code: def test_inference_no_head(self):
      model = MraModel.from_pretrained("uw-madison/mra-base-512-4")
      input_ids = torch.arange(256).unsqueeze(0)
  
      with torch.no_grad():
          output = model(input_ids)[0]
  
      expected_shape = torch.Size((1, 256, 768))
      self.assertEqual(output.shape, expected_shape)
  
      expected_slice = torch.tensor(
          [
              [
                  [-0.0140, 0.0830, -0.0381],
                  [0.1546, 0.1402, 0.0220],
                  [0.1162, 0.0851, 0.0165],
              ]
          ]
      )
  
      self.assertTrue(
          torch.allclose(output[:, :3, :3], expected_slice, atol=1e-4)
      )
  
imports: import unittest
  from transformers import MraConfig, is_torch_available
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 for calling the MraModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_no_head() without return types