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BUILD.md

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Build Instructions

  1. Prerequisites
  2. OpenVINO™ integration with TensorFlow
  3. OpenVINO™
  4. TensorFlow
  5. Build ManyLinux2014 compatible OpenVINO™ integration with TensorFlow wheels

First, clone the openvino_tensorflow repository:

$ git clone https://github.com/openvinotoolkit/openvino_tensorflow.git
$ cd openvino_tensorflow
$ git submodule init
$ git submodule update --recursive

1. Prerequisites

1.1. Ubuntu

  1. Install apt packages

    # users may need sudo access to install some of the dependencies  
$ apt-get update
$ apt-get install python3 python3-dev
$ apt-get install -y --no-install-recommends ca-certificates autoconf automake build-essential \
libtool unzip git unzip wget zlib1g zlib1g-dev bash-completion \
build-essential cmake zip golang-go locate curl clang-format cpio libtinfo-dev jq \
lsb-core libusb-1.0-0-dev patchelf
    # install required gcc package (Optional; if gcc-7 is not installed)
$ apt-get install gcc-7 g++-7  

# if multiple gcc versions are installed then install alternatives
$ update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-7 70 
$ update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-7 70

# configure alternatives (select the required gcc version)
$ update-alternatives --config gcc
$ update-alternatives --config g++

  2. Install Python requirements

    $ pip3 install -r requirements.txt

  3. Install CMake, supported version >=3.14.0 and =<3.20.0,

    # to install CMake 3.18.2
$ wget https://github.com/Kitware/CMake/releases/download/v3.18.4/cmake-3.18.4-Linux-x86_64.tar.gz && \
$ tar -xzvf cmake-3.18.4-Linux-x86_64.tar.gz && \
$ cp cmake-3.18.4-Linux-x86_64/bin/* /usr/local/bin/ && \
  cp -r cmake-3.18.4-Linux-x86_64/share/cmake-3.18 /usr/local/share/

  4. Install Bazelisk (Optional; required only while building TensorFlow from source)

    $ apt-get update && apt-get install -y openjdk-8-jdk
$ curl -fsSL https://deb.nodesource.com/setup_12.x | bash -
$ apt-get install -y nodejs
$ npm install -g @bazel/bazelisk

1.2. macOS

  1. Install HomeBrew packages

    $ brew install python@3.9
$ brew install cmake autoconf automake libtool libusb wget

  2. Install Pip and requirements

    $ wget https://bootstrap.pypa.io/get-pip.py
$ python3 get-pip.py
$ pip3 install -r requirements.txt

  3. Install Bazelisk v1.10.1 (Optional; required only while building TensorFlow from source)

    $ wget https://github.com/bazelbuild/bazelisk/releases/download/v1.10.1/bazelisk-darwin-amd64
$ mv bazelisk-darwin-amd64 /usr/local/bin/bazel
$ chmod 777 /usr/local/bin/bazel

  4. Install Apple XCode Command Line Tools

    $ xcode-select --install

Notes: Developed and Tested on macOS version 11.2.3 with CMake version 3.21.1 User can install Python 3.7, 3.8, or 3.9.

2. OpenVINO™ integration with TensorFlow

2.1. Build Instructions

Use one of the following build options based on the requirements. OpenVINO™ integration with TensorFlow built using PyPI TensorFlow enables only the Python APIs. TensorFlow C++ libraries built from source is required to use the C++ APIs.

  1. Pulls compatible prebuilt TensorFlow package from PyPi, clones and builds OpenVINO™ from source. The arguments are optional. If any argument is not provided, then the default versions as specified in build_ovtf.py will be used.

     python3 build_ovtf.py --tf_version=v2.5.1 --openvino_version=2021.4.1

  2. Pulls compatible prebuilt TensorFlow package from Github release assets. Uses OpenVINO™ binary from specified location.

     python3 build_ovtf.py --use_openvino_from_location=/opt/intel/openvino_2021.4.689/ --cxx11_abi_version=1

  3. Uses pre-built TensorFlow from the given location (refer the TensorFlow build instructions). Pulls and builds OpenVINO™ from source. Use this if you need to build OpenVINO™ integration with TensorFlow frequently without building TensorFlow from source everytime.

     python3 build_ovtf.py --use_tensorflow_from_location=/path/to/tensorflow/build/

  4. Uses prebuilt TensorFlow from the given location (refer the TensorFlow build instructions). Uses OpenVINO™ binary from specified location. This is only compatible with ABI1 built TensorFlow.

     python3 build_ovtf.py --use_tensorflow_from_location=/path/to/tensorflow/build/  --use_openvino_from_location=/opt/intel/openvino_2021.4.689/ --cxx11_abi_version=1

  5. Pulls and builds TensorFlow from Source. Uses OpenVINO™ binary from specified location.

     python3 build_ovtf.py --build_tf_from_source --use_openvino_from_location=/opt/intel/openvino_2021.4.689/ --cxx11_abi_version=1

  6. Pulls and builds TensorFlow and OpenVINO™ from source

     python3 build_ovtf.py --build_tf_from_source

Select the help option of build_ovtf.py script to learn more about various build options.

    python3 build_ovtf.py --help

2.2. Build Instructions for Intel Atom® Processor

In order to build OpenVINO™ integration with TensorFlow to use with the Intel Atom® processor, we recommend building TensorFlow from source, by using the following command:

    python3 build_ovtf.py --build_tf_from_source --cxx11_abi_version=1 --target_arch silvermont

2.3. Build Verification

When the build is finished, a new virtualenv directory with name venv-tf-py3 is created in build_cmake. Build artifacts (e.g. the openvino_tensorflow-<VERSION>-cp36-cp36m-manylinux2014_x86_64.whl) are created in the build_cmake/artifacts/ directory.

Activate the following virtualenv to start using OpenVINO™ integration with TensorFlow.

    source build_cmake/venv-tf-py3/bin/activate

Alternatively, you may install the TensorFlow and OpenVINO™ integration with TensorFlow outside of a virtualenv. The Python whl files are located in the build_cmake/artifacts/ and build_cmake/artifacts/tensorflow directories, respectively.

Verify that openvino-tensorflow is installed correctly:

python3 -c "import tensorflow as tf; print('TensorFlow version: ',tf.__version__);\
            import openvino_tensorflow; print(openvino_tensorflow.__version__)"

This should produce an output like:

    TensorFlow version:  2.5.1
    OpenVINO integration with TensorFlow version: b'1.0.1'
    OpenVINO version used for this build: b'2021.4.1'
    TensorFlow version used for this build: v2.5.1
    CXX11_ABI flag used for this build: 1

Test the installation:

    python3 test_ovtf.py

This command runs all C++ and Python unit tests from the openvino_tensorflow source tree. It also runs various TensorFlow Python tests using OpenVINO™.

3. OpenVINO™

OpenVINO™ can be built from source independently using build_ov.py

4. TensorFlow

TensorFlow can be built from source using build_tf.py. The build artifacts can be found under ${PATH_TO_TF_BUILD}/artifacts/

  • Set your build path

      export PATH_TO_TF_BUILD=/path/to/tensorflow/build/

  • For all available build options

      python3 build_tf.py -h

  • Builds TensorFlow with CXX11_ABI=0.

      python3 build_tf.py --output_dir=${PATH_TO_TF_BUILD} --cxx11_abi_version=0

  • Builds TensorFlow with CXX11_ABI=1

      python3 build_tf.py --output_dir=${PATH_TO_TF_BUILD} --cxx11_abi_version=1

  • To build with a desired TensorFlow version, for example: v2.5.1

      python3 build_tf.py --output_dir=${PATH_TO_TF_BUILD} --tf_version=v2.5.1

5. Build ManyLinux2014 compatible OpenVINO™ integration with TensorFlow wheels

To build wheel files compatible with manylinux2014, use the following commands. The build artifacts will be available in your container's /whl/ folder.

cd tools/builds/
docker build --no-cache -t openvino_tensorflow/pip --build-arg OVTF_BRANCH=releases/v1.0.1 . -f Dockerfile.manylinux2014