Metadata-Version: 2.1
Name: e3nn
Version: 0.3.5
Summary: Equivariant convolutional neural networks for the group E(3) of 3 dimensional rotations, translations, and mirrors.
Home-page: https://e3nn.org
License: MIT
Description: # e3nn
        [![Coverage Status](https://coveralls.io/repos/github/e3nn/e3nn/badge.svg?branch=main)](https://coveralls.io/github/e3nn/e3nn?branch=main)
        [![DOI](https://zenodo.org/badge/237431920.svg)](https://zenodo.org/badge/latestdoi/237431920)
        
        **[Documentation](https://docs.e3nn.org)** | **[Code](https://github.com/e3nn/e3nn)** | **[ChangeLog](https://github.com/e3nn/e3nn/blob/main/ChangeLog.md)** | **[Colab](https://colab.research.google.com/drive/1Gps7mMOmzLe3Rt_b012xsz4UyuexTKAf?usp=sharing)**
        
        The aim of this library is to help the developement of E3 equivariant neural networks.
        It contains fundamental mathematical operations such as [tensor products](https://docs.e3nn.org/en/stable/api/o3/o3_tp.html) and [spherical harmonics](https://docs.e3nn.org/en/stable/api/o3/o3_sh.html).
        
        ![](https://user-images.githubusercontent.com/333780/79220728-dbe82c00-7e54-11ea-82c7-b3acbd9b2246.gif)
        
        ## Installation
        
        **Important:** install pytorch and only then run the command
        
        ```
        pip install --upgrade pip
        pip install --upgrade e3nn
        ```
        
        For details and optional dependencies, see [INSTALL.md](https://github.com/e3nn/e3nn/blob/main/INSTALL.md)
        
        ### Breaking changes
        e3nn is under development.
        It is recommanded to install using pip. The main branch is considered as unstable.
        The second version number is incremented every time a breaking change is made to the code.
        ```
        0.(increment when backwards incompatible release).(increment for backwards compatible release)
        ```
        
        ## Help
        We are happy to help! The best way to get help on `e3nn` is to submit a [Question](https://github.com/e3nn/e3nn/issues/new?assignees=&labels=question&template=question.md&title=%E2%9D%93+%5BQUESTION%5D) or [Bug Report](https://github.com/e3nn/e3nn/issues/new?assignees=&labels=bug&template=bug-report.md&title=%F0%9F%90%9B+%5BBUG%5D).
        
        ## Want to get involved? Great!
        If you want to get involved in and contribute to the development, improvement, and application of `e3nn`, introduce yourself in the [discussions](https://github.com/e3nn/e3nn/discussions/new).
        
        ## Code of conduct
        Our community abides by the [Contributor Covenant Code of Conduct](https://github.com/e3nn/e3nn/blob/main/code_of_conduct.md).
        
        ## Citing
        ```
        @software{mario_geiger_2021_5006322,
          author       = {Mario Geiger and
                          Tess Smidt and
                          Alby M. and
                          Benjamin Kurt Miller and
                          Wouter Boomsma and
                          Bradley Dice and
                          Kostiantyn Lapchevskyi and
                          Maurice Weiler and
                          Michał Tyszkiewicz and
                          Simon Batzner and
                          Jes Frellsen and
                          Nuri Jung and
                          Sophia Sanborn and
                          Josh Rackers and
                          Michael Bailey},
          title        = {e3nn/e3nn: 2021-06-21},
          month        = jun,
          year         = 2021,
          publisher    = {Zenodo},
          version      = {0.3.3},
          doi          = {10.5281/zenodo.5006322},
          url          = {https://doi.org/10.5281/zenodo.5006322}
        }
        ```
        
        ### Copyright
        
        Euclidean neural networks (e3nn) Copyright (c) 2020, The Regents of the
        University of California, through Lawrence Berkeley National Laboratory
        (subject to receipt of any required approvals from the U.S. Dept. of Energy),
        Ecole Polytechnique Federale de Lausanne (EPFL), Free University of Berlin
        and Kostiantyn Lapchevskyi. All rights reserved.
        
        If you have questions about your rights to use or distribute this software,
        please contact Berkeley Lab's Intellectual Property Office at
        IPO@lbl.gov.
        
        NOTICE.  This Software was developed under funding from the U.S. Department
        of Energy and the U.S. Government consequently retains certain rights.  As
        such, the U.S. Government has been granted for itself and others acting on
        its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the
        Software to reproduce, distribute copies to the public, prepare derivative
        works, and perform publicly and display publicly, and to permit others to do so.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: POSIX
Classifier: Operating System :: MacOS
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: dev
