compatibility with TensorRT 10 #188
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Following the official migration guide https://docs.nvidia.com/deeplearning/tensorrt/latest/api/migration-guide.html the`Engine.allocate_buffers` method can be updated to make this repo compatible with TensorRT 10. This significantly simplifies dependencies, removing the need for the additional script `python -m streamdiffusion.tools.install-tensorrt` 1. Latest versions of `tensorrt`, `polygraphy` and `onnx-graphsurgeon` can be installed from PyPi. 2. TensorRT can be installed using a more modern dependency manager Poetry ```bash poetry source add --priority=supplemental nvidia https://pypi.nvidia.com poetry add --source nvidia tensorrt-cu12 tensorrt-cu12-libs tensorrt-cu12-bindings ``` Related issues: cumulo-autumn#77 NVIDIA/TensorRT#3050
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Following the official migration guide https://docs.nvidia.com/deeplearning/tensorrt/latest/api/migration-guide.html the
Engine.allocate_buffersmethod can be updated to make this repo compatible with TensorRT 10.This significantly simplifies dependencies, removing the need for the additional script
python -m streamdiffusion.tools.install-tensorrttensorrt,polygraphyandonnx-graphsurgeoncan be installed from PyPi.poetry source add --priority=supplemental nvidia https://pypi.nvidia.com poetry add --source nvidia tensorrt-cu12 tensorrt-cu12-libs tensorrt-cu12-bindingsRelated issues:
#77
NVIDIA/TensorRT#3050