| Name | fugw JSON |
| Version |
0.1.0
JSON |
| download |
| home_page | |
| Summary | A collection of gpu-compatible solvers for fused unbalanced gromov-wasserstein optimization problems |
| upload_time | 2023-03-19 17:09:12 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.7 |
| license | |
| keywords |
optimal transport
gromov wasserstein
solver
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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# Fused Unbalanced Gromov-Wasserstein for Python
This package implements multiple GPU-compatible PyTorch solvers
to the Fused Unbalanced Gromov-Wasserstein optimal transport problem.
**This package is under active development. There is no guarantee that the API and solvers
won't change in the near future.**
## Installation
**To install this package, make sure you have an up-to-date version of** `pip`.
### From PyPI
In a dedicated Python env, run:
```bash
pip install fugw
```
### From source
```bash
git clone https://github.com/alexisthual/fugw.git
cd fugw
```
In a dedicated Python env, run:
```bash
pip install -e .
```
Contributors should also install the development dependencies
in order to test and automatically format their contributions.
```bash
pip install -e ".[dev]"
pre-commit install
```
Tests run on CPU and GPU, depending on the configuration of your machine.
You can run them with:
```bash
pytest
```
## Citing this work
If this package was useful to you, please cite it in your work:
```bibtex
@article{Thual-2022-fugw,
title={Aligning individual brains with Fused Unbalanced Gromov-Wasserstein},
author={Thual, Alexis and Tran, Huy and Zemskova, Tatiana and Courty, Nicolas and Flamary, Rémi and Dehaene, Stanislas and Thirion, Bertrand},
publisher={arXiv},
doi={10.48550/ARXIV.2206.09398},
url={https://arxiv.org/abs/2206.09398},
year={2022},
copyright={Creative Commons Attribution 4.0 International}
}
```
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