Flower Framework Documentation

Welcome to Flower’s documentation. Flower is a friendly federated learning framework.

Join the Flower Community

The Flower Community is growing quickly - we’re a friendly group of researchers, engineers, students, professionals, academics, and other enthusiasts.

Join us on Slack

Flower Framework

The user guide is targeted at researchers and developers who want to use Flower to bring existing machine learning workloads into a federated setting. One of Flower’s design goals was to make this simple. Read on to learn more.

Tutorials

A learning-oriented series of federated learning tutorials, the best place to start.

Tutorial

• What is Federated Learning?
• Get started with Flower
• Use a federated learning strategy
• Build a strategy from scratch
• Customize the client

QUICKSTART TUTORIALS: PyTorch | TensorFlow | MLX | 🤗 Transformers | JAX | Pandas | fastai | PyTorch Lightning | scikit-learn | XGBoost | Android | iOS

How-to Guides

Problem-oriented how-to guides show step-by-step how to achieve a specific goal.

How-to Guides

• Build
  • Install Flower
  • Configure Clients
  • Design stateful ClientApps
  • Use strategies
  • Implement strategies
  • Aggregate evaluation results
  • Save and Load Model Checkpoints
  • Use Built-in Mods
  • Use Differential Privacy
  • Implement FedBN
  • Use CLI JSON output
  • Upgrade to Flower 1.0
  • Upgrade to Flower 1.13
• Simulate
  • Run simulations
• Deploy
  • Run Flower with the Deployment Engine
  • Enable TLS connections
  • Authenticate SuperNodes
  • Configure logging
  • Run Flower on Azure
  • Run Flower using Docker
    • Quickstart with Docker
    • Enable TLS for Secure Connections
    • Persist the State of the SuperLink
    • Set Environment Variables
    • Run with Root User Privileges
    • Run ServerApp or ClientApp as a Subprocess
    • Pin a Docker Image to a Specific Version
    • Use a Different Flower Version
    • Quickstart with Docker Compose
    • Run Flower Quickstart Examples with Docker Compose
    • Deploy Flower on Multiple Machines with Docker Compose

Explanations

Understanding-oriented concept guides explain and discuss key topics and underlying ideas behind Flower and collaborative AI.

Explanations

• Federated evaluation
• Differential Privacy
• Flower Architecture

References

References

• Reference
  • flwr
  • Flower CLI reference
  • Example projects
  • Telemetry
  • Changelog
  • Flower Network Communication
  • Exit Codes
  • FAQ

Contribute

The Flower community welcomes contributions. The following docs are intended to help along the way.

Contributor docs

• Contribute
  • Contribute on GitHub
  • Get started as a contributor
  • Install development versions
  • Set up a virtual env
  • Develop in VSCode Dev Containers
  • Write documentation
  • Release Flower
  • Contribute translations
  • How to Build Docker Flower Images Locally
  • Public and private APIs
  • Good first contributions
  • Secure Aggregation Protocols