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我正在尝试创建由以下函数创建的张量的检查点,但我的时间很艰难(Tensorflow 1.x)。泡菜不起作用。

    def _create_discriminator(self, x, train=True, reuse=False, name="discriminator"):
        with tf.variable_scope(name) as scope:
            if reuse:
                scope.reuse_variables()

            h = x
            for i in range(self.num_conv_layers):
                h = lrelu(batch_norm(conv2d(h, self.num_dis_feature_maps * (2 ** i),
                                            stddev=0.02, name="d_h{}_conv".format(i)),
                                     is_training=train,
                                     scope="d_bn{}".format(i)))

            dim = h.get_shape()[1:].num_elements()
            h = tf.reshape(h, [-1, dim])
            d_bin_logits = linear(h, 1, scope='d_bin_logits')
            d_mul_logits = linear(h, self.num_gens, scope='d_mul_logits')
        return d_bin_logits, d_mul_logits
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