Please follow the instructions below to run the code.

Instructions

1. Clone the repository
2. Install the required packages
3. Run the code
4. View the results
5. View the report
6. View the presentation

1. Clone the repository

Clone the repository to your local machine using the following command:

git clone https://github.com/DongzhuoranZhou/synthetic_dataset.git

2. Install the required packages

Install the required packages using the following command:

conda create -n deep_gcn_benchmark python=3.8
conda activate deep_gcn_benchmark
conda install pytorch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 pytorch-cuda=11.7 -c pytorch -c nvidia
pip install torch-scatter -f https://pytorch-geometric.com/whl/torch-1.13.1+cu117.html
pip install torch-sparse -f https://pytorch-geometric.com/whl/torch-1.13.1+cu117.html
pip install torch-cluster -f https://pytorch-geometric.com/whl/torch-1.13.0+cu117.html
pip install torch-spline-conv -f https://pytorch-geometric.com/whl/torch-1.13.0+cu117.html
pip install torch-geometric
pip install networkx
pip install matplotlib

3. Run the code

Run the code using the following command:

python main.py --dataset syn2 --epochs 100 --N_exp 5 --num_layers 16 --type_model SGC --type_norm pair --type_split single --logdir logs/SGC_pairnorm

4. View the results

The results will be saved in the results folder.

5. View the log

The logs will be saved in the logs folder.

6. View the acc curves

python plot_acc_curve.py

The acc curve will be saved in the acc_curve.png.