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

#include <TrainingJob.h>

Public Member Functions

 TrainingJob ()
 
 TrainingJob (Aws::Utils::Json::JsonView jsonValue)
 
TrainingJoboperator= (Aws::Utils::Json::JsonView jsonValue)
 
Aws::Utils::Json::JsonValue Jsonize () const
 
const Aws::StringGetTrainingJobName () const
 
bool TrainingJobNameHasBeenSet () const
 
void SetTrainingJobName (const Aws::String &value)
 
void SetTrainingJobName (Aws::String &&value)
 
void SetTrainingJobName (const char *value)
 
TrainingJobWithTrainingJobName (const Aws::String &value)
 
TrainingJobWithTrainingJobName (Aws::String &&value)
 
TrainingJobWithTrainingJobName (const char *value)
 
const Aws::StringGetTrainingJobArn () const
 
bool TrainingJobArnHasBeenSet () const
 
void SetTrainingJobArn (const Aws::String &value)
 
void SetTrainingJobArn (Aws::String &&value)
 
void SetTrainingJobArn (const char *value)
 
TrainingJobWithTrainingJobArn (const Aws::String &value)
 
TrainingJobWithTrainingJobArn (Aws::String &&value)
 
TrainingJobWithTrainingJobArn (const char *value)
 
const Aws::StringGetTuningJobArn () const
 
bool TuningJobArnHasBeenSet () const
 
void SetTuningJobArn (const Aws::String &value)
 
void SetTuningJobArn (Aws::String &&value)
 
void SetTuningJobArn (const char *value)
 
TrainingJobWithTuningJobArn (const Aws::String &value)
 
TrainingJobWithTuningJobArn (Aws::String &&value)
 
TrainingJobWithTuningJobArn (const char *value)
 
const Aws::StringGetLabelingJobArn () const
 
bool LabelingJobArnHasBeenSet () const
 
void SetLabelingJobArn (const Aws::String &value)
 
void SetLabelingJobArn (Aws::String &&value)
 
void SetLabelingJobArn (const char *value)
 
TrainingJobWithLabelingJobArn (const Aws::String &value)
 
TrainingJobWithLabelingJobArn (Aws::String &&value)
 
TrainingJobWithLabelingJobArn (const char *value)
 
const Aws::StringGetAutoMLJobArn () const
 
bool AutoMLJobArnHasBeenSet () const
 
void SetAutoMLJobArn (const Aws::String &value)
 
void SetAutoMLJobArn (Aws::String &&value)
 
void SetAutoMLJobArn (const char *value)
 
TrainingJobWithAutoMLJobArn (const Aws::String &value)
 
TrainingJobWithAutoMLJobArn (Aws::String &&value)
 
TrainingJobWithAutoMLJobArn (const char *value)
 
const ModelArtifactsGetModelArtifacts () const
 
bool ModelArtifactsHasBeenSet () const
 
void SetModelArtifacts (const ModelArtifacts &value)
 
void SetModelArtifacts (ModelArtifacts &&value)
 
TrainingJobWithModelArtifacts (const ModelArtifacts &value)
 
TrainingJobWithModelArtifacts (ModelArtifacts &&value)
 
const TrainingJobStatusGetTrainingJobStatus () const
 
bool TrainingJobStatusHasBeenSet () const
 
void SetTrainingJobStatus (const TrainingJobStatus &value)
 
void SetTrainingJobStatus (TrainingJobStatus &&value)
 
TrainingJobWithTrainingJobStatus (const TrainingJobStatus &value)
 
TrainingJobWithTrainingJobStatus (TrainingJobStatus &&value)
 
const SecondaryStatusGetSecondaryStatus () const
 
bool SecondaryStatusHasBeenSet () const
 
void SetSecondaryStatus (const SecondaryStatus &value)
 
void SetSecondaryStatus (SecondaryStatus &&value)
 
TrainingJobWithSecondaryStatus (const SecondaryStatus &value)
 
TrainingJobWithSecondaryStatus (SecondaryStatus &&value)
 
const Aws::StringGetFailureReason () const
 
bool FailureReasonHasBeenSet () const
 
void SetFailureReason (const Aws::String &value)
 
void SetFailureReason (Aws::String &&value)
 
void SetFailureReason (const char *value)
 
TrainingJobWithFailureReason (const Aws::String &value)
 
TrainingJobWithFailureReason (Aws::String &&value)
 
TrainingJobWithFailureReason (const char *value)
 
const Aws::Map< Aws::String, Aws::String > & GetHyperParameters () const
 
bool HyperParametersHasBeenSet () const
 
void SetHyperParameters (const Aws::Map< Aws::String, Aws::String > &value)
 
void SetHyperParameters (Aws::Map< Aws::String, Aws::String > &&value)
 
TrainingJobWithHyperParameters (const Aws::Map< Aws::String, Aws::String > &value)
 
TrainingJobWithHyperParameters (Aws::Map< Aws::String, Aws::String > &&value)
 
TrainingJobAddHyperParameters (const Aws::String &key, const Aws::String &value)
 
TrainingJobAddHyperParameters (Aws::String &&key, const Aws::String &value)
 
TrainingJobAddHyperParameters (const Aws::String &key, Aws::String &&value)
 
TrainingJobAddHyperParameters (Aws::String &&key, Aws::String &&value)
 
TrainingJobAddHyperParameters (const char *key, Aws::String &&value)
 
TrainingJobAddHyperParameters (Aws::String &&key, const char *value)
 
TrainingJobAddHyperParameters (const char *key, const char *value)
 
const AlgorithmSpecificationGetAlgorithmSpecification () const
 
bool AlgorithmSpecificationHasBeenSet () const
 
void SetAlgorithmSpecification (const AlgorithmSpecification &value)
 
void SetAlgorithmSpecification (AlgorithmSpecification &&value)
 
TrainingJobWithAlgorithmSpecification (const AlgorithmSpecification &value)
 
TrainingJobWithAlgorithmSpecification (AlgorithmSpecification &&value)
 
const Aws::StringGetRoleArn () const
 
bool RoleArnHasBeenSet () const
 
void SetRoleArn (const Aws::String &value)
 
void SetRoleArn (Aws::String &&value)
 
void SetRoleArn (const char *value)
 
TrainingJobWithRoleArn (const Aws::String &value)
 
TrainingJobWithRoleArn (Aws::String &&value)
 
TrainingJobWithRoleArn (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)
 
TrainingJobWithInputDataConfig (const Aws::Vector< Channel > &value)
 
TrainingJobWithInputDataConfig (Aws::Vector< Channel > &&value)
 
TrainingJobAddInputDataConfig (const Channel &value)
 
TrainingJobAddInputDataConfig (Channel &&value)
 
const OutputDataConfigGetOutputDataConfig () const
 
bool OutputDataConfigHasBeenSet () const
 
void SetOutputDataConfig (const OutputDataConfig &value)
 
void SetOutputDataConfig (OutputDataConfig &&value)
 
TrainingJobWithOutputDataConfig (const OutputDataConfig &value)
 
TrainingJobWithOutputDataConfig (OutputDataConfig &&value)
 
const ResourceConfigGetResourceConfig () const
 
bool ResourceConfigHasBeenSet () const
 
void SetResourceConfig (const ResourceConfig &value)
 
void SetResourceConfig (ResourceConfig &&value)
 
TrainingJobWithResourceConfig (const ResourceConfig &value)
 
TrainingJobWithResourceConfig (ResourceConfig &&value)
 
const VpcConfigGetVpcConfig () const
 
bool VpcConfigHasBeenSet () const
 
void SetVpcConfig (const VpcConfig &value)
 
void SetVpcConfig (VpcConfig &&value)
 
TrainingJobWithVpcConfig (const VpcConfig &value)
 
TrainingJobWithVpcConfig (VpcConfig &&value)
 
const StoppingConditionGetStoppingCondition () const
 
bool StoppingConditionHasBeenSet () const
 
void SetStoppingCondition (const StoppingCondition &value)
 
void SetStoppingCondition (StoppingCondition &&value)
 
TrainingJobWithStoppingCondition (const StoppingCondition &value)
 
TrainingJobWithStoppingCondition (StoppingCondition &&value)
 
const Aws::Utils::DateTimeGetCreationTime () const
 
bool CreationTimeHasBeenSet () const
 
void SetCreationTime (const Aws::Utils::DateTime &value)
 
void SetCreationTime (Aws::Utils::DateTime &&value)
 
TrainingJobWithCreationTime (const Aws::Utils::DateTime &value)
 
TrainingJobWithCreationTime (Aws::Utils::DateTime &&value)
 
const Aws::Utils::DateTimeGetTrainingStartTime () const
 
bool TrainingStartTimeHasBeenSet () const
 
void SetTrainingStartTime (const Aws::Utils::DateTime &value)
 
void SetTrainingStartTime (Aws::Utils::DateTime &&value)
 
TrainingJobWithTrainingStartTime (const Aws::Utils::DateTime &value)
 
TrainingJobWithTrainingStartTime (Aws::Utils::DateTime &&value)
 
const Aws::Utils::DateTimeGetTrainingEndTime () const
 
bool TrainingEndTimeHasBeenSet () const
 
void SetTrainingEndTime (const Aws::Utils::DateTime &value)
 
void SetTrainingEndTime (Aws::Utils::DateTime &&value)
 
TrainingJobWithTrainingEndTime (const Aws::Utils::DateTime &value)
 
TrainingJobWithTrainingEndTime (Aws::Utils::DateTime &&value)
 
const Aws::Utils::DateTimeGetLastModifiedTime () const
 
bool LastModifiedTimeHasBeenSet () const
 
void SetLastModifiedTime (const Aws::Utils::DateTime &value)
 
void SetLastModifiedTime (Aws::Utils::DateTime &&value)
 
TrainingJobWithLastModifiedTime (const Aws::Utils::DateTime &value)
 
TrainingJobWithLastModifiedTime (Aws::Utils::DateTime &&value)
 
const Aws::Vector< SecondaryStatusTransition > & GetSecondaryStatusTransitions () const
 
bool SecondaryStatusTransitionsHasBeenSet () const
 
void SetSecondaryStatusTransitions (const Aws::Vector< SecondaryStatusTransition > &value)
 
void SetSecondaryStatusTransitions (Aws::Vector< SecondaryStatusTransition > &&value)
 
TrainingJobWithSecondaryStatusTransitions (const Aws::Vector< SecondaryStatusTransition > &value)
 
TrainingJobWithSecondaryStatusTransitions (Aws::Vector< SecondaryStatusTransition > &&value)
 
TrainingJobAddSecondaryStatusTransitions (const SecondaryStatusTransition &value)
 
TrainingJobAddSecondaryStatusTransitions (SecondaryStatusTransition &&value)
 
const Aws::Vector< MetricData > & GetFinalMetricDataList () const
 
bool FinalMetricDataListHasBeenSet () const
 
void SetFinalMetricDataList (const Aws::Vector< MetricData > &value)
 
void SetFinalMetricDataList (Aws::Vector< MetricData > &&value)
 
TrainingJobWithFinalMetricDataList (const Aws::Vector< MetricData > &value)
 
TrainingJobWithFinalMetricDataList (Aws::Vector< MetricData > &&value)
 
TrainingJobAddFinalMetricDataList (const MetricData &value)
 
TrainingJobAddFinalMetricDataList (MetricData &&value)
 
bool GetEnableNetworkIsolation () const
 
bool EnableNetworkIsolationHasBeenSet () const
 
void SetEnableNetworkIsolation (bool value)
 
TrainingJobWithEnableNetworkIsolation (bool value)
 
bool GetEnableInterContainerTrafficEncryption () const
 
bool EnableInterContainerTrafficEncryptionHasBeenSet () const
 
void SetEnableInterContainerTrafficEncryption (bool value)
 
TrainingJobWithEnableInterContainerTrafficEncryption (bool value)
 
bool GetEnableManagedSpotTraining () const
 
bool EnableManagedSpotTrainingHasBeenSet () const
 
void SetEnableManagedSpotTraining (bool value)
 
TrainingJobWithEnableManagedSpotTraining (bool value)
 
const CheckpointConfigGetCheckpointConfig () const
 
bool CheckpointConfigHasBeenSet () const
 
void SetCheckpointConfig (const CheckpointConfig &value)
 
void SetCheckpointConfig (CheckpointConfig &&value)
 
TrainingJobWithCheckpointConfig (const CheckpointConfig &value)
 
TrainingJobWithCheckpointConfig (CheckpointConfig &&value)
 
int GetTrainingTimeInSeconds () const
 
bool TrainingTimeInSecondsHasBeenSet () const
 
void SetTrainingTimeInSeconds (int value)
 
TrainingJobWithTrainingTimeInSeconds (int value)
 
int GetBillableTimeInSeconds () const
 
bool BillableTimeInSecondsHasBeenSet () const
 
void SetBillableTimeInSeconds (int value)
 
TrainingJobWithBillableTimeInSeconds (int value)
 
const DebugHookConfigGetDebugHookConfig () const
 
bool DebugHookConfigHasBeenSet () const
 
void SetDebugHookConfig (const DebugHookConfig &value)
 
void SetDebugHookConfig (DebugHookConfig &&value)
 
TrainingJobWithDebugHookConfig (const DebugHookConfig &value)
 
TrainingJobWithDebugHookConfig (DebugHookConfig &&value)
 
const ExperimentConfigGetExperimentConfig () const
 
bool ExperimentConfigHasBeenSet () const
 
void SetExperimentConfig (const ExperimentConfig &value)
 
void SetExperimentConfig (ExperimentConfig &&value)
 
TrainingJobWithExperimentConfig (const ExperimentConfig &value)
 
TrainingJobWithExperimentConfig (ExperimentConfig &&value)
 
const Aws::Vector< DebugRuleConfiguration > & GetDebugRuleConfigurations () const
 
bool DebugRuleConfigurationsHasBeenSet () const
 
void SetDebugRuleConfigurations (const Aws::Vector< DebugRuleConfiguration > &value)
 
void SetDebugRuleConfigurations (Aws::Vector< DebugRuleConfiguration > &&value)
 
TrainingJobWithDebugRuleConfigurations (const Aws::Vector< DebugRuleConfiguration > &value)
 
TrainingJobWithDebugRuleConfigurations (Aws::Vector< DebugRuleConfiguration > &&value)
 
TrainingJobAddDebugRuleConfigurations (const DebugRuleConfiguration &value)
 
TrainingJobAddDebugRuleConfigurations (DebugRuleConfiguration &&value)
 
const TensorBoardOutputConfigGetTensorBoardOutputConfig () const
 
bool TensorBoardOutputConfigHasBeenSet () const
 
void SetTensorBoardOutputConfig (const TensorBoardOutputConfig &value)
 
void SetTensorBoardOutputConfig (TensorBoardOutputConfig &&value)
 
TrainingJobWithTensorBoardOutputConfig (const TensorBoardOutputConfig &value)
 
TrainingJobWithTensorBoardOutputConfig (TensorBoardOutputConfig &&value)
 
const Aws::Vector< DebugRuleEvaluationStatus > & GetDebugRuleEvaluationStatuses () const
 
bool DebugRuleEvaluationStatusesHasBeenSet () const
 
void SetDebugRuleEvaluationStatuses (const Aws::Vector< DebugRuleEvaluationStatus > &value)
 
void SetDebugRuleEvaluationStatuses (Aws::Vector< DebugRuleEvaluationStatus > &&value)
 
TrainingJobWithDebugRuleEvaluationStatuses (const Aws::Vector< DebugRuleEvaluationStatus > &value)
 
TrainingJobWithDebugRuleEvaluationStatuses (Aws::Vector< DebugRuleEvaluationStatus > &&value)
 
TrainingJobAddDebugRuleEvaluationStatuses (const DebugRuleEvaluationStatus &value)
 
TrainingJobAddDebugRuleEvaluationStatuses (DebugRuleEvaluationStatus &&value)
 
const Aws::Map< Aws::String, Aws::String > & GetEnvironment () const
 
bool EnvironmentHasBeenSet () const
 
void SetEnvironment (const Aws::Map< Aws::String, Aws::String > &value)
 
void SetEnvironment (Aws::Map< Aws::String, Aws::String > &&value)
 
TrainingJobWithEnvironment (const Aws::Map< Aws::String, Aws::String > &value)
 
TrainingJobWithEnvironment (Aws::Map< Aws::String, Aws::String > &&value)
 
TrainingJobAddEnvironment (const Aws::String &key, const Aws::String &value)
 
TrainingJobAddEnvironment (Aws::String &&key, const Aws::String &value)
 
TrainingJobAddEnvironment (const Aws::String &key, Aws::String &&value)
 
TrainingJobAddEnvironment (Aws::String &&key, Aws::String &&value)
 
TrainingJobAddEnvironment (const char *key, Aws::String &&value)
 
TrainingJobAddEnvironment (Aws::String &&key, const char *value)
 
TrainingJobAddEnvironment (const char *key, const char *value)
 
const RetryStrategyGetRetryStrategy () const
 
bool RetryStrategyHasBeenSet () const
 
void SetRetryStrategy (const RetryStrategy &value)
 
void SetRetryStrategy (RetryStrategy &&value)
 
TrainingJobWithRetryStrategy (const RetryStrategy &value)
 
TrainingJobWithRetryStrategy (RetryStrategy &&value)
 
const Aws::Vector< Tag > & GetTags () const
 
bool TagsHasBeenSet () const
 
void SetTags (const Aws::Vector< Tag > &value)
 
void SetTags (Aws::Vector< Tag > &&value)
 
TrainingJobWithTags (const Aws::Vector< Tag > &value)
 
TrainingJobWithTags (Aws::Vector< Tag > &&value)
 
TrainingJobAddTags (const Tag &value)
 
TrainingJobAddTags (Tag &&value)
 

Detailed Description

Contains information about a training job.

See Also:

AWS API Reference

Definition at line 53 of file TrainingJob.h.

Constructor & Destructor Documentation

◆ TrainingJob() [1/2]

Aws::SageMaker::Model::TrainingJob::TrainingJob ( )

◆ TrainingJob() [2/2]

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

Member Function Documentation

◆ AddDebugRuleConfigurations() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddDebugRuleConfigurations ( const DebugRuleConfiguration value)
inline

Information about the debug rule configuration.

Definition at line 1505 of file TrainingJob.h.

◆ AddDebugRuleConfigurations() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddDebugRuleConfigurations ( DebugRuleConfiguration &&  value)
inline

Information about the debug rule configuration.

Definition at line 1510 of file TrainingJob.h.

◆ AddDebugRuleEvaluationStatuses() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddDebugRuleEvaluationStatuses ( const DebugRuleEvaluationStatus value)
inline

Information about the evaluation status of the rules for the training job.

Definition at line 1572 of file TrainingJob.h.

◆ AddDebugRuleEvaluationStatuses() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddDebugRuleEvaluationStatuses ( DebugRuleEvaluationStatus &&  value)
inline

Information about the evaluation status of the rules for the training job.

Definition at line 1578 of file TrainingJob.h.

◆ AddEnvironment() [1/7]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddEnvironment ( Aws::String &&  key,
Aws::String &&  value 
)
inline

The environment variables to set in the Docker container.

Definition at line 1629 of file TrainingJob.h.

◆ AddEnvironment() [2/7]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddEnvironment ( Aws::String &&  key,
const Aws::String value 
)
inline

The environment variables to set in the Docker container.

Definition at line 1619 of file TrainingJob.h.

◆ AddEnvironment() [3/7]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddEnvironment ( Aws::String &&  key,
const char *  value 
)
inline

The environment variables to set in the Docker container.

Definition at line 1639 of file TrainingJob.h.

◆ AddEnvironment() [4/7]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddEnvironment ( const Aws::String key,
Aws::String &&  value 
)
inline

The environment variables to set in the Docker container.

Definition at line 1624 of file TrainingJob.h.

◆ AddEnvironment() [5/7]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddEnvironment ( const Aws::String key,
const Aws::String value 
)
inline

The environment variables to set in the Docker container.

Definition at line 1614 of file TrainingJob.h.

◆ AddEnvironment() [6/7]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddEnvironment ( const char *  key,
Aws::String &&  value 
)
inline

The environment variables to set in the Docker container.

Definition at line 1634 of file TrainingJob.h.

◆ AddEnvironment() [7/7]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddEnvironment ( const char *  key,
const char *  value 
)
inline

The environment variables to set in the Docker container.

Definition at line 1644 of file TrainingJob.h.

◆ AddFinalMetricDataList() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddFinalMetricDataList ( const MetricData value)
inline

A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.

Definition at line 1265 of file TrainingJob.h.

◆ AddFinalMetricDataList() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddFinalMetricDataList ( MetricData &&  value)
inline

A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.

Definition at line 1271 of file TrainingJob.h.

◆ AddHyperParameters() [1/7]

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

Algorithm-specific parameters.

Definition at line 655 of file TrainingJob.h.

◆ AddHyperParameters() [2/7]

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

Algorithm-specific parameters.

Definition at line 645 of file TrainingJob.h.

◆ AddHyperParameters() [3/7]

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

Algorithm-specific parameters.

Definition at line 665 of file TrainingJob.h.

◆ AddHyperParameters() [4/7]

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

Algorithm-specific parameters.

Definition at line 650 of file TrainingJob.h.

◆ AddHyperParameters() [5/7]

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

Algorithm-specific parameters.

Definition at line 640 of file TrainingJob.h.

◆ AddHyperParameters() [6/7]

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

Algorithm-specific parameters.

Definition at line 660 of file TrainingJob.h.

◆ AddHyperParameters() [7/7]

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

Algorithm-specific parameters.

Definition at line 670 of file TrainingJob.h.

◆ AddInputDataConfig() [1/2]

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

An array of Channel objects that describes each data input channel.

Definition at line 805 of file TrainingJob.h.

◆ AddInputDataConfig() [2/2]

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

An array of Channel objects that describes each data input channel.

Definition at line 799 of file TrainingJob.h.

◆ AddSecondaryStatusTransitions() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddSecondaryStatusTransitions ( const SecondaryStatusTransition value)
inline

A history of all of the secondary statuses that the training job has transitioned through.

Definition at line 1216 of file TrainingJob.h.

◆ AddSecondaryStatusTransitions() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::AddSecondaryStatusTransitions ( SecondaryStatusTransition &&  value)
inline

A history of all of the secondary statuses that the training job has transitioned through.

Definition at line 1222 of file TrainingJob.h.

◆ AddTags() [1/2]

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

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

Definition at line 1745 of file TrainingJob.h.

◆ AddTags() [2/2]

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

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

Definition at line 1754 of file TrainingJob.h.

◆ AlgorithmSpecificationHasBeenSet()

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

Information about the algorithm used for training, and algorithm metadata.

Definition at line 683 of file TrainingJob.h.

◆ AutoMLJobArnHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::AutoMLJobArnHasBeenSet ( ) const
inline

The Amazon Resource Name (ARN) of the job.

Definition at line 242 of file TrainingJob.h.

◆ BillableTimeInSecondsHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::BillableTimeInSecondsHasBeenSet ( ) const
inline

The billable time in seconds.

Definition at line 1421 of file TrainingJob.h.

◆ CheckpointConfigHasBeenSet()

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

Definition at line 1377 of file TrainingJob.h.

◆ CreationTimeHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::CreationTimeHasBeenSet ( ) const
inline

A timestamp that indicates when the training job was created.

Definition at line 1006 of file TrainingJob.h.

◆ DebugHookConfigHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::DebugHookConfigHasBeenSet ( ) const
inline

Definition at line 1438 of file TrainingJob.h.

◆ DebugRuleConfigurationsHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::DebugRuleConfigurationsHasBeenSet ( ) const
inline

Information about the debug rule configuration.

Definition at line 1480 of file TrainingJob.h.

◆ DebugRuleEvaluationStatusesHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::DebugRuleEvaluationStatusesHasBeenSet ( ) const
inline

Information about the evaluation status of the rules for the training job.

Definition at line 1542 of file TrainingJob.h.

◆ EnableInterContainerTrafficEncryptionHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::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 1319 of file TrainingJob.h.

◆ EnableManagedSpotTrainingHasBeenSet()

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

When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.

Definition at line 1354 of file TrainingJob.h.

◆ EnableNetworkIsolationHasBeenSet()

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

If the TrainingJob was created with network isolation, the value is set to true. If network isolation is enabled, nodes can't communicate beyond the VPC they run in.

Definition at line 1286 of file TrainingJob.h.

◆ EnvironmentHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::EnvironmentHasBeenSet ( ) const
inline

The environment variables to set in the Docker container.

Definition at line 1589 of file TrainingJob.h.

◆ ExperimentConfigHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::ExperimentConfigHasBeenSet ( ) const
inline

Definition at line 1457 of file TrainingJob.h.

◆ FailureReasonHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::FailureReasonHasBeenSet ( ) const
inline

If the training job failed, the reason it failed.

Definition at line 574 of file TrainingJob.h.

◆ FinalMetricDataListHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::FinalMetricDataListHasBeenSet ( ) const
inline

A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.

Definition at line 1235 of file TrainingJob.h.

◆ GetAlgorithmSpecification()

const AlgorithmSpecification& Aws::SageMaker::Model::TrainingJob::GetAlgorithmSpecification ( ) const
inline

Information about the algorithm used for training, and algorithm metadata.

Definition at line 677 of file TrainingJob.h.

◆ GetAutoMLJobArn()

const Aws::String& Aws::SageMaker::Model::TrainingJob::GetAutoMLJobArn ( ) const
inline

The Amazon Resource Name (ARN) of the job.

Definition at line 237 of file TrainingJob.h.

◆ GetBillableTimeInSeconds()

int Aws::SageMaker::Model::TrainingJob::GetBillableTimeInSeconds ( ) const
inline

The billable time in seconds.

Definition at line 1416 of file TrainingJob.h.

◆ GetCheckpointConfig()

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

Definition at line 1374 of file TrainingJob.h.

◆ GetCreationTime()

const Aws::Utils::DateTime& Aws::SageMaker::Model::TrainingJob::GetCreationTime ( ) const
inline

A timestamp that indicates when the training job was created.

Definition at line 1001 of file TrainingJob.h.

◆ GetDebugHookConfig()

const DebugHookConfig& Aws::SageMaker::Model::TrainingJob::GetDebugHookConfig ( ) const
inline

Definition at line 1435 of file TrainingJob.h.

◆ GetDebugRuleConfigurations()

const Aws::Vector<DebugRuleConfiguration>& Aws::SageMaker::Model::TrainingJob::GetDebugRuleConfigurations ( ) const
inline

Information about the debug rule configuration.

Definition at line 1475 of file TrainingJob.h.

◆ GetDebugRuleEvaluationStatuses()

const Aws::Vector<DebugRuleEvaluationStatus>& Aws::SageMaker::Model::TrainingJob::GetDebugRuleEvaluationStatuses ( ) const
inline

Information about the evaluation status of the rules for the training job.

Definition at line 1536 of file TrainingJob.h.

◆ GetEnableInterContainerTrafficEncryption()

bool Aws::SageMaker::Model::TrainingJob::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 1310 of file TrainingJob.h.

◆ GetEnableManagedSpotTraining()

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

When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.

Definition at line 1346 of file TrainingJob.h.

◆ GetEnableNetworkIsolation()

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

If the TrainingJob was created with network isolation, the value is set to true. If network isolation is enabled, nodes can't communicate beyond the VPC they run in.

Definition at line 1279 of file TrainingJob.h.

◆ GetEnvironment()

const Aws::Map<Aws::String, Aws::String>& Aws::SageMaker::Model::TrainingJob::GetEnvironment ( ) const
inline

The environment variables to set in the Docker container.

Definition at line 1584 of file TrainingJob.h.

◆ GetExperimentConfig()

const ExperimentConfig& Aws::SageMaker::Model::TrainingJob::GetExperimentConfig ( ) const
inline

Definition at line 1454 of file TrainingJob.h.

◆ GetFailureReason()

const Aws::String& Aws::SageMaker::Model::TrainingJob::GetFailureReason ( ) const
inline

If the training job failed, the reason it failed.

Definition at line 569 of file TrainingJob.h.

◆ GetFinalMetricDataList()

const Aws::Vector<MetricData>& Aws::SageMaker::Model::TrainingJob::GetFinalMetricDataList ( ) const
inline

A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.

Definition at line 1229 of file TrainingJob.h.

◆ GetHyperParameters()

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

Algorithm-specific parameters.

Definition at line 610 of file TrainingJob.h.

◆ GetInputDataConfig()

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

An array of Channel objects that describes each data input channel.

Definition at line 763 of file TrainingJob.h.

◆ GetLabelingJobArn()

const Aws::String& Aws::SageMaker::Model::TrainingJob::GetLabelingJobArn ( ) const
inline

The Amazon Resource Name (ARN) of the labeling job.

Definition at line 196 of file TrainingJob.h.

◆ GetLastModifiedTime()

const Aws::Utils::DateTime& Aws::SageMaker::Model::TrainingJob::GetLastModifiedTime ( ) const
inline

A timestamp that indicates when the status of the training job was last modified.

Definition at line 1143 of file TrainingJob.h.

◆ GetModelArtifacts()

const ModelArtifacts& Aws::SageMaker::Model::TrainingJob::GetModelArtifacts ( ) const
inline

Information about the Amazon S3 location that is configured for storing model artifacts.

Definition at line 279 of file TrainingJob.h.

◆ GetOutputDataConfig()

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

The S3 path where model artifacts that you configured when creating the job are stored. Amazon SageMaker creates subfolders for model artifacts.

Definition at line 812 of file TrainingJob.h.

◆ GetResourceConfig()

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

Resources, including ML compute instances and ML storage volumes, that are configured for model training.

Definition at line 849 of file TrainingJob.h.

◆ GetRetryStrategy()

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

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

Definition at line 1651 of file TrainingJob.h.

◆ GetRoleArn()

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

The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.

Definition at line 714 of file TrainingJob.h.

◆ GetSecondaryStatus()

const SecondaryStatus& Aws::SageMaker::Model::TrainingJob::GetSecondaryStatus ( ) const
inline

Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.

Amazon SageMaker provides primary statuses and secondary statuses that apply to each of them:

InProgress
  • Starting - Starting the training job.

  • Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.

  • Training - Training is in progress.

  • Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.

Completed
  • Completed - The training job has completed.

Failed
  • Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.

Stopped
  • MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.

  • Stopped - The training job has stopped.

Stopping
  • Stopping - Stopping the training job.

Valid values for SecondaryStatus are subject to change.

We no longer support the following secondary statuses:

  • LaunchingMLInstances

  • PreparingTrainingStack

  • DownloadingTrainingImage

Definition at line 418 of file TrainingJob.h.

◆ GetSecondaryStatusTransitions()

const Aws::Vector<SecondaryStatusTransition>& Aws::SageMaker::Model::TrainingJob::GetSecondaryStatusTransitions ( ) const
inline

A history of all of the secondary statuses that the training job has transitioned through.

Definition at line 1180 of file TrainingJob.h.

◆ GetStoppingCondition()

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

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

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.

Definition at line 940 of file TrainingJob.h.

◆ GetTags()

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

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

Definition at line 1691 of file TrainingJob.h.

◆ GetTensorBoardOutputConfig()

const TensorBoardOutputConfig& Aws::SageMaker::Model::TrainingJob::GetTensorBoardOutputConfig ( ) const
inline

Definition at line 1514 of file TrainingJob.h.

◆ GetTrainingEndTime()

const Aws::Utils::DateTime& Aws::SageMaker::Model::TrainingJob::GetTrainingEndTime ( ) const
inline

Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when Amazon SageMaker detects a job failure.

Definition at line 1091 of file TrainingJob.h.

◆ GetTrainingJobArn()

const Aws::String& Aws::SageMaker::Model::TrainingJob::GetTrainingJobArn ( ) const
inline

The Amazon Resource Name (ARN) of the training job.

Definition at line 106 of file TrainingJob.h.

◆ GetTrainingJobName()

const Aws::String& Aws::SageMaker::Model::TrainingJob::GetTrainingJobName ( ) const
inline

The name of the training job.

Definition at line 65 of file TrainingJob.h.

◆ GetTrainingJobStatus()

const TrainingJobStatus& Aws::SageMaker::Model::TrainingJob::GetTrainingJobStatus ( ) const
inline

The status of the training job.

Training job statuses are:

  • InProgress - The training is in progress.

  • Completed - The training job has completed.

  • Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.

  • Stopping - The training job is stopping.

  • Stopped - The training job has stopped.

For more detailed information, see SecondaryStatus.

Definition at line 323 of file TrainingJob.h.

◆ GetTrainingStartTime()

const Aws::Utils::DateTime& Aws::SageMaker::Model::TrainingJob::GetTrainingStartTime ( ) const
inline

Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.

Definition at line 1036 of file TrainingJob.h.

◆ GetTrainingTimeInSeconds()

int Aws::SageMaker::Model::TrainingJob::GetTrainingTimeInSeconds ( ) const
inline

The training time in seconds.

Definition at line 1395 of file TrainingJob.h.

◆ GetTuningJobArn()

const Aws::String& Aws::SageMaker::Model::TrainingJob::GetTuningJobArn ( ) const
inline

The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.

Definition at line 148 of file TrainingJob.h.

◆ GetVpcConfig()

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

A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Definition at line 888 of file TrainingJob.h.

◆ HyperParametersHasBeenSet()

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

Algorithm-specific parameters.

Definition at line 615 of file TrainingJob.h.

◆ InputDataConfigHasBeenSet()

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

An array of Channel objects that describes each data input channel.

Definition at line 769 of file TrainingJob.h.

◆ Jsonize()

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

◆ LabelingJobArnHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::LabelingJobArnHasBeenSet ( ) const
inline

The Amazon Resource Name (ARN) of the labeling job.

Definition at line 201 of file TrainingJob.h.

◆ LastModifiedTimeHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::LastModifiedTimeHasBeenSet ( ) const
inline

A timestamp that indicates when the status of the training job was last modified.

Definition at line 1149 of file TrainingJob.h.

◆ ModelArtifactsHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::ModelArtifactsHasBeenSet ( ) const
inline

Information about the Amazon S3 location that is configured for storing model artifacts.

Definition at line 285 of file TrainingJob.h.

◆ operator=()

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

◆ OutputDataConfigHasBeenSet()

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

The S3 path where model artifacts that you configured when creating the job are stored. Amazon SageMaker creates subfolders for model artifacts.

Definition at line 818 of file TrainingJob.h.

◆ ResourceConfigHasBeenSet()

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

Resources, including ML compute instances and ML storage volumes, that are configured for model training.

Definition at line 855 of file TrainingJob.h.

◆ RetryStrategyHasBeenSet()

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

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

Definition at line 1657 of file TrainingJob.h.

◆ RoleArnHasBeenSet()

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

The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.

Definition at line 720 of file TrainingJob.h.

◆ SecondaryStatusHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::SecondaryStatusHasBeenSet ( ) const
inline

Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.

Amazon SageMaker provides primary statuses and secondary statuses that apply to each of them:

InProgress
  • Starting - Starting the training job.

  • Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.

  • Training - Training is in progress.

  • Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.

Completed
  • Completed - The training job has completed.

Failed
  • Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.

Stopped
  • MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.

  • Stopped - The training job has stopped.

Stopping
  • Stopping - Stopping the training job.

Valid values for SecondaryStatus are subject to change.

We no longer support the following secondary statuses:

  • LaunchingMLInstances

  • PreparingTrainingStack

  • DownloadingTrainingImage

Definition at line 447 of file TrainingJob.h.

◆ SecondaryStatusTransitionsHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::SecondaryStatusTransitionsHasBeenSet ( ) const
inline

A history of all of the secondary statuses that the training job has transitioned through.

Definition at line 1186 of file TrainingJob.h.

◆ SetAlgorithmSpecification() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetAlgorithmSpecification ( AlgorithmSpecification &&  value)
inline

Information about the algorithm used for training, and algorithm metadata.

Definition at line 695 of file TrainingJob.h.

◆ SetAlgorithmSpecification() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetAlgorithmSpecification ( const AlgorithmSpecification value)
inline

Information about the algorithm used for training, and algorithm metadata.

Definition at line 689 of file TrainingJob.h.

◆ SetAutoMLJobArn() [1/3]

void Aws::SageMaker::Model::TrainingJob::SetAutoMLJobArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the job.

Definition at line 252 of file TrainingJob.h.

◆ SetAutoMLJobArn() [2/3]

void Aws::SageMaker::Model::TrainingJob::SetAutoMLJobArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the job.

Definition at line 247 of file TrainingJob.h.

◆ SetAutoMLJobArn() [3/3]

void Aws::SageMaker::Model::TrainingJob::SetAutoMLJobArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the job.

Definition at line 257 of file TrainingJob.h.

◆ SetBillableTimeInSeconds()

void Aws::SageMaker::Model::TrainingJob::SetBillableTimeInSeconds ( int  value)
inline

The billable time in seconds.

Definition at line 1426 of file TrainingJob.h.

◆ SetCheckpointConfig() [1/2]

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

Definition at line 1383 of file TrainingJob.h.

◆ SetCheckpointConfig() [2/2]

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

Definition at line 1380 of file TrainingJob.h.

◆ SetCreationTime() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetCreationTime ( Aws::Utils::DateTime &&  value)
inline

A timestamp that indicates when the training job was created.

Definition at line 1016 of file TrainingJob.h.

◆ SetCreationTime() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetCreationTime ( const Aws::Utils::DateTime value)
inline

A timestamp that indicates when the training job was created.

Definition at line 1011 of file TrainingJob.h.

◆ SetDebugHookConfig() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetDebugHookConfig ( const DebugHookConfig value)
inline

Definition at line 1441 of file TrainingJob.h.

◆ SetDebugHookConfig() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetDebugHookConfig ( DebugHookConfig &&  value)
inline

Definition at line 1444 of file TrainingJob.h.

◆ SetDebugRuleConfigurations() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetDebugRuleConfigurations ( Aws::Vector< DebugRuleConfiguration > &&  value)
inline

Information about the debug rule configuration.

Definition at line 1490 of file TrainingJob.h.

◆ SetDebugRuleConfigurations() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetDebugRuleConfigurations ( const Aws::Vector< DebugRuleConfiguration > &  value)
inline

Information about the debug rule configuration.

Definition at line 1485 of file TrainingJob.h.

◆ SetDebugRuleEvaluationStatuses() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetDebugRuleEvaluationStatuses ( Aws::Vector< DebugRuleEvaluationStatus > &&  value)
inline

Information about the evaluation status of the rules for the training job.

Definition at line 1554 of file TrainingJob.h.

◆ SetDebugRuleEvaluationStatuses() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetDebugRuleEvaluationStatuses ( const Aws::Vector< DebugRuleEvaluationStatus > &  value)
inline

Information about the evaluation status of the rules for the training job.

Definition at line 1548 of file TrainingJob.h.

◆ SetEnableInterContainerTrafficEncryption()

void Aws::SageMaker::Model::TrainingJob::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 1328 of file TrainingJob.h.

◆ SetEnableManagedSpotTraining()

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

When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.

Definition at line 1362 of file TrainingJob.h.

◆ SetEnableNetworkIsolation()

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

If the TrainingJob was created with network isolation, the value is set to true. If network isolation is enabled, nodes can't communicate beyond the VPC they run in.

Definition at line 1293 of file TrainingJob.h.

◆ SetEnvironment() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetEnvironment ( Aws::Map< Aws::String, Aws::String > &&  value)
inline

The environment variables to set in the Docker container.

Definition at line 1599 of file TrainingJob.h.

◆ SetEnvironment() [2/2]

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

The environment variables to set in the Docker container.

Definition at line 1594 of file TrainingJob.h.

◆ SetExperimentConfig() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetExperimentConfig ( const ExperimentConfig value)
inline

Definition at line 1460 of file TrainingJob.h.

◆ SetExperimentConfig() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetExperimentConfig ( ExperimentConfig &&  value)
inline

Definition at line 1463 of file TrainingJob.h.

◆ SetFailureReason() [1/3]

void Aws::SageMaker::Model::TrainingJob::SetFailureReason ( Aws::String &&  value)
inline

If the training job failed, the reason it failed.

Definition at line 584 of file TrainingJob.h.

◆ SetFailureReason() [2/3]

void Aws::SageMaker::Model::TrainingJob::SetFailureReason ( const Aws::String value)
inline

If the training job failed, the reason it failed.

Definition at line 579 of file TrainingJob.h.

◆ SetFailureReason() [3/3]

void Aws::SageMaker::Model::TrainingJob::SetFailureReason ( const char *  value)
inline

If the training job failed, the reason it failed.

Definition at line 589 of file TrainingJob.h.

◆ SetFinalMetricDataList() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetFinalMetricDataList ( Aws::Vector< MetricData > &&  value)
inline

A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.

Definition at line 1247 of file TrainingJob.h.

◆ SetFinalMetricDataList() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetFinalMetricDataList ( const Aws::Vector< MetricData > &  value)
inline

A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.

Definition at line 1241 of file TrainingJob.h.

◆ SetHyperParameters() [1/2]

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

Algorithm-specific parameters.

Definition at line 625 of file TrainingJob.h.

◆ SetHyperParameters() [2/2]

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

Algorithm-specific parameters.

Definition at line 620 of file TrainingJob.h.

◆ SetInputDataConfig() [1/2]

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

An array of Channel objects that describes each data input channel.

Definition at line 781 of file TrainingJob.h.

◆ SetInputDataConfig() [2/2]

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

An array of Channel objects that describes each data input channel.

Definition at line 775 of file TrainingJob.h.

◆ SetLabelingJobArn() [1/3]

void Aws::SageMaker::Model::TrainingJob::SetLabelingJobArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the labeling job.

Definition at line 211 of file TrainingJob.h.

◆ SetLabelingJobArn() [2/3]

void Aws::SageMaker::Model::TrainingJob::SetLabelingJobArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the labeling job.

Definition at line 206 of file TrainingJob.h.

◆ SetLabelingJobArn() [3/3]

void Aws::SageMaker::Model::TrainingJob::SetLabelingJobArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the labeling job.

Definition at line 216 of file TrainingJob.h.

◆ SetLastModifiedTime() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetLastModifiedTime ( Aws::Utils::DateTime &&  value)
inline

A timestamp that indicates when the status of the training job was last modified.

Definition at line 1161 of file TrainingJob.h.

◆ SetLastModifiedTime() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetLastModifiedTime ( const Aws::Utils::DateTime value)
inline

A timestamp that indicates when the status of the training job was last modified.

Definition at line 1155 of file TrainingJob.h.

◆ SetModelArtifacts() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetModelArtifacts ( const ModelArtifacts value)
inline

Information about the Amazon S3 location that is configured for storing model artifacts.

Definition at line 291 of file TrainingJob.h.

◆ SetModelArtifacts() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetModelArtifacts ( ModelArtifacts &&  value)
inline

Information about the Amazon S3 location that is configured for storing model artifacts.

Definition at line 297 of file TrainingJob.h.

◆ SetOutputDataConfig() [1/2]

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

The S3 path where model artifacts that you configured when creating the job are stored. Amazon SageMaker creates subfolders for model artifacts.

Definition at line 824 of file TrainingJob.h.

◆ SetOutputDataConfig() [2/2]

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

The S3 path where model artifacts that you configured when creating the job are stored. Amazon SageMaker creates subfolders for model artifacts.

Definition at line 830 of file TrainingJob.h.

◆ SetResourceConfig() [1/2]

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

Resources, including ML compute instances and ML storage volumes, that are configured for model training.

Definition at line 861 of file TrainingJob.h.

◆ SetResourceConfig() [2/2]

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

Resources, including ML compute instances and ML storage volumes, that are configured for model training.

Definition at line 867 of file TrainingJob.h.

◆ SetRetryStrategy() [1/2]

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

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

Definition at line 1663 of file TrainingJob.h.

◆ SetRetryStrategy() [2/2]

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

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

Definition at line 1669 of file TrainingJob.h.

◆ SetRoleArn() [1/3]

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

The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.

Definition at line 732 of file TrainingJob.h.

◆ SetRoleArn() [2/3]

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

The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.

Definition at line 726 of file TrainingJob.h.

◆ SetRoleArn() [3/3]

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

The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.

Definition at line 738 of file TrainingJob.h.

◆ SetSecondaryStatus() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetSecondaryStatus ( const SecondaryStatus value)
inline

Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.

Amazon SageMaker provides primary statuses and secondary statuses that apply to each of them:

InProgress
  • Starting - Starting the training job.

  • Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.

  • Training - Training is in progress.

  • Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.

Completed
  • Completed - The training job has completed.

Failed
  • Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.

Stopped
  • MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.

  • Stopped - The training job has stopped.

Stopping
  • Stopping - Stopping the training job.

Valid values for SecondaryStatus are subject to change.

We no longer support the following secondary statuses:

  • LaunchingMLInstances

  • PreparingTrainingStack

  • DownloadingTrainingImage

Definition at line 476 of file TrainingJob.h.

◆ SetSecondaryStatus() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetSecondaryStatus ( SecondaryStatus &&  value)
inline

Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.

Amazon SageMaker provides primary statuses and secondary statuses that apply to each of them:

InProgress
  • Starting - Starting the training job.

  • Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.

  • Training - Training is in progress.

  • Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.

Completed
  • Completed - The training job has completed.

Failed
  • Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.

Stopped
  • MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.

  • Stopped - The training job has stopped.

Stopping
  • Stopping - Stopping the training job.

Valid values for SecondaryStatus are subject to change.

We no longer support the following secondary statuses:

  • LaunchingMLInstances

  • PreparingTrainingStack

  • DownloadingTrainingImage

Definition at line 505 of file TrainingJob.h.

◆ SetSecondaryStatusTransitions() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetSecondaryStatusTransitions ( Aws::Vector< SecondaryStatusTransition > &&  value)
inline

A history of all of the secondary statuses that the training job has transitioned through.

Definition at line 1198 of file TrainingJob.h.

◆ SetSecondaryStatusTransitions() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetSecondaryStatusTransitions ( const Aws::Vector< SecondaryStatusTransition > &  value)
inline

A history of all of the secondary statuses that the training job has transitioned through.

Definition at line 1192 of file TrainingJob.h.

◆ SetStoppingCondition() [1/2]

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

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

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.

Definition at line 962 of file TrainingJob.h.

◆ SetStoppingCondition() [2/2]

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

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

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.

Definition at line 973 of file TrainingJob.h.

◆ SetTags() [1/2]

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

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

Definition at line 1718 of file TrainingJob.h.

◆ SetTags() [2/2]

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

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

Definition at line 1709 of file TrainingJob.h.

◆ SetTensorBoardOutputConfig() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetTensorBoardOutputConfig ( const TensorBoardOutputConfig value)
inline

Definition at line 1520 of file TrainingJob.h.

◆ SetTensorBoardOutputConfig() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetTensorBoardOutputConfig ( TensorBoardOutputConfig &&  value)
inline

Definition at line 1523 of file TrainingJob.h.

◆ SetTrainingEndTime() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetTrainingEndTime ( Aws::Utils::DateTime &&  value)
inline

Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when Amazon SageMaker detects a job failure.

Definition at line 1118 of file TrainingJob.h.

◆ SetTrainingEndTime() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetTrainingEndTime ( const Aws::Utils::DateTime value)
inline

Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when Amazon SageMaker detects a job failure.

Definition at line 1109 of file TrainingJob.h.

◆ SetTrainingJobArn() [1/3]

void Aws::SageMaker::Model::TrainingJob::SetTrainingJobArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the training job.

Definition at line 121 of file TrainingJob.h.

◆ SetTrainingJobArn() [2/3]

void Aws::SageMaker::Model::TrainingJob::SetTrainingJobArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the training job.

Definition at line 116 of file TrainingJob.h.

◆ SetTrainingJobArn() [3/3]

void Aws::SageMaker::Model::TrainingJob::SetTrainingJobArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the training job.

Definition at line 126 of file TrainingJob.h.

◆ SetTrainingJobName() [1/3]

void Aws::SageMaker::Model::TrainingJob::SetTrainingJobName ( Aws::String &&  value)
inline

The name of the training job.

Definition at line 80 of file TrainingJob.h.

◆ SetTrainingJobName() [2/3]

void Aws::SageMaker::Model::TrainingJob::SetTrainingJobName ( const Aws::String value)
inline

The name of the training job.

Definition at line 75 of file TrainingJob.h.

◆ SetTrainingJobName() [3/3]

void Aws::SageMaker::Model::TrainingJob::SetTrainingJobName ( const char *  value)
inline

The name of the training job.

Definition at line 85 of file TrainingJob.h.

◆ SetTrainingJobStatus() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetTrainingJobStatus ( const TrainingJobStatus value)
inline

The status of the training job.

Training job statuses are:

  • InProgress - The training is in progress.

  • Completed - The training job has completed.

  • Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.

  • Stopping - The training job is stopping.

  • Stopped - The training job has stopped.

For more detailed information, see SecondaryStatus.

Definition at line 349 of file TrainingJob.h.

◆ SetTrainingJobStatus() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetTrainingJobStatus ( TrainingJobStatus &&  value)
inline

The status of the training job.

Training job statuses are:

  • InProgress - The training is in progress.

  • Completed - The training job has completed.

  • Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.

  • Stopping - The training job is stopping.

  • Stopped - The training job has stopped.

For more detailed information, see SecondaryStatus.

Definition at line 362 of file TrainingJob.h.

◆ SetTrainingStartTime() [1/2]

void Aws::SageMaker::Model::TrainingJob::SetTrainingStartTime ( Aws::Utils::DateTime &&  value)
inline

Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.

Definition at line 1063 of file TrainingJob.h.

◆ SetTrainingStartTime() [2/2]

void Aws::SageMaker::Model::TrainingJob::SetTrainingStartTime ( const Aws::Utils::DateTime value)
inline

Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.

Definition at line 1054 of file TrainingJob.h.

◆ SetTrainingTimeInSeconds()

void Aws::SageMaker::Model::TrainingJob::SetTrainingTimeInSeconds ( int  value)
inline

The training time in seconds.

Definition at line 1405 of file TrainingJob.h.

◆ SetTuningJobArn() [1/3]

void Aws::SageMaker::Model::TrainingJob::SetTuningJobArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.

Definition at line 166 of file TrainingJob.h.

◆ SetTuningJobArn() [2/3]

void Aws::SageMaker::Model::TrainingJob::SetTuningJobArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.

Definition at line 160 of file TrainingJob.h.

◆ SetTuningJobArn() [3/3]

void Aws::SageMaker::Model::TrainingJob::SetTuningJobArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.

Definition at line 172 of file TrainingJob.h.

◆ SetVpcConfig() [1/2]

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

A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Definition at line 904 of file TrainingJob.h.

◆ SetVpcConfig() [2/2]

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

A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Definition at line 912 of file TrainingJob.h.

◆ StoppingConditionHasBeenSet()

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

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

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.

Definition at line 951 of file TrainingJob.h.

◆ TagsHasBeenSet()

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

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

Definition at line 1700 of file TrainingJob.h.

◆ TensorBoardOutputConfigHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::TensorBoardOutputConfigHasBeenSet ( ) const
inline

Definition at line 1517 of file TrainingJob.h.

◆ TrainingEndTimeHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::TrainingEndTimeHasBeenSet ( ) const
inline

Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when Amazon SageMaker detects a job failure.

Definition at line 1100 of file TrainingJob.h.

◆ TrainingJobArnHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::TrainingJobArnHasBeenSet ( ) const
inline

The Amazon Resource Name (ARN) of the training job.

Definition at line 111 of file TrainingJob.h.

◆ TrainingJobNameHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::TrainingJobNameHasBeenSet ( ) const
inline

The name of the training job.

Definition at line 70 of file TrainingJob.h.

◆ TrainingJobStatusHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::TrainingJobStatusHasBeenSet ( ) const
inline

The status of the training job.

Training job statuses are:

  • InProgress - The training is in progress.

  • Completed - The training job has completed.

  • Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.

  • Stopping - The training job is stopping.

  • Stopped - The training job has stopped.

For more detailed information, see SecondaryStatus.

Definition at line 336 of file TrainingJob.h.

◆ TrainingStartTimeHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::TrainingStartTimeHasBeenSet ( ) const
inline

Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.

Definition at line 1045 of file TrainingJob.h.

◆ TrainingTimeInSecondsHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::TrainingTimeInSecondsHasBeenSet ( ) const
inline

The training time in seconds.

Definition at line 1400 of file TrainingJob.h.

◆ TuningJobArnHasBeenSet()

bool Aws::SageMaker::Model::TrainingJob::TuningJobArnHasBeenSet ( ) const
inline

The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.

Definition at line 154 of file TrainingJob.h.

◆ VpcConfigHasBeenSet()

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

A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Definition at line 896 of file TrainingJob.h.

◆ WithAlgorithmSpecification() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithAlgorithmSpecification ( AlgorithmSpecification &&  value)
inline

Information about the algorithm used for training, and algorithm metadata.

Definition at line 707 of file TrainingJob.h.

◆ WithAlgorithmSpecification() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithAlgorithmSpecification ( const AlgorithmSpecification value)
inline

Information about the algorithm used for training, and algorithm metadata.

Definition at line 701 of file TrainingJob.h.

◆ WithAutoMLJobArn() [1/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithAutoMLJobArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the job.

Definition at line 267 of file TrainingJob.h.

◆ WithAutoMLJobArn() [2/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithAutoMLJobArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the job.

Definition at line 262 of file TrainingJob.h.

◆ WithAutoMLJobArn() [3/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithAutoMLJobArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the job.

Definition at line 272 of file TrainingJob.h.

◆ WithBillableTimeInSeconds()

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithBillableTimeInSeconds ( int  value)
inline

The billable time in seconds.

Definition at line 1431 of file TrainingJob.h.

◆ WithCheckpointConfig() [1/2]

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

Definition at line 1389 of file TrainingJob.h.

◆ WithCheckpointConfig() [2/2]

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

Definition at line 1386 of file TrainingJob.h.

◆ WithCreationTime() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithCreationTime ( Aws::Utils::DateTime &&  value)
inline

A timestamp that indicates when the training job was created.

Definition at line 1026 of file TrainingJob.h.

◆ WithCreationTime() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithCreationTime ( const Aws::Utils::DateTime value)
inline

A timestamp that indicates when the training job was created.

Definition at line 1021 of file TrainingJob.h.

◆ WithDebugHookConfig() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithDebugHookConfig ( const DebugHookConfig value)
inline

Definition at line 1447 of file TrainingJob.h.

◆ WithDebugHookConfig() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithDebugHookConfig ( DebugHookConfig &&  value)
inline

Definition at line 1450 of file TrainingJob.h.

◆ WithDebugRuleConfigurations() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithDebugRuleConfigurations ( Aws::Vector< DebugRuleConfiguration > &&  value)
inline

Information about the debug rule configuration.

Definition at line 1500 of file TrainingJob.h.

◆ WithDebugRuleConfigurations() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithDebugRuleConfigurations ( const Aws::Vector< DebugRuleConfiguration > &  value)
inline

Information about the debug rule configuration.

Definition at line 1495 of file TrainingJob.h.

◆ WithDebugRuleEvaluationStatuses() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithDebugRuleEvaluationStatuses ( Aws::Vector< DebugRuleEvaluationStatus > &&  value)
inline

Information about the evaluation status of the rules for the training job.

Definition at line 1566 of file TrainingJob.h.

◆ WithDebugRuleEvaluationStatuses() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithDebugRuleEvaluationStatuses ( const Aws::Vector< DebugRuleEvaluationStatus > &  value)
inline

Information about the evaluation status of the rules for the training job.

Definition at line 1560 of file TrainingJob.h.

◆ WithEnableInterContainerTrafficEncryption()

TrainingJob& Aws::SageMaker::Model::TrainingJob::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 1337 of file TrainingJob.h.

◆ WithEnableManagedSpotTraining()

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

When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.

Definition at line 1370 of file TrainingJob.h.

◆ WithEnableNetworkIsolation()

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

If the TrainingJob was created with network isolation, the value is set to true. If network isolation is enabled, nodes can't communicate beyond the VPC they run in.

Definition at line 1300 of file TrainingJob.h.

◆ WithEnvironment() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithEnvironment ( Aws::Map< Aws::String, Aws::String > &&  value)
inline

The environment variables to set in the Docker container.

Definition at line 1609 of file TrainingJob.h.

◆ WithEnvironment() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithEnvironment ( const Aws::Map< Aws::String, Aws::String > &  value)
inline

The environment variables to set in the Docker container.

Definition at line 1604 of file TrainingJob.h.

◆ WithExperimentConfig() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithExperimentConfig ( const ExperimentConfig value)
inline

Definition at line 1466 of file TrainingJob.h.

◆ WithExperimentConfig() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithExperimentConfig ( ExperimentConfig &&  value)
inline

Definition at line 1469 of file TrainingJob.h.

◆ WithFailureReason() [1/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithFailureReason ( Aws::String &&  value)
inline

If the training job failed, the reason it failed.

Definition at line 599 of file TrainingJob.h.

◆ WithFailureReason() [2/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithFailureReason ( const Aws::String value)
inline

If the training job failed, the reason it failed.

Definition at line 594 of file TrainingJob.h.

◆ WithFailureReason() [3/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithFailureReason ( const char *  value)
inline

If the training job failed, the reason it failed.

Definition at line 604 of file TrainingJob.h.

◆ WithFinalMetricDataList() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithFinalMetricDataList ( Aws::Vector< MetricData > &&  value)
inline

A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.

Definition at line 1259 of file TrainingJob.h.

◆ WithFinalMetricDataList() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithFinalMetricDataList ( const Aws::Vector< MetricData > &  value)
inline

A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.

Definition at line 1253 of file TrainingJob.h.

◆ WithHyperParameters() [1/2]

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

Algorithm-specific parameters.

Definition at line 635 of file TrainingJob.h.

◆ WithHyperParameters() [2/2]

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

Algorithm-specific parameters.

Definition at line 630 of file TrainingJob.h.

◆ WithInputDataConfig() [1/2]

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

An array of Channel objects that describes each data input channel.

Definition at line 793 of file TrainingJob.h.

◆ WithInputDataConfig() [2/2]

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

An array of Channel objects that describes each data input channel.

Definition at line 787 of file TrainingJob.h.

◆ WithLabelingJobArn() [1/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithLabelingJobArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the labeling job.

Definition at line 226 of file TrainingJob.h.

◆ WithLabelingJobArn() [2/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithLabelingJobArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the labeling job.

Definition at line 221 of file TrainingJob.h.

◆ WithLabelingJobArn() [3/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithLabelingJobArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the labeling job.

Definition at line 231 of file TrainingJob.h.

◆ WithLastModifiedTime() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithLastModifiedTime ( Aws::Utils::DateTime &&  value)
inline

A timestamp that indicates when the status of the training job was last modified.

Definition at line 1173 of file TrainingJob.h.

◆ WithLastModifiedTime() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithLastModifiedTime ( const Aws::Utils::DateTime value)
inline

A timestamp that indicates when the status of the training job was last modified.

Definition at line 1167 of file TrainingJob.h.

◆ WithModelArtifacts() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithModelArtifacts ( const ModelArtifacts value)
inline

Information about the Amazon S3 location that is configured for storing model artifacts.

Definition at line 303 of file TrainingJob.h.

◆ WithModelArtifacts() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithModelArtifacts ( ModelArtifacts &&  value)
inline

Information about the Amazon S3 location that is configured for storing model artifacts.

Definition at line 309 of file TrainingJob.h.

◆ WithOutputDataConfig() [1/2]

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

The S3 path where model artifacts that you configured when creating the job are stored. Amazon SageMaker creates subfolders for model artifacts.

Definition at line 836 of file TrainingJob.h.

◆ WithOutputDataConfig() [2/2]

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

The S3 path where model artifacts that you configured when creating the job are stored. Amazon SageMaker creates subfolders for model artifacts.

Definition at line 842 of file TrainingJob.h.

◆ WithResourceConfig() [1/2]

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

Resources, including ML compute instances and ML storage volumes, that are configured for model training.

Definition at line 873 of file TrainingJob.h.

◆ WithResourceConfig() [2/2]

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

Resources, including ML compute instances and ML storage volumes, that are configured for model training.

Definition at line 879 of file TrainingJob.h.

◆ WithRetryStrategy() [1/2]

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

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

Definition at line 1675 of file TrainingJob.h.

◆ WithRetryStrategy() [2/2]

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

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

Definition at line 1681 of file TrainingJob.h.

◆ WithRoleArn() [1/3]

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

The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.

Definition at line 750 of file TrainingJob.h.

◆ WithRoleArn() [2/3]

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

The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.

Definition at line 744 of file TrainingJob.h.

◆ WithRoleArn() [3/3]

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

The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.

Definition at line 756 of file TrainingJob.h.

◆ WithSecondaryStatus() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithSecondaryStatus ( const SecondaryStatus value)
inline

Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.

Amazon SageMaker provides primary statuses and secondary statuses that apply to each of them:

InProgress
  • Starting - Starting the training job.

  • Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.

  • Training - Training is in progress.

  • Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.

Completed
  • Completed - The training job has completed.

Failed
  • Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.

Stopped
  • MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.

  • Stopped - The training job has stopped.

Stopping
  • Stopping - Stopping the training job.

Valid values for SecondaryStatus are subject to change.

We no longer support the following secondary statuses:

  • LaunchingMLInstances

  • PreparingTrainingStack

  • DownloadingTrainingImage

Definition at line 534 of file TrainingJob.h.

◆ WithSecondaryStatus() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithSecondaryStatus ( SecondaryStatus &&  value)
inline

Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.

Amazon SageMaker provides primary statuses and secondary statuses that apply to each of them:

InProgress
  • Starting - Starting the training job.

  • Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.

  • Training - Training is in progress.

  • Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.

Completed
  • Completed - The training job has completed.

Failed
  • Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.

Stopped
  • MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.

  • Stopped - The training job has stopped.

Stopping
  • Stopping - Stopping the training job.

Valid values for SecondaryStatus are subject to change.

We no longer support the following secondary statuses:

  • LaunchingMLInstances

  • PreparingTrainingStack

  • DownloadingTrainingImage

Definition at line 563 of file TrainingJob.h.

◆ WithSecondaryStatusTransitions() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithSecondaryStatusTransitions ( Aws::Vector< SecondaryStatusTransition > &&  value)
inline

A history of all of the secondary statuses that the training job has transitioned through.

Definition at line 1210 of file TrainingJob.h.

◆ WithSecondaryStatusTransitions() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithSecondaryStatusTransitions ( const Aws::Vector< SecondaryStatusTransition > &  value)
inline

A history of all of the secondary statuses that the training job has transitioned through.

Definition at line 1204 of file TrainingJob.h.

◆ WithStoppingCondition() [1/2]

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

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

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.

Definition at line 984 of file TrainingJob.h.

◆ WithStoppingCondition() [2/2]

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

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

To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.

Definition at line 995 of file TrainingJob.h.

◆ WithTags() [1/2]

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

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

Definition at line 1736 of file TrainingJob.h.

◆ WithTags() [2/2]

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

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

Definition at line 1727 of file TrainingJob.h.

◆ WithTensorBoardOutputConfig() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTensorBoardOutputConfig ( const TensorBoardOutputConfig value)
inline

Definition at line 1526 of file TrainingJob.h.

◆ WithTensorBoardOutputConfig() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTensorBoardOutputConfig ( TensorBoardOutputConfig &&  value)
inline

Definition at line 1529 of file TrainingJob.h.

◆ WithTrainingEndTime() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTrainingEndTime ( Aws::Utils::DateTime &&  value)
inline

Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when Amazon SageMaker detects a job failure.

Definition at line 1136 of file TrainingJob.h.

◆ WithTrainingEndTime() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTrainingEndTime ( const Aws::Utils::DateTime value)
inline

Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when Amazon SageMaker detects a job failure.

Definition at line 1127 of file TrainingJob.h.

◆ WithTrainingJobArn() [1/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTrainingJobArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the training job.

Definition at line 136 of file TrainingJob.h.

◆ WithTrainingJobArn() [2/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTrainingJobArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the training job.

Definition at line 131 of file TrainingJob.h.

◆ WithTrainingJobArn() [3/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTrainingJobArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the training job.

Definition at line 141 of file TrainingJob.h.

◆ WithTrainingJobName() [1/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTrainingJobName ( Aws::String &&  value)
inline

The name of the training job.

Definition at line 95 of file TrainingJob.h.

◆ WithTrainingJobName() [2/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTrainingJobName ( const Aws::String value)
inline

The name of the training job.

Definition at line 90 of file TrainingJob.h.

◆ WithTrainingJobName() [3/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTrainingJobName ( const char *  value)
inline

The name of the training job.

Definition at line 100 of file TrainingJob.h.

◆ WithTrainingJobStatus() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTrainingJobStatus ( const TrainingJobStatus value)
inline

The status of the training job.

Training job statuses are:

  • InProgress - The training is in progress.

  • Completed - The training job has completed.

  • Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.

  • Stopping - The training job is stopping.

  • Stopped - The training job has stopped.

For more detailed information, see SecondaryStatus.

Definition at line 375 of file TrainingJob.h.

◆ WithTrainingJobStatus() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTrainingJobStatus ( TrainingJobStatus &&  value)
inline

The status of the training job.

Training job statuses are:

  • InProgress - The training is in progress.

  • Completed - The training job has completed.

  • Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.

  • Stopping - The training job is stopping.

  • Stopped - The training job has stopped.

For more detailed information, see SecondaryStatus.

Definition at line 388 of file TrainingJob.h.

◆ WithTrainingStartTime() [1/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTrainingStartTime ( Aws::Utils::DateTime &&  value)
inline

Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.

Definition at line 1081 of file TrainingJob.h.

◆ WithTrainingStartTime() [2/2]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTrainingStartTime ( const Aws::Utils::DateTime value)
inline

Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.

Definition at line 1072 of file TrainingJob.h.

◆ WithTrainingTimeInSeconds()

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTrainingTimeInSeconds ( int  value)
inline

The training time in seconds.

Definition at line 1410 of file TrainingJob.h.

◆ WithTuningJobArn() [1/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTuningJobArn ( Aws::String &&  value)
inline

The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.

Definition at line 184 of file TrainingJob.h.

◆ WithTuningJobArn() [2/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTuningJobArn ( const Aws::String value)
inline

The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.

Definition at line 178 of file TrainingJob.h.

◆ WithTuningJobArn() [3/3]

TrainingJob& Aws::SageMaker::Model::TrainingJob::WithTuningJobArn ( const char *  value)
inline

The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.

Definition at line 190 of file TrainingJob.h.

◆ WithVpcConfig() [1/2]

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

A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Definition at line 920 of file TrainingJob.h.

◆ WithVpcConfig() [2/2]

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

A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.

Definition at line 928 of file TrainingJob.h.


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