code: def _words_to_token(self, words):
      words = [
          self.word_to_token[word]
          for word in words
          if word in self.word_to_token
      ]
      if words:
          we = self._zero_pad_tensor_token(
              th.LongTensor(words), self.max_words
          )
          return we
      else:
          return th.zeros(self.max_words).long()
  
imports: import torch
  import torch.nn.functional
  import torch.nn
  import os
  import numpy
  import re
label_desc: Use image node_id 4 for calling the Sentence_Embedding obj's underlying member method code with example usage: obj._words_to_token(words) and returns: we, th