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

Interface CreateHyperParameterTuningJobRequest.Builder

All Superinterfaces:

AwsRequest.Builder, Buildable, CopyableBuilder<CreateHyperParameterTuningJobRequest.Builder,CreateHyperParameterTuningJobRequest>, SageMakerRequest.Builder, SdkBuilder<CreateHyperParameterTuningJobRequest.Builder,CreateHyperParameterTuningJobRequest>, SdkPojo, SdkRequest.Builder

Enclosing class:

CreateHyperParameterTuningJobRequest

public static interface CreateHyperParameterTuningJobRequest.Builder
extends SageMakerRequest.Builder, SdkPojo, CopyableBuilder<CreateHyperParameterTuningJobRequest.Builder,CreateHyperParameterTuningJobRequest>

Method Summary

Modifier and Type	Method	Description
default CreateHyperParameterTuningJobRequest.Builder	autotune(Consumer<Autotune.Builder> autotune)	Configures SageMaker Automatic model tuning (AMT) to automatically find optimal parameters for the following fields:
CreateHyperParameterTuningJobRequest.Builder	autotune(Autotune autotune)	Configures SageMaker Automatic model tuning (AMT) to automatically find optimal parameters for the following fields:
default CreateHyperParameterTuningJobRequest.Builder	hyperParameterTuningJobConfig(Consumer<HyperParameterTuningJobConfig.Builder> hyperParameterTuningJobConfig)	The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job.
CreateHyperParameterTuningJobRequest.Builder	hyperParameterTuningJobConfig(HyperParameterTuningJobConfig hyperParameterTuningJobConfig)	The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job.
CreateHyperParameterTuningJobRequest.Builder	hyperParameterTuningJobName(String hyperParameterTuningJobName)	The name of the tuning job.
CreateHyperParameterTuningJobRequest.Builder	overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)	Add an optional request override configuration.
CreateHyperParameterTuningJobRequest.Builder	overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)	Add an optional request override configuration.
CreateHyperParameterTuningJobRequest.Builder	tags(Collection<Tag> tags)	An array of key-value pairs.
CreateHyperParameterTuningJobRequest.Builder	tags(Consumer<Tag.Builder>... tags)	An array of key-value pairs.
CreateHyperParameterTuningJobRequest.Builder	tags(Tag... tags)	An array of key-value pairs.
default CreateHyperParameterTuningJobRequest.Builder	trainingJobDefinition(Consumer<HyperParameterTrainingJobDefinition.Builder> trainingJobDefinition)	The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.
CreateHyperParameterTuningJobRequest.Builder	trainingJobDefinition(HyperParameterTrainingJobDefinition trainingJobDefinition)	The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.
CreateHyperParameterTuningJobRequest.Builder	trainingJobDefinitions(Collection<HyperParameterTrainingJobDefinition> trainingJobDefinitions)	A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
CreateHyperParameterTuningJobRequest.Builder	trainingJobDefinitions(Consumer<HyperParameterTrainingJobDefinition.Builder>... trainingJobDefinitions)	A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
CreateHyperParameterTuningJobRequest.Builder	trainingJobDefinitions(HyperParameterTrainingJobDefinition... trainingJobDefinitions)	A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
default CreateHyperParameterTuningJobRequest.Builder	warmStartConfig(Consumer<HyperParameterTuningJobWarmStartConfig.Builder> warmStartConfig)	Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point.
CreateHyperParameterTuningJobRequest.Builder	warmStartConfig(HyperParameterTuningJobWarmStartConfig warmStartConfig)	Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point.

Methods inherited from interface software.amazon.awssdk.awscore.AwsRequest.Builder

overrideConfiguration

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

copy

Methods inherited from interface software.amazon.awssdk.services.sagemaker.model.SageMakerRequest.Builder

build

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

applyMutation, build

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

equalsBySdkFields, sdkFields

Method Details

hyperParameterTuningJobName

CreateHyperParameterTuningJobRequest.Builder hyperParameterTuningJobName(String hyperParameterTuningJobName)

The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.

Parameters:

hyperParameterTuningJobName - The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.

Returns:

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

hyperParameterTuningJobConfig

CreateHyperParameterTuningJobRequest.Builder hyperParameterTuningJobConfig(HyperParameterTuningJobConfig hyperParameterTuningJobConfig)

The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see How Hyperparameter Tuning Works.

Parameters:

hyperParameterTuningJobConfig - The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see How Hyperparameter Tuning Works.

Returns:

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

hyperParameterTuningJobConfig

default CreateHyperParameterTuningJobRequest.Builder hyperParameterTuningJobConfig(Consumer<HyperParameterTuningJobConfig.Builder> hyperParameterTuningJobConfig)

The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see How Hyperparameter Tuning Works.

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

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

Parameters:

hyperParameterTuningJobConfig - a consumer that will call methods on HyperParameterTuningJobConfig.Builder

Returns:

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

See Also:

• hyperParameterTuningJobConfig(HyperParameterTuningJobConfig)

trainingJobDefinition

CreateHyperParameterTuningJobRequest.Builder trainingJobDefinition(HyperParameterTrainingJobDefinition trainingJobDefinition)

The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.

Parameters:

trainingJobDefinition - The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.

Returns:

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

trainingJobDefinition

default CreateHyperParameterTuningJobRequest.Builder trainingJobDefinition(Consumer<HyperParameterTrainingJobDefinition.Builder> trainingJobDefinition)

The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.

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

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

Parameters:

trainingJobDefinition - a consumer that will call methods on HyperParameterTrainingJobDefinition.Builder

Returns:

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

See Also:

• trainingJobDefinition(HyperParameterTrainingJobDefinition)

trainingJobDefinitions

CreateHyperParameterTuningJobRequest.Builder trainingJobDefinitions(Collection<HyperParameterTrainingJobDefinition> trainingJobDefinitions)

A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.

Parameters:

trainingJobDefinitions - A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.

Returns:

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

trainingJobDefinitions

CreateHyperParameterTuningJobRequest.Builder trainingJobDefinitions(HyperParameterTrainingJobDefinition... trainingJobDefinitions)

A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.

Parameters:

trainingJobDefinitions - A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.

Returns:

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

trainingJobDefinitions

CreateHyperParameterTuningJobRequest.Builder trainingJobDefinitions(Consumer<HyperParameterTrainingJobDefinition.Builder>... trainingJobDefinitions)

A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.

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

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to trainingJobDefinitions(List<HyperParameterTrainingJobDefinition>).

Parameters:

trainingJobDefinitions - a consumer that will call methods on HyperParameterTrainingJobDefinition.Builder

Returns:

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

See Also:

• trainingJobDefinitions(java.util.Collection<HyperParameterTrainingJobDefinition>)

warmStartConfig

CreateHyperParameterTuningJobRequest.Builder warmStartConfig(HyperParameterTuningJobWarmStartConfig warmStartConfig)

Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.

All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM as the WarmStartType value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.

All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.

Parameters:

warmStartConfig - Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.

All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM as the WarmStartType value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.

All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.

Returns:

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

warmStartConfig

default CreateHyperParameterTuningJobRequest.Builder warmStartConfig(Consumer<HyperParameterTuningJobWarmStartConfig.Builder> warmStartConfig)

Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.

All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM as the WarmStartType value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.

All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.

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

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

Parameters:

warmStartConfig - a consumer that will call methods on HyperParameterTuningJobWarmStartConfig.Builder

Returns:

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

See Also:

• warmStartConfig(HyperParameterTuningJobWarmStartConfig)

tags

CreateHyperParameterTuningJobRequest.Builder tags(Collection<Tag> tags)

An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.

Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.

Parameters:

tags - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.

Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.

Returns:

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

tags

CreateHyperParameterTuningJobRequest.Builder tags(Tag... tags)

An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.

Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.

Parameters:

tags - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.

Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.

Returns:

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

tags

CreateHyperParameterTuningJobRequest.Builder tags(Consumer<Tag.Builder>... tags)

An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.

Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.

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

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to tags(List<Tag>).

Parameters:

tags - a consumer that will call methods on Tag.Builder

Returns:

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

See Also:

• tags(java.util.Collection<Tag>)

autotune

CreateHyperParameterTuningJobRequest.Builder autotune(Autotune autotune)

Configures SageMaker Automatic model tuning (AMT) to automatically find optimal parameters for the following fields:

• ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.

• ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.

• TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.

• RetryStrategy: The number of times to retry a training job.

• Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.

• ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.

Parameters:

autotune - Configures SageMaker Automatic model tuning (AMT) to automatically find optimal parameters for the following fields:

• ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.

• ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.

• TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.

• RetryStrategy: The number of times to retry a training job.

• Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.

• ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.

Returns:

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

autotune

default CreateHyperParameterTuningJobRequest.Builder autotune(Consumer<Autotune.Builder> autotune)

Configures SageMaker Automatic model tuning (AMT) to automatically find optimal parameters for the following fields:

• ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.

• ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.

• TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.

• RetryStrategy: The number of times to retry a training job.

• Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.

• ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.

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

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

Parameters:

autotune - a consumer that will call methods on Autotune.Builder

Returns:

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

See Also:

• autotune(Autotune)

overrideConfiguration

CreateHyperParameterTuningJobRequest.Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)

Description copied from interface: AwsRequest.Builder

Add an optional request override configuration.

Specified by:

overrideConfiguration in interface AwsRequest.Builder

Parameters:

overrideConfiguration - The override configuration.

Returns:

This object for method chaining.

overrideConfiguration

CreateHyperParameterTuningJobRequest.Builder overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)

Description copied from interface: AwsRequest.Builder

Add an optional request override configuration.

Specified by:

overrideConfiguration in interface AwsRequest.Builder

Parameters:

builderConsumer - A Consumer to which an empty AwsRequestOverrideConfiguration.Builder will be given.

Returns:

This object for method chaining.