code: def test_cardinality(self, batch_size, device, dtype):
      disparity = torch.rand(
          batch_size, 1, 3, 4, device=device, dtype=dtype
      )
      baseline = torch.rand(1, device=device, dtype=dtype)
      focal = torch.rand(1, device=device, dtype=dtype)
  
      points3d = kornia.geometry.depth.depth_from_disparity(
          disparity, baseline, focal
      )
      assert points3d.shape == (batch_size, 1, 3, 4)
  
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 2 for calling the TestDepthFromDisparity obj's underlying member method code with example usage: obj.test_cardinality(batch_size, device, dtype) without return types