Metadata-Version: 2.1
Name: prototorch
Version: 0.7.2
Summary: Highly extensible, GPU-supported Learning Vector Quantization (LVQ) toolbox built using PyTorch and its nn API.
Home-page: https://github.com/si-cim/prototorch
Author: Jensun Ravichandran
Author-email: jjensun@gmail.com
License: MIT
Download-URL: https://github.com/si-cim/prototorch.git
Platform: UNKNOWN
Classifier: Environment :: Console
Classifier: Natural Language :: English
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.7,<3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch (>=1.3.1)
Requires-Dist: torchvision (>=0.7.2)
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# ProtoTorch: Prototype Learning in PyTorch

![ProtoTorch Logo](https://prototorch.readthedocs.io/en/latest/_static/horizontal-lockup.png)

![tests](https://github.com/si-cim/prototorch/workflows/tests/badge.svg)
[![GitHub tag (latest by date)](https://img.shields.io/github/v/tag/si-cim/prototorch?color=yellow&label=version)](https://github.com/si-cim/prototorch/releases)
[![PyPI](https://img.shields.io/pypi/v/prototorch)](https://pypi.org/project/prototorch/)
[![GitHub license](https://img.shields.io/github/license/si-cim/prototorch)](https://github.com/si-cim/prototorch/blob/master/LICENSE)

*Tensorflow users, see:* [ProtoFlow](https://github.com/si-cim/protoflow)

## Description

This is a Python toolbox brewed at the Mittweida University of Applied Sciences
in Germany for bleeding-edge research in Prototype-based Machine Learning
methods and other interpretable models. The focus of ProtoTorch is ease-of-use,
extensibility and speed.

## Installation

ProtoTorch can be installed using `pip`.
```bash
pip install -U prototorch
```
To also install the extras, use
```bash
pip install -U prototorch[all]
```

*Note: If you're using [ZSH](https://www.zsh.org/) (which is also the default
shell on MacOS now), the square brackets `[ ]` have to be escaped like so:
`\[\]`, making the install command `pip install -U prototorch\[all\]`.*

To install the bleeding-edge features and improvements:
```bash
git clone https://github.com/si-cim/prototorch.git
cd prototorch
git checkout dev
pip install -e .[all]
```

## Documentation

The documentation is available at <https://www.prototorch.ml/en/latest/>. Should
that link not work try <https://prototorch.readthedocs.io/en/latest/>.

## Contribution

This repository contains definition for [git hooks](https://githooks.com).
[Pre-commit](https://pre-commit.com) is automatically installed as development
dependency with prototorch or you can install it manually with `pip install
pre-commit`.

Please install the hooks by running:
```bash
pre-commit install
pre-commit install --hook-type commit-msg
```
before creating the first commit.

The commit will fail if the commit message does not follow the specification
provided [here](https://www.conventionalcommits.org/en/v1.0.0/#specification).

## Bibtex

If you would like to cite the package, please use this:
```bibtex
@misc{Ravichandran2020b,
  author = {Ravichandran, J},
  title = {ProtoTorch},
  year = {2020},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/si-cim/prototorch}}
}


