[pypi-image]: https://badge.fury.io/py/torch-cluster.svg [pypi-url]: https://pypi.python.org/pypi/torch-cluster [build-image]: https://travis-ci.org/rusty1s/pytorch_cluster.svg?branch=master [build-url]: https://travis-ci.org/rusty1s/pytorch_cluster [coverage-image]: https://codecov.io/gh/rusty1s/pytorch_cluster/branch/master/graph/badge.svg [coverage-url]: https://codecov.io/github/rusty1s/pytorch_cluster?branch=master # PyTorch Cluster [![PyPI Version][pypi-image]][pypi-url] [![Build Status][build-image]][build-url] [![Code Coverage][coverage-image]][coverage-url] -------------------------------------------------------------------------------- This package consists of a small extension library of highly optimised graph cluster algorithms for the use in [PyTorch](http://pytorch.org/). All included operations work on varying data types and are implemented both for CPU and GPU. ## Installation Check that `nvcc` is accessible from terminal, e.g. `nvcc --version`. If not, add cuda (`/usr/local/cuda/bin`) to your `$PATH`. Then run: ``` pip install cffi torch-cluster python setup.py install ``` ## Running tests ``` python setup.py test ```