def _original_vocab(tmp_dir):
  """Returns a set containing the original vocabulary.

  This is important for comparing with published results.

  Args:
    tmp_dir: directory containing dataset.

  Returns:
    a set of strings
  """
  vocab_url = ("http://download.tensorflow.org/models/LM_LSTM_CNN/"
               "vocab-2016-09-10.txt")
  vocab_filename = os.path.basename(vocab_url + ".en")
  vocab_filepath = os.path.join(tmp_dir, vocab_filename)
  if not os.path.exists(vocab_filepath):
    generator_utils.maybe_download(tmp_dir, vocab_filename, vocab_url)
  return set([
      text_encoder.native_to_unicode(l.strip())
      for l in tf.gfile.Open(vocab_filepath)
  ])