fluke#
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:
flukeis 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:
flukeis 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:
flukeimplements state-of-the-art federated learning algorithms and datasets and is regularly updated to include the latest affirmed techniques.Simulated: in
flukethe 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#
Is it your first time using fluke? Start here.
Explore the fluke API.
Check out the tutorials to get acquainted with fluke.