class_docstr: Vocab class.
  
  Parameters
  ----------
  lower_case : boolean
      Specify whether to lowercase text, default: ``True``.
  tokenizer: function, optional
      Word tokenization function, default: nltk.tokenize.word_tokenize.
  
  Examples
  -------
  >>> word_vocab = Vocab()
  >>> word_vocab.build_vocab({'i': 10, 'like': 5, 'nlp': 3})
  >>> print(word_vocab.get_vocab_size())
code: def _add_words(self, words):
      # words: a list of str
      for word in words:
          if self.lower_case:
              word = word.lower()
  
          if word not in self.word2index:
              self.word2index[word] = len(self.index2word)
              self.index2word.append(word)
      assert len(self.word2index) == len(self.index2word)
  
imports: import os
  import pickle
  import re
  import warnings
  from collections import Counter
  from functools import lru_cache
  import numpy
  import torch
  from nltk.tokenize import word_tokenize
  from torchtext.vocab import GloVe, Vectors
  from .None import constants
label_desc: Use image node_id 3 for calling the Vocab obj's underlying member method code with example usage: obj._add_words(words) without return types