# TrainingJob
<a name="API_TrainingJob"></a>

Contains information about a training job.

## Contents
<a name="API_TrainingJob_Contents"></a>

 ** AlgorithmSpecification **   <a name="sagemaker-Type-TrainingJob-AlgorithmSpecification"></a>
Information about the algorithm used for training, and algorithm metadata.  
Type: [AlgorithmSpecification](API_AlgorithmSpecification.md) object  
Required: No

 ** AutoMLJobArn **   <a name="sagemaker-Type-TrainingJob-AutoMLJobArn"></a>
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

 ** BillableTimeInSeconds **   <a name="sagemaker-Type-TrainingJob-BillableTimeInSeconds"></a>
The billable time in seconds.  
Type: Integer  
Valid Range: Minimum value of 1.  
Required: No

 ** CheckpointConfig **   <a name="sagemaker-Type-TrainingJob-CheckpointConfig"></a>
Contains information about the output location for managed spot training checkpoint data.   
Type: [CheckpointConfig](API_CheckpointConfig.md) object  
Required: No

 ** CreationTime **   <a name="sagemaker-Type-TrainingJob-CreationTime"></a>
A timestamp that indicates when the training job was created.  
Type: Timestamp  
Required: No

 ** DebugHookConfig **   <a name="sagemaker-Type-TrainingJob-DebugHookConfig"></a>
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](https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html).  
Type: [DebugHookConfig](API_DebugHookConfig.md) object  
Required: No

 ** DebugRuleConfigurations **   <a name="sagemaker-Type-TrainingJob-DebugRuleConfigurations"></a>
Information about the debug rule configuration.  
Type: Array of [DebugRuleConfiguration](API_DebugRuleConfiguration.md) objects  
Array Members: Minimum number of 0 items. Maximum number of 20 items.  
Required: No

 ** DebugRuleEvaluationStatuses **   <a name="sagemaker-Type-TrainingJob-DebugRuleEvaluationStatuses"></a>
Information about the evaluation status of the rules for the training job.  
Type: Array of [DebugRuleEvaluationStatus](API_DebugRuleEvaluationStatus.md) objects  
Array Members: Minimum number of 0 items. Maximum number of 20 items.  
Required: No

 ** EnableInterContainerTrafficEncryption **   <a name="sagemaker-Type-TrainingJob-EnableInterContainerTrafficEncryption"></a>
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

 ** EnableManagedSpotTraining **   <a name="sagemaker-Type-TrainingJob-EnableManagedSpotTraining"></a>
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](https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.html).  
Type: Boolean  
Required: No

 ** EnableNetworkIsolation **   <a name="sagemaker-Type-TrainingJob-EnableNetworkIsolation"></a>
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

 ** Environment **   <a name="sagemaker-Type-TrainingJob-Environment"></a>
The environment variables to set in the Docker container.  
Type: String to string map  
Map Entries: Minimum number of 0 items. Maximum number of 100 items.  
Key Length Constraints: Minimum length of 0. Maximum length of 512.  
Key Pattern: `[a-zA-Z_][a-zA-Z0-9_]*`   
Value Length Constraints: Minimum length of 0. Maximum length of 512.  
Value Pattern: `[\S\s]*`   
Required: No

 ** ExperimentConfig **   <a name="sagemaker-Type-TrainingJob-ExperimentConfig"></a>
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:  
+  [CreateProcessingJob](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html) 
+  [CreateTrainingJob](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html) 
+  [CreateTransformJob](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html) 
Type: [ExperimentConfig](API_ExperimentConfig.md) object  
Required: No

 ** FailureReason **   <a name="sagemaker-Type-TrainingJob-FailureReason"></a>
If the training job failed, the reason it failed.  
Type: String  
Length Constraints: Minimum length of 0. Maximum length of 1024.  
Required: No

 ** FinalMetricDataList **   <a name="sagemaker-Type-TrainingJob-FinalMetricDataList"></a>
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](API_MetricData.md) objects  
Array Members: Minimum number of 0 items. Maximum number of 40 items.  
Required: No

 ** HyperParameters **   <a name="sagemaker-Type-TrainingJob-HyperParameters"></a>
Algorithm-specific parameters.  
Type: String to string map  
Map Entries: Minimum number of 0 items. Maximum number of 100 items.  
Key Length Constraints: Minimum length of 0. Maximum length of 256.  
Key Pattern: `.*`   
Value Length Constraints: Minimum length of 0. Maximum length of 2500.  
Value Pattern: `.*`   
Required: No

 ** InputDataConfig **   <a name="sagemaker-Type-TrainingJob-InputDataConfig"></a>
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](API_Channel.md) objects  
Array Members: Minimum number of 1 item. Maximum number of 20 items.  
Required: No

 ** LabelingJobArn **   <a name="sagemaker-Type-TrainingJob-LabelingJobArn"></a>
The Amazon Resource Name (ARN) of the labeling job.  
Type: String  
Length Constraints: Minimum length of 0. Maximum length of 2048.  
Pattern: `arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:labeling-job/.*`   
Required: No

 ** LastModifiedTime **   <a name="sagemaker-Type-TrainingJob-LastModifiedTime"></a>
A timestamp that indicates when the status of the training job was last modified.  
Type: Timestamp  
Required: No

 ** ModelArtifacts **   <a name="sagemaker-Type-TrainingJob-ModelArtifacts"></a>
Information about the Amazon S3 location that is configured for storing model artifacts.  
Type: [ModelArtifacts](API_ModelArtifacts.md) object  
Required: No

 ** ModelPackageConfig **   <a name="sagemaker-Type-TrainingJob-ModelPackageConfig"></a>
 The model package configuration.   
Type: [ModelPackageConfig](API_ModelPackageConfig.md) object  
Required: No

 ** OutputDataConfig **   <a name="sagemaker-Type-TrainingJob-OutputDataConfig"></a>
The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.  
Type: [OutputDataConfig](API_OutputDataConfig.md) object  
Required: No

 ** OutputModelPackageArn **   <a name="sagemaker-Type-TrainingJob-OutputModelPackageArn"></a>
 The output model package Amazon Resource Name (ARN) that contains model weights or checkpoint.   
Type: String  
Length Constraints: Minimum length of 1. Maximum length of 2048.  
Pattern: `arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]{9,16}:[0-9]{12}:model-package/[\S]{1,2048}`   
Required: No

 ** ProfilerConfig **   <a name="sagemaker-Type-TrainingJob-ProfilerConfig"></a>
Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.  
Type: [ProfilerConfig](API_ProfilerConfig.md) object  
Required: No

 ** ResourceConfig **   <a name="sagemaker-Type-TrainingJob-ResourceConfig"></a>
Resources, including ML compute instances and ML storage volumes, that are configured for model training.  
Type: [ResourceConfig](API_ResourceConfig.md) object  
Required: No

 ** RetryStrategy **   <a name="sagemaker-Type-TrainingJob-RetryStrategy"></a>
The number of times to retry the job when the job fails due to an `InternalServerError`.  
Type: [RetryStrategy](API_RetryStrategy.md) object  
Required: No

 ** RoleArn **   <a name="sagemaker-Type-TrainingJob-RoleArn"></a>
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

 ** SecondaryStatus **   <a name="sagemaker-Type-TrainingJob-SecondaryStatus"></a>
 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](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_SecondaryStatusTransition.html).  
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` 
Type: String  
Valid Values: `Starting | LaunchingMLInstances | PreparingTrainingStack | Downloading | DownloadingTrainingImage | Training | Uploading | Stopping | Stopped | MaxRuntimeExceeded | Completed | Failed | Interrupted | MaxWaitTimeExceeded | Updating | Restarting | Pending`   
Required: No

 ** SecondaryStatusTransitions **   <a name="sagemaker-Type-TrainingJob-SecondaryStatusTransitions"></a>
A history of all of the secondary statuses that the training job has transitioned through.  
Type: Array of [SecondaryStatusTransition](API_SecondaryStatusTransition.md) objects  
Required: No

 ** StoppingCondition **   <a name="sagemaker-Type-TrainingJob-StoppingCondition"></a>
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](API_StoppingCondition.md) object  
Required: No

 ** Tags **   <a name="sagemaker-Type-TrainingJob-Tags"></a>
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](https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html).  
Type: Array of [Tag](API_Tag.md) objects  
Array Members: Minimum number of 0 items. Maximum number of 50 items.  
Required: No

 ** TensorBoardOutputConfig **   <a name="sagemaker-Type-TrainingJob-TensorBoardOutputConfig"></a>
Configuration of storage locations for the Amazon SageMaker Debugger TensorBoard output data.  
Type: [TensorBoardOutputConfig](API_TensorBoardOutputConfig.md) object  
Required: No

 ** TrainingEndTime **   <a name="sagemaker-Type-TrainingJob-TrainingEndTime"></a>
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

 ** TrainingJobArn **   <a name="sagemaker-Type-TrainingJob-TrainingJobArn"></a>
The Amazon Resource Name (ARN) of the training job.  
Type: String  
Length Constraints: Minimum length of 0. Maximum length of 256.  
Pattern: `arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:training-job/[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}`   
Required: No

 ** TrainingJobName **   <a name="sagemaker-Type-TrainingJob-TrainingJobName"></a>
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

 ** TrainingJobStatus **   <a name="sagemaker-Type-TrainingJob-TrainingJobStatus"></a>
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`.   
Type: String  
Valid Values: `InProgress | Completed | Failed | Stopping | Stopped | Deleting`   
Required: No

 ** TrainingStartTime **   <a name="sagemaker-Type-TrainingJob-TrainingStartTime"></a>
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

 ** TrainingTimeInSeconds **   <a name="sagemaker-Type-TrainingJob-TrainingTimeInSeconds"></a>
The training time in seconds.  
Type: Integer  
Valid Range: Minimum value of 1.  
Required: No

 ** TuningJobArn **   <a name="sagemaker-Type-TrainingJob-TuningJobArn"></a>
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: Minimum length of 0. Maximum length of 256.  
Pattern: `arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:hyper-parameter-tuning-job/.*`   
Required: No

 ** VpcConfig **   <a name="sagemaker-Type-TrainingJob-VpcConfig"></a>
A [VpcConfig](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VpcConfig.html) 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](https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html).  
Type: [VpcConfig](API_VpcConfig.md) object  
Required: No

## See Also
<a name="API_TrainingJob_SeeAlso"></a>

For more information about using this API in one of the language-specific AWS SDKs, see the following:
+  [AWS SDK for C\$1\$1](https://docs.aws.amazon.com/goto/SdkForCpp/sagemaker-2017-07-24/TrainingJob) 
+  [AWS SDK for Java V2](https://docs.aws.amazon.com/goto/SdkForJavaV2/sagemaker-2017-07-24/TrainingJob) 
+  [AWS SDK for Ruby V3](https://docs.aws.amazon.com/goto/SdkForRubyV3/sagemaker-2017-07-24/TrainingJob)