code: def test_save_load_pretrained_default(self):
      tokenizer = self.get_tokenizer()
      feature_extractor = self.get_feature_extractor()
  
      processor = MCTCTProcessor(
          tokenizer=tokenizer, feature_extractor=feature_extractor
      )
  
      processor.save_pretrained(self.tmpdirname)
      processor = MCTCTProcessor.from_pretrained(self.tmpdirname)
  
      self.assertEqual(
          processor.tokenizer.get_vocab(), tokenizer.get_vocab()
      )
      self.assertIsInstance(processor.tokenizer, Wav2Vec2CTCTokenizer)
  
      self.assertEqual(
          processor.feature_extractor.to_json_string(),
          feature_extractor.to_json_string(),
      )
      self.assertIsInstance(
          processor.feature_extractor, MCTCTFeatureExtractor
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/models/mctct/test_processor_mctct.py
imports: import json
  import os
  import shutil
  import tempfile
  import unittest
  from transformers import MCTCTProcessor, is_speech_available, is_torch_available
  from transformers.file_utils import FEATURE_EXTRACTOR_NAME
  from transformers.models.wav2vec2.tokenization_wav2vec2 import VOCAB_FILES_NAMES, Wav2Vec2CTCTokenizer
  from transformers.testing_utils import require_torch, require_torchaudio
label_desc: Use image node_id 5 for calling the MCTCTProcessorTest obj's underlying member method code with example usage: obj.test_save_load_pretrained_default() without return types