upgrade tensorrt and tensorrt_rtx

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

@@ -60,6 +60,10 @@
             "urls": "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.13.2/zip/TensorRT-10.13.2.6.Windows.win10.cuda-12.9.zip",
             "strip_prefix": "TensorRT-10.13.2.6",
         },
+        "10.14.1": {
+            "urls": "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.14.1/zip/TensorRT-10.14.1.48.Windows.win10.cuda-12.9.zip",
+            "strip_prefix": "TensorRT-10.14.1.48",
+        },
     },
     "linux": {
         "10.3.0": {
@@ -94,6 +98,10 @@
             "urls": "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.13.2/tars/TensorRT-10.13.2.6.Linux.x86_64-gnu.cuda-12.9.tar.gz",
             "strip_prefix": "TensorRT-10.13.2.6",
         },
+        "10.14.1": {
+            "urls": "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.14.1/tars/TensorRT-10.14.1.48.Linux.x86_64-gnu.cuda-12.9.tar.gz",
+            "strip_prefix": "TensorRT-10.14.1.48",
+        },
     },
 }
 

.github/scripts/install-tensorrt-rtx.sh

@@ -1,7 +1,12 @@
 
 install_tensorrt_rtx() {
     if [[ ${USE_TRT_RTX} == true ]]; then
-        TRT_RTX_VERSION=1.0.0.21
+        if [[ ${CU_VERSION:2:2} == "13" ]]; then
+            export CU_UPPERBOUND="13.0"
+        else
+            export CU_UPPERBOUND="12.9"
+        fi
+        TRT_RTX_VERSION=1.2.0.54
         install_wheel_or_not=${1:-false}
         echo "It is the tensorrt-rtx build, install tensorrt-rtx with install_wheel_or_not:${install_wheel_or_not}"
         PLATFORM=$(python -c "import sys; print(sys.platform)")
@@ -15,24 +20,26 @@ install_tensorrt_rtx() {
         # python version is like 3.11, we need to convert it to cp311
         CPYTHON_TAG="cp${PYTHON_VERSION//./}"
         if [[ ${PLATFORM} == win32 ]]; then
-            curl -L https://developer.nvidia.com/downloads/trt/rtx_sdk/secure/1.0/TensorRT-RTX-${TRT_RTX_VERSION}.Windows.win10.cuda-12.9.zip -o TensorRT-RTX-${TRT_RTX_VERSION}.Windows.win10.cuda-12.9.zip
-            unzip TensorRT-RTX-${TRT_RTX_VERSION}.Windows.win10.cuda-12.9.zip
+            curl -L https://developer.nvidia.com/downloads/trt/rtx_sdk/secure/1.2/tensorrt-rtx-${TRT_RTX_VERSION}-win10-amd64-cuda-${CU_UPPERBOUND}-release-external.zip -o tensorrt-rtx-${TRT_RTX_VERSION}.win10-amd64-cuda-${CU_UPPERBOUND}.zip
+            unzip tensorrt-rtx-${TRT_RTX_VERSION}.win10-amd64-cuda-${CU_UPPERBOUND}.zip
             rtx_lib_dir=${PWD}/TensorRT-RTX-${TRT_RTX_VERSION}/lib
             export PATH=${rtx_lib_dir}:$PATH
             echo "PATH: $PATH"
             if [[ ${install_wheel_or_not} == true ]]; then
                 pip install TensorRT-RTX-${TRT_RTX_VERSION}/python/tensorrt_rtx-${TRT_RTX_VERSION}-${CPYTHON_TAG}-none-win_amd64.whl
             fi
         else
-            curl -L https://developer.nvidia.com/downloads/trt/rtx_sdk/secure/1.0/TensorRT-RTX-${TRT_RTX_VERSION}.Linux.x86_64-gnu.cuda-12.9.tar.gz -o TensorRT-RTX-${TRT_RTX_VERSION}.Linux.x86_64-gnu.cuda-12.9.tar.gz
-            tar -xzf TensorRT-RTX-${TRT_RTX_VERSION}.Linux.x86_64-gnu.cuda-12.9.tar.gz
+            curl -L https://developer.nvidia.com/downloads/trt/rtx_sdk/secure/1.2/tensorrt-rtx-${TRT_RTX_VERSION}-linux-x86_64-cuda-${CU_UPPERBOUND}-release-external.tar.gz -o tensorrt-rtx-${TRT_RTX_VERSION}-linux-x86_64-cuda-${CU_UPPERBOUND}-release-external.tar.gz
+            tar -xzf tensorrt-rtx-${TRT_RTX_VERSION}-linux-x86_64-cuda-${CU_UPPERBOUND}-release-external.tar.gz
             rtx_lib_dir=${PWD}/TensorRT-RTX-${TRT_RTX_VERSION}/lib
             export LD_LIBRARY_PATH=${rtx_lib_dir}:$LD_LIBRARY_PATH
             echo "LD_LIBRARY_PATH: $LD_LIBRARY_PATH"
             if [[ ${install_wheel_or_not} == true ]]; then
                 pip install TensorRT-RTX-${TRT_RTX_VERSION}/python/tensorrt_rtx-${TRT_RTX_VERSION}-${CPYTHON_TAG}-none-linux_x86_64.whl
             fi
         fi
+        # clean up the downloaded rtx tarball
+        rm tensorrt-rtx*.tar.gz
     else
         echo "It is the standard tensorrt build, skip install tensorrt-rtx"
     fi

MODULE.bazel

@@ -101,27 +101,27 @@ http_archive(
 http_archive(
     name = "tensorrt",
     build_file = "@//third_party/tensorrt/archive:BUILD",
-    strip_prefix = "TensorRT-10.13.3.9",
+    strip_prefix = "TensorRT-10.14.1.48",
     urls = [
-        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.13.3/tars/TensorRT-10.13.3.9.Linux.x86_64-gnu.cuda-13.0.tar.gz",
+        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.14.1/tars/TensorRT-10.14.1.48.Linux.x86_64-gnu.cuda-13.0.tar.gz",
     ],
 )
 
 http_archive(
     name = "tensorrt_rtx",
     build_file = "@//third_party/tensorrt_rtx/archive:BUILD",
-    strip_prefix = "TensorRT-RTX-1.0.0.21",
+    strip_prefix = "TensorRT-RTX-1.2.0.54",
     urls = [
-        "https://developer.nvidia.com/downloads/trt/rtx_sdk/secure/1.0/TensorRT-RTX-1.0.0.21.Linux.x86_64-gnu.cuda-12.9.tar.gz",
+        "https://developer.nvidia.com/downloads/trt/rtx_sdk/secure/1.2/tensorrt-rtx-1.2.0.54-linux-x86_64-cuda-13.0-release-external.tar.gz",
     ],
 )
 
 http_archive(
     name = "tensorrt_sbsa",
     build_file = "@//third_party/tensorrt/archive:BUILD",
-    strip_prefix = "TensorRT-10.13.3.9",
+    strip_prefix = "TensorRT-10.14.1.48",
     urls = [
-        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.13.3/tars/TensorRT-10.13.3.9.Linux.aarch64-gnu.cuda-13.0.tar.gz",
+        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.14.1/tars/TensorRT-10.14.1.48.Linux.aarch64-gnu.cuda-13.0.tar.gz",
     ],
 )
 
@@ -137,18 +137,18 @@ http_archive(
 http_archive(
     name = "tensorrt_win",
     build_file = "@//third_party/tensorrt/archive:BUILD",
-    strip_prefix = "TensorRT-10.13.3.9",
+    strip_prefix = "TensorRT-10.14.1.48",
     urls = [
-        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.13.3/zip/TensorRT-10.13.3.9.Windows.win10.cuda-13.0.zip",
+        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.14.1/zip/TensorRT-10.14.1.48.Windows.win10.cuda-13.0.zip",
     ],
 )
 
 http_archive(
     name = "tensorrt_rtx_win",
     build_file = "@//third_party/tensorrt_rtx/archive:BUILD",
-    strip_prefix = "TensorRT-RTX-1.0.0.21",
+    strip_prefix = "TensorRT-RTX-1.2.0.54",
     urls = [
-        "https://developer.nvidia.com/downloads/trt/rtx_sdk/secure/1.0/TensorRT-RTX-1.0.0.21.Windows.win10.cuda-12.9.zip",
+        "https://developer.nvidia.com/downloads/trt/rtx_sdk/secure/1.2/tensorrt-rtx-1.2.0.54-win10-amd64-cuda-13.0-release-external.zip",
     ],
 )
 ####################################################################################

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-2.10-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-10.13.0-green)](https://github.com/nvidia/tensorrt)
+[![trt](https://img.shields.io/badge/TensorRT-10.14.0-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)
@@ -123,7 +123,7 @@ These are the following dependencies used to verify the testcases. Torch-TensorR
 - Bazel 8.1.1
 - Libtorch 2.10.0.dev (latest nightly)
 - CUDA 13.0 (CUDA 12.6 on Jetson)
-- TensorRT 10.13.2.6 (TensorRT 10.3 on Jetson)
+- TensorRT 10.14.1.48 (TensorRT 10.3 on Jetson)
 
 ## Deprecation Policy
 

dev_dep_versions.yml

@@ -1,4 +1,4 @@
-__cuda_version__: "12.8"
-__tensorrt_version__: "10.13.3"
-__tensorrt_rtx_version__: "1.0.0"
+__cuda_version__: "13.0"
+__tensorrt_version__: "10.14.0"
+__tensorrt_rtx_version__: "1.2.0"
 __tensorrt_llm_version__: "0.17.0.post1"

docsrc/getting_started/tensorrt_rtx.rst

@@ -52,7 +52,7 @@ Install TensorRT-RTX Tarball
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 TensorRT-RTX tarball can be downloaded from https://developer.nvidia.com/tensorrt-rtx.  
-Currently, Torch-TensorRT uses TensorRT-RTX version **1.0.0.21**.
+Currently, Torch-TensorRT uses TensorRT-RTX version **1.2.0.54**.
 
 Once downloaded:
 
@@ -62,8 +62,8 @@ Make sure you add the lib path to the ``LD_LIBRARY_PATH`` environment variable.
 
 .. code-block:: sh
 
-    # If TensorRT-RTX is downloaded in /your_local_download_path/TensorRT-RTX-1.0.0.21
-    export LD_LIBRARY_PATH=/your_local_download_path/TensorRT-RTX-1.0.0.21/lib:$LD_LIBRARY_PATH
+    # If TensorRT-RTX is downloaded in /your_local_download_path/TensorRT-RTX-1.2.0.54
+    export LD_LIBRARY_PATH=/your_local_download_path/TensorRT-RTX-1.2.0.54/lib:$LD_LIBRARY_PATH
     echo $LD_LIBRARY_PATH | grep TensorRT-RTX
 
 **In Windows:**
@@ -72,8 +72,8 @@ Make sure you add the lib path to the Windows system variable ``PATH``.
 
 .. code-block:: sh
 
-    # If TensorRT-RTX is downloaded in C:\your_local_download_path\TensorRT-RTX-1.0.0.21
-    set PATH="%PATH%;C:\your_local_download_path\TensorRT-RTX-1.0.0.21\lib"
+    # If TensorRT-RTX is downloaded in C:\your_local_download_path\TensorRT-RTX-1.2.0.54
+    set PATH="%PATH%;C:\your_local_download_path\TensorRT-RTX-1.2.0.54\lib"
     echo %PATH% | findstr TensorRT-RTX
 
 Install TensorRT-RTX Wheel
@@ -84,8 +84,8 @@ You must install it manually from the downloaded tarball.
 
 .. code-block:: sh
 
-   # If the tarball is downloaded in /your_local_download_path/TensorRT-RTX-1.0.0.21
-   python -m pip install /your_local_download_path/TensorRT-RTX-1.0.0.21/python/tensorrt_rtx-1.0.0.21-cp39-none-linux_x86_64.whl
+   # If the tarball is downloaded in /your_local_download_path/TensorRT-RTX-1.2.0.54
+   python -m pip install /your_local_download_path/TensorRT-RTX-1.2.0.54/python/tensorrt_rtx-1.2.0.54-cp39-none-linux_x86_64.whl
 
 Build Torch-TensorRT with TensorRT-RTX
 --------------------------------------

setup.py

@@ -754,14 +754,15 @@ def get_requirements():
             requirements = requirements + ["torch>=2.10.0.dev,<2.11.0"]
             if USE_TRT_RTX:
                 requirements = requirements + [
-                    "tensorrt_rtx>=1.0.0.21",
+                    "tensorrt_rtx>=1.2.0.54",
                 ]
             else:
                 requirements = requirements + [
-                    "tensorrt>=10.13.0,<10.14.0",
-                    f"{tensorrt_prefix}>=10.13.0,<10.14.0",
-                    f"{tensorrt_prefix}-bindings>=10.13.0,<10.14.0",
-                    f"{tensorrt_prefix}-libs>=10.13.0,<10.14.0",
+                    # directly use tensorrt>=10.14.0,<10.15.0 in cu12* env, it will pull both tensorrt_cu12 and tensorrt_cu13
+                    # which will cause the conflict due to cuda-toolkit 13 is also pulled in, so we need to specify tensorrt_cu12 or tensorrt_cu13 here
+                    f"{tensorrt_prefix}>=10.14.0,<10.15.0",
+                    f"{tensorrt_prefix}-bindings>=10.14.0,<10.15.0",
+                    f"{tensorrt_prefix}-libs>=10.14.0,<10.15.0",
                 ]
     return requirements
 
@@ -781,7 +782,7 @@ def get_sbsa_requirements():
     # also due to we use sbsa torch_tensorrt wheel for thor, so when we build sbsa wheel, we need to only include tensorrt dependency.
     return sbsa_requirements + [
         "torch>=2.10.0.dev,<2.11.0",
-        "tensorrt>=10.13.0,<10.14.0",
+        "tensorrt>=10.14.0,<10.15.0",
     ]
 
 

third_party/tensorrt_rtx/archive/BUILD

@@ -38,7 +38,7 @@ cc_library(
 cc_import(
     name = "nvinfer_lib",
     shared_library = select({
-        ":rtx_win": "lib/tensorrt_rtx_1_0.dll",
+        ":rtx_win": "lib/tensorrt_rtx_1_2.dll",
         ":rtx_x86_64": "lib/libtensorrt_rtx.so",
     }),
     visibility = ["//visibility:private"],
@@ -47,7 +47,7 @@ cc_import(
 cc_import(
     name = "nvinfer_static_lib",
     static_library = select({
-        ":rtx_win": "lib/tensorrt_rtx_1_0.lib",
+        ":rtx_win": "lib/tensorrt_rtx_1_2.lib",
     }),
     visibility = ["//visibility:private"],
 )

third_party/tensorrt_rtx/local/BUILD

@@ -50,15 +50,15 @@ cc_library(
 cc_import(
     name = "nvinfer_static_lib",
     static_library = select({
-        ":rtx_win": "lib/tensorrt_rtx_1_0.lib",
+        ":rtx_win": "lib/tensorrt_rtx_1_2.lib",
     }),
     visibility = ["//visibility:private"],
 )
 
 cc_import(
     name = "nvinfer_lib",
     shared_library = select({
-        ":rtx_win": "lib/tensorrt_rtx_1_0.dll",
+        ":rtx_win": "bin/tensorrt_rtx_1_2.dll",
         ":rtx_x86_64": "lib/libtensorrt_rtx.so",
     }),
     visibility = ["//visibility:private"],

toolchains/ci_workspaces/MODULE.bazel.tmpl

@@ -75,27 +75,27 @@ http_archive = use_repo_rule("@bazel_tools//tools/build_defs/repo:http.bzl", "ht
 http_archive(
     name = "tensorrt",
     build_file = "@//third_party/tensorrt/archive:BUILD",
-    strip_prefix = "TensorRT-10.13.3.9",
+    strip_prefix = "TensorRT-10.14.1.48",
     urls = [
-        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.13.3/tars/TensorRT-10.13.3.9.Linux.x86_64-gnu.cuda-${CU_UPPERBOUND}.tar.gz",
+        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.14.1/tars/TensorRT-10.14.1.48.Linux.x86_64-gnu.cuda-${CU_UPPERBOUND}.tar.gz",
     ],
 )
 
 http_archive(
     name = "tensorrt_rtx",
     build_file = "@//third_party/tensorrt_rtx/archive:BUILD",
-    strip_prefix = "TensorRT-RTX-1.0.0.21",
+    strip_prefix = "TensorRT-RTX-1.2.0.54",
     urls = [
-        "https://developer.nvidia.com/downloads/trt/rtx_sdk/secure/1.0/TensorRT-RTX-1.0.0.21.Linux.x86_64-gnu.cuda-12.9.tar.gz",
+        "https://developer.nvidia.com/downloads/trt/rtx_sdk/secure/1.2/tensorrt-rtx-1.2.0.54-linux-x86_64-cuda-${CU_UPPERBOUND}-release-external.tar.gz",
     ],
 )
 
 http_archive(
     name = "tensorrt_sbsa",
     build_file = "@//third_party/tensorrt/archive:BUILD",
-    strip_prefix = "TensorRT-10.13.3.9",
+    strip_prefix = "TensorRT-10.14.1.48",
     urls = [
-        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.13.3/tars/TensorRT-10.13.3.9.Linux.aarch64-gnu.cuda-13.0.tar.gz",
+        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.14.1/tars/TensorRT-10.14.1.48.Linux.aarch64-gnu.cuda-13.0.tar.gz",
     ],
 )
 
@@ -111,18 +111,18 @@ http_archive(
 http_archive(
     name = "tensorrt_win",
     build_file = "@//third_party/tensorrt/archive:BUILD",
-    strip_prefix = "TensorRT-10.13.3.9",
+    strip_prefix = "TensorRT-10.14.1.48",
     urls = [
-        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.13.3/zip/TensorRT-10.13.3.9.Windows.win10.cuda-${CU_UPPERBOUND}.zip",
+        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.14.1/zip/TensorRT-10.14.1.48.Windows.win10.cuda-${CU_UPPERBOUND}.zip",
     ],
 )
 
 http_archive(
     name = "tensorrt_rtx_win",
     build_file = "@//third_party/tensorrt_rtx/archive:BUILD",
-    strip_prefix = "TensorRT-RTX-1.0.0.21",
+    strip_prefix = "TensorRT-RTX-1.2.0.54",
     urls = [
-        "https://developer.nvidia.com/downloads/trt/rtx_sdk/secure/1.0/TensorRT-RTX-1.0.0.21.Windows.win10.cuda-12.9.zip",
+        "https://developer.nvidia.com/downloads/trt/rtx_sdk/secure/1.2/tensorrt-rtx-1.2.0.54-win10-amd64-cuda-${CU_UPPERBOUND}-release-external.zip",
     ],
 )
 

tools/perf/Flux/create_env.sh

@@ -15,7 +15,7 @@ bazel
 cd /home/TensorRT
 
 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
+pip install tensorrt==10.14.1.48 --force-reinstall
 
 pip3 install --pre  torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu130