GNNLens2 is an interactive visualization tool for graph neural networks (GNN). It allows seamless integration with deep graph library (DGL) and can meet your various visualization requirements for presentation, analysis and model explanation. It is an open source version of GNNLens with simplification and extension.
You can install Flask-CORS with
pip install -U flask-cors
pip install gnnlens
If you want to try experimental features, you can install from source as follows:
git clone https://github.com/dmlc/GNNLens2.git
cd GNNLens2/python
python setup.py install
Once you have installed the package, you can verify the success of installation with
import gnnlens
print(gnnlens.__version__)
# 0.1.0
We provide a set of tutorials to get you started with the library:
- Tutorial 1: Graph structure
- Tutorial 2: Ground truth and predicted node labels
- Tutorial 3: Edge weights and attention
- Tutorial 4: Weighted subgraphs and explanation methods
HKUST VisLab: Zhihua Jin, Huamin Qu
AWS Shanghai AI Lab: Mufei Li, Wanru Zhao (work done during internship), Jian Zhang, Minjie Wang
SMU: Yong Wang