MONAI NVIDIA FLARE integration
Project description
MONAI Integration
Objective
Integration with MONAI's federated learning capabilities.
Add ClientAlgoExecutor class to allow using MONAI's ClientAlgo class in federated scenarios.
Goals:
Allow the use of bundles from the MONAI model zoo or custom configurations with NVFlare.
Background
MONAI allows the definition of AI models using the "bundle" concept.
It allows for easy experimentation and sharing of models that have been developed using MONAI.
Using the bundle configurations, we can use MONAI's MonaiAlgo (the implementation of ClientAlgo) to execute a bundle model in a federated scenario using NVFlare.
Description
NVFlare executes the ClientAlgo class using the ClientAlgoExecutor class provided with this package.
Examples
For an example of using NVIDIA FLARE to train a medical image analysis model using federated averaging (FedAvg) and MONAI Bundle, see the examples.
Requirements
We recommend following the instructions for setting up a virtual environment, and using it in JupyterLab for running the notebooks the MONAI integration examples.
Install MONAI-NVFlare integration from PyPI:
pip install monai_nvflare
(Optional) Install MONAI-NVFlare integration from source:
pip install -e .
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