The Nengo DL team is tickled to announce the release of Nengo DL 0.6.1.
Nengo DL 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.
To use Nengo DL, replace instances of
For example, if you have a network called
model and you run it with
with nengo.Simulator(model) as sim: sim.run(10)
you would change that to
with nengo_dl.Simulator(model) as sim: sim.run(10)
and that’s it!
Information on accessing the more advanced features of Nengo DL can be found in the documentation.
0.6.1 contains a number of quality of life improvements. Improved handling of optimizer initialization, more consistent management of shapes for simulation data, and updates to support the latest Nengo release, including the new
SpikingRectifiedLinear neuron model. Check out the GitHub release page for a full changelog.
To install Nengo DL, we recommend using
pip install nengo_dl
More detailed installation instructions can be found here.
Please come to the Nengo forum! We welcome any questions and suggestions you might have.