ef6bcc1079
The early stopping callback does not work as expected, and crashes at the end of
max_epochs with:
```
~/miniconda3/envs/py38/lib/python3.8/site-packages/pytorch_lightning/trainer/callback_hook.py in on_train_end(self)
155 """Called when the train ends."""
156 for callback in self.callbacks:
--> 157 callback.on_train_end(self, self.lightning_module)
158
159 def on_pretrain_routine_start(self) -> None:
~/work/repos/prototorch_models/prototorch/models/callbacks.py in on_train_end(self, trainer, pl_module)
18 def on_train_end(self, trainer, pl_module):
19 # instead, do it at the end of training loop
---> 20 self._run_early_stopping_check(trainer, pl_module)
21
22
TypeError: _run_early_stopping_check() takes 2 positional arguments but 3 were given
```
|
||
|---|---|---|
| docs | ||
| examples | ||
| prototorch/models | ||
| tests | ||
| .bumpversion.cfg | ||
| .codacy.yml | ||
| .codecov.yml | ||
| .gitignore | ||
| .readthedocs.yml | ||
| .travis.yml | ||
| LICENSE | ||
| README.md | ||
| setup.py | ||
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.
Available models
LVQ Family
- Learning Vector Quantization 1 (LVQ1)
- Generalized Learning Vector Quantization (GLVQ)
- Generalized Relevance Learning Vector Quantization (GRLVQ)
- Generalized Matrix Learning Vector Quantization (GMLVQ)
- Localized and Generalized Matrix Learning Vector Quantization (LGMLVQ)
- Limited-Rank Matrix Learning Vector Quantization (LiRaMLVQ)
- Learning Vector Quantization Multi-Layer Network (LVQMLN)
- Siamese GLVQ
- Cross-Entropy Learning Vector Quantization (CELVQ)
- Robust Soft Learning Vector Quantization (RSLVQ)
Other
- k-Nearest Neighbors (KNN)
- Neural Gas (NG)
- Growing Neural Gas (GNG)
Work in Progress
- Classification-By-Components Network (CBC)
- Learning Vector Quantization 2.1 (LVQ2.1)
Planned models
- Median-LVQ
- Generalized Tangent Learning Vector Quantization (GTLVQ)
- Probabilistic Learning Vector Quantization (PLVQ)
- Self-Incremental Learning Vector Quantization (SILVQ)
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
Note: Please avoid installing Tensorflow in this environment.
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.
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.