Package software.amazon.awssdk.services.sagemaker.model

Interface HyperParameterTrainingJobDefinition.Builder

All Superinterfaces:

Buildable, CopyableBuilder<HyperParameterTrainingJobDefinition.Builder,HyperParameterTrainingJobDefinition>, SdkBuilder<HyperParameterTrainingJobDefinition.Builder,HyperParameterTrainingJobDefinition>, SdkPojo

Enclosing class:

HyperParameterTrainingJobDefinition

public static interface HyperParameterTrainingJobDefinition.Builder
extends SdkPojo, CopyableBuilder<HyperParameterTrainingJobDefinition.Builder,HyperParameterTrainingJobDefinition>

Method Summary

Modifier and Type	Method	Description
default HyperParameterTrainingJobDefinition.Builder	algorithmSpecification(Consumer<HyperParameterAlgorithmSpecification.Builder> algorithmSpecification)	The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.
HyperParameterTrainingJobDefinition.Builder	algorithmSpecification(HyperParameterAlgorithmSpecification algorithmSpecification)	The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.
default HyperParameterTrainingJobDefinition.Builder	checkpointConfig(Consumer<CheckpointConfig.Builder> checkpointConfig)	Sets the value of the CheckpointConfig property for this object.
HyperParameterTrainingJobDefinition.Builder	checkpointConfig(CheckpointConfig checkpointConfig)	Sets the value of the CheckpointConfig property for this object.
HyperParameterTrainingJobDefinition.Builder	definitionName(String definitionName)	The job definition name.
HyperParameterTrainingJobDefinition.Builder	enableInterContainerTrafficEncryption(Boolean enableInterContainerTrafficEncryption)	To encrypt all communications between ML compute instances in distributed training, choose True.
HyperParameterTrainingJobDefinition.Builder	enableManagedSpotTraining(Boolean enableManagedSpotTraining)	A Boolean indicating whether managed spot training is enabled (True) or not (False ).
HyperParameterTrainingJobDefinition.Builder	enableNetworkIsolation(Boolean enableNetworkIsolation)	Isolates the training container.
HyperParameterTrainingJobDefinition.Builder	environment(Map<String,String> environment)	An environment variable that you can pass into the SageMaker CreateTrainingJob API.
default HyperParameterTrainingJobDefinition.Builder	hyperParameterRanges(Consumer<ParameterRanges.Builder> hyperParameterRanges)	Sets the value of the HyperParameterRanges property for this object.
HyperParameterTrainingJobDefinition.Builder	hyperParameterRanges(ParameterRanges hyperParameterRanges)	Sets the value of the HyperParameterRanges property for this object.
default HyperParameterTrainingJobDefinition.Builder	hyperParameterTuningResourceConfig(Consumer<HyperParameterTuningResourceConfig.Builder> hyperParameterTuningResourceConfig)	The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job.
HyperParameterTrainingJobDefinition.Builder	hyperParameterTuningResourceConfig(HyperParameterTuningResourceConfig hyperParameterTuningResourceConfig)	The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job.
HyperParameterTrainingJobDefinition.Builder	inputDataConfig(Collection<Channel> inputDataConfig)	An array of Channel objects that specify the input for the training jobs that the tuning job launches.
HyperParameterTrainingJobDefinition.Builder	inputDataConfig(Consumer<Channel.Builder>... inputDataConfig)	An array of Channel objects that specify the input for the training jobs that the tuning job launches.
HyperParameterTrainingJobDefinition.Builder	inputDataConfig(Channel... inputDataConfig)	An array of Channel objects that specify the input for the training jobs that the tuning job launches.
default HyperParameterTrainingJobDefinition.Builder	outputDataConfig(Consumer<OutputDataConfig.Builder> outputDataConfig)	Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
HyperParameterTrainingJobDefinition.Builder	outputDataConfig(OutputDataConfig outputDataConfig)	Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
default HyperParameterTrainingJobDefinition.Builder	resourceConfig(Consumer<ResourceConfig.Builder> resourceConfig)	The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
HyperParameterTrainingJobDefinition.Builder	resourceConfig(ResourceConfig resourceConfig)	The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
default HyperParameterTrainingJobDefinition.Builder	retryStrategy(Consumer<RetryStrategy.Builder> retryStrategy)	The number of times to retry the job when the job fails due to an InternalServerError.
HyperParameterTrainingJobDefinition.Builder	retryStrategy(RetryStrategy retryStrategy)	The number of times to retry the job when the job fails due to an InternalServerError.
HyperParameterTrainingJobDefinition.Builder	roleArn(String roleArn)	The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
HyperParameterTrainingJobDefinition.Builder	staticHyperParameters(Map<String,String> staticHyperParameters)	Specifies the values of hyperparameters that do not change for the tuning job.
default HyperParameterTrainingJobDefinition.Builder	stoppingCondition(Consumer<StoppingCondition.Builder> stoppingCondition)	Specifies a limit to how long a model hyperparameter training job can run.
HyperParameterTrainingJobDefinition.Builder	stoppingCondition(StoppingCondition stoppingCondition)	Specifies a limit to how long a model hyperparameter training job can run.
default HyperParameterTrainingJobDefinition.Builder	tuningObjective(Consumer<HyperParameterTuningJobObjective.Builder> tuningObjective)	Sets the value of the TuningObjective property for this object.
HyperParameterTrainingJobDefinition.Builder	tuningObjective(HyperParameterTuningJobObjective tuningObjective)	Sets the value of the TuningObjective property for this object.
default HyperParameterTrainingJobDefinition.Builder	vpcConfig(Consumer<VpcConfig.Builder> vpcConfig)	The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to.
HyperParameterTrainingJobDefinition.Builder	vpcConfig(VpcConfig vpcConfig)	The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to.

Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder

copy

Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder

applyMutation, build

Methods inherited from interface software.amazon.awssdk.core.SdkPojo

equalsBySdkFields, sdkFields

Method Detail

definitionName

HyperParameterTrainingJobDefinition.Builder definitionName(String definitionName)

The job definition name.

Parameters:

definitionName - The job definition name.

Returns:

Returns a reference to this object so that method calls can be chained together.

tuningObjective

HyperParameterTrainingJobDefinition.Builder tuningObjective(HyperParameterTuningJobObjective tuningObjective)

Sets the value of the TuningObjective property for this object.

Parameters:

tuningObjective - The new value for the TuningObjective property for this object.

Returns:

Returns a reference to this object so that method calls can be chained together.

tuningObjective

default HyperParameterTrainingJobDefinition.Builder tuningObjective(Consumer<HyperParameterTuningJobObjective.Builder> tuningObjective)

Sets the value of the TuningObjective property for this object. This is a convenience method that creates an instance of the HyperParameterTuningJobObjective.Builder avoiding the need to create one manually via HyperParameterTuningJobObjective.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to tuningObjective(HyperParameterTuningJobObjective).

Parameters:

tuningObjective - a consumer that will call methods on HyperParameterTuningJobObjective.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

tuningObjective(HyperParameterTuningJobObjective)

hyperParameterRanges

HyperParameterTrainingJobDefinition.Builder hyperParameterRanges(ParameterRanges hyperParameterRanges)

Sets the value of the HyperParameterRanges property for this object.

Parameters:

hyperParameterRanges - The new value for the HyperParameterRanges property for this object.

Returns:

Returns a reference to this object so that method calls can be chained together.

hyperParameterRanges

default HyperParameterTrainingJobDefinition.Builder hyperParameterRanges(Consumer<ParameterRanges.Builder> hyperParameterRanges)

Sets the value of the HyperParameterRanges property for this object. This is a convenience method that creates an instance of the ParameterRanges.Builder avoiding the need to create one manually via ParameterRanges.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to hyperParameterRanges(ParameterRanges).

Parameters:

hyperParameterRanges - a consumer that will call methods on ParameterRanges.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

hyperParameterRanges(ParameterRanges)

staticHyperParameters

HyperParameterTrainingJobDefinition.Builder staticHyperParameters(Map<String,String> staticHyperParameters)

Specifies the values of hyperparameters that do not change for the tuning job.

Parameters:

staticHyperParameters - Specifies the values of hyperparameters that do not change for the tuning job.

Returns:

Returns a reference to this object so that method calls can be chained together.

algorithmSpecification

HyperParameterTrainingJobDefinition.Builder algorithmSpecification(HyperParameterAlgorithmSpecification algorithmSpecification)

The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.

Parameters:

algorithmSpecification - The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.

Returns:

Returns a reference to this object so that method calls can be chained together.

algorithmSpecification

default HyperParameterTrainingJobDefinition.Builder algorithmSpecification(Consumer<HyperParameterAlgorithmSpecification.Builder> algorithmSpecification)

The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.

This is a convenience method that creates an instance of the HyperParameterAlgorithmSpecification.Builder avoiding the need to create one manually via HyperParameterAlgorithmSpecification.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to algorithmSpecification(HyperParameterAlgorithmSpecification).

Parameters:

algorithmSpecification - a consumer that will call methods on HyperParameterAlgorithmSpecification.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

algorithmSpecification(HyperParameterAlgorithmSpecification)

roleArn

HyperParameterTrainingJobDefinition.Builder roleArn(String roleArn)

The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.

Parameters:

roleArn - The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.

Returns:

Returns a reference to this object so that method calls can be chained together.

inputDataConfig

HyperParameterTrainingJobDefinition.Builder inputDataConfig(Collection<Channel> inputDataConfig)

An array of Channel objects that specify the input for the training jobs that the tuning job launches.

Parameters:

inputDataConfig - An array of Channel objects that specify the input for the training jobs that the tuning job launches.

Returns:

Returns a reference to this object so that method calls can be chained together.

inputDataConfig

HyperParameterTrainingJobDefinition.Builder inputDataConfig(Channel... inputDataConfig)

An array of Channel objects that specify the input for the training jobs that the tuning job launches.

Parameters:

inputDataConfig - An array of Channel objects that specify the input for the training jobs that the tuning job launches.

Returns:

Returns a reference to this object so that method calls can be chained together.

inputDataConfig

HyperParameterTrainingJobDefinition.Builder inputDataConfig(Consumer<Channel.Builder>... inputDataConfig)

An array of Channel objects that specify the input for the training jobs that the tuning job launches.

This is a convenience method that creates an instance of the Channel.Builder avoiding the need to create one manually via Channel.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to #inputDataConfig(List).

Parameters:

inputDataConfig - a consumer that will call methods on Channel.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

#inputDataConfig(java.util.Collection)

vpcConfig

HyperParameterTrainingJobDefinition.Builder vpcConfig(VpcConfig vpcConfig)

The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Parameters:

vpcConfig - The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Returns:

Returns a reference to this object so that method calls can be chained together.

vpcConfig

default HyperParameterTrainingJobDefinition.Builder vpcConfig(Consumer<VpcConfig.Builder> vpcConfig)

The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

This is a convenience method that creates an instance of the VpcConfig.Builder avoiding the need to create one manually via VpcConfig.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to vpcConfig(VpcConfig).

Parameters:

vpcConfig - a consumer that will call methods on VpcConfig.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

vpcConfig(VpcConfig)

outputDataConfig

HyperParameterTrainingJobDefinition.Builder outputDataConfig(OutputDataConfig outputDataConfig)

Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.

Parameters:

outputDataConfig - Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.

Returns:

Returns a reference to this object so that method calls can be chained together.

outputDataConfig

default HyperParameterTrainingJobDefinition.Builder outputDataConfig(Consumer<OutputDataConfig.Builder> outputDataConfig)

Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.

This is a convenience method that creates an instance of the OutputDataConfig.Builder avoiding the need to create one manually via OutputDataConfig.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to outputDataConfig(OutputDataConfig).

Parameters:

outputDataConfig - a consumer that will call methods on OutputDataConfig.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

outputDataConfig(OutputDataConfig)

resourceConfig

HyperParameterTrainingJobDefinition.Builder resourceConfig(ResourceConfig resourceConfig)

The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.

Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.

If you want to use hyperparameter optimization with instance type flexibility, use HyperParameterTuningResourceConfig instead.

Parameters:

resourceConfig - The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.

Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.

If you want to use hyperparameter optimization with instance type flexibility, use HyperParameterTuningResourceConfig instead.

Returns:

Returns a reference to this object so that method calls can be chained together.

resourceConfig

default HyperParameterTrainingJobDefinition.Builder resourceConfig(Consumer<ResourceConfig.Builder> resourceConfig)

The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.

Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.

If you want to use hyperparameter optimization with instance type flexibility, use HyperParameterTuningResourceConfig instead.

This is a convenience method that creates an instance of the ResourceConfig.Builder avoiding the need to create one manually via ResourceConfig.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to resourceConfig(ResourceConfig).

Parameters:

resourceConfig - a consumer that will call methods on ResourceConfig.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

resourceConfig(ResourceConfig)

hyperParameterTuningResourceConfig

HyperParameterTrainingJobDefinition.Builder hyperParameterTuningResourceConfig(HyperParameterTuningResourceConfig hyperParameterTuningResourceConfig)

The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File for TrainingInputMode in the AlgorithmSpecification parameter to additionally store training data in the storage volume (optional).

Parameters:

hyperParameterTuningResourceConfig - The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File for TrainingInputMode in the AlgorithmSpecification parameter to additionally store training data in the storage volume (optional).

Returns:

Returns a reference to this object so that method calls can be chained together.

hyperParameterTuningResourceConfig

default HyperParameterTrainingJobDefinition.Builder hyperParameterTuningResourceConfig(Consumer<HyperParameterTuningResourceConfig.Builder> hyperParameterTuningResourceConfig)

The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File for TrainingInputMode in the AlgorithmSpecification parameter to additionally store training data in the storage volume (optional).

This is a convenience method that creates an instance of the HyperParameterTuningResourceConfig.Builder avoiding the need to create one manually via HyperParameterTuningResourceConfig.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to hyperParameterTuningResourceConfig(HyperParameterTuningResourceConfig).

Parameters:

hyperParameterTuningResourceConfig - a consumer that will call methods on HyperParameterTuningResourceConfig.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

hyperParameterTuningResourceConfig(HyperParameterTuningResourceConfig)

stoppingCondition

HyperParameterTrainingJobDefinition.Builder stoppingCondition(StoppingCondition stoppingCondition)

Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.

Parameters:

stoppingCondition - Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.

Returns:

Returns a reference to this object so that method calls can be chained together.

stoppingCondition

default HyperParameterTrainingJobDefinition.Builder stoppingCondition(Consumer<StoppingCondition.Builder> stoppingCondition)

Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.

This is a convenience method that creates an instance of the StoppingCondition.Builder avoiding the need to create one manually via StoppingCondition.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to stoppingCondition(StoppingCondition).

Parameters:

stoppingCondition - a consumer that will call methods on StoppingCondition.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

stoppingCondition(StoppingCondition)

enableNetworkIsolation

HyperParameterTrainingJobDefinition.Builder enableNetworkIsolation(Boolean enableNetworkIsolation)

Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.

Parameters:

enableNetworkIsolation - Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.

Returns:

Returns a reference to this object so that method calls can be chained together.

enableInterContainerTrafficEncryption

HyperParameterTrainingJobDefinition.Builder enableInterContainerTrafficEncryption(Boolean enableInterContainerTrafficEncryption)

To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.

Parameters:

enableInterContainerTrafficEncryption - To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.

Returns:

Returns a reference to this object so that method calls can be chained together.

enableManagedSpotTraining

HyperParameterTrainingJobDefinition.Builder enableManagedSpotTraining(Boolean enableManagedSpotTraining)

A Boolean indicating whether managed spot training is enabled (True) or not (False ).

Parameters:

enableManagedSpotTraining - A Boolean indicating whether managed spot training is enabled (True) or not ( False).

Returns:

Returns a reference to this object so that method calls can be chained together.

checkpointConfig

HyperParameterTrainingJobDefinition.Builder checkpointConfig(CheckpointConfig checkpointConfig)

Sets the value of the CheckpointConfig property for this object.

Parameters:

checkpointConfig - The new value for the CheckpointConfig property for this object.

Returns:

Returns a reference to this object so that method calls can be chained together.

checkpointConfig

default HyperParameterTrainingJobDefinition.Builder checkpointConfig(Consumer<CheckpointConfig.Builder> checkpointConfig)

Sets the value of the CheckpointConfig property for this object. This is a convenience method that creates an instance of the CheckpointConfig.Builder avoiding the need to create one manually via CheckpointConfig.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to checkpointConfig(CheckpointConfig).

Parameters:

checkpointConfig - a consumer that will call methods on CheckpointConfig.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

checkpointConfig(CheckpointConfig)

retryStrategy

HyperParameterTrainingJobDefinition.Builder retryStrategy(RetryStrategy retryStrategy)

The number of times to retry the job when the job fails due to an InternalServerError.

Parameters:

retryStrategy - The number of times to retry the job when the job fails due to an InternalServerError.

Returns:

Returns a reference to this object so that method calls can be chained together.

retryStrategy

default HyperParameterTrainingJobDefinition.Builder retryStrategy(Consumer<RetryStrategy.Builder> retryStrategy)

The number of times to retry the job when the job fails due to an InternalServerError.

This is a convenience method that creates an instance of the RetryStrategy.Builder avoiding the need to create one manually via RetryStrategy.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to retryStrategy(RetryStrategy).

Parameters:

retryStrategy - a consumer that will call methods on RetryStrategy.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

retryStrategy(RetryStrategy)

environment

HyperParameterTrainingJobDefinition.Builder environment(Map<String,String> environment)

An environment variable that you can pass into the SageMaker CreateTrainingJob API. You can use an existing environment variable from the training container or use your own. See Define metrics and variables for more information.

The maximum number of items specified for Map Entries refers to the maximum number of environment variables for each TrainingJobDefinition and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of environment variables for all the training job definitions can't exceed the maximum number specified.

Parameters:

environment - An environment variable that you can pass into the SageMaker CreateTrainingJob API. You can use an existing environment variable from the training container or use your own. See Define metrics and variables for more information.

The maximum number of items specified for Map Entries refers to the maximum number of environment variables for each TrainingJobDefinition and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of environment variables for all the training job definitions can't exceed the maximum number specified.

Returns:

Returns a reference to this object so that method calls can be chained together.