Add support for TensorFlow 2.19

[psamanoelton]

Summary

Update TensorFlow Quantum build to support TensorFlow 2.19.1.

Keep TFQ aligned with TensorFlow 2.19.1’s Bazel and Python repository expectations, confirm Eigen remains on TensorFlow’s pinned revision, and regenerate Python dependencies from requirements.in.

Key changes

WORKSPACE

• bump @org_tensorflow to 2.19.1
• add python_version_repo to satisfy TensorFlow 2.19’s expected Python version repository layout
• add lightweight wrapper lockfiles (requirements_lock_3_10.txt, requirements_lock_3_11.txt, requirements_lock_3_12.txt) so the same compiled requirements can be reused across the supported Python versions
• confirm Eigen remains aligned with TensorFlow 2.19.1’s pinned revision

requirements.in / requirements.txt

• update TensorFlow requirement to 2.19.1
• update tf-keras requirement to 2.19.x
• regenerate requirements.txt from requirements.in with pip-compile under Python 3.10
• keep the dependency set compatible with Python 3.10, 3.11, and 3.12

TFQ source compatibility

• update noisy expectation ops to avoid copy-constructing tensorflow::mutex, which fails with TensorFlow 2.19
• keep the rest of the TensorFlow Quantum codepath unchanged as much as possible

Docs / install flow

• update install docs and tutorial notebook snippets to use TensorFlow 2.19.1
• document tf-keras==2.19.0 and TF_USE_LEGACY_KERAS=1 as part of the supported install path

Testing

Linux/Ubuntu 22.04 (Docker), Python 3.10, 3.11, and 3.12, Bazelisk → Bazel 6.5.0

• bazel build ... release:build_pip_package succeeds
• unit tests (./scripts/test_all.sh and ./scripts/ci_validate_tutorials.sh) pass
• wheel builds, installs, and imports successfully
• validated with TensorFlow 2.19.1 + tf-keras 2.19.0, Cirq 1.5.0, and NumPy 2.1.3

Notes

• This keeps TFQ on the Keras 2 path; Keras 3 migration can be handled in a future PR
• TensorFlow 2.19.1 keeps the same Eigen pin already used by TFQ
• this change should help with the incoming upgrades to 2.20
• Updating Bazel to 7.4.1 might be useful when upgrading to 2.20

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[gemini-code-assist]

Code Review

This pull request updates the project to support TensorFlow 2.19.1 and TF-Keras 2.19.0. Key changes include updating the Bazel workspace for multi-version Python support, adjusting dependency constraints in setup.py and requirements.in, and updating documentation to include the TF_USE_LEGACY_KERAS=1 environment variable. Additionally, the requirements generation script was refactored, and redundant mutex initializations in the C++ ops were removed. Feedback suggests restoring the pyyaml exclusion in generate_requirements.sh to prevent installation conflicts and explicitly setting the legacy Keras environment variable within the tutorial notebooks to ensure compatibility.