code: def _original_vocab(tmp_dir):
    
    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)
    ])
docs: 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