Python的Multiprocessing多进程实例

最近在拜读RBG大神的faster-rcnn源码时发现他用了多进程去分阶段处理神经网络，原因如下：

    # --------------------------------------------------------------------------
    # Pycaffe doesn't reliably free GPU memory when instantiated nets are
    # discarded (e.g. "del net" in Python code). To work around this issue, each
    # training stage is executed in a separate process using
    # multiprocessing.Process.
    # --------------------------------------------------------------------------

大致意思是pycaffe在安装网络后当不再需要使用该部分网络时，不能靠谱的释放GPU显存资源。为解决这个问题，每一个训练阶段都做一个独立的进程去执行，也就用到了多进程。

python的多进程示例如下：

import multiprocessing as mp

def function_name():
    do sth.
    queue.put({'xxx': yyy})

mp_queue = mp.Queue()

p = mp.Process(target=function_name, kwargs=dict_ur_mp_kwargs)
p.start()
output = mp_queue.get()
p.join()

#其他进程
p = mp.Process(target=function_name, kwargs=dict_ur_mp_kwargs)
p.start()
output = mp_queue.get()
p.join()
#.......