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chore: bump to TRT 10.9 (#3436)
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.github/scripts/generate-tensorrt-test-matrix.py

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@@ -40,6 +40,10 @@
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"urls": "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.8.0/zip/TensorRT-10.8.0.43.Windows.win10.cuda-12.8.zip",
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"strip_prefix": "TensorRT-10.8.0.43",
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},
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"10.9.0": {
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"urls": "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.9.0/zip/TensorRT-10.9.0.34.Windows.win10.cuda-12.8.zip",
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"strip_prefix": "TensorRT-10.9.0.34",
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},
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},
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"linux": {
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"10.6.0": {
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"urls": "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.8.0/tars/TensorRT-10.8.0.43.Linux.x86_64-gnu.cuda-12.8.tar.gz",
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"strip_prefix": "TensorRT-10.8.0.43",
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},
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"10.9.0": {
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"urls": "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.9.0/tars/TensorRT-10.9.0.34.Linux.x86_64-gnu.cuda-12.8.tar.gz",
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"strip_prefix": "TensorRT-10.9.0.34",
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},
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},
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}
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MODULE.bazel

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@@ -1,6 +1,6 @@
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module(
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name = "torch_tensorrt",
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version = "2.5.0a0",
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version = "2.7.0a0",
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repo_name = "org_pytorch_tensorrt",
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)
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http_archive(
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name = "tensorrt",
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build_file = "@//third_party/tensorrt/archive:BUILD",
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strip_prefix = "TensorRT-10.8.0.43",
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strip_prefix = "TensorRT-10.9.0.34",
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urls = [
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.8.0/tars/TensorRT-10.8.0.43.Linux.x86_64-gnu.cuda-12.8.tar.gz",
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.9.0/tars/TensorRT-10.9.0.34.Linux.x86_64-gnu.cuda-12.8.tar.gz",
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],
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)
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http_archive(
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name = "tensorrt_win",
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build_file = "@//third_party/tensorrt/archive:BUILD",
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strip_prefix = "TensorRT-10.8.0.43",
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strip_prefix = "TensorRT-10.9.0.34",
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urls = [
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.8.0/zip/TensorRT-10.8.0.43.Windows.win10.cuda-12.8.zip",
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.9.0/zip/TensorRT-10.9.0.34.Windows.win10.cuda-12.8.zip",
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],
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)
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README.md

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@@ -7,7 +7,7 @@ Torch-TensorRT
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[![Documentation](https://img.shields.io/badge/docs-master-brightgreen)](https://nvidia.github.io/Torch-TensorRT/)
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[![pytorch](https://img.shields.io/badge/PyTorch-2.4-green)](https://www.python.org/downloads/release/python-31013/)
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[![cuda](https://img.shields.io/badge/CUDA-12.4-green)](https://developer.nvidia.com/cuda-downloads)
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[![trt](https://img.shields.io/badge/TensorRT-10.8.0-green)](https://github.com/nvidia/tensorrt-llm)
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[![trt](https://img.shields.io/badge/TensorRT-10.9.0-green)](https://github.com/nvidia/tensorrt-llm)
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[![license](https://img.shields.io/badge/license-BSD--3--Clause-blue)](./LICENSE)
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[![linux_tests](https://github.com/pytorch/TensorRT/actions/workflows/build-test-linux.yml/badge.svg)](https://github.com/pytorch/TensorRT/actions/workflows/build-test-linux.yml)
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[![windows_tests](https://github.com/pytorch/TensorRT/actions/workflows/build-test-windows.yml/badge.svg)](https://github.com/pytorch/TensorRT/actions/workflows/build-test-windows.yml)
@@ -119,7 +119,7 @@ These are the following dependencies used to verify the testcases. Torch-TensorR
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- Bazel 6.3.2
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- Libtorch 2.7.0.dev (latest nightly) (built with CUDA 12.8)
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- CUDA 12.8
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- TensorRT 10.8.0.43
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- TensorRT 10.9.0.43
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## Deprecation Policy
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dev_dep_versions.yml

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__cuda_version__: "12.8"
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__tensorrt_version__: "10.8.0"
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__tensorrt_version__: "10.9.0"

docker/README.md

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@@ -17,14 +17,14 @@ Note: By default the container uses the `cxx11-abi` version of Torch + Torch-TRT
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### Instructions
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- The example below uses TensorRT 10.8.0.43
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- The example below uses TensorRT 10.9.0.34
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- See <a href="https://github.com/pytorch/TensorRT#dependencies">dependencies</a> for a list of current default dependencies.
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> From root of Torch-TensorRT repo
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Build:
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```
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DOCKER_BUILDKIT=1 docker build --build-arg TENSORRT_VERSION=10.8.0 -f docker/Dockerfile -t torch_tensorrt:latest .
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DOCKER_BUILDKIT=1 docker build --build-arg TENSORRT_VERSION=10.9.0 -f docker/Dockerfile -t torch_tensorrt:latest .
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```
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Run:

py/ci/Dockerfile.ci

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RUN yum install -y ninja-build
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# download TensorRT tarball
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RUN wget -q https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.8.0/tars/TensorRT-10.8.0.43.Linux.x86_64-gnu.cuda-12.8.tar.gz \
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&& gunzip TensorRT-10.8.0.43.Linux.x86_64-gnu.cuda-12.8.tar.gz \
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&& tar -xvf TensorRT-10.8.0.43.Linux.x86_64-gnu.cuda-12.8.tar \
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&& rm TensorRT-10.8.0.43.Linux.x86_64-gnu.cuda-12.8.tar
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RUN wget -q https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.9.0/tars/TensorRT-10.9.0.34.Linux.x86_64-gnu.cuda-12.8.tar.gz \
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&& gunzip TensorRT-10.9.0.34.Linux.x86_64-gnu.cuda-12.8.tar.gz \
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&& tar -xvf TensorRT-10.9.0.34.Linux.x86_64-gnu.cuda-12.8.tar \
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&& rm TensorRT-10.9.0.34.Linux.x86_64-gnu.cuda-12.8.tar
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ENV TENSORRT_DIR=/TensorRT-10.8.0.43
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ENV TENSORRT_VERSION=10.8.0
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ENV TENSORRT_DIR=/TensorRT-10.9.0.34
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ENV TENSORRT_VERSION=10.9.0
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RUN wget https://github.com/bazelbuild/bazelisk/releases/download/v1.17.0/bazelisk-linux-amd64 \
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&& mv bazelisk-linux-amd64 /usr/bin/bazel \

pyproject.toml

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"cffi>=1.15.1",
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"typing-extensions>=4.7.0",
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"future>=0.18.3",
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"tensorrt-cu12>=10.8.0,<10.9.0",
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"tensorrt-cu12>=10.9.0,<10.10.0",
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"torch>=2.7.0.dev,<2.8.0",
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"pybind11==2.6.2",
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"numpy",
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]
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dependencies = [
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"torch>=2.7.0.dev,<2.8.0",
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"tensorrt>=10.8.0,<10.9.0",
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"tensorrt-cu12>=10.8.0,<10.9.0",
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"tensorrt-cu12-bindings>=10.8.0,<10.9.0",
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"tensorrt-cu12-libs>=10.8.0,<10.9.0",
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"tensorrt>=10.9.0,<10.10.0",
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"tensorrt-cu12>=10.9.0,<10.10.0",
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"tensorrt-cu12-bindings>=10.9.0,<10.10.0",
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"tensorrt-cu12-libs>=10.9.0,<10.10.0",
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"packaging>=23",
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"numpy",
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"typing-extensions>=4.7.0",
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url = "https://download.pytorch.org/whl/nightly/cu126"
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explicit = false
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[[tool.uv.index]]
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name = "nvidia"
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url = "https://pypi.nvidia.com"
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explicit = false
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# [[tool.uv.index]]
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# name = "pytorch-nightly-cu124"
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# url = "https://download.pytorch.org/whl/nightly/cu124"

toolchains/ci_workspaces/MODULE.bazel.tmpl

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http_archive(
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name = "tensorrt",
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build_file = "@//third_party/tensorrt/archive:BUILD",
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strip_prefix = "TensorRT-10.8.0.43",
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strip_prefix = "TensorRT-10.9.0.34",
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urls = [
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.8.0/tars/TensorRT-10.8.0.43.Linux.x86_64-gnu.cuda-12.8.tar.gz",
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.9.0/tars/TensorRT-10.9.0.34.Linux.x86_64-gnu.cuda-12.8.tar.gz",
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],
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)
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http_archive(
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name = "tensorrt_win",
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build_file = "@//third_party/tensorrt/archive:BUILD",
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strip_prefix = "TensorRT-10.8.0.43",
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strip_prefix = "TensorRT-10.9.0.34",
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urls = [
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.8.0/zip/TensorRT-10.8.0.43.Windows.win10.cuda-12.8.zip",
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.9.0/zip/TensorRT-10.9.0.34.Windows.win10.cuda-12.8.zip",
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],
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)
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uv.lock

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