static void Main(string[] args)
{
FeedForward JARVIS = new FeedForward("JARVIS");
JARVIS.AddLayer(new InputLayer("Input", new int[] { 4, 1 }));
JARVIS.AddLayer(new DenseLayer("Dense1", new Identity(), 8));
JARVIS.AddLayer(new DenseLayer("Dense2", new Identity(), 6));
JARVIS.AddLayer(new DenseLayer("Output", new Identity(), 2));
JARVIS.CompileModel();
JARVIS.ShowSummary();
}
private static void Main(string[] args)
{
var activation = new Relu();
var n = new FeedForward();
n.AddLayer(new NeuronLayer(2, activation));
n.AddLayer(new NeuronLayer(3, activation));
n.AddLayer(new NeuronLayer(1, activation));
n.Construct();
var str = "";
for (int i = 0; i < n.Output.Length; i++)
{
str += n.Output[i].ToString() + "\n";
}
var inp = new MatrixFloat[] {
new MatrixFloat(new float[, ] {
{ 1, 1 }
}),
new MatrixFloat(new float[, ] {
{ 0, 1 }
}),
new MatrixFloat(new float[, ] {
{ 1, 0 }
}),
new MatrixFloat(new float[, ] {
{ 0, 0 }
}),
};
var expected = new MatrixFloat[] {
new MatrixFloat(new float[, ] {
{ 0 }
}),
new MatrixFloat(new float[, ] {
{ 1 }
}),
new MatrixFloat(new float[, ] {
{ 1 }
}),
new MatrixFloat(new float[, ] {
{ 0 }
})
};
for (int i = 0; i < 500000; i++)
{
var error = 0f;
for (int k = 0; k < 4; k++)
{
var np1 = inp[k];
for (int j = 0; j < np1.Columns; j++)
{
n.Input[j] = np1[0, j];
}
var exp = expected[k];
n.Forward();
for (int z = 0; z < exp.Columns; z++)
{
var tmp = (n.Output[z] - exp[0, z]);
error += tmp * tmp;
}
n.Backward(exp);
n.Clear();
}
Console.WriteLine(error);
}
Console.ReadKey();
}
