public R2Tensor ForwardPropagation(R2Tensor Input, bool norm = true)
{
R2Tensor Hidden = Tanh(R2Tensor.Add(R2Tensor.MatMul(ih_weight, Input), ih_bias));
if (!norm)
{
return(Hidden);
}
R2Tensor Output = R2Tensor.Add(R2Tensor.MatMul(ho_weight, Hidden), ho_bias);
return(Sign(Output));
}
public R2Tensor ForwardPropagation(R2Tensor Input, bool norm = true)
{
R2Tensor Hidden = Tanh(R2Tensor.Add(R2Tensor.MatMul(ih_weight, Input), ih_bias));
if (!norm)
{
return(Hidden);
}
R2Tensor Output = R2Tensor.Add(R2Tensor.MatMul(ho_weight, Hidden), ho_bias);
switch (outtype)
{
case "Basisdirection":
return(Tanh(Output));
case "Direction":
int maxind = Max(Output);
float[] tensor_out = new float[9];
for (int i = 0; i < 9; i++)
{
if (i == maxind)
{
tensor_out[i] = 1; continue;
}
tensor_out[i] = 0;
}
return(R2Tensor.ToMatrix(tensor_out, "col"));
case "Keystroke":
return(Sign(Output));
case "Debug":
return(Output);
default:
return(Output);
}
}