cudaCheckError() failed : no kernel image is available for execution on the device

[897051629]

I donot know how to do this?

[ozym4nd145]

This may be because you are not exposing CUDA environment variables during compilation (running make.sh), in my case, I needed to set:

CUDA_VISIBLE_DEVICES=0
LD_LIBRARY_PATH=/usr/local/cuda-80/lib64:$LD_LIBRARY_PATH
PATH=/usr/local/cuda-80/bin:$PATH

Also, do make sure that you are setting the correct architecture in build script ( in my case it was sm60 ).

[eyildiz-ugoe]

I fixed this error by removing the comment which was preventing my architecture (sm70) to be included in the build script.

[fatihbaltaci]

https://github.com/roytseng-tw/Detectron.pytorch/blob/1b1c4ba58428b7277a45b0dce6cc1bce3744b86a/lib/make.sh#L15

Uncomment this line. This is a compatibility issue for Turing architecture GPUs (e.g RTX20**). See:

https://docs.nvidia.com/cuda/turing-compatibility-guide/index.html

[konstantin-frolov]

Hi. I have same problem with pytorch 1.4.0, cudatoolkit 10.1 and Tesla K20c I downgraded pytorch, cudatoolkit and cuda drivers. I just uninstall pytorch, cudatoolkit and torchvision from conda conda uninstall pytorch cudatoolkit torchvision Reinstall drivers for Tesla with cuda version 10.1 Install Pytorch 1.2.0, cudatoolkit 10.0, torchvision 0.4.0 It's works for me.