[None][infra] Update upgrade related docs for release 1.2 (#10760)

[chzblych]

Summary by CodeRabbit

• Documentation
  • Updated installation documentation with CUDA 13.1 and PyTorch 2.9.1 requirements
  • Updated support matrix with latest versions of dependencies
  • Added compatibility notes regarding PyTorch wheel compatibility with container environments and recommendations for pre-built wheels

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Description

Test Coverage

PR Checklist

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• PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.

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• Documentation updated as needed

• Update tava architecture diagram if there is a significant design change in PR.

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• Please check this after reviewing the above items as appropriate for this PR.

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[coderabbitai]

📝 Walkthrough

Walkthrough

This PR updates version references across documentation and CI configuration files. CUDA is updated from 13.0 to 13.1, PyTorch from 2.9.0 to 2.9.1, and Triton repository tags from r25.10 to r25.12. Support matrix references are updated to align with newer container and TensorRT versions, and a sanity check configuration is removed.

Changes

Cohort / File(s)	Summary
Documentation Version Updates README.md, docs/source/installation/linux.md, docs/source/legacy/reference/support-matrix.md	Updated CUDA (13.0→13.1), PyTorch (2.9.0→2.9.1), and container/TensorRT version references (25.10→25.12, 10.13→10.14). Added compatibility notes regarding PyTorch 2.9.1 wheel usage with NVIDIA containers.
CI Build Configuration jenkins/Build.groovy	Updated Triton repository tags from r25.10 to r25.12 for cmake invocations.
CI Test Configuration jenkins/L0_Test.groovy	Updated NVIDIA_TRITON_SERVER_VERSION from 25.10 to 25.12 in test list check; removed PY312-UB2404 block from aarch64 sanity check configurations.

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~10 minutes

Possibly related PRs

• [None][infra] Update upgrade related docs for release 1.2 #10760: Directly overlapping changes to the same documentation and CI files (README.md, linux.md, support-matrix.md, Build.groovy, L0_Test.groovy) updating CUDA/PyTorch/Triton/TensorRT version strings.

🚥 Pre-merge checks | ✅ 2 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Description check	⚠️ Warning	The PR description is completely empty. Only the template and GitHub bot help section are present with no actual description of changes, rationale, or test coverage.	Add a clear description explaining: (1) what versions are being updated (CUDA 13.1, PyTorch 2.9.1, Triton 25.12), (2) why these updates are necessary, and (3) which tests validate these documentation and build configuration changes.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly summarizes the main change: updating upgrade-related documentation and dependencies for release 1.2 across README, installation docs, support matrix, and build scripts.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.

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✨ Finishing touches

• 📝 Generate docstrings

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[coderabbitai]

Actionable comments posted: 1

🤖 Fix all issues with AI agents

In `@docs/source/installation/linux.md`:
- Around line 19-20: Rewrite the sentence that precedes the pip command to fix
grammar and clarify compatibility: replace the fragment "By default, PyTorch
CUDA 12.8 package is installed. Since PyTorch CUDA 13.0 package to align with
the CUDA version used for building TensorRT LLM wheels." with a single clear
sentence explaining that we specify the cu130 wheel to match the CUDA family
used to build TensorRT-LLM and that the cu130 (CUDA 13.0) wheel is
forward-compatible with a CUDA 13.1 system; ensure the pip invocation shown
(pip3 install torch==2.9.1 torchvision --index-url
https://download.pytorch.org/whl/cu130) remains unchanged.

🧹 Nitpick comments (1)

jenkins/L0_Test.groovy (1)

3434-3445: Add a tracking reference for the PyTorch compatibility workaround.

Lines 3434-3445 document a PyTorch incompatibility workaround; consider linking a tracking issue/bug ID so it’s clear when to revert the temporary configuration.