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

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"10.7.0": {
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"urls": "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.7.0/tars/TensorRT-10.7.0.23.Linux.x86_64-gnu.cuda-12.6.tar.gz",
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"strip_prefix": "TensorRT-10.7.0.23",
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"sha256": "27d0f7e9af657b9fa19bfe9d62376d4de64182ed6274bde04bf143f56d308ec9",
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"sha256": "d7f16520457caaf97ad8a7e94d802f89d77aedf9f361a255f2c216e2a3a40a11",
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},
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},
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}

MODULE.bazel

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@@ -79,20 +79,20 @@ http_archive(
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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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sha256 = "adff1cd5abe5d87013806172351e58fd024e5bf0fc61d49ef4b84cd38ed99081",
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strip_prefix = "TensorRT-10.3.0.26",
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sha256 = "d7f16520457caaf97ad8a7e94d802f89d77aedf9f361a255f2c216e2a3a40a11",
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strip_prefix = "TensorRT-10.7.0.23",
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urls = [
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.3.0/tars/TensorRT-10.3.0.26.Linux.x86_64-gnu.cuda-12.5.tar.gz",
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.7.0/tars/TensorRT-10.7.0.23.Linux.x86_64-gnu.cuda-12.6.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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sha256 = "2bb4bcb79e8c33575816d874b0512ea28c302af1c06ee6d224da71aa182f75e0",
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strip_prefix = "TensorRT-10.3.0.26",
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sha256 = "fbdef004578e7ccd5ee51fe7f846b57422364a743372fd8f9f1d7dbd33f62879",
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strip_prefix = "TensorRT-10.7.0.23",
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urls = [
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.3.0/zip/TensorRT-10.3.0.26.Windows.win10.cuda-12.5.zip",
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.7.0/zip/TensorRT-10.7.0.23.Windows.win10.cuda-12.6.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-10.3.0-green)](https://github.com/nvidia/tensorrt-llm)
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[![trt](https://img.shields.io/badge/TensorRT-10.7.0-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 2.5.0.dev (latest nightly) (built with CUDA 12.4)
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- CUDA 12.4
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- TensorRT 10.3.0.26
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- TensorRT 10.7.0.23
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## Deprecation Policy
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dev_dep_versions.yml

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__cuda_version__: "12.4"
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__tensorrt_version__: "10.3.0"
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__tensorrt_version__: "10.7.0"

packaging/pre_build_script_windows.sh

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@@ -23,7 +23,7 @@ if [[ "${CU_VERSION::4}" < "cu12" ]]; then
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pyproject.toml
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fi
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#curl -Lo TensorRT.zip https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.3.0/zip/TensorRT-10.3.0.26.Windows.win10.cuda-12.5.zip
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#curl -Lo TensorRT.zip https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.7.0/zip/TensorRT-10.7.0.23.Windows.win10.cuda-12.6.zip
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#unzip -o TensorRT.zip -d C:/
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TORCH_TORCHVISION=$(grep "^torch" py/requirements.txt)
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INDEX_URL=https://download.pytorch.org/whl/${CHANNEL}/${CU_VERSION}

packaging/smoke_test_script.sh

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# The issue was smoke test installs the built torch_tensorrt wheel file and checks `import torch_tensorrt; print(torch_tensorrt.__version__)`
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# Since tensorrt cannot be pip installable in CI, the smoke test will fail.
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# One way we tried to handle it is manually install tensorrt wheel while by extracting from the tarball.
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# However, the TensorRT-10.3.0.26/lib path doesn't seem to show up in LD_LIBRARY_PATH even if we explicitly set it.
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# However, the TensorRT-10.7.0.23/lib path doesn't seem to show up in LD_LIBRARY_PATH even if we explicitly set it.
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# TODO: Implement a custom smoke_test script to verify torch_tensorrt installation.

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/10.3.0/tars/TensorRT-10.3.0.26.Linux.x86_64-gnu.cuda-12.5.tar.gz \
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&& gunzip TensorRT-10.3.0.26.Linux.x86_64-gnu.cuda-12.5.tar.gz \
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&& tar -xvf TensorRT-10.3.0.26.Linux.x86_64-gnu.cuda-12.5.tar \
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&& rm TensorRT-10.3.0.26.Linux.x86_64-gnu.cuda-12.5.tar
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RUN wget -q https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.7.0/tars/TensorRT-10.7.0.23.Linux.x86_64-gnu.cuda-12.6.tar.gz \
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&& gunzip TensorRT-10.7.0.23.Linux.x86_64-gnu.cuda-12.6.tar.gz \
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&& tar -xvf TensorRT-10.7.0.23.Linux.x86_64-gnu.cuda-12.6.tar \
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&& rm TensorRT-10.7.0.23.Linux.x86_64-gnu.cuda-12.6.tar
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ENV TENSORRT_DIR=/TensorRT-10.3.0.26
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ENV TENSORRT_VERSION=10.3.0
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ENV TENSORRT_DIR=/TensorRT-10.7.0.23
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ENV TENSORRT_VERSION=10.7.0
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ENV USE_CXX11_ABI=1
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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==10.3.0",
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"tensorrt-cu12==10.7.0",
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"torch>=2.6.0.dev,<2.7.0",
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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>=2.6.0.dev,<2.7.0",
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"tensorrt-cu12==10.3.0",
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"tensorrt-cu12-bindings==10.3.0",
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"tensorrt-cu12-libs==10.3.0",
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"tensorrt-cu12==10.7.0",
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"tensorrt-cu12-bindings==10.7.0",
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"tensorrt-cu12-libs==10.7.0",
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"packaging>=23",
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"numpy",
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"typing-extensions>=4.7.0",

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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sha256 = "adff1cd5abe5d87013806172351e58fd024e5bf0fc61d49ef4b84cd38ed99081",
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strip_prefix = "TensorRT-10.3.0.26",
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sha256 = "d7f16520457caaf97ad8a7e94d802f89d77aedf9f361a255f2c216e2a3a40a11",
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strip_prefix = "TensorRT-10.7.0.23",
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urls = [
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.3.0/tars/TensorRT-10.3.0.26.Linux.x86_64-gnu.cuda-12.5.tar.gz",
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.7.0/tars/TensorRT-10.7.0.23.Linux.x86_64-gnu.cuda-12.6.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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sha256 = "2bb4bcb79e8c33575816d874b0512ea28c302af1c06ee6d224da71aa182f75e0",
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strip_prefix = "TensorRT-10.3.0.26",
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sha256 = "fbdef004578e7ccd5ee51fe7f846b57422364a743372fd8f9f1d7dbd33f62879",
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strip_prefix = "TensorRT-10.7.0.23",
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urls = [
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.3.0/zip/TensorRT-10.3.0.26.Windows.win10.cuda-12.5.zip",
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.7.0/zip/TensorRT-10.7.0.23.Windows.win10.cuda-12.6.zip",
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],
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)
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toolchains/legacy/WORKSPACE.win.release.tmpl

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new_local_repository(
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name = "tensorrt_win",
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path = "C:/TensorRT-10.3.0.26",
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path = "C:/TensorRT-10.7.0.23",
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build_file = "@//third_party/tensorrt/local:BUILD"
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)
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toolchains/legacy/WORKSPACE.x86_64.release.rhel.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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sha256 = "adff1cd5abe5d87013806172351e58fd024e5bf0fc61d49ef4b84cd38ed99081",
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strip_prefix = "TensorRT-10.3.0.26",
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sha256 = "d7f16520457caaf97ad8a7e94d802f89d77aedf9f361a255f2c216e2a3a40a11",
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strip_prefix = "TensorRT-10.7.0.23",
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urls = [
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.3.0/tars/TensorRT-10.3.0.26.Linux.x86_64-gnu.cuda-12.5.tar.gz",
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.7.0/tars/TensorRT-10.7.0.23.Linux.x86_64-gnu.cuda-12.6.tar.gz",
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],
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)
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