openvinotoolkit / openvinotoolkit/nncf
[TorchFX][Optimization] Run eliminate dead code once for constant correction commands
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- Python
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Description
🚀 Feature request
https://github.com/openvinotoolkit/nncf/pull/2882/files#r1735077003
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Look like eliminate_dead_code should be run ones after apply all bias_update transormation.
Or maybe will be better to use something like self.erase_node(old_constant_node) to remove only old constant node to avoid loops for all nodes.
As i understand eliminate_dead_code here removes only old constant node. And it's actual for all usage eliminate_dead_code in transformation.py. -
We can do it, but we should give up on transformations and move to commands for that. Leaf insertion transformation not expecting eliminate_dead_code call yet model transformer could not split bias correction and leaf insertion commands apart
Feature Use Case
No response
Are you going to submit a PR?
- Yes I'd like to help by submitting a PR!
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 in transformation.py and trace the TorchFX bias_update transformations and their uses of eliminate_dead_code. Compare the proposed single cleanup after all bias corrections with removing the old constant node or moving to commands; done means the selected approach handles constant correction without unnecessary repeated cleanup or missed node removal.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100