tfx_bsl (TFX Basic Shared Libraries) contains libraries shared by many TFX (TensorFlow eXtended) libraries and components.
TFX Basic Shared Libraries (tfx_bsl
) contains libraries shared by many
TensorFlow eXtended (TFX) components.
Only symbols exported by sub-modules under tfx_bsl/public
are intended for
direct use by TFX users, including by standalone TFX library (e.g. TFDV, TFMA,
TFT) users, TFX pipeline authors and TFX component authors. Those APIs will
become stable and follow semantic versioning once tfx_bsl
goes beyond 1.0
.
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 library 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
TFX-BSL also hosts nightly packages at https://pypi-nightly.tensorflow.org on Google Cloud. To install the latest nightly package, please use the following command:
pip install --extra-index-url https://pypi-nightly.tensorflow.org/simple tfx-bsl
This will install the nightly packages for the major dependencies of TFX-BSL such as TensorFlow Metadata (TFMD).
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.
tfx_bsl
repositorygit 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 {38, 39}
.
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
repositorygit 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.
tfx_bsl
wheel is Python version dependent -- to build the pip package that
works for a specific Python version, use that Python binary to run:
python setup.py bdist_wheel
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:
The following table is the tfx_bsl
package versions that are compatible with
each other. This is determined by our testing framework, but other untested
combinations may also work.
tfx-bsl | apache-beam[gcp] | pyarrow | tensorflow | tensorflow-metadata | tensorflow-serving-api |
---|---|---|---|---|---|
GitHub master | 2.47.0 | 10.0.0 | nightly (2.x) | 1.14.0 | 2.13.0 |
1.14.0 | 2.47.0 | 10.0.0 | 2.13 | 1.14.0 | 2.13.0 |
1.13.0 | 2.40.0 | 6.0.0 | 2.12 | 1.13.1 | 2.9.0 |
1.12.0 | 2.40.0 | 6.0.0 | 2.11 | 1.12.0 | 2.9.0 |
1.11.0 | 2.40.0 | 6.0.0 | 1.15 / 2.10 | 1.11.0 | 2.9.0 |
1.10.0 | 2.40.0 | 6.0.0 | 1.15 / 2.9 | 1.10.0 | 2.9.0 |
1.9.0 | 2.38.0 | 5.0.0 | 1.15 / 2.9 | 1.9.0 | 2.9.0 |
1.8.0 | 2.38.0 | 5.0.0 | 1.15 / 2.8 | 1.8.0 | 2.8.0 |
1.7.0 | 2.36.0 | 5.0.0 | 1.15 / 2.8 | 1.7.0 | 2.8.0 |
1.6.0 | 2.35.0 | 5.0.0 | 1.15 / 2.7 | 1.6.0 | 2.7.0 |
1.5.0 | 2.34.0 | 5.0.0 | 1.15 / 2.7 | 1.5.0 | 2.7.0 |
1.4.0 | 2.31.0 | 5.0.0 | 1.15 / 2.6 | 1.4.0 | 2.6.0 |
1.3.0 | 2.31.0 | 2.0.0 | 1.15 / 2.6 | 1.2.0 | 2.6.0 |
1.2.0 | 2.31.0 | 2.0.0 | 1.15 / 2.5 | 1.2.0 | 2.5.1 |
1.1.0 | 2.29.0 | 2.0.0 | 1.15 / 2.5 | 1.1.0 | 2.5.1 |
1.0.0 | 2.29.0 | 2.0.0 | 1.15 / 2.5 | 1.0.0 | 2.5.1 |
0.30.0 | 2.28.0 | 2.0.0 | 1.15 / 2.4 | 0.30.0 | 2.4.0 |
0.29.0 | 2.28.0 | 2.0.0 | 1.15 / 2.4 | 0.29.0 | 2.4.0 |
0.28.0 | 2.28.0 | 2.0.0 | 1.15 / 2.4 | 0.28.0 | 2.4.0 |
0.27.1 | 2.27.0 | 2.0.0 | 1.15 / 2.4 | 0.27.0 | 2.4.0 |
0.27.0 | 2.27.0 | 2.0.0 | 1.15 / 2.4 | 0.27.0 | 2.4.0 |
0.26.1 | 2.25.0 | 0.17.0 | 1.15 / 2.3 | 0.27.0 | 2.3.0 |
0.26.0 | 2.25.0 | 0.17.0 | 1.15 / 2.3 | 0.27.0 | 2.3.0 |