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Hi Everyone! I'Ve A Question Concerning The Integration With Optuna. I'Ve Been Able To Run The Hyperparameter Optimization Sample Successfully (

Hi everyone! I've a question concerning the integration with Optuna.
I've been able to run the hyperparameter optimization sample successfully ( None ), and the jobs are correctly added to the queue and run by the agents, however it looks like only the Random sampler is used, since sometimes multiple jobs are run with the same set of hyperparameters
How can I choose a different sampler?
None

  
  
Posted one year ago
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Answers 4


For example, when I use this set of hyperparameters:

DiscreteParameterRange('General/activation', values=["relu", "sigmoid"]),
UniformParameterRange('General/dropout_prob', min_value=0.1, max_value=0.2, step_size=0.1),
UniformIntegerParameterRange('General/n_epochs', min_value=5, max_value=15, step_size=5),

and set the total_max_jobs to 223=12, some combinations are not tried and some other are tried multiple times

  
  
Posted one year ago

Thanks ! Yeah, I finally figured it out by looking a bit more at the source code of the clearml package

  
  
Posted one year ago

Also in the source code of the Python module ( clearml/automation/optuna/optuna.py ) it looks like the behavior of randomly choosing a value between the specified limits is hardcoded. Is there a way to use a smarter/another sampler, like GridSampler for example to try every possible combination?

  
  
Posted one year ago

Hi @<1555000557775622144:profile|CharmingSealion31> ! When creating the HyperParameterOptimizer , pass the argument optuna_sampler=YOUR_SAMPLER .

  
  
Posted one year ago
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