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Merge pull request #242 from kozistr/feature/fadam-optimizer
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[Feature] Implement FAdam optimizer
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kozistr authored Jun 2, 2024
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3 changes: 2 additions & 1 deletion README.md
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**pytorch-optimizer** is optimizer & lr scheduler collections in PyTorch.
I just re-implemented (speed & memory tweaks, plug-ins) the algorithm while based on the original paper. Also, It includes useful and practical optimization ideas.
Currently, **67 optimizers (+ `bitsandbytes`)**, **11 lr schedulers**, and **13 loss functions** are supported!
Currently, **68 optimizers (+ `bitsandbytes`)**, **11 lr schedulers**, and **13 loss functions** are supported!

Highly inspired by [pytorch-optimizer](https://github.com/jettify/pytorch-optimizer).

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| Adalite | *Adalite optimizer* | [github](https://github.com/VatsaDev/adalite) | <https://github.com/VatsaDev/adalite> | [cite](https://github.com/VatsaDev/adalite) |
| bSAM | *SAM as an Optimal Relaxation of Bayes* | [github](https://github.com/team-approx-bayes/bayesian-sam) | <https://arxiv.org/abs/2210.01620> | [cite](https://ui.adsabs.harvard.edu/abs/2022arXiv221001620M/exportcitation) |
| Schedule-Free | *Schedule-Free Optimizers* | [github](https://github.com/facebookresearch/schedule_free) | <https://github.com/facebookresearch/schedule_free> | [cite](https://github.com/facebookresearch/schedule_free) |
| FAdam | *Adam is a natural gradient optimizer using diagonal empirical Fisher information* | [github](https://github.com/lessw2020/fadam_pytorch) | <https://arxiv.org/abs/2405.12807> | [cite](https://ui.adsabs.harvard.edu/abs/2024arXiv240512807H/exportcitation) |

## Supported LR Scheduler

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15 changes: 15 additions & 0 deletions docs/changelogs/v3.0.1.md
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## Change Log

### Feature

* Implement `FAdam` optimizer. (#241, #242)
* [Adam is a natural gradient optimizer using diagonal empirical Fisher information](https://arxiv.org/abs/2405.12807)

### Bug

* Wrong typing of reg_noise. (#239, #240)
* Lookahead`s param_groups attribute is not loaded from checkpoint. (#237, #238)

## Contributions

thanks to @michaldyczko
3 changes: 2 additions & 1 deletion docs/index.md
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**pytorch-optimizer** is optimizer & lr scheduler collections in PyTorch.
I just re-implemented (speed & memory tweaks, plug-ins) the algorithm while based on the original paper. Also, It includes useful and practical optimization ideas.
Currently, **67 optimizers (+ `bitsandbytes`)**, **11 lr schedulers**, and **13 loss functions** are supported!
Currently, **68 optimizers (+ `bitsandbytes`)**, **11 lr schedulers**, and **13 loss functions** are supported!

Highly inspired by [pytorch-optimizer](https://github.com/jettify/pytorch-optimizer).

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| Adalite | *Adalite optimizer* | [github](https://github.com/VatsaDev/adalite) | <https://github.com/VatsaDev/adalite> | [cite](https://github.com/VatsaDev/adalite) |
| bSAM | *SAM as an Optimal Relaxation of Bayes* | [github](https://github.com/team-approx-bayes/bayesian-sam) | <https://arxiv.org/abs/2210.01620> | [cite](https://ui.adsabs.harvard.edu/abs/2022arXiv221001620M/exportcitation) |
| Schedule-Free | *Schedule-Free Optimizers* | [github](https://github.com/facebookresearch/schedule_free) | <https://github.com/facebookresearch/schedule_free> | [cite](https://github.com/facebookresearch/schedule_free) |
| FAdam | *Adam is a natural gradient optimizer using diagonal empirical Fisher information* | [github](https://github.com/lessw2020/fadam_pytorch) | <https://arxiv.org/abs/2405.12807> | [cite](https://ui.adsabs.harvard.edu/abs/2024arXiv240512807H/exportcitation) |

## Supported LR Scheduler

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4 changes: 4 additions & 0 deletions docs/optimizer.md
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:docstring:
:members:

::: pytorch_optimizer.FAdam
:docstring:
:members:

::: pytorch_optimizer.Fromage
:docstring:
:members:
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