Megvii-BaseDetection / Megvii-BaseDetection/YOLOX
how to speed up the training process
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- Python
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Description
-
8卡V100，对10000张图片训300epoch，
-d 8 -b 64 --fp16，ETA显示需要17个小时。这正常吗？
可以调整哪些参数提高训练速度？发现CPU和内存使用率较低，显存基本跑满。 -
另外，训练开始时提示：
Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
这会影响训练速度吗？我在setup_env.py加上os.environ["OMP_NUM_THREADS"] = "8"，还是弹这个提示。怎么修改才有效？
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading setup_env.py and locating the training launcher that handles -d, -b, --fp16, and OMP_NUM_THREADS. Reproduce the reported configuration, then determine whether the issue needs a code change or documentation explaining expected training time, tuning options, and effective thread configuration.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100