Tfx
TFX is an end-to-end platform for deploying production ML pipelines
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Jina | 17,946 |  | 2 | 9 hours ago | 2,019 | July 06, 2022 | 40 | apache-2.0 | Python | |
| 🔮 Build multimodal AI services via cloud native technologies · Neural Search · Generative AI · Cloud Native | ||||||||||
| Kubeflow | 12,413 | 2 | 10 hours ago | 112 | April 13, 2021 | 401 | apache-2.0 | TypeScript | ||
| Machine Learning Toolkit for Kubernetes | ||||||||||
| Kedro | 8,213 |  | 8 | 32 | 9 hours ago | 35 | May 09, 2022 | 282 | apache-2.0 | Python |
| A Python framework for creating reproducible, maintainable and modular data science code. | ||||||||||
| Stanza | 6,552 |  | 2 | 68 | 17 hours ago | 17 | April 23, 2022 | 75 | other | Python |
| Official Stanford NLP Python Library for Many Human Languages | ||||||||||
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| Image augmentation library in Python for machine learning. | ||||||||||
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| ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management | ||||||||||
| Deeplearningproject | 4,043 | 3 years ago | 3 | mit | HTML | |||||
| An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch. | ||||||||||
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| Build data pipelines, the easy way 🛠️ | ||||||||||
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| 🧙 The modern replacement for Airflow. Build, run, and manage data pipelines for integrating and transforming data. | ||||||||||
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Readme
TFX
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.
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 | apache-beam[gcp] | ml-metadata | pyarrow | tensorflow | tensorflow-data-validation | tensorflow-metadata | tensorflow-model-analysis | tensorflow-serving-api | tensorflow-transform | tfx-bsl |
|---|---|---|---|---|---|---|---|---|---|---|
| GitHub master | 2.40.0 | 1.12.0 | 6.0.0 | nightly (2.x) | 1.12.0 | 1.12.0 | 0.43.0 | 2.9.0 | 1.12.0 | 1.12.0 |
| 1.12.0 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 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 | 2.17.0 | 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 | 2.17.0 | 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 | 2.17.0 | 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 | 2.17.0 | 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 | 2.17.0 | 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 | 2.17.0 | 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 | 2.16.0 | 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 | 2.14.0 | 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 | 2.12.0 | 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 | 2.10.0 | 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 |
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