Release 2.69.0 postrelease CP 36583

[Amar3tto]

Cherry-pick #36583 to post-release branch

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[gemini-code-assist]

Summary of Changes

Hello @Amar3tto, 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 is a cherry-pick to the post-release branch for version 2.69.0, primarily aimed at refining the Python SDK container's machine learning environment. It introduces a dedicated 'ml_cpu' dependency configuration to ensure that PyTorch and other ML libraries are installed using CPU-specific wheels. This change addresses potential licensing conflicts by preventing the inclusion of GPU-dependent packages and standardizes the ML dependency management across various Python versions within the Beam ecosystem.

Highlights

• Introduction of ml_cpu Extra: A new 'ml_cpu' dependency group has been added to 'setup.py' to specifically manage CPU-only machine learning dependencies, providing a clear separation from GPU-enabled configurations.
• CPU-only PyTorch Installation Enforcement: Build scripts ('Dockerfile', 'run_generate_requirements.sh') are updated to explicitly pull PyTorch dependencies from the PyTorch CPU wheel repository, preventing the inclusion of GPU-specific dependencies that might have licensing restrictions.
• Updated ML Requirements Files: New 'ml_image_requirements.txt' files are generated for Python versions 3.9, 3.10, 3.11, and 3.12, and the existing one for 3.13 is updated. All these files now reflect the 'ml_cpu' dependencies and specifically list 'torch==2.8.0+cpu'.
• Dependency Version Bumps: Several ML-related package versions have been updated across the requirements files, including 'cryptography', 'grpcio', 'hypothesis', 'idna', 'referencing', 'regex', 'wrapt', and 'yarl', ensuring compatibility and incorporating the latest stable versions.

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[github-actions]

Checks are failing. Will not request review until checks are succeeding. If you'd like to override that behavior, comment assign set of reviewers

[damccorm]

Thanks

[damccorm]

Checks still seem to be failing, but are unrelated to this pr. Running https://github.com/apache/beam/actions/runs/18949703006 to confirm that this also fails at head on this branch, but I'm not sure why this broke on the postrelease branch...

If that check also fails, this should be safe to merge

EDIT: That fails too, so I'll merge. I'm guessing we're running those tests when we shouldn't be somehow