TensorRT OSS 10.1 GA Release

Signed-off-by: Akhil Goel <akhilg@nvidia.com>

Author: akhilg-nv

.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