code: def test_3d(self):
      a = torch.ones(1, 1, 4, 3, 4)
      g = GaussianFilter(3, 3, 3).to(torch.device("cpu:0"))
  
      expected = np.array(
          [
              [
                  [
                      [
                          [
                              0.07189433,
                              0.07911152,
                              0.07911152,
                              0.07189433,
                          ],
                          [
                              0.07566228,
                              0.08325771,
                              0.08325771,
                              0.07566228,
                          ],
                          [
                              0.07189433,
                              0.07911152,
                              0.07911152,
                              0.07189433,
                          ],
                      ],
                      [
                          [
                              0.07911152,
                              0.08705322,
                              0.08705322,
                              0.07911152,
                          ],
                          [
                              0.08325771,
                              0.09161563,
                              0.09161563,
                              0.08325771,
                          ],
                          [
                              0.07911152,
                              0.08705322,
                              0.08705322,
                              0.07911152,
                          ],
                      ],
                      [
                          [
                              0.07911152,
                              0.08705322,
                              0.08705322,
                              0.07911152,
                          ],
                          [
                              0.08325771,
                              0.09161563,
                              0.09161563,
                              0.08325771,
                          ],
                          [
                              0.07911152,
                              0.08705322,
                              0.08705322,
                              0.07911152,
                          ],
                      ],
                      [
                          [
                              0.07189433,
                              0.07911152,
                              0.07911152,
                              0.07189433,
                          ],
                          [
                              0.07566228,
                              0.08325771,
                              0.08325771,
                              0.07566228,
                          ],
                          [
                              0.07189433,
                              0.07911152,
                              0.07911152,
                              0.07189433,
                          ],
                      ],
                  ]
              ]
          ]
      )
      np.testing.assert_allclose(
          g(a).cpu().numpy(), expected, rtol=1e-5
      )
  
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 3 for calling the GaussianFilterTestCase obj's underlying member method code with example usage: obj.test_3d() without return types