pytorch - set seed everything

seed_everything.py

def seed_everything(seed: int):
    import random, os
    import numpy as np
    import torch
    
    random.seed(seed)
    os.environ['PYTHONHASHSEED'] = str(seed)
    np.random.seed(seed)
    torch.manual_seed(seed)
    torch.cuda.manual_seed(seed)
    torch.backends.cudnn.deterministic = True
    torch.backends.cudnn.benchmark = True
    
seed_everything(42)

you have forgotten to seed the generator function of the train dataloader. add this:

def seed_worker(worker_id):
    worker_seed = torch.initial_seed() % 2**32
    np.random.seed(worker_seed)
    random.seed(worker_seed)

g = torch.Generator()
g.manual_seed(seed)
train_loader = torch.utils.data.DataLoader(
        eval(dset_string)(root='./data', train=True, transform=transforms.Compose([
            transforms.RandomHorizontalFlip(),
            transforms.RandomCrop(32, 4),
            transforms.ToTensor(),
            normalize,
        ]),download=True),
        batch_size=args.batch_size, shuffle=True,
        num_workers=args.workers, pin_memory=True, worker_init_fn=seed_worker)

@peymanrostami does it work?