This repository is the official implementation of Bispectral Neural Networks.
To install the requirements and package, run:
pip install -r requirements.txt
python setup.py install
To download the datasets, run:
wget --load-cookies /tmp/cookies.txt "https://docs.google.com/uc?export=download&confirm=$(wget --quiet --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=10w3fKdO0eWEe2KxZxpf8YFndXdCNNR8b' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=10w3fKdO0eWEe2KxZxpf8YFndXdCNNR8b" -O datasets.zip
rm -rf /tmp/cookies.txt
unzip datasets.zip
rm -r datasets.zip
If your machine doesn't have wget, follow these steps:
- Download the zip file here.
- Place the file in the top node of this directory, i.e. in
bispectral-networks/. - Run:
unzip datasets.zip rm -r datasets.zip
To train the models in the paper, run the following commands.
python train.py --config rotation_experiment
python train.py --config translation_experiment
To run on GPU, add the following argument, with the integer specifying the device number, i.e.:
--device 0
The full set of hyperparameters and training configurations are specified in the config files in the configs/ folder.
To view learning curves in Tensorboard, run:
tensorboard --logdir logs/
The pre-trained models are included in the repo, in the following locations:
logs/rotation_model/
logs/translation_model/
All results and figures from the paper are generated in the Jupyter notebooks located at:
notebooks/rotation_experiment_analysis.ipynb
notebooks/translation_experiment_analysis.ipynb
This repository is licensed under the MIT License.