can ASP be used to form NM sparsity other than 2:4?
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Description
I have read the paper "Channel permutation for NM sparsity" . I guess it is a great job.
However, I am confused whether or not the codes that are publically available can be used to prune a network into the NM sparsity other than 2:4? E.g., 1:4, or 1:8.
If the codes can be used to realize the function as I say above, either directly or only with minor modifiction, please let me know.
Thank you anyway.
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Research direction
Start by locating the public ASP implementation and its pruning entry points, then check whether the code or documentation defines supported N:M ratios beyond 2:4. The issue would be complete when support for 1:4 or 1:8 is confirmed with a reproducible example, or the required scope and limitations are documented.
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Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100