AWS SDK for C++  1.8.100
AWS SDK for C++
Public Member Functions | List of all members
Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig Class Reference

#include <HyperParameterTuningJobWarmStartConfig.h>

Public Member Functions

 HyperParameterTuningJobWarmStartConfig ()
 
 HyperParameterTuningJobWarmStartConfig (Aws::Utils::Json::JsonView jsonValue)
 
HyperParameterTuningJobWarmStartConfigoperator= (Aws::Utils::Json::JsonView jsonValue)
 
Aws::Utils::Json::JsonValue Jsonize () const
 
const Aws::Vector< ParentHyperParameterTuningJob > & GetParentHyperParameterTuningJobs () const
 
bool ParentHyperParameterTuningJobsHasBeenSet () const
 
void SetParentHyperParameterTuningJobs (const Aws::Vector< ParentHyperParameterTuningJob > &value)
 
void SetParentHyperParameterTuningJobs (Aws::Vector< ParentHyperParameterTuningJob > &&value)
 
HyperParameterTuningJobWarmStartConfigWithParentHyperParameterTuningJobs (const Aws::Vector< ParentHyperParameterTuningJob > &value)
 
HyperParameterTuningJobWarmStartConfigWithParentHyperParameterTuningJobs (Aws::Vector< ParentHyperParameterTuningJob > &&value)
 
HyperParameterTuningJobWarmStartConfigAddParentHyperParameterTuningJobs (const ParentHyperParameterTuningJob &value)
 
HyperParameterTuningJobWarmStartConfigAddParentHyperParameterTuningJobs (ParentHyperParameterTuningJob &&value)
 
const HyperParameterTuningJobWarmStartTypeGetWarmStartType () const
 
bool WarmStartTypeHasBeenSet () const
 
void SetWarmStartType (const HyperParameterTuningJobWarmStartType &value)
 
void SetWarmStartType (HyperParameterTuningJobWarmStartType &&value)
 
HyperParameterTuningJobWarmStartConfigWithWarmStartType (const HyperParameterTuningJobWarmStartType &value)
 
HyperParameterTuningJobWarmStartConfigWithWarmStartType (HyperParameterTuningJobWarmStartType &&value)
 

Detailed Description

Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter 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, and the training job that performs the best 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.

See Also:

AWS API Reference

Definition at line 43 of file HyperParameterTuningJobWarmStartConfig.h.

Constructor & Destructor Documentation

◆ HyperParameterTuningJobWarmStartConfig() [1/2]

Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::HyperParameterTuningJobWarmStartConfig ( )

◆ HyperParameterTuningJobWarmStartConfig() [2/2]

Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::HyperParameterTuningJobWarmStartConfig ( Aws::Utils::Json::JsonView  jsonValue)

Member Function Documentation

◆ AddParentHyperParameterTuningJobs() [1/2]

HyperParameterTuningJobWarmStartConfig& Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::AddParentHyperParameterTuningJobs ( const ParentHyperParameterTuningJob value)
inline

An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.

Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.

Definition at line 127 of file HyperParameterTuningJobWarmStartConfig.h.

◆ AddParentHyperParameterTuningJobs() [2/2]

HyperParameterTuningJobWarmStartConfig& Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::AddParentHyperParameterTuningJobs ( ParentHyperParameterTuningJob &&  value)
inline

An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.

Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.

Definition at line 138 of file HyperParameterTuningJobWarmStartConfig.h.

◆ GetParentHyperParameterTuningJobs()

const Aws::Vector<ParentHyperParameterTuningJob>& Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::GetParentHyperParameterTuningJobs ( ) const
inline

An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.

Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.

Definition at line 61 of file HyperParameterTuningJobWarmStartConfig.h.

◆ GetWarmStartType()

const HyperParameterTuningJobWarmStartType& Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::GetWarmStartType ( ) const
inline

Specifies one of the following:

IDENTICAL_DATA_AND_ALGORITHM

The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

TRANSFER_LEARNING

The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

Definition at line 164 of file HyperParameterTuningJobWarmStartConfig.h.

◆ Jsonize()

Aws::Utils::Json::JsonValue Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::Jsonize ( ) const

◆ operator=()

HyperParameterTuningJobWarmStartConfig& Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::operator= ( Aws::Utils::Json::JsonView  jsonValue)

◆ ParentHyperParameterTuningJobsHasBeenSet()

bool Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::ParentHyperParameterTuningJobsHasBeenSet ( ) const
inline

An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.

Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.

Definition at line 72 of file HyperParameterTuningJobWarmStartConfig.h.

◆ SetParentHyperParameterTuningJobs() [1/2]

void Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::SetParentHyperParameterTuningJobs ( const Aws::Vector< ParentHyperParameterTuningJob > &  value)
inline

An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.

Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.

Definition at line 83 of file HyperParameterTuningJobWarmStartConfig.h.

◆ SetParentHyperParameterTuningJobs() [2/2]

void Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::SetParentHyperParameterTuningJobs ( Aws::Vector< ParentHyperParameterTuningJob > &&  value)
inline

An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.

Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.

Definition at line 94 of file HyperParameterTuningJobWarmStartConfig.h.

◆ SetWarmStartType() [1/2]

void Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::SetWarmStartType ( const HyperParameterTuningJobWarmStartType value)
inline

Specifies one of the following:

IDENTICAL_DATA_AND_ALGORITHM

The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

TRANSFER_LEARNING

The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

Definition at line 214 of file HyperParameterTuningJobWarmStartConfig.h.

◆ SetWarmStartType() [2/2]

void Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::SetWarmStartType ( HyperParameterTuningJobWarmStartType &&  value)
inline

Specifies one of the following:

IDENTICAL_DATA_AND_ALGORITHM

The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

TRANSFER_LEARNING

The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

Definition at line 239 of file HyperParameterTuningJobWarmStartConfig.h.

◆ WarmStartTypeHasBeenSet()

bool Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::WarmStartTypeHasBeenSet ( ) const
inline

Specifies one of the following:

IDENTICAL_DATA_AND_ALGORITHM

The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

TRANSFER_LEARNING

The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

Definition at line 189 of file HyperParameterTuningJobWarmStartConfig.h.

◆ WithParentHyperParameterTuningJobs() [1/2]

HyperParameterTuningJobWarmStartConfig& Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::WithParentHyperParameterTuningJobs ( const Aws::Vector< ParentHyperParameterTuningJob > &  value)
inline

An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.

Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.

Definition at line 105 of file HyperParameterTuningJobWarmStartConfig.h.

◆ WithParentHyperParameterTuningJobs() [2/2]

HyperParameterTuningJobWarmStartConfig& Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::WithParentHyperParameterTuningJobs ( Aws::Vector< ParentHyperParameterTuningJob > &&  value)
inline

An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.

Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.

Definition at line 116 of file HyperParameterTuningJobWarmStartConfig.h.

◆ WithWarmStartType() [1/2]

HyperParameterTuningJobWarmStartConfig& Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::WithWarmStartType ( const HyperParameterTuningJobWarmStartType value)
inline

Specifies one of the following:

IDENTICAL_DATA_AND_ALGORITHM

The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

TRANSFER_LEARNING

The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

Definition at line 264 of file HyperParameterTuningJobWarmStartConfig.h.

◆ WithWarmStartType() [2/2]

HyperParameterTuningJobWarmStartConfig& Aws::SageMaker::Model::HyperParameterTuningJobWarmStartConfig::WithWarmStartType ( HyperParameterTuningJobWarmStartType &&  value)
inline

Specifies one of the following:

IDENTICAL_DATA_AND_ALGORITHM

The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

TRANSFER_LEARNING

The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

Definition at line 289 of file HyperParameterTuningJobWarmStartConfig.h.


The documentation for this class was generated from the following file: