code: def test_smoke(self, device, dtype):
      disparity = 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,
      )
  
      baseline = torch.tensor([1.0], device=device, dtype=dtype)
      focal = torch.tensor([1.0], device=device, dtype=dtype)
  
      depth_expected = torch.tensor(
          [
              [
                  [
                      [0.5000, 0.5000, 0.5000],
                      [0.5000, 0.5000, 0.5000],
                      [0.5000, 0.5000, 0.5000],
                      [0.5000, 0.5000, 0.5000],
                  ]
              ]
          ],
          device=device,
          dtype=dtype,
      )
  
      depth = kornia.geometry.depth.depth_from_disparity(
          disparity, baseline, focal
      )
      assert_close(depth, depth_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 1 for calling the TestDepthFromDisparity obj's underlying member method code with example usage: obj.test_smoke(device, dtype) without return types