Optimized pillow-simd needed to leverage new GPU instances
- 主要語言
- Python
- 星號
- 2.7k
- 分支
- 1k
- 平均合併
- 7 天 14 小時
- 30 天內合併 PR
- 2
描述
(Copied from https://www.kaggle.com/dansbecker/running-kaggle-kernels-with-a-gpu/code#328307 as requested by @sebbov ).
With the limited CPU available, being able to quickly read and manipulate images is important. Can I suggest you install pillow-simd with an optimized jpeg library? It will reduce CPU use by around 2-4x when training models, which will dramatically increase the utility of these new instances. The step by step instructions for installing it have been kindly provided by Soumith Chintala here (note that without these exact steps pillow-simd will not use libjpeg-turbo, even if you have it installed as your system libjpeg):
https://gist.github.com/soumith/01da3874bf014d8a8c53406c2b95d56b
I'm not familiar enough with docker to know what PR to send in exactly - hopefully this is enough info for the in-house experts to set it up.
貢獻指南
這個儲存庫沒有索引到貢獻指南
評估
這個 Issue 還沒有評估資料。