dcgan.py 文件源码

def create_objectives(self, deterministic=False):
    # load network
    l_g, l_d = self.network

    # load ouput
    g      = lasagne.layers.get_output(l_g, deterministic=deterministic)
    d_real = lasagne.layers.get_output(l_d, deterministic=deterministic)
    d_fake = lasagne.layers.get_output(l_d, g, deterministic=deterministic)

    # define loss
    loss_g = lasagne.objectives.binary_crossentropy(d_fake, 1).mean()
    loss_d = ( lasagne.objectives.binary_crossentropy(d_real, 1)
             + lasagne.objectives.binary_crossentropy(d_fake, 0) ).mean()

    # compute and store discriminator probabilities
    p_real = (d_real > 0.5).mean()
    p_fake = (d_fake < 0.5).mean()

    return loss_g, loss_d, p_real, p_fake