Use eager mode quantize_ with QDQLayout for non-delegated quantized ops in ExecuTorch
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Description
🚀 The feature, motivation and pitch
This is recommendation 5 in post: https://fb.workplace.com/groups/pytorch.edge2.team/permalink/1168405054415345/
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 points to recommendation 5 in the linked Workplace post; read that recommendation first for the intended behavior. Then investigate ExecuTorch's handling of non-delegated quantized ops, QDQLayout, and eager-mode quantize_; completion means supporting that combination for the targeted ops.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- embedded-iot, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100