(self)
| 85 | assert torch.allclose(projections, projs) |
| 86 | |
| 87 | def test_chunk(self): |
| 88 | b_shape = [3, 5] |
| 89 | n = 10 |
| 90 | m = 7 |
| 91 | points = torch.randn(*b_shape, n, 3) |
| 92 | ray_origins = torch.randn(*b_shape, m, 3) |
| 93 | ray_directions = torch.zeros(*b_shape, m, 3) |
| 94 | ray_directions[..., 2] = 1. |
| 95 | |
| 96 | # standard (no chunking) |
| 97 | out_dict_gt = utils.compute_point_ray_distance( |
| 98 | points=points, |
| 99 | ray_origins=ray_origins, |
| 100 | ray_directions=ray_directions, |
| 101 | ) |
| 102 | |
| 103 | # with chunking |
| 104 | mn = m * n |
| 105 | for max_chunk_size in [int(1e9), mn//2, mn+1]: |
| 106 | out_dict = utils.compute_point_ray_distance_in_chunks( |
| 107 | points=points, |
| 108 | ray_origins=ray_origins, |
| 109 | ray_directions=ray_directions, |
| 110 | max_chunk_size=max_chunk_size, |
| 111 | ) |
| 112 | for key in out_dict_gt: |
| 113 | assert torch.allclose(out_dict_gt[key], out_dict[key]), f'{max_chunk_size}' |
| 114 | |
| 115 | |
| 116 |
nothing calls this directly
no outgoing calls
no test coverage detected