class_docstr: Collection of data from a real stereo setup.
class_docstr_tok: ["Collection","of","data","from","a","real","stereo","setup","."]
code: def _get_real_point_cloud(batch_size, device, dtype):
      # First 10 cols of 1 row in the ground truth point cloud computed from above disparity map.
      pc = torch.tensor(
          [
              [
                  [[-30.2769, -19.3972, 80.4424]],
                  [[-30.1945, -19.3961, 80.4377]],
                  [[-30.1120, -19.3950, 80.4330]],
                  [[-30.0295, -19.3938, 80.4284]],
                  [[-29.9471, -19.3927, 80.4237]],
                  [[-29.8646, -19.3916, 80.4191]],
                  [[-29.7822, -19.3905, 80.4144]],
                  [[-29.6998, -19.3893, 80.4098]],
                  [[-29.6174, -19.3882, 80.4051]],
                  [[-29.5350, -19.3871, 80.4005]],
              ]
          ],
          device=device,
          dtype=dtype,
      )
  
      return pc.expand(batch_size, -1, -1, -1)
  
imports: import pytest
  import torch
  from kornia.geometry.camera import StereoCamera
  from kornia.testing import assert_close
label_desc: Use image node_id 7 for calling the _RealTestData obj's underlying member method code with example usage: obj._get_real_point_cloud(batch_size, device, dtype) and returns: pc