Sinabs (Sinabs Is Not A Brain Simulator) is a python library for the development and implementation of Spiking Convolutional Neural Networks (SCNNs).
The library implements several layers that are spiking equivalents of CNN layers.
In addition it provides support to import CNN models implemented in torch conveniently to test their spiking equivalent implementation.
This project is managed by SynSense (former aiCTX AG).
The sinabs-dynapcnn was incorporated to this project, and it enables porting sinabs models to chips and dev-kits with DYNAP-CNN technology.
For the stable release on the main branch:
pip install sinabs
or (thanks to @Tobias-Fischer)
conda install -c conda-forge sinabs
For the latest pre-release on the develop branch that passed the tests:
pip install sinabs --pre
The package has been tested on the following configurations
https://sinabs.readthedocs.io/
Please join us on the #sinabs Discord channel!
Sinabs is published under AGPL v3.0. See the LICENSE file for details.
Checkout the contributing page for more info.
In case you find this software library useful for your work please consider citing it as follows:
@software{sinabs,
author = {Sheik, Sadique and Lenz, Gregor and Bauer, Felix and Kuepelioglu, Nogay },
doi = {10.5281/zenodo.8385545},
license = {AGPL-3.0},
title = {{SINABS: A simple Pytorch based SNN library specialised for Speck}},
url = {https://github.com/synsense/sinabs}
}
FAQs
SynSense Spiking Neural Network simulator for deep neural networks (DNNs).
We found that sinabs demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.
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