| import numpy as np | |
| import random | |
| import torch | |
| import os | |
| def seed_everything(seed: int = 42): | |
| random.seed(seed) | |
| np.random.seed(seed) | |
| os.environ["PYTHONHASHSEED"] = str(seed) | |
| torch.manual_seed(seed) | |
| torch.cuda.manual_seed(seed) # type: ignore | |
| torch.backends.cudnn.deterministic = True # type: ignore | |
| torch.backends.cudnn.benchmark = True # type: ignore | |
| def randomize_seed_fn(seed: int, randomize_seed: bool) -> int: | |
| MAX_SEED = np.iinfo(np.int32).max | |
| if randomize_seed: | |
| seed = random.randint(0, MAX_SEED) | |
| seed_everything(seed) | |
| return seed |