Spiking neural network conversion toolbox
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].
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Release files for snntoolbox 0.6.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| snntoolbox-0.6.0.tar.gz | 144.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| snntoolbox-0.6.0-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 348.8 kB
Release files / snntoolbox-0.6.0.tar.gz
| Download URL | snntoolbox-0.6.0.tar.gz |
|---|---|
| Size | 144.9 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/44.0.0.post20200106 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.7.6
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Release files / snntoolbox-0.6.0-py2.py3-none-any.whl
| Download URL | snntoolbox-0.6.0-py2.py3-none-any.whl |
|---|---|
| Size | 203.9 kB |
| Tags | Python 2 Python 3 |
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SHA-256 checksum How to use checksums |
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twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/44.0.0.post20200106 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.7.6
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