How to decay your Learning Rate (PyTorch)
PyTorch implementation of ABEL LRScheduler based on weight-norm. If you find this work interesting, do consider starring the repository. If you use this in your research, don't forget to cite!
Original paper: https://arxiv.org/pdf/2103.12682v1.pdf
Docs: https://abel-pytorch.readthedocs.io/en/latest/
Installation
pip install abel-pytorch
Usage
import torch
from torch import nn, optim
from abel import ABEL
model = resnet18()
optim = optim.SGD(model.parameters(), 1e-3)
scheduler = ABEL(optim, 0.2)
for i, (images, labels) in enumerate(trainloader):
# forward pass...
optim.step()
scheduler.step()Cite original paper:
@article{lewkowycz2021decay,
title={How to decay your learning rate},
author={Lewkowycz, Aitor},
journal={arXiv preprint arXiv:2103.12682},
year={2021}
}
Cite this work:
@misc{abel2021pytorch,
author = {Vaibhav Balloli},
title = {A PyTorch implementation of ABEL},
year = {2021},
howpublished = {\url{https://github.com/tourdeml/abel-pytorch}}
}