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Answered
Hey Community! I Have A Question Regarding The Optuna Optimizer With Clearml. I'M Using A Config Yaml File That I'M Connecting Via

Hey community! I have a question regarding the Optuna optimizer with ClearML.
I'm using a config yaml file that I'm connecting via task.connect_configuration . When a job is started, the file is parsed and parameters are used from there.

Now I am in the process of implementing a hyperparameter search, where ClearML is spawning new trainings:

hyper_parameters=[
            UniformParameterRange(
                "training/optimizer/lr",
                min_value=0.00025,
                max_value=0.01,
                step_size=0.00025,
            ),
        ],

These hyperpaters are now in the "Args" section of my Clearml task, how can I get them into the connected config file to be used correctly?

  
  
Posted 10 months ago
Votes Newest

Answers 4


The optimizer part works out of the box, yes. But my training is usually consuming a yaml file with parameters and not via argparse. This is the part I had to adjust

  
  
Posted 10 months ago

Hi @<1547390438648844288:profile|ScaryJellyfish75>

These hyperpaters are now in the "Args" section of my Clearml task

Sure that would probably mean

UniformParameterRange(
                "Args/training/optimizer/lr",
                min_value=0.00025,
                max_value=0.01,
                step_size=0.00025,
            ),

assuming your Task has training/optimizer/lr in its Args section (under configuration tab), make sense ?

  
  
Posted 10 months ago

Yes that makes sense. I solved it by actively reading them via Task.parameters. Now that works, I just had to adjust the config parser a bit

  
  
Posted 10 months ago

Well it should work out if the box as long as you have the full route, i.e. Section/param

  
  
Posted 10 months ago