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PhysNet

Tensorflow implementation of PhysNet (see https://arxiv.org/abs/1902.08408) for details

Requirements

To run this software, you need:

  • python3 (tested with version 3.6.3)
  • TensorFlow (tested with version 1.10.1)

Environment

conda create -y -n physnet python=3.6 #3.5
conda activate physnet
conda install -y tensorflow-gpu=1.10.0
conda install -y ipykernel
ipython kernel install --user --name=physnet

How to use

Edit the config.txt file to specify hyperparameters, dataset location, training/validation set size etc. (see "train.py" for a list of all options)

Then, simply run

# Prepare data
mkdir data && cd data
wget https://zenodo.org/record/2605341/files/sn2_reactions.npz
wget https://zenodo.org/record/2605341/files/README.txt
wget https://zenodo.org/record/2605341/files/read_data.py
cd ..

# Training! Remember to choose correct config file in train.py 
python3 train.py 

in a terminal to start training.

The included "config.txt" assumes that the dataset "sn2_reactions.npz" is present. It can be downloaded from: https://zenodo.org/record/2605341. In order to use a different dataset, it needs to be formatted in the same way as this example ("sn2_reactions.npz"). Please refer to the README file of the dataset (available from https://zenodo.org/record/2605341) for details.

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Code for training PhysNet models

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  • Python 91.9%
  • Jupyter Notebook 8.1%