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

Interface HyperParameterTuningJobConfig.Builder

All Superinterfaces:

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

Enclosing class:

HyperParameterTuningJobConfig

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

Method Summary

Modifier and Type	Method	Description
default HyperParameterTuningJobConfig.Builder	hyperParameterTuningJobObjective(Consumer<HyperParameterTuningJobObjective.Builder> hyperParameterTuningJobObjective)	The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.
HyperParameterTuningJobConfig.Builder	hyperParameterTuningJobObjective(HyperParameterTuningJobObjective hyperParameterTuningJobObjective)	The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.
default HyperParameterTuningJobConfig.Builder	parameterRanges(Consumer<ParameterRanges.Builder> parameterRanges)	The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.
HyperParameterTuningJobConfig.Builder	parameterRanges(ParameterRanges parameterRanges)	The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.
HyperParameterTuningJobConfig.Builder	randomSeed(Integer randomSeed)	A value used to initialize a pseudo-random number generator.
default HyperParameterTuningJobConfig.Builder	resourceLimits(Consumer<ResourceLimits.Builder> resourceLimits)	The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.
HyperParameterTuningJobConfig.Builder	resourceLimits(ResourceLimits resourceLimits)	The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.
HyperParameterTuningJobConfig.Builder	strategy(String strategy)	Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches.
HyperParameterTuningJobConfig.Builder	strategy(HyperParameterTuningJobStrategyType strategy)	Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches.
default HyperParameterTuningJobConfig.Builder	strategyConfig(Consumer<HyperParameterTuningJobStrategyConfig.Builder> strategyConfig)	The configuration for the Hyperband optimization strategy.
HyperParameterTuningJobConfig.Builder	strategyConfig(HyperParameterTuningJobStrategyConfig strategyConfig)	The configuration for the Hyperband optimization strategy.
HyperParameterTuningJobConfig.Builder	trainingJobEarlyStoppingType(String trainingJobEarlyStoppingType)	Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job.
HyperParameterTuningJobConfig.Builder	trainingJobEarlyStoppingType(TrainingJobEarlyStoppingType trainingJobEarlyStoppingType)	Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job.
default HyperParameterTuningJobConfig.Builder	tuningJobCompletionCriteria(Consumer<TuningJobCompletionCriteria.Builder> tuningJobCompletionCriteria)	The tuning job's completion criteria.
HyperParameterTuningJobConfig.Builder	tuningJobCompletionCriteria(TuningJobCompletionCriteria tuningJobCompletionCriteria)	The tuning job's completion criteria.

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, sdkFieldNameToField, sdkFields

Method Detail

strategy

HyperParameterTuningJobConfig.Builder strategy(String strategy)

Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see How Hyperparameter Tuning Works.

Parameters:

strategy - Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see How Hyperparameter Tuning Works.

Returns:

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

See Also:

HyperParameterTuningJobStrategyType, HyperParameterTuningJobStrategyType

strategy

HyperParameterTuningJobConfig.Builder strategy(HyperParameterTuningJobStrategyType strategy)

Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see How Hyperparameter Tuning Works.

Parameters:

strategy - Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see How Hyperparameter Tuning Works.

Returns:

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

See Also:

HyperParameterTuningJobStrategyType, HyperParameterTuningJobStrategyType

strategyConfig

HyperParameterTuningJobConfig.Builder strategyConfig(HyperParameterTuningJobStrategyConfig strategyConfig)

The configuration for the Hyperband optimization strategy. This parameter should be provided only if Hyperband is selected as the strategy for HyperParameterTuningJobConfig.

Parameters:

strategyConfig - The configuration for the Hyperband optimization strategy. This parameter should be provided only if Hyperband is selected as the strategy for HyperParameterTuningJobConfig.

Returns:

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

strategyConfig

default HyperParameterTuningJobConfig.Builder strategyConfig(Consumer<HyperParameterTuningJobStrategyConfig.Builder> strategyConfig)

The configuration for the Hyperband optimization strategy. This parameter should be provided only if Hyperband is selected as the strategy for HyperParameterTuningJobConfig.

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

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

Parameters:

strategyConfig - a consumer that will call methods on HyperParameterTuningJobStrategyConfig.Builder

Returns:

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

See Also:

strategyConfig(HyperParameterTuningJobStrategyConfig)

hyperParameterTuningJobObjective

HyperParameterTuningJobConfig.Builder hyperParameterTuningJobObjective(HyperParameterTuningJobObjective hyperParameterTuningJobObjective)

The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.

Parameters:

hyperParameterTuningJobObjective - The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.

Returns:

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

hyperParameterTuningJobObjective

default HyperParameterTuningJobConfig.Builder hyperParameterTuningJobObjective(Consumer<HyperParameterTuningJobObjective.Builder> hyperParameterTuningJobObjective)

The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.

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 hyperParameterTuningJobObjective(HyperParameterTuningJobObjective).

Parameters:

hyperParameterTuningJobObjective - 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:

hyperParameterTuningJobObjective(HyperParameterTuningJobObjective)

resourceLimits

HyperParameterTuningJobConfig.Builder resourceLimits(ResourceLimits resourceLimits)

The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.

Parameters:

resourceLimits - The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.

Returns:

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

resourceLimits

default HyperParameterTuningJobConfig.Builder resourceLimits(Consumer<ResourceLimits.Builder> resourceLimits)

The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.

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

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

Parameters:

resourceLimits - a consumer that will call methods on ResourceLimits.Builder

Returns:

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

See Also:

resourceLimits(ResourceLimits)

parameterRanges

HyperParameterTuningJobConfig.Builder parameterRanges(ParameterRanges parameterRanges)

The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.

Parameters:

parameterRanges - The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.

Returns:

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

parameterRanges

default HyperParameterTuningJobConfig.Builder parameterRanges(Consumer<ParameterRanges.Builder> parameterRanges)

The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.

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 parameterRanges(ParameterRanges).

Parameters:

parameterRanges - 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:

parameterRanges(ParameterRanges)

trainingJobEarlyStoppingType

HyperParameterTuningJobConfig.Builder trainingJobEarlyStoppingType(String trainingJobEarlyStoppingType)

Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the Hyperband strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType must be OFF to use Hyperband. This parameter can take on one of the following values (the default value is OFF):

OFF

Training jobs launched by the hyperparameter tuning job do not use early stopping.

AUTO

SageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see Stop Training Jobs Early.

Parameters:

trainingJobEarlyStoppingType - Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the Hyperband strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType must be OFF to use Hyperband. This parameter can take on one of the following values (the default value is OFF):

OFF

Training jobs launched by the hyperparameter tuning job do not use early stopping.

AUTO

SageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see Stop Training Jobs Early.

Returns:

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

See Also:

TrainingJobEarlyStoppingType, TrainingJobEarlyStoppingType

trainingJobEarlyStoppingType

HyperParameterTuningJobConfig.Builder trainingJobEarlyStoppingType(TrainingJobEarlyStoppingType trainingJobEarlyStoppingType)

Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the Hyperband strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType must be OFF to use Hyperband. This parameter can take on one of the following values (the default value is OFF):

OFF

Training jobs launched by the hyperparameter tuning job do not use early stopping.

AUTO

SageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see Stop Training Jobs Early.

Parameters:

trainingJobEarlyStoppingType - Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the Hyperband strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType must be OFF to use Hyperband. This parameter can take on one of the following values (the default value is OFF):

OFF

Training jobs launched by the hyperparameter tuning job do not use early stopping.

AUTO

SageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see Stop Training Jobs Early.

Returns:

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

See Also:

TrainingJobEarlyStoppingType, TrainingJobEarlyStoppingType

tuningJobCompletionCriteria

HyperParameterTuningJobConfig.Builder tuningJobCompletionCriteria(TuningJobCompletionCriteria tuningJobCompletionCriteria)

The tuning job's completion criteria.

Parameters:

tuningJobCompletionCriteria - The tuning job's completion criteria.

Returns:

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

tuningJobCompletionCriteria

default HyperParameterTuningJobConfig.Builder tuningJobCompletionCriteria(Consumer<TuningJobCompletionCriteria.Builder> tuningJobCompletionCriteria)

The tuning job's completion criteria.

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

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

Parameters:

tuningJobCompletionCriteria - a consumer that will call methods on TuningJobCompletionCriteria.Builder

Returns:

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

See Also:

tuningJobCompletionCriteria(TuningJobCompletionCriteria)

randomSeed

HyperParameterTuningJobConfig.Builder randomSeed(Integer randomSeed)

A value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.

Parameters:

randomSeed - A value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.

Returns:

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