Post-training integer quantization seems not to work on microcontroller

James B.

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Aug 10, 2021, 3:53:21 PM8/10/21

to SIG Micro

I'd like to print inference time on a serial terminal for a Keras model (with a STM32F401RE microcontroller) which has as an input sample a 2D tensor of shape (500, 1, 1). However, when I try to allocate tensors with the interpreter, the program hangs after entering AllocateTensors() function. Could it be caused by a dimension of the model too large (.tflite file is 67 KB and .h file is 412 KB)? I tried to use post-training integer quantization through TFLite Converter, but the situation doesn't change.

I attached the Keras model (in tcn_scratch.py) and the C++ model (in main.cpp).

Best regards.

tcn_scratch.py

main.cpp

Rocky Rhodes

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Aug 10, 2021, 9:02:06 PM8/10/21

to SIG Micro, James B.

I'd try increasing the arena size. The AllocateTensors() call allocates all the tensor space from there.

Advait Jain

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Aug 11, 2021, 1:04:04 AM8/11/21

to Rocky Rhodes, tfl...@tensorflow.org, SIG Micro, James B.

+tf...@tensorflow.org

Combining the threads on the same topic on two different mailing lists.

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