code: def test_feat_extract_properties(self):
      feature_extractor = self.feature_extraction_class(
          **self.feat_extract_dict
      )
      self.assertTrue(hasattr(feature_extractor, "image_mean"))
      self.assertTrue(hasattr(feature_extractor, "image_std"))
      self.assertTrue(hasattr(feature_extractor, "do_normalize"))
      self.assertTrue(hasattr(feature_extractor, "do_resize"))
      self.assertTrue(hasattr(feature_extractor, "size"))
      self.assertTrue(hasattr(feature_extractor, "max_size"))
  
imports: import json
  import pathlib
  import unittest
  import numpy
  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, prepare_image_inputs
label_desc: Use image node_id 3 for calling the DeformableDetrFeatureExtractionTest obj's underlying member method code with example usage: obj.test_feat_extract_properties() without return types