Group equivariant neural network library
Project description
GElib
GElib is a C++/CUDA library for building equivariant neural networks. The library can be used as a pure
C++ library or as a C++ extension for PyTorch.
GElib uses cnine as its backend.
Documentation for the C++ API can be found in the 'doc' directory.
Documentation for the PyTorch API is at https://risi-kondor.github.io/GElib/.
GElib is released under a combination of the Mozilla Public License v. 2.0. and a custom noncommercial license to be found in the file NONCOMMERCIAL.TXT.
The latter also applies to the cnine component. Commercial use requires a licence from the
author(s).
Installing GElib as a Python module
GElib is distributed in source code format, therefore to install it you need to have a working C++ compiler to be present on your system. The compiler must support the C++17 standard (or higher). You also need PyTorch.
To install GElib with CUDA support, you need to have the CUDA development environment to be installed on your system.
- Clone the package with
git clone --recurse-submodules git@github.com:risi-kondor/GElib.git
(The --recurse-submodules flag ensures that cnine is fetched automatically.)
- Move to the
pythonsubdirectory:
cd GElib/python
- If you wish to install GElib with CUDA support set the
WITH_CUDAenvironment variable toTRUE:
export WITH_CUDA="TRUE"
- Compile and install the package with
pip install -e .
or
pip3 install -e .
Credits
Lead developer: Risi Kondor
Contributors: Erik Henning Thiede, Ryan Keane
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file gelib-0.2.2.tar.gz.
File metadata
- Download URL: gelib-0.2.2.tar.gz
- Upload date:
- Size: 212.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d9a275492b1d6c5e2303e1dfcf19c7283f5dea0c82af3f970d518b7b20abdbf7
|
|
| MD5 |
be6d646db4be0b3f707506b61129042f
|
|
| BLAKE2b-256 |
79ee5adaa9cf96c77b840346a03e707df851eaf7855907d604757ff7341eace0
|