Dockerfile/environment.yaml for CUDA Version 12.3?

[kajc10]

I have CUDA Version 12.3 and therefore the given pytorch configurations will not work.
I tried to adjust dependency versions, but could not create a working config setup. Could you help me out?

With the current environment.yaml I get stuck at 'initializing ddp: GLOBAL_RANK: 0, MEMBER: 1/1'

EDIT: solved by installing latest torch torchvision torchaudio and pillow==8.4.0

[froestiago]

Hi @kajc10
Do you mind sharing your yaml or docker file for this?
I need to train the model on a custom dataset and I'm having big trouble trying to adjust dependency versions, specially regarding pytorch-lightining.
Thanks!

[Han1018]

Hi @kajc10 , I faced same issue and how do you solve that.

[froestiago]

Hi @Han1018
I was able to make it work without any docker file, only using conda envs

After running conda env create -f environment.yaml; conda activate taming I uninstalled pytorch (torch and torchvision)
Then I installed the 1.8.1 + cu111 version pip install torch==1.8.1+cu111 torchvision==0.9.1+cu111 torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html
After that uninstalled pillow and reinstalled using pip install pillow==9.5.0.
I do not remember very well but you might come across an error regarding torch._six, if you do, replace from torch._six import string_classes with string_classes = str (reference)

Hope this helps 🤗

[Han1018]

Hi @froestiago, Thank you sososo much. It works for me and helps me save a lot of time !!!

[senp98]

Hi @Han1018 I was able to make it work without any docker file, only using conda envs

After running conda env create -f environment.yaml; conda activate taming I uninstalled pytorch (torch and torchvision) Then I installed the 1.8.1 + cu111 version pip install torch==1.8.1+cu111 torchvision==0.9.1+cu111 torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html After that uninstalled pillow and reinstalled using pip install pillow==9.5.0. I do not remember very well but you might come across an error regarding torch._six, if you do, replace from torch._six import string_classes with string_classes = str (reference)

Hope this helps 🤗

Somehow resolves my problem about the hanging training process. Thank you!!