Tensorflow 2.1.0 for microcontrollers benchmarks on STM32F746 #ML #MLmonday @ST_World

Stupid Projects benchmarks Tensorflow 2.1.0 for microcontrollers on the STM32F746.

Over 8 months ago I’ve started writing the Machine Learning for Embedded post series, which starts here. The 3rd post in this series (here) was about using the tensorflow lite for microcontrollers on the STM32746NGH6U (STM32F746-disco board). At that post I’ve did some benchmarks and in the next post, I’ve compared the performance with the X-CUBE-AI framework from ST.

At that time the latest TF version was 1.14.0 and the tflite-micro was still in experimental state. The performance was quite bad compared to X-CUBE-AI. CMSIS-DSP and CMSIS-NN was not supported and also optimized or compressed models weren’t supported, too. When I tried to use an optimized model then I was getting an error that INT8 is not supported in the framework.

So, after almost a year TF is now in version 2.1.0,  2.2.0 is around the corner and also the tflite-micro is no longer experimental. Also, CMSIS-DSP/NN is now supported for many kernels as also optimized models. Therefore, I felt like it make sense to give another try.

See the surprising results in the post.


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