/**
* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
* SPDX-License-Identifier: Apache-2.0.
*/
#pragma once
#include Defines how the algorithm is used for a training job.See
* Also:
AWS
* API Reference
The Amazon ECR registry path of the Docker image that contains the training * algorithm.
*/ inline const Aws::String& GetTrainingImage() const{ return m_trainingImage; } /** *The Amazon ECR registry path of the Docker image that contains the training * algorithm.
*/ inline bool TrainingImageHasBeenSet() const { return m_trainingImageHasBeenSet; } /** *The Amazon ECR registry path of the Docker image that contains the training * algorithm.
*/ inline void SetTrainingImage(const Aws::String& value) { m_trainingImageHasBeenSet = true; m_trainingImage = value; } /** *The Amazon ECR registry path of the Docker image that contains the training * algorithm.
*/ inline void SetTrainingImage(Aws::String&& value) { m_trainingImageHasBeenSet = true; m_trainingImage = std::move(value); } /** *The Amazon ECR registry path of the Docker image that contains the training * algorithm.
*/ inline void SetTrainingImage(const char* value) { m_trainingImageHasBeenSet = true; m_trainingImage.assign(value); } /** *The Amazon ECR registry path of the Docker image that contains the training * algorithm.
*/ inline TrainingSpecification& WithTrainingImage(const Aws::String& value) { SetTrainingImage(value); return *this;} /** *The Amazon ECR registry path of the Docker image that contains the training * algorithm.
*/ inline TrainingSpecification& WithTrainingImage(Aws::String&& value) { SetTrainingImage(std::move(value)); return *this;} /** *The Amazon ECR registry path of the Docker image that contains the training * algorithm.
*/ inline TrainingSpecification& WithTrainingImage(const char* value) { SetTrainingImage(value); return *this;} /** *An MD5 hash of the training algorithm that identifies the Docker image used * for training.
*/ inline const Aws::String& GetTrainingImageDigest() const{ return m_trainingImageDigest; } /** *An MD5 hash of the training algorithm that identifies the Docker image used * for training.
*/ inline bool TrainingImageDigestHasBeenSet() const { return m_trainingImageDigestHasBeenSet; } /** *An MD5 hash of the training algorithm that identifies the Docker image used * for training.
*/ inline void SetTrainingImageDigest(const Aws::String& value) { m_trainingImageDigestHasBeenSet = true; m_trainingImageDigest = value; } /** *An MD5 hash of the training algorithm that identifies the Docker image used * for training.
*/ inline void SetTrainingImageDigest(Aws::String&& value) { m_trainingImageDigestHasBeenSet = true; m_trainingImageDigest = std::move(value); } /** *An MD5 hash of the training algorithm that identifies the Docker image used * for training.
*/ inline void SetTrainingImageDigest(const char* value) { m_trainingImageDigestHasBeenSet = true; m_trainingImageDigest.assign(value); } /** *An MD5 hash of the training algorithm that identifies the Docker image used * for training.
*/ inline TrainingSpecification& WithTrainingImageDigest(const Aws::String& value) { SetTrainingImageDigest(value); return *this;} /** *An MD5 hash of the training algorithm that identifies the Docker image used * for training.
*/ inline TrainingSpecification& WithTrainingImageDigest(Aws::String&& value) { SetTrainingImageDigest(std::move(value)); return *this;} /** *An MD5 hash of the training algorithm that identifies the Docker image used * for training.
*/ inline TrainingSpecification& WithTrainingImageDigest(const char* value) { SetTrainingImageDigest(value); return *this;} /** *A list of the HyperParameterSpecification
objects, that define
* the supported hyperparameters. This is required if the algorithm supports
* automatic model tuning.>
A list of the HyperParameterSpecification
objects, that define
* the supported hyperparameters. This is required if the algorithm supports
* automatic model tuning.>
A list of the HyperParameterSpecification
objects, that define
* the supported hyperparameters. This is required if the algorithm supports
* automatic model tuning.>
A list of the HyperParameterSpecification
objects, that define
* the supported hyperparameters. This is required if the algorithm supports
* automatic model tuning.>
A list of the HyperParameterSpecification
objects, that define
* the supported hyperparameters. This is required if the algorithm supports
* automatic model tuning.>
A list of the HyperParameterSpecification
objects, that define
* the supported hyperparameters. This is required if the algorithm supports
* automatic model tuning.>
A list of the HyperParameterSpecification
objects, that define
* the supported hyperparameters. This is required if the algorithm supports
* automatic model tuning.>
A list of the HyperParameterSpecification
objects, that define
* the supported hyperparameters. This is required if the algorithm supports
* automatic model tuning.>
A list of the instance types that this algorithm can use for training.
*/ inline const Aws::VectorA list of the instance types that this algorithm can use for training.
*/ inline bool SupportedTrainingInstanceTypesHasBeenSet() const { return m_supportedTrainingInstanceTypesHasBeenSet; } /** *A list of the instance types that this algorithm can use for training.
*/ inline void SetSupportedTrainingInstanceTypes(const Aws::VectorA list of the instance types that this algorithm can use for training.
*/ inline void SetSupportedTrainingInstanceTypes(Aws::VectorA list of the instance types that this algorithm can use for training.
*/ inline TrainingSpecification& WithSupportedTrainingInstanceTypes(const Aws::VectorA list of the instance types that this algorithm can use for training.
*/ inline TrainingSpecification& WithSupportedTrainingInstanceTypes(Aws::VectorA list of the instance types that this algorithm can use for training.
*/ inline TrainingSpecification& AddSupportedTrainingInstanceTypes(const TrainingInstanceType& value) { m_supportedTrainingInstanceTypesHasBeenSet = true; m_supportedTrainingInstanceTypes.push_back(value); return *this; } /** *A list of the instance types that this algorithm can use for training.
*/ inline TrainingSpecification& AddSupportedTrainingInstanceTypes(TrainingInstanceType&& value) { m_supportedTrainingInstanceTypesHasBeenSet = true; m_supportedTrainingInstanceTypes.push_back(std::move(value)); return *this; } /** *Indicates whether the algorithm supports distributed training. If set to * false, buyers can't request more than one instance during training.
*/ inline bool GetSupportsDistributedTraining() const{ return m_supportsDistributedTraining; } /** *Indicates whether the algorithm supports distributed training. If set to * false, buyers can't request more than one instance during training.
*/ inline bool SupportsDistributedTrainingHasBeenSet() const { return m_supportsDistributedTrainingHasBeenSet; } /** *Indicates whether the algorithm supports distributed training. If set to * false, buyers can't request more than one instance during training.
*/ inline void SetSupportsDistributedTraining(bool value) { m_supportsDistributedTrainingHasBeenSet = true; m_supportsDistributedTraining = value; } /** *Indicates whether the algorithm supports distributed training. If set to * false, buyers can't request more than one instance during training.
*/ inline TrainingSpecification& WithSupportsDistributedTraining(bool value) { SetSupportsDistributedTraining(value); return *this;} /** *A list of MetricDefinition
objects, which are used for parsing
* metrics generated by the algorithm.
A list of MetricDefinition
objects, which are used for parsing
* metrics generated by the algorithm.
A list of MetricDefinition
objects, which are used for parsing
* metrics generated by the algorithm.
A list of MetricDefinition
objects, which are used for parsing
* metrics generated by the algorithm.
A list of MetricDefinition
objects, which are used for parsing
* metrics generated by the algorithm.
A list of MetricDefinition
objects, which are used for parsing
* metrics generated by the algorithm.
A list of MetricDefinition
objects, which are used for parsing
* metrics generated by the algorithm.
A list of MetricDefinition
objects, which are used for parsing
* metrics generated by the algorithm.
A list of ChannelSpecification
objects, which specify the input
* sources to be used by the algorithm.
A list of ChannelSpecification
objects, which specify the input
* sources to be used by the algorithm.
A list of ChannelSpecification
objects, which specify the input
* sources to be used by the algorithm.
A list of ChannelSpecification
objects, which specify the input
* sources to be used by the algorithm.
A list of ChannelSpecification
objects, which specify the input
* sources to be used by the algorithm.
A list of ChannelSpecification
objects, which specify the input
* sources to be used by the algorithm.
A list of ChannelSpecification
objects, which specify the input
* sources to be used by the algorithm.
A list of ChannelSpecification
objects, which specify the input
* sources to be used by the algorithm.
A list of the metrics that the algorithm emits that can be used as the * objective metric in a hyperparameter tuning job.
*/ inline const Aws::VectorA list of the metrics that the algorithm emits that can be used as the * objective metric in a hyperparameter tuning job.
*/ inline bool SupportedTuningJobObjectiveMetricsHasBeenSet() const { return m_supportedTuningJobObjectiveMetricsHasBeenSet; } /** *A list of the metrics that the algorithm emits that can be used as the * objective metric in a hyperparameter tuning job.
*/ inline void SetSupportedTuningJobObjectiveMetrics(const Aws::VectorA list of the metrics that the algorithm emits that can be used as the * objective metric in a hyperparameter tuning job.
*/ inline void SetSupportedTuningJobObjectiveMetrics(Aws::VectorA list of the metrics that the algorithm emits that can be used as the * objective metric in a hyperparameter tuning job.
*/ inline TrainingSpecification& WithSupportedTuningJobObjectiveMetrics(const Aws::VectorA list of the metrics that the algorithm emits that can be used as the * objective metric in a hyperparameter tuning job.
*/ inline TrainingSpecification& WithSupportedTuningJobObjectiveMetrics(Aws::VectorA list of the metrics that the algorithm emits that can be used as the * objective metric in a hyperparameter tuning job.
*/ inline TrainingSpecification& AddSupportedTuningJobObjectiveMetrics(const HyperParameterTuningJobObjective& value) { m_supportedTuningJobObjectiveMetricsHasBeenSet = true; m_supportedTuningJobObjectiveMetrics.push_back(value); return *this; } /** *A list of the metrics that the algorithm emits that can be used as the * objective metric in a hyperparameter tuning job.
*/ 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 = false; Aws::String m_trainingImageDigest; bool m_trainingImageDigestHasBeenSet = false; Aws::Vector