Revert previous workarounds and upgrade TFX stack to 1.21.0#39164
Revert previous workarounds and upgrade TFX stack to 1.21.0#39164shunping wants to merge 7 commits into
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r: @aIbrahiim Running the failed workflow against this PR: https://github.com/apache/beam/actions/runs/28452712519/job/84319046212 Notice that this PR isn't meant to capture all changes from #39162. If you need to make additional changes to refactor the test, please feel free to rebase your work after it is merged. Thanks a lot! |
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Summary of ChangesHello, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request modernizes the TFX benchmark stack by upgrading core components to version 1.21.0. By updating these dependencies, the project is able to remove previous configuration workarounds and constraints files that were used to manage complex dependency resolution, simplifying the installation process for the benchmark environment. Highlights
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Code Review
This pull request removes the constraints file for CloudML benchmarks, updates and pins several TFX-related dependencies to version 1.21.0 in requirements.txt, and leaves other core dependencies (such as tensorflow, numpy, and pyarrow) completely unpinned. It also removes the @pytest.mark.uses_tft decorator from some MLTransform tests and updates the Gradle task to install requirements without a constraints file. The feedback points out that leaving core dependencies unpinned can lead to non-reproducible environments and unexpected CI failures, recommending that compatible version ranges or exact pins be specified.
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shunping
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tfx-bsl,tensorflow-transform, andtensorflow-metadata) to1.21.0in requirements.txt.@pytest.mark.uses_tftmarker from tests inmltransform_one_hot_encoding_test.pyto skip those tests in dataflow load test.fixes #38780
related to #39163