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Reproducibility


1. Usage


1.1 In terminal

# Run the main file (at the root of the project)
python main_molecules_graph_regression.py --dataset ZINC --config 'configs/molecules_graph_regression_GatedGCN_ZINC.json' # for CPU
python main_molecules_graph_regression.py --dataset ZINC --gpu_id 0 --config 'configs/molecules_graph_regression_GatedGCN_ZINC.json' # for GPU

The training and network parameters for each dataset and network is stored in a json file in the configs/ directory.


1.2 In jupyter notebook

# Run the notebook file (at the root of the project)
conda activate benchmark_gnn 
jupyter notebook

Use main_molecules_graph_regression.ipynb notebook to explore the code and do the training interactively.


2. Output, checkpoints and visualizations

Output results are located in the folder defined by the variable out_dir in the corresponding config file (eg. configs/molecules_graph_regression_GatedGCN_ZINC.json file).

If out_dir = 'out/molecules_graph_regression/', then

2.1 To see checkpoints and results

  1. Go toout/molecules_graph_regression/results to view all result text files.
  2. Directory out/molecules_graph_regression/checkpoints contains model checkpoints.

2.2 To see the training logs in Tensorboard

  1. Go to the logs directory, i.e. out/molecules_graph_regression/logs/
  2. Run the command tensorboard --logdir='./'
  3. Open http://localhost:6006 in your browser. Note that the port information (here 6006) appears on the terminal immediately after running Step 2.

3. Reproduce results


3.1 Results (1 run)

# At the root of the project
bash script_one_code_to_rull_them_all.sh # run all datasets and all GNNs

See script script_one_code_to_rull_them_all.sh.


3.2 Results (4 runs, except TSP)

# At the root of the project
bash script_main_TUs_graph_classification.sh # run TU datasets
bash script_main_superpixels_graph_classification_MNIST.sh # run MNIST dataset
bash script_main_superpixels_graph_classification_CIFAR10.sh # run CIFAR10 dataset
bash script_main_molecules_graph_regression_ZINC.sh # run ZINC dataset
bash script_main_SBMs_node_classification_PATTERN.sh # run PATTERN dataset
bash script_main_SBMs_node_classification_CLUSTER.sh # run CLUSTER dataset
bash script_main_TSP_edge_classification.sh # run TSP dataset

Scripts are located at the root of the repository.