code: def test_chunk(self):
      hidden_states = self._get_hidden_states()
      batch_size = 1
      seq_length = 8
      hidden_size = 4
      hidden_states = hidden_states.reshape(
          (batch_size, seq_length, hidden_size)
      )
  
      chunked_hidden_states = LongformerSelfAttention._chunk(
          hidden_states, window_overlap=2
      )
  
      # expected slices across chunk and seq length dim
      expected_slice_along_seq_length = torch.tensor(
          [0.4983, -0.7584, -1.6944],
          device=torch_device,
          dtype=torch.float32,
      )
      expected_slice_along_chunk = torch.tensor(
          [0.4983, -1.8348, -0.7584, 2.0514],
          device=torch_device,
          dtype=torch.float32,
      )
  
      self.assertTrue(
          torch.allclose(
              chunked_hidden_states[0, :, 0, 0],
              expected_slice_along_seq_length,
              atol=1e-3,
          )
      )
      self.assertTrue(
          torch.allclose(
              chunked_hidden_states[0, 0, :, 0],
              expected_slice_along_chunk,
              atol=1e-3,
          )
      )
      self.assertEqual(chunked_hidden_states.shape, (1, 3, 4, 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
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 4 for calling the LongformerModelIntegrationTest obj's underlying member method code with example usage: obj.test_chunk() without return types