OperatorNotAllowedInGraphError：在图形执行过程中，不允许将tf.Tensor作为Python bool使用]

Question

我正在尝试执行这些功能

def evaluate(sentence):
  sentence = preprocess_sentence(sentence)

  sentence = tf.expand_dims(
      START_TOKEN + tokenizer.encode(sentence) + END_TOKEN, axis=0)

  output = tf.expand_dims(START_TOKEN, 0)

  for i in range(MAX_LENGTH):

    predictions = model(inputs=[sentence, output], training=False)

    # select the last word from the seq_len dimension
    predictions = predictions[:, -1:, :]
    predicted_id = tf.cast(tf.argmax(predictions, axis=-1), tf.int32)

    # return the result if the predicted_id is equal to the end token

    if tf.equal(predicted_id, END_TOKEN[0]):
      break
    #check()
    #tf.cond(tf.equal(predicted_id, END_TOKEN[0]),true_fn=break,false_fn=lambda: tf.no_op())


    # concatenated the predicted_id to the output which is given to the decoder
    # as its input.
    output = tf.concat([output, predicted_id], axis=-1)

  return tf.squeeze(output, axis=0)


def predict(sentence):
  prediction = evaluate(sentence)

  predicted_sentence = tokenizer.decode(
      [i for i in prediction if i < tokenizer.vocab_size])

  print('Input: {}'.format(sentence))
  print('Output: {}'.format(predicted_sentence))

  return predicted_sentence

但是，我遇到以下错误：OperatorNotAllowedInGraphError: using a `tf.Tensor` as a Python `bool` is not allowed in Graph execution. Use Eager execution or decorate this function with @tf.function.我确实知道我必须以tf.cond（）的形式重写if条件。但是，我不知道如何在张量流中写入break，我也不知道是哪种情况导致了问题，因为此笔记本中的相同功能是否正常工作？https://colab.research.google.com/github/tensorflow/examples/blob/master/community/en/transformer_chatbot.ipynb#scrollTo=_NURhwYz5AXa有帮助吗？

我正在尝试执行这些函数def评估（句子）：句子= preprocess_sentence（句子）句子= tf.expand_dims（START_TOKEN + tokenizer.encode（句子）+ END_TOKEN，axis = ...

Answer 1

笔记本中的代码有效，因为它使用的是TF 2.0，默认情况下它启用了急切执行功能。您可以使用tf.enable_eager_execution在旧版本中将其打开。