semvec/pypi-packages huggingface dataset:
fugw 0.1.1
A collection of gpu-compatible solvers for fused unbalanced gromov-wasserstein optimization problems
Requires Python: >=3.7
Keywords: optimal transport,gromov wasserstein,solver

# Fused Unbalanced Gromov-Wasserstein for Python

![build](https://img.shields.io/github/actions/workflow/status/alexisthual/fugw/unit_tests.yml?event=push&style=for-the-badge)
![python version](https://img.shields.io/badge/python-3.8_|_3.9_|_3.10_|_3.11-blue?style=for-the-badge)
![license](https://img.shields.io/github/license/alexisthual/fugw?style=for-the-badge)
![code style](https://img.shields.io/badge/code_style-black-black?style=for-the-badge)

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}
}
```
w1hack 0.4.0
Una biblioteca para consultar cursos de hack4u.

# hack4u Academy Course Library

Una biblioteca de python para consultar cursos de la academia hack4u.

## cursos disponibles:

- Introduccion a Linux [15 horas]
- Personalizacion de Linux [3 horas]
- Introduccion al hacking [53 horas]

### Instalación

Instalar el paquete usando `pip3`:

```python
pip3 install hack4u
```

## Uso básico

## Listar todos los cursos

```python
from hack4u import list_courses

for course in list_courses():
    print(course)
```
### Obtener un curso por nombre

```python
from hack4u import get_course_by_name

course = get_course_by_name("Introduccion a Linux")
print(course)
```
### Calcular duración total de los cursos

```python
from hack4u.utils import total_duration

print(f"Duracion total: {total_duration()} horas")
```