Bug: atpe Exception: assert np.all(sigma > 0) fail in adaptive_normal_parzen in tpe.py

[DWDuq]

My fmin call generates the following exception on line 456 in adaptive_normal_parzen: AssertionError: (nan, 0.32894072757057796, 9.210340371976184). I've traced this error back a few levels to -inf values in the memo variable of rec_eval() in base.py. Looking at my trials variable shows no invalid values for ['result']['loss'] or ['result']['loss_variance'] and so I suspect they are being generated from hyperopt code.

I do use generate_trials_to_calculate() to set an initial set of default parameters to evaluate and I'm not sure I did it correctly because doing so required me to specify values for parameters that are inactive due to choice parameter values. Also, if that were the problem I would expect the issue to show up sooner than on the 57th set of parameters.

I'm using hyperopt 0.2.7.

[github-actions]

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