Cannot use neural network model in ST Edge AI

[brianon]

Hi,

I'm working with implementing a Spiking Neural Network on a neural ART equipped STM32N6 board. As a true SNN has operators that are not supported by the STEdgeAI compiler, I have opted to create a ANN model that simulates spiking behaviour. My problem is that the current approach utilizes custom RNN layers which seem to not be supported either by STEdge nor by TFLite conversion. A partial solution for that was to unroll my "RNN layers" by using a fixed time step. This allowed me to convert my model into TFLite but when I import my model into the STEdgeAI suite I seem to be unable to neither quantize, optimize or benchmark it. Am I still using something unsupported which blocks me from using my model? Or am I missing some other step to use my model in STEdgeAI?

Attached is the unrolled single neuron model in ".tflite", snn_to_ann_neuron.py which is the original implementation, and unrolled_s2a.py which is my code to unroll it.

Thanks in advance!

[Julian E.]

Hello @brianon,

What command did you use?

For a non neural art stm32 and with the stedgeai core v2.1, I successfully generated the code for your attached model.

stedgeai.exe generate --model snu_model_float32.tflite --target stm32

ST Edge AI Core v2.1.0-20194

Have a good day,

Julian