This page describes how to build the TensorFlow Lite static library for ARM64-based computers. If you just want to start using TensorFlow Lite to execute your models, the fastest option is to install the TensorFlow Lite runtime package as shown in the Python quickstart.
Cross-compile for ARM64
To ensure the proper build environment, we recommend using one of our TensorFlow Docker images such as tensorflow/tensorflow:nightly-devel.
To get started, install the toolchain and libs:
sudo apt-get update
sudo apt-get install crossbuild-essential-arm64
If you are using Docker, you may not use sudo.
Now git-clone the TensorFlow repository
(https://github.com/tensorflow/tensorflow)—if you're using the TensorFlow
Docker image, the repo is already provided in /tensorflow_src/—and then run
this script at the root of the TensorFlow repository to download all the
build dependencies:
./tensorflow/lite/tools/make/download_dependencies.sh
Note that you only need to do this once.
Then compile:
./tensorflow/lite/tools/make/build_aarch64_lib.sh
This should compile a static library in:
tensorflow/lite/tools/make/gen/aarch64_armv8-a/lib/libtensorflow-lite.a.
Compile natively on ARM64
These steps were tested on HardKernel Odroid C2, gcc version 5.4.0.
Log in to your board and install the toolchain:
sudo apt-get install build-essential
Now git-clone the TensorFlow repository
(https://github.com/tensorflow/tensorflow) and run this at the root of
the repository:
./tensorflow/lite/tools/make/download_dependencies.sh
Note that you only need to do this once.
Then compile:
./tensorflow/lite/tools/make/build_aarch64_lib.sh
This should compile a static library in:
tensorflow/lite/tools/make/gen/aarch64_armv8-a/lib/libtensorflow-lite.a.