1458 lines
67 KiB
C++
1458 lines
67 KiB
C++
/**
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* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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* SPDX-License-Identifier: Apache-2.0.
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*/
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#pragma once
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#include <aws/sagemaker/SageMaker_EXPORTS.h>
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#include <aws/core/utils/memory/stl/AWSString.h>
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#include <aws/sagemaker/model/ModelArtifacts.h>
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#include <aws/sagemaker/model/TrainingJobStatus.h>
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#include <aws/sagemaker/model/SecondaryStatus.h>
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#include <aws/core/utils/memory/stl/AWSMap.h>
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#include <aws/sagemaker/model/AlgorithmSpecification.h>
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#include <aws/core/utils/memory/stl/AWSVector.h>
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#include <aws/sagemaker/model/OutputDataConfig.h>
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#include <aws/sagemaker/model/ResourceConfig.h>
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#include <aws/sagemaker/model/VpcConfig.h>
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#include <aws/sagemaker/model/StoppingCondition.h>
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#include <aws/core/utils/DateTime.h>
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#include <aws/sagemaker/model/CheckpointConfig.h>
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#include <aws/sagemaker/model/DebugHookConfig.h>
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#include <aws/sagemaker/model/ExperimentConfig.h>
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#include <aws/sagemaker/model/TensorBoardOutputConfig.h>
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#include <aws/sagemaker/model/Channel.h>
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#include <aws/sagemaker/model/SecondaryStatusTransition.h>
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#include <aws/sagemaker/model/MetricData.h>
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#include <aws/sagemaker/model/DebugRuleConfiguration.h>
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#include <aws/sagemaker/model/DebugRuleEvaluationStatus.h>
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#include <utility>
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namespace Aws
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{
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template<typename RESULT_TYPE>
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class AmazonWebServiceResult;
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namespace Utils
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{
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namespace Json
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{
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class JsonValue;
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} // namespace Json
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} // namespace Utils
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namespace SageMaker
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{
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namespace Model
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{
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class AWS_SAGEMAKER_API DescribeTrainingJobResult
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{
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public:
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DescribeTrainingJobResult();
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DescribeTrainingJobResult(const Aws::AmazonWebServiceResult<Aws::Utils::Json::JsonValue>& result);
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DescribeTrainingJobResult& operator=(const Aws::AmazonWebServiceResult<Aws::Utils::Json::JsonValue>& result);
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/**
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* <p> Name of the model training job. </p>
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*/
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inline const Aws::String& GetTrainingJobName() const{ return m_trainingJobName; }
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/**
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* <p> Name of the model training job. </p>
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*/
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inline void SetTrainingJobName(const Aws::String& value) { m_trainingJobName = value; }
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/**
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* <p> Name of the model training job. </p>
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*/
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inline void SetTrainingJobName(Aws::String&& value) { m_trainingJobName = std::move(value); }
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/**
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* <p> Name of the model training job. </p>
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*/
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inline void SetTrainingJobName(const char* value) { m_trainingJobName.assign(value); }
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/**
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* <p> Name of the model training job. </p>
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*/
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inline DescribeTrainingJobResult& WithTrainingJobName(const Aws::String& value) { SetTrainingJobName(value); return *this;}
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/**
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* <p> Name of the model training job. </p>
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*/
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inline DescribeTrainingJobResult& WithTrainingJobName(Aws::String&& value) { SetTrainingJobName(std::move(value)); return *this;}
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/**
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* <p> Name of the model training job. </p>
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*/
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inline DescribeTrainingJobResult& WithTrainingJobName(const char* value) { SetTrainingJobName(value); return *this;}
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/**
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* <p>The Amazon Resource Name (ARN) of the training job.</p>
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*/
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inline const Aws::String& GetTrainingJobArn() const{ return m_trainingJobArn; }
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/**
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* <p>The Amazon Resource Name (ARN) of the training job.</p>
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*/
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inline void SetTrainingJobArn(const Aws::String& value) { m_trainingJobArn = value; }
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/**
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* <p>The Amazon Resource Name (ARN) of the training job.</p>
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*/
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inline void SetTrainingJobArn(Aws::String&& value) { m_trainingJobArn = std::move(value); }
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/**
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* <p>The Amazon Resource Name (ARN) of the training job.</p>
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*/
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inline void SetTrainingJobArn(const char* value) { m_trainingJobArn.assign(value); }
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/**
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* <p>The Amazon Resource Name (ARN) of the training job.</p>
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*/
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inline DescribeTrainingJobResult& WithTrainingJobArn(const Aws::String& value) { SetTrainingJobArn(value); return *this;}
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/**
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* <p>The Amazon Resource Name (ARN) of the training job.</p>
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*/
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inline DescribeTrainingJobResult& WithTrainingJobArn(Aws::String&& value) { SetTrainingJobArn(std::move(value)); return *this;}
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/**
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* <p>The Amazon Resource Name (ARN) of the training job.</p>
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*/
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inline DescribeTrainingJobResult& WithTrainingJobArn(const char* value) { SetTrainingJobArn(value); return *this;}
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/**
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* <p>The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if
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* the training job was launched by a hyperparameter tuning job.</p>
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*/
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inline const Aws::String& GetTuningJobArn() const{ return m_tuningJobArn; }
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/**
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* <p>The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if
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* the training job was launched by a hyperparameter tuning job.</p>
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*/
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inline void SetTuningJobArn(const Aws::String& value) { m_tuningJobArn = value; }
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/**
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* <p>The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if
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* the training job was launched by a hyperparameter tuning job.</p>
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*/
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inline void SetTuningJobArn(Aws::String&& value) { m_tuningJobArn = std::move(value); }
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/**
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* <p>The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if
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* the training job was launched by a hyperparameter tuning job.</p>
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*/
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inline void SetTuningJobArn(const char* value) { m_tuningJobArn.assign(value); }
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/**
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* <p>The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if
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* the training job was launched by a hyperparameter tuning job.</p>
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*/
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inline DescribeTrainingJobResult& WithTuningJobArn(const Aws::String& value) { SetTuningJobArn(value); return *this;}
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/**
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* <p>The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if
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* the training job was launched by a hyperparameter tuning job.</p>
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*/
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inline DescribeTrainingJobResult& WithTuningJobArn(Aws::String&& value) { SetTuningJobArn(std::move(value)); return *this;}
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/**
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* <p>The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if
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* the training job was launched by a hyperparameter tuning job.</p>
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*/
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inline DescribeTrainingJobResult& WithTuningJobArn(const char* value) { SetTuningJobArn(value); return *this;}
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/**
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* <p>The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling
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* job that created the transform or training job.</p>
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*/
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inline const Aws::String& GetLabelingJobArn() const{ return m_labelingJobArn; }
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/**
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* <p>The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling
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* job that created the transform or training job.</p>
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*/
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inline void SetLabelingJobArn(const Aws::String& value) { m_labelingJobArn = value; }
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/**
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* <p>The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling
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* job that created the transform or training job.</p>
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*/
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inline void SetLabelingJobArn(Aws::String&& value) { m_labelingJobArn = std::move(value); }
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/**
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* <p>The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling
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* job that created the transform or training job.</p>
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*/
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inline void SetLabelingJobArn(const char* value) { m_labelingJobArn.assign(value); }
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/**
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* <p>The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling
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* job that created the transform or training job.</p>
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*/
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inline DescribeTrainingJobResult& WithLabelingJobArn(const Aws::String& value) { SetLabelingJobArn(value); return *this;}
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/**
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* <p>The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling
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* job that created the transform or training job.</p>
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*/
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inline DescribeTrainingJobResult& WithLabelingJobArn(Aws::String&& value) { SetLabelingJobArn(std::move(value)); return *this;}
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/**
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* <p>The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling
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* job that created the transform or training job.</p>
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*/
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inline DescribeTrainingJobResult& WithLabelingJobArn(const char* value) { SetLabelingJobArn(value); return *this;}
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/**
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* <p>The Amazon Resource Name (ARN) of an AutoML job.</p>
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*/
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inline const Aws::String& GetAutoMLJobArn() const{ return m_autoMLJobArn; }
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/**
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* <p>The Amazon Resource Name (ARN) of an AutoML job.</p>
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*/
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inline void SetAutoMLJobArn(const Aws::String& value) { m_autoMLJobArn = value; }
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/**
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* <p>The Amazon Resource Name (ARN) of an AutoML job.</p>
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*/
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inline void SetAutoMLJobArn(Aws::String&& value) { m_autoMLJobArn = std::move(value); }
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/**
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* <p>The Amazon Resource Name (ARN) of an AutoML job.</p>
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*/
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inline void SetAutoMLJobArn(const char* value) { m_autoMLJobArn.assign(value); }
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/**
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* <p>The Amazon Resource Name (ARN) of an AutoML job.</p>
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*/
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inline DescribeTrainingJobResult& WithAutoMLJobArn(const Aws::String& value) { SetAutoMLJobArn(value); return *this;}
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/**
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* <p>The Amazon Resource Name (ARN) of an AutoML job.</p>
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*/
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inline DescribeTrainingJobResult& WithAutoMLJobArn(Aws::String&& value) { SetAutoMLJobArn(std::move(value)); return *this;}
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/**
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* <p>The Amazon Resource Name (ARN) of an AutoML job.</p>
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*/
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inline DescribeTrainingJobResult& WithAutoMLJobArn(const char* value) { SetAutoMLJobArn(value); return *this;}
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/**
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* <p>Information about the Amazon S3 location that is configured for storing model
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* artifacts. </p>
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*/
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inline const ModelArtifacts& GetModelArtifacts() const{ return m_modelArtifacts; }
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/**
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* <p>Information about the Amazon S3 location that is configured for storing model
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* artifacts. </p>
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*/
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inline void SetModelArtifacts(const ModelArtifacts& value) { m_modelArtifacts = value; }
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/**
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* <p>Information about the Amazon S3 location that is configured for storing model
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* artifacts. </p>
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*/
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inline void SetModelArtifacts(ModelArtifacts&& value) { m_modelArtifacts = std::move(value); }
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/**
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* <p>Information about the Amazon S3 location that is configured for storing model
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* artifacts. </p>
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*/
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inline DescribeTrainingJobResult& WithModelArtifacts(const ModelArtifacts& value) { SetModelArtifacts(value); return *this;}
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/**
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* <p>Information about the Amazon S3 location that is configured for storing model
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* artifacts. </p>
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*/
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inline DescribeTrainingJobResult& WithModelArtifacts(ModelArtifacts&& value) { SetModelArtifacts(std::move(value)); return *this;}
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/**
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* <p>The status of the training job.</p> <p>Amazon SageMaker provides the
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* following training job statuses:</p> <ul> <li> <p> <code>InProgress</code> - The
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* training is in progress.</p> </li> <li> <p> <code>Completed</code> - The
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* training job has completed.</p> </li> <li> <p> <code>Failed</code> - The
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* training job has failed. To see the reason for the failure, see the
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* <code>FailureReason</code> field in the response to a
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* <code>DescribeTrainingJobResponse</code> call.</p> </li> <li> <p>
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* <code>Stopping</code> - The training job is stopping.</p> </li> <li> <p>
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* <code>Stopped</code> - The training job has stopped.</p> </li> </ul> <p>For more
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* detailed information, see <code>SecondaryStatus</code>. </p>
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*/
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inline const TrainingJobStatus& GetTrainingJobStatus() const{ return m_trainingJobStatus; }
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/**
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* <p>The status of the training job.</p> <p>Amazon SageMaker provides the
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* following training job statuses:</p> <ul> <li> <p> <code>InProgress</code> - The
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* training is in progress.</p> </li> <li> <p> <code>Completed</code> - The
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* training job has completed.</p> </li> <li> <p> <code>Failed</code> - The
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* training job has failed. To see the reason for the failure, see the
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* <code>FailureReason</code> field in the response to a
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* <code>DescribeTrainingJobResponse</code> call.</p> </li> <li> <p>
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* <code>Stopping</code> - The training job is stopping.</p> </li> <li> <p>
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* <code>Stopped</code> - The training job has stopped.</p> </li> </ul> <p>For more
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* detailed information, see <code>SecondaryStatus</code>. </p>
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*/
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inline void SetTrainingJobStatus(const TrainingJobStatus& value) { m_trainingJobStatus = value; }
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/**
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* <p>The status of the training job.</p> <p>Amazon SageMaker provides the
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* following training job statuses:</p> <ul> <li> <p> <code>InProgress</code> - The
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* training is in progress.</p> </li> <li> <p> <code>Completed</code> - The
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* training job has completed.</p> </li> <li> <p> <code>Failed</code> - The
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* training job has failed. To see the reason for the failure, see the
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* <code>FailureReason</code> field in the response to a
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* <code>DescribeTrainingJobResponse</code> call.</p> </li> <li> <p>
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* <code>Stopping</code> - The training job is stopping.</p> </li> <li> <p>
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* <code>Stopped</code> - The training job has stopped.</p> </li> </ul> <p>For more
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* detailed information, see <code>SecondaryStatus</code>. </p>
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*/
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inline void SetTrainingJobStatus(TrainingJobStatus&& value) { m_trainingJobStatus = std::move(value); }
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/**
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* <p>The status of the training job.</p> <p>Amazon SageMaker provides the
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* following training job statuses:</p> <ul> <li> <p> <code>InProgress</code> - The
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* training is in progress.</p> </li> <li> <p> <code>Completed</code> - The
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* training job has completed.</p> </li> <li> <p> <code>Failed</code> - The
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* training job has failed. To see the reason for the failure, see the
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* <code>FailureReason</code> field in the response to a
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* <code>DescribeTrainingJobResponse</code> call.</p> </li> <li> <p>
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* <code>Stopping</code> - The training job is stopping.</p> </li> <li> <p>
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* <code>Stopped</code> - The training job has stopped.</p> </li> </ul> <p>For more
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* detailed information, see <code>SecondaryStatus</code>. </p>
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*/
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inline DescribeTrainingJobResult& WithTrainingJobStatus(const TrainingJobStatus& value) { SetTrainingJobStatus(value); return *this;}
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/**
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* <p>The status of the training job.</p> <p>Amazon SageMaker provides the
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* following training job statuses:</p> <ul> <li> <p> <code>InProgress</code> - The
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* training is in progress.</p> </li> <li> <p> <code>Completed</code> - The
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* training job has completed.</p> </li> <li> <p> <code>Failed</code> - The
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* training job has failed. To see the reason for the failure, see the
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* <code>FailureReason</code> field in the response to a
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* <code>DescribeTrainingJobResponse</code> call.</p> </li> <li> <p>
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* <code>Stopping</code> - The training job is stopping.</p> </li> <li> <p>
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* <code>Stopped</code> - The training job has stopped.</p> </li> </ul> <p>For more
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* detailed information, see <code>SecondaryStatus</code>. </p>
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*/
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inline DescribeTrainingJobResult& WithTrainingJobStatus(TrainingJobStatus&& value) { SetTrainingJobStatus(std::move(value)); return *this;}
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/**
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* <p> Provides detailed information about the state of the training job. For
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* detailed information on the secondary status of the training job, see
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* <code>StatusMessage</code> under <a>SecondaryStatusTransition</a>.</p> <p>Amazon
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* SageMaker provides primary statuses and secondary statuses that apply to each of
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* them:</p> <dl> <dt>InProgress</dt> <dd> <ul> <li> <p> <code>Starting</code> -
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* Starting the training job.</p> </li> <li> <p> <code>Downloading</code> - An
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* optional stage for algorithms that support <code>File</code> training input
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* mode. It indicates that data is being downloaded to the ML storage volumes.</p>
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* </li> <li> <p> <code>Training</code> - Training is in progress.</p> </li> <li>
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* <p> <code>Interrupted</code> - The job stopped because the managed spot training
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* instances were interrupted. </p> </li> <li> <p> <code>Uploading</code> -
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* Training is complete and the model artifacts are being uploaded to the S3
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* location.</p> </li> </ul> </dd> <dt>Completed</dt> <dd> <ul> <li> <p>
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* <code>Completed</code> - The training job has completed.</p> </li> </ul> </dd>
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* <dt>Failed</dt> <dd> <ul> <li> <p> <code>Failed</code> - The training job has
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* failed. The reason for the failure is returned in the <code>FailureReason</code>
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* field of <code>DescribeTrainingJobResponse</code>.</p> </li> </ul> </dd>
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* <dt>Stopped</dt> <dd> <ul> <li> <p> <code>MaxRuntimeExceeded</code> - The job
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* stopped because it exceeded the maximum allowed runtime.</p> </li> <li> <p>
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* <code>MaxWaitTimeExceeded</code> - The job stopped because it exceeded the
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* maximum allowed wait time.</p> </li> <li> <p> <code>Stopped</code> - The
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* training job has stopped.</p> </li> </ul> </dd> <dt>Stopping</dt> <dd> <ul> <li>
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* <p> <code>Stopping</code> - Stopping the training job.</p> </li> </ul> </dd>
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* </dl> <p>Valid values for <code>SecondaryStatus</code> are subject
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* to change. </p> <p>We no longer support the following secondary
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* statuses:</p> <ul> <li> <p> <code>LaunchingMLInstances</code> </p> </li> <li>
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* <p> <code>PreparingTrainingStack</code> </p> </li> <li> <p>
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* <code>DownloadingTrainingImage</code> </p> </li> </ul>
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*/
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inline const SecondaryStatus& GetSecondaryStatus() const{ return m_secondaryStatus; }
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|
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/**
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* <p> Provides detailed information about the state of the training job. For
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* detailed information on the secondary status of the training job, see
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|
* <code>StatusMessage</code> under <a>SecondaryStatusTransition</a>.</p> <p>Amazon
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|
* SageMaker provides primary statuses and secondary statuses that apply to each of
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|
* them:</p> <dl> <dt>InProgress</dt> <dd> <ul> <li> <p> <code>Starting</code> -
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* Starting the training job.</p> </li> <li> <p> <code>Downloading</code> - An
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|
* 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>
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|
* </li> <li> <p> <code>Training</code> - Training is in progress.</p> </li> <li>
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* <p> <code>Interrupted</code> - The job stopped because the managed spot training
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* instances were interrupted. </p> </li> <li> <p> <code>Uploading</code> -
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* Training is complete and the model artifacts are being uploaded to the S3
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* location.</p> </li> </ul> </dd> <dt>Completed</dt> <dd> <ul> <li> <p>
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* <code>Completed</code> - The training job has completed.</p> </li> </ul> </dd>
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* <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>MaxWaitTimeExceeded</code> - The job stopped because it exceeded the
|
|
* maximum allowed wait time.</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>Valid values for <code>SecondaryStatus</code> are subject
|
|
* to change. </p> <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>
|
|
*/
|
|
inline void SetSecondaryStatus(const SecondaryStatus& value) { m_secondaryStatus = value; }
|
|
|
|
/**
|
|
* <p> Provides detailed information about the state of the training job. For
|
|
* detailed information on the secondary status of the training job, see
|
|
* <code>StatusMessage</code> under <a>SecondaryStatusTransition</a>.</p> <p>Amazon
|
|
* SageMaker provides primary statuses and secondary statuses that apply to each of
|
|
* them:</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>Interrupted</code> - The job stopped because the managed spot training
|
|
* instances were interrupted. </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>MaxWaitTimeExceeded</code> - The job stopped because it exceeded the
|
|
* maximum allowed wait time.</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>Valid values for <code>SecondaryStatus</code> are subject
|
|
* to change. </p> <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>
|
|
*/
|
|
inline void SetSecondaryStatus(SecondaryStatus&& value) { m_secondaryStatus = std::move(value); }
|
|
|
|
/**
|
|
* <p> Provides detailed information about the state of the training job. For
|
|
* detailed information on the secondary status of the training job, see
|
|
* <code>StatusMessage</code> under <a>SecondaryStatusTransition</a>.</p> <p>Amazon
|
|
* SageMaker provides primary statuses and secondary statuses that apply to each of
|
|
* them:</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>Interrupted</code> - The job stopped because the managed spot training
|
|
* instances were interrupted. </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>MaxWaitTimeExceeded</code> - The job stopped because it exceeded the
|
|
* maximum allowed wait time.</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>Valid values for <code>SecondaryStatus</code> are subject
|
|
* to change. </p> <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>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithSecondaryStatus(const SecondaryStatus& value) { SetSecondaryStatus(value); return *this;}
|
|
|
|
/**
|
|
* <p> Provides detailed information about the state of the training job. For
|
|
* detailed information on the secondary status of the training job, see
|
|
* <code>StatusMessage</code> under <a>SecondaryStatusTransition</a>.</p> <p>Amazon
|
|
* SageMaker provides primary statuses and secondary statuses that apply to each of
|
|
* them:</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>Interrupted</code> - The job stopped because the managed spot training
|
|
* instances were interrupted. </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>MaxWaitTimeExceeded</code> - The job stopped because it exceeded the
|
|
* maximum allowed wait time.</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>Valid values for <code>SecondaryStatus</code> are subject
|
|
* to change. </p> <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>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithSecondaryStatus(SecondaryStatus&& value) { SetSecondaryStatus(std::move(value)); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>If the training job failed, the reason it failed. </p>
|
|
*/
|
|
inline const Aws::String& GetFailureReason() const{ return m_failureReason; }
|
|
|
|
/**
|
|
* <p>If the training job failed, the reason it failed. </p>
|
|
*/
|
|
inline void SetFailureReason(const Aws::String& value) { m_failureReason = value; }
|
|
|
|
/**
|
|
* <p>If the training job failed, the reason it failed. </p>
|
|
*/
|
|
inline void SetFailureReason(Aws::String&& value) { m_failureReason = std::move(value); }
|
|
|
|
/**
|
|
* <p>If the training job failed, the reason it failed. </p>
|
|
*/
|
|
inline void SetFailureReason(const char* value) { m_failureReason.assign(value); }
|
|
|
|
/**
|
|
* <p>If the training job failed, the reason it failed. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithFailureReason(const Aws::String& value) { SetFailureReason(value); return *this;}
|
|
|
|
/**
|
|
* <p>If the training job failed, the reason it failed. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithFailureReason(Aws::String&& value) { SetFailureReason(std::move(value)); return *this;}
|
|
|
|
/**
|
|
* <p>If the training job failed, the reason it failed. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithFailureReason(const char* value) { SetFailureReason(value); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>Algorithm-specific parameters. </p>
|
|
*/
|
|
inline const Aws::Map<Aws::String, Aws::String>& GetHyperParameters() const{ return m_hyperParameters; }
|
|
|
|
/**
|
|
* <p>Algorithm-specific parameters. </p>
|
|
*/
|
|
inline void SetHyperParameters(const Aws::Map<Aws::String, Aws::String>& value) { m_hyperParameters = value; }
|
|
|
|
/**
|
|
* <p>Algorithm-specific parameters. </p>
|
|
*/
|
|
inline void SetHyperParameters(Aws::Map<Aws::String, Aws::String>&& value) { m_hyperParameters = std::move(value); }
|
|
|
|
/**
|
|
* <p>Algorithm-specific parameters. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithHyperParameters(const Aws::Map<Aws::String, Aws::String>& value) { SetHyperParameters(value); return *this;}
|
|
|
|
/**
|
|
* <p>Algorithm-specific parameters. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithHyperParameters(Aws::Map<Aws::String, Aws::String>&& value) { SetHyperParameters(std::move(value)); return *this;}
|
|
|
|
/**
|
|
* <p>Algorithm-specific parameters. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddHyperParameters(const Aws::String& key, const Aws::String& value) { m_hyperParameters.emplace(key, value); return *this; }
|
|
|
|
/**
|
|
* <p>Algorithm-specific parameters. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddHyperParameters(Aws::String&& key, const Aws::String& value) { m_hyperParameters.emplace(std::move(key), value); return *this; }
|
|
|
|
/**
|
|
* <p>Algorithm-specific parameters. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddHyperParameters(const Aws::String& key, Aws::String&& value) { m_hyperParameters.emplace(key, std::move(value)); return *this; }
|
|
|
|
/**
|
|
* <p>Algorithm-specific parameters. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddHyperParameters(Aws::String&& key, Aws::String&& value) { m_hyperParameters.emplace(std::move(key), std::move(value)); return *this; }
|
|
|
|
/**
|
|
* <p>Algorithm-specific parameters. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddHyperParameters(const char* key, Aws::String&& value) { m_hyperParameters.emplace(key, std::move(value)); return *this; }
|
|
|
|
/**
|
|
* <p>Algorithm-specific parameters. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddHyperParameters(Aws::String&& key, const char* value) { m_hyperParameters.emplace(std::move(key), value); return *this; }
|
|
|
|
/**
|
|
* <p>Algorithm-specific parameters. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddHyperParameters(const char* key, const char* value) { m_hyperParameters.emplace(key, value); return *this; }
|
|
|
|
|
|
/**
|
|
* <p>Information about the algorithm used for training, and algorithm metadata.
|
|
* </p>
|
|
*/
|
|
inline const AlgorithmSpecification& GetAlgorithmSpecification() const{ return m_algorithmSpecification; }
|
|
|
|
/**
|
|
* <p>Information about the algorithm used for training, and algorithm metadata.
|
|
* </p>
|
|
*/
|
|
inline void SetAlgorithmSpecification(const AlgorithmSpecification& value) { m_algorithmSpecification = value; }
|
|
|
|
/**
|
|
* <p>Information about the algorithm used for training, and algorithm metadata.
|
|
* </p>
|
|
*/
|
|
inline void SetAlgorithmSpecification(AlgorithmSpecification&& value) { m_algorithmSpecification = std::move(value); }
|
|
|
|
/**
|
|
* <p>Information about the algorithm used for training, and algorithm metadata.
|
|
* </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithAlgorithmSpecification(const AlgorithmSpecification& value) { SetAlgorithmSpecification(value); return *this;}
|
|
|
|
/**
|
|
* <p>Information about the algorithm used for training, and algorithm metadata.
|
|
* </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithAlgorithmSpecification(AlgorithmSpecification&& value) { SetAlgorithmSpecification(std::move(value)); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>The AWS Identity and Access Management (IAM) role configured for the training
|
|
* job. </p>
|
|
*/
|
|
inline const Aws::String& GetRoleArn() const{ return m_roleArn; }
|
|
|
|
/**
|
|
* <p>The AWS Identity and Access Management (IAM) role configured for the training
|
|
* job. </p>
|
|
*/
|
|
inline void SetRoleArn(const Aws::String& value) { m_roleArn = value; }
|
|
|
|
/**
|
|
* <p>The AWS Identity and Access Management (IAM) role configured for the training
|
|
* job. </p>
|
|
*/
|
|
inline void SetRoleArn(Aws::String&& value) { m_roleArn = std::move(value); }
|
|
|
|
/**
|
|
* <p>The AWS Identity and Access Management (IAM) role configured for the training
|
|
* job. </p>
|
|
*/
|
|
inline void SetRoleArn(const char* value) { m_roleArn.assign(value); }
|
|
|
|
/**
|
|
* <p>The AWS Identity and Access Management (IAM) role configured for the training
|
|
* job. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithRoleArn(const Aws::String& value) { SetRoleArn(value); return *this;}
|
|
|
|
/**
|
|
* <p>The AWS Identity and Access Management (IAM) role configured for the training
|
|
* job. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithRoleArn(Aws::String&& value) { SetRoleArn(std::move(value)); return *this;}
|
|
|
|
/**
|
|
* <p>The AWS Identity and Access Management (IAM) role configured for the training
|
|
* job. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithRoleArn(const char* value) { SetRoleArn(value); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>An array of <code>Channel</code> objects that describes each data input
|
|
* channel. </p>
|
|
*/
|
|
inline const Aws::Vector<Channel>& GetInputDataConfig() const{ return m_inputDataConfig; }
|
|
|
|
/**
|
|
* <p>An array of <code>Channel</code> objects that describes each data input
|
|
* channel. </p>
|
|
*/
|
|
inline void SetInputDataConfig(const Aws::Vector<Channel>& value) { m_inputDataConfig = value; }
|
|
|
|
/**
|
|
* <p>An array of <code>Channel</code> objects that describes each data input
|
|
* channel. </p>
|
|
*/
|
|
inline void SetInputDataConfig(Aws::Vector<Channel>&& value) { m_inputDataConfig = std::move(value); }
|
|
|
|
/**
|
|
* <p>An array of <code>Channel</code> objects that describes each data input
|
|
* channel. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithInputDataConfig(const Aws::Vector<Channel>& value) { SetInputDataConfig(value); return *this;}
|
|
|
|
/**
|
|
* <p>An array of <code>Channel</code> objects that describes each data input
|
|
* channel. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithInputDataConfig(Aws::Vector<Channel>&& value) { SetInputDataConfig(std::move(value)); return *this;}
|
|
|
|
/**
|
|
* <p>An array of <code>Channel</code> objects that describes each data input
|
|
* channel. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddInputDataConfig(const Channel& value) { m_inputDataConfig.push_back(value); return *this; }
|
|
|
|
/**
|
|
* <p>An array of <code>Channel</code> objects that describes each data input
|
|
* channel. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddInputDataConfig(Channel&& value) { m_inputDataConfig.push_back(std::move(value)); return *this; }
|
|
|
|
|
|
/**
|
|
* <p>The S3 path where model artifacts that you configured when creating the job
|
|
* are stored. Amazon SageMaker creates subfolders for model artifacts. </p>
|
|
*/
|
|
inline const OutputDataConfig& GetOutputDataConfig() const{ return m_outputDataConfig; }
|
|
|
|
/**
|
|
* <p>The S3 path where model artifacts that you configured when creating the job
|
|
* are stored. Amazon SageMaker creates subfolders for model artifacts. </p>
|
|
*/
|
|
inline void SetOutputDataConfig(const OutputDataConfig& value) { m_outputDataConfig = value; }
|
|
|
|
/**
|
|
* <p>The S3 path where model artifacts that you configured when creating the job
|
|
* are stored. Amazon SageMaker creates subfolders for model artifacts. </p>
|
|
*/
|
|
inline void SetOutputDataConfig(OutputDataConfig&& value) { m_outputDataConfig = std::move(value); }
|
|
|
|
/**
|
|
* <p>The S3 path where model artifacts that you configured when creating the job
|
|
* are stored. Amazon SageMaker creates subfolders for model artifacts. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithOutputDataConfig(const OutputDataConfig& value) { SetOutputDataConfig(value); return *this;}
|
|
|
|
/**
|
|
* <p>The S3 path where model artifacts that you configured when creating the job
|
|
* are stored. Amazon SageMaker creates subfolders for model artifacts. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithOutputDataConfig(OutputDataConfig&& value) { SetOutputDataConfig(std::move(value)); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>Resources, including ML compute instances and ML storage volumes, that are
|
|
* configured for model training. </p>
|
|
*/
|
|
inline const ResourceConfig& GetResourceConfig() const{ return m_resourceConfig; }
|
|
|
|
/**
|
|
* <p>Resources, including ML compute instances and ML storage volumes, that are
|
|
* configured for model training. </p>
|
|
*/
|
|
inline void SetResourceConfig(const ResourceConfig& value) { m_resourceConfig = value; }
|
|
|
|
/**
|
|
* <p>Resources, including ML compute instances and ML storage volumes, that are
|
|
* configured for model training. </p>
|
|
*/
|
|
inline void SetResourceConfig(ResourceConfig&& value) { m_resourceConfig = std::move(value); }
|
|
|
|
/**
|
|
* <p>Resources, including ML compute instances and ML storage volumes, that are
|
|
* configured for model training. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithResourceConfig(const ResourceConfig& value) { SetResourceConfig(value); return *this;}
|
|
|
|
/**
|
|
* <p>Resources, including ML compute instances and ML storage volumes, that are
|
|
* configured for model training. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithResourceConfig(ResourceConfig&& value) { SetResourceConfig(std::move(value)); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>A <a>VpcConfig</a> object that specifies the VPC that this training job has
|
|
* access to. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html">Protect
|
|
* Training Jobs by Using an Amazon Virtual Private Cloud</a>.</p>
|
|
*/
|
|
inline const VpcConfig& GetVpcConfig() const{ return m_vpcConfig; }
|
|
|
|
/**
|
|
* <p>A <a>VpcConfig</a> object that specifies the VPC that this training job has
|
|
* access to. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html">Protect
|
|
* Training Jobs by Using an Amazon Virtual Private Cloud</a>.</p>
|
|
*/
|
|
inline void SetVpcConfig(const VpcConfig& value) { m_vpcConfig = value; }
|
|
|
|
/**
|
|
* <p>A <a>VpcConfig</a> object that specifies the VPC that this training job has
|
|
* access to. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html">Protect
|
|
* Training Jobs by Using an Amazon Virtual Private Cloud</a>.</p>
|
|
*/
|
|
inline void SetVpcConfig(VpcConfig&& value) { m_vpcConfig = std::move(value); }
|
|
|
|
/**
|
|
* <p>A <a>VpcConfig</a> object that specifies the VPC that this training job has
|
|
* access to. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html">Protect
|
|
* Training Jobs by Using an Amazon Virtual Private Cloud</a>.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithVpcConfig(const VpcConfig& value) { SetVpcConfig(value); return *this;}
|
|
|
|
/**
|
|
* <p>A <a>VpcConfig</a> object that specifies the VPC that this training job has
|
|
* access to. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html">Protect
|
|
* Training Jobs by Using an Amazon Virtual Private Cloud</a>.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithVpcConfig(VpcConfig&& value) { SetVpcConfig(std::move(value)); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>Specifies a limit to how long a model training job can run. It also specifies
|
|
* the maximum time to wait for a spot instance. When the job reaches the time
|
|
* limit, Amazon SageMaker ends the training job. Use this API to cap model
|
|
* training costs.</p> <p>To stop a job, Amazon SageMaker sends the algorithm the
|
|
* <code>SIGTERM</code> 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. </p>
|
|
*/
|
|
inline const StoppingCondition& GetStoppingCondition() const{ return m_stoppingCondition; }
|
|
|
|
/**
|
|
* <p>Specifies a limit to how long a model training job can run. It also specifies
|
|
* the maximum time to wait for a spot instance. When the job reaches the time
|
|
* limit, Amazon SageMaker ends the training job. Use this API to cap model
|
|
* training costs.</p> <p>To stop a job, Amazon SageMaker sends the algorithm the
|
|
* <code>SIGTERM</code> 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. </p>
|
|
*/
|
|
inline void SetStoppingCondition(const StoppingCondition& value) { m_stoppingCondition = value; }
|
|
|
|
/**
|
|
* <p>Specifies a limit to how long a model training job can run. It also specifies
|
|
* the maximum time to wait for a spot instance. When the job reaches the time
|
|
* limit, Amazon SageMaker ends the training job. Use this API to cap model
|
|
* training costs.</p> <p>To stop a job, Amazon SageMaker sends the algorithm the
|
|
* <code>SIGTERM</code> 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. </p>
|
|
*/
|
|
inline void SetStoppingCondition(StoppingCondition&& value) { m_stoppingCondition = std::move(value); }
|
|
|
|
/**
|
|
* <p>Specifies a limit to how long a model training job can run. It also specifies
|
|
* the maximum time to wait for a spot instance. When the job reaches the time
|
|
* limit, Amazon SageMaker ends the training job. Use this API to cap model
|
|
* training costs.</p> <p>To stop a job, Amazon SageMaker sends the algorithm the
|
|
* <code>SIGTERM</code> 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. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithStoppingCondition(const StoppingCondition& value) { SetStoppingCondition(value); return *this;}
|
|
|
|
/**
|
|
* <p>Specifies a limit to how long a model training job can run. It also specifies
|
|
* the maximum time to wait for a spot instance. When the job reaches the time
|
|
* limit, Amazon SageMaker ends the training job. Use this API to cap model
|
|
* training costs.</p> <p>To stop a job, Amazon SageMaker sends the algorithm the
|
|
* <code>SIGTERM</code> 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. </p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithStoppingCondition(StoppingCondition&& value) { SetStoppingCondition(std::move(value)); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>A timestamp that indicates when the training job was created.</p>
|
|
*/
|
|
inline const Aws::Utils::DateTime& GetCreationTime() const{ return m_creationTime; }
|
|
|
|
/**
|
|
* <p>A timestamp that indicates when the training job was created.</p>
|
|
*/
|
|
inline void SetCreationTime(const Aws::Utils::DateTime& value) { m_creationTime = value; }
|
|
|
|
/**
|
|
* <p>A timestamp that indicates when the training job was created.</p>
|
|
*/
|
|
inline void SetCreationTime(Aws::Utils::DateTime&& value) { m_creationTime = std::move(value); }
|
|
|
|
/**
|
|
* <p>A timestamp that indicates when the training job was created.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithCreationTime(const Aws::Utils::DateTime& value) { SetCreationTime(value); return *this;}
|
|
|
|
/**
|
|
* <p>A timestamp that indicates when the training job was created.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithCreationTime(Aws::Utils::DateTime&& value) { SetCreationTime(std::move(value)); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>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
|
|
* <code>TrainingEndTime</code>. 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.</p>
|
|
*/
|
|
inline const Aws::Utils::DateTime& GetTrainingStartTime() const{ return m_trainingStartTime; }
|
|
|
|
/**
|
|
* <p>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
|
|
* <code>TrainingEndTime</code>. 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.</p>
|
|
*/
|
|
inline void SetTrainingStartTime(const Aws::Utils::DateTime& value) { m_trainingStartTime = value; }
|
|
|
|
/**
|
|
* <p>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
|
|
* <code>TrainingEndTime</code>. 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.</p>
|
|
*/
|
|
inline void SetTrainingStartTime(Aws::Utils::DateTime&& value) { m_trainingStartTime = std::move(value); }
|
|
|
|
/**
|
|
* <p>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
|
|
* <code>TrainingEndTime</code>. 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.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithTrainingStartTime(const Aws::Utils::DateTime& value) { SetTrainingStartTime(value); return *this;}
|
|
|
|
/**
|
|
* <p>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
|
|
* <code>TrainingEndTime</code>. 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.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithTrainingStartTime(Aws::Utils::DateTime&& value) { SetTrainingStartTime(std::move(value)); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>Indicates the time when the training job ends on training instances. You are
|
|
* billed for the time interval between the value of <code>TrainingStartTime</code>
|
|
* 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 Amazon
|
|
* SageMaker detects a job failure.</p>
|
|
*/
|
|
inline const Aws::Utils::DateTime& GetTrainingEndTime() const{ return m_trainingEndTime; }
|
|
|
|
/**
|
|
* <p>Indicates the time when the training job ends on training instances. You are
|
|
* billed for the time interval between the value of <code>TrainingStartTime</code>
|
|
* 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 Amazon
|
|
* SageMaker detects a job failure.</p>
|
|
*/
|
|
inline void SetTrainingEndTime(const Aws::Utils::DateTime& value) { m_trainingEndTime = value; }
|
|
|
|
/**
|
|
* <p>Indicates the time when the training job ends on training instances. You are
|
|
* billed for the time interval between the value of <code>TrainingStartTime</code>
|
|
* 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 Amazon
|
|
* SageMaker detects a job failure.</p>
|
|
*/
|
|
inline void SetTrainingEndTime(Aws::Utils::DateTime&& value) { m_trainingEndTime = std::move(value); }
|
|
|
|
/**
|
|
* <p>Indicates the time when the training job ends on training instances. You are
|
|
* billed for the time interval between the value of <code>TrainingStartTime</code>
|
|
* 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 Amazon
|
|
* SageMaker detects a job failure.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithTrainingEndTime(const Aws::Utils::DateTime& value) { SetTrainingEndTime(value); return *this;}
|
|
|
|
/**
|
|
* <p>Indicates the time when the training job ends on training instances. You are
|
|
* billed for the time interval between the value of <code>TrainingStartTime</code>
|
|
* 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 Amazon
|
|
* SageMaker detects a job failure.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithTrainingEndTime(Aws::Utils::DateTime&& value) { SetTrainingEndTime(std::move(value)); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>A timestamp that indicates when the status of the training job was last
|
|
* modified.</p>
|
|
*/
|
|
inline const Aws::Utils::DateTime& GetLastModifiedTime() const{ return m_lastModifiedTime; }
|
|
|
|
/**
|
|
* <p>A timestamp that indicates when the status of the training job was last
|
|
* modified.</p>
|
|
*/
|
|
inline void SetLastModifiedTime(const Aws::Utils::DateTime& value) { m_lastModifiedTime = value; }
|
|
|
|
/**
|
|
* <p>A timestamp that indicates when the status of the training job was last
|
|
* modified.</p>
|
|
*/
|
|
inline void SetLastModifiedTime(Aws::Utils::DateTime&& value) { m_lastModifiedTime = std::move(value); }
|
|
|
|
/**
|
|
* <p>A timestamp that indicates when the status of the training job was last
|
|
* modified.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithLastModifiedTime(const Aws::Utils::DateTime& value) { SetLastModifiedTime(value); return *this;}
|
|
|
|
/**
|
|
* <p>A timestamp that indicates when the status of the training job was last
|
|
* modified.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithLastModifiedTime(Aws::Utils::DateTime&& value) { SetLastModifiedTime(std::move(value)); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>A history of all of the secondary statuses that the training job has
|
|
* transitioned through.</p>
|
|
*/
|
|
inline const Aws::Vector<SecondaryStatusTransition>& GetSecondaryStatusTransitions() const{ return m_secondaryStatusTransitions; }
|
|
|
|
/**
|
|
* <p>A history of all of the secondary statuses that the training job has
|
|
* transitioned through.</p>
|
|
*/
|
|
inline void SetSecondaryStatusTransitions(const Aws::Vector<SecondaryStatusTransition>& value) { m_secondaryStatusTransitions = value; }
|
|
|
|
/**
|
|
* <p>A history of all of the secondary statuses that the training job has
|
|
* transitioned through.</p>
|
|
*/
|
|
inline void SetSecondaryStatusTransitions(Aws::Vector<SecondaryStatusTransition>&& value) { m_secondaryStatusTransitions = std::move(value); }
|
|
|
|
/**
|
|
* <p>A history of all of the secondary statuses that the training job has
|
|
* transitioned through.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithSecondaryStatusTransitions(const Aws::Vector<SecondaryStatusTransition>& value) { SetSecondaryStatusTransitions(value); return *this;}
|
|
|
|
/**
|
|
* <p>A history of all of the secondary statuses that the training job has
|
|
* transitioned through.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithSecondaryStatusTransitions(Aws::Vector<SecondaryStatusTransition>&& value) { SetSecondaryStatusTransitions(std::move(value)); return *this;}
|
|
|
|
/**
|
|
* <p>A history of all of the secondary statuses that the training job has
|
|
* transitioned through.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddSecondaryStatusTransitions(const SecondaryStatusTransition& value) { m_secondaryStatusTransitions.push_back(value); return *this; }
|
|
|
|
/**
|
|
* <p>A history of all of the secondary statuses that the training job has
|
|
* transitioned through.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddSecondaryStatusTransitions(SecondaryStatusTransition&& value) { m_secondaryStatusTransitions.push_back(std::move(value)); return *this; }
|
|
|
|
|
|
/**
|
|
* <p>A collection of <code>MetricData</code> objects that specify the names,
|
|
* values, and dates and times that the training algorithm emitted to Amazon
|
|
* CloudWatch.</p>
|
|
*/
|
|
inline const Aws::Vector<MetricData>& GetFinalMetricDataList() const{ return m_finalMetricDataList; }
|
|
|
|
/**
|
|
* <p>A collection of <code>MetricData</code> objects that specify the names,
|
|
* values, and dates and times that the training algorithm emitted to Amazon
|
|
* CloudWatch.</p>
|
|
*/
|
|
inline void SetFinalMetricDataList(const Aws::Vector<MetricData>& value) { m_finalMetricDataList = value; }
|
|
|
|
/**
|
|
* <p>A collection of <code>MetricData</code> objects that specify the names,
|
|
* values, and dates and times that the training algorithm emitted to Amazon
|
|
* CloudWatch.</p>
|
|
*/
|
|
inline void SetFinalMetricDataList(Aws::Vector<MetricData>&& value) { m_finalMetricDataList = std::move(value); }
|
|
|
|
/**
|
|
* <p>A collection of <code>MetricData</code> objects that specify the names,
|
|
* values, and dates and times that the training algorithm emitted to Amazon
|
|
* CloudWatch.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithFinalMetricDataList(const Aws::Vector<MetricData>& value) { SetFinalMetricDataList(value); return *this;}
|
|
|
|
/**
|
|
* <p>A collection of <code>MetricData</code> objects that specify the names,
|
|
* values, and dates and times that the training algorithm emitted to Amazon
|
|
* CloudWatch.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithFinalMetricDataList(Aws::Vector<MetricData>&& value) { SetFinalMetricDataList(std::move(value)); return *this;}
|
|
|
|
/**
|
|
* <p>A collection of <code>MetricData</code> objects that specify the names,
|
|
* values, and dates and times that the training algorithm emitted to Amazon
|
|
* CloudWatch.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddFinalMetricDataList(const MetricData& value) { m_finalMetricDataList.push_back(value); return *this; }
|
|
|
|
/**
|
|
* <p>A collection of <code>MetricData</code> objects that specify the names,
|
|
* values, and dates and times that the training algorithm emitted to Amazon
|
|
* CloudWatch.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddFinalMetricDataList(MetricData&& value) { m_finalMetricDataList.push_back(std::move(value)); return *this; }
|
|
|
|
|
|
/**
|
|
* <p>If you want to allow inbound or outbound network calls, except for calls
|
|
* between peers within a training cluster for distributed training, choose
|
|
* <code>True</code>. If you enable network isolation for training jobs that are
|
|
* configured to use a VPC, Amazon SageMaker downloads and uploads customer data
|
|
* and model artifacts through the specified VPC, but the training container does
|
|
* not have network access.</p>
|
|
*/
|
|
inline bool GetEnableNetworkIsolation() const{ return m_enableNetworkIsolation; }
|
|
|
|
/**
|
|
* <p>If you want to allow inbound or outbound network calls, except for calls
|
|
* between peers within a training cluster for distributed training, choose
|
|
* <code>True</code>. If you enable network isolation for training jobs that are
|
|
* configured to use a VPC, Amazon SageMaker downloads and uploads customer data
|
|
* and model artifacts through the specified VPC, but the training container does
|
|
* not have network access.</p>
|
|
*/
|
|
inline void SetEnableNetworkIsolation(bool value) { m_enableNetworkIsolation = value; }
|
|
|
|
/**
|
|
* <p>If you want to allow inbound or outbound network calls, except for calls
|
|
* between peers within a training cluster for distributed training, choose
|
|
* <code>True</code>. If you enable network isolation for training jobs that are
|
|
* configured to use a VPC, Amazon SageMaker downloads and uploads customer data
|
|
* and model artifacts through the specified VPC, but the training container does
|
|
* not have network access.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithEnableNetworkIsolation(bool value) { SetEnableNetworkIsolation(value); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>To encrypt all communications between ML compute instances in distributed
|
|
* training, choose <code>True</code>. 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.</p>
|
|
*/
|
|
inline bool GetEnableInterContainerTrafficEncryption() const{ return m_enableInterContainerTrafficEncryption; }
|
|
|
|
/**
|
|
* <p>To encrypt all communications between ML compute instances in distributed
|
|
* training, choose <code>True</code>. 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.</p>
|
|
*/
|
|
inline void SetEnableInterContainerTrafficEncryption(bool value) { m_enableInterContainerTrafficEncryption = value; }
|
|
|
|
/**
|
|
* <p>To encrypt all communications between ML compute instances in distributed
|
|
* training, choose <code>True</code>. 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.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithEnableInterContainerTrafficEncryption(bool value) { SetEnableInterContainerTrafficEncryption(value); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>A Boolean indicating whether managed spot training is enabled
|
|
* (<code>True</code>) or not (<code>False</code>).</p>
|
|
*/
|
|
inline bool GetEnableManagedSpotTraining() const{ return m_enableManagedSpotTraining; }
|
|
|
|
/**
|
|
* <p>A Boolean indicating whether managed spot training is enabled
|
|
* (<code>True</code>) or not (<code>False</code>).</p>
|
|
*/
|
|
inline void SetEnableManagedSpotTraining(bool value) { m_enableManagedSpotTraining = value; }
|
|
|
|
/**
|
|
* <p>A Boolean indicating whether managed spot training is enabled
|
|
* (<code>True</code>) or not (<code>False</code>).</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithEnableManagedSpotTraining(bool value) { SetEnableManagedSpotTraining(value); return *this;}
|
|
|
|
|
|
|
|
inline const CheckpointConfig& GetCheckpointConfig() const{ return m_checkpointConfig; }
|
|
|
|
|
|
inline void SetCheckpointConfig(const CheckpointConfig& value) { m_checkpointConfig = value; }
|
|
|
|
|
|
inline void SetCheckpointConfig(CheckpointConfig&& value) { m_checkpointConfig = std::move(value); }
|
|
|
|
|
|
inline DescribeTrainingJobResult& WithCheckpointConfig(const CheckpointConfig& value) { SetCheckpointConfig(value); return *this;}
|
|
|
|
|
|
inline DescribeTrainingJobResult& WithCheckpointConfig(CheckpointConfig&& value) { SetCheckpointConfig(std::move(value)); return *this;}
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/**
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* <p>The training time in seconds.</p>
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*/
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inline int GetTrainingTimeInSeconds() const{ return m_trainingTimeInSeconds; }
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/**
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* <p>The training time in seconds.</p>
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*/
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inline void SetTrainingTimeInSeconds(int value) { m_trainingTimeInSeconds = value; }
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/**
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* <p>The training time in seconds.</p>
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*/
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inline DescribeTrainingJobResult& WithTrainingTimeInSeconds(int value) { SetTrainingTimeInSeconds(value); return *this;}
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/**
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* <p>The billable time in seconds.</p> <p>You can calculate the savings from using
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* managed spot training using the formula <code>(1 - BillableTimeInSeconds /
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* TrainingTimeInSeconds) * 100</code>. For example, if
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* <code>BillableTimeInSeconds</code> is 100 and <code>TrainingTimeInSeconds</code>
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* is 500, the savings is 80%.</p>
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*/
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inline int GetBillableTimeInSeconds() const{ return m_billableTimeInSeconds; }
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/**
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* <p>The billable time in seconds.</p> <p>You can calculate the savings from using
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* managed spot training using the formula <code>(1 - BillableTimeInSeconds /
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* TrainingTimeInSeconds) * 100</code>. For example, if
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* <code>BillableTimeInSeconds</code> is 100 and <code>TrainingTimeInSeconds</code>
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* is 500, the savings is 80%.</p>
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*/
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inline void SetBillableTimeInSeconds(int value) { m_billableTimeInSeconds = value; }
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/**
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* <p>The billable time in seconds.</p> <p>You can calculate the savings from using
|
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* managed spot training using the formula <code>(1 - BillableTimeInSeconds /
|
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* TrainingTimeInSeconds) * 100</code>. For example, if
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* <code>BillableTimeInSeconds</code> is 100 and <code>TrainingTimeInSeconds</code>
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* is 500, the savings is 80%.</p>
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*/
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inline DescribeTrainingJobResult& WithBillableTimeInSeconds(int value) { SetBillableTimeInSeconds(value); return *this;}
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inline const DebugHookConfig& GetDebugHookConfig() const{ return m_debugHookConfig; }
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inline void SetDebugHookConfig(const DebugHookConfig& value) { m_debugHookConfig = value; }
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inline void SetDebugHookConfig(DebugHookConfig&& value) { m_debugHookConfig = std::move(value); }
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inline DescribeTrainingJobResult& WithDebugHookConfig(const DebugHookConfig& value) { SetDebugHookConfig(value); return *this;}
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inline DescribeTrainingJobResult& WithDebugHookConfig(DebugHookConfig&& value) { SetDebugHookConfig(std::move(value)); return *this;}
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inline const ExperimentConfig& GetExperimentConfig() const{ return m_experimentConfig; }
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inline void SetExperimentConfig(const ExperimentConfig& value) { m_experimentConfig = value; }
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inline void SetExperimentConfig(ExperimentConfig&& value) { m_experimentConfig = std::move(value); }
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inline DescribeTrainingJobResult& WithExperimentConfig(const ExperimentConfig& value) { SetExperimentConfig(value); return *this;}
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inline DescribeTrainingJobResult& WithExperimentConfig(ExperimentConfig&& value) { SetExperimentConfig(std::move(value)); return *this;}
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/**
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* <p>Configuration information for debugging rules.</p>
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*/
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inline const Aws::Vector<DebugRuleConfiguration>& GetDebugRuleConfigurations() const{ return m_debugRuleConfigurations; }
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/**
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* <p>Configuration information for debugging rules.</p>
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*/
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inline void SetDebugRuleConfigurations(const Aws::Vector<DebugRuleConfiguration>& value) { m_debugRuleConfigurations = value; }
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/**
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* <p>Configuration information for debugging rules.</p>
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*/
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inline void SetDebugRuleConfigurations(Aws::Vector<DebugRuleConfiguration>&& value) { m_debugRuleConfigurations = std::move(value); }
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/**
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* <p>Configuration information for debugging rules.</p>
|
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*/
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inline DescribeTrainingJobResult& WithDebugRuleConfigurations(const Aws::Vector<DebugRuleConfiguration>& value) { SetDebugRuleConfigurations(value); return *this;}
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/**
|
|
* <p>Configuration information for debugging rules.</p>
|
|
*/
|
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inline DescribeTrainingJobResult& WithDebugRuleConfigurations(Aws::Vector<DebugRuleConfiguration>&& value) { SetDebugRuleConfigurations(std::move(value)); return *this;}
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/**
|
|
* <p>Configuration information for debugging rules.</p>
|
|
*/
|
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inline DescribeTrainingJobResult& AddDebugRuleConfigurations(const DebugRuleConfiguration& value) { m_debugRuleConfigurations.push_back(value); return *this; }
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|
|
/**
|
|
* <p>Configuration information for debugging rules.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddDebugRuleConfigurations(DebugRuleConfiguration&& value) { m_debugRuleConfigurations.push_back(std::move(value)); return *this; }
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inline const TensorBoardOutputConfig& GetTensorBoardOutputConfig() const{ return m_tensorBoardOutputConfig; }
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inline void SetTensorBoardOutputConfig(const TensorBoardOutputConfig& value) { m_tensorBoardOutputConfig = value; }
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inline void SetTensorBoardOutputConfig(TensorBoardOutputConfig&& value) { m_tensorBoardOutputConfig = std::move(value); }
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inline DescribeTrainingJobResult& WithTensorBoardOutputConfig(const TensorBoardOutputConfig& value) { SetTensorBoardOutputConfig(value); return *this;}
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inline DescribeTrainingJobResult& WithTensorBoardOutputConfig(TensorBoardOutputConfig&& value) { SetTensorBoardOutputConfig(std::move(value)); return *this;}
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|
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|
|
/**
|
|
* <p>Status about the debug rule evaluation.</p>
|
|
*/
|
|
inline const Aws::Vector<DebugRuleEvaluationStatus>& GetDebugRuleEvaluationStatuses() const{ return m_debugRuleEvaluationStatuses; }
|
|
|
|
/**
|
|
* <p>Status about the debug rule evaluation.</p>
|
|
*/
|
|
inline void SetDebugRuleEvaluationStatuses(const Aws::Vector<DebugRuleEvaluationStatus>& value) { m_debugRuleEvaluationStatuses = value; }
|
|
|
|
/**
|
|
* <p>Status about the debug rule evaluation.</p>
|
|
*/
|
|
inline void SetDebugRuleEvaluationStatuses(Aws::Vector<DebugRuleEvaluationStatus>&& value) { m_debugRuleEvaluationStatuses = std::move(value); }
|
|
|
|
/**
|
|
* <p>Status about the debug rule evaluation.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithDebugRuleEvaluationStatuses(const Aws::Vector<DebugRuleEvaluationStatus>& value) { SetDebugRuleEvaluationStatuses(value); return *this;}
|
|
|
|
/**
|
|
* <p>Status about the debug rule evaluation.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& WithDebugRuleEvaluationStatuses(Aws::Vector<DebugRuleEvaluationStatus>&& value) { SetDebugRuleEvaluationStatuses(std::move(value)); return *this;}
|
|
|
|
/**
|
|
* <p>Status about the debug rule evaluation.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddDebugRuleEvaluationStatuses(const DebugRuleEvaluationStatus& value) { m_debugRuleEvaluationStatuses.push_back(value); return *this; }
|
|
|
|
/**
|
|
* <p>Status about the debug rule evaluation.</p>
|
|
*/
|
|
inline DescribeTrainingJobResult& AddDebugRuleEvaluationStatuses(DebugRuleEvaluationStatus&& value) { m_debugRuleEvaluationStatuses.push_back(std::move(value)); return *this; }
|
|
|
|
private:
|
|
|
|
Aws::String m_trainingJobName;
|
|
|
|
Aws::String m_trainingJobArn;
|
|
|
|
Aws::String m_tuningJobArn;
|
|
|
|
Aws::String m_labelingJobArn;
|
|
|
|
Aws::String m_autoMLJobArn;
|
|
|
|
ModelArtifacts m_modelArtifacts;
|
|
|
|
TrainingJobStatus m_trainingJobStatus;
|
|
|
|
SecondaryStatus m_secondaryStatus;
|
|
|
|
Aws::String m_failureReason;
|
|
|
|
Aws::Map<Aws::String, Aws::String> m_hyperParameters;
|
|
|
|
AlgorithmSpecification m_algorithmSpecification;
|
|
|
|
Aws::String m_roleArn;
|
|
|
|
Aws::Vector<Channel> m_inputDataConfig;
|
|
|
|
OutputDataConfig m_outputDataConfig;
|
|
|
|
ResourceConfig m_resourceConfig;
|
|
|
|
VpcConfig m_vpcConfig;
|
|
|
|
StoppingCondition m_stoppingCondition;
|
|
|
|
Aws::Utils::DateTime m_creationTime;
|
|
|
|
Aws::Utils::DateTime m_trainingStartTime;
|
|
|
|
Aws::Utils::DateTime m_trainingEndTime;
|
|
|
|
Aws::Utils::DateTime m_lastModifiedTime;
|
|
|
|
Aws::Vector<SecondaryStatusTransition> m_secondaryStatusTransitions;
|
|
|
|
Aws::Vector<MetricData> m_finalMetricDataList;
|
|
|
|
bool m_enableNetworkIsolation;
|
|
|
|
bool m_enableInterContainerTrafficEncryption;
|
|
|
|
bool m_enableManagedSpotTraining;
|
|
|
|
CheckpointConfig m_checkpointConfig;
|
|
|
|
int m_trainingTimeInSeconds;
|
|
|
|
int m_billableTimeInSeconds;
|
|
|
|
DebugHookConfig m_debugHookConfig;
|
|
|
|
ExperimentConfig m_experimentConfig;
|
|
|
|
Aws::Vector<DebugRuleConfiguration> m_debugRuleConfigurations;
|
|
|
|
TensorBoardOutputConfig m_tensorBoardOutputConfig;
|
|
|
|
Aws::Vector<DebugRuleEvaluationStatus> m_debugRuleEvaluationStatuses;
|
|
};
|
|
|
|
} // namespace Model
|
|
} // namespace SageMaker
|
|
} // namespace Aws
|