| """ | |
| Fix random seeds | |
| Authors | |
| * Heng-Jui Chang 2022 | |
| """ | |
| import random | |
| import numpy as np | |
| import torch | |
| __all__ = [ | |
| "fix_random_seeds", | |
| ] | |
| def fix_random_seeds(seed: int = 1337) -> None: | |
| """Fixes all random seeds, including cuDNN backends. | |
| Args: | |
| seed (int, optional): Random seed. Defaults to 1337. | |
| """ | |
| random.seed(seed) | |
| np.random.seed(seed) | |
| torch.manual_seed(seed) | |
| if torch.cuda.is_available(): | |
| torch.cuda.manual_seed(seed) | |
| torch.cuda.manual_seed_all(seed) | |
| torch.backends.cudnn.benchmark = False | |
| torch.backends.cudnn.deterministic = True | |