def _build_network(self):
self.X = Parameter(is_placeholder=True, name="X")
self.Y = Parameter(is_placeholder=True, name="Y")
prev_inp = self.X
prev_shape = self.inp_shape
for idx, num_units in enumerate(self.hidden_layers):
W = Parameter(np.random.random((prev_shape, num_units)),
requires_grad=True,
name="W" + str(idx + 1))
B = Parameter(np.zeros((num_units, )),
requires_grad=True,
name="B" + str(idx + 1))
if idx == len(self.hidden_layers) - 1:
out = Node.Add(Node.Mul(prev_inp, W), B)
out = Node.SoftmaxCrossEnt(out, self.Y)
else:
out = Node.ReLU(Node.Add(Node.Mul(prev_inp, W), B))
prev_inp = out
prev_shape = num_units
self.loss = out
