code: def test_divide_by_zero2d(self, height, width, device, dtype):
      output = kornia.geometry.conversions.normal_transform_pixel(
          height, width, device=device, dtype=dtype
      )
      assert torch.isinf(output).sum().item() == 0
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
  from kornia.utils.helpers import _torch_inverse_cast
label_desc: Use image node_id 2 for calling the TestHomographyNormalTransform obj's underlying member method code with example usage: obj.test_divide_by_zero2d(height, width, device, dtype) without return types