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

Project description

ProtoTorch: Prototype Learning in PyTorch

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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, 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
git checkout dev
cd prototorch
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:

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

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prototorch-0.2.0.tar.gz (119.0 kB view hashes)

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