Spiking neural network conversion toolbox
Project description
The SNN conversion toolbox (SNN-TB) is a framework to transform rate-based artificial neural networks into spiking neural networks, and to run them using various spike encodings. A unique feature about SNN-TB is that it accepts input models from many different deep-learning libraries (Keras / TF, pytorch, …) and provides an interface to several backends for simulation (pyNN, brian2, …) or deployment (SpiNNaker, Loihi).
Please refer to the Documentation for a complete user guide and API reference. See also the accompanying articles [Rueckauer et al., 2017] and [Rueckauer and Liu, 2018].
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for snntoolbox-0.4.1-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d49160051b8578389f68bbc5d16ddf966793796eac61a0ee27da908a8dc60737 |
|
MD5 | fbdfcba5b50cb81fd445a90ad89b288c |
|
BLAKE2b-256 | b74fc5db710f03ac518db982b2e6ddeef694ca1cc54b87cdaa55e729f6a60d50 |