Xenos24R commented on issue #17887: URL: https://github.com/apache/incubator-mxnet/issues/17887#issuecomment-657008241
> Hi Xenos24R, > No, not really found a perfect solution. > I use a virtual env, so I implemented a little .bat script and I basically copy the DLL to Python packages dir: > > ``` > :begin > @echo off > @echo copy cuda libs > call copy /y "C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v9.2\\bin\\cublas64_92.dll" "C:\\.env38\\Lib\\site-packages\\mxnet" > call copy /y "C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v9.2\\bin\\curand64_92.dll" "C:\\.env38\\Lib\\site-packages\\mxnet" > call copy /y "C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v9.2\\bin\\cufft64_92.dll" "C:\\.env38\\Lib\\site-packages\\mxnet" > call copy /y "C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v9.2\\bin\\cusolver64_92.dll" "C:\\.env38\\Lib\\site-packages\\mxnet" > call copy /y "C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v9.2\\bin\\nvrtc64_92.dll" "C:\\.env38\\Lib\\site-packages\\mxnet" > @echo activate python env > call C:\.env38\Scripts\activate.bat > ``` > > Not ideal, but functional! > AL Hi alinagithub, Thank you for your reply.I think the problem may have been caused by a file path error in some configuration files due to the installation of both GPU and CPU versions of MXNET,and I solved the problem by creating a virtual environment. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
