static void Main(string[] args)
{
Sequential xornet = new Sequential(
new Linear(2, 100),
new ReLU(),
new Linear(100, 1));
double[,] x = { { 0, 0 }, { 0, 1 }, { 1, 0 }, { 1, 1 } };
double[,] y = { { 0 }, { 1 }, { 1 }, { 0 } };
NDArray a_np = np.array(x);
NDArray b_np = np.array(y);
Tensor input = new Tensor(a_np);
Tensor label = new Tensor(b_np);
int epoch = 1000;
SGD optim = new SGD(xornet.parameters(), 0.05);
MSELoss mse = new MSELoss();
for (int i = 1; i <= epoch; i++)
{
Tensor output = xornet.forward(input);
Tensor loss = mse.forward(output, label);
optim.zero_grad();
loss.backward();
optim.step();
Console.WriteLine("[+] Epoch: " + i + " Loss: " + loss);
}
Tensor z = new Tensor(new NDArray(x));
Tensor outputs = xornet.forward(z);
Console.WriteLine("Result: " + outputs.data.flatten().ToString());
Console.ReadLine();
}
