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Source code for mmcv.utils.seed

# Copyright (c) OpenMMLab. All rights reserved.
import random

import numpy as np
import torch


[docs]def worker_init_fn(worker_id: int, num_workers: int, rank: int, seed: int): """Function to initialize each worker. The seed of each worker equals to ``num_worker * rank + worker_id + user_seed``. Args: worker_id (int): Id for each worker. num_workers (int): Number of workers. rank (int): Rank in distributed training. seed (int): Random seed. """ worker_seed = num_workers * rank + worker_id + seed np.random.seed(worker_seed) random.seed(worker_seed) torch.manual_seed(worker_seed)
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