AWS SDK for C++  1.9.123
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)
 
const RetryStrategyGetRetryStrategy () const
 
bool RetryStrategyHasBeenSet () const
 
void SetRetryStrategy (const RetryStrategy &value)
 
void SetRetryStrategy (RetryStrategy &&value)
 
HyperParameterTrainingJobDefinitionWithRetryStrategy (const RetryStrategy &value)
 
HyperParameterTrainingJobDefinitionWithRetryStrategy (RetryStrategy &&value)
 

Detailed Description

Defines the training jobs launched by a hyperparameter tuning job.

See Also:

AWS API Reference

Definition at line 44 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 ( Channel &&  value)
inline

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

Definition at line 349 of file HyperParameterTrainingJobDefinition.h.

◆ AddInputDataConfig() [2/2]

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 343 of file HyperParameterTrainingJobDefinition.h.

◆ AddStaticHyperParameters() [1/7]

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 190 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 178 of file HyperParameterTrainingJobDefinition.h.

◆ AddStaticHyperParameters() [3/7]

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 202 of file HyperParameterTrainingJobDefinition.h.

◆ AddStaticHyperParameters() [4/7]

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 184 of file HyperParameterTrainingJobDefinition.h.

◆ AddStaticHyperParameters() [5/7]

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 172 of file HyperParameterTrainingJobDefinition.h.

◆ AddStaticHyperParameters() [6/7]

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 196 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 208 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 223 of file HyperParameterTrainingJobDefinition.h.

◆ CheckpointConfigHasBeenSet()

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

Definition at line 673 of file HyperParameterTrainingJobDefinition.h.

◆ DefinitionNameHasBeenSet()

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

The job definition name.

Definition at line 61 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 623 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 654 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 584 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 216 of file HyperParameterTrainingJobDefinition.h.

◆ GetCheckpointConfig()

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

Definition at line 670 of file HyperParameterTrainingJobDefinition.h.

◆ GetDefinitionName()

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

The job definition name.

Definition at line 56 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 614 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 648 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 574 of file HyperParameterTrainingJobDefinition.h.

◆ GetHyperParameterRanges()

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

Definition at line 114 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 307 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 417 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 459 of file HyperParameterTrainingJobDefinition.h.

◆ GetRetryStrategy()

const RetryStrategy& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::GetRetryStrategy ( ) const
inline

The number of times to retry the job when the job fails due to an InternalServerError.

Definition at line 692 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 258 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 136 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 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.

Definition at line 523 of file HyperParameterTrainingJobDefinition.h.

◆ GetTuningObjective()

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

Definition at line 95 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 360 of file HyperParameterTrainingJobDefinition.h.

◆ HyperParameterRangesHasBeenSet()

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

Definition at line 117 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 313 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 423 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 470 of file HyperParameterTrainingJobDefinition.h.

◆ RetryStrategyHasBeenSet()

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

The number of times to retry the job when the job fails due to an InternalServerError.

Definition at line 698 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 264 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 230 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 237 of file HyperParameterTrainingJobDefinition.h.

◆ SetCheckpointConfig() [1/2]

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

Definition at line 679 of file HyperParameterTrainingJobDefinition.h.

◆ SetCheckpointConfig() [2/2]

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

Definition at line 676 of file HyperParameterTrainingJobDefinition.h.

◆ SetDefinitionName() [1/3]

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

The job definition name.

Definition at line 71 of file HyperParameterTrainingJobDefinition.h.

◆ SetDefinitionName() [2/3]

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

The job definition name.

Definition at line 66 of file HyperParameterTrainingJobDefinition.h.

◆ SetDefinitionName() [3/3]

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

The job definition name.

Definition at line 76 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 632 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 660 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 594 of file HyperParameterTrainingJobDefinition.h.

◆ SetHyperParameterRanges() [1/2]

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

Definition at line 120 of file HyperParameterTrainingJobDefinition.h.

◆ SetHyperParameterRanges() [2/2]

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

Definition at line 123 of file HyperParameterTrainingJobDefinition.h.

◆ SetInputDataConfig() [1/2]

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 325 of file HyperParameterTrainingJobDefinition.h.

◆ SetInputDataConfig() [2/2]

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 319 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 429 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 435 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 481 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 492 of file HyperParameterTrainingJobDefinition.h.

◆ SetRetryStrategy() [1/2]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetRetryStrategy ( const RetryStrategy value)
inline

The number of times to retry the job when the job fails due to an InternalServerError.

Definition at line 704 of file HyperParameterTrainingJobDefinition.h.

◆ SetRetryStrategy() [2/2]

void Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::SetRetryStrategy ( RetryStrategy &&  value)
inline

The number of times to retry the job when the job fails due to an InternalServerError.

Definition at line 710 of file HyperParameterTrainingJobDefinition.h.

◆ SetRoleArn() [1/3]

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 276 of file HyperParameterTrainingJobDefinition.h.

◆ SetRoleArn() [2/3]

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 270 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 282 of file HyperParameterTrainingJobDefinition.h.

◆ SetStaticHyperParameters() [1/2]

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 154 of file HyperParameterTrainingJobDefinition.h.

◆ SetStaticHyperParameters() [2/2]

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 148 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 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.

Definition at line 539 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 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.

Definition at line 547 of file HyperParameterTrainingJobDefinition.h.

◆ SetTuningObjective() [1/2]

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

Definition at line 101 of file HyperParameterTrainingJobDefinition.h.

◆ SetTuningObjective() [2/2]

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

Definition at line 104 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 380 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 390 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 142 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 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.

Definition at line 531 of file HyperParameterTrainingJobDefinition.h.

◆ TuningObjectiveHasBeenSet()

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

Definition at line 98 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 370 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 244 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 251 of file HyperParameterTrainingJobDefinition.h.

◆ WithCheckpointConfig() [1/2]

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

Definition at line 685 of file HyperParameterTrainingJobDefinition.h.

◆ WithCheckpointConfig() [2/2]

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

Definition at line 682 of file HyperParameterTrainingJobDefinition.h.

◆ WithDefinitionName() [1/3]

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

The job definition name.

Definition at line 86 of file HyperParameterTrainingJobDefinition.h.

◆ WithDefinitionName() [2/3]

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

The job definition name.

Definition at line 81 of file HyperParameterTrainingJobDefinition.h.

◆ WithDefinitionName() [3/3]

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

The job definition name.

Definition at line 91 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 641 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 666 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 604 of file HyperParameterTrainingJobDefinition.h.

◆ WithHyperParameterRanges() [1/2]

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

Definition at line 126 of file HyperParameterTrainingJobDefinition.h.

◆ WithHyperParameterRanges() [2/2]

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

Definition at line 129 of file HyperParameterTrainingJobDefinition.h.

◆ WithInputDataConfig() [1/2]

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 337 of file HyperParameterTrainingJobDefinition.h.

◆ WithInputDataConfig() [2/2]

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 331 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 441 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 447 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 503 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 514 of file HyperParameterTrainingJobDefinition.h.

◆ WithRetryStrategy() [1/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithRetryStrategy ( const RetryStrategy value)
inline

The number of times to retry the job when the job fails due to an InternalServerError.

Definition at line 716 of file HyperParameterTrainingJobDefinition.h.

◆ WithRetryStrategy() [2/2]

HyperParameterTrainingJobDefinition& Aws::SageMaker::Model::HyperParameterTrainingJobDefinition::WithRetryStrategy ( RetryStrategy &&  value)
inline

The number of times to retry the job when the job fails due to an InternalServerError.

Definition at line 722 of file HyperParameterTrainingJobDefinition.h.

◆ WithRoleArn() [1/3]

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 294 of file HyperParameterTrainingJobDefinition.h.

◆ WithRoleArn() [2/3]

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 288 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 300 of file HyperParameterTrainingJobDefinition.h.

◆ WithStaticHyperParameters() [1/2]

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 166 of file HyperParameterTrainingJobDefinition.h.

◆ WithStaticHyperParameters() [2/2]

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 160 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 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.

Definition at line 555 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 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.

Definition at line 563 of file HyperParameterTrainingJobDefinition.h.

◆ WithTuningObjective() [1/2]

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

Definition at line 107 of file HyperParameterTrainingJobDefinition.h.

◆ WithTuningObjective() [2/2]

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

Definition at line 110 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 400 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 410 of file HyperParameterTrainingJobDefinition.h.


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