Source code for univi.utils.seed

# univi/utils/seed.py

from __future__ import annotations
import random
import numpy as np
import torch


[docs] def set_seed(seed: int = 0, deterministic: bool = False): random.seed(seed) np.random.seed(seed) torch.manual_seed(seed) if torch.cuda.is_available(): torch.cuda.manual_seed_all(seed) if deterministic: torch.backends.cudnn.deterministic = True torch.backends.cudnn.benchmark = False