code: def test_broadcast_normalize(self, device, dtype):
      # prepare input data
      data = torch.ones(2, 3, 1, 1, device=device, dtype=dtype)
      data += 2
  
      mean = torch.tensor([2.0], device=device, dtype=dtype)
      std = torch.tensor([0.5], device=device, dtype=dtype)
  
      # expected output
      expected = torch.ones_like(data) + 1
  
      f = kornia.enhance.Normalize(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 3 for calling the TestNormalize obj's underlying member method code with example usage: obj.test_broadcast_normalize(device, dtype) without return types