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() #.......