Update pytorch-optimizer requirement from ~=3.8.0 to ~=3.8.1

[dependabot]

Updates the requirements on pytorch-optimizer to permit the latest version.

Release notes

Sourced from pytorch-optimizer's releases.

pytorch-optimizer v3.8.1

Change Log

Feature

• Implement FriendlySAM optimizer. (#424, #434)
  • Friendly Sharpness-Aware Minimization
• Implement AdaGO optimizer. (#436, #437)
  • AdaGrad Meets Muon: Adaptive Stepsizes for Orthogonal Updates
• Update EXAdam optimizer to the latest version. (#438)
• Update EmoNavi optimizer to the latest version. (#433, #439)
• Implement Conda optimizer. (#440, #441)
  • Conda: Column-Normalized Adam for Training Large Language Models Faster

Update

• Accept the GaloreProjector parameters in the init params of the Conda optimizer. (#443, #444)

Bug

• Fix NaN problem when grad norm is zero in StableSPAM optimizer. (#431)

Docs

• Update the documentation page. (#428)

Contribution

thanks to @​liveck, @​AhmedMostafa16

Changelog

Sourced from pytorch-optimizer's changelog.

v3.8.1

Change Log

Feature

• Implement FriendlySAM optimizer. (#424, #434)
  • Friendly Sharpness-Aware Minimization
• Implement AdaGO optimizer. (#436, #437)
  • AdaGrad Meets Muon: Adaptive Stepsizes for Orthogonal Updates
• Update EXAdam optimizer to the latest version. (#438)
• Update EmoNavi optimizer to the latest version. (#433, #439)
• Implement Conda optimizer. (#440, #441)
  • Conda: Column-Normalized Adam for Training Large Language Models Faster

Update

• Accept the GaloreProjector parameters in the init params of the Conda optimizer. (#443, #444)

Bug

• Fix NaN problem when grad norm is zero in StableSPAM optimizer. (#431)

Docs

• Update the documentation page. (#428)

Contribution

thanks to @​liveck, @​AhmedMostafa16

v3.8.0

Change Log

Feature

• Implement EmoNeco and EmoZeal optimizers. (#407)
• Implement Refined Schedule-Free AdamW optimizer. (#409, #414)
  • Through the River: Understanding the Benefit of Schedule-Free Methods for Language Model Training
  • You can use this variant by setting decoupling_c parameter in the ScheduleFreeAdamW optimizer.
• Add more built-in optimizers, NAdam, RMSProp, and LBFGS optimizers. (#415)
• Support cautious variant for Muon optimizer. (#417)
• Separate distributed functionality from Muon to DistribtuedMuon optimizer. (#418)
• Implement StochasticAccumulator, which is a gradient hook. (#418)
  • stochastic optimizer

Update

• Re-implement Muon and AdaMuon optimizers based on the recent official implementation. (#408, #410)

... (truncated)

Commits

• 657092f build(version): v3.8.1 (#446)
• 56c2be0 [Update] Expose the parameters of the GaloreProjector to the init params of...
• 63f6623 [Feature] Implement Conda optimizer (#441)
• aa70cc9 [Update] EmoNavi optimizer to the latest version (#439)
• 0c0f48f [Update] Eliminate numpy usage and update learning rate application from EXAd...
• 9dd83d0 [Feature] Implement AdaGO optimizer (#437)
• 3ee5925 [Update] Introduce pyright for type checking (#435)
• 0a671c9 [Feature] Implement FriendlySAM optimizer (#434)
• 45e00ec Update spam.py (#431)
• bf711d8 [Dependency] Remove isort (#429)
• Additional commits viewable in compare view

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[dependabot]

Looks like pytorch-optimizer is up-to-date now, so this is no longer needed.