Skip to main content

TensorFlow Extended (TFX) is a TensorFlow-based general-purpose machine learning platform implemented at Google.

Project description

TFX

Python PyPI TensorFlow

TensorFlow Extended (TFX) is a Google-production-scale machine learning platform based on TensorFlow. It provides a configuration framework to express ML pipelines consisting of TFX components. TFX pipelines can be orchestrated using Apache Airflow and Kubeflow Pipelines. Both the components themselves as well as the integrations with orchestration systems can be extended.

TFX components interact with a ML Metadata backend that keeps a record of component runs, input and output artifacts, and runtime configuration. This metadata backend enables advanced functionality like experiment tracking or warmstarting/resuming ML models from previous runs.

TFX Components

Documentation

User Documentation

Please see the TFX User Guide.

Development References

Roadmap

The TFX Roadmap, which is updated quarterly.

Release Details

For detailed previous and upcoming changes, please check here

Requests For Comment

TFX is an open-source project and we strongly encourage active participation by the ML community in helping to shape TFX to meet or exceed their needs. An important component of that effort is the RFC process. Please see the listing of current and past TFX RFCs. Please see the TensorFlow Request for Comments (TF-RFC) process page for information on how community members can contribute.

Examples

Compatible versions

The following table describes how the tfx package versions are compatible with its major dependency PyPI packages. This is determined by our testing framework, but other untested combinations may also work.

tfx Python apache-beam[gcp] ml-metadata pyarrow tensorflow tensorflow-data-validation tensorflow-metadata tensorflow-model-analysis tensorflow-serving-api tensorflow-transform tfx-bsl
GitHub master >=3.10,<3.13 2.73.0 1.21.0 18.1.0 nightly (2.x) 1.21.0 1.21.0 0.52.0 2.19.1 1.21.0 1.21.0
1.21.0 >=3.10,<3.13 2.73.0 1.21.0 18.1.0 2.21 1.21.0 1.21.0 0.52.0 2.19.1 1.21.0 1.21.0
1.17.2 >=3.9,<3.11 2.59.0 1.17.1 10.0.1 2.17 1.17.0 1.17.1 0.48.0 2.17.1 1.17.0 1.17.1
1.17.1 >=3.9,<3.11 2.59.0 1.17.1 10.0.1 2.17 1.17.0 1.17.1 0.48.0 2.17.1 1.17.0 1.17.1
1.17.0 >=3.9,<3.11 2.59.0 1.17.1 10.0.1 2.17 1.17.0 1.17.1 0.48.0 2.17.1 1.17.0 1.17.1
1.16.0 >=3.9,<3.11 2.59.0 1.16.0 10.0.1 2.16 1.16.1 1.16.1 0.47.0 2.16.1 1.16.0 1.16.1
1.15.0 >=3.9,<3.11 2.47.0 1.15.0 10.0.0 2.15 1.15.1 1.15.0 0.46.0 2.15.1 1.15.0 1.15.1
1.14.0 >=3.8,<3.11 2.47.0 1.14.0 10.0.0 2.13 1.14.0 1.14.0 0.45.0 2.9.0 1.14.0 1.14.0
1.13.0 >=3.8,<3.10 2.40.0 1.13.1 6.0.0 2.12 1.13.0 1.13.1 0.44.0 2.9.0 1.13.0 1.13.0
1.12.0 >=3.7,<3.10 2.40.0 1.12.0 6.0.0 2.11 1.12.0 1.12.0 0.43.0 2.9.0 1.12.0 1.12.0
1.11.0 >=3.7,<3.10 2.40.0 1.11.0 6.0.0 1.15.5 / 2.10.0 1.11.0 1.11.0 0.42.0 2.9.0 1.11.0 1.11.0
1.10.0 >=3.7,<3.10 2.40.0 1.10.0 6.0.0 1.15.5 / 2.9.0 1.10.0 1.10.0 0.41.0 2.9.0 1.10.0 1.10.0
1.9.0 >=3.7,<3.10 2.38.0 1.9.0 5.0.0 1.15.5 / 2.9.0 1.9.0 1.9.0 0.40.0 2.9.0 1.9.0 1.9.0
1.8.0 >=3.7,<3.10 2.38.0 1.8.0 5.0.0 1.15.5 / 2.8.0 1.8.0 1.8.0 0.39.0 2.8.0 1.8.0 1.8.0
1.7.0 >=3.7,<3.9 2.36.0 1.7.0 5.0.0 1.15.5 / 2.8.0 1.7.0 1.7.0 0.38.0 2.8.0 1.7.0 1.7.0
1.6.2 >=3.7,<3.9 2.35.0 1.6.0 5.0.0 1.15.5 / 2.8.0 1.6.0 1.6.0 0.37.0 2.7.0 1.6.0 1.6.0
1.6.0 >=3.7,<3.9 2.35.0 1.6.0 5.0.0 1.15.5 / 2.7.0 1.6.0 1.6.0 0.37.0 2.7.0 1.6.0 1.6.0
1.5.0 >=3.7,<3.9 2.34.0 1.5.0 5.0.0 1.15.2 / 2.7.0 1.5.0 1.5.0 0.36.0 2.7.0 1.5.0 1.5.0
1.4.0 >=3.7,<3.9 2.33.0 1.4.0 5.0.0 1.15.0 / 2.6.0 1.4.0 1.4.0 0.35.0 2.6.0 1.4.0 1.4.0
1.3.4 >=3.6,<3.9 2.32.0 1.3.0 2.0.0 1.15.0 / 2.6.0 1.3.0 1.2.0 0.34.1 2.6.0 1.3.0 1.3.0
1.3.3 >=3.6,<3.9 2.32.0 1.3.0 2.0.0 1.15.0 / 2.6.0 1.3.0 1.2.0 0.34.1 2.6.0 1.3.0 1.3.0
1.3.2 >=3.6,<3.9 2.32.0 1.3.0 2.0.0 1.15.0 / 2.6.0 1.3.0 1.2.0 0.34.1 2.6.0 1.3.0 1.3.0
1.3.1 >=3.6,<3.9 2.32.0 1.3.0 2.0.0 1.15.0 / 2.6.0 1.3.0 1.2.0 0.34.1 2.6.0 1.3.0 1.3.0
1.3.0 >=3.6,<3.9 2.32.0 1.3.0 2.0.0 1.15.0 / 2.6.0 1.3.0 1.2.0 0.34.1 2.6.0 1.3.0 1.3.0
1.2.1 >=3.6,<3.9 2.31.0 1.2.0 2.0.0 1.15.0 / 2.5.0 1.2.0 1.2.0 0.33.0 2.5.1 1.2.0 1.2.0
1.2.0 >=3.6,<3.9 2.31.0 1.2.0 2.0.0 1.15.0 / 2.5.0 1.2.0 1.2.0 0.33.0 2.5.1 1.2.0 1.2.0
1.0.0 >=3.6,<3.9 2.29.0 1.0.0 2.0.0 1.15.0 / 2.5.0 1.0.0 1.0.0 0.31.0 2.5.1 1.0.0 1.0.0
0.30.0 >=3.6,<3.9 2.28.0 0.30.0 2.0.0 1.15.0 / 2.4.0 0.30.0 0.30.0 0.30.0 2.4.0 0.30.0 0.30.0
0.29.0 >=3.6,<3.9 2.28.0 0.29.0 2.0.0 1.15.0 / 2.4.0 0.29.0 0.29.0 0.29.0 2.4.0 0.29.0 0.29.0
0.28.0 >=3.6,<3.9 2.28.0 0.28.0 2.0.0 1.15.0 / 2.4.0 0.28.0 0.28.0 0.28.0 2.4.0 0.28.0 0.28.1
0.27.0 >=3.6,<3.9 2.27.0 0.27.0 2.0.0 1.15.0 / 2.4.0 0.27.0 0.27.0 0.27.0 2.4.0 0.27.0 0.27.0
0.26.4 >=3.6,<3.9 2.28.0 0.26.0 0.17.0 1.15.0 / 2.3.0 0.26.1 0.26.0 0.26.0 2.3.0 0.26.0 0.26.0
0.26.3 >=3.6,<3.9 2.25.0 0.26.0 0.17.0 1.15.0 / 2.3.0 0.26.0 0.26.0 0.26.0 2.3.0 0.26.0 0.26.0
0.26.1 >=3.6,<3.9 2.25.0 0.26.0 0.17.0 1.15.0 / 2.3.0 0.26.0 0.26.0 0.26.0 2.3.0 0.26.0 0.26.0
0.26.0 >=3.6,<3.9 2.25.0 0.26.0 0.17.0 1.15.0 / 2.3.0 0.26.0 0.26.0 0.26.0 2.3.0 0.26.0 0.26.0
0.25.0 >=3.6,<3.9 2.25.0 0.24.0 0.17.0 1.15.0 / 2.3.0 0.25.0 0.25.0 0.25.0 2.3.0 0.25.0 0.25.0
0.24.1 >=3.6,<3.9 2.24.0 0.24.0 0.17.0 1.15.0 / 2.3.0 0.24.1 0.24.0 0.24.3 2.3.0 0.24.1 0.24.1
0.24.0 >=3.6,<3.9 2.24.0 0.24.0 0.17.0 1.15.0 / 2.3.0 0.24.1 0.24.0 0.24.3 2.3.0 0.24.1 0.24.1
0.23.1 >=3.5,<4 2.24.0 0.23.0 0.17.0 1.15.0 / 2.3.0 0.23.1 0.23.0 0.23.0 2.3.0 0.23.0 0.23.0
0.23.0 >=3.5,<4 2.23.0 0.23.0 0.17.0 1.15.0 / 2.3.0 0.23.0 0.23.0 0.23.0 2.3.0 0.23.0 0.23.0
0.22.2 >=3.5,<4 2.21.0 0.22.1 0.16.0 1.15.0 / 2.2.0 0.22.2 0.22.2 0.22.2 2.2.0 0.22.0 0.22.1
0.22.1 >=3.5,<4 2.21.0 0.22.1 0.16.0 1.15.0 / 2.2.0 0.22.2 0.22.2 0.22.2 2.2.0 0.22.0 0.22.1
0.22.0 >=3.5,<4 2.21.0 0.22.0 0.16.0 1.15.0 / 2.2.0 0.22.0 0.22.0 0.22.1 2.2.0 0.22.0 0.22.0
0.21.5 >=2.7,<3 or >=3.5,<4 2.17.0 0.21.2 0.15.0 1.15.0 / 2.1.0 0.21.5 0.21.1 0.21.5 2.1.0 0.21.2 0.21.4
0.21.4 >=2.7,<3 or >=3.5,<4 2.17.0 0.21.2 0.15.0 1.15.0 / 2.1.0 0.21.5 0.21.1 0.21.5 2.1.0 0.21.2 0.21.4
0.21.3 >=2.7,<3 or >=3.5,<4 2.17.0 0.21.2 0.15.0 1.15.0 / 2.1.0 0.21.5 0.21.1 0.21.5 2.1.0 0.21.2 0.21.4
0.21.2 >=2.7,<3 or >=3.5,<4 2.17.0 0.21.2 0.15.0 1.15.0 / 2.1.0 0.21.5 0.21.1 0.21.5 2.1.0 0.21.2 0.21.4
0.21.1 >=2.7,<3 or >=3.5,<4 2.17.0 0.21.2 0.15.0 1.15.0 / 2.1.0 0.21.4 0.21.1 0.21.4 2.1.0 0.21.2 0.21.3
0.21.0 >=2.7,<3 or >=3.5,<4 2.17.0 0.21.0 0.15.0 1.15.0 / 2.1.0 0.21.0 0.21.0 0.21.1 2.1.0 0.21.0 0.21.0
0.15.0 >=2.7,<3 or >=3.5,<4 2.16.0 0.15.0 0.15.0 1.15.0 0.15.0 0.15.0 0.15.2 1.15.0 0.15.0 0.15.1
0.14.0 >=2.7,<3 or >=3.5,<4 2.14.0 0.14.0 0.14.0 1.14.0 0.14.1 0.14.0 0.14.0 1.14.0 0.14.0 n/a
0.13.0 >=2.7,<3 or >=3.5,<4 2.12.0 0.13.2 n/a 1.13.1 0.13.1 0.13.0 0.13.2 1.13.0 0.13.0 n/a
0.12.0 >=2.7,<3 2.10.0 0.13.2 n/a 1.12.0 0.12.0 0.12.1 0.12.1 1.12.0 0.12.0 n/a

Resources

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

tfx-1.21.0.tar.gz (6.9 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

tfx-1.21.0-py3-none-any.whl (7.5 MB view details)

Uploaded Python 3

File details

Details for the file tfx-1.21.0.tar.gz.

File metadata

  • Download URL: tfx-1.21.0.tar.gz
  • Upload date:
  • Size: 6.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.12.13

File hashes

Hashes for tfx-1.21.0.tar.gz
Algorithm Hash digest
SHA256 43a79e0fa207ed918c67030d997a35022248c85f493ed561944304f539738923
MD5 45946b81c1b46430a2a03a39fac897b6
BLAKE2b-256 a70d64b1db6cc9748fc0ffa28729173e90cb31efb506f57965cbfe6b464ec51a

See more details on using hashes here.

File details

Details for the file tfx-1.21.0-py3-none-any.whl.

File metadata

  • Download URL: tfx-1.21.0-py3-none-any.whl
  • Upload date:
  • Size: 7.5 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.12.13

File hashes

Hashes for tfx-1.21.0-py3-none-any.whl
Algorithm Hash digest
SHA256 51032ac740ac6d28185c2814ada5a7e917f3016bcd2043f03ba98e7e674e4165
MD5 fd363e6294aedcc962f76f2cee4dbbbc
BLAKE2b-256 1a850a08dc66a944efe4185618cdfa79f9371deb542ee5bf86eeb5e61d5c7278

See more details on using hashes here.

Supported by

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