code: def test_toy(self, device):
      patch = torch.ones(1, 1, 6, 6).to(device).float()
      patch[0, 0, :, 3:] = 0
      gradients = MKDGradients().to(device)
      out = gradients(patch)
      expected_mags_1 = torch.Tensor([0, 0, 1.0, 1.0, 0, 0]).to(device)
      expected_mags = expected_mags_1.unsqueeze(0).repeat(6, 1)
      expected_oris_1 = torch.Tensor([-pi, -pi, 0, 0, -pi, -pi]).to(
          device
      )
      expected_oris = expected_oris_1.unsqueeze(0).repeat(6, 1)
      assert_close(out[0, 0, :, :], expected_mags, atol=1e-3, rtol=1e-3)
      assert_close(out[0, 1, :, :], expected_oris, 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 4 for calling the TestMKDGradients obj's underlying member method code with example usage: obj.test_toy(device) without return types