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MachineLearningTrainingSettings.cs
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MachineLearningTrainingSettings.cs
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// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// <auto-generated/>
#nullable disable
using System;
namespace Azure.ResourceManager.MachineLearning.Models
{
/// <summary> Training related configuration. </summary>
public partial class MachineLearningTrainingSettings
{
/// <summary> Initializes a new instance of <see cref="MachineLearningTrainingSettings"/>. </summary>
public MachineLearningTrainingSettings()
{
}
/// <summary> Initializes a new instance of <see cref="MachineLearningTrainingSettings"/>. </summary>
/// <param name="isDnnTrainingEnabled"> Enable recommendation of DNN models. </param>
/// <param name="isModelExplainabilityEnabled"> Flag to turn on explainability on best model. </param>
/// <param name="isOnnxCompatibleModelsEnabled"> Flag for enabling onnx compatible models. </param>
/// <param name="isStackEnsembleEnabled"> Enable stack ensemble run. </param>
/// <param name="isVoteEnsembleEnabled"> Enable voting ensemble run. </param>
/// <param name="ensembleModelDownloadTimeout">
/// During VotingEnsemble and StackEnsemble model generation, multiple fitted models from the previous child runs are downloaded.
/// Configure this parameter with a higher value than 300 secs, if more time is needed.
/// </param>
/// <param name="stackEnsembleSettings"> Stack ensemble settings for stack ensemble run. </param>
/// <param name="trainingMode">
/// TrainingMode mode - Setting to 'auto' is same as setting it to 'non-distributed' for now, however in the future may result in mixed mode or heuristics based mode selection. Default is 'auto'.
/// If 'Distributed' then only distributed featurization is used and distributed algorithms are chosen.
/// If 'NonDistributed' then only non distributed algorithms are chosen.
/// </param>
internal MachineLearningTrainingSettings(bool? isDnnTrainingEnabled, bool? isModelExplainabilityEnabled, bool? isOnnxCompatibleModelsEnabled, bool? isStackEnsembleEnabled, bool? isVoteEnsembleEnabled, TimeSpan? ensembleModelDownloadTimeout, MachineLearningStackEnsembleSettings stackEnsembleSettings, TrainingMode? trainingMode)
{
IsDnnTrainingEnabled = isDnnTrainingEnabled;
IsModelExplainabilityEnabled = isModelExplainabilityEnabled;
IsOnnxCompatibleModelsEnabled = isOnnxCompatibleModelsEnabled;
IsStackEnsembleEnabled = isStackEnsembleEnabled;
IsVoteEnsembleEnabled = isVoteEnsembleEnabled;
EnsembleModelDownloadTimeout = ensembleModelDownloadTimeout;
StackEnsembleSettings = stackEnsembleSettings;
TrainingMode = trainingMode;
}
/// <summary> Enable recommendation of DNN models. </summary>
public bool? IsDnnTrainingEnabled { get; set; }
/// <summary> Flag to turn on explainability on best model. </summary>
public bool? IsModelExplainabilityEnabled { get; set; }
/// <summary> Flag for enabling onnx compatible models. </summary>
public bool? IsOnnxCompatibleModelsEnabled { get; set; }
/// <summary> Enable stack ensemble run. </summary>
public bool? IsStackEnsembleEnabled { get; set; }
/// <summary> Enable voting ensemble run. </summary>
public bool? IsVoteEnsembleEnabled { get; set; }
/// <summary>
/// During VotingEnsemble and StackEnsemble model generation, multiple fitted models from the previous child runs are downloaded.
/// Configure this parameter with a higher value than 300 secs, if more time is needed.
/// </summary>
public TimeSpan? EnsembleModelDownloadTimeout { get; set; }
/// <summary> Stack ensemble settings for stack ensemble run. </summary>
public MachineLearningStackEnsembleSettings StackEnsembleSettings { get; set; }
/// <summary>
/// TrainingMode mode - Setting to 'auto' is same as setting it to 'non-distributed' for now, however in the future may result in mixed mode or heuristics based mode selection. Default is 'auto'.
/// If 'Distributed' then only distributed featurization is used and distributed algorithms are chosen.
/// If 'NonDistributed' then only non distributed algorithms are chosen.
/// </summary>
public TrainingMode? TrainingMode { get; set; }
}
}