Fix e2e regressions in HF export mask handling for QNN path
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 45/100
- Issue type
- Bug
- Clarity
- Mostly clear
- Activity status
- Active
- Tech stack
- python
- Domain
- machine-learning
Research direction
No file paths are named. Start with the focused unit tests and e2e cases for question-answering, fill-mask, and image-to-text-fp16, then trace the HF export QNN path around attention-mask normalization, decoder kwargs, and BLIP mask handling. Done means those three scenarios pass without the listed regressions.
Written by the indexing model from the issue text.
Description
Summary
DistilBERT fill-mask/question-answering and BLIP image-to-text e2e regressions.
Root causes
- SDPA attention mask dtype mismatch
- Decoder kwargs path incompatibility
- BLIP decoder mask shape mismatch
Fixes
- Export IO bool normalization for binary
attention_mask - Robust transformers compatibility patching
decoder_wrapperkwargs support- BLIP 2D mask pass-through
Validation
Focused unit tests and e2e tests passed: question-answering, fill-mask, and image-to-text-fp16.
- Dominant language
- Python
- Stars
- 41
- Forks
- 12
- Avg merge
- 19h 32m
- Merged PRs (30d)
- 51
Getting set up
- No Dockerfile or Docker Compose file
- No pull request template
- Read the contributing guide
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.
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