我有三个并行的过程。两个handleWorker和一个aggregateSum，两个handleWorker进程将从两个连接并行接收值，而第三个进程即aggregateSum将计算两个{{1 }}。如何同步他们的工作，以便在完成两个handleWorker的值收集工作后aggregateSum开始工作？
handleWorker此代码尝试使用from multiprocessing import Process, Queue, Value, Manager, Lock
def handleWorker(port,gradients_q,done_flag,global_avg,ack_q,n,lock):
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
print("Connecting to port : ", port)
s.bind((TCP_IP, port))
s.listen(5)
conn, addr = s.accept()
print('Connection address:', addr)
k=0
while 1:
size = safe_recv(17,conn)
size = pickle.loads(size)
data = safe_recv(size,conn)
local_worker_gradients = pickle.loads(data)
gradients_q.put(local_worker_gradients)
while(done_flag.value == 0):
pass
size = len(global_avg.value)
size = pickle.dumps(size, pickle.HIGHEST_PROTOCOL)
conn.sendall(size)
conn.sendall(global_avg.value)
ack_q.put(1)
k=k+1
if(k==(n+1)):
break
conn.close()
s.close()
def aggregateSum(gradients_q,done_flag, global_avg, ack_q,lock):
global global_avg
global done_flag
global global_sum
while(1):
global_sum = []
for i in range(MAX_NUMBER_WORKERS):
local_worker_gradients = gradients_q.get()
if(i == 0):
global_sum = local_worker_gradients
else:
add_local_gradients(global_sum, local_worker_gradients)
avg = average_gradients(global_sum)
global_avg.value = pickle.dumps(avg, pickle.HIGHEST_PROTOCOL)
done_flag.value = 1
for i in range(MAX_NUMBER_WORKERS):
val = ack_q.get()
done_flag.value = 0
def main(argv=None):
lock = Lock()
manager = Manager()
global_avg = manager.Value(c_char_p, "")
done_flag = manager.Value('i', 0)
gradients_q = Queue()
ack_q = Queue()
master_process = Process(target=aggregateSum, args=(gradients_q,done_flag, global_avg, ack_q,lock))
master_process.start()
port = int(sys.argv[1])
process_list = []
for i in range(MAX_NUMBER_WORKERS):
process_port = port + i + 1
p = Process(target=handleWorker, args=(process_port,gradients_q,done_flag,global_avg, ack_q, n, lock))
p.start()
process_list.append(p)
for p in process_list:
p.join()
进行同步，但是运行了几步后仍然卡住。