DemonRangerOptimizer
pytorch-optimizer
| DemonRangerOptimizer | pytorch-optimizer | |
|---|---|---|
| 1 | 3 | |
| 23 | 2,946 | |
| - | - | |
| 0.0 | 3.1 | |
| over 3 years ago | about 1 month ago | |
| Python | Python | |
| - | Apache License 2.0 |
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DemonRangerOptimizer
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[R] AdasOptimizer Update: Cifar-100+MobileNetV2 Adas generalizes with Adas 15% better and 9x faster than Adam
The results are interesting, but in terms of novelty of the main theory - isn't it almost identical to Baydin et al.? https://arxiv.org/pdf/1703.04782.pdf It seems the difference may be in some implementation details, like using a running average for the past gradient. If it's useful, I implemented a bunch of optimizers with options to synergize different techniques (https://github.com/JRC1995/DemonRangerOptimizer) including hypergradient updates for stuffs (and taking into account decorrelated weight decay and per-parameter lrs for hypergradient lr) when I was bored before practically abandoning it all together. I didn't really run any experiments with it though, but some people tried although they may not have got any particularly striking results.
pytorch-optimizer
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[D]: Implementation: Deconvolutional Paragraph Representation Learning
The specific implementation is from (here)[https://github.com/jettify/pytorch-optimizer] since pytorch doesn't have it directly.
- VQGAN+CLIP : "RAdam" from torch_optimizer could not be imported ?
- [R] AdasOptimizer Update: Cifar-100+MobileNetV2 Adas generalizes with Adas 15% better and 9x faster than Adam
What are some alternatives?
ML-Optimizers-JAX - Toy implementations of some popular ML optimizers using Python/JAX
sam - SAM: Sharpness-Aware Minimization (PyTorch)
AdasOptimizer - ADAS is short for Adaptive Step Size, it's an optimizer that unlike other optimizers that just normalize the derivative, it fine-tunes the step size, truly making step size scheduling obsolete, achieving state-of-the-art training performance
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
imagenette - A smaller subset of 10 easily classified classes from Imagenet, and a little more French
Gradient-Centralization-TensorFlow - Instantly improve your training performance of TensorFlow models with just 2 lines of code!
simple-sam - Sharpness-Aware Minimization for Efficiently Improving Generalization
RAdam - On the Variance of the Adaptive Learning Rate and Beyond
PythonPID_Tuner - Python PID Tuner - Based on a FOPDT model obtained using a Open Loop Process Reaction Curve