code: def test_gradcheck(self, device, dtype):
      # TODO: implement differentiability
      cm = AUTUMN(device=device, dtype=dtype)
      input_tensor = torch.randint(
          0, 63, (1, 2, 1), device=device, dtype=dtype
      )
  
      input_tensor = tensor_to_gradcheck_var(input_tensor)
      cm.colors = tensor_to_gradcheck_var(cm.colors)
  
      assert gradcheck(
          apply_colormap,
          (input_tensor, cm),
          raise_exception=True,
          fast_mode=True,
      )
  
file_path: kornia/test/color/test_colormap.py
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  from kornia.color import AUTUMN, ApplyColorMap, apply_colormap
  from kornia.core import tensor
  from kornia.testing import BaseTester, assert_close, tensor_to_gradcheck_var
label_desc: Use image node_id 5 for calling the TestApplyColorMap obj's underlying member method code with example usage: obj.test_gradcheck(device, dtype) without return types