code: def test_pad_and_transpose_last_two_dims(self):
      hidden_states = self._get_hidden_states()
      self.assertEqual(hidden_states.shape, (1, 4, 8))
      padding = (0, 0, 0, 1)
  
      padded_hidden_states = (
          LongformerSelfAttention._pad_and_transpose_last_two_dims(
              hidden_states, padding
          )
      )
      self.assertEqual(padded_hidden_states.shape, (1, 8, 5))
  
      expected_added_dim = torch.zeros(
          (5,), device=torch_device, dtype=torch.float32
      )
      self.assertTrue(
          torch.allclose(
              expected_added_dim,
              padded_hidden_states[0, -1, :],
              atol=1e-6,
          )
      )
      self.assertTrue(
          torch.allclose(
              hidden_states[0, -1, :],
              padded_hidden_states.view(1, -1)[0, 24:32],
              atol=1e-6,
          )
      )
  
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 3 for calling the LongformerModelIntegrationTest obj's underlying member method code with example usage: obj.test_pad_and_transpose_last_two_dims() without return types