/** * Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. * SPDX-License-Identifier: Apache-2.0. */ #pragma once #include #include #include #include #include namespace Aws { namespace Utils { namespace Json { class JsonValue; class JsonView; } // namespace Json } // namespace Utils namespace SageMaker { namespace Model { /** *

An array element of SecondaryStatusTransitions for DescribeTrainingJob. * It provides additional details about a status that the training job has * transitioned through. A training job can be in one of several states, for * example, starting, downloading, training, or uploading. Within each state, there * are a number of intermediate states. For example, within the starting state, * SageMaker could be starting the training job or launching the ML instances. * These transitional states are referred to as the job's secondary status.

*

See Also:

AWS * API Reference

*/ class SecondaryStatusTransition { public: AWS_SAGEMAKER_API SecondaryStatusTransition(); AWS_SAGEMAKER_API SecondaryStatusTransition(Aws::Utils::Json::JsonView jsonValue); AWS_SAGEMAKER_API SecondaryStatusTransition& operator=(Aws::Utils::Json::JsonView jsonValue); AWS_SAGEMAKER_API Aws::Utils::Json::JsonValue Jsonize() const; /** *

Contains a secondary status information from a training job.

Status * might be one of the following secondary statuses:

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.

*

We no longer support the following secondary statuses:

    *

  • LaunchingMLInstances

  • * PreparingTrainingStack

  • * DownloadingTrainingImage

*/ inline const SecondaryStatus& GetStatus() const{ return m_status; } /** *

Contains a secondary status information from a training job.

Status * might be one of the following secondary statuses:

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.

*

We no longer support the following secondary statuses:

    *

  • LaunchingMLInstances

  • * PreparingTrainingStack

  • * DownloadingTrainingImage

*/ inline bool StatusHasBeenSet() const { return m_statusHasBeenSet; } /** *

Contains a secondary status information from a training job.

Status * might be one of the following secondary statuses:

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.

*

We no longer support the following secondary statuses:

    *

  • LaunchingMLInstances

  • * PreparingTrainingStack

  • * DownloadingTrainingImage

*/ inline void SetStatus(const SecondaryStatus& value) { m_statusHasBeenSet = true; m_status = value; } /** *

Contains a secondary status information from a training job.

Status * might be one of the following secondary statuses:

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.

*

We no longer support the following secondary statuses:

    *

  • LaunchingMLInstances

  • * PreparingTrainingStack

  • * DownloadingTrainingImage

*/ inline void SetStatus(SecondaryStatus&& value) { m_statusHasBeenSet = true; m_status = std::move(value); } /** *

Contains a secondary status information from a training job.

Status * might be one of the following secondary statuses:

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.

*

We no longer support the following secondary statuses:

    *

  • LaunchingMLInstances

  • * PreparingTrainingStack

  • * DownloadingTrainingImage

*/ inline SecondaryStatusTransition& WithStatus(const SecondaryStatus& value) { SetStatus(value); return *this;} /** *

Contains a secondary status information from a training job.

Status * might be one of the following secondary statuses:

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.

*

We no longer support the following secondary statuses:

    *

  • LaunchingMLInstances

  • * PreparingTrainingStack

  • * DownloadingTrainingImage

*/ inline SecondaryStatusTransition& WithStatus(SecondaryStatus&& value) { SetStatus(std::move(value)); return *this;} /** *

A timestamp that shows when the training job transitioned to the current * secondary status state.

*/ inline const Aws::Utils::DateTime& GetStartTime() const{ return m_startTime; } /** *

A timestamp that shows when the training job transitioned to the current * secondary status state.

*/ inline bool StartTimeHasBeenSet() const { return m_startTimeHasBeenSet; } /** *

A timestamp that shows when the training job transitioned to the current * secondary status state.

*/ inline void SetStartTime(const Aws::Utils::DateTime& value) { m_startTimeHasBeenSet = true; m_startTime = value; } /** *

A timestamp that shows when the training job transitioned to the current * secondary status state.

*/ inline void SetStartTime(Aws::Utils::DateTime&& value) { m_startTimeHasBeenSet = true; m_startTime = std::move(value); } /** *

A timestamp that shows when the training job transitioned to the current * secondary status state.

*/ inline SecondaryStatusTransition& WithStartTime(const Aws::Utils::DateTime& value) { SetStartTime(value); return *this;} /** *

A timestamp that shows when the training job transitioned to the current * secondary status state.

*/ inline SecondaryStatusTransition& WithStartTime(Aws::Utils::DateTime&& value) { SetStartTime(std::move(value)); return *this;} /** *

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.

*/ inline const Aws::Utils::DateTime& GetEndTime() const{ return m_endTime; } /** *

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.

*/ inline bool EndTimeHasBeenSet() const { return m_endTimeHasBeenSet; } /** *

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.

*/ inline void SetEndTime(const Aws::Utils::DateTime& value) { m_endTimeHasBeenSet = true; m_endTime = value; } /** *

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.

*/ inline void SetEndTime(Aws::Utils::DateTime&& value) { m_endTimeHasBeenSet = true; m_endTime = std::move(value); } /** *

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.

*/ inline SecondaryStatusTransition& WithEndTime(const Aws::Utils::DateTime& value) { SetEndTime(value); return *this;} /** *

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.

*/ inline SecondaryStatusTransition& WithEndTime(Aws::Utils::DateTime&& value) { SetEndTime(std::move(value)); return *this;} /** *

A detailed description of the progress within a secondary status.

*

SageMaker provides secondary statuses and status messages that apply to each * of them:

Starting

  • Starting the training * job.

  • Launching requested ML instances.

  • *

    Insufficient capacity error from EC2 while launching instances, retrying!

    *

  • Launched instance was unhealthy, replacing it!

  • *

    Preparing the instances for training.

Training
*

  • Downloading the training image.

  • Training * image download completed. Training in progress.

*

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.

To * have an overview of your training job's progress, view * TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, * and StatusMessage together. For example, at the start of a training * job, you might see the following:

  • * TrainingJobStatus - InProgress

  • * SecondaryStatus - Training

  • * StatusMessage - Downloading the training image

*/ inline const Aws::String& GetStatusMessage() const{ return m_statusMessage; } /** *

A detailed description of the progress within a secondary status.

*

SageMaker provides secondary statuses and status messages that apply to each * of them:

Starting

  • Starting the training * job.

  • Launching requested ML instances.

  • *

    Insufficient capacity error from EC2 while launching instances, retrying!

    *

  • Launched instance was unhealthy, replacing it!

  • *

    Preparing the instances for training.

Training
*

  • Downloading the training image.

  • Training * image download completed. Training in progress.

*

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.

To * have an overview of your training job's progress, view * TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, * and StatusMessage together. For example, at the start of a training * job, you might see the following:

  • * TrainingJobStatus - InProgress

  • * SecondaryStatus - Training

  • * StatusMessage - Downloading the training image

*/ inline bool StatusMessageHasBeenSet() const { return m_statusMessageHasBeenSet; } /** *

A detailed description of the progress within a secondary status.

*

SageMaker provides secondary statuses and status messages that apply to each * of them:

Starting

  • Starting the training * job.

  • Launching requested ML instances.

  • *

    Insufficient capacity error from EC2 while launching instances, retrying!

    *

  • Launched instance was unhealthy, replacing it!

  • *

    Preparing the instances for training.

Training
*

  • Downloading the training image.

  • Training * image download completed. Training in progress.

*

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.

To * have an overview of your training job's progress, view * TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, * and StatusMessage together. For example, at the start of a training * job, you might see the following:

  • * TrainingJobStatus - InProgress

  • * SecondaryStatus - Training

  • * StatusMessage - Downloading the training image

*/ inline void SetStatusMessage(const Aws::String& value) { m_statusMessageHasBeenSet = true; m_statusMessage = value; } /** *

A detailed description of the progress within a secondary status.

*

SageMaker provides secondary statuses and status messages that apply to each * of them:

Starting

  • Starting the training * job.

  • Launching requested ML instances.

  • *

    Insufficient capacity error from EC2 while launching instances, retrying!

    *

  • Launched instance was unhealthy, replacing it!

  • *

    Preparing the instances for training.

Training
*

  • Downloading the training image.

  • Training * image download completed. Training in progress.

*

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.

To * have an overview of your training job's progress, view * TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, * and StatusMessage together. For example, at the start of a training * job, you might see the following:

  • * TrainingJobStatus - InProgress

  • * SecondaryStatus - Training

  • * StatusMessage - Downloading the training image

*/ inline void SetStatusMessage(Aws::String&& value) { m_statusMessageHasBeenSet = true; m_statusMessage = std::move(value); } /** *

A detailed description of the progress within a secondary status.

*

SageMaker provides secondary statuses and status messages that apply to each * of them:

Starting

  • Starting the training * job.

  • Launching requested ML instances.

  • *

    Insufficient capacity error from EC2 while launching instances, retrying!

    *

  • Launched instance was unhealthy, replacing it!

  • *

    Preparing the instances for training.

Training
*

  • Downloading the training image.

  • Training * image download completed. Training in progress.

*

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.

To * have an overview of your training job's progress, view * TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, * and StatusMessage together. For example, at the start of a training * job, you might see the following:

  • * TrainingJobStatus - InProgress

  • * SecondaryStatus - Training

  • * StatusMessage - Downloading the training image

*/ inline void SetStatusMessage(const char* value) { m_statusMessageHasBeenSet = true; m_statusMessage.assign(value); } /** *

A detailed description of the progress within a secondary status.

*

SageMaker provides secondary statuses and status messages that apply to each * of them:

Starting

  • Starting the training * job.

  • Launching requested ML instances.

  • *

    Insufficient capacity error from EC2 while launching instances, retrying!

    *

  • Launched instance was unhealthy, replacing it!

  • *

    Preparing the instances for training.

Training
*

  • Downloading the training image.

  • Training * image download completed. Training in progress.

*

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.

To * have an overview of your training job's progress, view * TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, * and StatusMessage together. For example, at the start of a training * job, you might see the following:

  • * TrainingJobStatus - InProgress

  • * SecondaryStatus - Training

  • * StatusMessage - Downloading the training image

*/ inline SecondaryStatusTransition& WithStatusMessage(const Aws::String& value) { SetStatusMessage(value); return *this;} /** *

A detailed description of the progress within a secondary status.

*

SageMaker provides secondary statuses and status messages that apply to each * of them:

Starting

  • Starting the training * job.

  • Launching requested ML instances.

  • *

    Insufficient capacity error from EC2 while launching instances, retrying!

    *

  • Launched instance was unhealthy, replacing it!

  • *

    Preparing the instances for training.

Training
*

  • Downloading the training image.

  • Training * image download completed. Training in progress.

*

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.

To * have an overview of your training job's progress, view * TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, * and StatusMessage together. For example, at the start of a training * job, you might see the following:

  • * TrainingJobStatus - InProgress

  • * SecondaryStatus - Training

  • * StatusMessage - Downloading the training image

*/ inline SecondaryStatusTransition& WithStatusMessage(Aws::String&& value) { SetStatusMessage(std::move(value)); return *this;} /** *

A detailed description of the progress within a secondary status.

*

SageMaker provides secondary statuses and status messages that apply to each * of them:

Starting

  • Starting the training * job.

  • Launching requested ML instances.

  • *

    Insufficient capacity error from EC2 while launching instances, retrying!

    *

  • Launched instance was unhealthy, replacing it!

  • *

    Preparing the instances for training.

Training
*

  • Downloading the training image.

  • Training * image download completed. Training in progress.

*

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.

To * have an overview of your training job's progress, view * TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, * and StatusMessage together. For example, at the start of a training * job, you might see the following:

  • * TrainingJobStatus - InProgress

  • * SecondaryStatus - Training

  • * StatusMessage - Downloading the training image

*/ inline SecondaryStatusTransition& WithStatusMessage(const char* value) { SetStatusMessage(value); return *this;} private: SecondaryStatus m_status; bool m_statusHasBeenSet = false; Aws::Utils::DateTime m_startTime; bool m_startTimeHasBeenSet = false; Aws::Utils::DateTime m_endTime; bool m_endTimeHasBeenSet = false; Aws::String m_statusMessage; bool m_statusMessageHasBeenSet = false; }; } // namespace Model } // namespace SageMaker } // namespace Aws