train_prog = fluid.default_main_program()
startup_prog = fluid.default_startup_program()
with fluid.program_guard(train_prog, startup_prog):
    with fluid.unique_name.guard():
        lm = LanguageModel(config, config.vocab_size)
        src = layers.data(name="src",
                          shape=[-1, config.max_input_length + 2, 1],
                          dtype='int64')

        label = layers.data(name="label", shape=[-1, 1], dtype='int64')

        embedded = lm.embeder(src)
        y = fluid.layers.cast(label, dtype='float32')
        init_hidden = fluid.layers.expand(x=y, expand_times=[1, 700])
        out1, out2 = lm.net(embedded, init_hidden=init_hidden)
        forward_target = src[:, 1:, :]
        forward_target.stop_gradient = True
        backward_target = src[:, 1:, :]
        backward_target.stop_gradient = True
        loss = lm.loss(out1, out2, forward_target, backward_target, config.max_input_length + 2)
        lm.optmize(loss)
        reader = fluid.io.PyReader(feed_list=[src, label],
                                   capacity=20,
                                   iterable=True,
                                   return_list=True)
        eval_reader = fluid.io.PyReader(feed_list=[src, label],
                                        capacity=20,
                                        iterable=True,
                                        return_list=True)
infer_program = train_prog.clone(for_test=True)
exe.run(startup_prog)

============
代码如上，提示在infer_program = train_prog.clone(for_test=True)这句报错了，错误信息如标题。
我看了一下模型库的例子，好像结构是类似的，为什么会报这个错误呢？用法上有问题吗？