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], [Rueckauer and Liu, 2018], and [Rueckauer and Liu, 2021].
