444 lines
20 KiB
C
444 lines
20 KiB
C
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/**
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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/core/utils/memory/stl/AWSVector.h>
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#include <aws/sagemaker/model/HyperParameterSpecification.h>
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#include <aws/sagemaker/model/TrainingInstanceType.h>
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#include <aws/sagemaker/model/MetricDefinition.h>
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#include <aws/sagemaker/model/ChannelSpecification.h>
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#include <aws/sagemaker/model/HyperParameterTuningJobObjective.h>
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#include <utility>
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namespace Aws
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{
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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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class JsonView;
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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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/**
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* <p>Defines how the algorithm is used for a training job.</p><p><h3>See
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* Also:</h3> <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrainingSpecification">AWS
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* API Reference</a></p>
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*/
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class AWS_SAGEMAKER_API TrainingSpecification
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{
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public:
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TrainingSpecification();
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TrainingSpecification(Aws::Utils::Json::JsonView jsonValue);
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TrainingSpecification& operator=(Aws::Utils::Json::JsonView jsonValue);
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Aws::Utils::Json::JsonValue Jsonize() const;
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/**
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* <p>The Amazon ECR registry path of the Docker image that contains the training
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* algorithm.</p>
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*/
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inline const Aws::String& GetTrainingImage() const{ return m_trainingImage; }
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/**
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* <p>The Amazon ECR registry path of the Docker image that contains the training
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* algorithm.</p>
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*/
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inline bool TrainingImageHasBeenSet() const { return m_trainingImageHasBeenSet; }
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/**
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* <p>The Amazon ECR registry path of the Docker image that contains the training
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* algorithm.</p>
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*/
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inline void SetTrainingImage(const Aws::String& value) { m_trainingImageHasBeenSet = true; m_trainingImage = value; }
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/**
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* <p>The Amazon ECR registry path of the Docker image that contains the training
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* algorithm.</p>
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*/
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inline void SetTrainingImage(Aws::String&& value) { m_trainingImageHasBeenSet = true; m_trainingImage = std::move(value); }
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/**
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* <p>The Amazon ECR registry path of the Docker image that contains the training
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* algorithm.</p>
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*/
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inline void SetTrainingImage(const char* value) { m_trainingImageHasBeenSet = true; m_trainingImage.assign(value); }
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/**
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* <p>The Amazon ECR registry path of the Docker image that contains the training
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* algorithm.</p>
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*/
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inline TrainingSpecification& WithTrainingImage(const Aws::String& value) { SetTrainingImage(value); return *this;}
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/**
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* <p>The Amazon ECR registry path of the Docker image that contains the training
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* algorithm.</p>
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*/
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inline TrainingSpecification& WithTrainingImage(Aws::String&& value) { SetTrainingImage(std::move(value)); return *this;}
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/**
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* <p>The Amazon ECR registry path of the Docker image that contains the training
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* algorithm.</p>
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*/
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inline TrainingSpecification& WithTrainingImage(const char* value) { SetTrainingImage(value); return *this;}
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/**
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* <p>An MD5 hash of the training algorithm that identifies the Docker image used
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* for training.</p>
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*/
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inline const Aws::String& GetTrainingImageDigest() const{ return m_trainingImageDigest; }
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/**
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* <p>An MD5 hash of the training algorithm that identifies the Docker image used
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* for training.</p>
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*/
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inline bool TrainingImageDigestHasBeenSet() const { return m_trainingImageDigestHasBeenSet; }
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/**
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* <p>An MD5 hash of the training algorithm that identifies the Docker image used
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* for training.</p>
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*/
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inline void SetTrainingImageDigest(const Aws::String& value) { m_trainingImageDigestHasBeenSet = true; m_trainingImageDigest = value; }
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/**
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* <p>An MD5 hash of the training algorithm that identifies the Docker image used
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* for training.</p>
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*/
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inline void SetTrainingImageDigest(Aws::String&& value) { m_trainingImageDigestHasBeenSet = true; m_trainingImageDigest = std::move(value); }
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/**
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* <p>An MD5 hash of the training algorithm that identifies the Docker image used
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* for training.</p>
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*/
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inline void SetTrainingImageDigest(const char* value) { m_trainingImageDigestHasBeenSet = true; m_trainingImageDigest.assign(value); }
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/**
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* <p>An MD5 hash of the training algorithm that identifies the Docker image used
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* for training.</p>
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*/
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inline TrainingSpecification& WithTrainingImageDigest(const Aws::String& value) { SetTrainingImageDigest(value); return *this;}
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/**
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* <p>An MD5 hash of the training algorithm that identifies the Docker image used
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* for training.</p>
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*/
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inline TrainingSpecification& WithTrainingImageDigest(Aws::String&& value) { SetTrainingImageDigest(std::move(value)); return *this;}
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/**
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* <p>An MD5 hash of the training algorithm that identifies the Docker image used
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* for training.</p>
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*/
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inline TrainingSpecification& WithTrainingImageDigest(const char* value) { SetTrainingImageDigest(value); return *this;}
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/**
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* <p>A list of the <code>HyperParameterSpecification</code> objects, that define
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* the supported hyperparameters. This is required if the algorithm supports
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* automatic model tuning.></p>
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*/
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inline const Aws::Vector<HyperParameterSpecification>& GetSupportedHyperParameters() const{ return m_supportedHyperParameters; }
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/**
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* <p>A list of the <code>HyperParameterSpecification</code> objects, that define
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* the supported hyperparameters. This is required if the algorithm supports
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* automatic model tuning.></p>
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*/
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inline bool SupportedHyperParametersHasBeenSet() const { return m_supportedHyperParametersHasBeenSet; }
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/**
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* <p>A list of the <code>HyperParameterSpecification</code> objects, that define
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* the supported hyperparameters. This is required if the algorithm supports
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* automatic model tuning.></p>
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*/
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inline void SetSupportedHyperParameters(const Aws::Vector<HyperParameterSpecification>& value) { m_supportedHyperParametersHasBeenSet = true; m_supportedHyperParameters = value; }
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/**
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* <p>A list of the <code>HyperParameterSpecification</code> objects, that define
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* the supported hyperparameters. This is required if the algorithm supports
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* automatic model tuning.></p>
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*/
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inline void SetSupportedHyperParameters(Aws::Vector<HyperParameterSpecification>&& value) { m_supportedHyperParametersHasBeenSet = true; m_supportedHyperParameters = std::move(value); }
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/**
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* <p>A list of the <code>HyperParameterSpecification</code> objects, that define
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* the supported hyperparameters. This is required if the algorithm supports
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* automatic model tuning.></p>
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*/
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inline TrainingSpecification& WithSupportedHyperParameters(const Aws::Vector<HyperParameterSpecification>& value) { SetSupportedHyperParameters(value); return *this;}
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/**
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* <p>A list of the <code>HyperParameterSpecification</code> objects, that define
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* the supported hyperparameters. This is required if the algorithm supports
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* automatic model tuning.></p>
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*/
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inline TrainingSpecification& WithSupportedHyperParameters(Aws::Vector<HyperParameterSpecification>&& value) { SetSupportedHyperParameters(std::move(value)); return *this;}
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/**
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* <p>A list of the <code>HyperParameterSpecification</code> objects, that define
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* the supported hyperparameters. This is required if the algorithm supports
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* automatic model tuning.></p>
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*/
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inline TrainingSpecification& AddSupportedHyperParameters(const HyperParameterSpecification& value) { m_supportedHyperParametersHasBeenSet = true; m_supportedHyperParameters.push_back(value); return *this; }
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/**
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* <p>A list of the <code>HyperParameterSpecification</code> objects, that define
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* the supported hyperparameters. This is required if the algorithm supports
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* automatic model tuning.></p>
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*/
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inline TrainingSpecification& AddSupportedHyperParameters(HyperParameterSpecification&& value) { m_supportedHyperParametersHasBeenSet = true; m_supportedHyperParameters.push_back(std::move(value)); return *this; }
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/**
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* <p>A list of the instance types that this algorithm can use for training.</p>
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*/
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inline const Aws::Vector<TrainingInstanceType>& GetSupportedTrainingInstanceTypes() const{ return m_supportedTrainingInstanceTypes; }
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/**
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* <p>A list of the instance types that this algorithm can use for training.</p>
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*/
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inline bool SupportedTrainingInstanceTypesHasBeenSet() const { return m_supportedTrainingInstanceTypesHasBeenSet; }
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/**
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* <p>A list of the instance types that this algorithm can use for training.</p>
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*/
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inline void SetSupportedTrainingInstanceTypes(const Aws::Vector<TrainingInstanceType>& value) { m_supportedTrainingInstanceTypesHasBeenSet = true; m_supportedTrainingInstanceTypes = value; }
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/**
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* <p>A list of the instance types that this algorithm can use for training.</p>
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*/
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inline void SetSupportedTrainingInstanceTypes(Aws::Vector<TrainingInstanceType>&& value) { m_supportedTrainingInstanceTypesHasBeenSet = true; m_supportedTrainingInstanceTypes = std::move(value); }
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/**
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* <p>A list of the instance types that this algorithm can use for training.</p>
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*/
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inline TrainingSpecification& WithSupportedTrainingInstanceTypes(const Aws::Vector<TrainingInstanceType>& value) { SetSupportedTrainingInstanceTypes(value); return *this;}
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/**
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* <p>A list of the instance types that this algorithm can use for training.</p>
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*/
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inline TrainingSpecification& WithSupportedTrainingInstanceTypes(Aws::Vector<TrainingInstanceType>&& value) { SetSupportedTrainingInstanceTypes(std::move(value)); return *this;}
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/**
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* <p>A list of the instance types that this algorithm can use for training.</p>
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*/
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inline TrainingSpecification& AddSupportedTrainingInstanceTypes(const TrainingInstanceType& value) { m_supportedTrainingInstanceTypesHasBeenSet = true; m_supportedTrainingInstanceTypes.push_back(value); return *this; }
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/**
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* <p>A list of the instance types that this algorithm can use for training.</p>
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*/
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inline TrainingSpecification& AddSupportedTrainingInstanceTypes(TrainingInstanceType&& value) { m_supportedTrainingInstanceTypesHasBeenSet = true; m_supportedTrainingInstanceTypes.push_back(std::move(value)); return *this; }
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/**
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* <p>Indicates whether the algorithm supports distributed training. If set to
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* false, buyers can't request more than one instance during training.</p>
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*/
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inline bool GetSupportsDistributedTraining() const{ return m_supportsDistributedTraining; }
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/**
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* <p>Indicates whether the algorithm supports distributed training. If set to
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* false, buyers can't request more than one instance during training.</p>
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*/
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inline bool SupportsDistributedTrainingHasBeenSet() const { return m_supportsDistributedTrainingHasBeenSet; }
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/**
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* <p>Indicates whether the algorithm supports distributed training. If set to
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* false, buyers can't request more than one instance during training.</p>
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*/
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inline void SetSupportsDistributedTraining(bool value) { m_supportsDistributedTrainingHasBeenSet = true; m_supportsDistributedTraining = value; }
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/**
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* <p>Indicates whether the algorithm supports distributed training. If set to
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* false, buyers can't request more than one instance during training.</p>
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*/
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inline TrainingSpecification& WithSupportsDistributedTraining(bool value) { SetSupportsDistributedTraining(value); return *this;}
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/**
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* <p>A list of <code>MetricDefinition</code> objects, which are used for parsing
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* metrics generated by the algorithm.</p>
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*/
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inline const Aws::Vector<MetricDefinition>& GetMetricDefinitions() const{ return m_metricDefinitions; }
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/**
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* <p>A list of <code>MetricDefinition</code> objects, which are used for parsing
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* metrics generated by the algorithm.</p>
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*/
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inline bool MetricDefinitionsHasBeenSet() const { return m_metricDefinitionsHasBeenSet; }
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/**
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* <p>A list of <code>MetricDefinition</code> objects, which are used for parsing
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* metrics generated by the algorithm.</p>
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*/
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inline void SetMetricDefinitions(const Aws::Vector<MetricDefinition>& value) { m_metricDefinitionsHasBeenSet = true; m_metricDefinitions = value; }
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/**
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* <p>A list of <code>MetricDefinition</code> objects, which are used for parsing
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* metrics generated by the algorithm.</p>
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*/
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inline void SetMetricDefinitions(Aws::Vector<MetricDefinition>&& value) { m_metricDefinitionsHasBeenSet = true; m_metricDefinitions = std::move(value); }
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/**
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* <p>A list of <code>MetricDefinition</code> objects, which are used for parsing
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* metrics generated by the algorithm.</p>
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*/
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inline TrainingSpecification& WithMetricDefinitions(const Aws::Vector<MetricDefinition>& value) { SetMetricDefinitions(value); return *this;}
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/**
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* <p>A list of <code>MetricDefinition</code> objects, which are used for parsing
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* metrics generated by the algorithm.</p>
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*/
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inline TrainingSpecification& WithMetricDefinitions(Aws::Vector<MetricDefinition>&& value) { SetMetricDefinitions(std::move(value)); return *this;}
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/**
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* <p>A list of <code>MetricDefinition</code> objects, which are used for parsing
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* metrics generated by the algorithm.</p>
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*/
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inline TrainingSpecification& AddMetricDefinitions(const MetricDefinition& value) { m_metricDefinitionsHasBeenSet = true; m_metricDefinitions.push_back(value); return *this; }
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/**
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* <p>A list of <code>MetricDefinition</code> objects, which are used for parsing
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* metrics generated by the algorithm.</p>
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*/
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inline TrainingSpecification& AddMetricDefinitions(MetricDefinition&& value) { m_metricDefinitionsHasBeenSet = true; m_metricDefinitions.push_back(std::move(value)); return *this; }
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/**
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* <p>A list of <code>ChannelSpecification</code> objects, which specify the input
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* sources to be used by the algorithm.</p>
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*/
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inline const Aws::Vector<ChannelSpecification>& GetTrainingChannels() const{ return m_trainingChannels; }
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/**
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* <p>A list of <code>ChannelSpecification</code> objects, which specify the input
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* sources to be used by the algorithm.</p>
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*/
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inline bool TrainingChannelsHasBeenSet() const { return m_trainingChannelsHasBeenSet; }
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/**
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* <p>A list of <code>ChannelSpecification</code> objects, which specify the input
|
|||
|
|
* sources to be used by the algorithm.</p>
|
|||
|
|
*/
|
|||
|
|
inline void SetTrainingChannels(const Aws::Vector<ChannelSpecification>& value) { m_trainingChannelsHasBeenSet = true; m_trainingChannels = value; }
|
|||
|
|
|
|||
|
|
/**
|
|||
|
|
* <p>A list of <code>ChannelSpecification</code> objects, which specify the input
|
|||
|
|
* sources to be used by the algorithm.</p>
|
|||
|
|
*/
|
|||
|
|
inline void SetTrainingChannels(Aws::Vector<ChannelSpecification>&& value) { m_trainingChannelsHasBeenSet = true; m_trainingChannels = std::move(value); }
|
|||
|
|
|
|||
|
|
/**
|
|||
|
|
* <p>A list of <code>ChannelSpecification</code> objects, which specify the input
|
|||
|
|
* sources to be used by the algorithm.</p>
|
|||
|
|
*/
|
|||
|
|
inline TrainingSpecification& WithTrainingChannels(const Aws::Vector<ChannelSpecification>& value) { SetTrainingChannels(value); return *this;}
|
|||
|
|
|
|||
|
|
/**
|
|||
|
|
* <p>A list of <code>ChannelSpecification</code> objects, which specify the input
|
|||
|
|
* sources to be used by the algorithm.</p>
|
|||
|
|
*/
|
|||
|
|
inline TrainingSpecification& WithTrainingChannels(Aws::Vector<ChannelSpecification>&& value) { SetTrainingChannels(std::move(value)); return *this;}
|
|||
|
|
|
|||
|
|
/**
|
|||
|
|
* <p>A list of <code>ChannelSpecification</code> objects, which specify the input
|
|||
|
|
* sources to be used by the algorithm.</p>
|
|||
|
|
*/
|
|||
|
|
inline TrainingSpecification& AddTrainingChannels(const ChannelSpecification& value) { m_trainingChannelsHasBeenSet = true; m_trainingChannels.push_back(value); return *this; }
|
|||
|
|
|
|||
|
|
/**
|
|||
|
|
* <p>A list of <code>ChannelSpecification</code> objects, which specify the input
|
|||
|
|
* sources to be used by the algorithm.</p>
|
|||
|
|
*/
|
|||
|
|
inline TrainingSpecification& AddTrainingChannels(ChannelSpecification&& value) { m_trainingChannelsHasBeenSet = true; m_trainingChannels.push_back(std::move(value)); return *this; }
|
|||
|
|
|
|||
|
|
|
|||
|
|
/**
|
|||
|
|
* <p>A list of the metrics that the algorithm emits that can be used as the
|
|||
|
|
* objective metric in a hyperparameter tuning job.</p>
|
|||
|
|
*/
|
|||
|
|
inline const Aws::Vector<HyperParameterTuningJobObjective>& GetSupportedTuningJobObjectiveMetrics() const{ return m_supportedTuningJobObjectiveMetrics; }
|
|||
|
|
|
|||
|
|
/**
|
|||
|
|
* <p>A list of the metrics that the algorithm emits that can be used as the
|
|||
|
|
* objective metric in a hyperparameter tuning job.</p>
|
|||
|
|
*/
|
|||
|
|
inline bool SupportedTuningJobObjectiveMetricsHasBeenSet() const { return m_supportedTuningJobObjectiveMetricsHasBeenSet; }
|
|||
|
|
|
|||
|
|
/**
|
|||
|
|
* <p>A list of the metrics that the algorithm emits that can be used as the
|
|||
|
|
* objective metric in a hyperparameter tuning job.</p>
|
|||
|
|
*/
|
|||
|
|
inline void SetSupportedTuningJobObjectiveMetrics(const Aws::Vector<HyperParameterTuningJobObjective>& value) { m_supportedTuningJobObjectiveMetricsHasBeenSet = true; m_supportedTuningJobObjectiveMetrics = value; }
|
|||
|
|
|
|||
|
|
/**
|
|||
|
|
* <p>A list of the metrics that the algorithm emits that can be used as the
|
|||
|
|
* objective metric in a hyperparameter tuning job.</p>
|
|||
|
|
*/
|
|||
|
|
inline void SetSupportedTuningJobObjectiveMetrics(Aws::Vector<HyperParameterTuningJobObjective>&& value) { m_supportedTuningJobObjectiveMetricsHasBeenSet = true; m_supportedTuningJobObjectiveMetrics = std::move(value); }
|
|||
|
|
|
|||
|
|
/**
|
|||
|
|
* <p>A list of the metrics that the algorithm emits that can be used as the
|
|||
|
|
* objective metric in a hyperparameter tuning job.</p>
|
|||
|
|
*/
|
|||
|
|
inline TrainingSpecification& WithSupportedTuningJobObjectiveMetrics(const Aws::Vector<HyperParameterTuningJobObjective>& value) { SetSupportedTuningJobObjectiveMetrics(value); return *this;}
|
|||
|
|
|
|||
|
|
/**
|
|||
|
|
* <p>A list of the metrics that the algorithm emits that can be used as the
|
|||
|
|
* objective metric in a hyperparameter tuning job.</p>
|
|||
|
|
*/
|
|||
|
|
inline TrainingSpecification& WithSupportedTuningJobObjectiveMetrics(Aws::Vector<HyperParameterTuningJobObjective>&& value) { SetSupportedTuningJobObjectiveMetrics(std::move(value)); return *this;}
|
|||
|
|
|
|||
|
|
/**
|
|||
|
|
* <p>A list of the metrics that the algorithm emits that can be used as the
|
|||
|
|
* objective metric in a hyperparameter tuning job.</p>
|
|||
|
|
*/
|
|||
|
|
inline TrainingSpecification& AddSupportedTuningJobObjectiveMetrics(const HyperParameterTuningJobObjective& value) { m_supportedTuningJobObjectiveMetricsHasBeenSet = true; m_supportedTuningJobObjectiveMetrics.push_back(value); return *this; }
|
|||
|
|
|
|||
|
|
/**
|
|||
|
|
* <p>A list of the metrics that the algorithm emits that can be used as the
|
|||
|
|
* objective metric in a hyperparameter tuning job.</p>
|
|||
|
|
*/
|
|||
|
|
inline TrainingSpecification& AddSupportedTuningJobObjectiveMetrics(HyperParameterTuningJobObjective&& value) { m_supportedTuningJobObjectiveMetricsHasBeenSet = true; m_supportedTuningJobObjectiveMetrics.push_back(std::move(value)); return *this; }
|
|||
|
|
|
|||
|
|
private:
|
|||
|
|
|
|||
|
|
Aws::String m_trainingImage;
|
|||
|
|
bool m_trainingImageHasBeenSet;
|
|||
|
|
|
|||
|
|
Aws::String m_trainingImageDigest;
|
|||
|
|
bool m_trainingImageDigestHasBeenSet;
|
|||
|
|
|
|||
|
|
Aws::Vector<HyperParameterSpecification> m_supportedHyperParameters;
|
|||
|
|
bool m_supportedHyperParametersHasBeenSet;
|
|||
|
|
|
|||
|
|
Aws::Vector<TrainingInstanceType> m_supportedTrainingInstanceTypes;
|
|||
|
|
bool m_supportedTrainingInstanceTypesHasBeenSet;
|
|||
|
|
|
|||
|
|
bool m_supportsDistributedTraining;
|
|||
|
|
bool m_supportsDistributedTrainingHasBeenSet;
|
|||
|
|
|
|||
|
|
Aws::Vector<MetricDefinition> m_metricDefinitions;
|
|||
|
|
bool m_metricDefinitionsHasBeenSet;
|
|||
|
|
|
|||
|
|
Aws::Vector<ChannelSpecification> m_trainingChannels;
|
|||
|
|
bool m_trainingChannelsHasBeenSet;
|
|||
|
|
|
|||
|
|
Aws::Vector<HyperParameterTuningJobObjective> m_supportedTuningJobObjectiveMetrics;
|
|||
|
|
bool m_supportedTuningJobObjectiveMetricsHasBeenSet;
|
|||
|
|
};
|
|||
|
|
|
|||
|
|
} // namespace Model
|
|||
|
|
} // namespace SageMaker
|
|||
|
|
} // namespace Aws
|