We make an attempt to adjust feddep Dgen to get better results and consider more about the privacy of each client.
First of all, users need to clone the source code and install the required packages (we suggest python version >= 3.9).
git clone https://github.com/GalaxyBangBang/FeddepWithEM.git
cd FeddepWithEM
We recommend using a new virtual environment to install FederatedScope:
conda create -n fs python=3.9
conda activate fs
If your backend is torch, please install torch in advance (torch-get-started). For example, if your cuda version is 11.3 please execute the following command:
conda install -y pytorch=1.10.1 torchvision=0.11.2 torchaudio=0.10.1 cudatoolkit=11.3 -c pytorch -c conda-forge
Finally, after the backend is installed, you can install FederatedScope from source:
pip install .
pip install cytoolz
Now, you have successfully installed the minimal version of FederatedScope. For application version including graph run:
conda install -y pyg==2.0.4 -c pyg
conda install -y rdkit=2021.09.4=py39hccf6a74_0 -c conda-forge
conda install -y nltk
After all the above steps are completed, you can run
#pwd PATH/TO/FeddepWithEM
python ./federatedscope/main.py --cfg federatedscope/gfl/feddep/feddep_on_cora5.yaml
If you encouter a problem of the version of scipy, just use
pip uninstall scipy
pip install scipy
to solove the compatiblity problem.