fluke

v 0.7.9

Federated Learning Utility frameworK for Experimentation and research.

Made by researchers for researchers!

fluke is a benchmarking tool for Federated Learning (FL). It is designed to be flexible, easy to use, and easy to extend, and can be used to benchmark a wide variety of federated learning algorithms. fluke is meant for researchers and practitioners who want to quickly develop their own federated algorithm and test its performance against state-of-the-art algorithms on a variety of datasets and conditions. In fluke the federation is simulated.

Philosophy

fluke is designed to minimize the development overhead of adding new algorithms and performing experiments. It is built on the following principles:

  • Easy to use: fluke is designed to be easy to use. It is easy to install, to run, and to configure. Running a federated learning experiment is as simple as running a single command.

  • Easy to extend: fluke is designed to be easy to extend minimazing the overhead of adding new algorithms. Adding a new method is as simple as adding the definition of the client and the server.

  • Up-to-date: fluke implements state-of-the-art federated learning algorithms and datasets and is regularly updated to include the latest affirmed techniques.

  • Simulated: in fluke the federation is simulated. This means that the communication between the clients and the server is happens in a simulated channel and the data is not actually sent over the network. The simulated environment frees the user from aspects not related to the algorithm itself.

Explore fluke

Getting Started

Is it your first time using fluke? Start here.

./getting_started.html
API Reference

Explore the fluke API.

./api_reference.html
Tutorials

Check out the tutorials to get acquainted with fluke.

./tutorials.html