Metadata-Version: 2.3
Name: fairchem-core
Version: 1.2.0
Summary: Machine learning models for use in catalysis as part of the Open Catalyst Project
Project-URL: repository, https://github.com/FAIR-Chem/fairchem
Project-URL: home, https://opencatalystproject.org/
Project-URL: documentation, https://fair-chem.github.io/
License: MIT License
Requires-Python: <3.13,>=3.9
Requires-Dist: ase
Requires-Dist: e3nn>=0.5
Requires-Dist: lmdb
Requires-Dist: numba
Requires-Dist: numpy<2.0.0,>=1.25.0
Requires-Dist: orjson
Requires-Dist: pymatgen>=2023.10.3
Requires-Dist: pyyaml
Requires-Dist: requests
Requires-Dist: submitit
Requires-Dist: tensorboard
Requires-Dist: torch>=2.2
Requires-Dist: tqdm
Requires-Dist: wandb
Provides-Extra: adsorbml
Requires-Dist: dscribe; extra == 'adsorbml'
Requires-Dist: scikit-image; extra == 'adsorbml'
Requires-Dist: x3dase; extra == 'adsorbml'
Provides-Extra: dev
Requires-Dist: coverage; extra == 'dev'
Requires-Dist: pre-commit; extra == 'dev'
Requires-Dist: pytest; extra == 'dev'
Requires-Dist: pytest-cov; extra == 'dev'
Requires-Dist: ruff==0.5.1; extra == 'dev'
Requires-Dist: syrupy; extra == 'dev'
Provides-Extra: docs
Requires-Dist: jupyter-book; extra == 'docs'
Requires-Dist: jupytext; extra == 'docs'
Requires-Dist: sphinx; extra == 'docs'
Requires-Dist: sphinx-autoapi; extra == 'docs'
Requires-Dist: umap-learn; extra == 'docs'
Requires-Dist: vdict; extra == 'docs'
Description-Content-Type: text/markdown

<h1 align="center"> <code>fairchem</code> by FAIR Chemistry </h1>

<p align="center">
  <img width="559" height="200" src="https://github.com/FAIR-Chem/fairchem/assets/45150244/5872c21c-8f39-41af-b703-af9817f0affe"?
</p>


<h4 align="center">

![tests](https://github.com/FAIR-Chem/fairchem/actions/workflows/test.yml/badge.svg?branch=main)
[![documentation](https://github.com/FAIR-Chem/fairchem/actions/workflows/docs.yml/badge.svg?branch=main)](https://github.com/FAIR-Chem/fairchem/actions/workflows/docs.yml)
[![Static Badge](https://img.shields.io/badge/python-3.9%2B-blue)](https://www.python.org/downloads/)

</h4>

`fairchem` is the [FAIR](https://ai.meta.com/research/) Chemistry's centralized repository of all its data, models, demos, and application efforts for materials science and quantum chemistry.

`fairchem` provides training and evaluation code for tasks and models that take arbitrary
chemical structures as input to predict energies / forces / positions / stresses,
and can be used as a base scaffold for research projects. For an overview of
tasks, data, and metrics, please read the documentations and respective papers:
 - [OC20](https://fair-chem.github.io/core/datasets/oc20.html)
 - [OC22](https://fair-chem.github.io/core/datasets/oc22.html)
 - [ODAC23](https://fair-chem.github.io/core/datasets/odac.html)

## Acknowledgements

- This codebase was initially forked from [CGCNN](https://github.com/txie-93/cgcnn)
by [Tian Xie](http://txie.me), but has undergone significant changes since.
- A lot of engineering ideas have been borrowed from [github.com/facebookresearch/mmf](https://github.com/facebookresearch/mmf).
- The DimeNet++ implementation is based on the [author's Tensorflow implementation](https://github.com/klicperajo/dimenet) and the [DimeNet implementation in Pytorch Geometric](https://github.com/rusty1s/pytorch_geometric/blob/master/torch_geometric/nn/models/dimenet.py).

## License

`fairchem` is released under the [MIT](https://github.com/FAIR-Chem/fairchem/blob/main/LICENSE.md) license.

## Citing `fairchem`

If you use this codebase in your work, please consider citing:

```bibtex
@article{ocp_dataset,
    author = {Chanussot*, Lowik and Das*, Abhishek and Goyal*, Siddharth and Lavril*, Thibaut and Shuaibi*, Muhammed and Riviere, Morgane and Tran, Kevin and Heras-Domingo, Javier and Ho, Caleb and Hu, Weihua and Palizhati, Aini and Sriram, Anuroop and Wood, Brandon and Yoon, Junwoong and Parikh, Devi and Zitnick, C. Lawrence and Ulissi, Zachary},
    title = {Open Catalyst 2020 (OC20) Dataset and Community Challenges},
    journal = {ACS Catalysis},
    year = {2021},
    doi = {10.1021/acscatal.0c04525},
}
```

MIT License

Copyright (c) Facebook, Inc. and its affiliates.

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
