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https://github.com/beiyuouo/fedhf
🔨 A Flexible Federated Learning Simulator for Heterogeneous and Asynchronous.
https://github.com/beiyuouo/fedhf
distributed-machine-learning federated-learning federated-learning-framework fedhf machine-learning python
Last synced: 21 days ago
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🔨 A Flexible Federated Learning Simulator for Heterogeneous and Asynchronous.
- Host: GitHub
- URL: https://github.com/beiyuouo/fedhf
- Owner: beiyuouo
- License: apache-2.0
- Created: 2021-10-11T15:50:43.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2022-08-19T07:51:08.000Z (about 2 years ago)
- Last Synced: 2024-10-07T14:24:05.099Z (about 1 month ago)
- Topics: distributed-machine-learning, federated-learning, federated-learning-framework, fedhf, machine-learning, python
- Language: Python
- Homepage: https://www.bj-yan.top/fedhf
- Size: 905 KB
- Stars: 20
- Watchers: 1
- Forks: 20
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Contributing: docs/contributing.md
- License: LICENSE
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README
# FedHF
[FedHF](https://github.com/beiyuouo/fedhf) is a loosely coupled, **H**eterogeneous resource supported, and **F**lexible federated learning framework.
*Accelerate your research*
![](https://img.shields.io/github/stars/beiyuouo/fedhf?style=flat-square) ![](https://img.shields.io/github/forks/beiyuouo/fedhf?style=flat-square) ![https://www.bj-yan.top/fedhf/](https://img.shields.io/badge/document-building-blue?style=flat-square) ![](https://img.shields.io/github/languages/code-size/beiyuouo/fedhf?style=flat-square) ![](https://img.shields.io/github/issues/beiyuouo/fedhf?style=flat-square) ![](https://img.shields.io/github/issues-pr/beiyuouo/fedhf?style=flat-square) ![](https://img.shields.io/pypi/pyversions/fedhf?style=flat-square) ![](https://img.shields.io/pypi/l/fedhf?style=flat-square) [![Downloads](https://pepy.tech/badge/fedhf)](https://pepy.tech/project/fedhf)
[![Discord](https://img.shields.io/discord/942746457855889469.svg?logo=discord&logoColor=white&logoWidth=20&labelColor=7289DA&label=Discord&style=flat-square)](https://discord.gg/AsvX9Q75)
## Features
- [x] Losely coupled
- [x] Heterogeneous resource supported
- [x] Flexible federated learning framework
- [x] Support for asynchronous aggregation
- [x] Support for multiple federated learning algorithms## Algorithms Supported
### Synchronous Aggregation
- [x] **[FedAvg]** Communication-Efficient Learning of Deep Networks from Decentralized Data(*AISTAT*) [[paper]](https://arxiv.org/abs/1602.05629.pdf)
### Asynchronous Aggregation
- [x] **[FedAsync]** Asynchronous Federated Optimization(*OPT2020*) [[paper]](https://arxiv.org/abs/1903.03934)
### Tiered Aggregation
- [ ] **[TiFL]** TiFL: A Tier-based Federated Learning System (*HPDC 2020*) [[paper]](https://dl.acm.org/doi/abs/10.1145/3369583.3392686)
## Getting Start
```sh
pip install fedhf# If you want to use wandb to view log, please login first
wandb login
```You can see the [Document](https://www.bj-yan.top/fedhf/) for more details.
## Contributing
For more information, please see the [Contributing](https://www.bj-yan.top/fedhf/contributing/) page.
## Citation
> *In progress*
## Licence
This work is provided under [Apache License Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).
## Acknowledgement
Many thanks to [FedLab](https://github.com/SMILELab-FL/FedLab) and [FedML](https://github.com/FedML-AI/FedML) for their great work.