Uses of Class
com.amazonaws.services.sagemaker.model.CreateTrainingJobRequest

Packages that use CreateTrainingJobRequest

Package	Description
com.amazonaws.services.sagemaker	Provides APIs for creating and managing SageMaker resources.
com.amazonaws.services.sagemaker.model

Uses of CreateTrainingJobRequest in com.amazonaws.services.sagemaker

Methods in com.amazonaws.services.sagemaker with parameters of type CreateTrainingJobRequest

Modifier and Type	Method and Description
CreateTrainingJobResult	AmazonSageMakerClient.createTrainingJob(CreateTrainingJobRequest request) Starts a model training job.
CreateTrainingJobResult	AmazonSageMaker.createTrainingJob(CreateTrainingJobRequest createTrainingJobRequest) Starts a model training job.
CreateTrainingJobResult	AbstractAmazonSageMaker.createTrainingJob(CreateTrainingJobRequest request)
Future<CreateTrainingJobResult>	AmazonSageMakerAsyncClient.createTrainingJobAsync(CreateTrainingJobRequest request)
Future<CreateTrainingJobResult>	AmazonSageMakerAsync.createTrainingJobAsync(CreateTrainingJobRequest createTrainingJobRequest) Starts a model training job.
Future<CreateTrainingJobResult>	AbstractAmazonSageMakerAsync.createTrainingJobAsync(CreateTrainingJobRequest request)
Future<CreateTrainingJobResult>	AmazonSageMakerAsyncClient.createTrainingJobAsync(CreateTrainingJobRequest request, AsyncHandler<CreateTrainingJobRequest,CreateTrainingJobResult> asyncHandler)
Future<CreateTrainingJobResult>	AmazonSageMakerAsync.createTrainingJobAsync(CreateTrainingJobRequest createTrainingJobRequest, AsyncHandler<CreateTrainingJobRequest,CreateTrainingJobResult> asyncHandler) Starts a model training job.
Future<CreateTrainingJobResult>	AbstractAmazonSageMakerAsync.createTrainingJobAsync(CreateTrainingJobRequest request, AsyncHandler<CreateTrainingJobRequest,CreateTrainingJobResult> asyncHandler)

Method parameters in com.amazonaws.services.sagemaker with type arguments of type CreateTrainingJobRequest

Modifier and Type	Method and Description
Future<CreateTrainingJobResult>	AmazonSageMakerAsyncClient.createTrainingJobAsync(CreateTrainingJobRequest request, AsyncHandler<CreateTrainingJobRequest,CreateTrainingJobResult> asyncHandler)
Future<CreateTrainingJobResult>	AmazonSageMakerAsync.createTrainingJobAsync(CreateTrainingJobRequest createTrainingJobRequest, AsyncHandler<CreateTrainingJobRequest,CreateTrainingJobResult> asyncHandler) Starts a model training job.
Future<CreateTrainingJobResult>	AbstractAmazonSageMakerAsync.createTrainingJobAsync(CreateTrainingJobRequest request, AsyncHandler<CreateTrainingJobRequest,CreateTrainingJobResult> asyncHandler)

Uses of CreateTrainingJobRequest in com.amazonaws.services.sagemaker.model

Methods in com.amazonaws.services.sagemaker.model that return CreateTrainingJobRequest

Modifier and Type	Method and Description
CreateTrainingJobRequest	CreateTrainingJobRequest.addEnvironmentEntry(String key, String value) Add a single Environment entry
CreateTrainingJobRequest	CreateTrainingJobRequest.addHyperParametersEntry(String key, String value) Add a single HyperParameters entry
CreateTrainingJobRequest	CreateTrainingJobRequest.clearEnvironmentEntries() Removes all the entries added into Environment.
CreateTrainingJobRequest	CreateTrainingJobRequest.clearHyperParametersEntries() Removes all the entries added into HyperParameters.
CreateTrainingJobRequest	CreateTrainingJobRequest.clone()
CreateTrainingJobRequest	CreateTrainingJobRequest.withAlgorithmSpecification(AlgorithmSpecification algorithmSpecification) The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata, including the input mode.
CreateTrainingJobRequest	CreateTrainingJobRequest.withCheckpointConfig(CheckpointConfig checkpointConfig) Contains information about the output location for managed spot training checkpoint data.
CreateTrainingJobRequest	CreateTrainingJobRequest.withDebugHookConfig(DebugHookConfig debugHookConfig)
CreateTrainingJobRequest	CreateTrainingJobRequest.withDebugRuleConfigurations(Collection<DebugRuleConfiguration> debugRuleConfigurations) Configuration information for Debugger rules for debugging output tensors.
CreateTrainingJobRequest	CreateTrainingJobRequest.withDebugRuleConfigurations(DebugRuleConfiguration... debugRuleConfigurations) Configuration information for Debugger rules for debugging output tensors.
CreateTrainingJobRequest	CreateTrainingJobRequest.withEnableInterContainerTrafficEncryption(Boolean enableInterContainerTrafficEncryption) To encrypt all communications between ML compute instances in distributed training, choose True.
CreateTrainingJobRequest	CreateTrainingJobRequest.withEnableManagedSpotTraining(Boolean enableManagedSpotTraining) To train models using managed spot training, choose True.
CreateTrainingJobRequest	CreateTrainingJobRequest.withEnableNetworkIsolation(Boolean enableNetworkIsolation) Isolates the training container.
CreateTrainingJobRequest	CreateTrainingJobRequest.withEnvironment(Map<String,String> environment) The environment variables to set in the Docker container.
CreateTrainingJobRequest	CreateTrainingJobRequest.withExperimentConfig(ExperimentConfig experimentConfig)
CreateTrainingJobRequest	CreateTrainingJobRequest.withHyperParameters(Map<String,String> hyperParameters) Algorithm-specific parameters that influence the quality of the model.
CreateTrainingJobRequest	CreateTrainingJobRequest.withInputDataConfig(Channel... inputDataConfig) An array of Channel objects.
CreateTrainingJobRequest	CreateTrainingJobRequest.withInputDataConfig(Collection<Channel> inputDataConfig) An array of Channel objects.
CreateTrainingJobRequest	CreateTrainingJobRequest.withOutputDataConfig(OutputDataConfig outputDataConfig) Specifies the path to the S3 location where you want to store model artifacts.
CreateTrainingJobRequest	CreateTrainingJobRequest.withProfilerConfig(ProfilerConfig profilerConfig)
CreateTrainingJobRequest	CreateTrainingJobRequest.withProfilerRuleConfigurations(Collection<ProfilerRuleConfiguration> profilerRuleConfigurations) Configuration information for Debugger rules for profiling system and framework metrics.
CreateTrainingJobRequest	CreateTrainingJobRequest.withProfilerRuleConfigurations(ProfilerRuleConfiguration... profilerRuleConfigurations) Configuration information for Debugger rules for profiling system and framework metrics.
CreateTrainingJobRequest	CreateTrainingJobRequest.withResourceConfig(ResourceConfig resourceConfig) The resources, including the ML compute instances and ML storage volumes, to use for model training.
CreateTrainingJobRequest	CreateTrainingJobRequest.withRetryStrategy(RetryStrategy retryStrategy) The number of times to retry the job when the job fails due to an InternalServerError.
CreateTrainingJobRequest	CreateTrainingJobRequest.withRoleArn(String roleArn) The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
CreateTrainingJobRequest	CreateTrainingJobRequest.withStoppingCondition(StoppingCondition stoppingCondition) Specifies a limit to how long a model training job can run.
CreateTrainingJobRequest	CreateTrainingJobRequest.withTags(Collection<Tag> tags) An array of key-value pairs.
CreateTrainingJobRequest	CreateTrainingJobRequest.withTags(Tag... tags) An array of key-value pairs.
CreateTrainingJobRequest	CreateTrainingJobRequest.withTensorBoardOutputConfig(TensorBoardOutputConfig tensorBoardOutputConfig)
CreateTrainingJobRequest	CreateTrainingJobRequest.withTrainingJobName(String trainingJobName) The name of the training job.
CreateTrainingJobRequest	CreateTrainingJobRequest.withVpcConfig(VpcConfig vpcConfig) A VpcConfig object that specifies the VPC that you want your training job to connect to.