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.
85 lines
2.6 KiB
Markdown
85 lines
2.6 KiB
Markdown
# ProtoTorch Models
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[](https://travis-ci.org/si-cim/prototorch_models)
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[](https://pypi.org/project/prototorch_models/)
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Pre-packaged prototype-based machine learning models using ProtoTorch and
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PyTorch-Lightning.
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## Installation
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To install this plugin, simply run the following command:
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```sh
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pip install prototorch_models
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```
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The plugin should then be available for use in your Python environment as
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`prototorch.models`.
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*Note: Installing the models plugin should automatically install a suitable
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version of * [ProtoTorch](https://github.com/si-cim/prototorch).
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## Development setup
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It is recommended that you use a virtual environment for development. If you do
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not use `conda`, the easiest way to work with virtual environments is by using
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[virtualenvwrapper](https://virtualenvwrapper.readthedocs.io/en/latest/). Once
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you've installed it with `pip install virtualenvwrapper`, you can do the
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following:
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```sh
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export WORKON_HOME=~/pyenvs
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mkdir -p $WORKON_HOME
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source /usr/local/bin/virtualenvwrapper.sh # location may vary
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mkvirtualenv pt
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```
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Once you have a virtual environment setup, you can start install the `models`
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plugin with:
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```sh
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workon pt
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git clone git@github.com:si-cim/prototorch_models.git
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cd prototorch_models
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git checkout dev
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pip install -e .[all] # \[all\] if you are using zsh or MacOS
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```
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To assist in the development process, you may also find it useful to install
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`yapf`, `isort` and `autoflake`. You can install them easily with `pip`.
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## Available models
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- k-Nearest Neighbors (KNN)
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- Learning Vector Quantization 1 (LVQ1)
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- Generalized Learning Vector Quantization (GLVQ)
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- Generalized Relevance Learning Vector Quantization (GRLVQ)
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- Generalized Matrix Learning Vector Quantization (GMLVQ)
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- Limited-Rank Matrix Learning Vector Quantization (LiRaMLVQ)
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- Learning Vector Quantization Multi-Layer Network (LVQMLN)
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- Siamese GLVQ
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- Neural Gas (NG)
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## Work in Progress
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- Classification-By-Components Network (CBC)
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- Learning Vector Quantization 2.1 (LVQ2.1)
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## Planned models
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- Median-LVQ
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- Local-Matrix GMLVQ
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- Generalized Tangent Learning Vector Quantization (GTLVQ)
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- Robust Soft Learning Vector Quantization (RSLVQ)
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- Probabilistic Learning Vector Quantization (PLVQ)
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- Self-Incremental Learning Vector Quantization (SILVQ)
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## FAQ
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### How do I update the plugin?
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If you have already cloned and installed `prototorch` and the
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`prototorch_models` plugin with the `-e` flag via `pip`, all you have to do is
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navigate to those folders from your terminal and do `git pull` to update.
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