p2pfl 0.2.2

p2p Federated Learning framework

P2PFL - Federated Learning over P2P networks

P2PFL is a general-purpose open-source library for the execution (simulated and in real environments) of Decentralized Federated Learning systems, specifically making use of P2P networks and the Gossisp protocol.

✅ Features

• Easy to use and extend
• Fault tolerant
• Decentralized and Scalable
• Simulated (to-do, changed in 0.2.0) and real environments
• Privacy-preserving
• Framework agnostic

📥 Installation

Note We recommend using Python 3.9 or lower. We have found some compatibility issues with Python 3.10 and PyTorch.

👨🏼‍💻 For users

To install the library, you can simply run:

pip install p2pfl

Or you can install it from source:

git clone https://github.com/pguijas/p2pfl.git
cd p2pfl
pip install -e .

👨🏼‍🔧 For developers

To install the library for development we recommend using a virtual environment. For example, with pipenv:

pipenv install --requirements requirements.txt

📚 Documentation

• Documentation.

• Report of the end-of-degree project.

• Report for the award for the best open source end-of-degree project.

🚀 TO DO

Note Don't be shy, share your ideas with us!

• Agnostic installation with variants for different frameworks (include TensorFlow)
• Add secure channels and node authentication
• Improved simulation environment
• Control panel
• add FEMNIST example
• add typing
• New aggregation methods
• Hot node inclusion
• Secure aggregation
• Non trainable nodes (gossip nodes) to increase the efficiency of the network

👫 Contributing

Contributions are always welcome!

See CONTRIBUTING.md for ways to get started.

Please adhere to this project's code of conduct specified in CODE_OF_CONDUCT.md.

💬 Google Group

If you have any questions, or you to be notified of any updates, you can join the Google Group here.

📜 License

GNU General Public License, Version 3.0