Flower: A Friendly Federated Learning Framework
Flower: A Friendly Federated Learning Framework
ScalabilityFlower was built to enable real-world systems with a large number of clients. Researchers used Flower to run workloads with tens of millions of clients.ML Framework AgnosticFlower is compatible with most existing and future machine learning frameworks. You love Keras? Great. You prefer PyTorch? Awesome. Raw NumPy, no automatic differentiation? You rock!Cloud, Mobile, Edge & BeyondFlower enables research on all kinds of servers and devices, including mobile. AWS, GCP, Azure, Android, iOS, Raspberry Pi, and Nvidia Jetson are all compatible with Flower.Research to ProductionFlower enables ideas to start as research projects and then gradually move towards production deployment with low engineering effort and proven infrastructure.Platform IndependentFlower is interoperable with different operating systems and hardware platforms to work well in heterogeneous edge device environments.UsabilityIt's easy to get started. 20 lines of Python is enough to build a full federated learning system. Check the code examples to get started with your favorite framework.