code: def test_smoke(self, device, dtype):
      C, H, W = 1, 10, 20
      img = torch.rand(C, H, W, device=device, dtype=dtype)
      res = enhance.equalize_clahe(img)
      assert isinstance(res, torch.Tensor)
      assert res.shape == img.shape
      assert res.device == img.device
      assert res.dtype == img.dtype
  
imports: from typing import Tuple
  import pytest
  import torch
  from torch.autograd import gradcheck
  from kornia import enhance
  from kornia.geometry import rotate
  from kornia.testing import BaseTester, tensor_to_gradcheck_var
label_desc: Use image node_id 1 for calling the TestEqualization obj's underlying member method code with example usage: obj.test_smoke(device, dtype) without return types