model.py 文件源码

def patch_discriminator(inputdisc, name="discriminator"):
    with tf.variable_scope(name):
        f = 4

        patch_input = tf.random_crop(inputdisc, [1, 70, 70, 3])
        o_c1 = layers.general_conv2d(patch_input, ndf, f, f, 2, 2,
                                     0.02, "SAME", "c1", do_norm="False",
                                     relufactor=0.2)
        o_c2 = layers.general_conv2d(o_c1, ndf * 2, f, f, 2, 2,
                                     0.02, "SAME", "c2", relufactor=0.2)
        o_c3 = layers.general_conv2d(o_c2, ndf * 4, f, f, 2, 2,
                                     0.02, "SAME", "c3", relufactor=0.2)
        o_c4 = layers.general_conv2d(o_c3, ndf * 8, f, f, 2, 2,
                                     0.02, "SAME", "c4", relufactor=0.2)
        o_c5 = layers.general_conv2d(
            o_c4, 1, f, f, 1, 1, 0.02, "SAME", "c5", do_norm=False,
            do_relu=False)

        return o_c5