Request for Support adaptive_instance_normalization for executorch
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- Dominant language
- Python
- Stars
- 5k
- Forks
- 1.2k
- Avg merge
- 2d 10h
- Merged PRs (30d)
- 581
Description
🚀 The feature, motivation and pitch
I am developing a Realtime Style Transfer for Android Mobile and It's slow because it I could not enable since It could not support adaptive_instance_normalization or even instance normalization.
Alternatives
No response
Additional context
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RFC (Optional)
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Contributor 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.
Research direction
The issue names adaptive_instance_normalization and instance normalization but provides no file or test paths. Start by locating the corresponding operator support and its ExecuTorch Android entry point, then check existing operator tests. Done means the requested normalization path works for the stated realtime Android style-transfer use case with coverage for the supported behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- android, pytorch
- Domain
- embedded-iot, machine-learning, mobile-dev
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100