code: def extend_vectors(self, tokens, vectors):
      tot_dim = sum(v.dim for v in vectors)
      prev_len = len(self.itos)
  
      new_tokens = []
      for token in tokens:
          if token not in self.stoi:
              self.itos.append(token)
              self.stoi[token] = len(self.itos) - 1
              new_tokens.append(token)
      self.vectors.resize_(len(self.itos), tot_dim)
  
      for i in range(prev_len, prev_len + len(new_tokens)):
          token = self.itos[i]
          assert token == new_tokens[i - prev_len]
  
          start_dim = 0
          for v in vectors:
              end_dim = start_dim + v.dim
              self.vectors[i][start_dim:end_dim] = v[token.strip()]
              start_dim = end_dim
          assert start_dim == tot_dim
  
imports: import gzip
  import logging
  import os
  import shutil
  import tarfile
  import zipfile
  import nltk
  import six
  import fasttext
  import torch
  from torchtext.legacy import data, vocab
  from torchtext.utils import download_from_url
  from urllib.request import urlretrieve
label_desc: Use image node_id 1 for calling the MatchingVocab obj's underlying member method code with example usage: obj.extend_vectors(tokens, vectors) without return types