Implementing feedforward

feedforward.py

y = torch.tensor([2])
x = torch.tensor([[0.9, 0.5, 0.3]])
w = torch.tensor([[0.2, 0.1, 0.4], [0.5, 0.6, 0.1], [0.1, 0.7, 0.2]], requires_grad=True)
b = torch.tensor([[0.1, 0.2, 0.1]], requires_grad=True)

#----------- Using our functions -----------#

z = x @ w.T + b # = [[0.4500, 0.9800, 0.6000]]

sm = softmax(z) # = [[0.2590, 0.4401, 0.3009]]

ce = cross_entropy(sm, y) # = 1.2009

#----------- Equivalent Pytorch -----------#

t_ce = F.cross_entropy(z, y) # = 1.2009