class_docstr: Here we also overwrite some of the tests of test_modeling_common.py, as ConvNext does not use input_ids, inputs_embeds,
  attention_mask and seq_length.
class_docstr_tok: ["Here","we","also","overwrite","some","of","the","tests","of","test_modeling_common.py",",","as","ConvNext","does","not","use","input_ids",",","inputs_embeds",",","attention_mask","and","seq_length","."]
code: def test_forward_signature(self):
      (
          config,
          _,
      ) = self.model_tester.prepare_config_and_inputs_for_common()
  
      for model_class in self.all_model_classes:
          model = model_class(config)
          signature = inspect.signature(model.forward)
          # signature.parameters is an OrderedDict => so arg_names order is deterministic
          arg_names = [*signature.parameters.keys()]
  
          expected_arg_names = ["pixel_values"]
          self.assertListEqual(arg_names[:1], expected_arg_names)
  
imports: import inspect
  import unittest
  from transformers import ConvNextConfig
  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 7 for calling the ConvNextModelTest obj's underlying member method code with example usage: obj.test_forward_signature() without return types