code: def test_feat_extract_to_json_file(self):
      feat_extract_first = self.feature_extraction_class(
          **self.feat_extract_dict
      )
  
      with tempfile.TemporaryDirectory() as tmpdirname:
          json_file_path = os.path.join(tmpdirname, "feat_extract.json")
          feat_extract_first.to_json_file(json_file_path)
          feat_extract_second = (
              self.feature_extraction_class.from_json_file(
                  json_file_path
              )
          )
  
      dict_first = feat_extract_first.to_dict()
      dict_second = feat_extract_second.to_dict()
      self.assertEqual(dict_first, dict_second)
  
imports: import itertools
  import os
  import random
  import tempfile
  import unittest
  import numpy
  from datasets import load_dataset
  from transformers import SeamlessM4TFeatureExtractor, is_speech_available
  from transformers.testing_utils import check_json_file_has_correct_format, require_torch
  from transformers.utils.import_utils import is_torch_available
  from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
label_desc: Use image node_id 3 for calling the SeamlessM4TFeatureExtractionTest obj's underlying member method code with example usage: obj.test_feat_extract_to_json_file() without return types