OpenMOSS / OpenMOSS/MOSS-Transcribe-Diarize
CUDA out of memory.
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 2k
- Forks
- 126
- Avg merge
- 17h 42m
- Merged PRs (30d)
- 5
Description
CUDA out of memory. Tried to allocate 20.92 GiB. GPU 0 has a total capacity of 8.00 GiB of which 2.22 GiB is free. Of the allocated memory 4.13 GiB is allocated by PyTorch, and 556.63 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
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 with the reported CUDA out-of-memory message and the linked PyTorch CUDA Memory Management documentation, especially the PYTORCH_CUDA_ALLOC_CONF guidance. Identify the repository entry point and workload that triggers the 20.92 GiB allocation; the issue does not name files, commands, or a test, so completion criteria need to be established before implementation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100