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Hi, Trying To Understand Clearml-Session. I Have An Agent Running On A Machine Monitoring A Queue Then I Ran Clearml-Session --Queue Myqueu --Docker Torch-Image. The Clearml Session Ended Up Tunneling Into The Physical Machine That My Agent Is Running

Hi, trying to understand clearml-session.
I have an agent running on a machine monitoring a queue

Then I ran clearml-session --queue myqueu --docker torch-image.

The ClearML session ended up tunneling into the physical machine that my agent is running on, instead of establishing one with a container as specified. Is this correct behaviour?

  
  
Posted 3 years ago
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Answers 6


Hi SubstantialElk6

The ClearML session ended up tunneling into the physical machine that my agent is running on,

Yes that is the correct behavior. basically the clearml-session is using the agent to "schedule" a machine, then spin a container with JupyterLab/VSCode , and finally connect your CLI directly with that machine.
You can think of it as a way to solve the resource allocation problem.
Make sense ?

  
  
Posted 3 years ago

Hi, I was expecting to see the container rather then the actual physical machine. For example, in the file panel on the left of the jupyter panel, I see the file contents of the physical machine. I was expecting this to be the container.

  
  
Posted 3 years ago

Are you running the agent in docker mode ?
Is there a mount to the host machine ?

  
  
Posted 3 years ago

Dynamic GPU option only available with Enterprise version right?

Correct 🙂

  
  
Posted 3 years ago

Hi, I was expecting to see the container rather then the actual physical machine.

It is the container, it should tunnels directly into it. (or that's how it should be).
SSH port 10022

  
  
Posted 3 years ago

Hi it is missing --docker on the agent. Thanks! Dynamic GPU option only available with Enterprise version right?

  
  
Posted 3 years ago
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