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Answered
Hi All, I Was Trying To Use Clearml-Task To Run A Custom Docker(With Poetry To Install All The Python Dependencies And Activated The Environment) Using Clearml Gpu, But It Seems Like Clearml Always Create A Virtual Environment And Run The Python Script Fr

Hi all, I was trying to use clearml-task to run a custom docker(with poetry to install all the python dependencies and activated the environment) using clearml GPU, but it seems like clearml always create a virtual environment and run the python script from /root/.clearml/venvs-builds/3.10/bin/python . Is there a way that I can have the clearml-task to automatically activated a virtual environment use the activated custom virtual environment in my docker and run the scripts from there instead of always creating a new venv inheriting from the clearml system_site_packages? I noticed that clearml.conf has a configuration agent.docker_use_activated_venv , but I am not sure how to enable it from clearml-task

  
  
Posted one year ago
Votes Newest

Answers 38


None
See: Add an experiment hyperparameter:
and add gpu : True

  
  
Posted one year ago

I've added gpu:True to my hydra config file but the GPU is still not used

  
  
Posted one year ago

Not the file the UI

  
  
Posted one year ago

I see, like that?
image

  
  
Posted one year ago

image

  
  
Posted one year ago

That's the right place but
like you would use hydra --override, which in your case I think it should be "accelerator.gpu" ,

You can also change allow_omegaconf_editin the UI to True, and then you could just edit the OmegaConf in the UI (if you do not changeallow_omegaconf_edit` then the edit in the UI is ignored)

  
  
Posted one year ago

okay, when I run main.py on my local machine, I can use python main.py experiement=example.yaml to override acceleator to GPU option. But seems like the --args experiement=example.yaml in clearml-task didn't work so I have to manually modify it on UI?

clearml-task \
    --project fluoro-motion-detection \
    --name uniformer-test \
    --repo git@github.com:imperative-care-campbell/algorithms-python.git \
    --branch SW-956-Fluoro-Motion-Detection \
    --script fluoro_motion_detection/src/run/main.py \
    --args experiment=example.yaml \
    --docker mzhengtelos/algorithm-ml:pyenv \
    --docker_args "--env CLEARML_AGENT_SKIP_PIP_VENV_INSTALL=$PYTHON_ENV_DIR --env AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID --env AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY" \
    --queue test-gpu
  
  
Posted one year ago

I got the same cuda issue after being able to use GPU
image

  
  
Posted one year ago