From 0096b50ba00164f2a93fef96789d4353964e5a25 Mon Sep 17 00:00:00 2001 From: Yanchao Lu Date: Sun, 18 Jan 2026 00:14:27 +0800 Subject: [PATCH] [None][infra] Update upgrade related docs for release 1.2 (#10760) (#10773) Signed-off-by: qqiao Signed-off-by: Yanchao Lu Co-authored-by: Emma Qiao --- README.md | 4 ++-- docs/source/installation/linux.md | 9 ++++++--- docs/source/legacy/reference/support-matrix.md | 4 ++-- jenkins/Build.groovy | 2 +- jenkins/L0_Test.groovy | 8 +++++--- 5 files changed, 16 insertions(+), 11 deletions(-) diff --git a/README.md b/README.md index eb0223bcce..52f48f2b15 100644 --- a/README.md +++ b/README.md @@ -11,8 +11,8 @@ This branch is a prototype and not stable for production use. PRs are not accept [![Documentation](https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat)](https://nvidia.github.io/TensorRT-LLM/) [![python](https://img.shields.io/badge/python-3.12-green)](https://www.python.org/downloads/release/python-3123/) [![python](https://img.shields.io/badge/python-3.10-green)](https://www.python.org/downloads/release/python-31012/) -[![cuda](https://img.shields.io/badge/cuda-13.0.0-green)](https://developer.nvidia.com/cuda-downloads) -[![torch](https://img.shields.io/badge/torch-2.9.0-green)](https://pytorch.org) +[![cuda](https://img.shields.io/badge/cuda-13.1.0-green)](https://developer.nvidia.com/cuda-downloads) +[![torch](https://img.shields.io/badge/torch-2.9.1-green)](https://pytorch.org) [![version](https://img.shields.io/badge/release-1.3.0rc0-green)](https://github.com/NVIDIA/TensorRT-LLM/blob/main/tensorrt_llm/version.py) [![license](https://img.shields.io/badge/license-Apache%202-blue)](https://github.com/NVIDIA/TensorRT-LLM/blob/main/LICENSE) diff --git a/docs/source/installation/linux.md b/docs/source/installation/linux.md index a9704f9cad..c9c9cc5084 100644 --- a/docs/source/installation/linux.md +++ b/docs/source/installation/linux.md @@ -9,15 +9,15 @@ Before the pre-built Python wheel can be installed via `pip`, a few prerequisites must be put into place: - Install CUDA Toolkit 13.0 following the [CUDA Installation Guide for Linux](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/) + Install CUDA Toolkit 13.1 following the [CUDA Installation Guide for Linux](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/) and make sure `CUDA_HOME` environment variable is properly set. - The `cuda-compat-13-0` package may be required depending on your system's NVIDIA GPU + The `cuda-compat-13-1` package may be required depending on your system's NVIDIA GPU driver version. For additional information, refer to the [CUDA Forward Compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/forward-compatibility.html). ```bash # By default, PyTorch CUDA 12.8 package is installed. Install PyTorch CUDA 13.0 package to align with the CUDA version used for building TensorRT LLM wheels. - pip3 install torch==2.9.0 torchvision --index-url https://download.pytorch.org/whl/cu130 + pip3 install torch==2.9.1 torchvision --index-url https://download.pytorch.org/whl/cu130 sudo apt-get -y install libopenmpi-dev @@ -39,6 +39,9 @@ ```bash pip3 install --upgrade pip setuptools && pip3 install tensorrt_llm ``` + + > **Note:** The TensorRT LLM wheel on PyPI is built with PyTorch 2.9.1. This version may be incompatible with the NVIDIA NGC PyTorch 25.12 container, which uses a more recent PyTorch build from the main branch. If you are using this container or a similar environment, please install the pre-built wheel located at `/app/tensorrt_llm` inside the TensorRT LLM NGC Release container instead. + **This project will download and install additional third-party open source software projects. Review the license terms of these open source projects before use.** 2. Sanity check the installation by running the following in Python (tested on Python 3.12): diff --git a/docs/source/legacy/reference/support-matrix.md b/docs/source/legacy/reference/support-matrix.md index c05c689ab4..8cf072d0af 100644 --- a/docs/source/legacy/reference/support-matrix.md +++ b/docs/source/legacy/reference/support-matrix.md @@ -154,9 +154,9 @@ The following table shows the supported software for TensorRT-LLM. * - - Software Compatibility * - Container - - [25.10](https://docs.nvidia.com/deeplearning/frameworks/support-matrix/index.html) + - [25.12](https://docs.nvidia.com/deeplearning/frameworks/support-matrix/index.html) * - TensorRT - - [10.13](https://docs.nvidia.com/deeplearning/tensorrt/release-notes/index.html) + - [10.14](https://docs.nvidia.com/deeplearning/tensorrt/release-notes/index.html) * - Precision - - Blackwell (SM100/SM103/SM120) - FP32, FP16, BF16, FP8, FP4, INT8, INT4 diff --git a/jenkins/Build.groovy b/jenkins/Build.groovy index 35b95d4cac..f36071acb8 100644 --- a/jenkins/Build.groovy +++ b/jenkins/Build.groovy @@ -454,7 +454,7 @@ def runLLMBuild(pipeline, buildFlags, tarName, is_linux_x86_64) def llmPath = sh (script: "realpath ${LLM_ROOT}",returnStdout: true).trim() // TODO: Remove after the cmake version is upgraded to 3.31.8 // Get triton tag from docker/dockerfile.multi - def tritonShortTag = "r25.10" + def tritonShortTag = "r25.12" sh "cd ${LLM_ROOT}/triton_backend/inflight_batcher_llm && mkdir build && cd build && cmake .. -DTRTLLM_DIR=${llmPath} -DTRITON_COMMON_REPO_TAG=${tritonShortTag} -DTRITON_CORE_REPO_TAG=${tritonShortTag} -DTRITON_THIRD_PARTY_REPO_TAG=${tritonShortTag} -DTRITON_BACKEND_REPO_TAG=${tritonShortTag} -DUSE_CXX11_ABI=ON && make -j${buildJobs} install" // Step 3: packaging wheels into tarfile diff --git a/jenkins/L0_Test.groovy b/jenkins/L0_Test.groovy index d915b7f1da..eb251801eb 100644 --- a/jenkins/L0_Test.groovy +++ b/jenkins/L0_Test.groovy @@ -1988,7 +1988,7 @@ def launchTestListCheck(pipeline) def llmPath = sh (script: "realpath .", returnStdout: true).trim() def llmSrc = "${llmPath}/TensorRT-LLM/src" trtllm_utils.llmExecStepWithRetry(pipeline, script: "pip3 install -r ${llmSrc}/requirements-dev.txt") - sh "NVIDIA_TRITON_SERVER_VERSION=25.10 LLM_ROOT=${llmSrc} LLM_BACKEND_ROOT=${llmSrc}/triton_backend python3 ${llmSrc}/scripts/check_test_list.py --l0 --qa --waive" + sh "NVIDIA_TRITON_SERVER_VERSION=25.12 LLM_ROOT=${llmSrc} LLM_BACKEND_ROOT=${llmSrc}/triton_backend python3 ${llmSrc}/scripts/check_test_list.py --l0 --qa --waive" } catch (InterruptedException e) { throw e } catch (Exception e) { @@ -3431,7 +3431,9 @@ def launchTestJobs(pipeline, testFilter) ] aarch64SanityCheckConfigs = [ - /* //Disable PY312-UB2404 temporarily since lack of official PyTorch for CUDA 13.1. + // Workaround PyTorch 2.9.1 vs. 2.10.0a0 incompatibility issue. Once resolved, change back to: + // 1. DLFW_IMAGE -> UBUNTU_24_04_IMAGE + // 2. Extra PyTorch CUDA install: false -> true "PY312-UB2404": [ LLM_DOCKER_IMAGE, "GH200", @@ -3440,7 +3442,7 @@ def launchTestJobs(pipeline, testFilter) "", DLFW_IMAGE, false, // Extra PyTorch CUDA 13.0 install - ],*/ + ], "PY312-DLFW": [ LLM_DOCKER_IMAGE, "GH200",