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
              ).to_dict()
          )
  
      feat_extract_first = feat_extract_first.to_dict()
      for key, value in feat_extract_first.items():
          if key == "clusters":
              self.assertTrue(
                  np.array_equal(value, feat_extract_second[key])
              )
          else:
              self.assertEqual(feat_extract_first[key], value)
  
imports: import json
  import os
  import tempfile
  import unittest
  import numpy
  from datasets import load_dataset
  from transformers.testing_utils import require_torch, require_vision, slow
  from transformers.utils import is_torch_available, is_vision_available
  from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
label_desc: Use image node_id 5 for calling the ImageGPTFeatureExtractionTest obj's underlying member method code with example usage: obj.test_feat_extract_to_json_file() without return types