code: def test_simple(self, device, dtype):
      # this is for default normalize_points=False
      depth = 2 * torch.tensor(
          [
              [
                  [
                      [1.0, 1.0, 1.0],
                      [1.0, 1.0, 1.0],
                      [1.0, 1.0, 1.0],
                      [1.0, 1.0, 1.0],
                  ]
              ]
          ],
          device=device,
          dtype=dtype,
      )
  
      camera_matrix = torch.tensor(
          [[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]]],
          device=device,
          dtype=dtype,
      )
  
      normals_expected = torch.tensor(
          [
              [
                  [
                      [0.0, 0.0, 0.0],
                      [0.0, 0.0, 0.0],
                      [0.0, 0.0, 0.0],
                      [0.0, 0.0, 0.0],
                  ],
                  [
                      [0.0, 0.0, 0.0],
                      [0.0, 0.0, 0.0],
                      [0.0, 0.0, 0.0],
                      [0.0, 0.0, 0.0],
                  ],
                  [
                      [1.0, 1.0, 1.0],
                      [1.0, 1.0, 1.0],
                      [1.0, 1.0, 1.0],
                      [1.0, 1.0, 1.0],
                  ],
              ]
          ],
          device=device,
          dtype=dtype,
      )
  
      normals = kornia.geometry.depth.depth_to_normals(
          depth, camera_matrix
      )  # default is normalize_points=False
      assert_close(normals, normals_expected, rtol=1e-3, atol=1e-3)
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
label_desc: Use image node_id 4 for calling the TestDepthToNormals obj's underlying member method code with example usage: obj.test_simple(device, dtype) without return types