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

#include <HyperParameterTrainingJobDefinition.h>

Public Member Functions

 HyperParameterTrainingJobDefinition ()
 
 HyperParameterTrainingJobDefinition (Aws::Utils::Json::JsonView jsonValue)
 
HyperParameterTrainingJobDefinitionoperator= (Aws::Utils::Json::JsonView jsonValue)
 
Aws::Utils::Json::JsonValue Jsonize () const
 
const Aws::StringGetDefinitionName () const
 
bool DefinitionNameHasBeenSet () const
 
void SetDefinitionName (const Aws::String &value)
 
void SetDefinitionName (Aws::String &&value)
 
void SetDefinitionName (const char *value)
 
HyperParameterTrainingJobDefinitionWithDefinitionName (const Aws::String &value)
 
HyperParameterTrainingJobDefinitionWithDefinitionName (Aws::String &&value)
 
HyperParameterTrainingJobDefinitionWithDefinitionName (const char *value)
 
const HyperParameterTuningJobObjectiveGetTuningObjective () const
 
bool TuningObjectiveHasBeenSet () const
 
void SetTuningObjective (const HyperParameterTuningJobObjective &value)
 
void SetTuningObjective (HyperParameterTuningJobObjective &&value)
 
HyperParameterTrainingJobDefinitionWithTuningObjective (const HyperParameterTuningJobObjective &value)
 
HyperParameterTrainingJobDefinitionWithTuningObjective (HyperParameterTuningJobObjective &&value)
 
const ParameterRangesGetHyperParameterRanges () const
 
bool HyperParameterRangesHasBeenSet () const
 
void SetHyperParameterRanges (const ParameterRanges &value)
 
void SetHyperParameterRanges (ParameterRanges &&value)
 
HyperParameterTrainingJobDefinitionWithHyperParameterRanges (const ParameterRanges &value)
 
HyperParameterTrainingJobDefinitionWithHyperParameterRanges (ParameterRanges &&value)
 
const Aws::Map< Aws::String, Aws::String > & GetStaticHyperParameters () const
 
bool StaticHyperParametersHasBeenSet () const
 
void SetStaticHyperParameters (const Aws::Map< Aws::String, Aws::String > &value)
 
void SetStaticHyperParameters (Aws::Map< Aws::String, Aws::String > &&value)
 
HyperParameterTrainingJobDefinitionWithStaticHyperParameters (const Aws::Map< Aws::String, Aws::String > &value)
 
HyperParameterTrainingJobDefinitionWithStaticHyperParameters (Aws::Map< Aws::String, Aws::String > &&value)
 
HyperParameterTrainingJobDefinitionAddStaticHyperParameters (const Aws::String &key, const Aws::String &value)
 
HyperParameterTrainingJobDefinitionAddStaticHyperParameters (Aws::String &&key, const Aws::String &value)
 
HyperParameterTrainingJobDefinitionAddStaticHyperParameters (const Aws::String &key, Aws::String &&value)
 
HyperParameterTrainingJobDefinitionAddStaticHyperParameters (Aws::String &&key, Aws::String &&value)
 
HyperParameterTrainingJobDefinitionAddStaticHyperParameters (const char *key, Aws::String &&value)
 
HyperParameterTrainingJobDefinitionAddStaticHyperParameters (Aws::String &&key, const char *value)
 
HyperParameterTrainingJobDefinitionAddStaticHyperParameters (const char *key, const char *value)
 
const HyperParameterAlgorithmSpecificationGetAlgorithmSpecification () const
 
bool AlgorithmSpecificationHasBeenSet () const
 
void SetAlgorithmSpecification (const HyperParameterAlgorithmSpecification &value)
 
void SetAlgorithmSpecification (HyperParameterAlgorithmSpecification &&value)
 
HyperParameterTrainingJobDefinitionWithAlgorithmSpecification (const HyperParameterAlgorithmSpecification &value)
 
HyperParameterTrainingJobDefinitionWithAlgorithmSpecification (HyperParameterAlgorithmSpecification &&value)
 
const Aws::StringGetRoleArn () const
 
bool RoleArnHasBeenSet () const
 
void SetRoleArn (const Aws::String &value)
 
void SetRoleArn (Aws::String &&value)
 
void SetRoleArn (const char *value)
 
HyperParameterTrainingJobDefinitionWithRoleArn (const Aws::String &value)
 
HyperParameterTrainingJobDefinitionWithRoleArn (Aws::String &&value)
 
HyperParameterTrainingJobDefinitionWithRoleArn (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)
 
HyperParameterTrainingJobDefinitionWithInputDataConfig (const Aws::Vector< Channel > &value)
 
HyperParameterTrainingJobDefinitionWithInputDataConfig (Aws::Vector< Channel > &&value)
 
HyperParameterTrainingJobDefinitionAddInputDataConfig (const Channel &value)
 
HyperParameterTrainingJobDefinitionAddInputDataConfig (Channel &&value)
 
const VpcConfigGetVpcConfig () const
 
bool VpcConfigHasBeenSet () const
 
void SetVpcConfig (const VpcConfig &value)
 
void SetVpcConfig (VpcConfig &&value)
 
HyperParameterTrainingJobDefinitionWithVpcConfig (const VpcConfig &value)
 
HyperParameterTrainingJobDefinitionWithVpcConfig (VpcConfig &&value)
 
const OutputDataConfigGetOutputDataConfig () const
 
bool OutputDataConfigHasBeenSet () const
 
void SetOutputDataConfig (const OutputDataConfig &value)
 
void SetOutputDataConfig (OutputDataConfig &&value)
 
HyperParameterTrainingJobDefinitionWithOutputDataConfig (const OutputDataConfig &value)
 
HyperParameterTrainingJobDefinitionWithOutputDataConfig (OutputDataConfig &&value)
 
const ResourceConfigGetResourceConfig () const
 
bool ResourceConfigHasBeenSet () const
 
void SetResourceConfig (const ResourceConfig &value)
 
void SetResourceConfig (ResourceConfig &&value)
 
HyperParameterTrainingJobDefinitionWithResourceConfig (const ResourceConfig &value)
 
HyperParameterTrainingJobDefinitionWithResourceConfig (ResourceConfig &&value)
 
const StoppingConditionGetStoppingCondition () const
 
bool StoppingConditionHasBeenSet () const
 
void SetStoppingCondition (const StoppingCondition &value)
 
void SetStoppingCondition (StoppingCondition &&value)
 
HyperParameterTrainingJobDefinitionWithStoppingCondition (const StoppingCondition &value)
 
HyperParameterTrainingJobDefinitionWithStoppingCondition (StoppingCondition &&value)
 
bool GetEnableNetworkIsolation () const
 
bool EnableNetworkIsolationHasBeenSet () const
 
void SetEnableNetworkIsolation (bool value)
 
HyperParameterTrainingJobDefinitionWithEnableNetworkIsolation (bool value)
 
bool GetEnableInterContainerTrafficEncryption () const
 
bool EnableInterContainerTrafficEncryptionHasBeenSet () const
 
void SetEnableInterContainerTrafficEncryption (bool value)
 
HyperParameterTrainingJobDefinitionWithEnableInterContainerTrafficEncryption (bool value)
 
bool GetEnableManagedSpotTraining () const
 
bool EnableManagedSpotTrainingHasBeenSet () const
 
void SetEnableManagedSpotTraining (bool value)
 
HyperParameterTrainingJobDefinitionWithEnableManagedSpotTraining (bool value)
 
const CheckpointConfigGetCheckpointConfig () const
 
bool CheckpointConfigHasBeenSet () const
 
void SetCheckpointConfig (const CheckpointConfig &value)
 
void SetCheckpointConfig (CheckpointConfig &&value)
 
HyperParameterTrainingJobDefinitionWithCheckpointConfig (const CheckpointConfig &value)
 
HyperParameterTrainingJobDefinitionWithCheckpointConfig (CheckpointConfig &&value)
 

Detailed Description

Defines the training jobs launched by a hyperparameter tuning job.

See Also:

AWS API Reference

Definition at line 43 of file HyperParameterTrainingJobDefinition.h.

Constructor & Destructor Documentation

◆ HyperParameterTrainingJobDefinition() [1/2]

Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::HyperParameterTrainingJobDefinition ( )

◆ HyperParameterTrainingJobDefinition() [2/2]

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

Member Function Documentation

◆ AddInputDataConfig() [1/2]

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

An array of Channel objects that specify the input for the training jobs that the tuning job launches.

Definition at line 342 of file HyperParameterTrainingJobDefinition.h.

◆ AddInputDataConfig() [2/2]

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

An array of Channel objects that specify the input for the training jobs that the tuning job launches.

Definition at line 348 of file HyperParameterTrainingJobDefinition.h.

◆ AddStaticHyperParameters() [1/7]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::AddStaticHyperParameters ( const Aws::String key,
const Aws::String value 
)
inline

Specifies the values of hyperparameters that do not change for the tuning job.

Definition at line 171 of file HyperParameterTrainingJobDefinition.h.

◆ AddStaticHyperParameters() [2/7]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::AddStaticHyperParameters ( Aws::String &&  key,
const Aws::String value 
)
inline

Specifies the values of hyperparameters that do not change for the tuning job.

Definition at line 177 of file HyperParameterTrainingJobDefinition.h.

◆ AddStaticHyperParameters() [3/7]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::AddStaticHyperParameters ( const Aws::String key,
Aws::String &&  value 
)
inline

Specifies the values of hyperparameters that do not change for the tuning job.

Definition at line 183 of file HyperParameterTrainingJobDefinition.h.

◆ AddStaticHyperParameters() [4/7]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::AddStaticHyperParameters ( Aws::String &&  key,
Aws::String &&  value 
)
inline

Specifies the values of hyperparameters that do not change for the tuning job.

Definition at line 189 of file HyperParameterTrainingJobDefinition.h.

◆ AddStaticHyperParameters() [5/7]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::AddStaticHyperParameters ( const char *  key,
Aws::String &&  value 
)
inline

Specifies the values of hyperparameters that do not change for the tuning job.

Definition at line 195 of file HyperParameterTrainingJobDefinition.h.

◆ AddStaticHyperParameters() [6/7]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::AddStaticHyperParameters ( Aws::String &&  key,
const char *  value 
)
inline

Specifies the values of hyperparameters that do not change for the tuning job.

Definition at line 201 of file HyperParameterTrainingJobDefinition.h.

◆ AddStaticHyperParameters() [7/7]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::AddStaticHyperParameters ( const char *  key,
const char *  value 
)
inline

Specifies the values of hyperparameters that do not change for the tuning job.

Definition at line 207 of file HyperParameterTrainingJobDefinition.h.

◆ AlgorithmSpecificationHasBeenSet()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::AlgorithmSpecificationHasBeenSet ( ) const
inline

The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.

Definition at line 222 of file HyperParameterTrainingJobDefinition.h.

◆ CheckpointConfigHasBeenSet()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::CheckpointConfigHasBeenSet ( ) const
inline

Definition at line 672 of file HyperParameterTrainingJobDefinition.h.

◆ DefinitionNameHasBeenSet()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::DefinitionNameHasBeenSet ( ) const
inline

The job definition name.

Definition at line 60 of file HyperParameterTrainingJobDefinition.h.

◆ EnableInterContainerTrafficEncryptionHasBeenSet()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::EnableInterContainerTrafficEncryptionHasBeenSet ( ) const
inline

To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.

Definition at line 622 of file HyperParameterTrainingJobDefinition.h.

◆ EnableManagedSpotTrainingHasBeenSet()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::EnableManagedSpotTrainingHasBeenSet ( ) const
inline

A Boolean indicating whether managed spot training is enabled (True) or not (False).

Definition at line 653 of file HyperParameterTrainingJobDefinition.h.

◆ EnableNetworkIsolationHasBeenSet()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::EnableNetworkIsolationHasBeenSet ( ) const
inline

Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, Amazon SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.

Definition at line 583 of file HyperParameterTrainingJobDefinition.h.

◆ GetAlgorithmSpecification()

const HyperParameterAlgorithmSpecification& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::GetAlgorithmSpecification ( ) const
inline

The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.

Definition at line 215 of file HyperParameterTrainingJobDefinition.h.

◆ GetCheckpointConfig()

const CheckpointConfig& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::GetCheckpointConfig ( ) const
inline

Definition at line 669 of file HyperParameterTrainingJobDefinition.h.

◆ GetDefinitionName()

const Aws::String& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::GetDefinitionName ( ) const
inline

The job definition name.

Definition at line 55 of file HyperParameterTrainingJobDefinition.h.

◆ GetEnableInterContainerTrafficEncryption()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::GetEnableInterContainerTrafficEncryption ( ) const
inline

To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.

Definition at line 613 of file HyperParameterTrainingJobDefinition.h.

◆ GetEnableManagedSpotTraining()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::GetEnableManagedSpotTraining ( ) const
inline

A Boolean indicating whether managed spot training is enabled (True) or not (False).

Definition at line 647 of file HyperParameterTrainingJobDefinition.h.

◆ GetEnableNetworkIsolation()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::GetEnableNetworkIsolation ( ) const
inline

Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, Amazon SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.

Definition at line 573 of file HyperParameterTrainingJobDefinition.h.

◆ GetHyperParameterRanges()

const ParameterRanges& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::GetHyperParameterRanges ( ) const
inline

Definition at line 113 of file HyperParameterTrainingJobDefinition.h.

◆ GetInputDataConfig()

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

An array of Channel objects that specify the input for the training jobs that the tuning job launches.

Definition at line 306 of file HyperParameterTrainingJobDefinition.h.

◆ GetOutputDataConfig()

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

Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.

Definition at line 416 of file HyperParameterTrainingJobDefinition.h.

◆ GetResourceConfig()

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

The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.

Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want Amazon SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.

Definition at line 458 of file HyperParameterTrainingJobDefinition.h.

◆ GetRoleArn()

const Aws::String& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::GetRoleArn ( ) const
inline

The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.

Definition at line 257 of file HyperParameterTrainingJobDefinition.h.

◆ GetStaticHyperParameters()

const Aws::Map<Aws::String, Aws::String>& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::GetStaticHyperParameters ( ) const
inline

Specifies the values of hyperparameters that do not change for the tuning job.

Definition at line 135 of file HyperParameterTrainingJobDefinition.h.

◆ GetStoppingCondition()

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

Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long you are willing to wait for a managed spot training job to complete. When the job reaches the a limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

Definition at line 522 of file HyperParameterTrainingJobDefinition.h.

◆ GetTuningObjective()

const HyperParameterTuningJobObjective& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::GetTuningObjective ( ) const
inline

Definition at line 94 of file HyperParameterTrainingJobDefinition.h.

◆ GetVpcConfig()

const VpcConfig& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::GetVpcConfig ( ) const
inline

The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Definition at line 359 of file HyperParameterTrainingJobDefinition.h.

◆ HyperParameterRangesHasBeenSet()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::HyperParameterRangesHasBeenSet ( ) const
inline

Definition at line 116 of file HyperParameterTrainingJobDefinition.h.

◆ InputDataConfigHasBeenSet()

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

An array of Channel objects that specify the input for the training jobs that the tuning job launches.

Definition at line 312 of file HyperParameterTrainingJobDefinition.h.

◆ Jsonize()

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

◆ operator=()

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

◆ OutputDataConfigHasBeenSet()

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

Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.

Definition at line 422 of file HyperParameterTrainingJobDefinition.h.

◆ ResourceConfigHasBeenSet()

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

The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.

Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want Amazon SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.

Definition at line 469 of file HyperParameterTrainingJobDefinition.h.

◆ RoleArnHasBeenSet()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::RoleArnHasBeenSet ( ) const
inline

The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.

Definition at line 263 of file HyperParameterTrainingJobDefinition.h.

◆ SetAlgorithmSpecification() [1/2]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetAlgorithmSpecification ( const HyperParameterAlgorithmSpecification value)
inline

The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.

Definition at line 229 of file HyperParameterTrainingJobDefinition.h.

◆ SetAlgorithmSpecification() [2/2]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetAlgorithmSpecification ( HyperParameterAlgorithmSpecification &&  value)
inline

The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.

Definition at line 236 of file HyperParameterTrainingJobDefinition.h.

◆ SetCheckpointConfig() [1/2]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetCheckpointConfig ( const CheckpointConfig value)
inline

Definition at line 675 of file HyperParameterTrainingJobDefinition.h.

◆ SetCheckpointConfig() [2/2]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetCheckpointConfig ( CheckpointConfig &&  value)
inline

Definition at line 678 of file HyperParameterTrainingJobDefinition.h.

◆ SetDefinitionName() [1/3]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetDefinitionName ( const Aws::String value)
inline

The job definition name.

Definition at line 65 of file HyperParameterTrainingJobDefinition.h.

◆ SetDefinitionName() [2/3]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetDefinitionName ( Aws::String &&  value)
inline

The job definition name.

Definition at line 70 of file HyperParameterTrainingJobDefinition.h.

◆ SetDefinitionName() [3/3]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetDefinitionName ( const char *  value)
inline

The job definition name.

Definition at line 75 of file HyperParameterTrainingJobDefinition.h.

◆ SetEnableInterContainerTrafficEncryption()

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetEnableInterContainerTrafficEncryption ( bool  value)
inline

To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.

Definition at line 631 of file HyperParameterTrainingJobDefinition.h.

◆ SetEnableManagedSpotTraining()

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetEnableManagedSpotTraining ( bool  value)
inline

A Boolean indicating whether managed spot training is enabled (True) or not (False).

Definition at line 659 of file HyperParameterTrainingJobDefinition.h.

◆ SetEnableNetworkIsolation()

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetEnableNetworkIsolation ( bool  value)
inline

Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, Amazon SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.

Definition at line 593 of file HyperParameterTrainingJobDefinition.h.

◆ SetHyperParameterRanges() [1/2]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetHyperParameterRanges ( const ParameterRanges value)
inline

Definition at line 119 of file HyperParameterTrainingJobDefinition.h.

◆ SetHyperParameterRanges() [2/2]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetHyperParameterRanges ( ParameterRanges &&  value)
inline

Definition at line 122 of file HyperParameterTrainingJobDefinition.h.

◆ SetInputDataConfig() [1/2]

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

An array of Channel objects that specify the input for the training jobs that the tuning job launches.

Definition at line 318 of file HyperParameterTrainingJobDefinition.h.

◆ SetInputDataConfig() [2/2]

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

An array of Channel objects that specify the input for the training jobs that the tuning job launches.

Definition at line 324 of file HyperParameterTrainingJobDefinition.h.

◆ SetOutputDataConfig() [1/2]

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

Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.

Definition at line 428 of file HyperParameterTrainingJobDefinition.h.

◆ SetOutputDataConfig() [2/2]

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

Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.

Definition at line 434 of file HyperParameterTrainingJobDefinition.h.

◆ SetResourceConfig() [1/2]

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

The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.

Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want Amazon SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.

Definition at line 480 of file HyperParameterTrainingJobDefinition.h.

◆ SetResourceConfig() [2/2]

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

The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.

Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want Amazon SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.

Definition at line 491 of file HyperParameterTrainingJobDefinition.h.

◆ SetRoleArn() [1/3]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetRoleArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.

Definition at line 269 of file HyperParameterTrainingJobDefinition.h.

◆ SetRoleArn() [2/3]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetRoleArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.

Definition at line 275 of file HyperParameterTrainingJobDefinition.h.

◆ SetRoleArn() [3/3]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetRoleArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.

Definition at line 281 of file HyperParameterTrainingJobDefinition.h.

◆ SetStaticHyperParameters() [1/2]

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

Specifies the values of hyperparameters that do not change for the tuning job.

Definition at line 147 of file HyperParameterTrainingJobDefinition.h.

◆ SetStaticHyperParameters() [2/2]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetStaticHyperParameters ( Aws::Map< Aws::String, Aws::String > &&  value)
inline

Specifies the values of hyperparameters that do not change for the tuning job.

Definition at line 153 of file HyperParameterTrainingJobDefinition.h.

◆ SetStoppingCondition() [1/2]

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

Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long you are willing to wait for a managed spot training job to complete. When the job reaches the a limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

Definition at line 538 of file HyperParameterTrainingJobDefinition.h.

◆ SetStoppingCondition() [2/2]

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

Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long you are willing to wait for a managed spot training job to complete. When the job reaches the a limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

Definition at line 546 of file HyperParameterTrainingJobDefinition.h.

◆ SetTuningObjective() [1/2]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetTuningObjective ( const HyperParameterTuningJobObjective value)
inline

Definition at line 100 of file HyperParameterTrainingJobDefinition.h.

◆ SetTuningObjective() [2/2]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetTuningObjective ( HyperParameterTuningJobObjective &&  value)
inline

Definition at line 103 of file HyperParameterTrainingJobDefinition.h.

◆ SetVpcConfig() [1/2]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetVpcConfig ( const VpcConfig value)
inline

The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Definition at line 379 of file HyperParameterTrainingJobDefinition.h.

◆ SetVpcConfig() [2/2]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetVpcConfig ( VpcConfig &&  value)
inline

The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Definition at line 389 of file HyperParameterTrainingJobDefinition.h.

◆ StaticHyperParametersHasBeenSet()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::StaticHyperParametersHasBeenSet ( ) const
inline

Specifies the values of hyperparameters that do not change for the tuning job.

Definition at line 141 of file HyperParameterTrainingJobDefinition.h.

◆ StoppingConditionHasBeenSet()

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

Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long you are willing to wait for a managed spot training job to complete. When the job reaches the a limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

Definition at line 530 of file HyperParameterTrainingJobDefinition.h.

◆ TuningObjectiveHasBeenSet()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::TuningObjectiveHasBeenSet ( ) const
inline

Definition at line 97 of file HyperParameterTrainingJobDefinition.h.

◆ VpcConfigHasBeenSet()

bool Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::VpcConfigHasBeenSet ( ) const
inline

The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Definition at line 369 of file HyperParameterTrainingJobDefinition.h.

◆ WithAlgorithmSpecification() [1/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithAlgorithmSpecification ( const HyperParameterAlgorithmSpecification value)
inline

The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.

Definition at line 243 of file HyperParameterTrainingJobDefinition.h.

◆ WithAlgorithmSpecification() [2/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithAlgorithmSpecification ( HyperParameterAlgorithmSpecification &&  value)
inline

The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.

Definition at line 250 of file HyperParameterTrainingJobDefinition.h.

◆ WithCheckpointConfig() [1/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithCheckpointConfig ( const CheckpointConfig value)
inline

Definition at line 681 of file HyperParameterTrainingJobDefinition.h.

◆ WithCheckpointConfig() [2/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithCheckpointConfig ( CheckpointConfig &&  value)
inline

Definition at line 684 of file HyperParameterTrainingJobDefinition.h.

◆ WithDefinitionName() [1/3]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithDefinitionName ( const Aws::String value)
inline

The job definition name.

Definition at line 80 of file HyperParameterTrainingJobDefinition.h.

◆ WithDefinitionName() [2/3]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithDefinitionName ( Aws::String &&  value)
inline

The job definition name.

Definition at line 85 of file HyperParameterTrainingJobDefinition.h.

◆ WithDefinitionName() [3/3]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithDefinitionName ( const char *  value)
inline

The job definition name.

Definition at line 90 of file HyperParameterTrainingJobDefinition.h.

◆ WithEnableInterContainerTrafficEncryption()

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithEnableInterContainerTrafficEncryption ( bool  value)
inline

To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.

Definition at line 640 of file HyperParameterTrainingJobDefinition.h.

◆ WithEnableManagedSpotTraining()

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithEnableManagedSpotTraining ( bool  value)
inline

A Boolean indicating whether managed spot training is enabled (True) or not (False).

Definition at line 665 of file HyperParameterTrainingJobDefinition.h.

◆ WithEnableNetworkIsolation()

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithEnableNetworkIsolation ( bool  value)
inline

Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, Amazon SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.

Definition at line 603 of file HyperParameterTrainingJobDefinition.h.

◆ WithHyperParameterRanges() [1/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithHyperParameterRanges ( const ParameterRanges value)
inline

Definition at line 125 of file HyperParameterTrainingJobDefinition.h.

◆ WithHyperParameterRanges() [2/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithHyperParameterRanges ( ParameterRanges &&  value)
inline

Definition at line 128 of file HyperParameterTrainingJobDefinition.h.

◆ WithInputDataConfig() [1/2]

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

An array of Channel objects that specify the input for the training jobs that the tuning job launches.

Definition at line 330 of file HyperParameterTrainingJobDefinition.h.

◆ WithInputDataConfig() [2/2]

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

An array of Channel objects that specify the input for the training jobs that the tuning job launches.

Definition at line 336 of file HyperParameterTrainingJobDefinition.h.

◆ WithOutputDataConfig() [1/2]

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

Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.

Definition at line 440 of file HyperParameterTrainingJobDefinition.h.

◆ WithOutputDataConfig() [2/2]

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

Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.

Definition at line 446 of file HyperParameterTrainingJobDefinition.h.

◆ WithResourceConfig() [1/2]

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

The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.

Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want Amazon SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.

Definition at line 502 of file HyperParameterTrainingJobDefinition.h.

◆ WithResourceConfig() [2/2]

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

The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.

Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want Amazon SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.

Definition at line 513 of file HyperParameterTrainingJobDefinition.h.

◆ WithRoleArn() [1/3]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithRoleArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.

Definition at line 287 of file HyperParameterTrainingJobDefinition.h.

◆ WithRoleArn() [2/3]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithRoleArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.

Definition at line 293 of file HyperParameterTrainingJobDefinition.h.

◆ WithRoleArn() [3/3]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithRoleArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.

Definition at line 299 of file HyperParameterTrainingJobDefinition.h.

◆ WithStaticHyperParameters() [1/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithStaticHyperParameters ( const Aws::Map< Aws::String, Aws::String > &  value)
inline

Specifies the values of hyperparameters that do not change for the tuning job.

Definition at line 159 of file HyperParameterTrainingJobDefinition.h.

◆ WithStaticHyperParameters() [2/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithStaticHyperParameters ( Aws::Map< Aws::String, Aws::String > &&  value)
inline

Specifies the values of hyperparameters that do not change for the tuning job.

Definition at line 165 of file HyperParameterTrainingJobDefinition.h.

◆ WithStoppingCondition() [1/2]

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

Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long you are willing to wait for a managed spot training job to complete. When the job reaches the a limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

Definition at line 554 of file HyperParameterTrainingJobDefinition.h.

◆ WithStoppingCondition() [2/2]

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

Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long you are willing to wait for a managed spot training job to complete. When the job reaches the a limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

Definition at line 562 of file HyperParameterTrainingJobDefinition.h.

◆ WithTuningObjective() [1/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithTuningObjective ( const HyperParameterTuningJobObjective value)
inline

Definition at line 106 of file HyperParameterTrainingJobDefinition.h.

◆ WithTuningObjective() [2/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithTuningObjective ( HyperParameterTuningJobObjective &&  value)
inline

Definition at line 109 of file HyperParameterTrainingJobDefinition.h.

◆ WithVpcConfig() [1/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithVpcConfig ( const VpcConfig value)
inline

The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Definition at line 399 of file HyperParameterTrainingJobDefinition.h.

◆ WithVpcConfig() [2/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithVpcConfig ( VpcConfig &&  value)
inline

The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Definition at line 409 of file HyperParameterTrainingJobDefinition.h.


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