Rethinking Graph Neural Architecture Search from Message-passing
GNAS-MP
Pytorch Implementation of Rethinking Graph Neural Architecture Search from Message-passing (CVPR2021)
Getting Started
0. Prerequisites
- Linux
- NVIDIA GPU + CUDA CuDNN
1. Setup Python Environment
# clone Github repo
conda install git
git clone https://github.com/phython96/GNAS-MP.git
cd GNAS-MP
# Install python environment
conda env create -f environment_gpu.yml
conda activate gnasmp
2. Download datasets
The datasets are provided by project benchmarking-gnns, you can click here to download all the required datasets.
3. Search Architectures
python scripts/search_molecules_zinc.sh [gpu_id]
4. Train & Test
python scripts/train_molecules_zinc.sh [gpu_id] '[path_to_genotypes]/example.yaml'
Reference
@inproceedings{cai2021rethinking,
title={Rethinking Graph Neural Architecture Search from Message-passing},
author={Cai, Shaofei and Li, Liang and Deng, Jincan and Zhang, Beichen and Zha, Zheng-Jun and Su, Li and