TrainingJob

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

Type: AlgorithmSpecification object

Required: No

The Amazon Resource Name (ARN) of the job.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 256.

Pattern: arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:automl-job/.*

Required: No

The billable time in seconds.

Type: Integer

Valid Range: Minimum value of 1.

Required: No

Contains information about the output location for managed spot training checkpoint data.

Type: CheckpointConfig object

Required: No

A timestamp that indicates when the training job was created.

Type: Timestamp

Required: No

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.

Type: DebugHookConfig object

Required: No

Information about the debug rule configuration.

Type: Array of DebugRuleConfiguration objects

Array Members: Minimum number of 0 items. Maximum number of 20 items.

Required: No

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

Type: Array of DebugRuleEvaluationStatus objects

Array Members: Minimum number of 0 items. Maximum number of 20 items.

Required: No

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.

Type: Boolean

Required: No

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.

Type: Boolean

Required: No

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.

Type: Boolean

Required: No

The environment variables to set in the Docker container.

Type: String to string map

Map Entries: Maximum number of 100 items.

Key Length Constraints: Maximum length of 512.

Key Pattern: [a-zA-Z_][a-zA-Z0-9_]*

Value Length Constraints: Maximum length of 512.

Value Pattern: [\S\s]*

Required: No

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

Type: ExperimentConfig object

Required: No

If the training job failed, the reason it failed.

Type: String

Length Constraints: Maximum length of 1024.

Required: No

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.

Type: Array of MetricData objects

Array Members: Minimum number of 0 items. Maximum number of 40 items.

Required: No

Algorithm-specific parameters.

Type: String to string map

Map Entries: Minimum number of 0 items. Maximum number of 100 items.

Key Length Constraints: Maximum length of 256.

Key Pattern: .*

Value Length Constraints: Maximum length of 2500.

Value Pattern: .*

Required: No

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

Your input must be in the same AWS region as your training job.

Type: Array of Channel objects

Array Members: Minimum number of 1 item. Maximum number of 20 items.

Required: No

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

Type: String

Length Constraints: Maximum length of 2048.

Pattern: arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:labeling-job/.*

Required: No

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

Type: Timestamp

Required: No

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

Type: ModelArtifacts object

Required: No

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

Type: OutputDataConfig object

Required: No

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

Type: ProfilerConfig object

Required: No

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

Type: ResourceConfig object

Required: No

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

Type: RetryStrategy object

Required: No

The AWS Identity and Access Management (IAM) role configured for the training job.

Type: String

Length Constraints: Minimum length of 20. Maximum length of 2048.

Pattern: ^arn:aws[a-z\-]*:iam::\d{12}:role/?[a-zA-Z_0-9+=,.@\-_/]+$

Required: No

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.

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

We no longer support the following secondary statuses:

Type: String

Valid Values: Starting | LaunchingMLInstances | PreparingTrainingStack | Downloading | DownloadingTrainingImage | Training | Uploading | Stopping | Stopped | MaxRuntimeExceeded | Completed | Failed | Interrupted | MaxWaitTimeExceeded | Updating | Restarting | Pending

Required: No

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

Type: Array of SecondaryStatusTransition objects

Required: No

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.

To stop a job, 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.

Type: StoppingCondition object

Required: No

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

Type: Array of Tag objects

Array Members: Minimum number of 0 items. Maximum number of 50 items.

Required: No

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

Type: TensorBoardOutputConfig object

Required: No

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.

Type: Timestamp

Required: No

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

Type: String

Length Constraints: Maximum length of 256.

Pattern: arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:training-job/.*

Required: No

The name of the training job.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 63.

Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}

Required: No

The status of the training job.

Training job statuses are:

For more detailed information, see SecondaryStatus.

Type: String

Valid Values: InProgress | Completed | Failed | Stopping | Stopped

Required: No

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.

Type: Timestamp

Required: No

The training time in seconds.

Type: Integer

Valid Range: Minimum value of 1.

Required: No

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

Type: String

Length Constraints: Maximum length of 256.

Pattern: arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:hyper-parameter-tuning-job/.*

Required: No

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.

Type: VpcConfig object

Required: No