LethalDolphin75 Yes you are correct, we should add here:

https://github.com/allegroai/clearml/blob/400c6ec103d9f2193694c54d7491bb1a74bbe8e8/clearml/automation/optuna/optuna.py#L210`elif isinstance(p, UniformLogarithmicParameterRange): hp_type = 'suggest_float' hp_params = dict(low=p.min_value, high=p.max_value if p.include_max else p.max_value - p.step_size, log=True, step=p.step_size)`

btw: I'm not sure if the min/max values should be before or after log (i.e. low=log(p.min_value) or low=p.min_value )

I'm having another problem now because I am using the OptunaOptimizer.

Hey LethalDolphin75 , when it works, could you PR it?

I'm having another problem now because I am using the OptunaOptimizer.

Hmm let me check a sec

I was looking at optuna package and noticed that they raise this ValueError:`if step is not None: if log: raise ValueError("The parameter`

step`is not supported when`

log`is True.")`

So `step_size`

should always be `None`

And the low and high values are already the log value. For example it couldbe sth like `low=1e-6, high=1e-3`

; and not `low=-6, high=-3`

.

Looks great, nice solution and easy to implement, thanks!

Hi AgitatedDove14 , I made the PR: https://github.com/allegroai/clearml/pull/462 . Check it out and let me know. Thanks!

Hi LethalDolphin75

I think you are right there isn't one (although I remember a discussion about it...)

Anyhow it will be very easy to implement, just inherit from:

https://github.com/allegroai/clearml/blob/400c6ec103d9f2193694c54d7491bb1a74bbe8e8/clearml/automation/parameters.py#L111

And return the power of the parent value here:

https://github.com/allegroai/clearml/blob/400c6ec103d9f2193694c54d7491bb1a74bbe8e8/clearml/automation/parameters.py#L146

And

https://github.com/allegroai/clearml/blob/400c6ec103d9f2193694c54d7491bb1a74bbe8e8/clearml/automation/parameters.py#L158

Wdyt?