code: def test_gradcheck(self, device, dtype):
      inp = torch.randn((1, 1, 3, 3), device=device, dtype=dtype)
      transform = torch.tensor(
          [[[2.0, 0.0, -2.0], [0.0, 1.0, -1.0], [0.0, 0.0, 1.0]]],
          device=device,
          dtype=dtype,
      )  # 1x3x3
  
      inp = utils.tensor_to_gradcheck_var(
          inp, requires_grad=True
      )  # to var
  
      assert gradcheck(
          kornia.geometry.transform.crop_by_transform_mat,
          (inp, transform, (2, 2)),
          raise_exception=True,
          fast_mode=True,
      )
  
imports: import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
label_desc: Use image node_id 3 for calling the TestCropByTransform obj's underlying member method code with example usage: obj.test_gradcheck(device, dtype) without return types