PyTorch Implement for Path Attention Graph Network

Last update: Dec 28, 2022

Related tags

Deep Learning SPAGAN

Overview

SPAGAN in PyTorch

This is a PyTorch implementation of the paper "SPAGAN: Shortest Path Graph Attention Network"

Prerequisites

We prefer to create a new conda environment to run the code.

PyTorch

Version >= 1.0.0

PyTorch-geometric

We use torch_geometric, torch_scatter and torch_sparse as backbone to implement the path attention mechanism. Please follow the official website to install them.

networkx

We use networkx to load the graph dataset.

graph-tool

We use graph-tool for fast APSP calculation. Please follow the official website to install.

Run the code:

Activating the corresponding conda env if you use a new conda environment.

python train_spgat.py

Owner

Yang Yiding

Ph.D. student at Stevens Institute of Technology

GitHub Repository

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PyTorch Implement for Path Attention Graph Network

Related tags

Overview

SPAGAN in PyTorch

Prerequisites

PyTorch

PyTorch-geometric

networkx

graph-tool

Run the code:

Owner

Yang Yiding

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