Skip to main content

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

Project description

TFX Basic Shared Libraries

Python PyPI

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.*)

Installing from PyPI

tfx_bsl is available as a PyPI package.

pip install tfx-bsl

Nightly Packages

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.

Build with Docker

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.

1. Install Docker

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

2. Clone the tfx_bsl repository

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.

3. Build the pip package

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 {39}.

A wheel will be produced under dist/.

4. Install the pip package

pip install dist/*.whl

Build from source

1. Prerequisites

Install NumPy

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

Install Bazel

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

2. Clone the tfx_bsl repository

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.

3. Build the pip package

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.

4. Install the pip package

pip install dist/*.whl

Supported platforms

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

  • macOS 10.12.6 (Sierra) or later.
  • Ubuntu 20.04 or later.

Compatible versions

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 2.64.0 10.0.1 nightly (2.x) 1.17.1 2.17.1
1.17.0 2.64.0 10.0.1 2.17 1.17.1 2.17.1
1.16.1 2.59.0 10.0.1 2.16 1.16.1 2.16.1
1.16.0 2.59.0 10.0.1 2.16 1.16.0 2.16.1
1.15.1 2.47.0 10.0.0 2.15 1.15.0 2.15.1
1.15.0 2.47.0 10.0.0 2.15 1.15.0 2.15.1
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

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

tfx_bsl-1.17.1-cp311-cp311-manylinux_2_39_x86_64.whl (28.7 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.39+ x86-64

tfx_bsl-1.17.1-cp310-cp310-manylinux_2_39_x86_64.whl (28.7 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.39+ x86-64

tfx_bsl-1.17.1-cp39-cp39-manylinux_2_39_x86_64.whl (28.7 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.39+ x86-64

File details

Details for the file tfx_bsl-1.17.1-cp311-cp311-manylinux_2_39_x86_64.whl.

File metadata

File hashes

Hashes for tfx_bsl-1.17.1-cp311-cp311-manylinux_2_39_x86_64.whl
Algorithm Hash digest
SHA256 8af566644597722664545366681d242b03dfc6b5784567951eb22062fe8b51ff
MD5 87f5b49505f65192c97e358e34a6573e
BLAKE2b-256 c2f58be4a53879cc4383386f33e2ae71f385138e5a29199f5529fab3181cadb6

See more details on using hashes here.

File details

Details for the file tfx_bsl-1.17.1-cp310-cp310-manylinux_2_39_x86_64.whl.

File metadata

File hashes

Hashes for tfx_bsl-1.17.1-cp310-cp310-manylinux_2_39_x86_64.whl
Algorithm Hash digest
SHA256 50860ae65175d6c857bfd27bd04b617ed5a5c72a587e1128836ae65e21bce23d
MD5 db9f83430b910e0f665da8103828787a
BLAKE2b-256 00844b359481924da5af44f17e252b87ac6a60f810b58a577c27b8aa815a68bb

See more details on using hashes here.

File details

Details for the file tfx_bsl-1.17.1-cp39-cp39-manylinux_2_39_x86_64.whl.

File metadata

File hashes

Hashes for tfx_bsl-1.17.1-cp39-cp39-manylinux_2_39_x86_64.whl
Algorithm Hash digest
SHA256 a192599a3249dce55e91436929ee926b8ed4aa84f5ba73dc3a1ba9a0edcc22ab
MD5 45cd22c08d992f31ef96b501c63438c2
BLAKE2b-256 c75ac7daa496e3a14d9b385ce115e57eb0705cc9bf323901e586adf39a005bd9

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page