code: def test_image_processor_from_and_save_pretrained(self):
      image_processor_first = self.image_processing_class(
          **self.image_processor_dict
      )
  
      with tempfile.TemporaryDirectory() as tmpdirname:
          saved_file = image_processor_first.save_pretrained(
              tmpdirname
          )[0]
          check_json_file_has_correct_format(saved_file)
          image_processor_second = (
              self.image_processing_class.from_pretrained(tmpdirname)
          )
  
      self.assertEqual(
          image_processor_second.to_dict(),
          image_processor_first.to_dict(),
      )
  
imports: import json
  import os
  import pathlib
  import tempfile
  from transformers import BatchFeature
  from transformers.image_utils import AnnotationFormat, AnnotionFormat
  from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_vision
  from transformers.utils import is_torch_available, is_vision_available
label_desc: Use image node_id 3 for calling the ImageProcessingTestMixin obj's underlying member method code with example usage: obj.test_image_processor_from_and_save_pretrained() without return types