Source code for ts_benchmark.utils.random_utils

import os
import random
from typing import Optional, NoReturn

import numpy as np
import torch




def fix_random_seed(seed: Optional[int] = 2021) -> NoReturn:
    """
    Fixes the random seed for Python, PyTorch, and NumPy to ensure reproducibility.

    :param seed: The seed value to be used for random number generation.
    :return: None
    """
    if seed is None:
        return

    random.seed(seed)
    torch.manual_seed(seed)
    np.random.seed(seed)





def fix_all_random_seed(seed: Optional[int] = 2021) -> NoReturn:
    """
    Fixes the random seed for Python, PyTorch, NumPy, and CUDA.

    :param seed: The seed value to be used for random number generation.
    :return: None
    """
    if seed is None:
        return

    torch.manual_seed(seed)
    torch.cuda.manual_seed_all(seed)
    np.random.seed(seed)
    random.seed(seed)
    torch.cuda.manual_seed(seed)
    torch.backends.cudnn.deterministic = True
    torch.backends.cudnn.benchmark = False
    torch.backends.cudnn.enabled = False

    os.environ['PYTHONHASHSEED'] = str(1)