com.amazonaws.services.sagemaker.model

Class HyperParameterTuningJobConfig

java.lang.Object

com.amazonaws.services.sagemaker.model.HyperParameterTuningJobConfig

All Implemented Interfaces:

StructuredPojo, Serializable, Cloneable

@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class HyperParameterTuningJobConfig
extends Object
implements Serializable, Cloneable, StructuredPojo

Configures a hyperparameter tuning job.

See Also:

AWS API Documentation, Serialized Form

Constructor Summary

Constructors

Constructor and Description
HyperParameterTuningJobConfig()

Method Summary

Modifier and Type	Method and Description
HyperParameterTuningJobConfig	clone()
boolean	equals(Object obj)
HyperParameterTuningJobObjective	getHyperParameterTuningJobObjective() The HyperParameterTuningJobObjective object that specifies the objective metric for this tuning job.
ParameterRanges	getParameterRanges() The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches.
ResourceLimits	getResourceLimits() The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs for this tuning job.
String	getStrategy() Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches.
String	getTrainingJobEarlyStoppingType() Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job.
int	hashCode()
void	marshall(ProtocolMarshaller protocolMarshaller) Marshalls this structured data using the given ProtocolMarshaller.
void	setHyperParameterTuningJobObjective(HyperParameterTuningJobObjective hyperParameterTuningJobObjective) The HyperParameterTuningJobObjective object that specifies the objective metric for this tuning job.
void	setParameterRanges(ParameterRanges parameterRanges) The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches.
void	setResourceLimits(ResourceLimits resourceLimits) The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs for this tuning job.
void	setStrategy(String strategy) Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches.
void	setTrainingJobEarlyStoppingType(String trainingJobEarlyStoppingType) Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job.
String	toString() Returns a string representation of this object.
HyperParameterTuningJobConfig	withHyperParameterTuningJobObjective(HyperParameterTuningJobObjective hyperParameterTuningJobObjective) The HyperParameterTuningJobObjective object that specifies the objective metric for this tuning job.
HyperParameterTuningJobConfig	withParameterRanges(ParameterRanges parameterRanges) The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches.
HyperParameterTuningJobConfig	withResourceLimits(ResourceLimits resourceLimits) The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs for this tuning job.
HyperParameterTuningJobConfig	withStrategy(HyperParameterTuningJobStrategyType strategy) Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches.
HyperParameterTuningJobConfig	withStrategy(String strategy) Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches.
HyperParameterTuningJobConfig	withTrainingJobEarlyStoppingType(String trainingJobEarlyStoppingType) Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job.
HyperParameterTuningJobConfig	withTrainingJobEarlyStoppingType(TrainingJobEarlyStoppingType trainingJobEarlyStoppingType) Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job.

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

HyperParameterTuningJobConfig

public HyperParameterTuningJobConfig()

Method Detail

setStrategy

public void setStrategy(String strategy)

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

See Also:

HyperParameterTuningJobStrategyType

getStrategy

public String getStrategy()

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

Returns:

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

See Also:

HyperParameterTuningJobStrategyType

withStrategy

public HyperParameterTuningJobConfig withStrategy(String strategy)

Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. To use the Bayesian search stategy, set this to Bayesian. To randomly search, set it to Random. 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. To use the Bayesian search stategy, set this to Bayesian. To randomly search, set it to Random. 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

withStrategy

public HyperParameterTuningJobConfig withStrategy(HyperParameterTuningJobStrategyType strategy)

Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. To use the Bayesian search stategy, set this to Bayesian. To randomly search, set it to Random. 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. To use the Bayesian search stategy, set this to Bayesian. To randomly search, set it to Random. 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

setHyperParameterTuningJobObjective

public void setHyperParameterTuningJobObjective(HyperParameterTuningJobObjective hyperParameterTuningJobObjective)

The HyperParameterTuningJobObjective object that specifies the objective metric for this tuning job.

Parameters:

hyperParameterTuningJobObjective - The HyperParameterTuningJobObjective object that specifies the objective metric for this tuning job.

getHyperParameterTuningJobObjective

public HyperParameterTuningJobObjective getHyperParameterTuningJobObjective()

The HyperParameterTuningJobObjective object that specifies the objective metric for this tuning job.

Returns:

The HyperParameterTuningJobObjective object that specifies the objective metric for this tuning job.

withHyperParameterTuningJobObjective

public HyperParameterTuningJobConfig withHyperParameterTuningJobObjective(HyperParameterTuningJobObjective hyperParameterTuningJobObjective)

The HyperParameterTuningJobObjective object that specifies the objective metric for this tuning job.

Parameters:

hyperParameterTuningJobObjective - The HyperParameterTuningJobObjective object that specifies the objective metric for this tuning job.

Returns:

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

setResourceLimits

public void setResourceLimits(ResourceLimits resourceLimits)

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

Parameters:

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

getResourceLimits

public ResourceLimits getResourceLimits()

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

Returns:

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

withResourceLimits

public HyperParameterTuningJobConfig withResourceLimits(ResourceLimits resourceLimits)

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

Parameters:

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

Returns:

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

setParameterRanges

public void setParameterRanges(ParameterRanges parameterRanges)

The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches.

Parameters:

parameterRanges - The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches.

getParameterRanges

public ParameterRanges getParameterRanges()

The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches.

Returns:

The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches.

withParameterRanges

public HyperParameterTuningJobConfig withParameterRanges(ParameterRanges parameterRanges)

The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches.

Parameters:

parameterRanges - The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches.

Returns:

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

setTrainingJobEarlyStoppingType

public void setTrainingJobEarlyStoppingType(String trainingJobEarlyStoppingType)

Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. This can be 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

Amazon 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. This can be 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

Amazon 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.

See Also:

TrainingJobEarlyStoppingType

getTrainingJobEarlyStoppingType

public String getTrainingJobEarlyStoppingType()

Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. This can be 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

Amazon 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:

Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. This can be 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

Amazon 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.

See Also:

TrainingJobEarlyStoppingType

withTrainingJobEarlyStoppingType

public HyperParameterTuningJobConfig withTrainingJobEarlyStoppingType(String trainingJobEarlyStoppingType)

Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. This can be 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

Amazon 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. This can be 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

Amazon 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

withTrainingJobEarlyStoppingType

public HyperParameterTuningJobConfig withTrainingJobEarlyStoppingType(TrainingJobEarlyStoppingType trainingJobEarlyStoppingType)

Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. This can be 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

Amazon 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. This can be 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

Amazon 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

toString

public String toString()

Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.

Overrides:

toString in class Object

Returns:

A string representation of this object.

See Also:

Object.toString()

equals

public boolean equals(Object obj)

Overrides:

equals in class Object

hashCode

public int hashCode()

Overrides:

hashCode in class Object

clone

public HyperParameterTuningJobConfig clone()

Overrides:

clone in class Object

marshall

public void marshall(ProtocolMarshaller protocolMarshaller)

Description copied from interface: StructuredPojo

Marshalls this structured data using the given ProtocolMarshaller.

Specified by:

marshall in interface StructuredPojo

Parameters:

protocolMarshaller - Implementation of ProtocolMarshaller used to marshall this object's data.