code: def test_inference_lm_head_model(self):
      model = BioGptForCausalLM.from_pretrained("microsoft/biogpt")
      input_ids = torch.tensor([[2, 4805, 9, 656, 21]])
      output = model(input_ids)[0]
  
      vocab_size = 42384
  
      expected_shape = torch.Size((1, 5, vocab_size))
      self.assertEqual(output.shape, expected_shape)
  
      expected_slice = torch.tensor(
          [
              [
                  [-9.5236, -9.8918, 10.4557],
                  [-11.0469, -9.6423, 8.1022],
                  [-8.8664, -7.8826, 5.5325],
              ]
          ]
      )
  
      self.assertTrue(
          torch.allclose(output[:, :3, :3], expected_slice, atol=1e-4)
      )
  
imports: import math
  import unittest
  from transformers import BioGptConfig, is_torch_available
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 for calling the BioGptModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_lm_head_model() without return types