Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.

debugRuleConfigurations

var debugRuleConfigurations: List<DebugRuleConfiguration>?

Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.

debugRuleEvaluationStatuses

var debugRuleEvaluationStatuses: List<DebugRuleEvaluationStatus>?

Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.

enableInterContainerTrafficEncryption

var enableInterContainerTrafficEncryption: Boolean?

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 algorithms in distributed training.

enableManagedSpotTraining

var enableManagedSpotTraining: Boolean?

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

enableNetworkIsolation

var enableNetworkIsolation: Boolean?

If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose True. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.

environment

var environment: Map<String, String>?

The environment variables to set in the Docker container.

experimentConfig

var experimentConfig: ExperimentConfig?

Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:

failureReason

var failureReason: String?

If the training job failed, the reason it failed.

finalMetricDataList

var finalMetricDataList: List<MetricData>?

A collection of MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.

hyperParameters

var hyperParameters: Map<String, String>?

Algorithm-specific parameters.

infraCheckConfig

var infraCheckConfig: InfraCheckConfig?

Contains information about the infrastructure health check configuration for the training job.

inputDataConfig

var inputDataConfig: List<Channel>?

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

labelingJobArn

var labelingJobArn: String?

The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.

lastModifiedTime

var lastModifiedTime: Instant?

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

modelArtifacts

var modelArtifacts: ModelArtifacts?

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

outputDataConfig

var outputDataConfig: OutputDataConfig?

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

profilerConfig

var profilerConfig: ProfilerConfig?

Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.

profilerRuleConfigurations

var profilerRuleConfigurations: List<ProfilerRuleConfiguration>?

Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.

profilerRuleEvaluationStatuses

var profilerRuleEvaluationStatuses: List<ProfilerRuleEvaluationStatus>?

Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.

profilingStatus

var profilingStatus: ProfilingStatus?

Profiling status of a training job.

remoteDebugConfig

var remoteDebugConfig: RemoteDebugConfig?

Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.

resourceConfig

var resourceConfig: ResourceConfig?

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

retryStrategy

var retryStrategy: RetryStrategy?

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

roleArn

var roleArn: String?

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

secondaryStatus

var secondaryStatus: SecondaryStatus?

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

secondaryStatusTransitions

var secondaryStatusTransitions: List<SecondaryStatusTransition>?

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

stoppingCondition

var stoppingCondition: StoppingCondition?

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, SageMaker ends the training job. Use this API to cap model training costs.

tensorBoardOutputConfig

var tensorBoardOutputConfig: TensorBoardOutputConfig?

Configuration of storage locations for the Amazon SageMaker Debugger TensorBoard output data.

trainingEndTime

var trainingEndTime: Instant?

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 SageMaker detects a job failure.

trainingJobArn

var trainingJobArn: String?

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

trainingJobName

var trainingJobName: String?

Name of the model training job.

trainingJobStatus

var trainingJobStatus: TrainingJobStatus?

The status of the training job.

trainingStartTime

var trainingStartTime: Instant?

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.

trainingTimeInSeconds

var trainingTimeInSeconds: Int?

The training time in seconds.

tuningJobArn

var tuningJobArn: String?

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

vpcConfig

var vpcConfig: VpcConfig?

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.

warmPoolStatus

var warmPoolStatus: WarmPoolStatus?

The status of the warm pool associated with the training job.