| 5 | |
| 6 | |
| 7 | def create_dataloader(dataset, dataset_opt, opt=None, sampler=None): |
| 8 | phase = dataset_opt['phase'] |
| 9 | if phase == 'train': |
| 10 | num_workers = dataset_opt['n_workers'] * len(opt['gpu_ids']) |
| 11 | batch_size = dataset_opt['batch_size'] |
| 12 | # shuffle = True |
| 13 | shuffle = dataset_opt['use_shuffle'] |
| 14 | return torch.utils.data.DataLoader(dataset, batch_size=batch_size, shuffle=shuffle, |
| 15 | num_workers=num_workers, sampler=sampler, |
| 16 | pin_memory=True) |
| 17 | else: |
| 18 | batch_size = dataset_opt['batch_size'] |
| 19 | # shuffle = dataset_opt['use_shuffle'] |
| 20 | shuffle = False |
| 21 | return torch.utils.data.DataLoader(dataset, batch_size=batch_size, shuffle=shuffle, num_workers=0, |
| 22 | pin_memory=False) |
| 23 | |
| 24 | |
| 25 | def create_dataset(opt,dataset_opt): |