code: def test_inference_masked_lm_long_input(self):
      model = YosoForMaskedLM.from_pretrained("uw-madison/yoso-4096")
      input_ids = torch.arange(4096).unsqueeze(0)
  
      with torch.no_grad():
          output = model(input_ids)[0]
  
      vocab_size = 50265
  
      expected_shape = torch.Size((1, 4096, vocab_size))
      self.assertEqual(output.shape, expected_shape)
  
      expected_slice = torch.tensor(
          [
              [
                  [-2.3914, -4.3742, -5.0956],
                  [-4.0988, -4.2384, -7.0406],
                  [-3.1427, -3.7192, -6.6800],
              ]
          ]
      )
  
      self.assertTrue(
          torch.allclose(output[:, :3, :3], expected_slice, atol=1e-4)
      )
  
imports: import unittest
  from transformers import YosoConfig, 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
label_desc: Use image node_id 3 for calling the YosoModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_masked_lm_long_input() without return types