# NepTrainKit

**Repository Path**: pfsuo/NepTrainKit

## Basic Information

- **Project Name**: NepTrainKit
- **Description**: NepTrainKit from github
- **Primary Language**: Unknown
- **License**: GPL-3.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-01-17
- **Last Updated**: 2025-09-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

<div align="center">
<a href="https://github.com/aboys-cb/NepTrainKit">
  <img src="./src/NepTrainKit/src/images/logo.svg" width="25%" alt="NepTrainKit Logo">
</a><br>    
<a href="https://pypi.org/project/NepTrainKit"><img src="https://img.shields.io/pypi/dm/NepTrainKit?logo=pypi&logoColor=white&color=blue&label=PyPI" alt="PyPI Downloads"></a>   
<a href="https://python.org/downloads"><img src="https://img.shields.io/badge/Python-3.10+-blue.svg?logo=python&logoColor=white" alt="Python Version"></a>  
<a href="https://codecov.io/github/aboys-cb/NepTrainKit"><img src="https://codecov.io/github/aboys-cb/NepTrainKit/graph/badge.svg?token=HQ5FMLD91F" alt="Codecov"></a>  
<a href="https://doi.org/10.48550/arXiv.2506.01868"><img src="https://img.shields.io/badge/arXiv-2506.01868-b31b1b.svg" alt="arXiv"></a>
<a href="https://github.com/aboys-cb/NepTrainKit/blob/master/LICENSE"><img src="https://img.shields.io/badge/license-GPL--3.0--or--later-blue" alt="License"></a>
</div>


---

# NepTrainKit

**NepTrainKit** is a toolkit focused on the operation and visualization of **neuroevolution potential** (NEP) training datasets. It is mainly used to simplify and optimize the NEP model training process, providing an intuitive graphical interface and analysis tools to help users adjust  train dataset.

---

## Community Support

- Join the community chat: [https://qm.qq.com/q/wPDQYHMhyg](https://qm.qq.com/q/wPDQYHMhyg)
- Report issues or contribute via [GitHub Issues](https://github.com/aboys-cb/NepTrainKit/issues)

---

## Installation

> **It is strongly recommended to use pip for installation.**

### Method 1: Install via pip

If you are using Python 3.10 or a later version, you can install `NepTrainKit` using an environment manager like `conda`:

1. Create a new environment:

   ```bash
   conda create -n nepkit python=3.10
   ```

2. Activate the environment:

   ```bash
   conda activate nepkit
   ```

3. For CentOS users, install PySide6 (required for GUI functionality):

   ```bash
   conda install -c conda-forge pyside6
   ```

- Install directly using the `pip install` command:

  ```bash
  pip install NepTrainKit
  ```

  After installation, you can call the program using either `NepTrainKit` or `nepkit`.

- For the **latest version** (from GitHub):

  ```bash
  pip install git+https://github.com/aboys-cb/NepTrainKit.git
  ```

---

### Method 2: Windows Executable

A standalone executable is available for Windows users.

- Visit the [Releases](https://github.com/aboys-cb/NepTrainKit/releases) page
- Download `NepTrainKit.win32.zip`

 > Note: Only supported on Windows platforms.

### GPU Acceleration (optional)

- NepTrainKit includes an optional GPU‑accelerated NEP backend.
- Requirements: NVIDIA GPU/driver compatible with CUDA 12.4 runtime.
- Selection: In the app, go to Settings → NEP Backend and choose Auto/CPU/GPU.
  - Auto tries GPU first and falls back to CPU if unavailable.
  - Adjust GPU Batch Size to balance speed and memory.
  - If you see “CUDA driver version is insufficient for CUDA runtime version”, switch to CPU.

---

## Documentation

For detailed usage documentation and examples, please refer to the official documentation:  
[https://neptrainkit.readthedocs.io/en/latest/index.html](https://neptrainkit.readthedocs.io/en/latest/index.html)

- What's new: see `docs/source/changelog.md` or the Documentation "Changelog" page.

---

## Licensing and Attribution

- License: This repository is licensed under the GNU General Public License v3.0
  (or, at your option, any later version). See `LICENSE` at the repository root.
- Third‑party code: NepTrainKit incorporates source files and adapted logic from:
  - NEP_CPU (by Zheyong Fan, Junjie Wang, Eric Lindgren, and contributors):
    https://github.com/brucefan1983/NEP_CPU (GPL‑3.0‑or‑later)
  - GPUMD (by Zheyong Fan and the GPUMD development team):
    https://github.com/brucefan1983/GPUMD (GPL‑3.0‑or‑later)
- Directory‑level notes: See `src/nep_cpu/README.md` and `src/nep_gpu/README.md` for
  file‑level provenance, what was modified or added, and links to the upstream projects.
  A consolidated overview is also available in `THIRD_PARTY_NOTICES.md`.
- Redistribution: Any modifications and redistributions must remain under the GPL and
  preserve copyright and license notices, per the GPL requirements.

If you use NepTrainKit in academic work, please cite the project and also acknowledge
NEP_CPU and/or GPUMD as appropriate.