code: def test_inference_no_head(self):
      model = LongformerModel.from_pretrained(
          "allenai/longformer-base-4096"
      )
      model.to(torch_device)
  
      # 'Hello world!'
      input_ids = torch.tensor(
          [[0, 20920, 232, 328, 1437, 2]],
          dtype=torch.long,
          device=torch_device,
      )
      attention_mask = torch.ones(
          input_ids.shape, dtype=torch.long, device=torch_device
      )
  
      output = model(input_ids, attention_mask=attention_mask)[0]
      output_without_mask = model(input_ids)[0]
  
      expected_output_slice = torch.tensor(
          [0.0549, 0.1087, -0.1119, -0.0368, 0.0250],
          device=torch_device,
      )
      self.assertTrue(
          torch.allclose(
              output[0, 0, -5:], expected_output_slice, atol=1e-4
          )
      )
      self.assertTrue(
          torch.allclose(
              output_without_mask[0, 0, -5:],
              expected_output_slice,
              atol=1e-4,
          )
      )
  
imports: import unittest
  from transformers import LongformerConfig, is_torch_available
  from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
label_desc: Use image node_id 9 for calling the LongformerModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_no_head() without return types