(data_loader, exp, epoch, rank, is_distributed)
| 57 | |
| 58 | |
| 59 | def random_resize(data_loader, exp, epoch, rank, is_distributed): |
| 60 | tensor = torch.LongTensor(1).cuda() |
| 61 | if is_distributed: |
| 62 | synchronize() |
| 63 | |
| 64 | if rank == 0: |
| 65 | if epoch > exp.max_epoch - 10: |
| 66 | size = exp.input_size |
| 67 | else: |
| 68 | size = random.randint(*exp.random_size) |
| 69 | size = int(32 * size) |
| 70 | tensor.fill_(size) |
| 71 | |
| 72 | if is_distributed: |
| 73 | synchronize() |
| 74 | dist.broadcast(tensor, 0) |
| 75 | |
| 76 | input_size = data_loader.change_input_dim(multiple=tensor.item(), random_range=None) |
| 77 | return input_size |
nothing calls this directly
no test coverage detected