AWS SDK for C++  1.8.78
AWS SDK for C++
Public Member Functions | List of all members
Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest Class Reference

#include <CreateHyperParameterTuningJobRequest.h>

+ Inheritance diagram for Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest:

Public Member Functions

 CreateHyperParameterTuningJobRequest ()
 
virtual const char * GetServiceRequestName () const override
 
Aws::String SerializePayload () const override
 
Aws::Http::HeaderValueCollection GetRequestSpecificHeaders () const override
 
const Aws::StringGetHyperParameterTuningJobName () const
 
bool HyperParameterTuningJobNameHasBeenSet () const
 
void SetHyperParameterTuningJobName (const Aws::String &value)
 
void SetHyperParameterTuningJobName (Aws::String &&value)
 
void SetHyperParameterTuningJobName (const char *value)
 
CreateHyperParameterTuningJobRequestWithHyperParameterTuningJobName (const Aws::String &value)
 
CreateHyperParameterTuningJobRequestWithHyperParameterTuningJobName (Aws::String &&value)
 
CreateHyperParameterTuningJobRequestWithHyperParameterTuningJobName (const char *value)
 
const HyperParameterTuningJobConfigGetHyperParameterTuningJobConfig () const
 
bool HyperParameterTuningJobConfigHasBeenSet () const
 
void SetHyperParameterTuningJobConfig (const HyperParameterTuningJobConfig &value)
 
void SetHyperParameterTuningJobConfig (HyperParameterTuningJobConfig &&value)
 
CreateHyperParameterTuningJobRequestWithHyperParameterTuningJobConfig (const HyperParameterTuningJobConfig &value)
 
CreateHyperParameterTuningJobRequestWithHyperParameterTuningJobConfig (HyperParameterTuningJobConfig &&value)
 
const HyperParameterTrainingJobDefinitionGetTrainingJobDefinition () const
 
bool TrainingJobDefinitionHasBeenSet () const
 
void SetTrainingJobDefinition (const HyperParameterTrainingJobDefinition &value)
 
void SetTrainingJobDefinition (HyperParameterTrainingJobDefinition &&value)
 
CreateHyperParameterTuningJobRequestWithTrainingJobDefinition (const HyperParameterTrainingJobDefinition &value)
 
CreateHyperParameterTuningJobRequestWithTrainingJobDefinition (HyperParameterTrainingJobDefinition &&value)
 
const Aws::Vector< HyperParameterTrainingJobDefinition > & GetTrainingJobDefinitions () const
 
bool TrainingJobDefinitionsHasBeenSet () const
 
void SetTrainingJobDefinitions (const Aws::Vector< HyperParameterTrainingJobDefinition > &value)
 
void SetTrainingJobDefinitions (Aws::Vector< HyperParameterTrainingJobDefinition > &&value)
 
CreateHyperParameterTuningJobRequestWithTrainingJobDefinitions (const Aws::Vector< HyperParameterTrainingJobDefinition > &value)
 
CreateHyperParameterTuningJobRequestWithTrainingJobDefinitions (Aws::Vector< HyperParameterTrainingJobDefinition > &&value)
 
CreateHyperParameterTuningJobRequestAddTrainingJobDefinitions (const HyperParameterTrainingJobDefinition &value)
 
CreateHyperParameterTuningJobRequestAddTrainingJobDefinitions (HyperParameterTrainingJobDefinition &&value)
 
const HyperParameterTuningJobWarmStartConfigGetWarmStartConfig () const
 
bool WarmStartConfigHasBeenSet () const
 
void SetWarmStartConfig (const HyperParameterTuningJobWarmStartConfig &value)
 
void SetWarmStartConfig (HyperParameterTuningJobWarmStartConfig &&value)
 
CreateHyperParameterTuningJobRequestWithWarmStartConfig (const HyperParameterTuningJobWarmStartConfig &value)
 
CreateHyperParameterTuningJobRequestWithWarmStartConfig (HyperParameterTuningJobWarmStartConfig &&value)
 
const Aws::Vector< Tag > & GetTags () const
 
bool TagsHasBeenSet () const
 
void SetTags (const Aws::Vector< Tag > &value)
 
void SetTags (Aws::Vector< Tag > &&value)
 
CreateHyperParameterTuningJobRequestWithTags (const Aws::Vector< Tag > &value)
 
CreateHyperParameterTuningJobRequestWithTags (Aws::Vector< Tag > &&value)
 
CreateHyperParameterTuningJobRequestAddTags (const Tag &value)
 
CreateHyperParameterTuningJobRequestAddTags (Tag &&value)
 
- Public Member Functions inherited from Aws::SageMaker::SageMakerRequest
virtual ~SageMakerRequest ()
 
void AddParametersToRequest (Aws::Http::HttpRequest &httpRequest) const
 
Aws::Http::HeaderValueCollection GetHeaders () const override
 
- Public Member Functions inherited from Aws::AmazonSerializableWebServiceRequest
 AmazonSerializableWebServiceRequest ()
 
virtual ~AmazonSerializableWebServiceRequest ()
 
std::shared_ptr< Aws::IOStreamGetBody () const override
 
- Public Member Functions inherited from Aws::AmazonWebServiceRequest
 AmazonWebServiceRequest ()
 
virtual ~AmazonWebServiceRequest ()=default
 
virtual void AddQueryStringParameters (Aws::Http::URI &uri) const
 
virtual void PutToPresignedUrl (Aws::Http::URI &uri) const
 
virtual bool IsStreaming () const
 
virtual bool IsEventStreamRequest () const
 
virtual bool SignBody () const
 
virtual bool IsChunked () const
 
virtual void SetRequestSignedHandler (const RequestSignedHandler &handler)
 
virtual const RequestSignedHandlerGetRequestSignedHandler () const
 
const Aws::IOStreamFactoryGetResponseStreamFactory () const
 
void SetResponseStreamFactory (const Aws::IOStreamFactory &factory)
 
virtual void SetDataReceivedEventHandler (const Aws::Http::DataReceivedEventHandler &dataReceivedEventHandler)
 
virtual void SetDataSentEventHandler (const Aws::Http::DataSentEventHandler &dataSentEventHandler)
 
virtual void SetContinueRequestHandler (const Aws::Http::ContinueRequestHandler &continueRequestHandler)
 
virtual void SetDataReceivedEventHandler (Aws::Http::DataReceivedEventHandler &&dataReceivedEventHandler)
 
virtual void SetDataSentEventHandler (Aws::Http::DataSentEventHandler &&dataSentEventHandler)
 
virtual void SetContinueRequestHandler (Aws::Http::ContinueRequestHandler &&continueRequestHandler)
 
virtual void SetRequestRetryHandler (const RequestRetryHandler &handler)
 
virtual void SetRequestRetryHandler (RequestRetryHandler &&handler)
 
virtual const Aws::Http::DataReceivedEventHandlerGetDataReceivedEventHandler () const
 
virtual const Aws::Http::DataSentEventHandlerGetDataSentEventHandler () const
 
virtual const Aws::Http::ContinueRequestHandlerGetContinueRequestHandler () const
 
virtual const RequestRetryHandlerGetRequestRetryHandler () const
 
virtual bool ShouldComputeContentMd5 () const
 

Additional Inherited Members

- Protected Member Functions inherited from Aws::AmazonWebServiceRequest
virtual void DumpBodyToUrl (Aws::Http::URI &uri) const
 

Detailed Description

Definition at line 26 of file CreateHyperParameterTuningJobRequest.h.

Constructor & Destructor Documentation

◆ CreateHyperParameterTuningJobRequest()

Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::CreateHyperParameterTuningJobRequest ( )

Member Function Documentation

◆ AddTags() [1/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::AddTags ( const Tag value)
inline

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

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

Definition at line 445 of file CreateHyperParameterTuningJobRequest.h.

◆ AddTags() [2/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::AddTags ( Tag &&  value)
inline

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

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

Definition at line 455 of file CreateHyperParameterTuningJobRequest.h.

◆ AddTrainingJobDefinitions() [1/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::AddTrainingJobDefinitions ( const HyperParameterTrainingJobDefinition value)
inline

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

Definition at line 265 of file CreateHyperParameterTuningJobRequest.h.

◆ AddTrainingJobDefinitions() [2/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::AddTrainingJobDefinitions ( HyperParameterTrainingJobDefinition &&  value)
inline

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

Definition at line 271 of file CreateHyperParameterTuningJobRequest.h.

◆ GetHyperParameterTuningJobConfig()

const HyperParameterTuningJobConfig& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::GetHyperParameterTuningJobConfig ( ) const
inline

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.

Definition at line 123 of file CreateHyperParameterTuningJobRequest.h.

◆ GetHyperParameterTuningJobName()

const Aws::String& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::GetHyperParameterTuningJobName ( ) const
inline

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 AWS account and AWS 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.

Definition at line 49 of file CreateHyperParameterTuningJobRequest.h.

◆ GetRequestSpecificHeaders()

Aws::Http::HeaderValueCollection Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::GetRequestSpecificHeaders ( ) const
overridevirtual

Reimplemented from Aws::SageMaker::SageMakerRequest.

◆ GetServiceRequestName()

virtual const char* Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::GetServiceRequestName ( ) const
inlineoverridevirtual

◆ GetTags()

const Aws::Vector<Tag>& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::GetTags ( ) const
inline

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

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

Definition at line 385 of file CreateHyperParameterTuningJobRequest.h.

◆ GetTrainingJobDefinition()

const HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::GetTrainingJobDefinition ( ) const
inline

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.

Definition at line 182 of file CreateHyperParameterTuningJobRequest.h.

◆ GetTrainingJobDefinitions()

const Aws::Vector<HyperParameterTrainingJobDefinition>& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::GetTrainingJobDefinitions ( ) const
inline

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

Definition at line 229 of file CreateHyperParameterTuningJobRequest.h.

◆ GetWarmStartConfig()

const HyperParameterTuningJobWarmStartConfig& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::GetWarmStartConfig ( ) const
inline

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.

Definition at line 289 of file CreateHyperParameterTuningJobRequest.h.

◆ HyperParameterTuningJobConfigHasBeenSet()

bool Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::HyperParameterTuningJobConfigHasBeenSet ( ) const
inline

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.

Definition at line 133 of file CreateHyperParameterTuningJobRequest.h.

◆ HyperParameterTuningJobNameHasBeenSet()

bool Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::HyperParameterTuningJobNameHasBeenSet ( ) const
inline

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 AWS account and AWS 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.

Definition at line 58 of file CreateHyperParameterTuningJobRequest.h.

◆ SerializePayload()

Aws::String Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SerializePayload ( ) const
overridevirtual

Convert payload into String.

Implements Aws::AmazonSerializableWebServiceRequest.

◆ SetHyperParameterTuningJobConfig() [1/2]

void Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SetHyperParameterTuningJobConfig ( const HyperParameterTuningJobConfig value)
inline

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.

Definition at line 143 of file CreateHyperParameterTuningJobRequest.h.

◆ SetHyperParameterTuningJobConfig() [2/2]

void Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SetHyperParameterTuningJobConfig ( HyperParameterTuningJobConfig &&  value)
inline

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.

Definition at line 153 of file CreateHyperParameterTuningJobRequest.h.

◆ SetHyperParameterTuningJobName() [1/3]

void Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SetHyperParameterTuningJobName ( const Aws::String value)
inline

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 AWS account and AWS 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.

Definition at line 67 of file CreateHyperParameterTuningJobRequest.h.

◆ SetHyperParameterTuningJobName() [2/3]

void Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SetHyperParameterTuningJobName ( Aws::String &&  value)
inline

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 AWS account and AWS 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.

Definition at line 76 of file CreateHyperParameterTuningJobRequest.h.

◆ SetHyperParameterTuningJobName() [3/3]

void Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SetHyperParameterTuningJobName ( const char *  value)
inline

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 AWS account and AWS 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.

Definition at line 85 of file CreateHyperParameterTuningJobRequest.h.

◆ SetTags() [1/2]

void Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SetTags ( const Aws::Vector< Tag > &  value)
inline

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

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

Definition at line 405 of file CreateHyperParameterTuningJobRequest.h.

◆ SetTags() [2/2]

void Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SetTags ( Aws::Vector< Tag > &&  value)
inline

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

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

Definition at line 415 of file CreateHyperParameterTuningJobRequest.h.

◆ SetTrainingJobDefinition() [1/2]

void Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SetTrainingJobDefinition ( const HyperParameterTrainingJobDefinition value)
inline

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.

Definition at line 198 of file CreateHyperParameterTuningJobRequest.h.

◆ SetTrainingJobDefinition() [2/2]

void Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SetTrainingJobDefinition ( HyperParameterTrainingJobDefinition &&  value)
inline

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.

Definition at line 206 of file CreateHyperParameterTuningJobRequest.h.

◆ SetTrainingJobDefinitions() [1/2]

void Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SetTrainingJobDefinitions ( const Aws::Vector< HyperParameterTrainingJobDefinition > &  value)
inline

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

Definition at line 241 of file CreateHyperParameterTuningJobRequest.h.

◆ SetTrainingJobDefinitions() [2/2]

void Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SetTrainingJobDefinitions ( Aws::Vector< HyperParameterTrainingJobDefinition > &&  value)
inline

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

Definition at line 247 of file CreateHyperParameterTuningJobRequest.h.

◆ SetWarmStartConfig() [1/2]

void Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SetWarmStartConfig ( const HyperParameterTuningJobWarmStartConfig value)
inline

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.

Definition at line 323 of file CreateHyperParameterTuningJobRequest.h.

◆ SetWarmStartConfig() [2/2]

void Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::SetWarmStartConfig ( HyperParameterTuningJobWarmStartConfig &&  value)
inline

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.

Definition at line 340 of file CreateHyperParameterTuningJobRequest.h.

◆ TagsHasBeenSet()

bool Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::TagsHasBeenSet ( ) const
inline

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

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

Definition at line 395 of file CreateHyperParameterTuningJobRequest.h.

◆ TrainingJobDefinitionHasBeenSet()

bool Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::TrainingJobDefinitionHasBeenSet ( ) const
inline

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.

Definition at line 190 of file CreateHyperParameterTuningJobRequest.h.

◆ TrainingJobDefinitionsHasBeenSet()

bool Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::TrainingJobDefinitionsHasBeenSet ( ) const
inline

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

Definition at line 235 of file CreateHyperParameterTuningJobRequest.h.

◆ WarmStartConfigHasBeenSet()

bool Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WarmStartConfigHasBeenSet ( ) const
inline

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.

Definition at line 306 of file CreateHyperParameterTuningJobRequest.h.

◆ WithHyperParameterTuningJobConfig() [1/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WithHyperParameterTuningJobConfig ( const HyperParameterTuningJobConfig value)
inline

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.

Definition at line 163 of file CreateHyperParameterTuningJobRequest.h.

◆ WithHyperParameterTuningJobConfig() [2/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WithHyperParameterTuningJobConfig ( HyperParameterTuningJobConfig &&  value)
inline

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.

Definition at line 173 of file CreateHyperParameterTuningJobRequest.h.

◆ WithHyperParameterTuningJobName() [1/3]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WithHyperParameterTuningJobName ( const Aws::String value)
inline

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 AWS account and AWS 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.

Definition at line 94 of file CreateHyperParameterTuningJobRequest.h.

◆ WithHyperParameterTuningJobName() [2/3]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WithHyperParameterTuningJobName ( Aws::String &&  value)
inline

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 AWS account and AWS 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.

Definition at line 103 of file CreateHyperParameterTuningJobRequest.h.

◆ WithHyperParameterTuningJobName() [3/3]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WithHyperParameterTuningJobName ( const char *  value)
inline

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 AWS account and AWS 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.

Definition at line 112 of file CreateHyperParameterTuningJobRequest.h.

◆ WithTags() [1/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WithTags ( const Aws::Vector< Tag > &  value)
inline

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

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

Definition at line 425 of file CreateHyperParameterTuningJobRequest.h.

◆ WithTags() [2/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WithTags ( Aws::Vector< Tag > &&  value)
inline

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

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

Definition at line 435 of file CreateHyperParameterTuningJobRequest.h.

◆ WithTrainingJobDefinition() [1/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WithTrainingJobDefinition ( const HyperParameterTrainingJobDefinition value)
inline

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.

Definition at line 214 of file CreateHyperParameterTuningJobRequest.h.

◆ WithTrainingJobDefinition() [2/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WithTrainingJobDefinition ( HyperParameterTrainingJobDefinition &&  value)
inline

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.

Definition at line 222 of file CreateHyperParameterTuningJobRequest.h.

◆ WithTrainingJobDefinitions() [1/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WithTrainingJobDefinitions ( const Aws::Vector< HyperParameterTrainingJobDefinition > &  value)
inline

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

Definition at line 253 of file CreateHyperParameterTuningJobRequest.h.

◆ WithTrainingJobDefinitions() [2/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WithTrainingJobDefinitions ( Aws::Vector< HyperParameterTrainingJobDefinition > &&  value)
inline

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

Definition at line 259 of file CreateHyperParameterTuningJobRequest.h.

◆ WithWarmStartConfig() [1/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WithWarmStartConfig ( const HyperParameterTuningJobWarmStartConfig value)
inline

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.

Definition at line 357 of file CreateHyperParameterTuningJobRequest.h.

◆ WithWarmStartConfig() [2/2]

CreateHyperParameterTuningJobRequest& Aws::SageMaker::Model::CreateHyperParameterTuningJobRequest::WithWarmStartConfig ( HyperParameterTuningJobWarmStartConfig &&  value)
inline

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.

Definition at line 374 of file CreateHyperParameterTuningJobRequest.h.


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