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chore: cherrypick of #2855 (#3027)
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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-10.0.1-green)](https://github.com/nvidia/tensorrt-llm)
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[![trt](https://img.shields.io/badge/TensorRT-10.1.0-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 10.0.1.6
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- TensorRT 10.1.0.27
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## Deprecation Policy
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‎WORKSPACE

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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 = "a5cd2863793d69187ce4c73b2fffc1f470ff28cfd91e3640017e53b8916453d5",
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strip_prefix = "TensorRT-10.0.1.6",
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sha256 = "606436ed219c72d1a25a889b2b0ae5cb5a68499dd6f944da4cabb3c34c067d55",
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strip_prefix = "TensorRT-10.1.0.27",
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urls = [
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.1/tars/TensorRT-10.0.1.6.Linux.x86_64-gnu.cuda-12.4.tar.gz",
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.1.0/tars/TensorRT-10.1.0.27.Linux.x86_64-gnu.cuda-12.4.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 = "d667bd10b178e239b621a8929008ef3e27967d181bf07a39845a0f99edeec47a",
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strip_prefix = "TensorRT-10.0.1.6",
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sha256 = "2eb98008944945377eb328871a308704e95bf3bb295fc548784c6da41a70bbed",
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strip_prefix = "TensorRT-10.1.0.27",
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urls = [
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.1/zip/TensorRT-10.0.1.6.Windows10.win10.cuda-12.4.zip",
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.1.0/zip/TensorRT-10.1.0.27.Windows.win10.cuda-12.4.zip",
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],
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)
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‎dev_dep_versions.yml

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__version__: "2.5.0.dev0"
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__cuda_version__: "12.4"
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__tensorrt_version__: "10.0.1"
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__tensorrt_version__: "10.1.0"

‎docker/README.md

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### Instructions
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- The example below uses TensorRT 10.0.1.6
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- The example below uses TensorRT 10.1.0.27
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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=10.0.1 -f docker/Dockerfile -t torch_tensorrt:latest .
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DOCKER_BUILDKIT=1 docker build --build-arg TENSORRT_VERSION=10.1.0 -f docker/Dockerfile -t torch_tensorrt:latest .
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```
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Run:

‎examples/dynamo/requirements.txt

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cupy==13.1.0
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tensorrt==10.0.1
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tensorrt==10.1.0
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torch>=2.4.0.dev20240503+cu121
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torch-tensorrt>=2.4.0.dev20240503+cu121
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triton==2.3.0

‎packaging/pre_build_script_windows.sh

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choco install bazelisk -y
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curl -Lo TensorRT.zip https://developer.download.nvidia.com/compute/machine-learning/tensorrt/10.0.1/zip/TensorRT-10.0.1.6.Windows10.win10.cuda-12.4.zip
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curl -Lo TensorRT.zip https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.1.0/zip/TensorRT-10.1.0.27.Windows.win10.cuda-12.4.zip
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unzip -o TensorRT.zip -d C:/
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export CUDA_HOME="$(echo ${CUDA_PATH} | sed -e 's#\\#\/#g')"

‎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-10.0.0.6/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-10.1.0.27/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/10.0.1/tars/TensorRT-10.0.1.6.Linux.x86_64-gnu.cuda-12.4.tar.gz \
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&& gunzip TensorRT-10.0.1.6.Linux.x86_64-gnu.cuda-12.4.tar.gz \
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&& tar -xvf TensorRT-10.0.1.6.Linux.x86_64-gnu.cuda-12.4.tar \
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&& rm TensorRT-10.0.1.6.Linux.x86_64-gnu.cuda-12.4.tar
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RUN wget -q https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.1.0/tars/TensorRT-10.1.0.27.Linux.x86_64-gnu.cuda-12.4.tar.gz \
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&& gunzip TensorRT-10.1.0.27.Linux.x86_64-gnu.cuda-12.4.tar.gz \
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&& tar -xvf TensorRT-10.1.0.27.Linux.x86_64-gnu.cuda-12.4.tar \
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&& rm TensorRT-10.1.0.27.Linux.x86_64-gnu.cuda-12.4.tar
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ENV TENSORRT_DIR=/TensorRT-10.0.1.6
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ENV TENSORRT_VERSION=10.0.1
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ENV TENSORRT_DIR=/TensorRT-10.1.0.27
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ENV TENSORRT_VERSION=10.1.0
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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 \

‎py/requirements.txt

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torchvision>=0.19.0,<0.20.0
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--extra-index-url https://pypi.ngc.nvidia.com
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pyyaml
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tensorrt==10.0.1
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tensorrt==10.1.0

‎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==10.0.1",
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"tensorrt==10.1.0",
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"torch>=2.4.0,<2.5.0",
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"pybind11==2.6.2",
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"numpy",
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keywords = ["pytorch", "torch", "tensorrt", "trt", "ai", "artificial intelligence", "ml", "machine learning", "dl", "deep learning", "compiler", "dynamo", "torchscript", "inference"]
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dependencies = [
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"torch>=2.4.0,<2.5.0",
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"tensorrt==10.0.1",
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"tensorrt-cu12_bindings==10.0.1",
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"tensorrt-cu12_libs==10.0.1",
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"tensorrt==10.1.0",
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"tensorrt-cu12_bindings==10.1.0",
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"tensorrt-cu12_libs==10.1.0",
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"packaging>=23",
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"numpy",
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"typing-extensions>=4.7.0",

‎tests/py/requirements.txt

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pytest>=8.2.1
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pytest-xdist>=3.6.1
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pyyaml
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tensorrt==10.0.1
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tensorrt==10.1.0
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timm>=1.0.3
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transformers==4.40.2
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--extra-index-url https://pypi.nvidia.com

‎toolchains/ci_workspaces/WORKSPACE.win.release.tmpl

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new_local_repository(
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path = "C:/TensorRT-10.0.1.6",
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path = "C:/TensorRT-10.1.0.27",
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build_file = "@//third_party/tensorrt/local:BUILD"
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)
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‎toolchains/ci_workspaces/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 = "a5cd2863793d69187ce4c73b2fffc1f470ff28cfd91e3640017e53b8916453d5",
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strip_prefix = "TensorRT-10.0.1.6",
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sha256 = "606436ed219c72d1a25a889b2b0ae5cb5a68499dd6f944da4cabb3c34c067d55",
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strip_prefix = "TensorRT-10.1.0.27",
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urls = [
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.1/tars/TensorRT-10.0.1.6.Linux.x86_64-gnu.cuda-12.4.tar.gz",
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"https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.1.0/tars/TensorRT-10.1.0.27.Linux.x86_64-gnu.cuda-12.4.tar.gz",
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],
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)
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