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Installation and Build Options

Prerequisites

Build Type Requirements
Use pre-built packages Python 3.6, 3.7, or 3.8, TensorFlow v2.5.0
Build from source Python 3.6, 3.7, or 3.8, GCC 7.5 (Ubuntu 18.04, 20.04), cmake 3.14 or higher, Bazelisk v1.7.5, virtualenv 16.0.0 or higher, patchelf 0.9, libusb 1.0.0

Use Pre-Built Packages

OpenVINO™ integration with TensorFlow has two releases: one built with CXX11_ABI=0 and another built with CXX11_ABI=1.

Since TensorFlow packages available in PyPi are built with CXX11_ABI=0 and OpenVINO™ release packages are built with CXX11_ABI=1, binary releases of these packages cannot be installed together. Based on your needs, you can choose one of the two available methods:

  • OpenVINO™ integration with TensorFlow alongside PyPi TensorFlow (CXX11_ABI=0, no OpenVINO™ installation required, no VAD-M support)

  • OpenVINO™ integration with TensorFlow alongside the Intel® Distribution of OpenVINO™ Toolkit (CXX11_ABI=1, needs a custom TensorFlow package, enables VAD-M support)

Install OpenVINO™ integration with TensorFlow alongside PyPi TensorFlow

This OpenVINO™ integration with TensorFlow package includes pre-built libraries of OpenVINO™ version 2021.3. The users do not have to install OpenVINO™ separately. This package supports Intel® CPUs, Intel® integrated GPUs, and Intel® Movidius™ Vision Processing Units (VPUs).

    pip3 install -U pip==21.0.1
    pip3 install -U tensorflow==2.5.0
    pip3 install openvino-tensorflow

Install OpenVINO™ integration with TensorFlow alongside the Intel® Distribution of OpenVINO™ Toolkit

This OpenVINO™ integration with TensorFlow package is currently compatible with OpenVINO™ version 2021.3. This package supports Intel® CPUs, Intel® integrated GPUs, Intel® Movidius™ Vision Processing Units (VPUs), and Intel® Vision Accelerator Design with Movidius™ (VAD-M).

You can build TensorFlow from source with -D_GLIBCXX_USE_CXX11_ABI=1 or use the following TensorFlow package:

  1. Ensure the following versions are being used for pip and numpy:

     pip3 install --upgrade pip==21.0.1
 pip3 install numpy==1.20.2

  2. Install TensorFlow. Based on your Python version, use the appropriate package below:

     pip3.6 install https://github.com/openvinotoolkit/openvino_tensorflow/releases/download/v0.6.0/tensorflow_abi1-2.5.0-cp36-cp36m-manylinux2010_x86_64.whl

 or

 pip3.7 install https://github.com/openvinotoolkit/openvino_tensorflow/releases/download/v0.6.0/tensorflow_abi1-2.5.0-cp37-cp37m-manylinux2010_x86_64.whl

 or

 pip3.8 install https://github.com/openvinotoolkit/openvino_tensorflow/releases/download/v0.6.0/tensorflow_abi1-2.5.0-cp38-cp38-manylinux2010_x86_64.whl

  3. Download & install Intel® Distribution of OpenVINO™ Toolkit 2021.3 release along with its dependencies from (https://software.intel.com/en-us/openvino-toolkit/download).

  4. Initialize the OpenVINO™ environment by running the setupvars.sh located in <openvino_install_directory>/bin using the command below:

     source setupvars.sh

  5. Install openvino-tensorflow. Based on your Python version, choose the appropriate package below:

     pip3.6 install https://github.com/openvinotoolkit/openvino_tensorflow/releases/download/v0.5.0/openvino_tensorflow_abi1-0.5.0-cp36-cp36m-linux_x86_64.whl

 or

 pip3.7 install https://github.com/openvinotoolkit/openvino_tensorflow/releases/download/v0.5.0/openvino_tensorflow_abi1-0.5.0-cp37-cp37m-linux_x86_64.whl

 or

 pip3.8 install https://github.com/openvinotoolkit/openvino_tensorflow/releases/download/v0.5.0/openvino_tensorflow_abi1-0.5.0-cp38-cp38-linux_x86_64.whl

Prebuilt packages summary

TensorFlow Package OpenVINO™ integration with TensorFlow Package Supported OpenVINO™ Flavor Supported Hardware Backends Comments
tensorflow openvino-tensorflow OpenVINO™ built from source CPU,GPU,MYRIAD OpenVINO™ libraries are built from source and included in the wheel package
tensorflow-abi1 openvino-tensorflow-abi1 Dynamically links to OpenVINO™ binary release CPU,GPU,MYRIAD,VAD-M OpenVINO™ integration with TensorFlow libraries are dynamically linked to OpenVINO™ binaries

Build From Source

Clone the openvino_tensorflow repository:

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

Install the following python packages

$ pip3 install -U psutil==5.8.0 wheel==0.36.2

OpenVINO™ integration with TensorFlow

Use one of the following build options based on the requirements

  1. Pulls compatible prebuilt TF package from PyPi, clones and builds OpenVINO™ from source.

     python3 build_ovtf.py

  2. Pulls compatible prebuilt TF package from PyPi. Uses OpenVINO™ binary.

     python3 build_ovtf.py --use_openvino_from_location=/opt/intel/openvino_2021.3.394/ --cxx11_abi_version=1

  3. Pulls and builds TF and OpenVINO™ from source

     python3 build_ovtf.py --build_tf_from_source

  4. Pulls and builds TF from Source. Uses OpenVINO™ binary.

     python3 build_ovtf.py --build_tf_from_source --use_openvino_from_location=/opt/intel/openvino_2021.3.394/ --cxx11_abi_version=1

  5. Uses pre-built TF 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 TF from source everytime.

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

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

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

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

    python3 build_ovtf.py --help

Verification

When the build is finished, a new virtualenv directory is created in build_cmake/venv-tf-py3. Build artifacts (ex: 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:  2.5.0
    OpenVINO integration with TensorFlow version: b'0.5.0'
    OpenVINO version used for this build: b'2021.3'
    TensorFlow version used for this build: v2.5.0
    CXX11_ABI flag used for this build: 1
    OpenVINO integration with TensorFlow built with Grappler: False

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™.

Build Instructions for Intel Atom® Processor

In order to build OpenVINO™ integration with TensorFlow to use on Intel Atom® processor, we recommend building TF from source. The command below will build TF and OpenVINO™ from source for Intel Atom® processors.

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

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 TF with CXX11_ABI=0.

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

  • Builds TF with CXX11_ABI=1

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

  • To build with a desired TF version, for example: v2.5.0

      python3 build_tf.py --output_dir=${PATH_TO_TF_BUILD} --tf_version=v2.5.0

OpenVINO™

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

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/v0.5.0 . -f Dockerfile.manylinux2014