Megvii-BaseDetection / Megvii-BaseDetection/YOLOX
同一个数据集上训练，时间越来越长
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- Dominant language
- Python
- Stars
- 10.6k
- Forks
- 2.5k
- PR merge metrics
- No merged PRs in 30d
Description
您好，
感谢开源， clone最新的代码，使用2张3090训练相同的数据集，前面几个epoch的时间比较短，后面的epoch时间越来越长是为什么？
目前测试硬件（显卡，内存）都是稳定的。
Contributor guide
No contributing guide indexed for this repository
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
No file, test, or entry point is named. Start by reproducing training on the same dataset with two 3090 GPUs and compare per-epoch timing, data-loading behavior, and training logs; inspect the training and data pipeline only after establishing which stage slows down. Done means identifying a reproducible cause and documenting or fixing the slowdown with evidence that later epochs no longer progressively lengthen.
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
- 25/100