code: def test_2d(self):
      a = torch.tensor(
          [[[list(range(7)), list(range(7, 0, -1)), list(range(7))]]],
          dtype=torch.float,
      )
      expected = np.array(
          [
              [28.0, 28.0, 28.0, 28.0, 28.0, 28.0],
              [30.0, 34.0, 38.0, 42.0, 46.0, 50.0],
              [28.0, 28.0, 28.0, 28.0, 28.0, 28.0],
          ]
      )
      expected = expected[None][None]
      out = separable_filtering(
          a, [torch.tensor([1, 1, 1]), torch.tensor([2, 2])]
      )
      np.testing.assert_allclose(out.cpu().numpy(), expected, rtol=1e-4)
      if torch.cuda.is_available():
          out = separable_filtering(
              a.cuda(),
              [
                  torch.tensor([1, 1, 1]).cuda(),
                  torch.tensor([2, 2]).cuda(),
              ],
          )
          np.testing.assert_allclose(
              out.cpu().numpy(), expected, rtol=1e-4
          )
  
file_path: MONAI/tests/test_separable_filter.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from monai.networks.layers import separable_filtering
label_desc: Use image node_id 2 for calling the SeparableFilterTestCase obj's underlying member method code with example usage: obj.test_2d() without return types