Reader small image

You're reading from  TinyML Cookbook - Second Edition

Product typeBook
Published inNov 2023
PublisherPackt
ISBN-139781837637362
Edition2nd Edition
Right arrow
Author (1)
Gian Marco Iodice
Gian Marco Iodice
author image
Gian Marco Iodice

Gian Marco Iodice is team and tech lead in the Machine Learning Group at Arm, who co-created the Arm Compute Library in 2017. The Arm Compute Library is currently the most performant library for ML on Arm, and it's deployed on billions of devices worldwide – from servers to smartphones. Gian Marco holds an MSc degree, with honors, in electronic engineering from the University of Pisa (Italy) and has several years of experience developing ML and computer vision algorithms on edge devices. Now, he's leading the ML performance optimization on Arm Mali GPUs. In 2020, Gian Marco cofounded the TinyML UK meetup group to encourage knowledge-sharing, educate, and inspire the next generation of ML developers on tiny and power-efficient devices.
Read more about Gian Marco Iodice

Right arrow

Getting ready

The main advantage we have found in all projects developed with tflite-micro is certainly code portability. Regardless of the target device, the model inference can be accelerated on various devices using almost the same application code, which can be exemplified with the following pseudocode:

model = load_model(tflite_model)
model.allocate_memory()
model.invoke();

In the preceding code snippet, we do the following:

  1. Load the model at runtime with load_model()
  2. Allocate the memory required for the model inference with allocate_memory()
  3. Invoke the model inference with invoke()

When writing the tflite-micro application code, it is not strictly necessary to have prior knowledge of the target microcontroller because the software stack takes advantage of vendor-specific optimized operator libraries (performance libraries) to execute the model efficiently. As a result, the selection of the appropriate set of optimized operators happens...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
TinyML Cookbook - Second Edition
Published in: Nov 2023Publisher: PacktISBN-13: 9781837637362

Author (1)

author image
Gian Marco Iodice

Gian Marco Iodice is team and tech lead in the Machine Learning Group at Arm, who co-created the Arm Compute Library in 2017. The Arm Compute Library is currently the most performant library for ML on Arm, and it's deployed on billions of devices worldwide – from servers to smartphones. Gian Marco holds an MSc degree, with honors, in electronic engineering from the University of Pisa (Italy) and has several years of experience developing ML and computer vision algorithms on edge devices. Now, he's leading the ML performance optimization on Arm Mali GPUs. In 2020, Gian Marco cofounded the TinyML UK meetup group to encourage knowledge-sharing, educate, and inspire the next generation of ML developers on tiny and power-efficient devices.
Read more about Gian Marco Iodice