code: def words_to_word_ids(data=None, word_to_id=None, unk_key='UNK'):
      
      if data is None:
          raise Exception("data : list of string or byte")
      if word_to_id is None:
          raise Exception("word_to_id : a dictionary")
      # if isinstance(data[0], six.string_types):
      #     tl.logging.info(type(data[0]))
      #     # exit()
      #     tl.logging.info(data[0])
      #     tl.logging.info(word_to_id)
      #     return [word_to_id[str(word)] for word in data]
      # else:
  
      word_ids = []
      for word in data:
          if word_to_id.get(word) is not None:
              word_ids.append(word_to_id[word])
          else:
              word_ids.append(word_to_id[unk_key])
      return word_ids
docs: Convert a list of string (words) to IDs.
  
      Parameters
      ----------
      data : list of string or byte
          The context in list format
      word_to_id : a dictionary
          that maps word to ID.
      unk_key : str
          Represent the unknown words.
  
      Returns
      --------
      list of int
          A list of IDs to represent the context.
  
      Examples
      --------
      >>> words = tl.files.load_matt_mahoney_text8_dataset()
      >>> vocabulary_size = 50000
      >>> data, count, dictionary, reverse_dictionary = tl.nlp.build_words_dataset(words, vocabulary_size, True)
      >>> context = [b'hello', b'how', b'are', b'you']
      >>> ids = tl.nlp.words_to_word_ids(words, dictionary)
      >>> context = tl.nlp.word_ids_to_words(ids, reverse_dictionary)
      >>> print(ids)
      [6434, 311, 26, 207]
      >>> print(context)
      [b'hello', b'how', b'are', b'you']
  
      References
      ---------------
      - `tensorflow.models.rnn.ptb.reader <https://github.com/tensorflow/tensorflow/tree/master/tensorflow/models/rnn/ptb>`__