50系列显卡运行paddleSeg项目推荐的paddlepaddle安装版本以及CUDA版本

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[2026/02/04 00:02:47] WARNING: Add the num_classes in train_dataset and val_dataset config to model config. We suggest you manually set num_classes in model config.
信息: 用提供的模式无法找到文件。
W0204 00:02:47.942577 68764 dynamic_loader.cc:285] Note: [Recommend] copy cudnn into CUDA installation directory.
For instance, download cudnn-10.0-windows10-x64-v7.6.5.32.zip from NVIDIA's official website,
then, unzip it and copy it into C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0
You should do this according to your CUDA installation directory and CUDNN version.
Traceback (most recent call last):
File "d:\3Dyixue\PaddleSeg-release-2.10\tools\train_yarn.py", line 252, in
main(args)
File "d:\3Dyixue\PaddleSeg-release-2.10\tools\train_yarn.py", line 177, in main
utils.show_env_info()
File "D:\3Dyixue\PaddleSeg-release-2.10\paddleseg\utils\utils.py", line 39, in show_env_info
env_info = get_sys_env()
File "D:\3Dyixue\PaddleSeg-release-2.10\paddleseg\utils\env\sys_env.py", line 102, in get_sys_env
v = paddle.get_cudnn_version()
File "C:\Users\WKY99.conda\envs\test\lib\site-packages\paddle\device_init_.py", line 179, in get_cudnn_version
cudnn_version = int(core.cudnn_version())
RuntimeError: (PreconditionNotMet) The third-party dynamic library (cudnn64_8.dll) that Paddle depends on is not configured correctly. (error code is 126)
Suggestions:

1. Check if the third-party dynamic library (e.g. CUDA, CUDNN) is installed correctly and its version is matched with paddlepaddle you installed.
2. Configure third-party dynamic library environment variables as follows:

• Linux: set LD_LIBRARY_PATH by export LD_LIBRARY_PATH=...
• Windows: set PATH by `set PATH=XXX; (at ..\paddle\phi\backends\dynload\dynamic_loader.cc:312)