Skip to content


Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?

DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models

GitHub release doi:10.1016/j.cpc.2020.107206 Citations conda install pip install

DP-GEN (Deep Generator) is a software written in Python, delicately designed to generate a deep learning based model of interatomic potential energy and force field. DP-GEN is dependent on DeePMD-kit. With highly scalable interface with common softwares for molecular simulation, DP-GEN is capable to automatically prepare scripts and maintain job queues on HPC machines (High Performance Cluster) and analyze results.

If you use this software in any publication, please cite:

Yuzhi Zhang, Haidi Wang, Weijie Chen, Jinzhe Zeng, Linfeng Zhang, Han Wang, and Weinan E, DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models, Computer Physics Communications, 2020, 253, 107206.

Highlighted features

  • Accurate and efficient: DP-GEN is capable to sample more than tens of million structures and select only a few for first principles calculation. DP-GEN will finally obtain a uniformly accurate model.
  • User-friendly and automatic: Users may install and run DP-GEN easily. Once successfully running, DP-GEN can dispatch and handle all jobs on HPCs, and thus there's no need for any personal effort.
  • Highly scalable: With modularized code structures, users and developers can easily extend DP-GEN for their most relevant needs. DP-GEN currently supports for HPC systems (Slurm, PBS, LSF and cloud machines), Deep Potential interface with DeePMD-kit, MD interface with LAMMPS, Gromacs, AMBER, Calypso and ab-initio calculation interface with VASP, PWSCF, CP2K, SIESTA, Gaussian, Abacus, PWmat, etc. We're sincerely welcome and embraced to users' contributions, with more possibilities and cases to use DP-GEN.

Download and Install

DP-GEN only supports Python 3.8 and above.

One can download the source code of dpgen by

git clone

then you may install DP-GEN easily by:

cd dpgen
pip install --user .

With this command, the dpgen executable is install to $HOME/.local/bin/dpgen. You may want to export the PATH by

export PATH=$HOME/.local/bin:$PATH

To test if the installation is successful, you may execute

dpgen -h

Workflows and usage

DP-GEN contains the following workflows:

  • dpgen run: Main process of Deep Generator.
  • Init: Generating initial data.
    • dpgen init_bulk: Generating initial data for bulk systems.
    • dpgen init_surf: Generating initial data for surface systems.
    • dpgen init_reaction: Generating initial data for reactive systems.
  • dpgen simplify: Reducing the amount of existing dataset.
  • dpgen autotest: Autotest for Deep Potential.

For detailed usage and parameters, read DP-GEN documentation.

Tutorials and examples


The project dpgen is licensed under GNU LGPLv3.0.


DP-GEN is maintained by DeepModeling's developers. Contributors are always welcome.


The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field







No packages published