The Flower Team is excited to announce the release of Flower 1.13.1 stable and it’s packed with updates!
Flower is a friendly framework for collaborative AI and data science.
It makes novel approaches such as federated learning, federated evaluation,
federated analytics, and fleet learning accessible to a wide audience of researchers and engineers.
Thanks to our contributors
We would like to give our special thanks to all the contributors who made the new version of Flower possible (in git shortlog
order):
Adam Narozniak
, Charles Beauville
, Heng Pan
, Javier
, Robert Steiner
What’s new?
-
Fix
SimulationEngine
Executor for SuperLink (#4563, #4568, #4570)Resolved an issue that prevented SuperLink from functioning correctly when using the
SimulationEngine
executor. -
Improve FAB build and install (#4571)
An updated FAB build and install process produces smaller FAB files and doesn’t rely on
pip install
any more. It also resolves an issue where all files were unnecessarily included in the FAB file. Theflwr
CLI commands now correctly pack only the necessary files, such as.md
,.toml
and.py
, ensuring more efficient and accurate packaging. -
Update
embedded-devices
example (#4381)The example now uses the
flwr run
command and the Deployment Engine. -
Update Documentation (#4566, #4569, #4560, #4556, #4581, #4537, #4562, #4582)
Enhanced documentation across various aspects, including updates to translation workflows, Docker-related READMEs, and recommended datasets. Improvements also include formatting fixes for dataset partitioning docs and better references to resources in the datasets documentation index.
-
Update Infrastructure and CI/CD (#4577, #4578, #4558, #4551, #3356, #4559, #4575)
-
General improvements (#4557, #4564, #4573, #4561, #4579, #4572)
As always, many parts of the Flower framework and quality infrastructure were improved and updated.