Merge pull request #265 from kozistr/feature/adamg-optimizer

[Feature] Implement AdamG optimizer

Author: kozistr

README.md

@@ -10,7 +10,7 @@
 
 **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, **74 optimizers (+ `bitsandbytes`, `qgalore`)**, **16 lr schedulers**, and **13 loss functions** are supported!  
+Currently, **75 optimizers (+ `bitsandbytes`, `qgalore`)**, **16 lr schedulers**, and **13 loss functions** are supported!  
 
 Highly inspired by [pytorch-optimizer](https://github.com/jettify/pytorch-optimizer).
 
@@ -172,6 +172,7 @@ supported_optimizers = get_supported_optimizers()
 | StableAdamW   | *Stable and low-precision training for large-scale vision-language models*                        |                                                                                                                | <https://arxiv.org/abs/2304.13013>                                                         | [cite](https://ui.adsabs.harvard.edu/abs/2023arXiv230413013W/exportcitation)                                                        |
 | AdamMini      | *Use Fewer Learning Rates To Gain More*                                                           | [github](https://github.com/zyushun/Adam-mini)                                                                 | <https://arxiv.org/abs/2406.16793>                                                         | [cite](https://github.com/zyushun/Adam-mini?tab=readme-ov-file#citation)                                                            |
 | TRAC          | *Adaptive Parameter-free Optimization*                                                            | [github](https://github.com/ComputationalRobotics/TRAC)                                                        | <https://arxiv.org/abs/2405.16642>                                                         | [cite](https://ui.adsabs.harvard.edu/abs/2024arXiv240516642M/exportcitation)                                                        |
+| AdamG         | *Towards Stability of Parameter-free Optimization*                                                |                                                                                                                | <https://arxiv.org/abs/2405.04376>                                                         | [cite](https://ui.adsabs.harvard.edu/abs/2024arXiv240504376P/exportcitation)                                                        |
 
 ## Supported LR Scheduler
 

docs/changelogs/v3.1.1.md

@@ -5,6 +5,8 @@
 * Implement `TRAC` optimizer. (#263)
     * [Fast TRAC: A Parameter-Free Optimizer for Lifelong Reinforcement Learning](https://arxiv.org/abs/2405.16642)
 * Support `AdamW` optimizer via `create_optimizer()`. (#263)
+* Implement `AdamG` optimizer. (#264, #265)
+    * [Towards Stability of Parameter-free Optimization](https://arxiv.org/abs/2405.04376) 
 
 ### Bug
 

docs/index.md

@@ -10,7 +10,7 @@
 
 **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, **74 optimizers (+ `bitsandbytes`, `qgalore`)**, **16 lr schedulers**, and **13 loss functions** are supported!  
+Currently, **75 optimizers (+ `bitsandbytes`, `qgalore`)**, **16 lr schedulers**, and **13 loss functions** are supported!  
 
 Highly inspired by [pytorch-optimizer](https://github.com/jettify/pytorch-optimizer).
 
@@ -172,6 +172,7 @@ supported_optimizers = get_supported_optimizers()
 | StableAdamW   | *Stable and low-precision training for large-scale vision-language models*                        |                                                                                                                | <https://arxiv.org/abs/2304.13013>                                                         | [cite](https://ui.adsabs.harvard.edu/abs/2023arXiv230413013W/exportcitation)                                                        |
 | AdamMini      | *Use Fewer Learning Rates To Gain More*                                                           | [github](https://github.com/zyushun/Adam-mini)                                                                 | <https://arxiv.org/abs/2406.16793>                                                         | [cite](https://github.com/zyushun/Adam-mini?tab=readme-ov-file#citation)                                                            |
 | TRAC          | *Adaptive Parameter-free Optimization*                                                            | [github](https://github.com/ComputationalRobotics/TRAC)                                                        | <https://arxiv.org/abs/2405.16642>                                                         | [cite](https://ui.adsabs.harvard.edu/abs/2024arXiv240516642M/exportcitation)                                                        |
+| AdamG         | *Towards Stability of Parameter-free Optimization*                                                |                                                                                                                | <https://arxiv.org/abs/2405.04376>                                                         | [cite](https://ui.adsabs.harvard.edu/abs/2024arXiv240504376P/exportcitation)                                                        |
 
 ## Supported LR Scheduler
 

docs/optimizer.md

@@ -44,6 +44,10 @@
     :docstring:
     :members:
 
+::: pytorch_optimizer.AdamG
+    :docstring:
+    :members:
+
 ::: pytorch_optimizer.AdaMod
     :docstring:
     :members: