ca39aa00d5
Pass the component initializer as an hparam slows down the script very much. The API has now been changed to pass it as a kwarg to the models instead. The example scripts have also been updated to reflect the new changes. Also, ImageGMLVQ and an example script `gmlvq_mnist.py` that uses it have also been added.
2.6 KiB
ProtoTorch Models
Pre-packaged prototype-based machine learning models using ProtoTorch and PyTorch-Lightning.
Installation
To install this plugin, simply run the following command:
pip install prototorch_models
The plugin should then be available for use in your Python environment as
prototorch.models.
*Note: Installing the models plugin should automatically install a suitable version of * ProtoTorch.
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
- k-Nearest Neighbors (KNN)
- Learning Vector Quantization 1 (LVQ1)
- Generalized Learning Vector Quantization (GLVQ)
- Generalized Relevance Learning Vector Quantization (GRLVQ)
- Generalized Matrix Learning Vector Quantization (GMLVQ)
- Limited-Rank Matrix Learning Vector Quantization (LiRaMLVQ)
- Learning Vector Quantization Multi-Layer Network (LVQMLN)
- Siamese GLVQ
- Neural Gas (NG)
Work in Progress
- Classification-By-Components Network (CBC)
- Learning Vector Quantization 2.1 (LVQ2.1)
Planned models
- Median-LVQ
- 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)
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.