code: def test_downscale_values(self, device, dtype):
      inp_x = torch.arange(20, device=device, dtype=dtype) / 20.0
      inp = inp_x[None].T @ inp_x[None]
      inp = inp[None, None]
      out = kornia.geometry.transform.rescale(
          inp, (0.25, 0.25), antialias=False, align_corners=False
      )
      expected = torch.tensor(
          [
              [
                  [
                      [0.0056, 0.0206, 0.0356, 0.0506, 0.0656],
                      [0.0206, 0.0756, 0.1306, 0.1856, 0.2406],
                      [0.0356, 0.1306, 0.2256, 0.3206, 0.4156],
                      [0.0506, 0.1856, 0.3206, 0.4556, 0.5906],
                      [0.0656, 0.2406, 0.4156, 0.5906, 0.7656],
                  ]
              ]
          ],
          device=device,
          dtype=dtype,
      )
      assert_close(out, expected, atol=1e-3, rtol=1e-3)
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
label_desc: Use image node_id 4 for calling the TestRescale obj's underlying member method code with example usage: obj.test_downscale_values(device, dtype) without return types