Question

我尝试使用以前训练过的LSTM生成文本。我找到了一个existing solution，但问题是它抛出了一些异常。据我所知，这是因为较旧的库使用。经过一些修复后，这是我生成文本的最终功能：

def generate_text(train_path, num_sentences, rnn_data):
gen_config = get_config()
gen_config.num_steps = 1
gen_config.batch_size = 1

with tf.Graph().as_default(), tf.Session() as session:
    initializer = tf.random_uniform_initializer(-gen_config.init_scale,
                                                gen_config.init_scale)

    with tf.name_scope("Generate"):
        rnn_input = PTBInput(config=gen_config, data=rnn_data, name="GenOut")
        with tf.variable_scope("OutModel", reuse=None, initializer=initializer):
            mout = PTBModel(is_training=False, config=gen_config, input_=rnn_input)

            # Restore variables from disk. TODO: save/load trained models
            # saver = tf.train.Saver()
            # saver.restore(session, model_path)
            # print("Model restored from file " + model_path)

        print('Getting Vocabulary')
        words = reader.get_vocab(train_path)

        mout.initial_state = tf.convert_to_tensor(mout.initial_state)

        state = mout.initial_state.eval()
        # state = session.run(mout.initial_state)
        x = 0  # the id for '<eos>' from the training set //TODO: fix this
        word_input = np.matrix([[x]])  # a 2D numpy matrix

        text = ""
        count = 0
        while count < num_sentences:
            output_probs, state = session.run([mout.output_probs, mout.final_state],
                                              {mout.input.input_data: word_input,
                                               mout.initial_state: state})

            print('Output Probs = ' + str(output_probs[0]))
            x = sample(output_probs[0], 0.9)
            if words[x] == "<eos>":
                text += ".\n\n"
                count += 1
            else:
                text += " " + words[x]
            # now feed this new word as input into the next iteration
            word_input = np.matrix([[x]])
        print(text)
    return

但我得到一个例外：

FailedPreconditionError（参见上面的回溯）：尝试使用未初始化的值OutModel / softmax_b [[Node：OutModel / softmax_b / read = IdentityT = DT_FLOAT，_ class = [＆＃34; loc：@ OutModel / softmax_b＆＃34;]，_ device =＆＃34; / job：localhost / replica：0 / task：0 / CPU：0＆＃34;]]

我该如何解决？我的代码还有其他问题吗？

Answer 1

问题是一个未初始化的变量，您可以通过单独初始化所有变量或使用帮助程序printf

来解决此问题。

Tensorflow - 使用训练有素的RNN生成文本

1 个答案: