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).
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I'd try increasing the arena size. The AllocateTensors() call allocates all the tensor space from there.
On Tuesday, August 10, 2021 at 12:53:21 PM UTC-7 James B. wrote:
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).
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