conda create -n GraphMaker python=3.8 -y conda activate GraphMaker pip install torch==1.12.0+cu116 --extra-index-url https://download.pytorch.org/whl/cu116 conda install -c conda-forge cudatoolkit=11.6 pip install dgl==1.1.0+cu116 -f https://data.dgl.ai/wheels/cu116/repo.html pip install pandas scikit-learn pydantic wandb huggingface_hub==0.30.2
You also need to compile orca.cpp (https://file.biolab.si/biolab/supp/orca/orca.html).
cd orca
g++ -O2 -std=c++11 -o orca orca.cpp# The GraphMaker-Sync variant simultaneously generates node attributes and graph structure. python train_sync.py -d D # The trained model checkpoint will be saved to {D}_cpts/Sync_XXX.pth # The GraphMaker-Async variant first generates node attributes, and then generates graph structure. python train_async.py -d D # The trained model checkpoint will be saved to {D}_cpts/Async_XXX.pth
D can be one of the three built-in datasets, including cora, amazon_photo, amazon_computer.
python sample.py --model_path P
P is the path to a model checkpoint saved in the training stage.
Alternatively, you can also use our pre-trained model checkpoints for sampling.
python sample.py --dataset D --type T
Dcan be one of the three built-in datasets, includingcora,amazon_photo,amazon_computer.Tcan besyncorasync.
An error occurs that the program cannot find libcusparse.so.
To search for the location of it on linux,
find /path/to/directory -name libcusparse.so.11 -exec realpath {} \;where /path/to/directory is the directory you want to search. Assume that the search returns home/miniconda3/envs/GraphMaker/lib/libcusparse.so.11. Then you need to manually specify the environment variable as follows.
export LD_LIBRARY_PATH=home/miniconda3/envs/GraphMaker/lib:$LD_LIBRARY_PATH
What is WandB?
WandB is a tool for visualizing and tracking your machine learning experiments. It's free to use for open source projects. You may also use our code without it.
I have a question or request not listed here.
- It's generally recommended to open a GitHub issue. This allows us to track the progress, and the discussion might help others who have the same question.
- Otherwise, you can also send an email to
mufeili1996@gmail.com.
@article{li2024graphmaker,
title={GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?},
author={Mufei Li and Eleonora Kreačić and Vamsi K. Potluru and Pan Li},
journal={Transactions on Machine Learning Research},
year={2024}
}