code: def create_and_check_for_image_classification(
      self, config, pixel_values, labels
  ):
      config.num_labels = self.num_labels
      model = ResNetForImageClassification(config)
      model.to(torch_device)
      model.eval()
      result = model(pixel_values, labels=labels)
      self.parent.assertEqual(
          result.logits.shape, (self.batch_size, self.num_labels)
      )
  
imports: import inspect
  import unittest
  from transformers import ResNetConfig
  from transformers.testing_utils import require_torch, require_vision, slow, torch_device
  from transformers.utils import cached_property, is_torch_available, is_vision_available
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
label_desc: Use image node_id 5 for calling the ResNetModelTester obj's underlying member method code with example usage: obj.create_and_check_for_image_classification(config, pixel_values, labels) without return types