onnx模型转trt模型报错TensorRT was linked against cuDNN 8.4.1 but loaded cuDNN 8.2.1_local timing cache in use. profiling results in th

具体报错：Results saved to D:\todesk\yolov8model
Predict:         yolo predict task=detect model=yolov8s.onnx imgsz=640
Validate:        yolo val task=detect model=yolov8s.onnx imgsz=640 data=coco.yaml
Visualize:       https://netron.app
(yolov8) PS D:\todesk\yolov8model> D:\1\TensorRT_YOLO\TensorRT-8.4.2.4\bin\trtexec.exe   --onnx=yolov8s.onnx  --saveEngine=yolov8s.trt  --buildOnly --minShapes=images:1x3x640x640 --optShapes=images:4x3x640x640 --maxShapes=images:8x3x640x640
&&&& RUNNING TensorRT.trtexec [TensorRT v8402] # D:\1\TensorRT_YOLO\TensorRT-8.4.2.4\bin\trtexec.exe --onnx=yolov8s.onnx --saveEngine=yolov8s.trt --buildOnly --minShapes=images:1x3x640x640 --optShapes=images:4x3x640x640 --maxShapes=images:8x3x640x640
[05/24/2023-16:33:33] [I] === Model Options ===
[05/24/2023-16:33:33] [I] Format: ONNX
[05/24/2023-16:33:33] [I] Model: yolov8s.onnx
[05/24/2023-16:33:33] [I] Output:
[05/24/2023-16:33:33] [I] === Build Options ===
[05/24/2023-16:33:33] [I] Max batch: explicit batch
[05/24/2023-16:33:33] [I] Memory Pools: workspace: default, dlaSRAM: default, dlaLocalDRAM: default, dlaGlobalDRAM: default
[05/24/2023-16:33:33] [I] minTiming: 1
[05/24/2023-16:33:33] [I] avgTiming: 8
[05/24/2023-16:33:33] [I] Precision: FP32
[05/24/2023-16:33:33] [I] LayerPrecisions:
[05/24/2023-16:33:33] [I] Calibration:
[05/24/2023-16:33:33] [I] Refit: Disabled
[05/24/2023-16:33:33] [I] Sparsity: Disabled
[05/24/2023-16:33:33] [I] Safe mode: Disabled
[05/24/2023-16:33:33] [I] DirectIO mode: Disabled
[05/24/2023-16:33:33] [I] Restricted mode: Disabled
[05/24/2023-16:33:33] [I] Build only: Enabled
[05/24/2023-16:33:33] [I] Save engine: yolov8s.trt
[05/24/2023-16:33:33] [I] Load engine:
[05/24/2023-16:33:33] [I] Profiling verbosity: 0
[05/24/2023-16:33:33] [I] Tactic sources: Using default tactic sources
[05/24/2023-16:33:33] [I] timingCacheMode: local
[05/24/2023-16:33:33] [I] timingCacheFile:
[05/24/2023-16:33:33] [I] Input(s)s format: fp32:CHW
[05/24/2023-16:33:33] [I] Output(s)s format: fp32:CHW
[05/24/2023-16:33:33] [I] Input build shape: images=1x3x640x640+4x3x640x640+8x3x640x640
[05/24/2023-16:33:33] [I] Input calibration shapes: model
[05/24/2023-16:33:33] [I] === System Options ===
[05/24/2023-16:33:33] [I] Device: 0
[05/24/2023-16:33:33] [I] DLACore:
[05/24/2023-16:33:33] [I] Plugins:
[05/24/2023-16:33:33] [I] === Inference Options ===
[05/24/2023-16:33:33] [I] Batch: Explicit
[05/24/2023-16:33:33] [I] Input inference shape: images=4x3x640x640
[05/24/2023-16:33:33] [I] Iterations: 10
[05/24/2023-16:33:33] [I] Duration: 3s (+ 200ms warm up)
[05/24/2023-16:33:33] [I] Sleep time: 0ms
[05/24/2023-16:33:33] [I] Idle time: 0ms
[05/24/2023-16:33:33] [I] Streams: 1
[05/24/2023-16:33:33] [I] ExposeDMA: Disabled
[05/24/2023-16:33:33] [I] Data transfers: Enabled
[05/24/2023-16:33:33] [I] Spin-wait: Disabled
[05/24/2023-16:33:33] [I] Multithreading: Disabled
[05/24/2023-16:33:33] [I] CUDA Graph: Disabled
[05/24/2023-16:33:33] [I] Separate profiling: Disabled
[05/24/2023-16:33:33] [I] Time Deserialize: Disabled
[05/24/2023-16:33:33] [I] Time Refit: Disabled
[05/24/2023-16:33:33] [I] Inputs:
[05/24/2023-16:33:33] [I] === Reporting Options ===
[05/24/2023-16:33:33] [I] Verbose: Disabled
[05/24/2023-16:33:33] [I] Averages: 10 inferences
[05/24/2023-16:33:33] [I] Percentile: 99
[05/24/2023-16:33:33] [I] Dump refittable layers:Disabled
[05/24/2023-16:33:33] [I] Dump output: Disabled
[05/24/2023-16:33:33] [I] Profile: Disabled
[05/24/2023-16:33:33] [I] Export timing to JSON file:
[05/24/2023-16:33:33] [I] Export output to JSON file:
[05/24/2023-16:33:33] [I] Export profile to JSON file:
[05/24/2023-16:33:33] [I]
[05/24/2023-16:33:33] [I] === Device Information ===
[05/24/2023-16:33:33] [I] Selected Device: NVIDIA GeForce RTX 4080
[05/24/2023-16:33:33] [I] Compute Capability: 8.9
[05/24/2023-16:33:33] [I] SMs: 76
[05/24/2023-16:33:33] [I] Compute Clock Rate: 2.535 GHz
[05/24/2023-16:33:33] [I] Device Global Memory: 16375 MiB
[05/24/2023-16:33:33] [I] Shared Memory per SM: 100 KiB
[05/24/2023-16:33:33] [I] Memory Bus Width: 256 bits (ECC disabled)
[05/24/2023-16:33:33] [I] Memory Clock Rate: 11.201 GHz
[05/24/2023-16:33:33] [I]
[05/24/2023-16:33:33] [I] TensorRT version: 8.4.2
[05/24/2023-16:33:34] [I] [TRT] [MemUsageChange] Init CUDA: CPU +489, GPU +0, now: CPU 13900, GPU 1491 (MiB)
[05/24/2023-16:33:34] [I] [TRT] [MemUsageChange] Init builder kernel library: CPU +378, GPU +104, now: CPU 14465, GPU 1595 (MiB)
[05/24/2023-16:33:34] [I] Start parsing network model
[05/24/2023-16:33:35] [I] [TRT] ----------------------------------------------------------------
[05/24/2023-16:33:35] [I] [TRT] Input filename:   yolov8s.onnx
[05/24/2023-16:33:35] [I] [TRT] ONNX IR version:  0.0.8
[05/24/2023-16:33:35] [I] [TRT] Opset version:    17
[05/24/2023-16:33:35] [I] [TRT] Producer name:    pytorch
[05/24/2023-16:33:35] [I] [TRT] Producer version: 2.0.1
[05/24/2023-16:33:35] [I] [TRT] Domain:
[05/24/2023-16:33:35] [I] [TRT] Model version:    0
[05/24/2023-16:33:35] [I] [TRT] Doc string:
[05/24/2023-16:33:35] [I] [TRT] ----------------------------------------------------------------
[05/24/2023-16:33:35] [W] [TRT] onnx2trt_utils.cpp:369: Your ONNX model has been generated with INT64 weights, while TensorRT does not natively support INT64. Attempting to cast down to INT32.
[05/24/2023-16:33:35] [I] Finish parsing network model
[05/24/2023-16:33:35] [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +759, GPU +272, now: CPU 15167, GPU 1867 (MiB)
[05/24/2023-16:33:36] [I] [TRT] [MemUsageChange] Init cuDNN: CPU +387, GPU +264, now: CPU 15554, GPU 2131 (MiB)
[05/24/2023-16:33:36] [W] [TRT] TensorRT was linked against cuDNN 8.4.1 but loaded cuDNN 8.2.1
[05/24/2023-16:33:36] [I] [TRT] Local timing cache in use. Profiling results in this builder pass will not be stored.
Unexpected Internal Error: [virtualMemoryBuffer.cpp::nvinfer1::StdVirtualMemoryBufferImpl::~StdVirtualMemoryBufferImpl::104] Error Code 1: Cuda Runtime (driver shutting down)
参考这篇博客

(16条消息) 【TensorRT】TensorRT was linked against cudnn 8.6.0 but loaded cudnn 8.3.2_半路转行的水博的博客-CSDN博客https://blog.csdn.net/sanxiaw/article/details/128017373

于是去cuDNN Archive | NVIDIA 开发者https://developer.nvidia.cn/rdp/cudnn-archive

下载cudnn8.4.1版本的cudnn（具体名称为cudnn-windows-x86_64-8.4.1.50_cuda11.6-archive.zip）

中间还报错抛出异常——Could not locate zlibwapi.dll. Please make sure it is in your library p

参考如下这两篇解决这个zlibwapi.dll的报错。(16条消息) Could not locate zlibwapi.dll. Please make sure it is in your library path_zlibwapi.dll无法注册_Chaos_Happy的博客-CSDN博客https://blog.csdn.net/Chaos_Happy/article/details/124064428Installation Guide - NVIDIA Docshttps://docs.nvidia.com/deeplearning/cudnn/install-guide/index.html#install-zlib-windows

最后成功输出了：

(yolov8) PS D:\todesk\yolov8model> D:\1\TensorRT_YOLO\TensorRT-8.4.2.4\bin\trtexec.exe   --onnx=yolov8s.onnx  --saveEngine=yolov8s.trt  --buildOnly --minShapes=images:1x3x640x640 --optShapes=images:4x3x640x640 --maxShapes=images:8x3x640x640
&&&& RUNNING TensorRT.trtexec [TensorRT v8402] # D:\1\TensorRT_YOLO\TensorRT-8.4.2.4\bin\trtexec.exe --onnx=yolov8s.onnx --saveEngine=yolov8s.trt --buildOnly --minShapes=images:1x3x640x640 --optShapes=images:4x3x640x640 --maxShapes=images:8x3x640x640
[05/24/2023-16:56:08] [I] === Model Options ===
[05/24/2023-16:56:08] [I] Format: ONNX
[05/24/2023-16:56:08] [I] Model: yolov8s.onnx
[05/24/2023-16:56:08] [I] Output:
[05/24/2023-16:56:08] [I] === Build Options ===
[05/24/2023-16:56:08] [I] Max batch: explicit batch
[05/24/2023-16:56:08] [I] Memory Pools: workspace: default, dlaSRAM: default, dlaLocalDRAM: default, dlaGlobalDRAM: default
[05/24/2023-16:56:08] [I] minTiming: 1
[05/24/2023-16:56:08] [I] avgTiming: 8
[05/24/2023-16:56:08] [I] Precision: FP32
[05/24/2023-16:56:08] [I] LayerPrecisions:
[05/24/2023-16:56:08] [I] Calibration:
[05/24/2023-16:56:08] [I] Refit: Disabled
[05/24/2023-16:56:08] [I] Sparsity: Disabled
[05/24/2023-16:56:08] [I] Safe mode: Disabled
[05/24/2023-16:56:08] [I] DirectIO mode: Disabled
[05/24/2023-16:56:08] [I] Restricted mode: Disabled
[05/24/2023-16:56:08] [I] Build only: Enabled
[05/24/2023-16:56:08] [I] Save engine: yolov8s.trt
[05/24/2023-16:56:08] [I] Load engine:
[05/24/2023-16:56:08] [I] Profiling verbosity: 0
[05/24/2023-16:56:08] [I] Tactic sources: Using default tactic sources
[05/24/2023-16:56:08] [I] timingCacheMode: local
[05/24/2023-16:56:08] [I] timingCacheFile:
[05/24/2023-16:56:08] [I] Input(s)s format: fp32:CHW
[05/24/2023-16:56:08] [I] Output(s)s format: fp32:CHW
[05/24/2023-16:56:08] [I] Input build shape: images=1x3x640x640+4x3x640x640+8x3x640x640
[05/24/2023-16:56:08] [I] Input calibration shapes: model
[05/24/2023-16:56:08] [I] === System Options ===
[05/24/2023-16:56:08] [I] Device: 0
[05/24/2023-16:56:08] [I] DLACore:
[05/24/2023-16:56:08] [I] Plugins:
[05/24/2023-16:56:08] [I] === Inference Options ===
[05/24/2023-16:56:08] [I] Batch: Explicit
[05/24/2023-16:56:08] [I] Input inference shape: images=4x3x640x640
[05/24/2023-16:56:08] [I] Iterations: 10
[05/24/2023-16:56:08] [I] Duration: 3s (+ 200ms warm up)
[05/24/2023-16:56:08] [I] Sleep time: 0ms
[05/24/2023-16:56:08] [I] Idle time: 0ms
[05/24/2023-16:56:08] [I] Streams: 1
[05/24/2023-16:56:08] [I] ExposeDMA: Disabled
[05/24/2023-16:56:08] [I] Data transfers: Enabled
[05/24/2023-16:56:08] [I] Spin-wait: Disabled
[05/24/2023-16:56:08] [I] Multithreading: Disabled
[05/24/2023-16:56:08] [I] CUDA Graph: Disabled
[05/24/2023-16:56:08] [I] Separate profiling: Disabled
[05/24/2023-16:56:08] [I] Time Deserialize: Disabled
[05/24/2023-16:56:08] [I] Time Refit: Disabled
[05/24/2023-16:56:08] [I] Inputs:
[05/24/2023-16:56:08] [I] === Reporting Options ===
[05/24/2023-16:56:08] [I] Verbose: Disabled
[05/24/2023-16:56:08] [I] Averages: 10 inferences
[05/24/2023-16:56:08] [I] Percentile: 99
[05/24/2023-16:56:08] [I] Dump refittable layers:Disabled
[05/24/2023-16:56:08] [I] Dump output: Disabled
[05/24/2023-16:56:08] [I] Profile: Disabled
[05/24/2023-16:56:08] [I] Export timing to JSON file:
[05/24/2023-16:56:08] [I] Export output to JSON file:
[05/24/2023-16:56:08] [I] Export profile to JSON file:
[05/24/2023-16:56:08] [I]
[05/24/2023-16:56:08] [I] === Device Information ===
[05/24/2023-16:56:08] [I] Selected Device: NVIDIA GeForce RTX 4080
[05/24/2023-16:56:08] [I] Compute Capability: 8.9
[05/24/2023-16:56:08] [I] SMs: 76
[05/24/2023-16:56:08] [I] Compute Clock Rate: 2.535 GHz
[05/24/2023-16:56:08] [I] Device Global Memory: 16375 MiB
[05/24/2023-16:56:08] [I] Shared Memory per SM: 100 KiB
[05/24/2023-16:56:08] [I] Memory Bus Width: 256 bits (ECC disabled)
[05/24/2023-16:56:08] [I] Memory Clock Rate: 11.201 GHz
[05/24/2023-16:56:08] [I]
[05/24/2023-16:56:08] [I] TensorRT version: 8.4.2
[05/24/2023-16:56:08] [I] [TRT] [MemUsageChange] Init CUDA: CPU +483, GPU +0, now: CPU 12059, GPU 1491 (MiB)
[05/24/2023-16:56:09] [I] [TRT] [MemUsageChange] Init builder kernel library: CPU +377, GPU +104, now: CPU 12626, GPU 1595 (MiB)
[05/24/2023-16:56:09] [I] Start parsing network model
[05/24/2023-16:56:09] [I] [TRT] ----------------------------------------------------------------
[05/24/2023-16:56:09] [I] [TRT] Input filename:   yolov8s.onnx
[05/24/2023-16:56:09] [I] [TRT] ONNX IR version:  0.0.8
[05/24/2023-16:56:09] [I] [TRT] Opset version:    17
[05/24/2023-16:56:09] [I] [TRT] Producer name:    pytorch
[05/24/2023-16:56:09] [I] [TRT] Producer version: 2.0.1
[05/24/2023-16:56:09] [I] [TRT] Domain:
[05/24/2023-16:56:09] [I] [TRT] Model version:    0
[05/24/2023-16:56:09] [I] [TRT] Doc string:
[05/24/2023-16:56:09] [I] [TRT] ----------------------------------------------------------------
[05/24/2023-16:56:09] [W] [TRT] onnx2trt_utils.cpp:369: Your ONNX model has been generated with INT64 weights, while TensorRT does not natively support INT64. Attempting to cast down to INT32.
[05/24/2023-16:56:09] [I] Finish parsing network model
[05/24/2023-16:56:09] [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +759, GPU +272, now: CPU 13318, GPU 1867 (MiB)
[05/24/2023-16:56:10] [I] [TRT] [MemUsageChange] Init cuDNN: CPU +164, GPU +56, now: CPU 13482, GPU 1923 (MiB)
[05/24/2023-16:56:10] [I] [TRT] Local timing cache in use. Profiling results in this builder pass will not be stored.
[05/24/2023-16:57:28] [I] [TRT] Detected 1 inputs and 3 output network tensors.
[05/24/2023-16:57:28] [I] [TRT] Total Host Persistent Memory: 154464
[05/24/2023-16:57:28] [I] [TRT] Total Device Persistent Memory: 1202688
[05/24/2023-16:57:28] [I] [TRT] Total Scratch Memory: 0
[05/24/2023-16:57:28] [I] [TRT] [MemUsageStats] Peak memory usage of TRT CPU/GPU memory allocators: CPU 15 MiB, GPU 6734 MiB
[05/24/2023-16:57:28] [I] [TRT] [BlockAssignment] Algorithm ShiftNTopDown took 114.958ms to assign 16 blocks to 223 nodes requiring 272035344 bytes.
[05/24/2023-16:57:28] [I] [TRT] Total Activation Memory: 272035344
[05/24/2023-16:57:28] [I] [TRT] [MemUsageChange] TensorRT-managed allocation in building engine: CPU +6, GPU +51, now: CPU 6, GPU 51 (MiB)
[05/24/2023-16:57:28] [W] [TRT] The getMaxBatchSize() function should not be used with an engine built from a network created with NetworkDefinitionCreationFlag::kEXPLICIT_BATCH flag. This function will always return 1.
[05/24/2023-16:57:28] [W] [TRT] The getMaxBatchSize() function should not be used with an engine built from a network created with NetworkDefinitionCreationFlag::kEXPLICIT_BATCH flag. This function will always return 1.
[05/24/2023-16:57:29] [I] Engine built in 81.0279 sec.
[05/24/2023-16:57:29] [I] [TRT] [MemUsageChange] Init CUDA: CPU +0, GPU +0, now: CPU 14781, GPU 2339 (MiB)
[05/24/2023-16:57:29] [I] [TRT] Loaded engine size: 51 MiB
[05/24/2023-16:57:29] [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +50, now: CPU 0, GPU 50 (MiB)
[05/24/2023-16:57:29] [I] Engine deserialized in 0.0364477 sec.
[05/24/2023-16:57:29] [I] Skipped inference phase since --buildOnly is added.
&&&& PASSED TensorRT.trtexec [TensorRT v8402] # D:\1\TensorRT_YOLO\TensorRT-8.4.2.4\bin\trtexec.exe --onnx=yolov8s.onnx --saveEngine=yolov8s.trt --buildOnly --minShapes=images:1x3x640x640 --optShapes=images:4x3x640x640 --maxShapes=images:8x3x640x640
 

安装环境依赖于python3.9

(yolov8) PS D:\todesk\yolov8model> conda list
# packages in environment at D:\soft\conda\envs\yolov8:
#
# Name                    Version                   Build  Channel
ca-certificates           2023.01.10           haa95532_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
certifi                   2023.5.7                 pypi_0    pypi
charset-normalizer        3.1.0                    pypi_0    pypi
colorama                  0.4.6                    pypi_0    pypi
contourpy                 1.0.7                    pypi_0    pypi
cycler                    0.11.0                   pypi_0    pypi
filelock                  3.12.0                   pypi_0    pypi
fonttools                 4.39.4                   pypi_0    pypi
idna                      3.4                      pypi_0    pypi
importlib-resources       5.12.0                   pypi_0    pypi
jinja2                    3.1.2                    pypi_0    pypi
kiwisolver                1.4.4                    pypi_0    pypi
markupsafe                2.1.2                    pypi_0    pypi
matplotlib                3.7.1                    pypi_0    pypi
mpmath                    1.3.0                    pypi_0    pypi
networkx                  3.1                      pypi_0    pypi
numpy                     1.24.3                   pypi_0    pypi
onnx                      1.14.0                   pypi_0    pypi
opencv-python             4.7.0.72                 pypi_0    pypi
openssl                   1.1.1t               h2bbff1b_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
packaging                 23.1                     pypi_0    pypi
pandas                    2.0.1                    pypi_0    pypi
pillow                    9.5.0                    pypi_0    pypi
pip                       23.0.1           py39haa95532_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
protobuf                  4.23.1                   pypi_0    pypi
psutil                    5.9.5                    pypi_0    pypi
pyparsing                 3.0.9                    pypi_0    pypi
python                    3.9.16               h6244533_2    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
python-dateutil           2.8.2                    pypi_0    pypi
pytz                      2023.3                   pypi_0    pypi
pyyaml                    6.0                      pypi_0    pypi
requests                  2.31.0                   pypi_0    pypi
scipy                     1.10.1                   pypi_0    pypi
seaborn                   0.12.2                   pypi_0    pypi
sentry-sdk                1.24.0                   pypi_0    pypi
setuptools                66.0.0           py39haa95532_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
six                       1.16.0                   pypi_0    pypi
sqlite                    3.41.2               h2bbff1b_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
sympy                     1.12                     pypi_0    pypi
torch                     2.0.1                    pypi_0    pypi
torchvision               0.15.2                   pypi_0    pypi
tqdm                      4.65.0                   pypi_0    pypi
typing-extensions         4.6.1                    pypi_0    pypi
tzdata                    2023.3                   pypi_0    pypi
ultralytics               8.0.107                  pypi_0    pypi
urllib3                   1.26.16                  pypi_0    pypi
vc                        14.2                 h21ff451_1    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
vs2015_runtime            14.27.29016          h5e58377_2    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
wheel                     0.38.4           py39haa95532_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
zipp                      3.15.0                   pypi_0    pypi

参考(16条消息) Win10环境下yolov8快速配置与测试_FeiYull_的博客-CSDN博客https://blog.csdn.net/m0_72734364/article/details/128815530

和这篇 

(16条消息) win10下 yolov8 tensorrt模型加速部署【实战】_FeiYull_的博客-CSDN博客https://blog.csdn.net/m0_72734364/article/details/128865904?spm=1001.2101.3001.6650.1&utm_medium=distribute.pc_relevant.none-task-blog-2~default~CTRLIST~Rate-1-128865904-blog-129989402.235%5Ev36%5Epc_relevant_anti_vip&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2~default~CTRLIST~Rate-1-128865904-blog-129989402.235%5Ev36%5Epc_relevant_anti_vip&utm_relevant_index=2清华镜像源+英伟达pypi库

 
conda create -n yolov8 python=3.9 -y
conda activate yolov8
pip install ultralytics