translate.py 文件源码

def decode():
  with tf.Session() as sess:
    # Create model and load parameters.
    model = create_model(sess, True)
    model.batch_size = 1  # We decode one sentence at a time.

    # Load vocabularies.
    en_vocab_path = os.path.join(FLAGS.data_dir,
                                 "vocab%d.from" % FLAGS.from_vocab_size)
    fr_vocab_path = os.path.join(FLAGS.data_dir,
                                 "vocab%d.to" % FLAGS.to_vocab_size)
    en_vocab, _ = data_utils.initialize_vocabulary(en_vocab_path)
    _, rev_fr_vocab = data_utils.initialize_vocabulary(fr_vocab_path)

    # Decode from standard input.
    sys.stdout.write("> ")
    sys.stdout.flush()
    sentence = sys.stdin.readline()
    while sentence:
      # Get token-ids for the input sentence.
      token_ids = data_utils.sentence_to_token_ids(tf.compat.as_bytes(sentence), en_vocab)
      # Which bucket does it belong to?
      bucket_id = len(_buckets) - 1
      for i, bucket in enumerate(_buckets):
        if bucket[0] >= len(token_ids):
          bucket_id = i
          break
      else:
        logging.warning("Sentence truncated: %s", sentence)

      # Get a 1-element batch to feed the sentence to the model.
      encoder_inputs, decoder_inputs, target_weights = model.get_batch(
          {bucket_id: [(token_ids, [])]}, bucket_id)
      # Get output logits for the sentence.
      _, _, output_logits = model.step(sess, encoder_inputs, decoder_inputs,
                                       target_weights, bucket_id, True)
      # This is a greedy decoder - outputs are just argmaxes of output_logits.
      outputs = [int(np.argmax(logit, axis=1)) for logit in output_logits]
      # If there is an EOS symbol in outputs, cut them at that point.
      if data_utils.EOS_ID in outputs:
        outputs = outputs[:outputs.index(data_utils.EOS_ID)]
      # Print out French sentence corresponding to outputs.
      print(" ".join([tf.compat.as_str(rev_fr_vocab[output]) for output in outputs]))
      print("> ", end="")
      sys.stdout.flush()
      sentence = sys.stdin.readline()