/// <summary>
/// Creates a graph learning context
/// </summary>
/// <param name="learningRate">Initial learning rate</param>
/// <param name="batchSize">Mini batch size</param>
/// <param name="trainingErrorCalculation">How to calculate the training error</param>
/// <param name="deferUpdates">True to defer updates (used when training recurrent neural networks)</param>
/// <returns></returns>
public ILearningContext CreateLearningContext(float learningRate, int batchSize,
TrainingErrorCalculation trainingErrorCalculation = TrainingErrorCalculation.Fast,
bool deferUpdates = false)
{
return(new LearningContext(LinearAlgebraProvider, learningRate, batchSize,
trainingErrorCalculation, deferUpdates));
}
/// <summary>
/// Creates a graph training engine
/// </summary>
/// <param name="dataSource">Data source with training data</param>
/// <param name="learningRate">Initial learning rate</param>
/// <param name="batchSize">Mini batch size</param>
/// <param name="trainingErrorCalculation">How to calculate the training error</param>
/// <returns></returns>
public IGraphTrainingEngine CreateTrainingEngine(IDataSource dataSource,
float learningRate = 0.1f, int batchSize = 128,
TrainingErrorCalculation trainingErrorCalculation = TrainingErrorCalculation.Fast)
{
var learningContext = new LearningContext(LinearAlgebraProvider, learningRate, batchSize,
trainingErrorCalculation, dataSource.IsSequential);
return(new TrainingEngine(LinearAlgebraProvider, dataSource, learningContext, null));
}
/// <summary>
/// Creates a graph training engine
/// </summary>
/// <param name="dataSource">Data source with training data</param>
/// <param name="graph">The serialised graph to execute</param>
/// <param name="trainingRate">Initial learning rate</param>
/// <param name="batchSize">Mini batch size</param>
/// <param name="trainingErrorCalculation">How to calculate the training error</param>
/// <returns></returns>
public IGraphTrainingEngine CreateTrainingEngine(IDataSource dataSource,
Models.ExecutionGraph graph, float trainingRate = 0.1f, int batchSize = 128,
TrainingErrorCalculation trainingErrorCalculation = TrainingErrorCalculation.Fast)
{
var learningContext = new LearningContext(LinearAlgebraProvider, trainingRate, batchSize,
trainingErrorCalculation, dataSource.IsSequential);
var input = this.CreateFrom(graph);
return(new TrainingEngine(LinearAlgebraProvider, dataSource, learningContext, input));
}
