public GruLayer(int xSize, int hSize,
IMatrixInitializer <T> linearWeightInitializer,
IMatrixInitializer <T> hiddenWeightInitializer,
IMatrixInitializer <T> biasInitializer)
{
_hSize = hSize;
_wxh = new NeuroWeight <T>(linearWeightInitializer.CreateMatrix(hSize, xSize));
_wxr = new NeuroWeight <T>(linearWeightInitializer.CreateMatrix(hSize, xSize));
_wxz = new NeuroWeight <T>(linearWeightInitializer.CreateMatrix(hSize, xSize));
_whh = new NeuroWeight <T>(hiddenWeightInitializer.CreateMatrix(hSize, hSize));
_whr = new NeuroWeight <T>(hiddenWeightInitializer.CreateMatrix(hSize, hSize));
_whz = new NeuroWeight <T>(hiddenWeightInitializer.CreateMatrix(hSize, hSize));
_bxh = new NeuroWeight <T>(biasInitializer.CreateMatrix(hSize, 1));
_bxr = new NeuroWeight <T>(biasInitializer.CreateMatrix(hSize, 1));
_bxz = new NeuroWeight <T>(biasInitializer.CreateMatrix(hSize, 1));
_bhh = new NeuroWeight <T>(biasInitializer.CreateMatrix(hSize, 1));
_bhr = new NeuroWeight <T>(biasInitializer.CreateMatrix(hSize, 1));
_bhz = new NeuroWeight <T>(biasInitializer.CreateMatrix(hSize, 1));
ResetOptimizer();
ErrorFunction = new MeanSquareError <T>();
RegisterWeights();
}
public LinearLayer(int xSize, int ySize, IMatrixInitializer <T> matrixInitializer)
{
_weights = new NeuroWeight <T>(matrixInitializer.CreateMatrix(ySize, xSize));
_bias = new NeuroWeight <T>(matrixInitializer.CreateMatrix(ySize, 1));
ErrorFunction = new MeanSquareError <T>();
RegisterWeights(_bias, _weights);
}
