Document end-to-end quantization journey in ExecuTorch
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- Dominant language
- Python
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Description
🚀 The feature, motivation and pitch
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Document how PTQ/QAT/quality validation looks in ET using the PT2E flow (the common flow implemented by all backends).
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Document advanced research flows (e.g., GPTQ, PARQ) using quantize_.
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
Start by locating the ExecuTorch documentation for the PT2E flow and the quantize_ APIs. Document the end-to-end PTQ, QAT, and quality-validation journey, then cover advanced flows such as GPTQ and PARQ. Done means both flow categories are documented clearly for ExecuTorch users.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100