TFX Basic Shared Libraries (tfx_bsl) contains libraries shared by many TensorFlow eXtended (TFX) components.

Only APIs in tfx_bsl/public are intended for direct use by TFX users. APIs under other directories should be considered internal to TFX (and therefore there is no backward or forward compatibility guarantee for them).

Each minor version of a TFX component or TFX itself, if it needs to depend on tfx_bsl, will depend on a specific minor version of it (e.g. tensorflow_data_validation 0.14.* will depend on and only work with tfx_bsl 0.14.*)

tfx_bsl is available as a PyPI package.

pip install tfx-bsl

However it is a dependency of many TFX components and usually as a user you don't need to install it directly.

If you want to build a TFX component from the master branch, past the latest release, you may also have to build the latest tfx_bsl, as that TFX component might have depended on new features introduced past the latest tfx_bsl release.

Building from Docker is the recommended way to build tfx_bsl under Linux, and is continuously tested at Google.

Please first install docker and docker-compose by following the directions.

git clone https://github.com/tensorflow/tfx-bsl
cd tfx-bsl

Note that these instructions will install the latest master branch of tfx-bsl. If you want to install a specific branch (such as a release branch), pass -b <branchname> to the git clone command.

Then, run the following at the project root:

sudo docker-compose build manylinux2010
sudo docker-compose run -e PYTHON_VERSION=${PYTHON_VERSION} manylinux2010

where PYTHON_VERSION is one of {35, 36, 37}.

A wheel will be produced under dist/.

pip install dist/*.whl

If NumPy is not installed on your system, install it now by following these directions.

If Bazel is not installed on your system, install it now by following these directions.

tfx_bsl needs to be built with specific PyArrow versions ( as indicated in third_party/pyarrow.version). Install pyarrow by following these directions.

When installing please make sure to specify the compatible pyarrow version. For example:

pip install "pyarrow>=0.14.0,<0.15.0"

git clone https://github.com/tensorflow/tfx-bsl
cd tfx-bsl

Note that these instructions will install the latest master branch of tfx_bsl If you want to install a specific branch (such as a release branch), pass -b <branchname> to the git clone command.

TFDV uses Bazel to build the pip package from source. Before invoking the following commands, make sure the python in your $PATH is the one of the target version and has NumPy and PyArrow installed.

./configure.sh
bazel run -c opt --cxxopt=-D_GLIBCXX_USE_CXX11_ABI=0 tfx_bsl:build_pip_package

The flag D_GLIBCXX_USE_CXX11_ABI=0 is to use an older std::string ABI. Which is used by all manylinux2010 compliant wheels (including PyArrow). If you also build PyArrow from source without that flag, you may not need to specify it here.

You can find the generated .whl file in the dist subdirectory.

pip install dist/*.whl

tfx_bsl is tested on the following 64-bit operating systems:

• macOS 10.12.6 (Sierra) or later.
• Ubuntu 16.04 or later.
• Windows 7 or later.