| # from pytorch lightning | |
| import random | |
| import numpy as np | |
| import torch | |
| max_seed_value = np.iinfo(np.uint32).max | |
| min_seed_value = np.iinfo(np.uint32).min | |
| def seed_everything(seed=None): | |
| seed = int(seed) | |
| if not (min_seed_value <= seed <= max_seed_value): | |
| raise ValueError(f"{seed} is not in bounds, numpy accepts from {min_seed_value} to {max_seed_value}") | |
| print(f"seed set to {seed}") | |
| random.seed(seed) | |
| np.random.seed(seed) | |
| torch.manual_seed(seed) | |
| torch.cuda.manual_seed_all(seed) | |
| return seed | |