Pytorch Extension to Bingham Statistics

Environment

To start, at least ensure these packages are installed.

torch==2.0.0
setuptools

Dependency

This code is tested on cuda-11.7 / cuda-11.8, with gcc-9 and g++-9 / gcc-11 and g++-11, if you are using conda environments, this should work. And remember to link your cuda in the environment.

conda install cudatoolkit=11.7

Quick Start

conda env create -f environment.yaml

How to build

1. (optional) if you are using conda, activate an environment that you want to work with
2. If you just want to compile the extension, use python setup.py build to build the extension. Uppon sussessfully compilation, you can find the *.so file in build/lib.*/. You can add this path to your python path or cd to this directory, and then start ipython to import the module
3. For installation you can run python setup.py install, and the extension will be installed, and then you can access it system-wise.

---

Acknowledgement

This is the updated version (torch 2.0.0, cuda 11.7, gcc-9, g++-9) of torch_bingham, which is built upon Bingham Statistics Library (BSL).