https://github.com/borealisai/adaflood
https://github.com/borealisai/adaflood
Last synced: about 1 year ago
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- Host: GitHub
- URL: https://github.com/borealisai/adaflood
- Owner: BorealisAI
- License: other
- Created: 2024-08-12T22:30:27.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-21T21:33:06.000Z (almost 2 years ago)
- Last Synced: 2025-02-16T03:35:57.443Z (over 1 year ago)
- Language: Python
- Size: 3.65 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# Adaflood
[[Paper](https://openreview.net/pdf?id=2s5YU6CSEz)][[OpenReview](https://openreview.net/forum?id=2s5YU6CSEz)]
## Setup
Setup the pipeline by installing dependencies using the following command.
pretrained models and utils.
```bash
pip install -r requirements.txt
```
## Train
A model can be trained (with hyper-parameter search) using the following command.
```bash
bash scripts/run_sweep.sh -d $DATASET -m $MODEL -r $CRITERION
```
`$DATASET` can be chosen from `{uber_drop, cifar100}`, `$MODEL` can be chosen from `{intensity_free,thp_mix,resnet18,}`.
Also, `$CRITERION` can be chosen from `{cls,flood,iflood,aux,adaflood}` for classification and `{tpp,flood,iflood,aux,adaflood}` for TPP tasks.
Other configurations can be also easily modified using hydra syntax. Please refer to `scripts/run_sweep.sh` and [hydra](https://hydra.cc/docs/intro/) for further details.
## Citation
If you use this code or model for your research, please cite:
@article{bae2024adaflood,
title={AdaFlood: Adaptive Flood Regularization},
author={Bae, Wonho and Ren, Yi and Ahmed, Mohamad Osama and Tung, Frederick and Sutherland, Danica J and Oliveira, Gabriel L},
journal={Transactions on Machine Learning Research (TMLR)},
year={2024}
}
## Acknowledgment
The pipeline is built on [PyTorch-Lightning Hydra Template](https://github.com/ashleve/lightning-hydra-template).
Intensity free is based on [the original implementation](https://github.com/shchur/ifl-tpp) and THP+ is based on (Meta TPP](https://github.com/BorealisAI/meta-tpp).