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A Python-based framework for federated learning simulation, emphasizing modularity, communication efficiency, and algorithmic flexibility. Supports both server- and client-side customization for research and development purposes.
Features
- Modular simulation of FL workflows (communication, optimization, compression)
- Customizable server/client logic via plug-in modules
- Scales to diverse computation & network scenarios
- PyPI-installable (pip install fedlab) or cloneable from GitHub
- Compatible with PyTorch models
- Focused on efficient algorithm experimentation
Project Samples
Categories
Federated Learning FrameworksLicense
Apache License V2.0Follow FedLab
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