Flower Docs

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

User Guide

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.

User Guide

• Flower Quickstart (with Keras)
  • Flower Client
  • Flower Server
  • Train the model, federated!
• Flower Quickstart (with PyTorch)
  • Ready… Set… Train!
  • Flower Server
  • Flower Client
  • A Closer Look
  • Give It a Try
• Installing Flower
  • Python Version
  • Install Stable Release
  • Install Nightly Release
  • Install from GitHub
• Usage Examples
  • Extra Dependencies
  • Run Examples Using Docker
  • PyTorch Examples
  • TensorFlow Examples
• Run examples on AWS
  • Intro
  • Setup
  • Outlook

API Reference

• API Reference
  • flwr package
    • Subpackages

Contributor Guide

The Flower authors welcome external contributions. The following guides are intended to help along the way.

Contributor Guide

• Getting Started (for Contributors)
  • Prerequisites
  • Developer Machine Setup
  • Convenience Scripts
  • Build Release
  • Build Documentation
• Good First Contributions
  • Where to Start
  • Request for Examples
• Flower Architecture

About Flower

About Flower

• People
• Organizations
  • Academia
  • Industry
• Publications
  • Papers