Keras Model Converter and Neuron Type Not Supported Nengo_Loihi Simulator

Backends Loihi
11

Hi @drasmuss,

Thanks for the reply. I am using tensorflow 2.1. In the case of swap_activations={tf.nn.relu: nengo.SpikingRectifiedLinear()}, I used the following code to print neuron_types as mentioned above:

Blockquote
nengo_converter = nengo_dl.Converter(model, allow_fallback=False, swap_activations={tf.nn.relu: nengo.SpikingRectifiedLinear()})
net = nengo_converter.net
for ensemble in net.ensembles: print(ensemble, ensemble.neuron_type)

and the following is the output:

Blockquote
<Ensemble “conv2d.0”> RectifiedLinear()
<Ensemble “conv2d_1.0”> RectifiedLinear()
<Ensemble “conv2d_2.0”> RectifiedLinear()
<Ensemble “conv2d_3.0”> RectifiedLinear()
<Ensemble “conv2d_4.0”> RectifiedLinear()
<Ensemble “conv2d_5.0”> RectifiedLinear()
<Ensemble “conv2d_6.0”> RectifiedLinear()
<Ensemble “conv2d_7.0”> RectifiedLinear()
<Ensemble “conv2d_8.0”> RectifiedLinear()
<Ensemble “conv2d_9.0”> RectifiedLinear()
<Ensemble “dense.0”> RectifiedLinear()

If I used swap_activations={nengo.RectifiedLinear(): nengo.SpikingRectifiedLinear()}, then the output became:

Blockquote
<Ensemble “conv2d.0”> SpikingRectifiedLinear()
<Ensemble “conv2d_1.0”> SpikingRectifiedLinear()
<Ensemble “conv2d_2.0”> SpikingRectifiedLinear()
<Ensemble “conv2d_3.0”> SpikingRectifiedLinear()
<Ensemble “conv2d_4.0”> SpikingRectifiedLinear()
<Ensemble “conv2d_5.0”> SpikingRectifiedLinear()
<Ensemble “conv2d_6.0”> SpikingRectifiedLinear()
<Ensemble “conv2d_7.0”> SpikingRectifiedLinear()
<Ensemble “conv2d_8.0”> SpikingRectifiedLinear()
<Ensemble “conv2d_9.0”> SpikingRectifiedLinear()
<Ensemble “dense.0”> SpikingRectifiedLinear()

which is the same as yours. I noticed that I printed out neuron_type of net.ensembles and in your code you printed out the one of net.all_ensembles, so are these two attributes different?

Will