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Python 3.10.10, PyTorch 2.0.0, conda 23.11.0, wandb 0.16.1
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All experiments are done on a single machine with 252GB RAM, 64 Intel Xeon Gold 6242 CPUs @ 2.80GHz, and 6 NVIDIA RTX A5000 GPUs with 24GB RAM each. The utilized OS is Ubuntu 20.04.6 LTS
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Set up a
conda
environment by runningconda create --name <envname> --file requirements.txt
and activate it by runningconda activate <envname>
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Read
training.py
file and add to the place that requires thewandb
API key.
- MNIST
export CUDA_VISIBLE_DEVICES=<gpu_id> && mytime=$(date "+%m.%d_%H.%M.%S") && mkdir -p $(pwd)"/experiments/exp<exp_id>/"$mytime && python training.py --name mnist --params configs/mnist_fed.yaml --time $mytime --exp exp<exp_id>> $(pwd)"/experiments/exp<exp_id>/"$mytime"/logs.txt"
- CIFAR-10
export CUDA_VISIBLE_DEVICES=<gpu_id> && mytime=$(date "+%m.%d_%H.%M.%S") && mkdir -p $(pwd)"/experiments/exp<exp_id>/"$mytime && python training.py --name cifar10 --params configs/cifar10_fed.yaml --time $mytime --exp exp<exp_id> > $(pwd)"/experiments/exp<exp_id>/"$mytime"/logs.txt"