public double[] Forward(double[] x_values, bool debug = false)
{
if (debug)
{
Console.WriteLine("input:" + x_values[0]);
}
// preliminary values
var hSums = new double[_numHidden]; // scratch array
var oSums = new double[_numOutput];
for (int i = 0; i < _numInput; i++)
{
_inputs[i] = x_values[i]; // copy independent vars into input nodes
}
for (int j = 0; j < _numHidden; j++)
for (int i = 0; i < _numInput; i++)
{
hSums[j] += _inputs[i] * ih_weights[i, j]; // full-connect network
}
// add the bias
for (int j = 0; j < _numHidden; j++)
hSums[j] += _hBiases[j];
if (debug)
{
Console.WriteLine("hSum");
Helper.ShowVector(hSums, 8, 12, true);
}
//activation
for (int j = 0; j < _numHidden; j++)
{
_hiddens[j] = Activation.HyperTan(hSums[j]);
}
if (debug)
{
Console.WriteLine("after activation hsum");
Helper.ShowVector(hSums, 8, 12, true);
}
for (int k = 0; k < _numOutput; k++)
for (int j = 0; j < _numHidden; j++)
{
oSums[k] += _hiddens[j] * _hoWeights[j, k];
}
for (int k = 0; k < _numOutput; k++)
{
oSums[k] += _oBiases[k];
}
if (debug)
{
Console.WriteLine("after add biases oSum");
Helper.ShowVector(oSums, 8, 12, true);
}
// no softmax activation in regression applied. Just copy
Array.Copy(oSums, _outputs, _outputs.Length);
double[] resRes = new double[_numOutput];
Array.Copy(_outputs, resRes, resRes.Length); // copy res_res to output[]
if (debug)
{
Console.WriteLine("output:" + _outputs[0]);
}
return resRes;
}
public override double Differentiate(double x, double a)
{
return(x < 0 ? Activation.ELU(x, a) + a : 1);
//throw new System.NotImplementedException();
}
public override double[] Calculate(ref double[] LayerSum, double a = 0)
{
return(Activation.Softmax(LayerSum));
// throw new NotImplementedException();
}
public override double Differentiate(double x, double a = 0)
{
return(Activation.Sigmoid(x) * (1 - Activation.Sigmoid(x)));
//throw new NotImplementedException();
}
