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对大批量数据进行人像分割推理时触发Linux OOM机制导致程序被kill #3486
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这可能是一个内存泄漏的bug,我们会尽快修复 |
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@enemy1205 我们这边似乎没有办法复现这个问题,能否进一步提供你的环境信息,例如paddle版本等 |
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问题确认 Search before asking
请提出你的问题 Please ask your question
按照Readme.md参考人像分割教程,使用
PaddleSeg/contrib/PP-HumanSeg/src/seg_demo.py
由于需要进行大批量视频的分割,因此对seg_demo.py文件进行了一定处理简化,由于仅需二值图,故删去较多不必要部分
此外其他文件未作修改,使用推理模型
human_pp_humansegv1_server_512x512_inference_model_with_softmax
可执行脚本:
tmux 挂至后台后(直接命令行运行情况相同),将会正常运行一段时间
显存占用 2~3G/24G(3090Ti),显存及显卡利用率都比较正常
但是,随着时间推移,大约每半分钟将会占用1G内存并且累积,最后直至触发Linux OOM机制导致被kill掉。
尝试过数次,以及调试,在每个视频的处理完后,它确实会释放部分内存,但每个视频增加的内存>释放的内存,,,,
最终导致250GB+的内存也被占满。。
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