fusedlayernorm does not work with elementwise_affine=False
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 9k
- Forks
- 1.5k
- Avg merge
- 2d 4h
- Merged PRs (30d)
- 3
Description
in distributed training setting with apex disitributed data parallel, when fused layernorm is used with elementwise_affine=False, doing convolution or elementwise sum or elementwise multiplication after fused layer norm throw following error
RuntimeError: CUDA error: invalid configuration argument
but torch nn layernorm works properly with elementwise_affine=False in same setting
also if i use elementwise_affine=True with fused layer norm in same setting, it works properly.
what is problem?
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 fused layernorm under Apex distributed data parallel with elementwise_affine=False, followed by convolution or an elementwise sum or multiplication. Compare the failing case with torch.nn LayerNorm and with elementwise_affine=True, then trace the invalid configuration argument to identify what differs; done means the failing operations work in the reported distributed setting.
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
- Mostly clear
- Newbie friendliness
- 30/100