code: def build_vocab(self, texts, verbose=1, **kwargs):
          
          if self.has_vocab:
              logger.warn(
                  "Tokenizer already has existing vocabulary. Overriding and building new vocabulary.")
  
          progbar = Progbar(len(texts), verbose=verbose, interval=0.25)
          count_tracker = utils._CountTracker()
  
          self._token_counts.clear()
          self._num_texts = len(texts)
  
          for token_data in self.token_generator(texts, **kwargs):
              indices, token = token_data[:-1], token_data[-1]
              count_tracker.update(indices)
              self._token_counts[token] += 1
  
              # Update progressbar per document level.
              progbar.update(indices[0])
  
          # Generate token2idx and idx2token.
          self.create_token_indices(self._token_counts.keys())
  
          # All done. Finalize progressbar update and count tracker.
          count_tracker.finalize()
          self._counts = count_tracker.counts
          progbar.update(len(texts))
docs: Builds the internal vocabulary and computes various statistics.
  
          Args:
              texts: The list of text items to encode.
              verbose: The verbosity level for progress. Can be 0, 1, 2. (Default value = 1)
              **kwargs: The kwargs for `token_generator`.