prototorch 0.7.6

Highly extensible, GPU-supported Learning Vector Quantization (LVQ) toolbox built using PyTorch and its nn API.

ProtoTorch: Prototype Learning in PyTorch

Tensorflow users, see: 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.

pip install -U prototorch

To also install the extras, use

pip install -U prototorch[all]

Note: If you're using ZSH (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:

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. Pre-commit 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:

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.

Bibtex

If you would like to cite the package, please use this:

@misc{Ravichandran2020b,
  author = {Ravichandran, J},
  title = {ProtoTorch},
  year = {2020},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/si-cim/prototorch}}
}