code: def test_shape(self, kernel_type, xform, output_dims, device):
      in_dims = 63 if kernel_type == "cart" else 175
      wh = Whitening(
          xform=xform,
          whitening_model=None,
          in_dims=in_dims,
          output_dims=output_dims,
      ).to(device)
      inp = torch.ones(1, in_dims).to(device)
      out = wh(inp)
      assert out.shape == (1, output_dims)
  
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 1 for calling the TestWhitening obj's underlying member method code with example usage: obj.test_shape(kernel_type, xform, output_dims, device) without return types