The NengoDL team is happy to announce the release of NengoDL 3.4.1.
NengoDL is a backend for Nengo that integrates deep learning methods (supported by the TensorFlow framework) with other Nengo modelling tools. NengoDL allows users to optimize their models using deep learning training methods, improves simulation speed (on CPU or GPU), can automatically convert Keras models to Nengo networks, and makes it easy to insert TensorFlow code (individual functions or whole network architectures) into Nengo networks.
To use NengoDL, replace instances of
For example, if you have a network called
net and you run it as
with nengo.Simulator(net) as sim: sim.run(10)
you would change that to
with nengo_dl.Simulator(net) as sim: sim.run(10)
and that’s it!
Information on accessing the more advanced features of NengoDL can be found in the documentation.
3.4.1 is a small compatibility release. It adds compatibility with TensorFlow 2.5.0, and drops support for Python 3.5. Check out the GitHub release page for a full changelog.
To install NengoDL, we recommend using
pip install nengo-dl
More detailed installation instructions can be found here.
You’re already there! If you have an issue upgrading or have any other questions, please post them in this forum.