SecondaryStatusTransition ¶

class SecondaryStatusTransition(TypedDict, closed=True):
    status: NotRequired["capo_sagemaker.types.secondary_status.SecondaryStatus"]
    """<p>Contains a secondary status information from a training job.</p> <p>Status might be one of the following secondary statuses:</p> <dl> <dt>InProgress</dt> <dd> <ul> <li> <p> <code>Starting</code> - Starting the training job.</p> </li> <li> <p> <code>Downloading</code> - An optional stage for algorithms that support <code>File</code> training input mode. It indicates that data is being downloaded to the ML storage volumes.</p> </li> <li> <p> <code>Training</code> - Training is in progress.</p> </li> <li> <p> <code>Uploading</code> - Training is complete and the model artifacts are being uploaded to the S3 location.</p> </li> </ul> </dd> <dt>Completed</dt> <dd> <ul> <li> <p> <code>Completed</code> - The training job has completed.</p> </li> </ul> </dd> <dt>Failed</dt> <dd> <ul> <li> <p> <code>Failed</code> - The training job has failed. The reason for the failure is returned in the <code>FailureReason</code> field of <code>DescribeTrainingJobResponse</code>.</p> </li> </ul> </dd> <dt>Stopped</dt> <dd> <ul> <li> <p> <code>MaxRuntimeExceeded</code> - The job stopped because it exceeded the maximum allowed runtime.</p> </li> <li> <p> <code>Stopped</code> - The training job has stopped.</p> </li> </ul> </dd> <dt>Stopping</dt> <dd> <ul> <li> <p> <code>Stopping</code> - Stopping the training job.</p> </li> </ul> </dd> </dl> <p>We no longer support the following secondary statuses:</p> <ul> <li> <p> <code>LaunchingMLInstances</code> </p> </li> <li> <p> <code>PreparingTrainingStack</code> </p> </li> <li> <p> <code>DownloadingTrainingImage</code> </p> </li> </ul>"""
    start_time: NotRequired["capo_sagemaker.types.timestamp.Timestamp"]
    """<p>A timestamp that shows when the training job transitioned to the current secondary status state.</p>"""
    end_time: NotRequired["capo_sagemaker.types.timestamp.Timestamp"]
    """<p>A timestamp that shows when the training job transitioned out of this secondary status state into another secondary status state or when the training job has ended.</p>"""
    status_message: NotRequired["capo_sagemaker.types.status_message.StatusMessage"]
    """<p>A detailed description of the progress within a secondary status. </p> <p>SageMaker provides secondary statuses and status messages that apply to each of them:</p> <dl> <dt>Starting</dt> <dd> <ul> <li> <p>Starting the training job.</p> </li> <li> <p>Launching requested ML instances.</p> </li> <li> <p>Insufficient capacity error from EC2 while launching instances, retrying!</p> </li> <li> <p>Launched instance was unhealthy, replacing it!</p> </li> <li> <p>Preparing the instances for training.</p> </li> </ul> </dd> <dt>Training</dt> <dd> <ul> <li> <p>Training image download completed. Training in progress.</p> </li> </ul> </dd> </dl> <important> <p>Status messages are subject to change. Therefore, we recommend not including them in code that programmatically initiates actions. For examples, don't use status messages in if statements.</p> </important> <p>To have an overview of your training job's progress, view <code>TrainingJobStatus</code> and <code>SecondaryStatus</code> in <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeTrainingJob.html">DescribeTrainingJob</a>, and <code>StatusMessage</code> together. For example, at the start of a training job, you might see the following:</p> <ul> <li> <p> <code>TrainingJobStatus</code> - InProgress</p> </li> <li> <p> <code>SecondaryStatus</code> - Training</p> </li> <li> <p> <code>StatusMessage</code> - Downloading the training image</p> </li> </ul>"""