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A Self-Attention Based Message Passing Neural Network for Identifying Structure-Property Relationships

Introduction

This is a PyTorch implementation of the research: A Self-Attention Based Message Passing Neural Network for Identifying Structure-Property Relationships Graph abstract

Environment

Python 3.6.5
Pytorch 1.0 
RDkit 2018.03.4 
Autograd 1.2 
Numpy 1.14.2 
Pandas 0.23.4 
tqdm 3.7.1

Data File

Data file format: </br>     Datafile can be CSV and text as showd in the data_RE2. </br>

train

python reg_wat.py #replace the data_path and cols_to_read as your want </br> The trained model weights will be also stored in save_test. </br>

prediction and visualization

python viz_wat.py #replace the data_path and checkpoint_path as your want </br> The results of prediction will be also stored in save_test and visualization file will be save in png_*. </br>

repeat this work

bash go_repeat.sh

Acknowledgement

We thank the previous work by Ramsundar and swansonk14 teams. The code in this repository is inspired on DeepChem and ChemProp