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FedAH: Aggregated Head for Personalized Federated Learning

fedah

fedah_client

This project FedAH is based on the open source project PFLlib development.

License: GPL v2 arXiv

img

Environments

Install CUDA.

Install conda and activate conda.

conda env create -f env_cuda_latest.yaml # You may need to downgrade the torch using pip to match CUDA version

How to start simulating (examples for FedAH)

  • Create proper environments (see Environments).

  • Download this project to an appropriate location using git.

    git clone https://github.com/heyuepeng/FedAH.git

  • Run evaluation:

    cd ./system
python main.py -data MNIST -m cnn -algo FedAH -gr 2000 -did 0 # using the MNIST dataset, the FedAH algorithm, and the 4-layer CNN model

    Or you can uncomment the lines you need in ./system/examples.sh and run:

    cd ./system
sh examples.sh

Note: The hyper-parameters have not been tuned for the algorithms. The values in ./system/examples.sh are just examples. You need to tune the hyper-parameters by yourself.