class_docstr: Here we also overwrite some of the tests of test_modeling_common.py, as VitMatte 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","VitMatte","does","not","use","input_ids",",","inputs_embeds",",","attention_mask","and","seq_length","."]
code: def test_hidden_states_output(self):
      def check_hidden_states_output(inputs_dict, config, model_class):
          model = model_class(config)
          model.to(torch_device)
          model.eval()
  
          with torch.no_grad():
              outputs = model(
                  **self._prepare_for_class(inputs_dict, model_class)
              )
  
          hidden_states = (
              outputs.encoder_hidden_states
              if config.is_encoder_decoder
              else outputs.hidden_states
          )
  
          expected_num_layers = getattr(
              self.model_tester,
              "expected_num_hidden_layers",
              self.model_tester.num_hidden_layers + 1,
          )
          self.assertEqual(len(hidden_states), expected_num_layers)
  
          self.assertListEqual(
              list(hidden_states[0].shape[-2:]),
              [2, 2],
          )
  
      (
          config,
          inputs_dict,
      ) = self.model_tester.prepare_config_and_inputs_for_common()
  
      for model_class in self.all_model_classes:
          inputs_dict["output_hidden_states"] = True
          check_hidden_states_output(inputs_dict, config, model_class)
  
          # check that output_hidden_states also work using config
          del inputs_dict["output_hidden_states"]
          config.output_hidden_states = True
  
          print("Hello we're here")
  
          check_hidden_states_output(inputs_dict, config, model_class)
  
imports: import unittest
  from huggingface_hub import hf_hub_download
  from transformers import VitMatteConfig
  from transformers.testing_utils import require_torch, slow, torch_device
  from transformers.utils import is_torch_available, is_vision_available
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 13 for calling the VitMatteModelTest obj's underlying member method code with example usage: obj.test_hidden_states_output() without return types