code: def test_denormalize(self, device, dtype):
      # prepare input data
      data = torch.ones(1, 2, 2, device=device, dtype=dtype)
      mean = torch.tensor([0.5])
      std = torch.tensor([2.0])
  
      # expected output
      expected = (
          torch.tensor([2.5], device=device, dtype=dtype)
          .repeat(1, 2, 2)
          .view_as(data)
      )
  
      f = kornia.enhance.Denormalize(mean, std)
      self.assert_close(f(data), expected)
  
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 2 for calling the TestDenormalize obj's underlying member method code with example usage: obj.test_denormalize(device, dtype) without return types