A pytorch multiprocessing problem

pytorch_problem.py

import os

import torch


class Dataset(torch.utils.data.Dataset):
    arg = {'batch_size': 1}
    def __init__(self, arg):
        print('__init__')
        self.arg.update(arg)
#         self.arg = self.arg
        print(self.arg)

    def _worker_init_fn(self, *args):
        print('worker init')
        print(self.arg)

    def get_dataloader(self):
        return torch.utils.data.DataLoader(self, batch_size=None,
                                         num_workers=3,
                                         worker_init_fn=self._worker_init_fn,
                                         pin_memory=True,
                                         multiprocessing_context='spawn')

    def __getitem__(self, idx):
        return 0

    def __len__(self):
        return 5


def main():
    dataloader = Dataset({'batch_size': 2}).get_dataloader()
    for _ in dataloader:
        pass


if __name__ == '__main__':
    main()

I want workers to have {'batch_size': 2} but it turns out to print {'batch_size': 1}

Here is the output

__init__
{'batch_size': 2}
worker init
{'batch_size': 1}
worker init
{'batch_size': 1}
worker init
{'batch_size': 1}

Strange enough! If I add line 11 it works...