code: def test_3d_sigmas(self):
      a = torch.ones(1, 1, 4, 3, 2)
      g = GaussianFilter(3, [3, 2, 1], 3).to(torch.device("cpu:0"))
  
      expected = np.array(
          [
              [
                  [
                      [
                          [0.13690521, 0.13690521],
                          [0.15181276, 0.15181276],
                          [0.13690521, 0.13690521],
                      ],
                      [
                          [0.1506486, 0.15064861],
                          [0.16705267, 0.16705267],
                          [0.1506486, 0.15064861],
                      ],
                      [
                          [0.1506486, 0.15064861],
                          [0.16705267, 0.16705267],
                          [0.1506486, 0.15064861],
                      ],
                      [
                          [0.13690521, 0.13690521],
                          [0.15181276, 0.15181276],
                          [0.13690521, 0.13690521],
                      ],
                  ]
              ]
          ]
      )
      np.testing.assert_allclose(
          g(a).cpu().numpy(), expected, rtol=1e-5
      )
      if torch.cuda.is_available():
          g = GaussianFilter(3, [3, 2, 1], 3).to(torch.device("cuda:0"))
          np.testing.assert_allclose(
              g(a.cuda()).cpu().numpy(), expected, rtol=1e-2
          )
  
file_path: MONAI/tests/test_gaussian_filter.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from monai.networks.layers import GaussianFilter
  from tests.utils import skip_if_quick
label_desc: Use image node_id 4 for calling the GaussianFilterTestCase obj's underlying member method code with example usage: obj.test_3d_sigmas() without return types