code: def test_different_timm_backbone(self):
      (
          config,
          inputs_dict,
      ) = self.model_tester.prepare_config_and_inputs_for_common()
  
      # let's pick a random timm backbone
      config.backbone = "tf_mobilenetv3_small_075"
  
      for model_class in self.all_model_classes:
          model = model_class(config)
          model.to(torch_device)
          model.eval()
          with torch.no_grad():
              outputs = model(
                  **self._prepare_for_class(inputs_dict, model_class)
              )
  
          if model_class.__name__ == "DeformableDetrForObjectDetection":
              expected_shape = (
                  self.model_tester.batch_size,
                  self.model_tester.num_queries,
                  self.model_tester.num_labels,
              )
              self.assertEqual(outputs.logits.shape, expected_shape)
  
          self.assertTrue(outputs)
  
imports: import inspect
  import math
  import unittest
  from typing import Dict, List, Tuple
  from transformers import DeformableDetrConfig, ResNetConfig, is_torch_available, is_vision_available
  from transformers.file_utils import cached_property
  from transformers.testing_utils import require_timm, require_torch, require_torch_accelerator, require_vision, slow, torch_device
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 15 for calling the DeformableDetrModelTest obj's underlying member method code with example usage: obj.test_different_timm_backbone() without return types