Open jangwoopark opened 4 years ago
-Install anaconda for windows (google it). In it, install cudnn and cuda10. -Install wsl2 (if wsl1 is installed upgrade to wsl2 also can be googled to how to do it) -Create aliases in wsl2 for commands in ananconda in windows passing to GPU in windows (http://www.erogol.com/using-windows-wsl-for-deep-learning-development/) -Install NVIDIA drivers for windows along with nvidia-cuda-toolkit for windows (very big file) -Follow this (https://www.thomasmaurer.ch/2019/08/run-linux-containers-with-docker-desktop-and-wsl-2/) to install dockers for windows preview with wsl 2 to run dockers in wsl and powershell or cmd.
* Use either real vnc or tightvnc for windows. -The rest can be just followed what this repository does but in windows. -Enjoy in windows!
@jangwoopark with a lot of struggle I managed to run mine, but it seems it is using the CPU instead of the GPU. How did you manage to set it up? And the GUI doesn't work with Subsystem right? Thanks in advance!
If you created the aliases that invoke the windows python commands used by docker (run notepad.exe in wsl2 and you will see that it can invoke windows programs from the linux cli), it should use the GPU. The desktop docker provides the graphics which uses hyper-v which doesn't allow for wsl2 to export graphics. The nvidia drivers have to match your hardware.
-Install anaconda for windows (google it). In it, install cudnn and cuda10. -Install wsl2 (if wsl1 is installed upgrade to wsl2 also can be googled to how to do it) -Create aliases in wsl2 for commands in ananconda in windows passing to GPU in windows (http://www.erogol.com/using-windows-wsl-for-deep-learning-development/) -Install NVIDIA drivers for windows along with nvidia-cuda-toolkit for windows (very big file) -Follow this (https://www.thomasmaurer.ch/2019/08/run-linux-containers-with-docker-desktop-and-wsl-2/) to install dockers for windows preview with wsl 2 to run dockers in wsl and powershell or cmd.