(mean_box, stdev, N, maxsize)
| 115 | from detectron2 import _C |
| 116 | |
| 117 | def random_boxes(mean_box, stdev, N, maxsize): |
| 118 | ret = torch.rand(N, 4) * stdev + torch.tensor(mean_box, dtype=torch.float) |
| 119 | ret.clamp_(min=0, max=maxsize) |
| 120 | return ret |
| 121 | |
| 122 | def func(N, C, H, W, nboxes_per_img): |
| 123 | input = torch.rand(N, C, H, W) |