update_function.py 文件源码

def fit(self, weights, o_error, tpo):

        gradients = theano.grad(o_error, weights)

        updates = []
        for v, w, g in zip(self.t_velocity, weights, gradients):
            #gradient = T.grad(o_error ,w)
            new_velocity = tpo["momentum_rate"] * v - tpo["learn_rate"] * g
            new_weights = w + new_velocity
            updates.append((w, new_weights))
            updates.append((v, new_velocity))
        return updates



######                       Vanilla SGD
########################################