NengoDL 1.1.0 released

The NengoDL team is happy to announce the release of NengoDL 1.1.0.

What is NengoDL?

NengoDL is a backend for Nengo that integrates deep learning methods (supported by the TensorFlow framework) with other Nengo modelling tools. This allows users to optimize their models using deep learning training methods, improves simulation speed (on CPU or GPU), and makes it easy to insert TensorFlow models (such as a convolutional neural network) into Nengo networks.

How do I use it?

To use NengoDL, replace instances of nengo.Simulator with nengo_dl.Simulator.

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.

What’s new?

The 1.1.0 release contains a number of usability improvements. We’ve added the new sim.freeze_params feature to make it easy to transfer an optimized NengoDL model to a different Nengo Simulator (you can read more about that here. Along with that we’ve improved the speed of fetching trained parameters from the simulation. We’ve also added a couple useful warnings or error messages in places where previous user feedback wasn’t clear (e.g., when attempting to train a network with non-differentiable elements). You may also notice that all previous NengoDL releases are now tracked in the documentation, handy for those looking for examples/documentation for an earlier version. Check out the GitHub release page for a full changelog.

How do I get it?

To install NengoDL, we recommend using pip:

pip install nengo-dl

More detailed installation instructions can be found here.

Where can I learn more?

Where can I get help?

Please come to the Nengo forum! We welcome any questions and suggestions you might have.