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[None][chroe] Update the cuda and tensorrt version in homepage icons. #7963
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[None][chroe] Update the cuda and tensorrt version in homepage icons. #7963
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/bot skip --comment "docs only change" |
📝 WalkthroughWalkthroughUpdated README badges to reflect new CUDA (13.0.0) and TensorRT (10.13.2) versions. No source code or public API changes. Changes
Estimated code review effort🎯 1 (Trivial) | ⏱️ ~2 minutes Pre-merge checks and finishing touches❌ Failed checks (1 warning)
✅ Passed checks (2 passed)
✨ Finishing touches
🧪 Generate unit tests
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Actionable comments posted: 0
🧹 Nitpick comments (1)
README.md (1)
10-11: Point badges to the Support Matrix to avoid drift with downloads pages.Linking badges to the project’s Support Matrix reduces confusion if download pages update ahead of repo support.
Apply:
-[](https://developer.nvidia.com/cuda-downloads) -[](https://developer.nvidia.com/tensorrt) +[](https://nvidia.github.io/TensorRT-LLM/reference/support-matrix.html) +[](https://nvidia.github.io/TensorRT-LLM/reference/support-matrix.html)
📜 Review details
Configuration used: Path: .coderabbit.yaml
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (1)
README.md(1 hunks)
🧰 Additional context used
🧠 Learnings (10)
📓 Common learnings
Learnt from: farshadghodsian
PR: NVIDIA/TensorRT-LLM#7101
File: docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md:36-36
Timestamp: 2025-08-21T00:16:56.457Z
Learning: TensorRT-LLM container release tags in documentation should only reference published NGC container images. The README badge version may be ahead of the actual published container versions.
📚 Learning: 2025-08-21T00:16:56.457Z
Learnt from: farshadghodsian
PR: NVIDIA/TensorRT-LLM#7101
File: docs/source/blogs/tech_blog/blog9_Deploying_GPT_OSS_on_TRTLLM.md:36-36
Timestamp: 2025-08-21T00:16:56.457Z
Learning: TensorRT-LLM container release tags in documentation should only reference published NGC container images. The README badge version may be ahead of the actual published container versions.
Applied to files:
README.md
📚 Learning: 2025-08-27T14:23:55.566Z
Learnt from: ixlmar
PR: NVIDIA/TensorRT-LLM#7294
File: tensorrt_llm/_torch/modules/rms_norm.py:17-17
Timestamp: 2025-08-27T14:23:55.566Z
Learning: The TensorRT-LLM project requires Python 3.10+ as evidenced by the use of TypeAlias from typing module, match/case statements, and union type | syntax throughout the codebase, despite some documentation still mentioning Python 3.8+.
Applied to files:
README.md
📚 Learning: 2025-08-06T13:58:07.506Z
Learnt from: galagam
PR: NVIDIA/TensorRT-LLM#6487
File: tests/unittest/_torch/auto_deploy/unit/singlegpu/test_ad_trtllm_bench.py:1-12
Timestamp: 2025-08-06T13:58:07.506Z
Learning: In TensorRT-LLM, test files (files under tests/ directories) do not require NVIDIA copyright headers, unlike production source code files. Test files typically start directly with imports, docstrings, or code.
Applied to files:
README.md
📚 Learning: 2025-08-01T15:14:45.673Z
Learnt from: yibinl-nvidia
PR: NVIDIA/TensorRT-LLM#6506
File: examples/models/core/mixtral/requirements.txt:3-3
Timestamp: 2025-08-01T15:14:45.673Z
Learning: In TensorRT-LLM, examples directory can have different dependency versions than the root requirements.txt file. Version conflicts between root and examples dependencies are acceptable because examples are designed to be standalone and self-contained.
Applied to files:
README.md
📚 Learning: 2025-09-23T15:12:38.312Z
Learnt from: nv-lschneider
PR: NVIDIA/TensorRT-LLM#7910
File: cpp/tensorrt_llm/thop/allreduceOp.cpp:352-446
Timestamp: 2025-09-23T15:12:38.312Z
Learning: In TensorRT-LLM NCCL device implementation, NCCL version 2.28+ requirements are handled at runtime in the nccl_device/config layer rather than with compile-time guards. This allows the allreduceOp to remain version-agnostic and delegates version compatibility validation to the appropriate lower-level components that can gracefully handle unsupported configurations.
Applied to files:
README.md
📚 Learning: 2025-09-09T09:40:45.658Z
Learnt from: fredricz-20070104
PR: NVIDIA/TensorRT-LLM#7645
File: tests/integration/test_lists/qa/llm_function_core.txt:648-648
Timestamp: 2025-09-09T09:40:45.658Z
Learning: In TensorRT-LLM test lists, it's common and intentional for the same test to appear in multiple test list files when they serve different purposes (e.g., llm_function_core.txt for comprehensive core functionality testing and llm_function_core_sanity.txt for quick sanity checks). This duplication allows tests to be run in different testing contexts.
Applied to files:
README.md
📚 Learning: 2025-07-28T17:06:08.621Z
Learnt from: moraxu
PR: NVIDIA/TensorRT-LLM#6303
File: tests/integration/test_lists/qa/examples_test_list.txt:494-494
Timestamp: 2025-07-28T17:06:08.621Z
Learning: In TensorRT-LLM testing, it's common to have both CLI flow tests (test_cli_flow.py) and PyTorch API tests (test_llm_api_pytorch.py) for the same model. These serve different purposes: CLI flow tests validate the traditional command-line workflow, while PyTorch API tests validate the newer LLM API backend. Both are legitimate and should coexist.
Applied to files:
README.md
📚 Learning: 2025-09-16T09:30:09.716Z
Learnt from: tongyuantongyu
PR: NVIDIA/TensorRT-LLM#7763
File: cpp/tensorrt_llm/CMakeLists.txt:297-301
Timestamp: 2025-09-16T09:30:09.716Z
Learning: In the TensorRT-LLM project, NCCL libraries are loaded earlier by PyTorch libraries or the bindings library, so the main shared library doesn't need NCCL paths in its RPATH - the libraries will already be available in the process address space when needed.
Applied to files:
README.md
📚 Learning: 2025-08-14T15:38:01.771Z
Learnt from: MatthiasKohl
PR: NVIDIA/TensorRT-LLM#6904
File: cpp/tensorrt_llm/pybind/thop/bindings.cpp:55-57
Timestamp: 2025-08-14T15:38:01.771Z
Learning: In TensorRT-LLM Python bindings, tensor parameter collections like mla_tensor_params and spec_decoding_tensor_params are kept as required parameters without defaults to maintain API consistency, even when it might affect backward compatibility.
Applied to files:
README.md
⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)
- GitHub Check: Pre-commit Check
🔇 Additional comments (1)
README.md (1)
10-11: Confirm NGC image & support-matrix match README badges (README.md:10-11)CUDA 13.0.0 and TensorRT 10.13.2 are GA, but I couldn't confirm an NGC TensorRT‑LLM container manifest that includes that exact CUDA/TensorRT pair (latest NGC tags reference release:1.1.0rc3 and earlier images show CUDA 12.x / TRT 10.x). Verify the nvcr.io/ngc TensorRT‑LLM image contains CUDA 13.0 and TRT 10.13.2 and update the Support Matrix/docs if needed.
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PR_Github #19813 [ skip ] triggered by Bot |
Signed-off-by: nv-guomingz <137257613+nv-guomingz@users.noreply.github.com>
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/bot skip --comment "docs only change" |
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PR_Github #19816 [ skip ] triggered by Bot |
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Summary by CodeRabbit
Description
Test Coverage
PR Checklist
Please review the following before submitting your PR:
PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.
PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.
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