code: def test_toy(self, device):
      inp = torch.ones(1, 1, 6, 6).to(device).float()
      inp[0, 0, :, :] = 0
      mkd = MKDDescriptor(
          patch_size=6, kernel_type="concat", whitening=None
      ).to(device)
      out = mkd(inp)
      out_part = out[0, -28:]
      expected = torch.zeros_like(out_part).to(device)
      assert_close(out_part, expected, atol=1e-3, rtol=1e-3)
  
imports: from math import pi
  import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia.testing
  from kornia.feature.mkd import COEFFS, EmbedGradients, ExplicitSpacialEncoding, MKDDescriptor, MKDGradients, SimpleKD, VonMisesKernel, Whitening, get_grid_dict, get_kron_order, spatial_kernel_embedding
  from kornia.testing import assert_close
label_desc: Use image node_id 5 for calling the TestMKDDescriptor obj's underlying member method code with example usage: obj.test_toy(device) without return types