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- Enabled INT8 and FP8 quantization for Stable Diffusion v1.5, v2.0 and v2.1 pipelines.
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- Enabled FP8 quantization for Stable Diffusion XL pipeline.
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- Sample changes
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- Add a new python sample `aliased_io_plugin` which demonstrates how in-place updates to plugin inputs can be achieved through I/O aliasing.
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- Plugin changes
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- Migrated IPluginV2-descendent versions (a) of the following plugins to newer versions (b) which implement IPluginV3 (a->b):
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- scatterElementsPlugin (1->2)
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- skipLayerNormPlugin (1->5, 2->6, 3->7, 4->8)
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- embLayerNormPlugin (2->4, 3->5)
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- bertQKVToContextPlugin (1->4, 2->5, 3->6)
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- Note
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- The newer versions preserve the corresponding attributes and I/O of the corresponding older plugin version.
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- The older plugin versions are deprecated and will be removed in a future release.
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- Quickstart guide
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- Updated deploy_to_triton guide and removed legacy APIs.
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- Removed legacy TF-TRT code as the project is no longer supported.
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- Removed quantization_tutorial as pytorch_quantization has been deprecated. Check out https://github.com/NVIDIA/TensorRT-Model-Optimizer for the latest quantization support. Check [Stable Diffusion XL (Base/Turbo) and Stable Diffusion 1.5 Quantization with Model Optimizer](https://github.com/NVIDIA/TensorRT-Model-Optimizer/tree/main/diffusers/quantization) for integration with TensorRT.
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- Parser changes
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- Added support for tensor `axes` for `Pad` operations.
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- Added support for `BlackmanWindow`, `HammingWindow`, and `HannWindow` operations.
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- Improved error handling in `IParserRefitter`.
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- Fixed kernel shape inference in multi-input convolutions.
@@ -73,25 +73,25 @@ To build the TensorRT-OSS components, you will first need the following software
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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 10.3.0.26 for CUDA 11.8, Linux x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.3.0/tars/TensorRT-10.3.0.26.Linux.x86_64-gnu.cuda-11.8.tar.gz)
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-[TensorRT 10.3.0.26 for CUDA 12.5, Linux x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.3.0/tars/TensorRT-10.3.0.26.Linux.x86_64-gnu.cuda-12.5.tar.gz)
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-[TensorRT 10.3.0.26 for CUDA 11.8, Windows x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.3.0/zip/TensorRT-10.3.0.26.Windows.win10.cuda-11.8.zip)
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-[TensorRT 10.3.0.26 for CUDA 12.5, Windows x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.3.0/zip/TensorRT-10.3.0.26.Windows.win10.cuda-12.5.zip)
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-[TensorRT 10.4.0.26 for CUDA 11.8, Linux x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.4.0/tars/TensorRT-10.4.0.26.Linux.x86_64-gnu.cuda-11.8.tar.gz)
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-[TensorRT 10.4.0.26 for CUDA 12.6, Linux x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.4.0/tars/TensorRT-10.4.0.26.Linux.x86_64-gnu.cuda-12.6.tar.gz)
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-[TensorRT 10.4.0.26 for CUDA 11.8, Windows x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.4.0/zip/TensorRT-10.4.0.26.Windows.win10.cuda-11.8.zip)
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-[TensorRT 10.4.0.26 for CUDA 12.6, Windows x86_64](https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.4.0/zip/TensorRT-10.4.0.26.Windows.win10.cuda-12.6.zip)
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**Example: Ubuntu 20.04 on x86-64 with cuda-12.5**
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**Example: Ubuntu 20.04 on x86-64 with cuda-12.6**
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```bash
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cd~/Downloads
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tar -xvzf TensorRT-10.3.0.26.Linux.x86_64-gnu.cuda-12.5.tar.gz
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export TRT_LIBPATH=`pwd`/TensorRT-10.3.0.26
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tar -xvzf TensorRT-10.4.0.26.Linux.x86_64-gnu.cuda-12.6.tar.gz
@@ -101,27 +101,27 @@ For Linux platforms, we recommend that you generate a docker container for build
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1. #### Generate the TensorRT-OSS build container.
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The TensorRT-OSS build container can be generated using the supplied Dockerfiles and build scripts. The build containers are configured for building TensorRT OSS out-of-the-box.
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**Example: Ubuntu 20.04 on x86-64 with cuda-12.5 (default)**
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**Example: Ubuntu 20.04 on x86-64 with cuda-12.6 (default)**
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