override AbstractAWSSigner CreateSigner()
{
return new AWS4Signer();
}
///
/// Customizes the runtime pipeline.
///
/// Runtime pipeline for the current client.
protected override void CustomizeRuntimePipeline(RuntimePipeline pipeline)
{
pipeline.RemoveHandler();
pipeline.AddHandlerAfter(new AmazonSageMakerEndpointResolver());
}
///
/// Capture metadata for the service.
///
protected override IServiceMetadata ServiceMetadata
{
get
{
return serviceMetadata;
}
}
#endregion
#region Dispose
///
/// Disposes the service client.
///
protected override void Dispose(bool disposing)
{
base.Dispose(disposing);
}
#endregion
#region AddAssociation
internal virtual AddAssociationResponse AddAssociation(AddAssociationRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = AddAssociationRequestMarshaller.Instance;
options.ResponseUnmarshaller = AddAssociationResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates an association between the source and the destination. A source can
/// be associated with multiple destinations, and a destination can be associated with
/// multiple sources. An association is a lineage tracking entity. For more information,
/// see Amazon
/// SageMaker ML Lineage Tracking.
///
/// Container for the necessary parameters to execute the AddAssociation service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the AddAssociation service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
///
/// Resource being access is not found.
///
/// REST API Reference for AddAssociation Operation
public virtual Task AddAssociationAsync(AddAssociationRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = AddAssociationRequestMarshaller.Instance;
options.ResponseUnmarshaller = AddAssociationResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region AddTags
internal virtual AddTagsResponse AddTags(AddTagsRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = AddTagsRequestMarshaller.Instance;
options.ResponseUnmarshaller = AddTagsResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Adds or overwrites one or more tags for the specified SageMaker resource. You can
/// add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform
/// jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints.
///
///
///
/// Each tag consists of a key and an optional value. Tag keys must be unique per resource.
/// For more information about tags, see For more information, see Amazon
/// Web Services Tagging Strategies.
///
///
///
/// Tags that you add to a hyperparameter tuning job by calling this API are also added
/// to any training jobs that the hyperparameter tuning job launches after you call this
/// API, but not to training jobs that the hyperparameter tuning job launched before you
/// called this API. To make sure that the tags associated with a hyperparameter tuning
/// job are also added to all training jobs that the hyperparameter tuning job launches,
/// add the tags when you first create the tuning job by specifying them in the Tags
/// parameter of CreateHyperParameterTuningJob
///
///
///
///
/// Tags that you add to a SageMaker Studio Domain or User Profile by calling this API
/// are also added to any Apps that the Domain or User Profile launches after you call
/// this API, but not to Apps that the Domain or User Profile launched before you called
/// this API. To make sure that the tags associated with a Domain or User Profile are
/// also added to all Apps that the Domain or User Profile launches, add the tags when
/// you first create the Domain or User Profile by specifying them in the Tags
/// parameter of CreateDomain
/// or CreateUserProfile.
///
///
///
/// Container for the necessary parameters to execute the AddTags service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the AddTags service method, as returned by SageMaker.
/// REST API Reference for AddTags Operation
public virtual Task AddTagsAsync(AddTagsRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = AddTagsRequestMarshaller.Instance;
options.ResponseUnmarshaller = AddTagsResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region AssociateTrialComponent
internal virtual AssociateTrialComponentResponse AssociateTrialComponent(AssociateTrialComponentRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = AssociateTrialComponentRequestMarshaller.Instance;
options.ResponseUnmarshaller = AssociateTrialComponentResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Associates a trial component with a trial. A trial component can be associated with
/// multiple trials. To disassociate a trial component from a trial, call the DisassociateTrialComponent
/// API.
///
/// Container for the necessary parameters to execute the AssociateTrialComponent service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the AssociateTrialComponent service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
///
/// Resource being access is not found.
///
/// REST API Reference for AssociateTrialComponent Operation
public virtual Task AssociateTrialComponentAsync(AssociateTrialComponentRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = AssociateTrialComponentRequestMarshaller.Instance;
options.ResponseUnmarshaller = AssociateTrialComponentResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region BatchDescribeModelPackage
internal virtual BatchDescribeModelPackageResponse BatchDescribeModelPackage(BatchDescribeModelPackageRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = BatchDescribeModelPackageRequestMarshaller.Instance;
options.ResponseUnmarshaller = BatchDescribeModelPackageResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// This action batch describes a list of versioned model packages
///
/// Container for the necessary parameters to execute the BatchDescribeModelPackage service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the BatchDescribeModelPackage service method, as returned by SageMaker.
/// REST API Reference for BatchDescribeModelPackage Operation
public virtual Task BatchDescribeModelPackageAsync(BatchDescribeModelPackageRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = BatchDescribeModelPackageRequestMarshaller.Instance;
options.ResponseUnmarshaller = BatchDescribeModelPackageResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateAction
internal virtual CreateActionResponse CreateAction(CreateActionRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateActionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateActionResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates an action. An action is a lineage tracking entity that represents an
/// action or activity. For example, a model deployment or an HPO job. Generally, an action
/// involves at least one input or output artifact. For more information, see Amazon
/// SageMaker ML Lineage Tracking.
///
/// Container for the necessary parameters to execute the CreateAction service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateAction service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateAction Operation
public virtual Task CreateActionAsync(CreateActionRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateActionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateActionResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateAlgorithm
internal virtual CreateAlgorithmResponse CreateAlgorithm(CreateAlgorithmRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateAlgorithmRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateAlgorithmResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Create a machine learning algorithm that you can use in SageMaker and list in the
/// Amazon Web Services Marketplace.
///
/// Container for the necessary parameters to execute the CreateAlgorithm service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateAlgorithm service method, as returned by SageMaker.
/// REST API Reference for CreateAlgorithm Operation
public virtual Task CreateAlgorithmAsync(CreateAlgorithmRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateAlgorithmRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateAlgorithmResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateApp
internal virtual CreateAppResponse CreateApp(CreateAppRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateAppRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateAppResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a running app for the specified UserProfile. 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.
///
/// Container for the necessary parameters to execute the CreateApp service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateApp service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateApp Operation
public virtual Task CreateAppAsync(CreateAppRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateAppRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateAppResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateAppImageConfig
internal virtual CreateAppImageConfigResponse CreateAppImageConfig(CreateAppImageConfigRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateAppImageConfigRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateAppImageConfigResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a configuration for running a SageMaker image as a KernelGateway app. The
/// configuration specifies the Amazon Elastic File System (EFS) storage volume on the
/// image, and a list of the kernels in the image.
///
/// Container for the necessary parameters to execute the CreateAppImageConfig service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateAppImageConfig service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
/// REST API Reference for CreateAppImageConfig Operation
public virtual Task CreateAppImageConfigAsync(CreateAppImageConfigRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateAppImageConfigRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateAppImageConfigResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateArtifact
internal virtual CreateArtifactResponse CreateArtifact(CreateArtifactRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateArtifactRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateArtifactResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates an artifact. An artifact is a lineage tracking entity that represents
/// a URI addressable object or data. Some examples are the S3 URI of a dataset and the
/// ECR registry path of an image. For more information, see Amazon
/// SageMaker ML Lineage Tracking.
///
/// Container for the necessary parameters to execute the CreateArtifact service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateArtifact service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateArtifact Operation
public virtual Task CreateArtifactAsync(CreateArtifactRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateArtifactRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateArtifactResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateAutoMLJob
internal virtual CreateAutoMLJobResponse CreateAutoMLJob(CreateAutoMLJobRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateAutoMLJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateAutoMLJobResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
///
///
///
/// We recommend using the new versions CreateAutoMLJobV2
/// and DescribeAutoMLJobV2,
/// which offer backward compatibility.
///
///
///
/// CreateAutoMLJobV2
can manage tabular problem types identical to those
/// of its previous version CreateAutoMLJob
, as well as non-tabular problem
/// types such as image or text classification.
///
///
///
/// Find guidelines about how to migrate a CreateAutoMLJob
to CreateAutoMLJobV2
/// in Migrate
/// a CreateAutoMLJob to CreateAutoMLJobV2.
///
///
///
/// You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2
/// (recommended) or DescribeAutoMLJob.
///
///
/// Container for the necessary parameters to execute the CreateAutoMLJob service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateAutoMLJob service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateAutoMLJob Operation
public virtual Task CreateAutoMLJobAsync(CreateAutoMLJobRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateAutoMLJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateAutoMLJobResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateAutoMLJobV2
internal virtual CreateAutoMLJobV2Response CreateAutoMLJobV2(CreateAutoMLJobV2Request request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateAutoMLJobV2RequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateAutoMLJobV2ResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.
///
///
///
/// CreateAutoMLJobV2
/// and DescribeAutoMLJobV2
/// are new versions of CreateAutoMLJob
/// and DescribeAutoMLJob
/// which offer backward compatibility.
///
///
///
/// CreateAutoMLJobV2
can manage tabular problem types identical to those
/// of its previous version CreateAutoMLJob
, as well as non-tabular problem
/// types such as image or text classification.
///
///
///
/// Find guidelines about how to migrate a CreateAutoMLJob
to CreateAutoMLJobV2
/// in Migrate
/// a CreateAutoMLJob to CreateAutoMLJobV2.
///
///
///
/// For the list of available problem types supported by CreateAutoMLJobV2
,
/// see AutoMLProblemTypeConfig.
///
///
///
/// You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.
///
///
/// Container for the necessary parameters to execute the CreateAutoMLJobV2 service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateAutoMLJobV2 service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateAutoMLJobV2 Operation
public virtual Task CreateAutoMLJobV2Async(CreateAutoMLJobV2Request request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateAutoMLJobV2RequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateAutoMLJobV2ResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateCodeRepository
internal virtual CreateCodeRepositoryResponse CreateCodeRepository(CreateCodeRepositoryRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateCodeRepositoryRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateCodeRepositoryResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a Git repository as a resource in your SageMaker account. You can associate
/// the repository with notebook instances so that you can use Git source control for
/// the notebooks you create. The Git repository is a resource in your SageMaker account,
/// so it can be associated with more than one notebook instance, and it persists independently
/// from the lifecycle of any notebook instances it is associated with.
///
///
///
/// The repository can be hosted either in Amazon
/// Web Services CodeCommit or in any other Git repository.
///
///
/// Container for the necessary parameters to execute the CreateCodeRepository service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateCodeRepository service method, as returned by SageMaker.
/// REST API Reference for CreateCodeRepository Operation
public virtual Task CreateCodeRepositoryAsync(CreateCodeRepositoryRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateCodeRepositoryRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateCodeRepositoryResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateCompilationJob
internal virtual CreateCompilationJobResponse CreateCompilationJob(CreateCompilationJobRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateCompilationJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateCompilationJobResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Starts a model compilation job. After the model has been compiled, Amazon SageMaker
/// saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3)
/// bucket that you specify.
///
///
///
/// If you choose to host your model using Amazon SageMaker hosting services, you can
/// use the resulting model artifacts as part of the model. You can also use the artifacts
/// with Amazon Web Services IoT Greengrass. In that case, deploy them as an ML resource.
///
///
///
/// In the request body, you provide the following:
///
/// -
///
/// A name for the compilation job
///
///
-
///
/// Information about the input model artifacts
///
///
-
///
/// The output location for the compiled model and the device (target) that the model
/// runs on
///
///
-
///
/// The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker assumes to perform
/// the model compilation job.
///
///
///
/// You can also provide a Tag
to track the model compilation job's resource
/// use and costs. The response body contains the CompilationJobArn
for the
/// compiled job.
///
///
///
/// To stop a model compilation job, use StopCompilationJob.
/// To get information about a particular model compilation job, use DescribeCompilationJob.
/// To get information about multiple model compilation jobs, use ListCompilationJobs.
///
///
/// Container for the necessary parameters to execute the CreateCompilationJob service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateCompilationJob service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateCompilationJob Operation
public virtual Task CreateCompilationJobAsync(CreateCompilationJobRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateCompilationJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateCompilationJobResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateContext
internal virtual CreateContextResponse CreateContext(CreateContextRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateContextRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateContextResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a context. A context is a lineage tracking entity that represents a
/// logical grouping of other tracking or experiment entities. Some examples are an endpoint
/// and a model package. For more information, see Amazon
/// SageMaker ML Lineage Tracking.
///
/// Container for the necessary parameters to execute the CreateContext service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateContext service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateContext Operation
public virtual Task CreateContextAsync(CreateContextRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateContextRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateContextResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateDataQualityJobDefinition
internal virtual CreateDataQualityJobDefinitionResponse CreateDataQualityJobDefinition(CreateDataQualityJobDefinitionRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateDataQualityJobDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateDataQualityJobDefinitionResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a definition for a job that monitors data quality and drift. For information
/// about model monitor, see Amazon
/// SageMaker Model Monitor.
///
/// Container for the necessary parameters to execute the CreateDataQualityJobDefinition service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateDataQualityJobDefinition service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateDataQualityJobDefinition Operation
public virtual Task CreateDataQualityJobDefinitionAsync(CreateDataQualityJobDefinitionRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateDataQualityJobDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateDataQualityJobDefinitionResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateDeviceFleet
internal virtual CreateDeviceFleetResponse CreateDeviceFleet(CreateDeviceFleetRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateDeviceFleetRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateDeviceFleetResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a device fleet.
///
/// Container for the necessary parameters to execute the CreateDeviceFleet service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateDeviceFleet service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateDeviceFleet Operation
public virtual Task CreateDeviceFleetAsync(CreateDeviceFleetRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateDeviceFleetRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateDeviceFleetResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateDomain
internal virtual CreateDomainResponse CreateDomain(CreateDomainRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateDomainRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateDomainResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a Domain
used by Amazon SageMaker Studio. A domain consists of
/// an associated Amazon Elastic File System (EFS) volume, a list of authorized users,
/// and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC)
/// configurations. Users within a domain can share notebook files and other artifacts
/// with each other.
///
///
///
/// EFS storage
///
///
///
/// When a domain is created, an EFS volume is created for use by all of the users within
/// the domain. Each user receives a private home directory within the EFS volume for
/// notebooks, Git repositories, and data files.
///
///
///
/// SageMaker uses the Amazon Web Services Key Management Service (Amazon Web Services
/// KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services
/// managed key by default. For more control, you can specify a customer managed key.
/// For more information, see Protect
/// Data at Rest Using Encryption.
///
///
///
/// VPC configuration
///
///
///
/// All SageMaker Studio traffic between the domain and the EFS volume is through the
/// specified VPC and subnets. For other Studio traffic, you can specify the AppNetworkAccessType
/// parameter. AppNetworkAccessType
corresponds to the network access type
/// that you choose when you onboard to Studio. The following options are available:
///
/// -
///
///
PublicInternetOnly
- Non-EFS traffic goes through a VPC managed by Amazon
/// SageMaker, which allows internet access. This is the default value.
///
/// -
///
///
VpcOnly
- All Studio traffic is through the specified VPC and subnets.
/// Internet access is disabled by default. To allow internet access, you must specify
/// a NAT gateway.
///
///
///
/// When internet access is disabled, you won't be able to run a Studio notebook or to
/// train or host models unless your VPC has an interface endpoint to the SageMaker API
/// and runtime or a NAT gateway and your security groups allow outbound connections.
///
///
///
/// 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.
///
///
///
/// For more information, see Connect
/// SageMaker Studio Notebooks to Resources in a VPC.
///
///
/// Container for the necessary parameters to execute the CreateDomain service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateDomain service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateDomain Operation
public virtual Task CreateDomainAsync(CreateDomainRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateDomainRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateDomainResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateEdgeDeploymentPlan
internal virtual CreateEdgeDeploymentPlanResponse CreateEdgeDeploymentPlan(CreateEdgeDeploymentPlanRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateEdgeDeploymentPlanRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateEdgeDeploymentPlanResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates an edge deployment plan, consisting of multiple stages. Each stage may have
/// a different deployment configuration and devices.
///
/// Container for the necessary parameters to execute the CreateEdgeDeploymentPlan service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateEdgeDeploymentPlan service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateEdgeDeploymentPlan Operation
public virtual Task CreateEdgeDeploymentPlanAsync(CreateEdgeDeploymentPlanRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateEdgeDeploymentPlanRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateEdgeDeploymentPlanResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateEdgeDeploymentStage
internal virtual CreateEdgeDeploymentStageResponse CreateEdgeDeploymentStage(CreateEdgeDeploymentStageRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateEdgeDeploymentStageRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateEdgeDeploymentStageResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a new stage in an existing edge deployment plan.
///
/// Container for the necessary parameters to execute the CreateEdgeDeploymentStage service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateEdgeDeploymentStage service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateEdgeDeploymentStage Operation
public virtual Task CreateEdgeDeploymentStageAsync(CreateEdgeDeploymentStageRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateEdgeDeploymentStageRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateEdgeDeploymentStageResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateEdgePackagingJob
internal virtual CreateEdgePackagingJobResponse CreateEdgePackagingJob(CreateEdgePackagingJobRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateEdgePackagingJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateEdgePackagingJobResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Starts a SageMaker Edge Manager model packaging job. Edge Manager will use the model
/// artifacts from the Amazon Simple Storage Service bucket that you specify. After the
/// model has been packaged, Amazon SageMaker saves the resulting artifacts to an S3 bucket
/// that you specify.
///
/// Container for the necessary parameters to execute the CreateEdgePackagingJob service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateEdgePackagingJob service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateEdgePackagingJob Operation
public virtual Task CreateEdgePackagingJobAsync(CreateEdgePackagingJobRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateEdgePackagingJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateEdgePackagingJobResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateEndpoint
internal virtual CreateEndpointResponse CreateEndpoint(CreateEndpointRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateEndpointRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateEndpointResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates an endpoint using the endpoint configuration specified in the request. SageMaker
/// uses the endpoint to provision resources and deploy models. You create the endpoint
/// configuration with the CreateEndpointConfig
/// API.
///
///
///
/// Use this API to deploy models using SageMaker hosting services.
///
///
///
/// For an example that calls this method when deploying a model to SageMaker hosting
/// services, see the Create
/// Endpoint example notebook.
///
///
///
/// You must not delete an EndpointConfig
that is in use by an endpoint
/// that is live or while the UpdateEndpoint
or CreateEndpoint
/// operations are being performed on the endpoint. To update an endpoint, you must create
/// a new EndpointConfig
.
///
///
///
/// The endpoint name must be unique within an Amazon Web Services Region in your Amazon
/// Web Services account.
///
///
///
/// When it receives the request, SageMaker creates the endpoint, launches the resources
/// (ML compute instances), and deploys the model(s) on them.
///
///
///
/// When you call CreateEndpoint,
/// a load call is made to DynamoDB to verify that your endpoint configuration exists.
/// When you read data from a DynamoDB table supporting
/// Eventually Consistent Reads
, the response might not reflect the
/// results of a recently completed write operation. The response might include some stale
/// data. If the dependent entities are not yet in DynamoDB, this causes a validation
/// error. If you repeat your read request after a short time, the response should return
/// the latest data. So retry logic is recommended to handle these possible issues. We
/// also recommend that customers call DescribeEndpointConfig
/// before calling CreateEndpoint
/// to minimize the potential impact of a DynamoDB eventually consistent read.
///
///
///
/// When SageMaker receives the request, it sets the endpoint status to Creating
.
/// After it creates the endpoint, it sets the status to InService
. SageMaker
/// can then process incoming requests for inferences. To check the status of an endpoint,
/// use the DescribeEndpoint
/// API.
///
///
///
/// If any of the models hosted at this endpoint get model data from an Amazon S3 location,
/// SageMaker uses Amazon Web Services Security Token Service to download model artifacts
/// from the S3 path you provided. Amazon Web Services STS is activated in your Amazon
/// Web Services account by default. If you previously deactivated Amazon Web Services
/// STS for a region, you need to reactivate Amazon Web Services STS for that region.
/// For more information, see Activating
/// and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the
/// Amazon Web Services Identity and Access Management User Guide.
///
///
///
/// To add the IAM role policies for using this API operation, go to the IAM
/// console, and choose Roles in the left navigation pane. Search the IAM role that
/// you want to grant access to use the CreateEndpoint
/// and CreateEndpointConfig
/// API operations, add the following policies to the role.
///
/// -
///
/// Option 1: For a full SageMaker access, search and attach the
AmazonSageMakerFullAccess
/// policy.
///
/// -
///
/// Option 2: For granting a limited access to an IAM role, paste the following Action
/// elements manually into the JSON file of the IAM role:
///
///
///
///
"Action": ["sagemaker:CreateEndpoint", "sagemaker:CreateEndpointConfig"]
///
///
///
///
/// "Resource": [
///
///
///
/// "arn:aws:sagemaker:region:account-id:endpoint/endpointName"
///
///
///
/// "arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"
///
///
///
///
/// ]
///
///
///
/// For more information, see SageMaker
/// API Permissions: Actions, Permissions, and Resources Reference.
///
///
///
/// Container for the necessary parameters to execute the CreateEndpoint service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateEndpoint service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateEndpoint Operation
public virtual Task CreateEndpointAsync(CreateEndpointRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateEndpointRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateEndpointResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateEndpointConfig
internal virtual CreateEndpointConfigResponse CreateEndpointConfig(CreateEndpointConfigRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateEndpointConfigRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateEndpointConfigResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates an endpoint configuration that SageMaker hosting services uses to deploy models.
/// In the configuration, you identify one or more models, created using the CreateModel
/// API, to deploy and the resources that you want SageMaker to provision. Then you call
/// the CreateEndpoint
/// API.
///
///
///
/// Use this API if you want to use SageMaker hosting services to deploy models into
/// production.
///
///
///
/// In the request, you define a ProductionVariant
, for each model that you
/// want to deploy. Each ProductionVariant
parameter also describes the resources
/// that you want SageMaker to provision. This includes the number and type of ML compute
/// instances to deploy.
///
///
///
/// If you are hosting multiple models, you also assign a VariantWeight
to
/// specify how much traffic you want to allocate to each model. For example, suppose
/// that you want to host two models, A and B, and you assign traffic weight 2 for model
/// A and 1 for model B. SageMaker distributes two-thirds of the traffic to Model A, and
/// one-third to model B.
///
///
///
/// When you call CreateEndpoint,
/// a load call is made to DynamoDB to verify that your endpoint configuration exists.
/// When you read data from a DynamoDB table supporting
/// Eventually Consistent Reads
, the response might not reflect the
/// results of a recently completed write operation. The response might include some stale
/// data. If the dependent entities are not yet in DynamoDB, this causes a validation
/// error. If you repeat your read request after a short time, the response should return
/// the latest data. So retry logic is recommended to handle these possible issues. We
/// also recommend that customers call DescribeEndpointConfig
/// before calling CreateEndpoint
/// to minimize the potential impact of a DynamoDB eventually consistent read.
///
///
///
/// Container for the necessary parameters to execute the CreateEndpointConfig service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateEndpointConfig service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateEndpointConfig Operation
public virtual Task CreateEndpointConfigAsync(CreateEndpointConfigRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateEndpointConfigRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateEndpointConfigResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateExperiment
internal virtual CreateExperimentResponse CreateExperiment(CreateExperimentRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateExperimentRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateExperimentResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a SageMaker experiment. An experiment is a collection of trials
/// that are observed, compared and evaluated as a group. A trial is a set of steps, called
/// trial components, that produce a machine learning model.
///
///
///
/// In the Studio UI, trials are referred to as run groups and trial components
/// are referred to as runs.
///
///
///
/// The goal of an experiment is to determine the components that produce the best model.
/// Multiple trials are performed, each one isolating and measuring the impact of a change
/// to one or more inputs, while keeping the remaining inputs constant.
///
///
///
/// When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials,
/// and trial components are automatically tracked, logged, and indexed. When you use
/// the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided
/// by the SDK.
///
///
///
/// You can add tags to experiments, trials, trial components and then use the Search
/// API to search for the tags.
///
///
///
/// To add a description to an experiment, specify the optional Description
/// parameter. To add a description later, or to change the description, call the UpdateExperiment
/// API.
///
///
///
/// To get a list of all your experiments, call the ListExperiments
/// API. To view an experiment's properties, call the DescribeExperiment
/// API. To get a list of all the trials associated with an experiment, call the ListTrials
/// API. To create a trial call the CreateTrial
/// API.
///
///
/// Container for the necessary parameters to execute the CreateExperiment service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateExperiment service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateExperiment Operation
public virtual Task CreateExperimentAsync(CreateExperimentRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateExperimentRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateExperimentResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateFeatureGroup
internal virtual CreateFeatureGroupResponse CreateFeatureGroup(CreateFeatureGroupRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateFeatureGroupRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateFeatureGroupResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Create a new FeatureGroup
. A FeatureGroup
is a group of
/// Features
defined in the FeatureStore
to describe a Record
.
///
///
///
///
/// The FeatureGroup
defines the schema and features contained in the FeatureGroup.
/// A FeatureGroup
definition is composed of a list of Features
,
/// a RecordIdentifierFeatureName
, an EventTimeFeatureName
and
/// configurations for its OnlineStore
and OfflineStore
. Check
/// Amazon
/// Web Services service quotas to see the FeatureGroup
s quota for your
/// Amazon Web Services account.
///
///
///
/// You must include at least one of OnlineStoreConfig
and OfflineStoreConfig
/// to create a FeatureGroup
.
///
///
///
/// Container for the necessary parameters to execute the CreateFeatureGroup service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateFeatureGroup service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateFeatureGroup Operation
public virtual Task CreateFeatureGroupAsync(CreateFeatureGroupRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateFeatureGroupRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateFeatureGroupResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateFlowDefinition
internal virtual CreateFlowDefinitionResponse CreateFlowDefinition(CreateFlowDefinitionRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateFlowDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateFlowDefinitionResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a flow definition.
///
/// Container for the necessary parameters to execute the CreateFlowDefinition service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateFlowDefinition service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateFlowDefinition Operation
public virtual Task CreateFlowDefinitionAsync(CreateFlowDefinitionRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateFlowDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateFlowDefinitionResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateHub
internal virtual CreateHubResponse CreateHub(CreateHubRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateHubRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateHubResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Create a hub.
///
///
///
/// Hub APIs are only callable through SageMaker Studio.
///
///
///
/// Container for the necessary parameters to execute the CreateHub service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateHub service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateHub Operation
public virtual Task CreateHubAsync(CreateHubRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateHubRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateHubResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateHumanTaskUi
internal virtual CreateHumanTaskUiResponse CreateHumanTaskUi(CreateHumanTaskUiRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateHumanTaskUiRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateHumanTaskUiResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// 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.
///
/// Container for the necessary parameters to execute the CreateHumanTaskUi service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateHumanTaskUi service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateHumanTaskUi Operation
public virtual Task CreateHumanTaskUiAsync(CreateHumanTaskUiRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateHumanTaskUiRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateHumanTaskUiResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateHyperParameterTuningJob
internal virtual CreateHyperParameterTuningJobResponse CreateHyperParameterTuningJob(CreateHyperParameterTuningJobRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateHyperParameterTuningJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateHyperParameterTuningJobResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version
/// of a model by running many training jobs on your dataset using the algorithm you choose
/// and values for hyperparameters within ranges that you specify. It then chooses the
/// hyperparameter values that result in a model that performs the best, as measured by
/// an objective metric that you choose.
///
///
///
/// A hyperparameter tuning job automatically creates Amazon SageMaker experiments, trials,
/// and trial components for each training job that it runs. You can view these entities
/// in Amazon SageMaker Studio. For more information, see View
/// Experiments, Trials, and Trial Components.
///
///
///
/// Do not include any security-sensitive information including account access IDs, secrets
/// or tokens in any hyperparameter field. If the use of security-sensitive credentials
/// are detected, SageMaker will reject your training job request and return an exception
/// error.
///
///
///
/// Container for the necessary parameters to execute the CreateHyperParameterTuningJob service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateHyperParameterTuningJob service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateHyperParameterTuningJob Operation
public virtual Task CreateHyperParameterTuningJobAsync(CreateHyperParameterTuningJobRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateHyperParameterTuningJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateHyperParameterTuningJobResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateImage
internal virtual CreateImageResponse CreateImage(CreateImageRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateImageRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateImageResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a custom SageMaker image. A SageMaker image is a set of image versions. Each
/// image version represents a container image stored in Amazon Elastic Container Registry
/// (ECR). For more information, see Bring
/// your own SageMaker image.
///
/// Container for the necessary parameters to execute the CreateImage service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateImage service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateImage Operation
public virtual Task CreateImageAsync(CreateImageRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateImageRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateImageResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateImageVersion
internal virtual CreateImageVersionResponse CreateImageVersion(CreateImageVersionRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateImageVersionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateImageVersionResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a version of the SageMaker image specified by ImageName
. The
/// version represents the Amazon Elastic Container Registry (ECR) container image specified
/// by BaseImage
.
///
/// Container for the necessary parameters to execute the CreateImageVersion service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateImageVersion service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
///
/// Resource being access is not found.
///
/// REST API Reference for CreateImageVersion Operation
public virtual Task CreateImageVersionAsync(CreateImageVersionRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateImageVersionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateImageVersionResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateInferenceExperiment
internal virtual CreateInferenceExperimentResponse CreateInferenceExperiment(CreateInferenceExperimentRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateInferenceExperimentRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateInferenceExperimentResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates an inference experiment using the configurations specified in the request.
///
///
///
///
/// Use this API to setup and schedule an experiment to compare model variants on a Amazon
/// SageMaker inference endpoint. For more information about inference experiments, see
/// Shadow
/// tests.
///
///
///
/// Amazon SageMaker begins your experiment at the scheduled time and routes traffic
/// to your endpoint's model variants based on your specified configuration.
///
///
///
/// While the experiment is in progress or after it has concluded, you can view metrics
/// that compare your model variants. For more information, see View,
/// monitor, and edit shadow tests.
///
///
/// Container for the necessary parameters to execute the CreateInferenceExperiment service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateInferenceExperiment service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateInferenceExperiment Operation
public virtual Task CreateInferenceExperimentAsync(CreateInferenceExperimentRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateInferenceExperimentRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateInferenceExperimentResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateInferenceRecommendationsJob
internal virtual CreateInferenceRecommendationsJobResponse CreateInferenceRecommendationsJob(CreateInferenceRecommendationsJobRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateInferenceRecommendationsJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateInferenceRecommendationsJobResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Starts a recommendation job. You can create either an instance recommendation or load
/// test job.
///
/// Container for the necessary parameters to execute the CreateInferenceRecommendationsJob service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateInferenceRecommendationsJob service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateInferenceRecommendationsJob Operation
public virtual Task CreateInferenceRecommendationsJobAsync(CreateInferenceRecommendationsJobRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateInferenceRecommendationsJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateInferenceRecommendationsJobResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateLabelingJob
internal virtual CreateLabelingJobResponse CreateLabelingJob(CreateLabelingJobRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateLabelingJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateLabelingJobResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a job that uses workers to label the data objects in your input dataset. You
/// can use the labeled data to train machine learning models.
///
///
///
/// You can select your workforce from one of three providers:
///
/// -
///
/// A private workforce that you create. It can include employees, contractors, and outside
/// experts. Use a private workforce when want the data to stay within your organization
/// or when a specific set of skills is required.
///
///
-
///
/// One or more vendors that you select from the Amazon Web Services Marketplace. Vendors
/// provide expertise in specific areas.
///
///
-
///
/// The Amazon Mechanical Turk workforce. This is the largest workforce, but it should
/// only be used for public data or data that has been stripped of any personally identifiable
/// information.
///
///
///
/// You can also use automated data labeling to reduce the number of data objects
/// that need to be labeled by a human. Automated data labeling uses active learning
/// to determine if a data object can be labeled by machine or if it needs to be sent
/// to a human worker. For more information, see Using
/// Automated Data Labeling.
///
///
///
/// The data objects to be labeled are contained in an Amazon S3 bucket. You create a
/// manifest file that describes the location of each object. For more information,
/// see Using
/// Input and Output Data.
///
///
///
/// The output can be used as the manifest file for another labeling job or as training
/// data for your machine learning models.
///
///
///
/// You can use this operation to create a static labeling job or a streaming labeling
/// job. A static labeling job stops if all data objects in the input manifest file identified
/// in ManifestS3Uri
have been labeled. A streaming labeling job runs perpetually
/// until it is manually stopped, or remains idle for 10 days. You can send new data objects
/// to an active (InProgress
) streaming labeling job in real time. To learn
/// how to create a static labeling job, see Create
/// a Labeling Job (API) in the Amazon SageMaker Developer Guide. To learn how to
/// create a streaming labeling job, see Create
/// a Streaming Labeling Job.
///
///
/// Container for the necessary parameters to execute the CreateLabelingJob service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateLabelingJob service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateLabelingJob Operation
public virtual Task CreateLabelingJobAsync(CreateLabelingJobRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateLabelingJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateLabelingJobResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateModel
internal virtual CreateModelResponse CreateModel(CreateModelRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a model in SageMaker. In the request, you name the model and describe a primary
/// container. For the primary container, you specify the Docker image that contains inference
/// code, artifacts (from prior training), and a custom environment map that the inference
/// code uses when you deploy the model for predictions.
///
///
///
/// Use this API to create a model if you want to use SageMaker hosting services or run
/// a batch transform job.
///
///
///
/// To host your model, you create an endpoint configuration with the CreateEndpointConfig
/// API, and then create an endpoint with the CreateEndpoint
API. SageMaker
/// then deploys all of the containers that you defined for the model in the hosting environment.
///
///
///
///
/// For an example that calls this method when deploying a model to SageMaker hosting
/// services, see Create
/// a Model (Amazon Web Services SDK for Python (Boto 3)).
///
///
///
/// To run a batch transform using your model, you start a job with the CreateTransformJob
/// API. SageMaker uses your model and your dataset to get inferences which are then saved
/// to a specified S3 location.
///
///
///
/// In the request, you also provide an IAM role that SageMaker can assume to access model
/// artifacts and docker image for deployment on ML compute hosting instances or for batch
/// transform jobs. In addition, you also use the IAM role to manage permissions the inference
/// code needs. For example, if the inference code access any other Amazon Web Services
/// resources, you grant necessary permissions via this role.
///
///
/// Container for the necessary parameters to execute the CreateModel service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateModel service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateModel Operation
public virtual Task CreateModelAsync(CreateModelRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateModelBiasJobDefinition
internal virtual CreateModelBiasJobDefinitionResponse CreateModelBiasJobDefinition(CreateModelBiasJobDefinitionRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelBiasJobDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelBiasJobDefinitionResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates the definition for a model bias job.
///
/// Container for the necessary parameters to execute the CreateModelBiasJobDefinition service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateModelBiasJobDefinition service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateModelBiasJobDefinition Operation
public virtual Task CreateModelBiasJobDefinitionAsync(CreateModelBiasJobDefinitionRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelBiasJobDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelBiasJobDefinitionResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateModelCard
internal virtual CreateModelCardResponse CreateModelCard(CreateModelCardRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelCardRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelCardResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates an Amazon SageMaker Model Card.
///
///
///
/// For information about how to use model cards, see Amazon
/// SageMaker Model Card.
///
///
/// Container for the necessary parameters to execute the CreateModelCard service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateModelCard service method, as returned by SageMaker.
///
/// There was a conflict when you attempted to modify a SageMaker entity such as an Experiment
/// or Artifact
.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateModelCard Operation
public virtual Task CreateModelCardAsync(CreateModelCardRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelCardRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelCardResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateModelCardExportJob
internal virtual CreateModelCardExportJobResponse CreateModelCardExportJob(CreateModelCardExportJobRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelCardExportJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelCardExportJobResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates an Amazon SageMaker Model Card export job.
///
/// Container for the necessary parameters to execute the CreateModelCardExportJob service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateModelCardExportJob service method, as returned by SageMaker.
///
/// There was a conflict when you attempted to modify a SageMaker entity such as an Experiment
/// or Artifact
.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
///
/// Resource being access is not found.
///
/// REST API Reference for CreateModelCardExportJob Operation
public virtual Task CreateModelCardExportJobAsync(CreateModelCardExportJobRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelCardExportJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelCardExportJobResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateModelExplainabilityJobDefinition
internal virtual CreateModelExplainabilityJobDefinitionResponse CreateModelExplainabilityJobDefinition(CreateModelExplainabilityJobDefinitionRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelExplainabilityJobDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelExplainabilityJobDefinitionResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates the definition for a model explainability job.
///
/// Container for the necessary parameters to execute the CreateModelExplainabilityJobDefinition service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateModelExplainabilityJobDefinition service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateModelExplainabilityJobDefinition Operation
public virtual Task CreateModelExplainabilityJobDefinitionAsync(CreateModelExplainabilityJobDefinitionRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelExplainabilityJobDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelExplainabilityJobDefinitionResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateModelPackage
internal virtual CreateModelPackageResponse CreateModelPackage(CreateModelPackageRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelPackageRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelPackageResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a model package that you can use to create SageMaker models or list on Amazon
/// Web Services Marketplace, or a versioned model that is part of a model group. Buyers
/// can subscribe to model packages listed on Amazon Web Services Marketplace to create
/// models in SageMaker.
///
///
///
/// To create a model package by specifying a Docker container that contains your inference
/// code and the Amazon S3 location of your model artifacts, provide values for InferenceSpecification
.
/// To create a model from an algorithm resource that you created or subscribed to in
/// Amazon Web Services Marketplace, provide a value for SourceAlgorithmSpecification
.
///
///
///
/// There are two types of model packages:
///
/// -
///
/// Versioned - a model that is part of a model group in the model registry.
///
///
-
///
/// Unversioned - a model package that is not part of a model group.
///
///
///
/// Container for the necessary parameters to execute the CreateModelPackage service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateModelPackage service method, as returned by SageMaker.
///
/// There was a conflict when you attempted to modify a SageMaker entity such as an Experiment
/// or Artifact
.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateModelPackage Operation
public virtual Task CreateModelPackageAsync(CreateModelPackageRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelPackageRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelPackageResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateModelPackageGroup
internal virtual CreateModelPackageGroupResponse CreateModelPackageGroup(CreateModelPackageGroupRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelPackageGroupRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelPackageGroupResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a model group. A model group contains a group of model versions.
///
/// Container for the necessary parameters to execute the CreateModelPackageGroup service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateModelPackageGroup service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateModelPackageGroup Operation
public virtual Task CreateModelPackageGroupAsync(CreateModelPackageGroupRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelPackageGroupRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelPackageGroupResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateModelQualityJobDefinition
internal virtual CreateModelQualityJobDefinitionResponse CreateModelQualityJobDefinition(CreateModelQualityJobDefinitionRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelQualityJobDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelQualityJobDefinitionResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a definition for a job that monitors model quality and drift. For information
/// about model monitor, see Amazon
/// SageMaker Model Monitor.
///
/// Container for the necessary parameters to execute the CreateModelQualityJobDefinition service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateModelQualityJobDefinition service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateModelQualityJobDefinition Operation
public virtual Task CreateModelQualityJobDefinitionAsync(CreateModelQualityJobDefinitionRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateModelQualityJobDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateModelQualityJobDefinitionResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateMonitoringSchedule
internal virtual CreateMonitoringScheduleResponse CreateMonitoringSchedule(CreateMonitoringScheduleRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateMonitoringScheduleRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateMonitoringScheduleResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor
/// the data captured for an Amazon SageMaker Endpoint.
///
/// Container for the necessary parameters to execute the CreateMonitoringSchedule service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateMonitoringSchedule service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateMonitoringSchedule Operation
public virtual Task CreateMonitoringScheduleAsync(CreateMonitoringScheduleRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateMonitoringScheduleRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateMonitoringScheduleResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateNotebookInstance
internal virtual CreateNotebookInstanceResponse CreateNotebookInstance(CreateNotebookInstanceRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateNotebookInstanceRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateNotebookInstanceResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates an SageMaker notebook instance. A notebook instance is a machine learning
/// (ML) compute instance running on a Jupyter notebook.
///
///
///
/// In a CreateNotebookInstance
request, specify the type of ML compute instance
/// that you want to run. SageMaker launches the instance, installs common libraries that
/// you can use to explore datasets for model training, and attaches an ML storage volume
/// to the notebook instance.
///
///
///
/// SageMaker also provides a set of example notebooks. Each notebook demonstrates how
/// to use SageMaker with a specific algorithm or with a machine learning framework.
///
///
///
/// After receiving the request, SageMaker does the following:
///
/// -
///
/// Creates a network interface in the SageMaker VPC.
///
///
-
///
/// (Option) If you specified
SubnetId
, SageMaker creates a network interface
/// in your own VPC, which is inferred from the subnet ID that you provide in the input.
/// When creating this network interface, SageMaker attaches the security group that you
/// specified in the request to the network interface that it creates in your VPC.
///
/// -
///
/// Launches an EC2 instance of the type specified in the request in the SageMaker VPC.
/// If you specified
SubnetId
of your VPC, SageMaker specifies both network
/// interfaces when launching this instance. This enables inbound traffic from your own
/// VPC to the notebook instance, assuming that the security groups allow it.
///
///
///
/// After creating the notebook instance, SageMaker returns its Amazon Resource Name (ARN).
/// You can't change the name of a notebook instance after you create it.
///
///
///
/// After SageMaker creates the notebook instance, you can connect to the Jupyter server
/// and work in Jupyter notebooks. For example, you can write code to explore a dataset
/// that you can use for model training, train a model, host models by creating SageMaker
/// endpoints, and validate hosted models.
///
///
///
/// For more information, see How
/// It Works.
///
///
/// Container for the necessary parameters to execute the CreateNotebookInstance service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateNotebookInstance service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateNotebookInstance Operation
public virtual Task CreateNotebookInstanceAsync(CreateNotebookInstanceRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateNotebookInstanceRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateNotebookInstanceResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateNotebookInstanceLifecycleConfig
internal virtual CreateNotebookInstanceLifecycleConfigResponse CreateNotebookInstanceLifecycleConfig(CreateNotebookInstanceLifecycleConfigRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateNotebookInstanceLifecycleConfigRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateNotebookInstanceLifecycleConfigResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a lifecycle configuration that you can associate with a notebook instance.
/// A lifecycle configuration is a collection of shell scripts that run when you
/// create or start a notebook instance.
///
///
///
/// Each lifecycle configuration script has a limit of 16384 characters.
///
///
///
/// The value of the $PATH
environment variable that is available to both
/// scripts is /sbin:bin:/usr/sbin:/usr/bin
.
///
///
///
/// View CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances
/// in log stream [notebook-instance-name]/[LifecycleConfigHook]
.
///
///
///
/// Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script
/// runs for longer than 5 minutes, it fails and the notebook instance is not created
/// or started.
///
///
///
/// For information about notebook instance lifestyle configurations, see Step
/// 2.1: (Optional) Customize a Notebook Instance.
///
///
/// Container for the necessary parameters to execute the CreateNotebookInstanceLifecycleConfig service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateNotebookInstanceLifecycleConfig service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateNotebookInstanceLifecycleConfig Operation
public virtual Task CreateNotebookInstanceLifecycleConfigAsync(CreateNotebookInstanceLifecycleConfigRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateNotebookInstanceLifecycleConfigRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateNotebookInstanceLifecycleConfigResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreatePipeline
internal virtual CreatePipelineResponse CreatePipeline(CreatePipelineRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreatePipelineRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreatePipelineResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a pipeline using a JSON pipeline definition.
///
/// Container for the necessary parameters to execute the CreatePipeline service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreatePipeline service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
///
/// Resource being access is not found.
///
/// REST API Reference for CreatePipeline Operation
public virtual Task CreatePipelineAsync(CreatePipelineRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreatePipelineRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreatePipelineResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreatePresignedDomainUrl
internal virtual CreatePresignedDomainUrlResponse CreatePresignedDomainUrl(CreatePresignedDomainUrlRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreatePresignedDomainUrlRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreatePresignedDomainUrlResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser,
/// the user will be automatically signed in to Amazon SageMaker Studio, and granted access
/// to all of the Apps and files associated with the Domain's Amazon Elastic File System
/// (EFS) volume. This operation can only be called when the authentication mode equals
/// IAM.
///
///
///
/// The IAM role or user passed to this API defines the permissions to access the app.
/// Once the presigned URL is created, no additional permission is required to access
/// this URL. IAM authorization policies for this API are also enforced for every HTTP
/// request and WebSocket frame that attempts to connect to the app.
///
///
///
/// You can restrict access to this API and to the URL that it returns to a list of IP
/// addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more information,
/// see Connect
/// to SageMaker Studio Through an Interface VPC Endpoint .
///
///
///
/// The URL that you get from a call to CreatePresignedDomainUrl
has a default
/// timeout of 5 minutes. You can configure this value using ExpiresInSeconds
.
/// If you try to use the URL after the timeout limit expires, you are directed to the
/// Amazon Web Services console sign-in page.
///
///
///
/// Container for the necessary parameters to execute the CreatePresignedDomainUrl service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreatePresignedDomainUrl service method, as returned by SageMaker.
///
/// Resource being access is not found.
///
/// REST API Reference for CreatePresignedDomainUrl Operation
public virtual Task CreatePresignedDomainUrlAsync(CreatePresignedDomainUrlRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreatePresignedDomainUrlRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreatePresignedDomainUrlResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreatePresignedNotebookInstanceUrl
internal virtual CreatePresignedNotebookInstanceUrlResponse CreatePresignedNotebookInstanceUrl(CreatePresignedNotebookInstanceUrlRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreatePresignedNotebookInstanceUrlRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreatePresignedNotebookInstanceUrlResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Returns a URL that you can use to connect to the Jupyter server from a notebook instance.
/// In the SageMaker console, when you choose Open
next to a notebook instance,
/// SageMaker opens a new tab showing the Jupyter server home page from the notebook instance.
/// The console uses this API to get the URL and show the page.
///
///
///
/// The IAM role or user used to call this API defines the permissions to access the
/// notebook instance. Once the presigned URL is created, no additional permission is
/// required to access this URL. IAM authorization policies for this API are also enforced
/// for every HTTP request and WebSocket frame that attempts to connect to the notebook
/// instance.
///
///
///
/// You can restrict access to this API and to the URL that it returns to a list of IP
/// addresses that you specify. Use the NotIpAddress
condition operator and
/// the aws:SourceIP
condition context key to specify the list of IP addresses
/// that you want to have access to the notebook instance. For more information, see Limit
/// Access to a Notebook Instance by IP Address.
///
///
///
/// The URL that you get from a call to CreatePresignedNotebookInstanceUrl
/// is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires,
/// you are directed to the Amazon Web Services console sign-in page.
///
///
///
/// Container for the necessary parameters to execute the CreatePresignedNotebookInstanceUrl service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreatePresignedNotebookInstanceUrl service method, as returned by SageMaker.
/// REST API Reference for CreatePresignedNotebookInstanceUrl Operation
public virtual Task CreatePresignedNotebookInstanceUrlAsync(CreatePresignedNotebookInstanceUrlRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreatePresignedNotebookInstanceUrlRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreatePresignedNotebookInstanceUrlResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateProcessingJob
internal virtual CreateProcessingJobResponse CreateProcessingJob(CreateProcessingJobRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateProcessingJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateProcessingJobResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a processing job.
///
/// Container for the necessary parameters to execute the CreateProcessingJob service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateProcessingJob service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
///
/// Resource being access is not found.
///
/// REST API Reference for CreateProcessingJob Operation
public virtual Task CreateProcessingJobAsync(CreateProcessingJobRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateProcessingJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateProcessingJobResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateProject
internal virtual CreateProjectResponse CreateProject(CreateProjectRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateProjectRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateProjectResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a machine learning (ML) project that can contain one or more templates that
/// set up an ML pipeline from training to deploying an approved model.
///
/// Container for the necessary parameters to execute the CreateProject service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateProject service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateProject Operation
public virtual Task CreateProjectAsync(CreateProjectRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateProjectRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateProjectResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateSpace
internal virtual CreateSpaceResponse CreateSpace(CreateSpaceRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateSpaceRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateSpaceResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a space used for real time collaboration in a Domain.
///
/// Container for the necessary parameters to execute the CreateSpace service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateSpace service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateSpace Operation
public virtual Task CreateSpaceAsync(CreateSpaceRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateSpaceRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateSpaceResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateStudioLifecycleConfig
internal virtual CreateStudioLifecycleConfigResponse CreateStudioLifecycleConfig(CreateStudioLifecycleConfigRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateStudioLifecycleConfigRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateStudioLifecycleConfigResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a new Studio Lifecycle Configuration.
///
/// Container for the necessary parameters to execute the CreateStudioLifecycleConfig service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateStudioLifecycleConfig service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
/// REST API Reference for CreateStudioLifecycleConfig Operation
public virtual Task CreateStudioLifecycleConfigAsync(CreateStudioLifecycleConfigRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateStudioLifecycleConfigRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateStudioLifecycleConfigResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateTrainingJob
internal virtual CreateTrainingJobResponse CreateTrainingJob(CreateTrainingJobRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateTrainingJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateTrainingJobResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Starts a model training job. After training completes, SageMaker saves the resulting
/// model artifacts to an Amazon S3 location that you specify.
///
///
///
/// If you choose to host your model using SageMaker hosting services, you can use the
/// resulting model artifacts as part of the model. You can also use the artifacts in
/// a machine learning service other than SageMaker, provided that you know how to use
/// them for inference.
///
///
///
/// In the request body, you provide the following:
///
/// -
///
///
AlgorithmSpecification
- Identifies the training algorithm to use.
///
/// -
///
///
HyperParameters
- Specify these algorithm-specific parameters to enable
/// the estimation of model parameters during training. Hyperparameters can be tuned to
/// optimize this learning process. For a list of hyperparameters for each training algorithm
/// provided by SageMaker, see Algorithms.
///
///
///
///
/// Do not include any security-sensitive information including account access IDs, secrets
/// or tokens in any hyperparameter field. If the use of security-sensitive credentials
/// are detected, SageMaker will reject your training job request and return an exception
/// error.
///
/// -
///
///
InputDataConfig
- Describes the input required by the training job and
/// the Amazon S3, EFS, or FSx location where it is stored.
///
/// -
///
///
OutputDataConfig
- Identifies the Amazon S3 bucket where you want SageMaker
/// to save the results of model training.
///
/// -
///
///
ResourceConfig
- Identifies the resources, ML compute instances, and
/// ML storage volumes to deploy for model training. In distributed training, you specify
/// more than one instance.
///
/// -
///
///
EnableManagedSpotTraining
- Optimize the cost of training machine learning
/// models by up to 80% by using Amazon EC2 Spot instances. For more information, see
/// Managed
/// Spot Training.
///
/// -
///
///
RoleArn
- The Amazon Resource Name (ARN) that SageMaker assumes to perform
/// tasks on your behalf during model training. You must grant this role the necessary
/// permissions so that SageMaker can successfully complete model training.
///
/// -
///
///
StoppingCondition
- To help cap training costs, use MaxRuntimeInSeconds
/// to set a time limit for training. Use MaxWaitTimeInSeconds
to specify
/// how long a managed spot training job has to complete.
///
/// -
///
///
Environment
- The environment variables to set in the Docker container.
///
/// -
///
///
RetryStrategy
- The number of times to retry the job when the job fails
/// due to an InternalServerError
.
///
///
///
/// For more information about SageMaker, see How
/// It Works.
///
///
/// Container for the necessary parameters to execute the CreateTrainingJob service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateTrainingJob service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
///
/// Resource being access is not found.
///
/// REST API Reference for CreateTrainingJob Operation
public virtual Task CreateTrainingJobAsync(CreateTrainingJobRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateTrainingJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateTrainingJobResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateTransformJob
internal virtual CreateTransformJobResponse CreateTransformJob(CreateTransformJobRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateTransformJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateTransformJobResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Starts a transform job. A transform job uses a trained model to get inferences on
/// a dataset and saves these results to an Amazon S3 location that you specify.
///
///
///
/// To perform batch transformations, you create a transform job and use the data that
/// you have readily available.
///
///
///
/// In the request body, you provide the following:
///
/// -
///
///
TransformJobName
- Identifies the transform job. The name must be unique
/// within an Amazon Web Services Region in an Amazon Web Services account.
///
/// -
///
///
ModelName
- Identifies the model to use. ModelName
must
/// be the name of an existing Amazon SageMaker model in the same Amazon Web Services
/// Region and Amazon Web Services account. For information on creating a model, see CreateModel.
///
/// -
///
///
TransformInput
- Describes the dataset to be transformed and the Amazon
/// S3 location where it is stored.
///
/// -
///
///
TransformOutput
- Identifies the Amazon S3 location where you want Amazon
/// SageMaker to save the results from the transform job.
///
/// -
///
///
TransformResources
- Identifies the ML compute instances for the transform
/// job.
///
///
///
/// For more information about how batch transformation works, see Batch
/// Transform.
///
///
/// Container for the necessary parameters to execute the CreateTransformJob service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateTransformJob service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
///
/// Resource being access is not found.
///
/// REST API Reference for CreateTransformJob Operation
public virtual Task CreateTransformJobAsync(CreateTransformJobRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateTransformJobRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateTransformJobResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateTrial
internal virtual CreateTrialResponse CreateTrial(CreateTrialRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateTrialRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateTrialResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates an SageMaker trial. A trial is a set of steps called trial components
/// that produce a machine learning model. A trial is part of a single SageMaker experiment.
///
///
///
/// When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials,
/// and trial components are automatically tracked, logged, and indexed. When you use
/// the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided
/// by the SDK.
///
///
///
/// You can add tags to a trial and then use the Search
/// API to search for the tags.
///
///
///
/// To get a list of all your trials, call the ListTrials
/// API. To view a trial's properties, call the DescribeTrial
/// API. To create a trial component, call the CreateTrialComponent
/// API.
///
///
/// Container for the necessary parameters to execute the CreateTrial service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateTrial service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
///
/// Resource being access is not found.
///
/// REST API Reference for CreateTrial Operation
public virtual Task CreateTrialAsync(CreateTrialRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateTrialRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateTrialResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateTrialComponent
internal virtual CreateTrialComponentResponse CreateTrialComponent(CreateTrialComponentRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateTrialComponentRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateTrialComponentResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a trial component, which is a stage of a machine learning trial.
/// A trial is composed of one or more trial components. A trial component can be used
/// in multiple trials.
///
///
///
/// Trial components include pre-processing jobs, training jobs, and batch transform jobs.
///
///
///
/// When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials,
/// and trial components are automatically tracked, logged, and indexed. When you use
/// the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided
/// by the SDK.
///
///
///
/// You can add tags to a trial component and then use the Search
/// API to search for the tags.
///
///
/// Container for the necessary parameters to execute the CreateTrialComponent service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateTrialComponent service method, as returned by SageMaker.
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateTrialComponent Operation
public virtual Task CreateTrialComponentAsync(CreateTrialComponentRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateTrialComponentRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateTrialComponentResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateUserProfile
internal virtual CreateUserProfileResponse CreateUserProfile(CreateUserProfileRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateUserProfileRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateUserProfileResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// 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
/// IAM Identity Center, a user profile is automatically created. A user profile is the
/// primary holder of settings for an individual user and has a reference to the user's
/// private Amazon Elastic File System (EFS) home directory.
///
/// Container for the necessary parameters to execute the CreateUserProfile service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateUserProfile service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateUserProfile Operation
public virtual Task CreateUserProfileAsync(CreateUserProfileRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateUserProfileRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateUserProfileResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateWorkforce
internal virtual CreateWorkforceResponse CreateWorkforce(CreateWorkforceRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateWorkforceRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateWorkforceResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Use this operation to create a workforce. This operation will return an error if a
/// workforce already exists in the Amazon Web Services Region that you specify. You can
/// only create one workforce in each Amazon Web Services Region per Amazon Web Services
/// account.
///
///
///
/// If you want to create a new workforce in an Amazon Web Services Region where a workforce
/// already exists, use the DeleteWorkforce
/// API operation to delete the existing workforce and then use CreateWorkforce
/// to create a new workforce.
///
///
///
/// To create a private workforce using Amazon Cognito, you must specify a Cognito user
/// pool in CognitoConfig
. You can also create an Amazon Cognito workforce
/// using the Amazon SageMaker console. For more information, see
/// Create a Private Workforce (Amazon Cognito).
///
///
///
/// To create a private workforce using your own OIDC Identity Provider (IdP), specify
/// your IdP configuration in OidcConfig
. Your OIDC IdP must support groups
/// because groups are used by Ground Truth and Amazon A2I to create work teams. For more
/// information, see
/// Create a Private Workforce (OIDC IdP).
///
///
/// Container for the necessary parameters to execute the CreateWorkforce service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateWorkforce service method, as returned by SageMaker.
/// REST API Reference for CreateWorkforce Operation
public virtual Task CreateWorkforceAsync(CreateWorkforceRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateWorkforceRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateWorkforceResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region CreateWorkteam
internal virtual CreateWorkteamResponse CreateWorkteam(CreateWorkteamRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateWorkteamRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateWorkteamResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Creates a new work team for labeling your data. A work team is defined by one or more
/// Amazon Cognito user pools. You must first create the user pools before you can create
/// a work team.
///
///
///
/// You cannot create more than 25 work teams in an account and region.
///
///
/// Container for the necessary parameters to execute the CreateWorkteam service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the CreateWorkteam service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// You have exceeded an SageMaker resource limit. For example, you might have too many
/// training jobs created.
///
/// REST API Reference for CreateWorkteam Operation
public virtual Task CreateWorkteamAsync(CreateWorkteamRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = CreateWorkteamRequestMarshaller.Instance;
options.ResponseUnmarshaller = CreateWorkteamResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteAction
internal virtual DeleteActionResponse DeleteAction(DeleteActionRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteActionRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteActionResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes an action.
///
/// Container for the necessary parameters to execute the DeleteAction service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteAction service method, as returned by SageMaker.
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteAction Operation
public virtual Task DeleteActionAsync(DeleteActionRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteActionRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteActionResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteAlgorithm
internal virtual DeleteAlgorithmResponse DeleteAlgorithm(DeleteAlgorithmRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteAlgorithmRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteAlgorithmResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Removes the specified algorithm from your account.
///
/// Container for the necessary parameters to execute the DeleteAlgorithm service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteAlgorithm service method, as returned by SageMaker.
/// REST API Reference for DeleteAlgorithm Operation
public virtual Task DeleteAlgorithmAsync(DeleteAlgorithmRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteAlgorithmRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteAlgorithmResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteApp
internal virtual DeleteAppResponse DeleteApp(DeleteAppRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteAppRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteAppResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Used to stop and delete an app.
///
/// Container for the necessary parameters to execute the DeleteApp service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteApp service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteApp Operation
public virtual Task DeleteAppAsync(DeleteAppRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteAppRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteAppResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteAppImageConfig
internal virtual DeleteAppImageConfigResponse DeleteAppImageConfig(DeleteAppImageConfigRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteAppImageConfigRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteAppImageConfigResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes an AppImageConfig.
///
/// Container for the necessary parameters to execute the DeleteAppImageConfig service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteAppImageConfig service method, as returned by SageMaker.
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteAppImageConfig Operation
public virtual Task DeleteAppImageConfigAsync(DeleteAppImageConfigRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteAppImageConfigRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteAppImageConfigResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteArtifact
internal virtual DeleteArtifactResponse DeleteArtifact(DeleteArtifactRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteArtifactRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteArtifactResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes an artifact. Either ArtifactArn
or Source
must be
/// specified.
///
/// Container for the necessary parameters to execute the DeleteArtifact service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteArtifact service method, as returned by SageMaker.
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteArtifact Operation
public virtual Task DeleteArtifactAsync(DeleteArtifactRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteArtifactRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteArtifactResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteAssociation
internal virtual DeleteAssociationResponse DeleteAssociation(DeleteAssociationRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteAssociationRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteAssociationResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes an association.
///
/// Container for the necessary parameters to execute the DeleteAssociation service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteAssociation service method, as returned by SageMaker.
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteAssociation Operation
public virtual Task DeleteAssociationAsync(DeleteAssociationRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteAssociationRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteAssociationResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteCodeRepository
internal virtual DeleteCodeRepositoryResponse DeleteCodeRepository(DeleteCodeRepositoryRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteCodeRepositoryRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteCodeRepositoryResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes the specified Git repository from your account.
///
/// Container for the necessary parameters to execute the DeleteCodeRepository service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteCodeRepository service method, as returned by SageMaker.
/// REST API Reference for DeleteCodeRepository Operation
public virtual Task DeleteCodeRepositoryAsync(DeleteCodeRepositoryRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteCodeRepositoryRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteCodeRepositoryResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteContext
internal virtual DeleteContextResponse DeleteContext(DeleteContextRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteContextRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteContextResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes an context.
///
/// Container for the necessary parameters to execute the DeleteContext service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteContext service method, as returned by SageMaker.
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteContext Operation
public virtual Task DeleteContextAsync(DeleteContextRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteContextRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteContextResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteDataQualityJobDefinition
internal virtual DeleteDataQualityJobDefinitionResponse DeleteDataQualityJobDefinition(DeleteDataQualityJobDefinitionRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteDataQualityJobDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteDataQualityJobDefinitionResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes a data quality monitoring job definition.
///
/// Container for the necessary parameters to execute the DeleteDataQualityJobDefinition service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteDataQualityJobDefinition service method, as returned by SageMaker.
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteDataQualityJobDefinition Operation
public virtual Task DeleteDataQualityJobDefinitionAsync(DeleteDataQualityJobDefinitionRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteDataQualityJobDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteDataQualityJobDefinitionResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteDeviceFleet
internal virtual DeleteDeviceFleetResponse DeleteDeviceFleet(DeleteDeviceFleetRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteDeviceFleetRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteDeviceFleetResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes a fleet.
///
/// Container for the necessary parameters to execute the DeleteDeviceFleet service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteDeviceFleet service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
/// REST API Reference for DeleteDeviceFleet Operation
public virtual Task DeleteDeviceFleetAsync(DeleteDeviceFleetRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteDeviceFleetRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteDeviceFleetResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteDomain
internal virtual DeleteDomainResponse DeleteDomain(DeleteDomainRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteDomainRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteDomainResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Used to delete a domain. If you onboarded with IAM mode, you will need to delete your
/// domain to onboard again using IAM Identity Center. Use with caution. All of the members
/// of the domain will lose access to their EFS volume, including data, notebooks, and
/// other artifacts.
///
/// Container for the necessary parameters to execute the DeleteDomain service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteDomain service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteDomain Operation
public virtual Task DeleteDomainAsync(DeleteDomainRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteDomainRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteDomainResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteEdgeDeploymentPlan
internal virtual DeleteEdgeDeploymentPlanResponse DeleteEdgeDeploymentPlan(DeleteEdgeDeploymentPlanRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteEdgeDeploymentPlanRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteEdgeDeploymentPlanResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes an edge deployment plan if (and only if) all the stages in the plan are inactive
/// or there are no stages in the plan.
///
/// Container for the necessary parameters to execute the DeleteEdgeDeploymentPlan service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteEdgeDeploymentPlan service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
/// REST API Reference for DeleteEdgeDeploymentPlan Operation
public virtual Task DeleteEdgeDeploymentPlanAsync(DeleteEdgeDeploymentPlanRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteEdgeDeploymentPlanRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteEdgeDeploymentPlanResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteEdgeDeploymentStage
internal virtual DeleteEdgeDeploymentStageResponse DeleteEdgeDeploymentStage(DeleteEdgeDeploymentStageRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteEdgeDeploymentStageRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteEdgeDeploymentStageResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Delete a stage in an edge deployment plan if (and only if) the stage is inactive.
///
/// Container for the necessary parameters to execute the DeleteEdgeDeploymentStage service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteEdgeDeploymentStage service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
/// REST API Reference for DeleteEdgeDeploymentStage Operation
public virtual Task DeleteEdgeDeploymentStageAsync(DeleteEdgeDeploymentStageRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteEdgeDeploymentStageRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteEdgeDeploymentStageResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteEndpoint
internal virtual DeleteEndpointResponse DeleteEndpoint(DeleteEndpointRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteEndpointRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteEndpointResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes an endpoint. SageMaker frees up all of the resources that were deployed when
/// the endpoint was created.
///
///
///
/// SageMaker retires any custom KMS key grants associated with the endpoint, meaning
/// you don't need to use the RevokeGrant
/// API call.
///
///
///
/// When you delete your endpoint, SageMaker asynchronously deletes associated endpoint
/// resources such as KMS key grants. You might still see these resources in your account
/// for a few minutes after deleting your endpoint. Do not delete or revoke the permissions
/// for your ExecutionRoleArn
///
, otherwise SageMaker cannot delete these resources.
///
///
/// Container for the necessary parameters to execute the DeleteEndpoint service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteEndpoint service method, as returned by SageMaker.
/// REST API Reference for DeleteEndpoint Operation
public virtual Task DeleteEndpointAsync(DeleteEndpointRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteEndpointRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteEndpointResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteEndpointConfig
internal virtual DeleteEndpointConfigResponse DeleteEndpointConfig(DeleteEndpointConfigRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteEndpointConfigRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteEndpointConfigResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes an endpoint configuration. The DeleteEndpointConfig
API deletes
/// only the specified configuration. It does not delete endpoints created using the configuration.
///
///
///
///
/// You must not delete an EndpointConfig
in use by an endpoint that is live
/// or while the UpdateEndpoint
or CreateEndpoint
operations
/// are being performed on the endpoint. If you delete the EndpointConfig
/// of an endpoint that is active or being created or updated you may lose visibility
/// into the instance type the endpoint is using. The endpoint must be deleted in order
/// to stop incurring charges.
///
///
/// Container for the necessary parameters to execute the DeleteEndpointConfig service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteEndpointConfig service method, as returned by SageMaker.
/// REST API Reference for DeleteEndpointConfig Operation
public virtual Task DeleteEndpointConfigAsync(DeleteEndpointConfigRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteEndpointConfigRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteEndpointConfigResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteExperiment
internal virtual DeleteExperimentResponse DeleteExperiment(DeleteExperimentRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteExperimentRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteExperimentResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes an SageMaker experiment. All trials associated with the experiment must be
/// deleted first. Use the ListTrials
/// API to get a list of the trials associated with the experiment.
///
/// Container for the necessary parameters to execute the DeleteExperiment service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteExperiment service method, as returned by SageMaker.
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteExperiment Operation
public virtual Task DeleteExperimentAsync(DeleteExperimentRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteExperimentRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteExperimentResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteFeatureGroup
internal virtual DeleteFeatureGroupResponse DeleteFeatureGroup(DeleteFeatureGroupRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteFeatureGroupRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteFeatureGroupResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Delete the FeatureGroup
and any data that was written to the OnlineStore
/// of the FeatureGroup
. Data cannot be accessed from the OnlineStore
/// immediately after DeleteFeatureGroup
is called.
///
///
///
/// Data written into the OfflineStore
will not be deleted. The Amazon Web
/// Services Glue database and tables that are automatically created for your OfflineStore
/// are not deleted.
///
///
/// Container for the necessary parameters to execute the DeleteFeatureGroup service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteFeatureGroup service method, as returned by SageMaker.
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteFeatureGroup Operation
public virtual Task DeleteFeatureGroupAsync(DeleteFeatureGroupRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteFeatureGroupRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteFeatureGroupResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteFlowDefinition
internal virtual DeleteFlowDefinitionResponse DeleteFlowDefinition(DeleteFlowDefinitionRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteFlowDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteFlowDefinitionResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes the specified flow definition.
///
/// Container for the necessary parameters to execute the DeleteFlowDefinition service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteFlowDefinition service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteFlowDefinition Operation
public virtual Task DeleteFlowDefinitionAsync(DeleteFlowDefinitionRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteFlowDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteFlowDefinitionResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteHub
internal virtual DeleteHubResponse DeleteHub(DeleteHubRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteHubRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteHubResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Delete a hub.
///
///
///
/// Hub APIs are only callable through SageMaker Studio.
///
///
///
/// Container for the necessary parameters to execute the DeleteHub service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteHub service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteHub Operation
public virtual Task DeleteHubAsync(DeleteHubRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteHubRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteHubResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteHubContent
internal virtual DeleteHubContentResponse DeleteHubContent(DeleteHubContentRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteHubContentRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteHubContentResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Delete the contents of a hub.
///
///
///
/// Hub APIs are only callable through SageMaker Studio.
///
///
///
/// Container for the necessary parameters to execute the DeleteHubContent service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteHubContent service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteHubContent Operation
public virtual Task DeleteHubContentAsync(DeleteHubContentRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteHubContentRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteHubContentResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteHumanTaskUi
internal virtual DeleteHumanTaskUiResponse DeleteHumanTaskUi(DeleteHumanTaskUiRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteHumanTaskUiRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteHumanTaskUiResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Use this operation to delete a human task user interface (worker task template).
///
///
///
/// To see a list of human task user interfaces (work task templates) in your account,
/// use ListHumanTaskUis.
/// When you delete a worker task template, it no longer appears when you call ListHumanTaskUis
.
///
///
/// Container for the necessary parameters to execute the DeleteHumanTaskUi service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteHumanTaskUi service method, as returned by SageMaker.
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteHumanTaskUi Operation
public virtual Task DeleteHumanTaskUiAsync(DeleteHumanTaskUiRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteHumanTaskUiRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteHumanTaskUiResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteImage
internal virtual DeleteImageResponse DeleteImage(DeleteImageRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteImageRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteImageResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes a SageMaker image and all versions of the image. The container images aren't
/// deleted.
///
/// Container for the necessary parameters to execute the DeleteImage service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteImage service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteImage Operation
public virtual Task DeleteImageAsync(DeleteImageRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteImageRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteImageResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteImageVersion
internal virtual DeleteImageVersionResponse DeleteImageVersion(DeleteImageVersionRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteImageVersionRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteImageVersionResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes a version of a SageMaker image. The container image the version represents
/// isn't deleted.
///
/// Container for the necessary parameters to execute the DeleteImageVersion service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteImageVersion service method, as returned by SageMaker.
///
/// Resource being accessed is in use.
///
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteImageVersion Operation
public virtual Task DeleteImageVersionAsync(DeleteImageVersionRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteImageVersionRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteImageVersionResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteInferenceExperiment
internal virtual DeleteInferenceExperimentResponse DeleteInferenceExperiment(DeleteInferenceExperimentRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteInferenceExperimentRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteInferenceExperimentResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes an inference experiment.
///
///
///
/// This operation does not delete your endpoint, variants, or any underlying resources.
/// This operation only deletes the metadata of your experiment.
///
///
///
/// Container for the necessary parameters to execute the DeleteInferenceExperiment service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteInferenceExperiment service method, as returned by SageMaker.
///
/// There was a conflict when you attempted to modify a SageMaker entity such as an Experiment
/// or Artifact
.
///
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteInferenceExperiment Operation
public virtual Task DeleteInferenceExperimentAsync(DeleteInferenceExperimentRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteInferenceExperimentRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteInferenceExperimentResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteModel
internal virtual DeleteModelResponse DeleteModel(DeleteModelRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteModelRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteModelResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes a model. The DeleteModel
API deletes only the model entry that
/// was created in SageMaker when you called the CreateModel
API. It does
/// not delete model artifacts, inference code, or the IAM role that you specified when
/// creating the model.
///
/// Container for the necessary parameters to execute the DeleteModel service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteModel service method, as returned by SageMaker.
/// REST API Reference for DeleteModel Operation
public virtual Task DeleteModelAsync(DeleteModelRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteModelRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteModelResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteModelBiasJobDefinition
internal virtual DeleteModelBiasJobDefinitionResponse DeleteModelBiasJobDefinition(DeleteModelBiasJobDefinitionRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteModelBiasJobDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteModelBiasJobDefinitionResponseUnmarshaller.Instance;
return Invoke(request, options);
}
///
/// Deletes an Amazon SageMaker model bias job definition.
///
/// Container for the necessary parameters to execute the DeleteModelBiasJobDefinition service method.
///
/// A cancellation token that can be used by other objects or threads to receive notice of cancellation.
///
///
/// The response from the DeleteModelBiasJobDefinition service method, as returned by SageMaker.
///
/// Resource being access is not found.
///
/// REST API Reference for DeleteModelBiasJobDefinition Operation
public virtual Task DeleteModelBiasJobDefinitionAsync(DeleteModelBiasJobDefinitionRequest request, System.Threading.CancellationToken cancellationToken = default(CancellationToken))
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteModelBiasJobDefinitionRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteModelBiasJobDefinitionResponseUnmarshaller.Instance;
return InvokeAsync(request, options, cancellationToken);
}
#endregion
#region DeleteModelCard
internal virtual DeleteModelCardResponse DeleteModelCard(DeleteModelCardRequest request)
{
var options = new InvokeOptions();
options.RequestMarshaller = DeleteModelCardRequestMarshaller.Instance;
options.ResponseUnmarshaller = DeleteModelCardResponseUnmarshaller.Instance;
return Invoke