Metadata-Version: 2.1
Name: prototorch
Version: 0.4.4
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
Description: # ProtoTorch: Prototype Learning in PyTorch
        
        ![ProtoTorch Logo](https://prototorch.readthedocs.io/en/latest/_static/horizontal-lockup.png)
        
        [![Build Status](https://travis-ci.org/si-cim/prototorch.svg?branch=master)](https://travis-ci.org/si-cim/prototorch)
        ![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/)
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        [![Codacy Badge](https://api.codacy.com/project/badge/Grade/76273904bf9343f0a8b29cd8aca242e7)](https://www.codacy.com/gh/si-cim/prototorch?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=si-cim/prototorch&amp;utm_campaign=Badge_Grade)
        ![PyPI - Downloads](https://img.shields.io/pypi/dm/prototorch?color=blue)
        [![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/>.
        
        ## 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}}
        }
        
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
Provides-Extra: docs
Provides-Extra: datasets
Provides-Extra: examples
Provides-Extra: tests
Provides-Extra: all
