Under STM32CubeIDE I generated a neural network form my Nucleo board with X-CUBE-AI 9.0.0 from a quantized TFLite model of a sine function. I followed the same steps as I did about one year ago with X-CUBE-AI 8.1.0 (at the time it worked) but this time, when I perform inference, the network answers with constant output independent on its input. My steps are essentially these:
- Create a project for my board (Nucleo F767ZI);
- Add the X-CUBE-AI 9.0.0 pack and the TFLite model;
- Accept all the optimizations that the IDE proposes;
- Activate the CRC;
- Generate code;
- Add in the main() the code to create the network / set the activations, input and output buffers / run the network; The code is almost identical to the example contained in the X-CUBE-AI documentation.
My development platform is a MacBook Pro with M3 chip and Sequoia OS. It is likely that I missed something, since one year passed and I possibly forgot to write down some details of the configuration, but I tried all the variations of the configurations that I could think about and nothing seems to work. I include my STM32CubeIDE project in attachment. If anyone is able to spot any error, I will be grateful.
