code: def _build_vocab(filename, vocab_path, vocab_size):
    
    data = _read_words(filename)
    counter = collections.Counter(data)
    count_pairs = sorted(counter.items(), key=lambda x: (-x[1], x[0]))
    words, _ = list(zip(*count_pairs))
    words = words[:vocab_size]
    with open(vocab_path, "w") as f:
      f.write("\n".join(words))
docs: Reads a file to build a vocabulary of `vocab_size` most common words.
  
     The vocabulary is sorted by occurrence count and has one word per line.
     Originally from:
     https://github.com/tensorflow/models/blob/master/tutorials/rnn/ptb/reader.py
  
    Args:
      filename: file to read list of words from.
      vocab_path: path where to save the vocabulary.
      vocab_size: size of the vocabulary to generate.