NVIDIA-NeMo / NVIDIA-NeMo/Emerging-Optimizers

Add support for the normalized and orthogonal optimizers with matrix sign

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enhancement
Dominant language
Python
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274
Forks
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1d 3h
Merged PRs (30d)
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Description

Is your feature request related to a problem? Please describe.
The optimizer for normalized layers is introduced by Franz Cesista in https://leloykun.github.io/ponder/steepest-descent-stiefel/#6-bonus-a-muon-like-optimizer-for-the-embedding-and-unembedding-layers
and the optimizer for stiefel is introduced by Jianlin Su in https://kexue.fm/archives/11221

Further, Tilde has introduced a set of optimizers relaxing the strong constraints: https://www.tilderesearch.com/vignettes/gram-space

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Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reading the linked Muon-like, Stiefel, and Gram-space optimizer references to determine the intended normalized and orthogonal behaviors. Then inspect the repository's existing optimizer entry points and tests, which are not named in the issue; done means the requested matrix-sign-based optimizers are implemented with coverage for their expected behavior.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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