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Understand the C++ library

The TensorFlow Lite for Microcontrollers C++ library is part of the TensorFlow repository. It is designed to be readable, easy to modify, well-tested, easy to integrate, and compatible with regular TensorFlow Lite.

The following document will outline the basic structure of the C++ library, provide the commands required for compilation, and give an overview of how to port to new devices.

The README.md contains more in-depth information on all of these topics.

File structure

The micro root directory has a relatively simple structure. However, since it is located inside of the extensive TensorFlow repository, we have created scripts and pre-generated project files that provide the relevant source files in isolation within various embedded development environments such as Arduino, Keil, Make, and Mbed.

Key files

The most important files for using the TensorFlow Lite for Microcontrollers interpreter are located in the root of the project, accompanied by tests:

See Get started with microcontrollers for a walkthrough of typical usage.

The build system provides for platform-specific implementations of certain files. These are located in a directory with the platform name, for example sparkfun_edge.

Several other directories exist, including:

  • kernel, which contains operation implementations and the associated code.
  • tools, which contains build tools and their output.
  • examples, which contains sample code.

Generate project files

The project's Makefile is able to generate standalone projects containing all necessary source files that can be imported into embedded development environments. The current supported environments are Arduino, Keil, Make, and Mbed.

To generate these projects with Make, use the following command:

make -f tensorflow/lite/experimental/micro/tools/make/Makefile generate_projects

This will take a few minutes, since it has to download some large toolchains for the dependencies. Once it has finished, you should see some folders created inside a path like tensorflow/lite/experimental/micro/tools/make/gen/linux_x86_64/prj/ (the exact path depends on your host operating system). These folders contain the generated project and source files. For example, tensorflow/lite/experimental/micro/tools/make/gen/linux_x86_64/prj/keil contains the Keil uVision targets.

Build the library

If you are using a generated project, see its included README for build instructions.

To build the library and run tests from the main TensorFlow repository, run the following commands:

  1. Clone the TensorFlow repository from GitHub to a convenient place.
git clone --depth 1 https://github.com/tensorflow/tensorflow.git
  1. Enter the directory that was created in the previous step.
cd tensorflow
  1. Invoke the Makefile to build the project and run tests. Note that this will download all required dependencies:
make -f tensorflow/lite/experimental/micro/tools/make/Makefile test

Port to new devices

Guidance on porting TensorFlow Lite for Microcontrollers to new platforms and devices can be found in README.md.