code: def test_simple(self, device, dtype):
      K = torch.tensor(
          [[[10.0, 0.0, 30.0], [0.0, 20.0, 40.0], [0.0, 0.0, 1.0]]],
          device=device,
          dtype=dtype,
      )
  
      R = torch.tensor(
          [[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]]],
          device=device,
          dtype=dtype,
      )
  
      t = torch.tensor(
          [[[1.0], [2.0], [3.0]]], device=device, dtype=dtype
      )
  
      P_expected = torch.tensor(
          [
              [
                  [10.0, 0.0, 30.0, 100.0],
                  [0.0, 20.0, 40.0, 160.0],
                  [0.0, 0.0, 1.0, 3.0],
              ]
          ],
          device=device,
          dtype=dtype,
      )
  
      P_estimated = epi.projection_from_KRt(K, R, t)
      assert_close(P_estimated, P_expected, atol=1e-4, rtol=1e-4)
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia.geometry.epipolar
  from kornia.testing import assert_close
label_desc: Use image node_id 3 for calling the TestProjectionFromKRt obj's underlying member method code with example usage: obj.test_simple(device, dtype) without return types