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TFX

PythonPyPITensorFlow

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.

tfxPythonapache-beam[gcp]ml-metadatapyarrowtensorflowtensorflow-data-validationtensorflow-metadatatensorflow-model-analysistensorflow-serving-apitensorflow-transformtfx-bsl
GitHub master>=3.9,<3.112.59.01.17.110.0.1nightly (2.x)1.17.01.17.10.48.02.17.11.17.01.17.1
1.17.2>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.1>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.0>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.16.0>=3.9,<3.112.59.01.16.010.0.12.161.16.11.16.10.47.02.16.11.16.01.16.1
1.15.0>=3.9,<3.112.47.01.15.010.0.02.151.15.11.15.00.46.02.15.11.15.01.15.1
1.14.0>=3.8,<3.112.47.01.14.010.0.02.131.14.01.14.00.45.02.9.01.14.01.14.0
1.13.0>=3.8,<3.102.40.01.13.16.0.02.121.13.01.13.10.44.02.9.01.13.01.13.0
1.12.0>=3.7,<3.102.40.01.12.06.0.02.111.12.01.12.00.43.02.9.01.12.01.12.0
1.11.0>=3.7,<3.102.40.01.11.06.0.01.15.5 / 2.10.01.11.01.11.00.42.02.9.01.11.01.11.0
1.10.0>=3.7,<3.102.40.01.10.06.0.01.15.5 / 2.9.01.10.01.10.00.41.02.9.01.10.01.10.0
1.9.0>=3.7,<3.102.38.01.9.05.0.01.15.5 / 2.9.01.9.01.9.00.40.02.9.01.9.01.9.0
1.8.0>=3.7,<3.102.38.01.8.05.0.01.15.5 / 2.8.01.8.01.8.00.39.02.8.01.8.01.8.0
1.7.0>=3.7,<3.92.36.01.7.05.0.01.15.5 / 2.8.01.7.01.7.00.38.02.8.01.7.01.7.0
1.6.2>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.8.01.6.01.6.00.37.02.7.01.6.01.6.0
1.6.0>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.7.01.6.01.6.00.37.02.7.01.6.01.6.0
1.5.0>=3.7,<3.92.34.01.5.05.0.01.15.2 / 2.7.01.5.01.5.00.36.02.7.01.5.01.5.0
1.4.0>=3.7,<3.92.33.01.4.05.0.01.15.0 / 2.6.01.4.01.4.00.35.02.6.01.4.01.4.0
1.3.4>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.3>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.2>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.1>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.0>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.2.1>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.2.0>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.0.0>=3.6,<3.92.29.01.0.02.0.01.15.0 / 2.5.01.0.01.0.00.31.02.5.11.0.01.0.0
0.30.0>=3.6,<3.92.28.00.30.02.0.01.15.0 / 2.4.00.30.00.30.00.30.02.4.00.30.00.30.0
0.29.0>=3.6,<3.92.28.00.29.02.0.01.15.0 / 2.4.00.29.00.29.00.29.02.4.00.29.00.29.0
0.28.0>=3.6,<3.92.28.00.28.02.0.01.15.0 / 2.4.00.28.00.28.00.28.02.4.00.28.00.28.1
0.27.0>=3.6,<3.92.27.00.27.02.0.01.15.0 / 2.4.00.27.00.27.00.27.02.4.00.27.00.27.0
0.26.4>=3.6,<3.92.28.00.26.00.17.01.15.0 / 2.3.00.26.10.26.00.26.02.3.00.26.00.26.0
0.26.3>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.1>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.0>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.25.0>=3.6,<3.92.25.00.24.00.17.01.15.0 / 2.3.00.25.00.25.00.25.02.3.00.25.00.25.0
0.24.1>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.24.0>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.23.1>=3.5,<42.24.00.23.00.17.01.15.0 / 2.3.00.23.10.23.00.23.02.3.00.23.00.23.0
0.23.0>=3.5,<42.23.00.23.00.17.01.15.0 / 2.3.00.23.00.23.00.23.02.3.00.23.00.23.0
0.22.2>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.1>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.0>=3.5,<42.21.00.22.00.16.01.15.0 / 2.2.00.22.00.22.00.22.12.2.00.22.00.22.0
0.21.5>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.4>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.3>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.2>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.1>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.40.21.10.21.42.1.00.21.20.21.3
0.21.0>=2.7,<3 or >=3.5,<42.17.00.21.00.15.01.15.0 / 2.1.00.21.00.21.00.21.12.1.00.21.00.21.0
0.15.0>=2.7,<3 or >=3.5,<42.16.00.15.00.15.01.15.00.15.00.15.00.15.21.15.00.15.00.15.1
0.14.0>=2.7,<3 or >=3.5,<42.14.00.14.00.14.01.14.00.14.10.14.00.14.01.14.00.14.0n/a
0.13.0>=2.7,<3 or >=3.5,<42.12.00.13.2n/a1.13.10.13.10.13.00.13.21.13.00.13.0n/a
0.12.0>=2.7,<32.10.00.13.2n/a1.12.00.12.00.12.10.12.11.12.00.12.0n/a

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TFX

PythonPyPITensorFlow

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.

tfxPythonapache-beam[gcp]ml-metadatapyarrowtensorflowtensorflow-data-validationtensorflow-metadatatensorflow-model-analysistensorflow-serving-apitensorflow-transformtfx-bsl
GitHub master>=3.9,<3.112.59.01.17.110.0.1nightly (2.x)1.17.01.17.10.48.02.17.11.17.01.17.1
1.17.2>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.1>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.0>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.16.0>=3.9,<3.112.59.01.16.010.0.12.161.16.11.16.10.47.02.16.11.16.01.16.1
1.15.0>=3.9,<3.112.47.01.15.010.0.02.151.15.11.15.00.46.02.15.11.15.01.15.1
1.14.0>=3.8,<3.112.47.01.14.010.0.02.131.14.01.14.00.45.02.9.01.14.01.14.0
1.13.0>=3.8,<3.102.40.01.13.16.0.02.121.13.01.13.10.44.02.9.01.13.01.13.0
1.12.0>=3.7,<3.102.40.01.12.06.0.02.111.12.01.12.00.43.02.9.01.12.01.12.0
1.11.0>=3.7,<3.102.40.01.11.06.0.01.15.5 / 2.10.01.11.01.11.00.42.02.9.01.11.01.11.0
1.10.0>=3.7,<3.102.40.01.10.06.0.01.15.5 / 2.9.01.10.01.10.00.41.02.9.01.10.01.10.0
1.9.0>=3.7,<3.102.38.01.9.05.0.01.15.5 / 2.9.01.9.01.9.00.40.02.9.01.9.01.9.0
1.8.0>=3.7,<3.102.38.01.8.05.0.01.15.5 / 2.8.01.8.01.8.00.39.02.8.01.8.01.8.0
1.7.0>=3.7,<3.92.36.01.7.05.0.01.15.5 / 2.8.01.7.01.7.00.38.02.8.01.7.01.7.0
1.6.2>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.8.01.6.01.6.00.37.02.7.01.6.01.6.0
1.6.0>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.7.01.6.01.6.00.37.02.7.01.6.01.6.0
1.5.0>=3.7,<3.92.34.01.5.05.0.01.15.2 / 2.7.01.5.01.5.00.36.02.7.01.5.01.5.0
1.4.0>=3.7,<3.92.33.01.4.05.0.01.15.0 / 2.6.01.4.01.4.00.35.02.6.01.4.01.4.0
1.3.4>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.3>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.2>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.1>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.0>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.2.1>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.2.0>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.0.0>=3.6,<3.92.29.01.0.02.0.01.15.0 / 2.5.01.0.01.0.00.31.02.5.11.0.01.0.0
0.30.0>=3.6,<3.92.28.00.30.02.0.01.15.0 / 2.4.00.30.00.30.00.30.02.4.00.30.00.30.0
0.29.0>=3.6,<3.92.28.00.29.02.0.01.15.0 / 2.4.00.29.00.29.00.29.02.4.00.29.00.29.0
0.28.0>=3.6,<3.92.28.00.28.02.0.01.15.0 / 2.4.00.28.00.28.00.28.02.4.00.28.00.28.1
0.27.0>=3.6,<3.92.27.00.27.02.0.01.15.0 / 2.4.00.27.00.27.00.27.02.4.00.27.00.27.0
0.26.4>=3.6,<3.92.28.00.26.00.17.01.15.0 / 2.3.00.26.10.26.00.26.02.3.00.26.00.26.0
0.26.3>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.1>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.0>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.25.0>=3.6,<3.92.25.00.24.00.17.01.15.0 / 2.3.00.25.00.25.00.25.02.3.00.25.00.25.0
0.24.1>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.24.0>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.23.1>=3.5,<42.24.00.23.00.17.01.15.0 / 2.3.00.23.10.23.00.23.02.3.00.23.00.23.0
0.23.0>=3.5,<42.23.00.23.00.17.01.15.0 / 2.3.00.23.00.23.00.23.02.3.00.23.00.23.0
0.22.2>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.1>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.0>=3.5,<42.21.00.22.00.16.01.15.0 / 2.2.00.22.00.22.00.22.12.2.00.22.00.22.0
0.21.5>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.4>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.3>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.2>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.1>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.40.21.10.21.42.1.00.21.20.21.3
0.21.0>=2.7,<3 or >=3.5,<42.17.00.21.00.15.01.15.0 / 2.1.00.21.00.21.00.21.12.1.00.21.00.21.0
0.15.0>=2.7,<3 or >=3.5,<42.16.00.15.00.15.01.15.00.15.00.15.00.15.21.15.00.15.00.15.1
0.14.0>=2.7,<3 or >=3.5,<42.14.00.14.00.14.01.14.00.14.10.14.00.14.01.14.00.14.0n/a
0.13.0>=2.7,<3 or >=3.5,<42.12.00.13.2n/a1.13.10.13.10.13.00.13.21.13.00.13.0n/a
0.12.0>=2.7,<32.10.00.13.2n/a1.12.00.12.00.12.10.12.11.12.00.12.0n/a

Resources

About

TFX is an end-to-end platform for deploying production ML pipelines

Resources

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Contributing

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Contributors

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Force GitHub README to respect dark mode (function() { var style = document.createElement('style'); style.textContent = ' .markdown-body { color-scheme: dark light; } .markdown-body pre { background: #161b22 !important; } .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; } .markdown-body table th, .markdown-body table td { border-color: #30363d !important; } .markdown-body img { background: #0d1117; } .markdown-body blockquote { border-left-color: #8b949e; } .markdown-body hr { border-color: #30363d; } '; document.head.appendChild(style); })(); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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TFX

PythonPyPITensorFlow

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.

tfxPythonapache-beam[gcp]ml-metadatapyarrowtensorflowtensorflow-data-validationtensorflow-metadatatensorflow-model-analysistensorflow-serving-apitensorflow-transformtfx-bsl
GitHub master>=3.9,<3.112.59.01.17.110.0.1nightly (2.x)1.17.01.17.10.48.02.17.11.17.01.17.1
1.17.2>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.1>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.0>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.16.0>=3.9,<3.112.59.01.16.010.0.12.161.16.11.16.10.47.02.16.11.16.01.16.1
1.15.0>=3.9,<3.112.47.01.15.010.0.02.151.15.11.15.00.46.02.15.11.15.01.15.1
1.14.0>=3.8,<3.112.47.01.14.010.0.02.131.14.01.14.00.45.02.9.01.14.01.14.0
1.13.0>=3.8,<3.102.40.01.13.16.0.02.121.13.01.13.10.44.02.9.01.13.01.13.0
1.12.0>=3.7,<3.102.40.01.12.06.0.02.111.12.01.12.00.43.02.9.01.12.01.12.0
1.11.0>=3.7,<3.102.40.01.11.06.0.01.15.5 / 2.10.01.11.01.11.00.42.02.9.01.11.01.11.0
1.10.0>=3.7,<3.102.40.01.10.06.0.01.15.5 / 2.9.01.10.01.10.00.41.02.9.01.10.01.10.0
1.9.0>=3.7,<3.102.38.01.9.05.0.01.15.5 / 2.9.01.9.01.9.00.40.02.9.01.9.01.9.0
1.8.0>=3.7,<3.102.38.01.8.05.0.01.15.5 / 2.8.01.8.01.8.00.39.02.8.01.8.01.8.0
1.7.0>=3.7,<3.92.36.01.7.05.0.01.15.5 / 2.8.01.7.01.7.00.38.02.8.01.7.01.7.0
1.6.2>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.8.01.6.01.6.00.37.02.7.01.6.01.6.0
1.6.0>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.7.01.6.01.6.00.37.02.7.01.6.01.6.0
1.5.0>=3.7,<3.92.34.01.5.05.0.01.15.2 / 2.7.01.5.01.5.00.36.02.7.01.5.01.5.0
1.4.0>=3.7,<3.92.33.01.4.05.0.01.15.0 / 2.6.01.4.01.4.00.35.02.6.01.4.01.4.0
1.3.4>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.3>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.2>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.1>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.0>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.2.1>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.2.0>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.0.0>=3.6,<3.92.29.01.0.02.0.01.15.0 / 2.5.01.0.01.0.00.31.02.5.11.0.01.0.0
0.30.0>=3.6,<3.92.28.00.30.02.0.01.15.0 / 2.4.00.30.00.30.00.30.02.4.00.30.00.30.0
0.29.0>=3.6,<3.92.28.00.29.02.0.01.15.0 / 2.4.00.29.00.29.00.29.02.4.00.29.00.29.0
0.28.0>=3.6,<3.92.28.00.28.02.0.01.15.0 / 2.4.00.28.00.28.00.28.02.4.00.28.00.28.1
0.27.0>=3.6,<3.92.27.00.27.02.0.01.15.0 / 2.4.00.27.00.27.00.27.02.4.00.27.00.27.0
0.26.4>=3.6,<3.92.28.00.26.00.17.01.15.0 / 2.3.00.26.10.26.00.26.02.3.00.26.00.26.0
0.26.3>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.1>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.0>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.25.0>=3.6,<3.92.25.00.24.00.17.01.15.0 / 2.3.00.25.00.25.00.25.02.3.00.25.00.25.0
0.24.1>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.24.0>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.23.1>=3.5,<42.24.00.23.00.17.01.15.0 / 2.3.00.23.10.23.00.23.02.3.00.23.00.23.0
0.23.0>=3.5,<42.23.00.23.00.17.01.15.0 / 2.3.00.23.00.23.00.23.02.3.00.23.00.23.0
0.22.2>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.1>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.0>=3.5,<42.21.00.22.00.16.01.15.0 / 2.2.00.22.00.22.00.22.12.2.00.22.00.22.0
0.21.5>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.4>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.3>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.2>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.1>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.40.21.10.21.42.1.00.21.20.21.3
0.21.0>=2.7,<3 or >=3.5,<42.17.00.21.00.15.01.15.0 / 2.1.00.21.00.21.00.21.12.1.00.21.00.21.0
0.15.0>=2.7,<3 or >=3.5,<42.16.00.15.00.15.01.15.00.15.00.15.00.15.21.15.00.15.00.15.1
0.14.0>=2.7,<3 or >=3.5,<42.14.00.14.00.14.01.14.00.14.10.14.00.14.01.14.00.14.0n/a
0.13.0>=2.7,<3 or >=3.5,<42.12.00.13.2n/a1.13.10.13.10.13.00.13.21.13.00.13.0n/a
0.12.0>=2.7,<32.10.00.13.2n/a1.12.00.12.00.12.10.12.11.12.00.12.0n/a

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TFX

PythonPyPITensorFlow

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.

tfxPythonapache-beam[gcp]ml-metadatapyarrowtensorflowtensorflow-data-validationtensorflow-metadatatensorflow-model-analysistensorflow-serving-apitensorflow-transformtfx-bsl
GitHub master>=3.9,<3.112.59.01.17.110.0.1nightly (2.x)1.17.01.17.10.48.02.17.11.17.01.17.1
1.17.2>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.1>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.0>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.16.0>=3.9,<3.112.59.01.16.010.0.12.161.16.11.16.10.47.02.16.11.16.01.16.1
1.15.0>=3.9,<3.112.47.01.15.010.0.02.151.15.11.15.00.46.02.15.11.15.01.15.1
1.14.0>=3.8,<3.112.47.01.14.010.0.02.131.14.01.14.00.45.02.9.01.14.01.14.0
1.13.0>=3.8,<3.102.40.01.13.16.0.02.121.13.01.13.10.44.02.9.01.13.01.13.0
1.12.0>=3.7,<3.102.40.01.12.06.0.02.111.12.01.12.00.43.02.9.01.12.01.12.0
1.11.0>=3.7,<3.102.40.01.11.06.0.01.15.5 / 2.10.01.11.01.11.00.42.02.9.01.11.01.11.0
1.10.0>=3.7,<3.102.40.01.10.06.0.01.15.5 / 2.9.01.10.01.10.00.41.02.9.01.10.01.10.0
1.9.0>=3.7,<3.102.38.01.9.05.0.01.15.5 / 2.9.01.9.01.9.00.40.02.9.01.9.01.9.0
1.8.0>=3.7,<3.102.38.01.8.05.0.01.15.5 / 2.8.01.8.01.8.00.39.02.8.01.8.01.8.0
1.7.0>=3.7,<3.92.36.01.7.05.0.01.15.5 / 2.8.01.7.01.7.00.38.02.8.01.7.01.7.0
1.6.2>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.8.01.6.01.6.00.37.02.7.01.6.01.6.0
1.6.0>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.7.01.6.01.6.00.37.02.7.01.6.01.6.0
1.5.0>=3.7,<3.92.34.01.5.05.0.01.15.2 / 2.7.01.5.01.5.00.36.02.7.01.5.01.5.0
1.4.0>=3.7,<3.92.33.01.4.05.0.01.15.0 / 2.6.01.4.01.4.00.35.02.6.01.4.01.4.0
1.3.4>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.3>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.2>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.1>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.0>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.2.1>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.2.0>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.0.0>=3.6,<3.92.29.01.0.02.0.01.15.0 / 2.5.01.0.01.0.00.31.02.5.11.0.01.0.0
0.30.0>=3.6,<3.92.28.00.30.02.0.01.15.0 / 2.4.00.30.00.30.00.30.02.4.00.30.00.30.0
0.29.0>=3.6,<3.92.28.00.29.02.0.01.15.0 / 2.4.00.29.00.29.00.29.02.4.00.29.00.29.0
0.28.0>=3.6,<3.92.28.00.28.02.0.01.15.0 / 2.4.00.28.00.28.00.28.02.4.00.28.00.28.1
0.27.0>=3.6,<3.92.27.00.27.02.0.01.15.0 / 2.4.00.27.00.27.00.27.02.4.00.27.00.27.0
0.26.4>=3.6,<3.92.28.00.26.00.17.01.15.0 / 2.3.00.26.10.26.00.26.02.3.00.26.00.26.0
0.26.3>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.1>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.0>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.25.0>=3.6,<3.92.25.00.24.00.17.01.15.0 / 2.3.00.25.00.25.00.25.02.3.00.25.00.25.0
0.24.1>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.24.0>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.23.1>=3.5,<42.24.00.23.00.17.01.15.0 / 2.3.00.23.10.23.00.23.02.3.00.23.00.23.0
0.23.0>=3.5,<42.23.00.23.00.17.01.15.0 / 2.3.00.23.00.23.00.23.02.3.00.23.00.23.0
0.22.2>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.1>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.0>=3.5,<42.21.00.22.00.16.01.15.0 / 2.2.00.22.00.22.00.22.12.2.00.22.00.22.0
0.21.5>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.4>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.3>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.2>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.1>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.40.21.10.21.42.1.00.21.20.21.3
0.21.0>=2.7,<3 or >=3.5,<42.17.00.21.00.15.01.15.0 / 2.1.00.21.00.21.00.21.12.1.00.21.00.21.0
0.15.0>=2.7,<3 or >=3.5,<42.16.00.15.00.15.01.15.00.15.00.15.00.15.21.15.00.15.00.15.1
0.14.0>=2.7,<3 or >=3.5,<42.14.00.14.00.14.01.14.00.14.10.14.00.14.01.14.00.14.0n/a
0.13.0>=2.7,<3 or >=3.5,<42.12.00.13.2n/a1.13.10.13.10.13.00.13.21.13.00.13.0n/a
0.12.0>=2.7,<32.10.00.13.2n/a1.12.00.12.00.12.10.12.11.12.00.12.0n/a

Resources

About

TFX is an end-to-end platform for deploying production ML pipelines

Resources

Code of conduct

Contributing

Stars

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Watchers

0 watching

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Releases

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
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TFX

PythonPyPITensorFlow

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.

tfxPythonapache-beam[gcp]ml-metadatapyarrowtensorflowtensorflow-data-validationtensorflow-metadatatensorflow-model-analysistensorflow-serving-apitensorflow-transformtfx-bsl
GitHub master>=3.9,<3.112.59.01.17.110.0.1nightly (2.x)1.17.01.17.10.48.02.17.11.17.01.17.1
1.17.2>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.1>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.0>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.16.0>=3.9,<3.112.59.01.16.010.0.12.161.16.11.16.10.47.02.16.11.16.01.16.1
1.15.0>=3.9,<3.112.47.01.15.010.0.02.151.15.11.15.00.46.02.15.11.15.01.15.1
1.14.0>=3.8,<3.112.47.01.14.010.0.02.131.14.01.14.00.45.02.9.01.14.01.14.0
1.13.0>=3.8,<3.102.40.01.13.16.0.02.121.13.01.13.10.44.02.9.01.13.01.13.0
1.12.0>=3.7,<3.102.40.01.12.06.0.02.111.12.01.12.00.43.02.9.01.12.01.12.0
1.11.0>=3.7,<3.102.40.01.11.06.0.01.15.5 / 2.10.01.11.01.11.00.42.02.9.01.11.01.11.0
1.10.0>=3.7,<3.102.40.01.10.06.0.01.15.5 / 2.9.01.10.01.10.00.41.02.9.01.10.01.10.0
1.9.0>=3.7,<3.102.38.01.9.05.0.01.15.5 / 2.9.01.9.01.9.00.40.02.9.01.9.01.9.0
1.8.0>=3.7,<3.102.38.01.8.05.0.01.15.5 / 2.8.01.8.01.8.00.39.02.8.01.8.01.8.0
1.7.0>=3.7,<3.92.36.01.7.05.0.01.15.5 / 2.8.01.7.01.7.00.38.02.8.01.7.01.7.0
1.6.2>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.8.01.6.01.6.00.37.02.7.01.6.01.6.0
1.6.0>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.7.01.6.01.6.00.37.02.7.01.6.01.6.0
1.5.0>=3.7,<3.92.34.01.5.05.0.01.15.2 / 2.7.01.5.01.5.00.36.02.7.01.5.01.5.0
1.4.0>=3.7,<3.92.33.01.4.05.0.01.15.0 / 2.6.01.4.01.4.00.35.02.6.01.4.01.4.0
1.3.4>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.3>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.2>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.1>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.0>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.2.1>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.2.0>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.0.0>=3.6,<3.92.29.01.0.02.0.01.15.0 / 2.5.01.0.01.0.00.31.02.5.11.0.01.0.0
0.30.0>=3.6,<3.92.28.00.30.02.0.01.15.0 / 2.4.00.30.00.30.00.30.02.4.00.30.00.30.0
0.29.0>=3.6,<3.92.28.00.29.02.0.01.15.0 / 2.4.00.29.00.29.00.29.02.4.00.29.00.29.0
0.28.0>=3.6,<3.92.28.00.28.02.0.01.15.0 / 2.4.00.28.00.28.00.28.02.4.00.28.00.28.1
0.27.0>=3.6,<3.92.27.00.27.02.0.01.15.0 / 2.4.00.27.00.27.00.27.02.4.00.27.00.27.0
0.26.4>=3.6,<3.92.28.00.26.00.17.01.15.0 / 2.3.00.26.10.26.00.26.02.3.00.26.00.26.0
0.26.3>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.1>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.0>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.25.0>=3.6,<3.92.25.00.24.00.17.01.15.0 / 2.3.00.25.00.25.00.25.02.3.00.25.00.25.0
0.24.1>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.24.0>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.23.1>=3.5,<42.24.00.23.00.17.01.15.0 / 2.3.00.23.10.23.00.23.02.3.00.23.00.23.0
0.23.0>=3.5,<42.23.00.23.00.17.01.15.0 / 2.3.00.23.00.23.00.23.02.3.00.23.00.23.0
0.22.2>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.1>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.0>=3.5,<42.21.00.22.00.16.01.15.0 / 2.2.00.22.00.22.00.22.12.2.00.22.00.22.0
0.21.5>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.4>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.3>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.2>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.1>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.40.21.10.21.42.1.00.21.20.21.3
0.21.0>=2.7,<3 or >=3.5,<42.17.00.21.00.15.01.15.0 / 2.1.00.21.00.21.00.21.12.1.00.21.00.21.0
0.15.0>=2.7,<3 or >=3.5,<42.16.00.15.00.15.01.15.00.15.00.15.00.15.21.15.00.15.00.15.1
0.14.0>=2.7,<3 or >=3.5,<42.14.00.14.00.14.01.14.00.14.10.14.00.14.01.14.00.14.0n/a
0.13.0>=2.7,<3 or >=3.5,<42.12.00.13.2n/a1.13.10.13.10.13.00.13.21.13.00.13.0n/a
0.12.0>=2.7,<32.10.00.13.2n/a1.12.00.12.00.12.10.12.11.12.00.12.0n/a

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TFX is an end-to-end platform for deploying production ML pipelines

Resources

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Auto-enable theater mode on YouTube (function() { function tryTheater() { var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]'); if (btn && !btn.classList.contains('activated')) { btn.click(); } } // Try immediately tryTheater(); // Try after navigation (SPA) var lastUrl = location.href; setInterval(function() { if (location.href !== lastUrl) { lastUrl = location.href; setTimeout(tryTheater, 500); } }, 1000); // Also try on player load var observer = new MutationObserver(tryTheater); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

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TFX

PythonPyPITensorFlow

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.

tfxPythonapache-beam[gcp]ml-metadatapyarrowtensorflowtensorflow-data-validationtensorflow-metadatatensorflow-model-analysistensorflow-serving-apitensorflow-transformtfx-bsl
GitHub master>=3.9,<3.112.59.01.17.110.0.1nightly (2.x)1.17.01.17.10.48.02.17.11.17.01.17.1
1.17.2>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.1>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.0>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.16.0>=3.9,<3.112.59.01.16.010.0.12.161.16.11.16.10.47.02.16.11.16.01.16.1
1.15.0>=3.9,<3.112.47.01.15.010.0.02.151.15.11.15.00.46.02.15.11.15.01.15.1
1.14.0>=3.8,<3.112.47.01.14.010.0.02.131.14.01.14.00.45.02.9.01.14.01.14.0
1.13.0>=3.8,<3.102.40.01.13.16.0.02.121.13.01.13.10.44.02.9.01.13.01.13.0
1.12.0>=3.7,<3.102.40.01.12.06.0.02.111.12.01.12.00.43.02.9.01.12.01.12.0
1.11.0>=3.7,<3.102.40.01.11.06.0.01.15.5 / 2.10.01.11.01.11.00.42.02.9.01.11.01.11.0
1.10.0>=3.7,<3.102.40.01.10.06.0.01.15.5 / 2.9.01.10.01.10.00.41.02.9.01.10.01.10.0
1.9.0>=3.7,<3.102.38.01.9.05.0.01.15.5 / 2.9.01.9.01.9.00.40.02.9.01.9.01.9.0
1.8.0>=3.7,<3.102.38.01.8.05.0.01.15.5 / 2.8.01.8.01.8.00.39.02.8.01.8.01.8.0
1.7.0>=3.7,<3.92.36.01.7.05.0.01.15.5 / 2.8.01.7.01.7.00.38.02.8.01.7.01.7.0
1.6.2>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.8.01.6.01.6.00.37.02.7.01.6.01.6.0
1.6.0>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.7.01.6.01.6.00.37.02.7.01.6.01.6.0
1.5.0>=3.7,<3.92.34.01.5.05.0.01.15.2 / 2.7.01.5.01.5.00.36.02.7.01.5.01.5.0
1.4.0>=3.7,<3.92.33.01.4.05.0.01.15.0 / 2.6.01.4.01.4.00.35.02.6.01.4.01.4.0
1.3.4>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.3>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.2>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.1>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.0>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.2.1>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.2.0>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.0.0>=3.6,<3.92.29.01.0.02.0.01.15.0 / 2.5.01.0.01.0.00.31.02.5.11.0.01.0.0
0.30.0>=3.6,<3.92.28.00.30.02.0.01.15.0 / 2.4.00.30.00.30.00.30.02.4.00.30.00.30.0
0.29.0>=3.6,<3.92.28.00.29.02.0.01.15.0 / 2.4.00.29.00.29.00.29.02.4.00.29.00.29.0
0.28.0>=3.6,<3.92.28.00.28.02.0.01.15.0 / 2.4.00.28.00.28.00.28.02.4.00.28.00.28.1
0.27.0>=3.6,<3.92.27.00.27.02.0.01.15.0 / 2.4.00.27.00.27.00.27.02.4.00.27.00.27.0
0.26.4>=3.6,<3.92.28.00.26.00.17.01.15.0 / 2.3.00.26.10.26.00.26.02.3.00.26.00.26.0
0.26.3>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.1>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.0>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.25.0>=3.6,<3.92.25.00.24.00.17.01.15.0 / 2.3.00.25.00.25.00.25.02.3.00.25.00.25.0
0.24.1>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.24.0>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.23.1>=3.5,<42.24.00.23.00.17.01.15.0 / 2.3.00.23.10.23.00.23.02.3.00.23.00.23.0
0.23.0>=3.5,<42.23.00.23.00.17.01.15.0 / 2.3.00.23.00.23.00.23.02.3.00.23.00.23.0
0.22.2>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.1>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.0>=3.5,<42.21.00.22.00.16.01.15.0 / 2.2.00.22.00.22.00.22.12.2.00.22.00.22.0
0.21.5>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.4>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.3>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.2>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.1>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.40.21.10.21.42.1.00.21.20.21.3
0.21.0>=2.7,<3 or >=3.5,<42.17.00.21.00.15.01.15.0 / 2.1.00.21.00.21.00.21.12.1.00.21.00.21.0
0.15.0>=2.7,<3 or >=3.5,<42.16.00.15.00.15.01.15.00.15.00.15.00.15.21.15.00.15.00.15.1
0.14.0>=2.7,<3 or >=3.5,<42.14.00.14.00.14.01.14.00.14.10.14.00.14.01.14.00.14.0n/a
0.13.0>=2.7,<3 or >=3.5,<42.12.00.13.2n/a1.13.10.13.10.13.00.13.21.13.00.13.0n/a
0.12.0>=2.7,<32.10.00.13.2n/a1.12.00.12.00.12.10.12.11.12.00.12.0n/a

Resources

About

TFX is an end-to-end platform for deploying production ML pipelines

Resources

Code of conduct

Contributing

Stars

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TFX

PythonPyPITensorFlow

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.

tfxPythonapache-beam[gcp]ml-metadatapyarrowtensorflowtensorflow-data-validationtensorflow-metadatatensorflow-model-analysistensorflow-serving-apitensorflow-transformtfx-bsl
GitHub master>=3.9,<3.112.59.01.17.110.0.1nightly (2.x)1.17.01.17.10.48.02.17.11.17.01.17.1
1.17.2>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.1>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.0>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.16.0>=3.9,<3.112.59.01.16.010.0.12.161.16.11.16.10.47.02.16.11.16.01.16.1
1.15.0>=3.9,<3.112.47.01.15.010.0.02.151.15.11.15.00.46.02.15.11.15.01.15.1
1.14.0>=3.8,<3.112.47.01.14.010.0.02.131.14.01.14.00.45.02.9.01.14.01.14.0
1.13.0>=3.8,<3.102.40.01.13.16.0.02.121.13.01.13.10.44.02.9.01.13.01.13.0
1.12.0>=3.7,<3.102.40.01.12.06.0.02.111.12.01.12.00.43.02.9.01.12.01.12.0
1.11.0>=3.7,<3.102.40.01.11.06.0.01.15.5 / 2.10.01.11.01.11.00.42.02.9.01.11.01.11.0
1.10.0>=3.7,<3.102.40.01.10.06.0.01.15.5 / 2.9.01.10.01.10.00.41.02.9.01.10.01.10.0
1.9.0>=3.7,<3.102.38.01.9.05.0.01.15.5 / 2.9.01.9.01.9.00.40.02.9.01.9.01.9.0
1.8.0>=3.7,<3.102.38.01.8.05.0.01.15.5 / 2.8.01.8.01.8.00.39.02.8.01.8.01.8.0
1.7.0>=3.7,<3.92.36.01.7.05.0.01.15.5 / 2.8.01.7.01.7.00.38.02.8.01.7.01.7.0
1.6.2>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.8.01.6.01.6.00.37.02.7.01.6.01.6.0
1.6.0>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.7.01.6.01.6.00.37.02.7.01.6.01.6.0
1.5.0>=3.7,<3.92.34.01.5.05.0.01.15.2 / 2.7.01.5.01.5.00.36.02.7.01.5.01.5.0
1.4.0>=3.7,<3.92.33.01.4.05.0.01.15.0 / 2.6.01.4.01.4.00.35.02.6.01.4.01.4.0
1.3.4>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.3>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.2>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.1>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.0>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.2.1>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.2.0>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.0.0>=3.6,<3.92.29.01.0.02.0.01.15.0 / 2.5.01.0.01.0.00.31.02.5.11.0.01.0.0
0.30.0>=3.6,<3.92.28.00.30.02.0.01.15.0 / 2.4.00.30.00.30.00.30.02.4.00.30.00.30.0
0.29.0>=3.6,<3.92.28.00.29.02.0.01.15.0 / 2.4.00.29.00.29.00.29.02.4.00.29.00.29.0
0.28.0>=3.6,<3.92.28.00.28.02.0.01.15.0 / 2.4.00.28.00.28.00.28.02.4.00.28.00.28.1
0.27.0>=3.6,<3.92.27.00.27.02.0.01.15.0 / 2.4.00.27.00.27.00.27.02.4.00.27.00.27.0
0.26.4>=3.6,<3.92.28.00.26.00.17.01.15.0 / 2.3.00.26.10.26.00.26.02.3.00.26.00.26.0
0.26.3>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.1>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.0>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.25.0>=3.6,<3.92.25.00.24.00.17.01.15.0 / 2.3.00.25.00.25.00.25.02.3.00.25.00.25.0
0.24.1>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.24.0>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.23.1>=3.5,<42.24.00.23.00.17.01.15.0 / 2.3.00.23.10.23.00.23.02.3.00.23.00.23.0
0.23.0>=3.5,<42.23.00.23.00.17.01.15.0 / 2.3.00.23.00.23.00.23.02.3.00.23.00.23.0
0.22.2>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.1>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.0>=3.5,<42.21.00.22.00.16.01.15.0 / 2.2.00.22.00.22.00.22.12.2.00.22.00.22.0
0.21.5>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.4>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.3>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.2>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.1>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.40.21.10.21.42.1.00.21.20.21.3
0.21.0>=2.7,<3 or >=3.5,<42.17.00.21.00.15.01.15.0 / 2.1.00.21.00.21.00.21.12.1.00.21.00.21.0
0.15.0>=2.7,<3 or >=3.5,<42.16.00.15.00.15.01.15.00.15.00.15.00.15.21.15.00.15.00.15.1
0.14.0>=2.7,<3 or >=3.5,<42.14.00.14.00.14.01.14.00.14.10.14.00.14.01.14.00.14.0n/a
0.13.0>=2.7,<3 or >=3.5,<42.12.00.13.2n/a1.13.10.13.10.13.00.13.21.13.00.13.0n/a
0.12.0>=2.7,<32.10.00.13.2n/a1.12.00.12.00.12.10.12.11.12.00.12.0n/a

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, 'i'); if (__m === '*' || __re.test(location.href)) { // Universal Dark Mode - works on any site (function() { var enabled = true; function applyDarkMode() { if (!enabled) return; // Create style element if it doesn't exist var style = document.getElementById('universal-dark-mode-style'); if (!style) { style = document.createElement('style'); style.id = 'universal-dark-mode-style'; document.head.appendChild(style); } // Dark mode CSS - inverts colors but preserves images/video style.textContent = ' /* Invert everything except media */ html { filter: invert(1) hue-rotate(180deg) !important; background: #1a1a2e !important; } /* Restore images, videos, iframes, canvas */ img, video, iframe, canvas, svg, picture, [style*="background-image"] { filter: invert(1) hue-rotate(180deg) !important; } /* Preserve specific elements that should not be inverted */ .no-dark-mode, .no-dark-mode *, [data-theme="light"], [data-theme="light"], .ace_editor, .ace_editor *, .CodeMirror, .CodeMirror *, .monaco-editor, .monaco-editor *, .markdown-body pre, .markdown-body pre *, .highlight, .highlight *, pre code, pre code * { filter: none !important; } /* Fix common UI elements */ .modal, .popup, .dropdown-menu, .tooltip, .popover { filter: invert(1) hue-rotate(180deg) !important; background: #2d2d44 !important; border-color: #444 !important; } /* Scrollbars */ ::-webkit-scrollbar { background: #1a1a2e !important; } ::-webkit-scrollbar-thumb { background: #444 !important; } ::-webkit-scrollbar-thumb:hover { background: #555 !important; } /* Selection */ ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; } ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; } '; } function removeDarkMode() { var style = document.getElementById('universal-dark-mode-style'); if (style) style.remove(); } // Toggle with Alt+Shift+D document.addEventListener('keydown', function(e) { if (e.altKey && e.shiftKey && e.key === 'D') { e.preventDefault(); enabled = !enabled; if (enabled) { applyDarkMode(); console.log('[Universal Dark Mode] Enabled'); } else { removeDarkMode(); console.log('[Universal Dark Mode] Disabled'); } } }); // Apply on load applyDarkMode(); // Re-apply on dynamic content var observer = new MutationObserver(function(mutations) { if (enabled && !document.getElementById('universal-dark-mode-style')) { applyDarkMode(); } }); observer.observe(document.head, { childList: true }); console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle'); })(); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
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TFX

PythonPyPITensorFlow

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.

tfxPythonapache-beam[gcp]ml-metadatapyarrowtensorflowtensorflow-data-validationtensorflow-metadatatensorflow-model-analysistensorflow-serving-apitensorflow-transformtfx-bsl
GitHub master>=3.9,<3.112.59.01.17.110.0.1nightly (2.x)1.17.01.17.10.48.02.17.11.17.01.17.1
1.17.2>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.1>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.17.0>=3.9,<3.112.59.01.17.110.0.12.171.17.01.17.10.48.02.17.11.17.01.17.1
1.16.0>=3.9,<3.112.59.01.16.010.0.12.161.16.11.16.10.47.02.16.11.16.01.16.1
1.15.0>=3.9,<3.112.47.01.15.010.0.02.151.15.11.15.00.46.02.15.11.15.01.15.1
1.14.0>=3.8,<3.112.47.01.14.010.0.02.131.14.01.14.00.45.02.9.01.14.01.14.0
1.13.0>=3.8,<3.102.40.01.13.16.0.02.121.13.01.13.10.44.02.9.01.13.01.13.0
1.12.0>=3.7,<3.102.40.01.12.06.0.02.111.12.01.12.00.43.02.9.01.12.01.12.0
1.11.0>=3.7,<3.102.40.01.11.06.0.01.15.5 / 2.10.01.11.01.11.00.42.02.9.01.11.01.11.0
1.10.0>=3.7,<3.102.40.01.10.06.0.01.15.5 / 2.9.01.10.01.10.00.41.02.9.01.10.01.10.0
1.9.0>=3.7,<3.102.38.01.9.05.0.01.15.5 / 2.9.01.9.01.9.00.40.02.9.01.9.01.9.0
1.8.0>=3.7,<3.102.38.01.8.05.0.01.15.5 / 2.8.01.8.01.8.00.39.02.8.01.8.01.8.0
1.7.0>=3.7,<3.92.36.01.7.05.0.01.15.5 / 2.8.01.7.01.7.00.38.02.8.01.7.01.7.0
1.6.2>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.8.01.6.01.6.00.37.02.7.01.6.01.6.0
1.6.0>=3.7,<3.92.35.01.6.05.0.01.15.5 / 2.7.01.6.01.6.00.37.02.7.01.6.01.6.0
1.5.0>=3.7,<3.92.34.01.5.05.0.01.15.2 / 2.7.01.5.01.5.00.36.02.7.01.5.01.5.0
1.4.0>=3.7,<3.92.33.01.4.05.0.01.15.0 / 2.6.01.4.01.4.00.35.02.6.01.4.01.4.0
1.3.4>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.3>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.2>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.1>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.3.0>=3.6,<3.92.32.01.3.02.0.01.15.0 / 2.6.01.3.01.2.00.34.12.6.01.3.01.3.0
1.2.1>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.2.0>=3.6,<3.92.31.01.2.02.0.01.15.0 / 2.5.01.2.01.2.00.33.02.5.11.2.01.2.0
1.0.0>=3.6,<3.92.29.01.0.02.0.01.15.0 / 2.5.01.0.01.0.00.31.02.5.11.0.01.0.0
0.30.0>=3.6,<3.92.28.00.30.02.0.01.15.0 / 2.4.00.30.00.30.00.30.02.4.00.30.00.30.0
0.29.0>=3.6,<3.92.28.00.29.02.0.01.15.0 / 2.4.00.29.00.29.00.29.02.4.00.29.00.29.0
0.28.0>=3.6,<3.92.28.00.28.02.0.01.15.0 / 2.4.00.28.00.28.00.28.02.4.00.28.00.28.1
0.27.0>=3.6,<3.92.27.00.27.02.0.01.15.0 / 2.4.00.27.00.27.00.27.02.4.00.27.00.27.0
0.26.4>=3.6,<3.92.28.00.26.00.17.01.15.0 / 2.3.00.26.10.26.00.26.02.3.00.26.00.26.0
0.26.3>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.1>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.26.0>=3.6,<3.92.25.00.26.00.17.01.15.0 / 2.3.00.26.00.26.00.26.02.3.00.26.00.26.0
0.25.0>=3.6,<3.92.25.00.24.00.17.01.15.0 / 2.3.00.25.00.25.00.25.02.3.00.25.00.25.0
0.24.1>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.24.0>=3.6,<3.92.24.00.24.00.17.01.15.0 / 2.3.00.24.10.24.00.24.32.3.00.24.10.24.1
0.23.1>=3.5,<42.24.00.23.00.17.01.15.0 / 2.3.00.23.10.23.00.23.02.3.00.23.00.23.0
0.23.0>=3.5,<42.23.00.23.00.17.01.15.0 / 2.3.00.23.00.23.00.23.02.3.00.23.00.23.0
0.22.2>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.1>=3.5,<42.21.00.22.10.16.01.15.0 / 2.2.00.22.20.22.20.22.22.2.00.22.00.22.1
0.22.0>=3.5,<42.21.00.22.00.16.01.15.0 / 2.2.00.22.00.22.00.22.12.2.00.22.00.22.0
0.21.5>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.4>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.3>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.2>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.50.21.10.21.52.1.00.21.20.21.4
0.21.1>=2.7,<3 or >=3.5,<42.17.00.21.20.15.01.15.0 / 2.1.00.21.40.21.10.21.42.1.00.21.20.21.3
0.21.0>=2.7,<3 or >=3.5,<42.17.00.21.00.15.01.15.0 / 2.1.00.21.00.21.00.21.12.1.00.21.00.21.0
0.15.0>=2.7,<3 or >=3.5,<42.16.00.15.00.15.01.15.00.15.00.15.00.15.21.15.00.15.00.15.1
0.14.0>=2.7,<3 or >=3.5,<42.14.00.14.00.14.01.14.00.14.10.14.00.14.01.14.00.14.0n/a
0.13.0>=2.7,<3 or >=3.5,<42.12.00.13.2n/a1.13.10.13.10.13.00.13.21.13.00.13.0n/a
0.12.0>=2.7,<32.10.00.13.2n/a1.12.00.12.00.12.10.12.11.12.00.12.0n/a

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