code: def test_gradcheck(self, device, dtype):
      # prepare input data
      data = torch.ones(2, 3, 1, 1, device=device, dtype=dtype)
      mean = torch.tensor(
          [0.5, 1.0, 2.0], device=device, dtype=dtype
      ).repeat(2, 1)
      std = torch.tensor(
          [2.0, 2.0, 2.0], device=device, dtype=dtype
      ).repeat(2, 1)
  
      data = utils.tensor_to_gradcheck_var(data)  # to var
      mean = utils.tensor_to_gradcheck_var(mean)  # to var
      std = utils.tensor_to_gradcheck_var(std)  # to var
  
      assert gradcheck(
          kornia.enhance.Normalize(mean, std),
          (data,),
          raise_exception=True,
          fast_mode=True,
      )
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import BaseTester
label_desc: Use image node_id 8 for calling the TestNormalize obj's underlying member method code with example usage: obj.test_gradcheck(device, dtype) without return types