Megvii-BaseDetection / Megvii-BaseDetection/YOLOX
Is Fault-tolerant Training possible with YOLOX?
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- Dominant language
- Python
- Stars
- 10.6k
- Forks
- 2.5k
- PR merge metrics
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Description
It doesn't have to be a complete Fault-tolerant Training. I just need to be able to restart from the specified weight from the epoch where it was interrupted with the specified scheduler. The results do not have to be a rigorous reproduction of the results of complete training.
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
No files, tests, or entry points are named in the issue. Start by locating how checkpoint weights, interrupted epochs, and schedulers are currently specified; done means training can restart from the requested state without requiring exact reproduction of a complete run.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100