public void DumpSetting()
{
Logger.WriteLine("Model File: {0}", ModelFile);
Logger.WriteLine("Hidden Layer Type: {0}", ModelType.ToString());
Logger.WriteLine("Output Layer Type: {0}", OutputLayerType.ToString());
if (ModelDirection == 0)
{
Logger.WriteLine("RNN Direction: Forward");
}
else
{
Logger.WriteLine("RNN Direction: Bi-directional");
}
Logger.WriteLine("Learning rate: {0}", LearningRate);
Logger.WriteLine("Dropout: {0}", Dropout);
Logger.WriteLine("Max Iteration: {0}", MaxIteration);
Logger.WriteLine("Hidden layers: {0}", HiddenLayerSizeList.Count);
Logger.WriteLine("RNN-CRF: {0}", IsCRFTraining);
Logger.WriteLine("SIMD: {0}, Size: {1}bits", System.Numerics.Vector.IsHardwareAccelerated,
Vector <double> .Count * sizeof(double) * 8);
Logger.WriteLine("Gradient cut-off: {0}", GradientCutoff);
if (SaveStep > 0)
{
Logger.WriteLine("Save temporary model after every {0} sentences", SaveStep);
}
}
/// <summary>
/// Выходной слой.
/// </summary>
/// <param name="inputs">Входные значения.</param>
/// <param name="type">Тип выходного слоя (по-умолчанию распознавание чисел).</param>
/// <param name="countOfNeurons">Количество нейронов.</param>
public OutputLayer(List<double> inputs, OutputLayerType type = OutputLayerType.NumberRecognizing,
int countOfNeurons = 10)
{
_inputs = inputs;
_type = type;
_countOfNeurons = countOfNeurons;
}
/// <summary>
/// Конструктор выходного слоя для распознавания чисел.
/// </summary>
/// <param name="neurons">Нейроны.</param>
/// <param name="modeType">Тип мода сети.</param>
/// <param name="type">Тип распознавания.</param>
public OutputLayer(List<Neuron> neurons, NetworkModeType modeType,
OutputLayerType type = OutputLayerType.NumberRecognizing)
{
if (!type.Equals(OutputLayerType.NumberRecognizing) &&
!modeType.Equals(NetworkModeType.Recognizing))
throw new Exception("Данный конструкто предназначен только для распознавания чисел.");
_type = type;
_layerNeurons = neurons;
}
