FedJust was projected to be a fully adjustable code base that takes off the need to write boilerplate code for Federated Learning. Its components are fully modifiable building blocks that can be adjusted to your needs in a few lines of code. FedJust was designed to be a minimalist Python boilerplate for running Federated simulations (on a single or multiple GPUs at the same time). It does not aim to work as a Federated framework for actual communication between the devices, as there are already frameworks for doing that, e.g. Flower or part of PySyft. However, the niche of a well-documented and easily adjustable framework for the customization of FL experiments is still open - hence a FedJust tries to deliver the most straightforward boilerplate ecosystem that you may need for performing decentralised simulations in a controlled environment.
As FedJust was designed to be an easy-to-use boilerplate, it comes in several different ways to use it.
Python pip
As FedJust is registered in the Python Package Index (PyPI), it can be downloaded using the pip install command. Simply run:
pip install fedjust
Template Cloning
This GitHub repository is set up as a public template repository. It means, that it is possible to simply clone it and use it as a standalone repository without actually forking it. The package is built with the help of Poetry. To install the project together with a virtual environment, navigate to the main folder and run:
poetry install.
The virtual environment will be installed together with the required dependencies.
The current version of the repository contains only a limited version of FedJust and a preliminary draft of the documentation. More is coming soon!
The full documentation can be found at FedJust. The documentation will be updated with incremental changes.