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svtr_tiny 性能优化 和 修改多卡启动方式为msrun #810
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``` | ||
**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/tutorials/experts/en/r2.3.1/parallel/msrun_launcher.html). |
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这里是不是链接mindspore 2.5.0的文档好一些
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文档上环境信息就是2.3.1,这边是考虑保持一致
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好的 了解 后续v0.5.0分支适配的pr会把这里修改掉
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后续统一修改为2.5分支
``` | ||
**Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/tutorials/experts/en/r2.3.1/parallel/msrun_launcher.html). |
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后续统一修改为2.5分支
configs/det/east/README_CN.md
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msrun --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/det/east/east_r50_icdar15.yaml | ||
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# 经验证,绑核在大部分情况下有性能加速,请配置参数并运行 | ||
export MS_ENABLE_NUMA=True |
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为什么numa和msrun的bind_core要同时加?
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我这边尝试一起加性能会有提升,只加bind_core性能不明显
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云上或者在容器跑numa绑核会有问题,这个应该只有裸机跑可以有效
Thank you for your contribution to the MindOCR repo.
Before submitting this PR, please make sure:
Motivation
1、GradSampler2D算子优化
2、多卡启动由mpirun修改为msrun
Test Plan
(How should this PR be tested? Do you require special setup to run the test or repro the fixed bug?)
Related Issues and PRs
(Is this PR part of a group of changes? Link the other relevant PRs and Issues here. Use https://help.github.com/en/articles/closing-issues-using-keywords for help on GitHub syntax)