code: def test_noncontiguous(self, device, dtype):
      batch_size = 3
      inp = torch.rand(3, 5, 5, device=device, dtype=dtype).expand(
          batch_size, -1, -1, -1
      )
  
      kernel_size = 3
      angle = 200.0
      direction = 0.3
      actual = motion_blur(inp, kernel_size, angle, direction)
      assert actual.is_contiguous()
  
imports: import pytest
  import torch
  from kornia.filters import MotionBlur, MotionBlur3D, get_motion_kernel2d, get_motion_kernel3d, motion_blur, motion_blur3d
  from kornia.testing import BaseTester, tensor_to_gradcheck_var
label_desc: Use image node_id 5 for calling the TestMotionBlur obj's underlying member method code with example usage: obj.test_noncontiguous(device, dtype) without return types