I want to have a model with shared memory (same model parameter, no training) across all processes, so it is necessary to use torch.multiprocessing.Process. And in addition, I want to have duplex communicator between master and all workers, can I combine PyTorch Process and python Pipe together ?
i.e. sending pipe connection heads as argument to PyTorch Process
from torch.multiprocessing import Process
from multiprocessing import Pipe

def worker(master_connection, worker_connection):
    do something

def master():
    master_connection, worker_connection = Pipe()
    process = Process(target=worker, args=[master_connection, worker_connection])
    process.start()
    process.join()