code: def test_functional(self, device, dtype):  # skipcq: PYL-R0201
      data = torch.tensor(
          [
              [
                  [1, 0.5, 0.2, 0.4],
                  [0.75, 0.25, 0.8, 0.3],
                  [0.65, 0.15, 0.7, 0.2],
                  [0.55, 0.5, 0.6, 0.1],
              ]
          ],
          device=device,
          dtype=dtype,
      )
      # checked by hand as correct interpolation. Note the ugly replication that happens for Red on the last column
      # and row. We shall accept to live with that
      expected = torch.tensor(
          [
              [
                  [1.0000, 0.6000, 0.2000, 0.2000],
                  [0.8250, 0.6375, 0.4500, 0.4500],
                  [0.6500, 0.6750, 0.7000, 0.7000],
                  [0.6500, 0.6750, 0.7000, 0.7000],
              ],
              [
                  [0.6250, 0.5000, 0.6250, 0.4000],
                  [0.7500, 0.5500, 0.8000, 0.5500],
                  [0.4000, 0.1500, 0.4375, 0.2000],
                  [0.5500, 0.3625, 0.6000, 0.4000],
              ],
              [
                  [0.2500, 0.2500, 0.2750, 0.3000],
                  [0.2500, 0.2500, 0.2750, 0.3000],
                  [0.3750, 0.3750, 0.2875, 0.2000],
                  [0.5000, 0.5000, 0.3000, 0.1000],
              ],
          ],
          device=device,
          dtype=dtype,
      )
  
      img_rgb = kornia.color.raw_to_rgb(data, kornia.color.raw.CFA.BG)
      assert_close(img_rgb, expected)
  
imports: import warnings
  import pytest
  import torch
  from packaging import version
  from torch.autograd import gradcheck
  import kornia
  from kornia.testing import BaseTester, assert_close
label_desc: Use image node_id 6 for calling the TestRawToRgb obj's underlying member method code with example usage: obj.test_functional(device, dtype) without return types