sagemaker/aws.sdk.kotlin.services.sagemaker.model/DescribeHyperParameterTuningJobResponse/Builder

Builder

Properties

var autotune: Autotune?

A flag to indicate if autotune is enabled for the hyperparameter tuning job.

bestTrainingJob

var bestTrainingJob: HyperParameterTrainingJobSummary?

A TrainingJobSummary object that describes the training job that completed with the best current HyperParameterTuningJobObjective.

consumedResources

var consumedResources: HyperParameterTuningJobConsumedResources?

The total resources consumed by your hyperparameter tuning job.

var creationTime: Instant?

The date and time that the tuning job started.

var failureReason: String?

If the tuning job failed, the reason it failed.

hyperParameterTuningEndTime

var hyperParameterTuningEndTime: Instant?

The date and time that the tuning job ended.

hyperParameterTuningJobArn

var hyperParameterTuningJobArn: String?

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

hyperParameterTuningJobConfig

var hyperParameterTuningJobConfig: HyperParameterTuningJobConfig?

The HyperParameterTuningJobConfig object that specifies the configuration of the tuning job.

hyperParameterTuningJobName

var hyperParameterTuningJobName: String?

The name of the hyperparameter tuning job.

hyperParameterTuningJobStatus

var hyperParameterTuningJobStatus: HyperParameterTuningJobStatus?

The status of the tuning job.

lastModifiedTime

var lastModifiedTime: Instant?

The date and time that the status of the tuning job was modified.

objectiveStatusCounters

var objectiveStatusCounters: ObjectiveStatusCounters?

The ObjectiveStatusCounters object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.

overallBestTrainingJob

var overallBestTrainingJob: HyperParameterTrainingJobSummary?

If the hyperparameter tuning job is an warm start tuning job with a WarmStartType of IDENTICAL_DATA_AND_ALGORITHM, this is the TrainingJobSummary for the training job with the best objective metric value of all training jobs launched by this tuning job and all parent jobs specified for the warm start tuning job.

trainingJobDefinition

var trainingJobDefinition: HyperParameterTrainingJobDefinition?

The HyperParameterTrainingJobDefinition object that specifies the definition of the training jobs that this tuning job launches.

trainingJobDefinitions

var trainingJobDefinitions: List<HyperParameterTrainingJobDefinition>?

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

trainingJobStatusCounters

var trainingJobStatusCounters: TrainingJobStatusCounters?

The TrainingJobStatusCounters object that specifies the number of training jobs, categorized by status, that this tuning job launched.

tuningJobCompletionDetails

var tuningJobCompletionDetails: HyperParameterTuningJobCompletionDetails?

Tuning job completion information returned as the response from a hyperparameter tuning job. This information tells if your tuning job has or has not converged. It also includes the number of training jobs that have not improved model performance as evaluated against the objective function.

warmStartConfig

var warmStartConfig: HyperParameterTuningJobWarmStartConfig?

The configuration for starting the hyperparameter parameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.

Functions

fun autotune(block: Autotune.Builder.() -> Unit)

construct an aws.sdk.kotlin.services.sagemaker.model.Autotune inside the given block

bestTrainingJob

fun bestTrainingJob(block: HyperParameterTrainingJobSummary.Builder.() -> Unit)

construct an aws.sdk.kotlin.services.sagemaker.model.HyperParameterTrainingJobSummary inside the given block

consumedResources

fun consumedResources(block: HyperParameterTuningJobConsumedResources.Builder.() -> Unit)

construct an aws.sdk.kotlin.services.sagemaker.model.HyperParameterTuningJobConsumedResources inside the given block

hyperParameterTuningJobConfig

fun hyperParameterTuningJobConfig(block: HyperParameterTuningJobConfig.Builder.() -> Unit)

construct an aws.sdk.kotlin.services.sagemaker.model.HyperParameterTuningJobConfig inside the given block

objectiveStatusCounters

fun objectiveStatusCounters(block: ObjectiveStatusCounters.Builder.() -> Unit)

construct an aws.sdk.kotlin.services.sagemaker.model.ObjectiveStatusCounters inside the given block

overallBestTrainingJob

fun overallBestTrainingJob(block: HyperParameterTrainingJobSummary.Builder.() -> Unit)

construct an aws.sdk.kotlin.services.sagemaker.model.HyperParameterTrainingJobSummary inside the given block

trainingJobDefinition

fun trainingJobDefinition(block: HyperParameterTrainingJobDefinition.Builder.() -> Unit)

construct an aws.sdk.kotlin.services.sagemaker.model.HyperParameterTrainingJobDefinition inside the given block

trainingJobStatusCounters

fun trainingJobStatusCounters(block: TrainingJobStatusCounters.Builder.() -> Unit)

construct an aws.sdk.kotlin.services.sagemaker.model.TrainingJobStatusCounters inside the given block

tuningJobCompletionDetails

fun tuningJobCompletionDetails(block: HyperParameterTuningJobCompletionDetails.Builder.() -> Unit)

construct an aws.sdk.kotlin.services.sagemaker.model.HyperParameterTuningJobCompletionDetails inside the given block

warmStartConfig

fun warmStartConfig(block: HyperParameterTuningJobWarmStartConfig.Builder.() -> Unit)

construct an aws.sdk.kotlin.services.sagemaker.model.HyperParameterTuningJobWarmStartConfig inside the given block