[stdArchiveReader.cpp::StdArchiveReader::40] Error Code 1: Serialization (Serialization assertion stdVersionRead == serializationVersion failed.Versio

AI & Data Science Deep Learning (Training & Inference) TensorRT
1

I am using tensorrt with yolov5 on ubuntu machine i got this error : [TRT] [E] 1: [stdArchiveReader.cpp::StdArchiveReader::40] Error Code 1: Serialization (Serialization assertion stdVersionRead == serializationVersion failed.Version tag does not match. Note: Current Version: 213, Serialized Engine Version: 232)
[06/24/2024-13:37:59] [TRT] [E] 4: [runtime.cpp::deserializeCudaEngine::49] Error Code 4: Internal Error (Engine deserialization failed.)

$ dpkg -l | grep TensorRT
ii graphsurgeon-tf 8.4.1-1+cuda11.4 arm64 GraphSurgeon for TensorRT package
ii libnvinfer-bin 8.4.1-1+cuda11.4 arm64 TensorRT binaries
ii libnvinfer-dev 8.4.1-1+cuda11.4 arm64 TensorRT development libraries and headers
ii libnvinfer-plugin-dev 8.4.1-1+cuda11.4 arm64 TensorRT plugin libraries
ii libnvinfer-plugin8 8.4.1-1+cuda11.4 arm64 TensorRT plugin libraries
ii libnvinfer-samples 8.4.1-1+cuda11.4 all TensorRT samples
ii libnvinfer8 8.4.1-1+cuda11.4 arm64 TensorRT runtime libraries
ii libnvonnxparsers-dev 8.4.1-1+cuda11.4 arm64 TensorRT ONNX libraries
ii libnvonnxparsers8 8.4.1-1+cuda11.4 arm64 TensorRT ONNX libraries
ii libnvparsers-dev 8.4.1-1+cuda11.4 arm64 TensorRT parsers libraries
ii libnvparsers8 8.4.1-1+cuda11.4 arm64 TensorRT parsers libraries
ii nvidia-tensorrt 5.0.2-b231 arm64 NVIDIA TensorRT Meta Package
ii nvidia-tensorrt-dev 5.0.2-b231 arm64 NVIDIA TensorRT dev Meta Package
ii python3-libnvinfer 8.4.1-1+cuda11.4 arm64 Python 3 bindings for TensorRT
ii python3-libnvinfer-dev 8.4.1-1+cuda11.4 arm64 Python 3 development package for TensorRT
ii tensorrt 8.4.1.5-1+cuda11.4 arm64 Meta package for TensorRT
ii uff-converter-tf 8.4.1-1+cuda11.4 arm64 UFF converter for TensorRT package

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Hi @ky982007 ,
The error means that you build the engine using TRT version A, but load it with TRT version B.
Please make sure you build and load the engine file using the same TRT version.