code: def test_save_load_pretrained_default(self):
      feature_extractor = self.get_feature_extractor()
      tokenizers = self.get_tokenizers()
      for tokenizer in tokenizers:
          processor = LayoutLMv2Processor(
              feature_extractor=feature_extractor, tokenizer=tokenizer
          )
  
          processor.save_pretrained(self.tmpdirname)
          processor = LayoutLMv2Processor.from_pretrained(
              self.tmpdirname
          )
  
          self.assertEqual(
              processor.tokenizer.get_vocab(), tokenizer.get_vocab()
          )
          self.assertIsInstance(
              processor.tokenizer,
              (LayoutLMv2Tokenizer, LayoutLMv2TokenizerFast),
          )
  
          self.assertEqual(
              processor.feature_extractor.to_json_string(),
              feature_extractor.to_json_string(),
          )
          self.assertIsInstance(
              processor.feature_extractor, LayoutLMv2FeatureExtractor
          )
  
imports: import json
  import os
  import shutil
  import tempfile
  import unittest
  from typing import List
  from transformers import PreTrainedTokenizer, PreTrainedTokenizerBase, PreTrainedTokenizerFast
  from transformers.models.layoutlmv2 import LayoutLMv2Tokenizer, LayoutLMv2TokenizerFast
  from transformers.models.layoutlmv2.tokenization_layoutlmv2 import VOCAB_FILES_NAMES
  from transformers.testing_utils import require_pytesseract, require_tokenizers, require_torch, slow
  from transformers.utils import FEATURE_EXTRACTOR_NAME, cached_property, is_pytesseract_available
label_desc: Use image node_id 7 for calling the LayoutLMv2ProcessorTest obj's underlying member method code with example usage: obj.test_save_load_pretrained_default() without return types