duzx16 / lcgnn

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LCGNN

Dependency

The code is written in Python 3. We use PyTorch 1.5.1 with CUDA 10.1 to train our models.

The dependencies of our code are:

Please follow the instructions to install these dependencies.

Usage

Preprocessing

Use the following command to run local clustering for all nodes and save the data:

python preprocess.py --task {task} --dataset {name} --ego_size {ego_size}

The preprocessed data will be saved into ./data/{name}-lc-ego-graphs-{ego_size}.npy and ./data/{name}-lc-conds-{ego_size}.npy where task is chosen from [saint, ogbn], name is chosen from [flickr, reddit, yelp, amazon, products, papers100M], ego_size denotes the maximum cluster size.

Training

Our code supports four inductive datasets including flickr, reddit, yelp, amazon and two OGB datasets including products, papers100M.

To run LCGNN-Transformer, use:

python train.py --dataset flickr|reddit|yelp|amazon|products|papers100M

To run LCGNN-GCN/GAT/SAGE, use:

python train_gnn.py --dataset flickr|reddit|yelp|amazon|products --model gcn/gat/sage

You can find the best configuration in the best_configs.py.

Datasets

  • Four inductive datasets can be downloaded from here.
  • OGB datasets will be automatically downloaded through OGB APIs. You can find more details about OGB datasets from here.

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