Using cross entropy to calculate loss function

loss.py

def calculate_loss(self, x, y):
    assert len(x) == len(y)
    output = Softmax()
    layers = self.forward_propagation(x)
    loss = 0.0
    for i, layer in enumerate(layers):
        loss += output.loss(layer.mulv, y[i])
    return loss / float(len(y))

def calculate_total_loss(self, X, Y):
    loss = 0.0
    for i in range(len(Y)):
        loss += self.calculate_loss(X[i], Y[i])
    return loss / float(len(Y))