Training gets stuck when using SyncBN
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 9k
- Forks
- 1.5k
- Avg merge
- 2d 4h
- Merged PRs (30d)
- 3
Description
DistributedDataParallel works great for me. But when I use it together with the synchronized batch normalization, either the Python version or the optimized version, the training will get stuck after a few iterations and the code gives the following warning:
/home/heilaw/.conda/envs/CornerNet/lib/python3.6/multiprocessing/semaphore_tracker.py:143: UserWarning: semaphore_tracker: There appear to be 1 leaked semaphores to clean up at shutdown
len(cache))
Any idea how I should debug it?
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
Start by reproducing training with PyTorch DistributedDataParallel and synchronized batch normalization, testing both the Python and optimized versions. Inspect where execution stops after a few iterations and use the reported semaphore_tracker warning as a debugging clue. Done means training completes without getting stuck or leaking semaphores.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- distributed-systems, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100