Metadata-Version: 2.1
Name: e3nn-jax
Version: 0.20.0
Summary: Equivariant convolutional neural networks for the group E(3) of 3 dimensional rotations, translations, and mirrors.
Home-page: https://e3nn.org
License: Apache License 2.0
Description: # e3nn-jax [![Coverage Status](https://coveralls.io/repos/github/e3nn/e3nn-jax/badge.svg?branch=main)](https://coveralls.io/github/e3nn/e3nn-jax?branch=main)
        
        ### :rocket: 44% faster than pytorch*
        
        *Speed comparison done with a full model (MACE) during training (revMD-17) on a GPU (NVIDIA RTX A5000)
        
        ### [Documentation](https://e3nn-jax.readthedocs.io/en/latest) [![Documentation Status](https://readthedocs.org/projects/e3nn-jax/badge/?version=latest)](https://e3nn-jax.readthedocs.io/en/latest/?badge=latest)
        
        Please always check the [ChangeLog](Changelog.md) for breaking changes.
        
        ## Installation
        
        To install the latest released version:
        ```bash
        pip install --upgrade e3nn-jax
        ```
        
        To install the latest GitHub version:
        ```bash
        pip install git+https://github.com/e3nn/e3nn-jax.git
        ```
        
        ## Need Help?
        Ask a question in the [discussions tab](https://github.com/e3nn/e3nn-jax/discussions).
        
        ## What is different from the PyTorch version?
        
        The main difference is the presence of the class [`IrrepsArray`](https://e3nn-jax.readthedocs.io/en/latest/api/irreps_array.html).
        `IrrepsArray` contains the irreps (`Irreps`) along with the data array.
        
        ## Citing
        ```
        @misc{e3nn_paper,
            doi = {10.48550/ARXIV.2207.09453},
            url = {https://arxiv.org/abs/2207.09453},
            author = {Geiger, Mario and Smidt, Tess},
            keywords = {Machine Learning (cs.LG), Artificial Intelligence (cs.AI), Neural and Evolutionary Computing (cs.NE), FOS: Computer and information sciences, FOS: Computer and information sciences}, 
            title = {e3nn: Euclidean Neural Networks},
            publisher = {arXiv},
            year = {2022},
            copyright = {Creative Commons Attribution 4.0 International}
        }
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.7
Description-Content-Type: text/markdown
