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