The Nengo team is pumped to announce the release of Nengo 2.5.0!
What is Nengo?
Nengo is a Python library for building and simulating large-scale neural models for AI and robotics. It can be thought of as a neural compiler, transforming a functional description of a neural model to a network of spiking or non-spiking neurons that can run on multiple backends including GPUs and neuromorphic hardware.
What’s new?
Nengo 2.5.0 contains several improvements to documentation, bugfixes, and a few new features.
Networks now have an n_neurons property that gives the number of neurons in the network, including all subnetworks.
It is now possible to combine LinearFilter synapses, to implement more complex synapses types like double exponentials.
Neuron types can now determine maximum firing rates and intercepts given gain and bias values. If the gain and bias is specified, the maximum firing rates and intercepts will be determined in the build process, or can be found at any time using the max_rates_intercepts method.
To see the full list of changes in Nengo 2.5.0, head to the Github release page.
How do I get it?
To get the new version of Nengo, use pip.
pip install --upgrade nengo
Where can I learn more?
Where can I get help?
You’re already there! If you have an issue upgrading or have any other questions, please post them in this forum.