Inference exception：exit code -1073740791 (0xC0000409)

[WZH13]

my environmental information:
02/26 16:33:52 - mmengine - INFO -

02/26 16:33:52 - mmengine - INFO - Environmental information
02/26 16:33:58 - mmengine - INFO - sys.platform: win32
02/26 16:33:58 - mmengine - INFO - Python: 3.8.20 (default, Oct 3 2024, 15:19:54) [MSC v.1929 64 bit (AMD64)]
02/26 16:33:58 - mmengine - INFO - CUDA available: True
02/26 16:33:58 - mmengine - INFO - MUSA available: False
02/26 16:33:58 - mmengine - INFO - numpy_random_seed: 2147483648
02/26 16:33:58 - mmengine - INFO - GPU 0: NVIDIA GeForce RTX 3060 Laptop GPU
02/26 16:33:58 - mmengine - INFO - CUDA_HOME: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7
02/26 16:33:58 - mmengine - INFO - NVCC: Cuda compilation tools, release 11.7, V11.7.64
02/26 16:33:58 - mmengine - INFO - MSVC: 用于 x64 的 Microsoft (R) C/C++ 优化编译器 19.42.34435 版
02/26 16:33:58 - mmengine - INFO - GCC: n/a
02/26 16:33:58 - mmengine - INFO - PyTorch: 2.0.1
02/26 16:33:58 - mmengine - INFO - PyTorch compiling details: PyTorch built with:

• C++ Version: 199711
• MSVC 193431937
• Intel(R) Math Kernel Library Version 2020.0.2 Product Build 20200624 for Intel(R) 64 architecture applications
• Intel(R) MKL-DNN v2.7.3 (Git Hash 6dbeffbae1f23cbbeae17adb7b5b13f1f37c080e)
• OpenMP 2019
• LAPACK is enabled (usually provided by MKL)
• CPU capability usage: AVX2
• CUDA Runtime 11.7
• NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_37,code=compute_37
• CuDNN 8.5
• Magma 2.5.4
• Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.7, CUDNN_VERSION=8.5.0, CXX_COMPILER=C:/cb/pytorch_1000000000000/work/tmp_bin/sccache-cl.exe, CXX_FLAGS=/DWIN32 /D_WINDOWS /GR /EHsc /w /bigobj /FS -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_DISABLE_GPU_ASSERTS=OFF, TORCH_VERSION=2.0.1, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=OFF, USE_OPENMP=ON, USE_ROCM=OFF,

02/26 16:33:58 - mmengine - INFO - TorchVision: 0.15.2
02/26 16:33:58 - mmengine - INFO - OpenCV: 4.11.0
02/26 16:33:58 - mmengine - INFO - MMEngine: 0.10.6
02/26 16:33:58 - mmengine - INFO - MMCV: 2.2.0
02/26 16:33:58 - mmengine - INFO - MMCV Compiler: MSVC 192930148
02/26 16:33:58 - mmengine - INFO - MMCV CUDA Compiler: 11.7
02/26 16:33:58 - mmengine - INFO - MMDeploy: 1.3.1+unknown
02/26 16:33:58 - mmengine - INFO -

02/26 16:33:58 - mmengine - INFO - Backend information
02/26 16:33:58 - mmengine - INFO - tensorrt: None
02/26 16:33:58 - mmengine - INFO - ONNXRuntime: None
02/26 16:33:58 - mmengine - INFO - ONNXRuntime-gpu: 1.15.1
02/26 16:33:58 - mmengine - INFO - ONNXRuntime custom ops: Available
02/26 16:33:58 - mmengine - INFO - pplnn: None
02/26 16:33:58 - mmengine - INFO - ncnn: None
02/26 16:33:58 - mmengine - INFO - snpe: None
02/26 16:33:58 - mmengine - INFO - openvino: None
02/26 16:33:58 - mmengine - INFO - torchscript: 2.0.1
02/26 16:33:58 - mmengine - INFO - torchscript custom ops: NotAvailable
02/26 16:33:58 - mmengine - INFO - rknn-toolkit: None
02/26 16:33:58 - mmengine - INFO - rknn-toolkit2: None
02/26 16:33:58 - mmengine - INFO - ascend: None
02/26 16:33:58 - mmengine - INFO - coreml: None
02/26 16:33:58 - mmengine - INFO - tvm: None
02/26 16:33:58 - mmengine - INFO - vacc: None
02/26 16:33:58 - mmengine - INFO -

02/26 16:33:58 - mmengine - INFO - Codebase information
02/26 16:33:58 - mmengine - INFO - mmdet: None
02/26 16:33:58 - mmengine - INFO - mmseg: None
02/26 16:33:58 - mmengine - INFO - mmpretrain: 1.2.0
02/26 16:33:58 - mmengine - INFO - mmocr: None
02/26 16:33:58 - mmengine - INFO - mmagic: None
02/26 16:33:58 - mmengine - INFO - mmdet3d: None
02/26 16:33:58 - mmengine - INFO - mmpose: None
02/26 16:33:58 - mmengine - INFO - mmrotate: None
02/26 16:33:58 - mmengine - INFO - mmaction: None
02/26 16:33:58 - mmengine - INFO - mmrazor: None
02/26 16:33:58 - mmengine - INFO - mmyolo: None

After exporting the ONNX model, the inference using mmdeploy-main/demo/python/image_classification.py failed, but no error messages or prompts are output.

The printed information:
D:\ProgramData\anaconda3\envs\OpenMMLab\python.exe E:\OpenMMLab\mmdeploy-main\demo\python\image_classification.py cuda E:\OpenMMLab\mmdeploy-main\output\StainClassification E:\OpenMMLab\mmpretrain-main\data\test\Stain_10.bmp 
loading mmdeploy_trt_net.dll ...
loading mmdeploy_ort_net.dll ...
[2025-02-26 16:35:47.679] [mmdeploy] [info] [model.cpp:35] [DirectoryModel] Load model: "E:\OpenMMLab\mmdeploy-main\output\StainClassification"

Process finished with exit code -1073740791 (0xC0000409)

[WZH13]

I have resolved this issue. The problem was caused by the absence of two files in CUDA: zlibwapi.lib and zlibwapi.dll. I downloaded these two files and placed them in the bin and lib directories of CUDA, which solved the problem.