In my setting I have an abstract situation like the following, which shall only function as an example case: base = trial.suggest_int(1, 3) power = trial.suggest_int(1, 10) # value = base ** power As when the base == 1 the power parameter becomes irrelevant and I would like to fix it to 1. For example: base = trial.suggest_int("base", 1, 3) if base == 1: # Different distribution! But still inside the other. power = trial.suggest_int("power", 1, 1) else: power = trial.suggest_int("power", 1, 10) While this works it creates later problems in the form of ValueErrors because the underlying distributions are not the same. How can I suggest a fixed value with the same parameter name that depends on another value that is sampled within the trial? Continue reading...
