HardGAT

DGL Implementation of h/cGAO paper.

This DGL example implements the GNN model proposed in the paper HardGraphAttention.

HardGANet implementor

This example was implemented by Ericcsr during his Internship work at the AWS Shanghai AI Lab.

The graph dataset used in this example

The DGL's built-in CoraGraphDataset. Dataset summary:

• NumNodes: 2708
• NumEdges: 10556
• NumFeats: 1433
• NumClasses: 7
• NumTrainingSamples: 140
• NumValidationSamples: 500
• NumTestSamples: 1000

How to run example files

In the MVP4ModelExample folder, run

python main.py

If want to use a GPU, run

python main.py --gpu 0

If you want to use more Graph Hard Attention Modules

python main.py --num_module <your number>

If you want to change the hard attention threshold k

python main.py --k <your number>

Performance

TODO: Debug the implementation

TODO: Compare Cora Performance

TODO: Compare Performance in other Node classification ds

TODO: Implement Graph Classification Pipeline