chore: cherrypick of #2855 (#3027)

Author: zewenli98

README.md

@@ -7,7 +7,7 @@ Torch-TensorRT
 [![Documentation](https://img.shields.io/badge/docs-master-brightgreen)](https://nvidia.github.io/Torch-TensorRT/)
 [![pytorch](https://img.shields.io/badge/PyTorch-2.4-green)](https://www.python.org/downloads/release/python-31013/)
 [![cuda](https://img.shields.io/badge/CUDA-12.4-green)](https://developer.nvidia.com/cuda-downloads)
-[![trt](https://img.shields.io/badge/TensorRT-10.0.1-green)](https://github.com/nvidia/tensorrt-llm)
+[![trt](https://img.shields.io/badge/TensorRT-10.1.0-green)](https://github.com/nvidia/tensorrt-llm)
 [![license](https://img.shields.io/badge/license-BSD--3--Clause-blue)](./LICENSE)
 [![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)
 [![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
 - Bazel 6.3.2
 - Libtorch 2.5.0.dev (latest nightly) (built with CUDA 12.4)
 - CUDA 12.4
-- TensorRT 10.0.1.6
+- TensorRT 10.1.0.27
 
 ## Deprecation Policy
 

WORKSPACE

@@ -84,20 +84,20 @@ http_archive(
 http_archive(
     name = "tensorrt",
     build_file = "@//third_party/tensorrt/archive:BUILD",
-    sha256 = "a5cd2863793d69187ce4c73b2fffc1f470ff28cfd91e3640017e53b8916453d5",
-    strip_prefix = "TensorRT-10.0.1.6",
+    sha256 = "606436ed219c72d1a25a889b2b0ae5cb5a68499dd6f944da4cabb3c34c067d55",
+    strip_prefix = "TensorRT-10.1.0.27",
     urls = [
-        "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",
+        "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",
     ],
 )
 
 http_archive(
     name = "tensorrt_win",
     build_file = "@//third_party/tensorrt/archive:BUILD",
-    sha256 = "d667bd10b178e239b621a8929008ef3e27967d181bf07a39845a0f99edeec47a",
-    strip_prefix = "TensorRT-10.0.1.6",
+    sha256 = "2eb98008944945377eb328871a308704e95bf3bb295fc548784c6da41a70bbed",
+    strip_prefix = "TensorRT-10.1.0.27",
     urls = [
-        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.1/zip/TensorRT-10.0.1.6.Windows10.win10.cuda-12.4.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",
     ],
 )
 

dev_dep_versions.yml

@@ -1,3 +1,3 @@
 __version__: "2.5.0.dev0"
 __cuda_version__: "12.4"
-__tensorrt_version__: "10.0.1"
+__tensorrt_version__: "10.1.0"

docker/README.md

@@ -17,14 +17,14 @@ Note: By default the container uses the `pre-cxx11-abi` version of Torch + Torch
 
 ### Instructions
 
-- The example below uses TensorRT 10.0.1.6
+- The example below uses TensorRT 10.1.0.27
 - See <a href="https://github.com/pytorch/TensorRT#dependencies">dependencies</a> for a list of current default dependencies.
 
 > From root of Torch-TensorRT repo
 
 Build:
 ```
-DOCKER_BUILDKIT=1 docker build --build-arg TENSORRT_VERSION=10.0.1 -f docker/Dockerfile -t torch_tensorrt:latest .
+DOCKER_BUILDKIT=1 docker build --build-arg TENSORRT_VERSION=10.1.0 -f docker/Dockerfile -t torch_tensorrt:latest .
 ```
 
 Run:

examples/dynamo/requirements.txt

@@ -1,5 +1,5 @@
 cupy==13.1.0
-tensorrt==10.0.1
+tensorrt==10.1.0
 torch>=2.4.0.dev20240503+cu121
 torch-tensorrt>=2.4.0.dev20240503+cu121
 triton==2.3.0

packaging/pre_build_script_windows.sh

@@ -8,7 +8,7 @@ pip install tensorrt==${TRT_VERSION} tensorrt-${CU_VERSION::4}-bindings==${TRT_V
 
 choco install bazelisk -y
 
-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
+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
 unzip -o TensorRT.zip -d C:/
 
 export CUDA_HOME="$(echo ${CUDA_PATH} | sed -e 's#\\#\/#g')"

packaging/smoke_test_script.sh

@@ -2,5 +2,5 @@
 # The issue was smoke test installs the built torch_tensorrt wheel file and checks `import torch_tensorrt; print(torch_tensorrt.__version__)`
 # Since tensorrt cannot be pip installable in CI, the smoke test will fail.
 # One way we tried to handle it is manually install tensorrt wheel while by extracting from the tarball.
-# 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.
+# 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.
 # TODO: Implement a custom smoke_test script to verify torch_tensorrt installation.

py/ci/Dockerfile.ci

@@ -3,13 +3,13 @@ FROM pytorch/manylinux-builder:cuda12.4
 RUN yum install -y ninja-build
 
 # download TensorRT tarball
-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 \
-&& gunzip TensorRT-10.0.1.6.Linux.x86_64-gnu.cuda-12.4.tar.gz \
-&& tar -xvf TensorRT-10.0.1.6.Linux.x86_64-gnu.cuda-12.4.tar \
-&& rm TensorRT-10.0.1.6.Linux.x86_64-gnu.cuda-12.4.tar
+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 \
+&& gunzip TensorRT-10.1.0.27.Linux.x86_64-gnu.cuda-12.4.tar.gz \
+&& tar -xvf TensorRT-10.1.0.27.Linux.x86_64-gnu.cuda-12.4.tar \
+&& rm TensorRT-10.1.0.27.Linux.x86_64-gnu.cuda-12.4.tar
 
-ENV TENSORRT_DIR=/TensorRT-10.0.1.6
-ENV TENSORRT_VERSION=10.0.1
+ENV TENSORRT_DIR=/TensorRT-10.1.0.27
+ENV TENSORRT_VERSION=10.1.0
 
 RUN wget https://github.com/bazelbuild/bazelisk/releases/download/v1.17.0/bazelisk-linux-amd64 \
     && mv bazelisk-linux-amd64 /usr/bin/bazel \

py/requirements.txt

@@ -6,4 +6,4 @@ torch>=2.4.0,<2.5.0
 torchvision>=0.19.0,<0.20.0
 --extra-index-url https://pypi.ngc.nvidia.com
 pyyaml
-tensorrt==10.0.1
+tensorrt==10.1.0

pyproject.toml

@@ -8,7 +8,7 @@ requires = [
     "cffi>=1.15.1",
     "typing-extensions>=4.7.0",
     "future>=0.18.3",
-    "tensorrt==10.0.1",
+    "tensorrt==10.1.0",
     "torch>=2.4.0,<2.5.0",
     "pybind11==2.6.2",
     "numpy",
@@ -42,9 +42,9 @@ requires-python = ">=3.8"
 keywords = ["pytorch", "torch", "tensorrt", "trt", "ai", "artificial intelligence", "ml", "machine learning", "dl", "deep learning", "compiler", "dynamo", "torchscript", "inference"]
 dependencies = [
     "torch>=2.4.0,<2.5.0",
-    "tensorrt==10.0.1",
-    "tensorrt-cu12_bindings==10.0.1",
-    "tensorrt-cu12_libs==10.0.1",
+    "tensorrt==10.1.0",
+    "tensorrt-cu12_bindings==10.1.0",
+    "tensorrt-cu12_libs==10.1.0",
     "packaging>=23",
     "numpy",
     "typing-extensions>=4.7.0",