Please refer to https://github.com/snap-stanford/pretrain-gnns#installation for environment setup and https://github.com/snap-stanford/pretrain-gnns#dataset-download to download dataset.
If you cannot manage to install the old torch-geometric version, one alternative way is to use the new one (maybe ==1.6.0) and make some modifications based on this issue snap-stanford/pretrain-gnns#14. This might leads to some inconsistent results with those in the paper.
cd ./bio
python pretrain_graphcl.py --aug1 random --aug2 random
cd ./chem
python pretrain_graphcl.py --aug1 random --aug2 random
cd ./bio
./finetune.sh
cd ./chem
./run.sh
Results will be recorded in result.log.
The backbone implementation is reference to https://github.com/snap-stanford/pretrain-gnns.