Comments (1)
Hi @mikolajwojciuk !
Apologies for the slow reply. It looks like the issue is due to the evaluator_type
in GPyOpt, i.e. how GPyOpt chooses to evaluate concurrent trials. I didn't realize RF didn't work with local_penalization
which I had hardcoded as the option for the evaluator type. Unless you have otherwise resolved the issue, could you try setting max_concurrent=1
. That is, for your code:
algorithm = sherpa.algorithms.GPyOpt(model_type='RF',acquisition_type='MPI',verbosity=True,max_num_trials=8, max_concurrent=1)
In that case GPyOpt should ignore the setting. If that doesn't work, you could try going to this line
in your code and setting it toevaluator_type='random'
.
Thanks for raising the issue.
Best,
Lars
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