code: def test_downscale_values_AA(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=True, align_corners=False
      )
      expected = torch.tensor(
          [
              [
                  [
                      [0.0074, 0.0237, 0.0409, 0.0581, 0.0743],
                      [0.0237, 0.0756, 0.1306, 0.1856, 0.2376],
                      [0.0409, 0.1306, 0.2256, 0.3206, 0.4104],
                      [0.0581, 0.1856, 0.3206, 0.4556, 0.5832],
                      [0.0743, 0.2376, 0.4104, 0.5832, 0.7464],
                  ]
              ]
          ],
          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 5 for calling the TestRescale obj's underlying member method code with example usage: obj.test_downscale_values_AA(device, dtype) without return types