AWS SDK for C++  1.9.123
AWS SDK for C++
Public Member Functions | List of all members
Aws::SageMaker::Model::TrainingJobDefinition Class Reference

#include <TrainingJobDefinition.h>

Public Member Functions

 TrainingJobDefinition ()
 
 TrainingJobDefinition (Aws::Utils::Json::JsonView jsonValue)
 
TrainingJobDefinitionoperator= (Aws::Utils::Json::JsonView jsonValue)
 
Aws::Utils::Json::JsonValue Jsonize () const
 
const TrainingInputModeGetTrainingInputMode () const
 
bool TrainingInputModeHasBeenSet () const
 
void SetTrainingInputMode (const TrainingInputMode &value)
 
void SetTrainingInputMode (TrainingInputMode &&value)
 
TrainingJobDefinitionWithTrainingInputMode (const TrainingInputMode &value)
 
TrainingJobDefinitionWithTrainingInputMode (TrainingInputMode &&value)
 
const Aws::Map< Aws::String, Aws::String > & GetHyperParameters () const
 
bool HyperParametersHasBeenSet () const
 
void SetHyperParameters (const Aws::Map< Aws::String, Aws::String > &value)
 
void SetHyperParameters (Aws::Map< Aws::String, Aws::String > &&value)
 
TrainingJobDefinitionWithHyperParameters (const Aws::Map< Aws::String, Aws::String > &value)
 
TrainingJobDefinitionWithHyperParameters (Aws::Map< Aws::String, Aws::String > &&value)
 
TrainingJobDefinitionAddHyperParameters (const Aws::String &key, const Aws::String &value)
 
TrainingJobDefinitionAddHyperParameters (Aws::String &&key, const Aws::String &value)
 
TrainingJobDefinitionAddHyperParameters (const Aws::String &key, Aws::String &&value)
 
TrainingJobDefinitionAddHyperParameters (Aws::String &&key, Aws::String &&value)
 
TrainingJobDefinitionAddHyperParameters (const char *key, Aws::String &&value)
 
TrainingJobDefinitionAddHyperParameters (Aws::String &&key, const char *value)
 
TrainingJobDefinitionAddHyperParameters (const char *key, const char *value)
 
const Aws::Vector< Channel > & GetInputDataConfig () const
 
bool InputDataConfigHasBeenSet () const
 
void SetInputDataConfig (const Aws::Vector< Channel > &value)
 
void SetInputDataConfig (Aws::Vector< Channel > &&value)
 
TrainingJobDefinitionWithInputDataConfig (const Aws::Vector< Channel > &value)
 
TrainingJobDefinitionWithInputDataConfig (Aws::Vector< Channel > &&value)
 
TrainingJobDefinitionAddInputDataConfig (const Channel &value)
 
TrainingJobDefinitionAddInputDataConfig (Channel &&value)
 
const OutputDataConfigGetOutputDataConfig () const
 
bool OutputDataConfigHasBeenSet () const
 
void SetOutputDataConfig (const OutputDataConfig &value)
 
void SetOutputDataConfig (OutputDataConfig &&value)
 
TrainingJobDefinitionWithOutputDataConfig (const OutputDataConfig &value)
 
TrainingJobDefinitionWithOutputDataConfig (OutputDataConfig &&value)
 
const ResourceConfigGetResourceConfig () const
 
bool ResourceConfigHasBeenSet () const
 
void SetResourceConfig (const ResourceConfig &value)
 
void SetResourceConfig (ResourceConfig &&value)
 
TrainingJobDefinitionWithResourceConfig (const ResourceConfig &value)
 
TrainingJobDefinitionWithResourceConfig (ResourceConfig &&value)
 
const StoppingConditionGetStoppingCondition () const
 
bool StoppingConditionHasBeenSet () const
 
void SetStoppingCondition (const StoppingCondition &value)
 
void SetStoppingCondition (StoppingCondition &&value)
 
TrainingJobDefinitionWithStoppingCondition (const StoppingCondition &value)
 
TrainingJobDefinitionWithStoppingCondition (StoppingCondition &&value)
 

Detailed Description

Defines the input needed to run a training job using the algorithm.

See Also:

AWS API Reference

Definition at line 39 of file TrainingJobDefinition.h.

Constructor & Destructor Documentation

◆ TrainingJobDefinition() [1/2]

Aws::SageMaker::Model::TrainingJobDefinition::TrainingJobDefinition ( )

◆ TrainingJobDefinition() [2/2]

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

Member Function Documentation

◆ AddHyperParameters() [1/7]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::AddHyperParameters ( Aws::String &&  key,
Aws::String &&  value 
)
inline

The hyperparameters used for the training job.

Definition at line 115 of file TrainingJobDefinition.h.

◆ AddHyperParameters() [2/7]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::AddHyperParameters ( Aws::String &&  key,
const Aws::String value 
)
inline

The hyperparameters used for the training job.

Definition at line 105 of file TrainingJobDefinition.h.

◆ AddHyperParameters() [3/7]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::AddHyperParameters ( Aws::String &&  key,
const char *  value 
)
inline

The hyperparameters used for the training job.

Definition at line 125 of file TrainingJobDefinition.h.

◆ AddHyperParameters() [4/7]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::AddHyperParameters ( const Aws::String key,
Aws::String &&  value 
)
inline

The hyperparameters used for the training job.

Definition at line 110 of file TrainingJobDefinition.h.

◆ AddHyperParameters() [5/7]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::AddHyperParameters ( const Aws::String key,
const Aws::String value 
)
inline

The hyperparameters used for the training job.

Definition at line 100 of file TrainingJobDefinition.h.

◆ AddHyperParameters() [6/7]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::AddHyperParameters ( const char *  key,
Aws::String &&  value 
)
inline

The hyperparameters used for the training job.

Definition at line 120 of file TrainingJobDefinition.h.

◆ AddHyperParameters() [7/7]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::AddHyperParameters ( const char *  key,
const char *  value 
)
inline

The hyperparameters used for the training job.

Definition at line 130 of file TrainingJobDefinition.h.

◆ AddInputDataConfig() [1/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::AddInputDataConfig ( Channel &&  value)
inline

An array of Channel objects, each of which specifies an input source.

Definition at line 179 of file TrainingJobDefinition.h.

◆ AddInputDataConfig() [2/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::AddInputDataConfig ( const Channel value)
inline

An array of Channel objects, each of which specifies an input source.

Definition at line 173 of file TrainingJobDefinition.h.

◆ GetHyperParameters()

const Aws::Map<Aws::String, Aws::String>& Aws::SageMaker::Model::TrainingJobDefinition::GetHyperParameters ( ) const
inline

The hyperparameters used for the training job.

Definition at line 70 of file TrainingJobDefinition.h.

◆ GetInputDataConfig()

const Aws::Vector<Channel>& Aws::SageMaker::Model::TrainingJobDefinition::GetInputDataConfig ( ) const
inline

An array of Channel objects, each of which specifies an input source.

Definition at line 137 of file TrainingJobDefinition.h.

◆ GetOutputDataConfig()

const OutputDataConfig& Aws::SageMaker::Model::TrainingJobDefinition::GetOutputDataConfig ( ) const
inline

the path to the S3 bucket where you want to store model artifacts. Amazon SageMaker creates subfolders for the artifacts.

Definition at line 186 of file TrainingJobDefinition.h.

◆ GetResourceConfig()

const ResourceConfig& Aws::SageMaker::Model::TrainingJobDefinition::GetResourceConfig ( ) const
inline

The resources, including the ML compute instances and ML storage volumes, to use for model training.

Definition at line 223 of file TrainingJobDefinition.h.

◆ GetStoppingCondition()

const StoppingCondition& Aws::SageMaker::Model::TrainingJobDefinition::GetStoppingCondition ( ) const
inline

Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.

Definition at line 264 of file TrainingJobDefinition.h.

◆ GetTrainingInputMode()

const TrainingInputMode& Aws::SageMaker::Model::TrainingJobDefinition::GetTrainingInputMode ( ) const
inline

Definition at line 49 of file TrainingJobDefinition.h.

◆ HyperParametersHasBeenSet()

bool Aws::SageMaker::Model::TrainingJobDefinition::HyperParametersHasBeenSet ( ) const
inline

The hyperparameters used for the training job.

Definition at line 75 of file TrainingJobDefinition.h.

◆ InputDataConfigHasBeenSet()

bool Aws::SageMaker::Model::TrainingJobDefinition::InputDataConfigHasBeenSet ( ) const
inline

An array of Channel objects, each of which specifies an input source.

Definition at line 143 of file TrainingJobDefinition.h.

◆ Jsonize()

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

◆ operator=()

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

◆ OutputDataConfigHasBeenSet()

bool Aws::SageMaker::Model::TrainingJobDefinition::OutputDataConfigHasBeenSet ( ) const
inline

the path to the S3 bucket where you want to store model artifacts. Amazon SageMaker creates subfolders for the artifacts.

Definition at line 192 of file TrainingJobDefinition.h.

◆ ResourceConfigHasBeenSet()

bool Aws::SageMaker::Model::TrainingJobDefinition::ResourceConfigHasBeenSet ( ) const
inline

The resources, including the ML compute instances and ML storage volumes, to use for model training.

Definition at line 229 of file TrainingJobDefinition.h.

◆ SetHyperParameters() [1/2]

void Aws::SageMaker::Model::TrainingJobDefinition::SetHyperParameters ( Aws::Map< Aws::String, Aws::String > &&  value)
inline

The hyperparameters used for the training job.

Definition at line 85 of file TrainingJobDefinition.h.

◆ SetHyperParameters() [2/2]

void Aws::SageMaker::Model::TrainingJobDefinition::SetHyperParameters ( const Aws::Map< Aws::String, Aws::String > &  value)
inline

The hyperparameters used for the training job.

Definition at line 80 of file TrainingJobDefinition.h.

◆ SetInputDataConfig() [1/2]

void Aws::SageMaker::Model::TrainingJobDefinition::SetInputDataConfig ( Aws::Vector< Channel > &&  value)
inline

An array of Channel objects, each of which specifies an input source.

Definition at line 155 of file TrainingJobDefinition.h.

◆ SetInputDataConfig() [2/2]

void Aws::SageMaker::Model::TrainingJobDefinition::SetInputDataConfig ( const Aws::Vector< Channel > &  value)
inline

An array of Channel objects, each of which specifies an input source.

Definition at line 149 of file TrainingJobDefinition.h.

◆ SetOutputDataConfig() [1/2]

void Aws::SageMaker::Model::TrainingJobDefinition::SetOutputDataConfig ( const OutputDataConfig value)
inline

the path to the S3 bucket where you want to store model artifacts. Amazon SageMaker creates subfolders for the artifacts.

Definition at line 198 of file TrainingJobDefinition.h.

◆ SetOutputDataConfig() [2/2]

void Aws::SageMaker::Model::TrainingJobDefinition::SetOutputDataConfig ( OutputDataConfig &&  value)
inline

the path to the S3 bucket where you want to store model artifacts. Amazon SageMaker creates subfolders for the artifacts.

Definition at line 204 of file TrainingJobDefinition.h.

◆ SetResourceConfig() [1/2]

void Aws::SageMaker::Model::TrainingJobDefinition::SetResourceConfig ( const ResourceConfig value)
inline

The resources, including the ML compute instances and ML storage volumes, to use for model training.

Definition at line 235 of file TrainingJobDefinition.h.

◆ SetResourceConfig() [2/2]

void Aws::SageMaker::Model::TrainingJobDefinition::SetResourceConfig ( ResourceConfig &&  value)
inline

The resources, including the ML compute instances and ML storage volumes, to use for model training.

Definition at line 241 of file TrainingJobDefinition.h.

◆ SetStoppingCondition() [1/2]

void Aws::SageMaker::Model::TrainingJobDefinition::SetStoppingCondition ( const StoppingCondition value)
inline

Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.

Definition at line 284 of file TrainingJobDefinition.h.

◆ SetStoppingCondition() [2/2]

void Aws::SageMaker::Model::TrainingJobDefinition::SetStoppingCondition ( StoppingCondition &&  value)
inline

Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.

Definition at line 294 of file TrainingJobDefinition.h.

◆ SetTrainingInputMode() [1/2]

void Aws::SageMaker::Model::TrainingJobDefinition::SetTrainingInputMode ( const TrainingInputMode value)
inline

Definition at line 55 of file TrainingJobDefinition.h.

◆ SetTrainingInputMode() [2/2]

void Aws::SageMaker::Model::TrainingJobDefinition::SetTrainingInputMode ( TrainingInputMode &&  value)
inline

Definition at line 58 of file TrainingJobDefinition.h.

◆ StoppingConditionHasBeenSet()

bool Aws::SageMaker::Model::TrainingJobDefinition::StoppingConditionHasBeenSet ( ) const
inline

Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.

Definition at line 274 of file TrainingJobDefinition.h.

◆ TrainingInputModeHasBeenSet()

bool Aws::SageMaker::Model::TrainingJobDefinition::TrainingInputModeHasBeenSet ( ) const
inline

Definition at line 52 of file TrainingJobDefinition.h.

◆ WithHyperParameters() [1/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::WithHyperParameters ( Aws::Map< Aws::String, Aws::String > &&  value)
inline

The hyperparameters used for the training job.

Definition at line 95 of file TrainingJobDefinition.h.

◆ WithHyperParameters() [2/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::WithHyperParameters ( const Aws::Map< Aws::String, Aws::String > &  value)
inline

The hyperparameters used for the training job.

Definition at line 90 of file TrainingJobDefinition.h.

◆ WithInputDataConfig() [1/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::WithInputDataConfig ( Aws::Vector< Channel > &&  value)
inline

An array of Channel objects, each of which specifies an input source.

Definition at line 167 of file TrainingJobDefinition.h.

◆ WithInputDataConfig() [2/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::WithInputDataConfig ( const Aws::Vector< Channel > &  value)
inline

An array of Channel objects, each of which specifies an input source.

Definition at line 161 of file TrainingJobDefinition.h.

◆ WithOutputDataConfig() [1/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::WithOutputDataConfig ( const OutputDataConfig value)
inline

the path to the S3 bucket where you want to store model artifacts. Amazon SageMaker creates subfolders for the artifacts.

Definition at line 210 of file TrainingJobDefinition.h.

◆ WithOutputDataConfig() [2/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::WithOutputDataConfig ( OutputDataConfig &&  value)
inline

the path to the S3 bucket where you want to store model artifacts. Amazon SageMaker creates subfolders for the artifacts.

Definition at line 216 of file TrainingJobDefinition.h.

◆ WithResourceConfig() [1/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::WithResourceConfig ( const ResourceConfig value)
inline

The resources, including the ML compute instances and ML storage volumes, to use for model training.

Definition at line 247 of file TrainingJobDefinition.h.

◆ WithResourceConfig() [2/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::WithResourceConfig ( ResourceConfig &&  value)
inline

The resources, including the ML compute instances and ML storage volumes, to use for model training.

Definition at line 253 of file TrainingJobDefinition.h.

◆ WithStoppingCondition() [1/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::WithStoppingCondition ( const StoppingCondition value)
inline

Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.

Definition at line 304 of file TrainingJobDefinition.h.

◆ WithStoppingCondition() [2/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::WithStoppingCondition ( StoppingCondition &&  value)
inline

Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.

Definition at line 314 of file TrainingJobDefinition.h.

◆ WithTrainingInputMode() [1/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::WithTrainingInputMode ( const TrainingInputMode value)
inline

Definition at line 61 of file TrainingJobDefinition.h.

◆ WithTrainingInputMode() [2/2]

TrainingJobDefinition& Aws::SageMaker::Model::TrainingJobDefinition::WithTrainingInputMode ( TrainingInputMode &&  value)
inline

Definition at line 64 of file TrainingJobDefinition.h.


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