| 60 | |
| 61 | |
| 62 | def _data_transforms_cifar10(args): |
| 63 | CIFAR_MEAN = [0.49139968, 0.48215827, 0.44653124] |
| 64 | CIFAR_STD = [0.24703233, 0.24348505, 0.26158768] |
| 65 | |
| 66 | train_transform = transforms.Compose([ |
| 67 | transforms.RandomCrop(32, padding=4), |
| 68 | transforms.RandomHorizontalFlip(), |
| 69 | transforms.ToTensor(), |
| 70 | transforms.Normalize(CIFAR_MEAN, CIFAR_STD), |
| 71 | ]) |
| 72 | if args.cutout: |
| 73 | train_transform.transforms.append(Cutout(args.cutout_length)) |
| 74 | |
| 75 | valid_transform = transforms.Compose([ |
| 76 | transforms.ToTensor(), |
| 77 | transforms.Normalize(CIFAR_MEAN, CIFAR_STD), |
| 78 | ]) |
| 79 | return train_transform, valid_transform |
| 80 | |
| 81 | |
| 82 | def count_parameters_in_MB(model): |