code: def test_extend_vocab_1(self):
      vectors_cache_dir = ".cache"
      if os.path.exists(vectors_cache_dir):
          shutil.rmtree(vectors_cache_dir)
  
      mf = MatchingField()
      lf = MatchingField(id=True, sequential=False)
      fields = [
          ("id", lf),
          ("left_a", mf),
          ("right_a", mf),
          ("label", lf),
      ]
      col_naming = {
          "id": "id",
          "label": "label",
          "left": "left_",
          "right": "right_",
      }
  
      pathdir = os.path.abspath(
          os.path.join(test_dir_path, "test_datasets")
      )
      filename = "fasttext_sample.vec"
      file = os.path.join(pathdir, filename)
      url_base = urljoin("file:", pathname2url(file))
      vecs = Vectors(
          name=filename, cache=vectors_cache_dir, url=url_base
      )
  
      data_path = os.path.join(
          test_dir_path, "test_datasets", "sample_table_small.csv"
      )
      md = MatchingDataset(fields, col_naming, path=data_path)
  
      mf.build_vocab()
      mf.vocab.vectors = torch.Tensor(len(mf.vocab.itos), 300)
      mf.extend_vocab(md, vectors=vecs)
      self.assertEqual(len(mf.vocab.itos), 6)
      self.assertEqual(mf.vocab.vectors.size(), torch.Size([6, 300]))
  
imports: import os
  import shutil
  import unittest
  from collections import Counter
  from test import test_dir_path
  from nose.tools import *
  import torch
  from deepmatcher.data.dataset import MatchingDataset
  from deepmatcher.data.field import FastText, FastTextBinary, MatchingField, MatchingVocab, reset_vector_cache
  from torchtext.vocab import Vectors
  from urllib.parse import urljoin
  from urllib.request import pathname2url
label_desc: Use image node_id 11 for calling the ClassMatchingFieldTestCases obj's underlying member method code with example usage: obj.test_extend_vocab_1() without return types