code: def test_smoke(self, device, dtype):
      trans = torch.rand(2, 2, device=device, dtype=dtype)
      trans_norm = epi.normalize_transformation(trans)
      assert trans_norm.shape == (2, 2)
  
imports: from typing import Dict
  import pytest
  import test_common
  import torch
  from torch.autograd import gradcheck
  import kornia.geometry.epipolar
  import kornia.testing
  from kornia.testing import assert_close
label_desc: Use image node_id 1 for calling the TestNormalizeTransformation obj's underlying member method code with example usage: obj.test_smoke(device, dtype) without return types