Merge pull request #3949 from akhilg-nv/dev-akhilg-10.1-GA

TensorRT OSS 10.1 GA Release

.clang-format

@@ -74,6 +74,7 @@ SpacesInContainerLiterals: true
 SpacesInParentheses: false
 SpacesInSquareBrackets: false
 Standard:        Cpp11
+StatementMacros: [API_ENTRY_TRY]
 TabWidth:        4
 UseTab:          Never
 ...

CHANGELOG.md

@@ -1,6 +1,23 @@
 # TensorRT OSS Release Changelog
 
-## 10.0.1 GA - 2024-04-30
+## 10.1.0 GA - 2024-06-17
+
+Key Features and Updates:
+
+ - Parser changes
+   - Added `supportsModelV2` API
+   - Added support for `DeformConv` operation
+   - Added support for `PluginV3` TensorRT Plugins
+   - Marked all IParser and IParserRefitter APIs as `noexcept`
+ - Plugin changes
+   - Added version 2 of ROIAlign_TRT plugin, which implements the IPluginV3 plugin interface. When importing an ONNX model with the RoiAlign op, this new version of the plugin will be inserted to the TRT network.
+ - Samples changes
+   - Added a new sample [non_zero_plugin](samples/python/non_zero_plugin), which is a Python version of the C++ sample [sampleNonZeroPlugin](samples/sampleNonZeroPlugin).
+ - Updated tooling
+   - Polygraphy v0.49.12
+   - ONNX-GraphSurgeon v0.5.3
+
+## 10.0.1 GA - 2024-04-24
 
 Key Features and Updates:
 

LICENSE

@@ -353,3 +353,30 @@
      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
      See the License for the specific language governing permissions and
      limitations under the License.
+
+   > demo/Diffusion/utils_sd3/sd3_impls.py
+   > demo/Diffusion/utils_sd3/other_impls.py
+   > demo/Diffusion/utils_sd3/mmdit.py
+   > demo/Diffusion/stable_diffusion_3_pipeline.py
+
+      MIT License
+
+      Copyright (c) 2024 Stability AI
+
+      Permission is hereby granted, free of charge, to any person obtaining a copy
+      of this software and associated documentation files (the "Software"), to deal
+      in the Software without restriction, including without limitation the rights
+      to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+      copies of the Software, and to permit persons to whom the Software is
+      furnished to do so, subject to the following conditions:
+
+      The above copyright notice and this permission notice shall be included in all
+      copies or substantial portions of the Software.
+
+      THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+      IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+      FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+      AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+      LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+      OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+      SOFTWARE.

README.md

@@ -26,13 +26,13 @@ You can skip the **Build** section to enjoy TensorRT with Python.
 To build the TensorRT-OSS components, you will first need the following software packages.
 
 **TensorRT GA build**
-* TensorRT v10.0.1.6
+* TensorRT v10.1.0.27
   * Available from direct download links listed below
 
 **System Packages**
 * [CUDA](https://developer.nvidia.com/cuda-toolkit)
   * Recommended versions:
-  * cuda-12.2.0 + cuDNN-8.9
+  * cuda-12.4.0 + cuDNN-8.9
   * cuda-11.8.0 + cuDNN-8.9
 * [GNU make](https://ftp.gnu.org/gnu/make/) >= v4.1
 * [cmake](https://github.com/Kitware/CMake/releases) >= v3.13
@@ -73,24 +73,25 @@ To build the TensorRT-OSS components, you will first need the following software
     If using the TensorRT OSS build container, TensorRT libraries are preinstalled under `/usr/lib/x86_64-linux-gnu` and you may skip this step.
 
     Else download and extract the TensorRT GA build from [NVIDIA Developer Zone](https://developer.nvidia.com) with the direct links below:
-      - [TensorRT 10.0.1.6 for CUDA 11.8, Linux x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.1/tars/TensorRT-10.0.1.6.Linux.x86_64-gnu.cuda-11.8.tar.gz)
-      - [TensorRT 10.0.1.6 for CUDA 12.4, Linux x86_64](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)
-      - [TensorRT 10.0.1.6 for CUDA 11.8, Windows x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.1/zip/TensorRT-10.0.1.6.Windows10.win10.cuda-11.8.zip)
-      - [TensorRT 10.0.1.6 for CUDA 12.4, Windows x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.1/zip/TensorRT-10.0.1.6.Windows10.win10.cuda-12.4.zip)
+      - [TensorRT 10.1.0.27 for CUDA 11.8, Linux x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.1.0/tars/TensorRT-10.1.0.27.Linux.x86_64-gnu.cuda-11.8.tar.gz)
+      - [TensorRT 10.1.0.27 for CUDA 12.4, Linux x86_64](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)
+      - [TensorRT 10.1.0.27 for CUDA 11.8, Windows x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.1.0/zip/TensorRT-10.1.0.27.Windows.win10.cuda-11.8.zip)
+      - [TensorRT 10.1.0.27 for CUDA 12.4, Windows x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.1.0/zip/TensorRT-10.1.0.27.Windows.win10.cuda-12.4.zip)
+
 
     **Example: Ubuntu 20.04 on x86-64 with cuda-12.4**
 
     ```bash
     cd ~/Downloads
-    tar -xvzf TensorRT-10.0.1.6.Linux.x86_64-gnu.cuda-12.4.tar.gz
-    export TRT_LIBPATH=`pwd`/TensorRT-10.0.1.6
+    tar -xvzf TensorRT-10.1.0.27.Linux.x86_64-gnu.cuda-12.4.tar.gz
+    export TRT_LIBPATH=`pwd`/TensorRT-10.1.0.27
     ```
 
     **Example: Windows on x86-64 with cuda-12.4**
 
     ```powershell
-    Expand-Archive -Path TensorRT-10.0.1.6.Windows10.win10.cuda-12.4.zip
-    $env:TRT_LIBPATH="$pwd\TensorRT-10.0.1.6\lib"
+    Expand-Archive -Path TensorRT-10.1.0.27.Windows.win10.cuda-12.4.zip
+    $env:TRT_LIBPATH="$pwd\TensorRT-10.1.0.27\lib"
     ```
 
 ## Setting Up The Build Environment
@@ -162,7 +163,7 @@ For Linux platforms, we recommend that you generate a docker container for build
 	make -j$(nproc)
 	```
 
-      **Example: Native builds on Windows (x86) with cuda-12.4**
+    **Example: Native builds on Windows (x86) with cuda-12.4**
 	```powershell
 	cd $TRT_OSSPATH
 	mkdir -p build

VERSION

@@ -1 +1 @@
-10.0.1.6
+10.1.0.27