public NDArray ForwardPass(NDArray input)
{
//input has size numDims x inputFeats
//output has size numDims x outputFeats
//weights has size inputFeats x outputFeats
//TODO create weights, create biases,
//number of input feats
int num_input = input.shape[1];
int num_hidden = 16;
int num_output = 1;
var sigmoid = new Sigmoid();
var tanh = new Tanh();
var fc1 = new Linear(num_input, num_hidden);
var x = fc1.Apply(input);
x = tanh.Apply(x);
var fc2 = new Linear(num_hidden, num_hidden);
x = fc2.Apply(x);
x = tanh.Apply(x);
var fc3 = new Linear(num_hidden, num_output);
x = fc3.Apply(x);
x = sigmoid.Apply(x);
return(x);
}
public NDArray ForwardPass(NDArray input)
{
var x = input;
var tanh = new Tanh();
var sigmoid = new Sigmoid();
for (int i = 0; i < layers.Count - 1; i++)
{
x = layers[i].Apply(x);
x = tanh.Apply(x);
}
//final layer needs to be sigmoid so output in range (0, 1)
x = layers[layers.Count - 1].Apply(x);
x = sigmoid.Apply(x);
return(x);
}