ProtoTorch Models

Pre-packaged prototype-based machine learning models using ProtoTorch and PyTorch-Lightning.

Installation

To install this plugin, first install ProtoTorch with:

git clone https://github.com/si-cim/prototorch.git && cd prototorch
pip install -e .

and then install the plugin itself with:

git clone https://github.com/si-cim/prototorch_models.git && cd prototorch_models
pip install -e .

The plugin should then be available for use in your Python environment as prototorch.models.

Development setup

It is recommended that you use a virtual environment for development. If you do not use conda, the easiest way to work with virtual environments is by using virtualenvwrapper. Once you've installed it with pip install virtualenvwrapper, you can do the following:

export WORKON_HOME=~/pyenvs
mkdir -p $WORKON_HOME
source /usr/local/bin/virtualenvwrapper.sh  # location may vary
mkvirtualenv pt

Once you have a virtual environment setup, you can start install the models plugin with:

workon pt
git clone git@github.com:si-cim/prototorch_models.git
cd prototorch_models
git checkout dev
pip install -e .[all]  # \[all\] if you are using zsh or MacOS

To assist in the development process, you may also find it useful to install yapf, isort and autoflake. You can install them easily with pip.

Available models

• Generalized Learning Vector Quantization (GLVQ)
• Generalized Matrix Learning Vector Quantization (GMLVQ)
• Limited-Rank Matrix Learning Vector Quantization (LiRaMLVQ)
• Siamese GLVQ
• Neural Gas (NG)

Work in Progress

• Classification-By-Components Network (CBC)
• Learning Vector Quantization Multi-Layer Network (LVQMLN)

Planned models

• Local-Matrix GMLVQ
• Generalized Tangent Learning Vector Quantization (GTLVQ)
• Robust Soft Learning Vector Quantization (RSLVQ)
• Probabilistic Learning Vector Quantization (PLVQ)
• Self-Incremental Learning Vector Quantization (SILVQ)
• K-Nearest Neighbors (KNN)
• Learning Vector Quantization 1 (LVQ1)

FAQ

How do I update the plugin?

If you have already cloned and installed prototorch and the prototorch_models plugin with the -e flag via pip, all you have to do is navigate to those folders from your terminal and do git pull to update.