Python Multiprocess diff between Windows and Linux

本文介绍了一个关于Python多进程环境下全局变量BBOX在不同操作系统(OSX、Ubuntu及Windows)间的传递问题。作者发现该变量在Windows平台上的表现异常,并通过修改代码解决了这一问题。文中提供了解决方案的具体实现。

I have a script called jobrunner.py that calls class methods in main.py. See below...

# jobrunner.py
from multiprocessing import Process
import main
from main import BBOX

def _a(arg):
    f = main.a()
    print f.run()

def _b(arg):
    p = main.b()
    print p.run()

if __name__ == '__main__':
    world = '-180,180,-90,90'
    BBOX.append(world.split(','))

    p1 = Process(target=_a, args=("1",))
    p2 = Process(target=_b, args=("1",))

    p1.start()
    p2.start()

    p1.join()
    p2.join()

Processes _a and _b are invoked without any problems on OSX and Ubuntu but when I try to run the same thing on Windows (same version of python and all), it fails saying that index is out of range. This leads me to believe that the "global" variable BBOX is not being set or passed between modules on the Windows platform. Has anyone else seen something like this and know how to fix it?

Adam

UPDATE: I figured it out even though it might be a total hack...See below!

# jobrunner.py
from multiprocessing import Process
import main
from main import BBOX

def _a(arg):
    BBOX.append(arg) #This is the key
    f = main.a()
    print f.run()

def _b(arg):
    BBOX.append(arg) #This is the key
    p = main.b()
    print p.run()

if __name__ == '__main__':
    world = '-180,180,-90,90'
    BBOX.append(world.split(','))

    p1 = Process(target=_a, args=(BBOX[0],))
    p2 = Process(target=_b, args=(BBOX[0],))

    p1.start()
    p2.start()

    p1.join()
    p2.join()
内容概要:本文围绕六自由度机械臂的人工神经网络(ANN)设计展开,重点研究了正向与逆向运动学求解、正向动力学控制以及基于拉格朗日-欧拉法推导逆向动力学方程,并通过Matlab代码实现相关算法。文章结合理论推导与仿真实践,利用人工神经网络对复杂的非线性关系进行建模与逼近,提升机械臂运动控制的精度与效率。同时涵盖了路径规划中的RRT算法与B样条优化方法,形成从运动学到动力学再到轨迹优化的完整技术链条。; 适合人群:具备一定机器人学、自动控制理论基础,熟悉Matlab编程,从事智能控制、机器人控制、运动学六自由度机械臂ANN人工神经网络设计:正向逆向运动学求解、正向动力学控制、拉格朗日-欧拉法推导逆向动力学方程(Matlab代码实现)建模等相关方向的研究生、科研人员及工程技术人员。; 使用场景及目标:①掌握机械臂正/逆运动学的数学建模与ANN求解方法;②理解拉格朗日-欧拉法在动力学建模中的应用;③实现基于神经网络的动力学补偿与高精度轨迹跟踪控制;④结合RRT与B样条完成平滑路径规划与优化。; 阅读建议:建议读者结合Matlab代码动手实践,先从运动学建模入手,逐步深入动力学分析与神经网络训练,注重理论推导与仿真实验的结合,以充分理解机械臂控制系统的设计流程与优化策略。
watch -n 1 nvidia-smi Every 1.0s: nvidia-smi cluster-0upmpamemeipxipkw2-node0002: Mon Sep 22 08:34:12 2025 [HAMI-core Msg(578:140531917454208:libvgpu.c:836)]: Initializing..... Mon Sep 22 08:34:12 2025 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 560.35.03 Driver Version: 560.35.03 CUDA Version: 12.6 | |-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA A30 On | 00000000:00:06.0 Off | 0 | | N/A 66C P0 163W / 165W | 11011MiB / 12288MiB | 78% Default | | | | Disabled | +-----------------------------------------+------------------------+----------------------+ +-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| +-----------------------------------------------------------------------------------------+ [HAMI-core Msg(578:140531917454208:multiprocess_memory_limit.c:497)]: Calling exit handler 578 watch -n 1 nvidia-smi Every 1.0s: nvidia-smi cluster-0upmpamemeipxipkw2-node0001: Mon Sep 22 08:34:25 2025 Mon Sep 22 08:34:25 2025 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 560.35.03 Driver Version: 560.35.03 CUDA Version: 12.6 | |-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA A30 On | 00000000:00:06.0 Off | 0 | | N/A 65C P0 167W / 165W | 21765MiB / 24576MiB | 83% Default | | | | Disabled | +-----------------------------------------+------------------------+----------------------+ +-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| +-----------------------------------------------------------------------------------------+ 比较一下
09-23
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