hi, @ptrblck
I have some confusion about CUDA compatibility.
We have a NVIDIA A10 GPU,
and nvidia-smi  shows ( NVIDIA-SMI 470.57.02    Driver Version: 470.57.02    CUDA Version: 11.4)
We install pytorch with pip method. below wheel pkgs
torch-1.3.0%2Bcu100-cp37-cp37m-linux_x86_64.whl
torchvision-0.4.1%2Bcu100-cp37-cp37m-linux_x86_64.whl
should torch-1.3.0+cu100 be compatible with my gpu driver version?
When we run below python code, it takes about  too long time(more than 8 minutes) to finish. we find cpu 100% using top command.  So why does it cost so long time?
import torch
torch.Tensor([1,2]).cuda()

And with some other torch code like torch.relu_(input), it encounters errors ?
RuntimeError: CUDA error: no kernel image is available for execution on the device