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TinyML Cookbook

You're reading from   TinyML Cookbook Combine artificial intelligence and ultra-low-power embedded devices to make the world smarter

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781801814973
Length 344 pages
Edition 1st Edition
Tools
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Author (1):
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Gian Marco Iodice Gian Marco Iodice
Author Profile Icon Gian Marco Iodice
Gian Marco Iodice
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Table of Contents (10) Chapters Close

Preface 1. Chapter 1: Getting Started with TinyML 2. Chapter 2: Prototyping with Microcontrollers FREE CHAPTER 3. Chapter 3: Building a Weather Station with TensorFlow Lite for Microcontrollers 4. Chapter 4: Voice Controlling LEDs with Edge Impulse 5. Chapter 5: Indoor Scene Classification with TensorFlow Lite for Microcontrollers and the Arduino Nano 6. Chapter 6: Building a Gesture-Based Interface for YouTube Playback 7. Chapter 7: Running a Tiny CIFAR-10 Model on a Virtual Platform with the Zephyr OS 8. Chapter 8: Toward the Next TinyML Generation with microNPU 9. Other Books You May Enjoy

Generating C code with TVM

Compiling the TFLite model to C code is straightforward with TVM. TVM only needs an input model, a target device, and a single command line to generate a TAR package with the generated C code.

In this recipe, we will show how to convert a pretrained CIFAR-10 model into C code with microTVM, an extension of TVM for microcontroller deployment.

The following Bash script contains the commands referred to in this recipe:

  • compile_model_microtvm.sh:

https://github.com/PacktPublishing/TinyML-Cookbook/blob/main/Chapter08/BashScripts/compile_model_microtvm.sh

Getting ready

In this section, we will examine how TVM can generate C code and explain what microTVM is.

TVM is a DL compiler technology that we can use in Python and in the same environment where we build, train, and quantize the model with TFLite. Although TVM natively offers a Python API, there is an alternative and more straightforward API that is based on a command-line interface...

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