code: def get_optuna_distributions(
      distributions: Dict[str, Distribution]
  ) -> dict:
      return {
          k: (v.get_optuna() if isinstance(v, Distribution) else v)
          for k, v in distributions.items()
      }
  
imports: from typing import Dict, Optional
  from scipy.stats import loguniform, randint, uniform
  from copy import copy
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: get_optuna_distributions(distributions) and returns: unknown