Example for using model_profiler.cc

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Aakash Tyagi

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Apr 12, 2022, 10:24:43 AMApr 12
to SIG Micro
Hi Team, I am trying to use the model_profiler api for measuring inference time per layer of my model. Due to lack of documentation I am unable to figure out how to use that.
If anyone can provide a working example for hello_world it would be really helpful.

Thanks

Joe Antognini

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Apr 12, 2022, 6:36:19 PMApr 12
to Aakash Tyagi, SIG Micro
Hi Aakash,

I was able to get the profiler working a little while back so I can share how I did it.  The way to set up the profiler will be microprocessor dependent.  You will need to have access to a function that gives you the system time.  Basically, the profiler relies on two functions which have been stubbed out in micro_time.cc.  One is ticks_per_second and the other is GetCurrentTimeTicks.  You may need to create a version of `micro_time.cc` that implements these functions for your hardware.  Versions of `micro_time.cc` have already been implemented for a variety of different kinds of microprocessors in the different subdirectories in `tflite-micro/tensorflow/lite/micro/`.  If your microprocessor is already there, you just need to link to the correct version of `micro_time.cc` when you compile TFLM.

If your microprocessor is not there, you will need to add the appropriate `microe_time.cc` file yourself.  What I did was to implement this through some callbacks.  So in a file called `tflite-micro/tensorflow/lite/micro/<my_microprocessor>/micro_time.cc` I have:

static CurrentTimeCallback current_time_callback = nullptr;
static TicksPerSecondCallback ticks_per_second_callback = nullptr;

void RegisterCurrentTimeCallback(CurrentTimeCallback cb) {
  current_time_callback = cb;
}

void RegisterTicksPerSecondCallback(TicksPerSecondCallback cb) {
  ticks_per_second_callback = cb;
}

int32_t ticks_per_second() {
    return (int32_t)ticks_per_second_callback();
}

int32_t GetCurrentTimeTicks() {
    return (int32_t)current_time_callback();
}

Once you've done that, in your main function you can then do something like this:

#include "tensorflow/lite/micro/<my_microprocessor>/micro_time_callback.h"

// Register the callbacks with the appropriate timer calls on your system
// (May not be needed if model_time.cc can already find the right functions.)
tflite::RegisterCurrentTimeCallback(<my_microprocessors_timer_function>);
tflite::RegisterTicksPerSecondCallback(<my_microprocessors_clock_frequency_function>);

// Create a profiler
tflite::MicroProfiler profiler;

// Include it when you create your interpreter.
tflite::MicroInterpreter interpreter = MicroInterpreter(model, ..., &profiler);

// Invoke your model as normal.
interpreter.Invoke();

// Now you can just do this and it will print out the per-layer times.
profiler.Log();

Hope that helps!

Best,
Joe Antognini

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