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nvflare

Federated Learning Application Runtime Environment

2.5.2
PyPI
Maintainers
2

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NVIDIA FLARE

NVIDIA FLARE (NVIDIA Federated Learning Application Runtime Environment) is a domain-agnostic, open-source, extensible SDK that allows researchers and data scientists to adapt existing ML/DL workflows to a federated paradigm. It enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration.

Features

FLARE is built on a componentized architecture that allows you to take federated learning workloads from research and simulation to real-world production deployment.

Application Features

  • Support both deep learning and traditional machine learning algorithms (eg. PyTorch, TensorFlow, Scikit-learn, XGBoost etc.)
  • Support horizontal and vertical federated learning
  • Built-in Federated Learning algorithms (e.g., FedAvg, FedProx, FedOpt, Scaffold, Ditto, etc.)
  • Support multiple server and client-controlled training workflows (e.g., scatter & gather, cyclic) and validation workflows (global model evaluation, cross-site validation)
  • Support both data analytics (federated statistics) and machine learning lifecycle management
  • Privacy preservation with differential privacy, homomorphic encryption, private set intersection (PSI)

From Simulation to Real-World

  • FLARE Client API to transition seamlessly from ML/DL to FL with minimal code changes
  • Simulator and POC mode for rapid development and prototyping
  • Fully customizable and extensible components with modular design
  • Deployment on cloud and on-premise
  • Dashboard for project management and deployment
  • Security enforcement through federated authorization and privacy policy
  • Built-in support for system resiliency and fault tolerance

Take a look at NVIDIA FLARE Overview for a complete overview, and What's New for the lastest changes.

Installation

To install the current release:

$ python3 -m pip install nvflare

Getting Started

You can quickly get started using the FL simulator. A detailed getting started guide is available in the documentation.

Examples and notebook tutorials are located at NVFlare/examples.

Community

We welcome community contributions! Please refer to the contributing guidelines for more details.

Ask and answer questions, share ideas, and engage with other community members at NVFlare Discussions.

Take a look at our growing list of talks, blogs, and publications related to NVIDIA FLARE.

License

NVIDIA FLARE is released under an Apache 2.0 license.

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