Code repository for Muon GNN
Setup for CUDA10.1, check if it matches with nvidia-smi:
wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda.sh
bash ~/miniconda.sh -b -p $HOME/miniconda
export PATH="$HOME/miniconda/bin:$PATH"
export CPATH=/usr/local/cuda/include:$CPATH
echo export PATH="$HOME/miniconda/bin:$PATH" >> ~/.bashrc
echo export CPATH=/usr/local/cuda/include:$CPATH >> ~/.bashrc
conda create -n torch -c pytorch Python=3.6 numpy cuda100 magma-cuda100 pytorch torchvision cudatoolkit=10.1
conda init bash
source $HOME/.bashrc
conda activate torch
conda install pandas matplotlib jupyter nbconvert==5.4.1
conda install -c conda-forge tqdm
pip install uproot scipy xgboost sklearn --user
pip install networkx
#get this repo
git clone [email protected]:mialiu149/heptrkx-gnn-tracking.git
#get torch geometric
#for a in pytorch_cluster pytorch_sparse pytorch_spline_conv pytorch_geometric; do
# git clone https://github.com/rusty1s/$a.git
#pushd $a
# python setup.py install
#popd
#done
export CUDA=cu101
pip install torch-scatter==latest+${CUDA} -f https://pytorch-geometric.com/whl/torch-1.5.0.html
pip install torch-sparse==latest+${CUDA} -f https://pytorch-geometric.com/whl/torch-1.5.0.html
pip install torch-cluster==latest+${CUDA} -f https://pytorch-geometric.com/whl/torch-1.5.0.html
pip install torch-spline-conv==latest+${CUDA} -f https://pytorch-geometric.com/whl/torch-1.5.0.html
pip install torch-geometric
(or replace pip with the corresponding conda installation for safer compatibility)
and install pytorch geometric according to the instructions here:
https://pytorch-geometric.readthedocs.io/en/latest/notes/installation.html