code: def test_nms(self, device):
      inp = torch.tensor(
          [
              [
                  [
                      [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
                      [0.0, 0.1, 1.0, 0.0, 1.0, 1.0, 0.0],
                      [0.0, 0.7, 1.1, 0.0, 1.0, 2.0, 0.0],
                      [0.0, 0.8, 1.0, 0.0, 1.0, 1.0, 0.0],
                  ]
              ]
          ],
          device=device,
      ).float()
  
      expected = torch.tensor(
          [
              [
                  [
                      [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
                      [0.0, 0, 0, 0.0, 0, 0.0, 0.0],
                      [0.0, 0, 1.1, 0.0, 0.0, 2.0, 0.0],
                      [0.0, 0, 0, 0.0, 0.0, 0.0, 0.0],
                  ]
              ]
          ],
          device=device,
      ).float()
      nms = kornia.geometry.subpix.NonMaximaSuppression2d((3, 3)).to(
          device
      )
      scores = nms(inp)
      assert_close(scores, expected, atol=1e-4, rtol=1e-3)
  
file_path: kornia/test/geometry/subpix/test_nms.py
imports: import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
label_desc: Use image node_id 3 for calling the TestNMS2d obj's underlying member method code with example usage: obj.test_nms(device) without return types