prototorch-models 0.0.0

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

# ProtoTorch Models

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

## Installation

To install this plugin, first install [ProtoTorch](https://github.com/si-cim/prototorch) with:

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

and then install the plugin itself with:

`sh 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](https://virtualenvwrapper.readthedocs.io/en/latest/). Once you’ve installed it with pip install virtualenvwrapper, you can do the following:

`sh 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:

`sh workon pt git clone [e-mail]: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 Relevance Learning Vector Quantization (GRLVQ)

• 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.