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Merge pull request #3949 from akhilg-nv/dev-akhilg-10.1-GA
TensorRT OSS 10.1 GA Release
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.clang-format

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SpacesInParentheses: false
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SpacesInSquareBrackets: false
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Standard: Cpp11
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StatementMacros: [API_ENTRY_TRY]
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TabWidth: 4
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UseTab: Never
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...

CHANGELOG.md

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# TensorRT OSS Release Changelog
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## 10.0.1 GA - 2024-04-30
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## 10.1.0 GA - 2024-06-17
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Key Features and Updates:
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- Parser changes
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- Added `supportsModelV2` API
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- Added support for `DeformConv` operation
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- Added support for `PluginV3` TensorRT Plugins
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- Marked all IParser and IParserRefitter APIs as `noexcept`
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- Plugin changes
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- 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.
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- Samples changes
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- Added a new sample [non_zero_plugin](samples/python/non_zero_plugin), which is a Python version of the C++ sample [sampleNonZeroPlugin](samples/sampleNonZeroPlugin).
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- Updated tooling
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- Polygraphy v0.49.12
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- ONNX-GraphSurgeon v0.5.3
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## 10.0.1 GA - 2024-04-24
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Key Features and Updates:
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LICENSE

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

README.md

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

VERSION

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10.0.1.6
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10.1.0.27

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