The tension package is a Python package for building and FORCE training chaotic recurrent neural networks. tension is built to integrate seamlessly with TensorFlow/Keras, a widely used software package for training artificial neural networks.
Installation guide, contributing guide, and API reference are available on the documentation website
Example notebooks for reproducing the experiments in the associated software report can also be found on the documentation website and in the examples folder. These notebooks can be run either in Google Colab or in a local jupyter notebook.
Documentation for TensorFlow/Keras, on which tension is based and interoperable with, can be found at the TensorFlow guide.
tension depends on Python >= 3.7, tensorflow>=2.5, numpy and matplotlib.
We recommend installing tension into a conda environment
conda create -n tension python=3.7
followed by
conda activate tension
Clone this repo using
git clone https://github.com/zhenruiliao/tension.git
Change into the tension directory and install using pip
cd tension/
pip install -e .
pip install tension
To quickly get started with tension, the package can also be installed in Google Colab using the following commands
!git clone https://github.com/zhenruiliao/tension.git tension
!pip install -e tension
The runtime must be restarted for the package to become importable
Bug reports, feature requests, and pull requests are welcome and encouraged! Use the Issues and Pull requests tabs to open new issues or pull requests. Always be kind and respectful.
tension is provided under the MIT License. TensorFlow is provided under the Apache 2.0 license.
Based on work by David Sussillo and Larry Abbott https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2756108/
With thanks to James Priestley for the package name.