TFlite-builds

TFlite cross-platform builds. Current stable version: 2.18.0.

Why this repo?

The information provided in the official tensorflow lite page for building whl packages for ARM to cross-compile TFlite for different architectures is a good start. However there seem to be several issues. This repo aims at providing more info towards successful compilation. And some binaries as well.

The provided builds are fully compatible with Coral.ai EdgeTPU through the updated libedgetpu drivers.

Building - Docker

• Install docker:

sudo apt install docker.io

• Download tensorflow and checkout the relevant version.

git clone https://github.com/tensorflow/tensorflow.git

cd tensorflow

git checkout vX.XX.XX

If compiling against python 3.11 or newer, you have to allow installation of whl packages from external sources. Add the following line in tensorflow/lite/tools/pip_package/Dockerfile.py3:

    RUN ln -sf /usr/bin/python$PYTHON_VERSION /usr/bin/python3
    RUN curl -OL https://bootstrap.pypa.io/get-pip.py
->  RUN rm /usr/lib/python$PYTHON_VERSION/EXTERNALLY-MANAGED
    RUN python3 get-pip.py
    RUN rm get-pip.py

Optional: update cmake by editing tensorflow/lite/tools/pip_package/Dockerfile.py3 to replace:

RUN curl -OL https://github.com/Kitware/CMake/releases/download/v3.16.8/cmake-3.16.8-Linux-x86_64.sh
RUN mkdir /opt/cmake
RUN sh cmake-3.16.8-Linux-x86_64.sh --prefix=/opt/cmake --skip-license

with:

RUN curl -OL https://github.com/Kitware/CMake/releases/download/v3.29.6/cmake-3.29.6-linux-x86_64.sh
RUN mkdir /opt/cmake
RUN sh cmake-3.29.6-linux-x86_64.sh --prefix=/opt/cmake --skip-license

• Edit Makefile to your system tensorflow/lite/tools/pip_package/Makefile:

For Python 3.11 and earlier:

# Values: debian:<version>, ubuntu:<version>
BASE_IMAGE ?= ubuntu:22.04
PYTHON_VERSION ?= 3.11
NUMPY_VERSION ?= 1.24.4

For Python 3.12 and later:

# Values: debian:<version>, ubuntu:<version>
BASE_IMAGE ?= ubuntu:22.04
PYTHON_VERSION ?= 3.12
NUMPY_VERSION ?= 1.26.4

Changes specific to Ubuntu 24.04 and newer

• Replace the file tensorflow/lite/tools/pip_package/update_sources.sh with the one provided in this repository.
• In the file tensorflow/lite/tools/pip_package/Makefile replace:

docker-build: docker-image
	mkdir -p $(TENSORFLOW_DIR)/bazel-ci_build-cache
	docker run \
		--rm --interactive $(shell tty -s && echo --tty) \
		$(DOCKER_PARAMS) \
		$(TAG_IMAGE) \
		/with_the_same_user /bin/bash -C /tensorflow/tensorflow/lite/tools/pip_package/build_pip_package_with_cmake.sh $(TENSORFLOW_TARGET)

with

docker-build: docker-image
  mkdir -p $(TENSORFLOW_DIR)/bazel-ci_build-cache
  docker run \
  	--rm --interactive $(shell tty -s && echo --tty) \
  	$(DOCKER_PARAMS) \
  	$(TAG_IMAGE) \
      /bin/bash -C /tensorflow/tensorflow/lite/tools/pip_package/build_pip_package_with_cmake.sh $(TENSORFLOW_TARGET)

• In the file tensorflow/lite/tools/pip_package/Dockerfile.py3 remove:

python$PYTHON_VERSION \
      python$PYTHON_VERSION-dev \
      python$PYTHON_VERSION-venv \
-->   python$PYTHON_VERSION-distutils \
      libpython$PYTHON_VERSION-dev \
      libpython$PYTHON_VERSION-dev:armhf \
      libpython$PYTHON_VERSION-dev:arm64

Building using Debian

If you are building for debian:bookworm or debian:bullseye, you need to remove/comment the following line from tensorflow/lite/tools/pip_package/Dockerfile.py3, since the added ppa repository is specific only to ubuntu.

RUN yes | add-apt-repository ppa:deadsnakes/ppa

Compilation

• Run compilation (adjust the values for TENSORFLOW_TARGET and PYTHON_VERSION to fit your needs:

BUILD_NUM_JOBS=4 make -C tensorflow/lite/tools/pip_package docker-build TENSORFLOW_TARGET=aarch64 PYTHON_VERSION=3.11

Note: You can change the variable BUILD_NUM_JOBS from 4 to $(nproc) to use the max number of cores in your CPU for fastest compilation.

These are the supported targets.

• armhf: ARMv7 VFP with Neon Compatible with Raspberry Pi 3 and 4
• rpi0: ARMv6 Compatible with Raspberry Pi Zero
• aarch64: aarch64 (ARM 64-bit) Coral Mendel Linux 4.0 or Raspberry Pi with Ubuntu Server 20.04.01 LTS 64-bit of 22.04.x LTS 64-bit
• native: Your workstation It builds with "-mnative" optimization

Building - Native

Using Bazel

export TF_PYTHON_VERSION=3.12; PYTHON=python3 tensorflow/lite/tools/pip_package/build_pip_package_with_bazel.sh native

Using CMake

BUILD_NUM_JOBS=4 PYTHON=python3 tensorflow/lite/tools/pip_package/build_pip_package_with_cmake.sh native

Note: You can change the variable BUILD_NUM_JOBS from 4 to $(nproc) to use the max number of cores in your CPU for fastest compilation.

GPU support for native builds

When compiling with either docker or native using cmake GPU support is disableed by default. To enable it, edit this file:

nano tensorflow/lite/tools/pip_package/build_pip_package_with_cmake.sh

and add to line 110:

     native)
       BUILD_FLAGS=${BUILD_FLAGS:-"-march=native -I${PYTHON_INCLUDE} -I${PYBIND11_INCLUDE} -I${NUMPY_INCLUDE}"}
       cmake \
         -DCMAKE_C_FLAGS="${BUILD_FLAGS}" \
         -DCMAKE_CXX_FLAGS="${BUILD_FLAGS}" \
  ==>    -DTFLITE_ENABLE_GPU=ON \
         "${TENSORFLOW_LITE_DIR}"