enable cu130

.github/scripts/filter-matrix.py

@@ -8,7 +8,7 @@
 
 # currently we don't support python 3.13t due to tensorrt does not support 3.13t
 disabled_python_versions: List[str] = ["3.13t", "3.14", "3.14t"]
-disabled_cuda_versions: List[str] = ["cu130"]
+disabled_cuda_versions: List[str] = []
 
 # jetpack 6.2 only officially supports python 3.10 and cu126
 jetpack_python_versions: List[str] = ["3.10"]

.github/scripts/generate-release-matrix.py

@@ -5,8 +5,8 @@
 import sys
 
 RELEASE_CUDA_VERSION = {
-    "wheel": ["cu129"],
-    "tarball": ["cu129"],
+    "wheel": ["cu130"],
+    "tarball": ["cu130"],
 }
 RELEASE_PYTHON_VERSION = {
     "wheel": ["3.10", "3.11", "3.12", "3.13"],
@@ -15,7 +15,7 @@
 sbsa_container_image: str = "quay.io/pypa/manylinux_2_34_aarch64"
 
 CXX11_TARBALL_CONTAINER_IMAGE = {
-    "cu129": "pytorch/libtorch-cxx11-builder:cuda12.9-main",
+    "cu130": "pytorch/libtorch-cxx11-builder:cuda13.0-main",
 }
 
 

.github/scripts/generate-tensorrt-test-matrix.py

@@ -11,18 +11,18 @@
 # channel: nightly if the future tensorRT version test workflow is triggered from the main branch or your personal branch
 # channel: test if the future tensorRT version test workflow is triggered from the release branch(release/2.5 etc....)
 CUDA_VERSIONS_DICT = {
-    "nightly": ["cu129"],
-    "test": ["cu126", "cu128", "cu129"],
-    "release": ["cu126", "cu128", "cu129"],
+    "nightly": ["cu130"],
+    "test": ["cu126", "cu128", "cu130"],
+    "release": ["cu126", "cu128", "cu130"],
 }
 
 # please update the python version you want to test with the future tensorRT version here
 # channel: nightly if the future tensorRT version test workflow is triggered from the main branch or your personal branch
 # channel: test if the future tensorRT version test workflow is triggered from the release branch(release/2.5 etc....)
 PYTHON_VERSIONS_DICT = {
     "nightly": ["3.11"],
-    "test": ["3.9", "3.10", "3.11", "3.12", "3.13"],
-    "release": ["3.9", "3.10", "3.11", "3.12", "3.13"],
+    "test": ["3.10", "3.11", "3.12", "3.13"],
+    "release": ["3.10", "3.11", "3.12", "3.13"],
 }
 
 # please update the future tensorRT version you want to test here

.github/workflows/build_windows.yml

@@ -241,6 +241,7 @@ jobs:
         env:
           ENV_SCRIPT: ${{ inputs.env-script }}
         run: |
+          set -x
           source "${BUILD_ENV_FILE}"
           if [[ -z "${ENV_SCRIPT}" ]]; then
             ${CONDA_RUN} python setup.py clean

.github/workflows/docgen.yml

@@ -14,12 +14,12 @@ jobs:
         if: ${{ ! contains(github.actor, 'pytorchbot') }}
         environment: pytorchbot-env
         container:
-            image: docker.io/pytorch/manylinux2_28-builder:cuda12.9
+            image: docker.io/pytorch/manylinux2_28-builder:cuda13.0
             options: --gpus all
         env:
-            CUDA_HOME: /usr/local/cuda-12.9
-            VERSION_SUFFIX: cu129
-            CU_VERSION: cu129
+            CUDA_HOME: /usr/local/cuda-13.0
+            VERSION_SUFFIX: cu130
+            CU_VERSION: cu130
             CHANNEL: nightly
             CI_BUILD: 1
         steps:
@@ -35,14 +35,14 @@ jobs:
             - name: Install base deps
               run: |
                   python3 -m pip install pip --upgrade
-                  python3 -m pip install pyyaml numpy torch --pre --extra-index-url https://download.pytorch.org/whl/nightly/cu129
+                  python3 -m pip install pyyaml numpy torch --pre --extra-index-url https://download.pytorch.org/whl/nightly/cu130
                   ./packaging/pre_build_script.sh
             - name: Get HEAD SHA
               id: vars
               run: echo "sha=$(git rev-parse --short HEAD)" >> $GITHUB_OUTPUT
             - name: Build Python Package
               run: |
-                  python3 -m pip install --pre . --extra-index-url https://download.pytorch.org/whl/nightly/cu129
+                  python3 -m pip install --pre . --extra-index-url https://download.pytorch.org/whl/nightly/cu130
             - name: Generate New Docs
               run: |
                   cd docsrc

MODULE.bazel

@@ -36,7 +36,7 @@ new_local_repository(
 new_local_repository(
     name = "cuda",
     build_file = "@//third_party/cuda:BUILD",
-    path = "/usr/local/cuda-12.9/",
+    path = "/usr/local/cuda-13.0/",
 )
 
 # for Jetson
@@ -65,7 +65,7 @@ http_archive(
     name = "libtorch",
     build_file = "@//third_party/libtorch:BUILD",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/nightly/cu129/libtorch-shared-with-deps-latest.zip"],
+    urls = ["https://download.pytorch.org/libtorch/nightly/cu130/libtorch-shared-with-deps-latest.zip"],
 )
 
 # in aarch64 platform you can get libtorch via either local or wheel file
@@ -83,7 +83,7 @@ http_archive(
     name = "libtorch_win",
     build_file = "@//third_party/libtorch:BUILD",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/nightly/cu129/libtorch-win-shared-with-deps-latest.zip"],
+    urls = ["https://download.pytorch.org/libtorch/nightly/cu130/libtorch-win-shared-with-deps-latest.zip"],
 )
 
 http_archive(

README.md

@@ -5,9 +5,9 @@ Torch-TensorRT
 <h4> Easily achieve the best inference performance for any PyTorch model on the NVIDIA platform. </h4>
 
 [![Documentation](https://img.shields.io/badge/docs-master-brightgreen)](https://nvidia.github.io/Torch-TensorRT/)
-[![pytorch](https://img.shields.io/badge/PyTorch-2.8-green)](https://download.pytorch.org/whl/nightly/cu128)
-[![cuda](https://img.shields.io/badge/CUDA-12.8-green)](https://developer.nvidia.com/cuda-downloads)
-[![trt](https://img.shields.io/badge/TensorRT-10.13.2.6-green)](https://github.com/nvidia/tensorrt-llm)
+[![pytorch](https://img.shields.io/badge/PyTorch-2.9-green)](https://download.pytorch.org/whl/nightly/cu130)
+[![cuda](https://img.shields.io/badge/CUDA-13.0-green)](https://developer.nvidia.com/cuda-downloads)
+[![trt](https://img.shields.io/badge/TensorRT-10.12.0-green)](https://github.com/nvidia/tensorrt)
 [![license](https://img.shields.io/badge/license-BSD--3--Clause-blue)](./LICENSE)
 [![Linux x86-64 Nightly Wheels](https://github.com/pytorch/TensorRT/actions/workflows/build-test-linux-x86_64.yml/badge.svg?branch=nightly)](https://github.com/pytorch/TensorRT/actions/workflows/build-test-linux-x86_64.yml)
 [![Linux SBSA Nightly Wheels](https://github.com/pytorch/TensorRT/actions/workflows/build-test-linux-aarch64.yml/badge.svg?branch=nightly)](https://github.com/pytorch/TensorRT/actions/workflows/build-test-linux-aarch64.yml)
@@ -27,7 +27,7 @@ pip install torch-tensorrt
 
 Nightly versions of Torch-TensorRT are published on the PyTorch package index
 ```bash
-pip install --pre torch-tensorrt --index-url https://download.pytorch.org/whl/nightly/cu128
+pip install --pre torch-tensorrt --index-url https://download.pytorch.org/whl/nightly/cu130
 ```
 
 Torch-TensorRT is also distributed in the ready-to-run [NVIDIA NGC PyTorch Container](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch) which has all dependencies with the proper versions and example notebooks included.

docker/Dockerfile

@@ -2,9 +2,9 @@
 
 # Base image starts with CUDA
 #TODO: cuda version
-ARG BASE_IMG=nvidia/cuda:12.9.0-devel-ubuntu22.04
+ARG BASE_IMG=nvidia/cuda:13.0.0-devel-ubuntu22.04
 FROM ${BASE_IMG} as base
-ENV BASE_IMG=nvidia/cuda:12.9.0-devel-ubuntu22.04
+ENV BASE_IMG=nvidia/cuda:13.0.0-devel-ubuntu22.04
 
 ARG TENSORRT_VERSION
 ENV TENSORRT_VERSION=${TENSORRT_VERSION}

docker/dist-build.sh

@@ -4,7 +4,7 @@ set -x
 
 TOP_DIR=$(cd $(dirname $0); pwd)/..
 
-BUILD_CMD="python -m pip wheel .  --extra-index-url https://download.pytorch.org/whl/nightly/cu129 -w dist"
+BUILD_CMD="python -m pip wheel .  --extra-index-url https://download.pytorch.org/whl/nightly/cu130 -w dist"
 
 # TensorRT restricts our pip version
 cd ${TOP_DIR} \

docsrc/getting_started/installation.rst

@@ -46,7 +46,7 @@ Torch-TensorRT distributed nightlies targeting the PyTorch nightly. These can be
 
 .. code-block:: sh
 
-    python -m pip install --pre torch torch-tensorrt tensorrt --extra-index-url https://download.pytorch.org/whl/nightly/cu128
+    python -m pip install --pre torch torch-tensorrt tensorrt --extra-index-url https://download.pytorch.org/whl/nightly/cu130
 
 
 
@@ -131,7 +131,7 @@ Once the WORKSPACE has been configured properly, all that is required to build t
 
     .. code-block:: sh
 
-        python -m pip install --pre . --extra-index-url https://download.pytorch.org/whl/nightly/cu128
+        python -m pip install --pre . --extra-index-url https://download.pytorch.org/whl/nightly/cu130
 
 
 If you use the ``uv`` (`https://docs.astral.sh/uv/ <https://docs.astral.sh/uv/>`_) tool to manage python and your projects, the command is slightly simpler
@@ -146,7 +146,7 @@ To build the wheel file
 
     .. code-block:: sh
 
-        python -m pip wheel --no-deps --pre . --extra-index-url https://download.pytorch.org/whl/nightly/cu128 -w dist
+        python -m pip wheel --no-deps --pre . --extra-index-url https://download.pytorch.org/whl/nightly/cu130 -w dist
 
 Additional Build Options
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -164,7 +164,7 @@ which has implications for features like serialization.
 
 .. code-block:: sh
 
-    PYTHON_ONLY=1 python -m pip install --pre . --extra-index-url https://download.pytorch.org/whl/nightly/cu128
+    PYTHON_ONLY=1 python -m pip install --pre . --extra-index-url https://download.pytorch.org/whl/nightly/cu130
 
 
 No TorchScript Frontend
@@ -175,7 +175,7 @@ of C++ code that is no longer necessary for most users. Therefore you can exclud
 
 .. code-block:: sh
 
-    NO_TORCHSCRIPT=1 python -m pip install --pre . --extra-index-url https://download.pytorch.org/whl/nightly/cu128
+    NO_TORCHSCRIPT=1 python -m pip install --pre . --extra-index-url https://download.pytorch.org/whl/nightly/cu130
 
 
 Building the C++ Library Standalone (TorchScript Only)
@@ -245,7 +245,7 @@ Build steps
 
 * Open the app "x64 Native Tools Command Prompt for VS 2022" - note that Admin privileges may be necessary
 * Ensure Bazelisk (Bazel launcher) is installed on your machine and available from the command line. Package installers such as Chocolatey can be used to install Bazelisk
-* Install latest version of Torch (i.e. with ``pip install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu128``)
+* Install latest version of Torch (i.e. with ``pip install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu130``)
 * Clone the Torch-TensorRT repository and navigate to its root directory
 * Run ``pip install ninja wheel setuptools``
 * Run ``pip install --pre -r py/requirements.txt``

py/requirements.txt

@@ -1,8 +1,9 @@
 numpy
 packaging
 pybind11==2.6.2
---extra-index-url https://download.pytorch.org/whl/nightly/cu129
+--extra-index-url https://download.pytorch.org/whl/nightly/cu130
 torch>=2.9.0.dev,<2.10.0
 --extra-index-url https://pypi.ngc.nvidia.com
 pyyaml
-dllist
+dllist
+setuptools

pyproject.toml

@@ -100,14 +100,19 @@ index-strategy = "unsafe-best-match"
 
 [tool.uv.sources]
 torch = [
-    { index = "pytorch-nightly-cu129", marker = "platform_machine != 'aarch64' or (platform_machine == 'aarch64' and 'tegra' not in platform_release)" },
+    { index = "pytorch-nightly-cu130", marker = "platform_machine != 'aarch64' or (platform_machine == 'aarch64' and 'tegra' not in platform_release)" },
     { index = "jetson-containers", marker = "platform_machine == 'aarch64' and 'tegra' in platform_release" },
 ]
 torchvision = [
-    { index = "pytorch-nightly-cu129", marker = "platform_machine != 'aarch64' or (platform_machine == 'aarch64' and 'tegra' not in platform_release)" },
+    { index = "pytorch-nightly-cu130", marker = "platform_machine != 'aarch64' or (platform_machine == 'aarch64' and 'tegra' not in platform_release)" },
     { index = "jetson-containers", marker = "platform_machine == 'aarch64' and 'tegra' in platform_release" },
 ]
 
+[[tool.uv.index]]
+name = "pytorch-nightly-cu130"
+url = "https://download.pytorch.org/whl/nightly/cu130"
+explicit = false
+
 [[tool.uv.index]]
 name = "pytorch-nightly-cu129"
 url = "https://download.pytorch.org/whl/nightly/cu129"

tests/py/requirements.txt

@@ -3,6 +3,7 @@
 expecttest==0.1.6
 networkx==2.8.8
 numpy
+setuptools
 parameterized>=0.2.0
 pytest>=8.2.1
 pytest-xdist>=3.6.1
@@ -13,6 +14,6 @@ nvidia-modelopt[all]; python_version >'3.9' and python_version <'3.13'
 # flashinfer-python is not supported for python version 3.13 or higher
 # flashinfer-python is broken on python 3.9 at the moment, so skip it for now
 flashinfer-python; python_version >'3.9' and python_version <'3.13'
---extra-index-url https://download.pytorch.org/whl/nightly/cu129
+--extra-index-url https://download.pytorch.org/whl/nightly/cu130
 torchvision>=0.24.0.dev,<0.25.0
 timm>=1.0.3

tools/perf/Flux/create_env.sh

@@ -14,10 +14,10 @@ apt install bazel
 bazel
 cd /home/TensorRT
 
-python -m pip install --pre -e . --extra-index-url https://download.pytorch.org/whl/nightly/cu128
-pip install tensorrt==10.9.0.34 --force-reinstall
+python -m pip install --pre -e . --extra-index-url https://download.pytorch.org/whl/nightly/cu130
+pip install tensorrt==10.13.2.6 --force-reinstall
 
-pip3 install --pre  torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128
+pip3 install --pre  torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu130
 
 
 pip install sentencepiece=="0.2.0" transformers=="4.48.2" accelerate=="1.3.0" diffusers=="0.32.2" protobuf=="5.29.3"