class_docstr: A data structure that provides an interface to access nested dictionaries with "flattened keys", and a few more functions.
  
  e.g.
      dct = RecursiveDict({'a':{'b':2}})
      assert dct["a__b"] == 2
      dct["a__b__c"] = 3
      assert dct['a']['b']['c'] == dct["a__b__c"] == dct.to_flat_dict()["a__b__c"]
  
  This class serves as a base for HyperparameterSamples and HyperparameterSpace
class_docstr_tok: ["A","data","structure","that","provides","an","interface","to","access","nested","dictionaries","with","``","flattened","keys","''",",","and","a","few","more","functions",".","e.g",".","dct","=","RecursiveDict","(","{","'","a","'",":","{","'","b':2","}","}",")","assert","dct","[","``","a__b","''","]","==","2","dct","[","``","a__b__c","''","]","=","3","assert","dct","[","'","a","'","]","[","'","b","'","]","[","'","c","'","]","==","dct","[","``","a__b__c","''","]","==","dct.to_flat_dict","(",")","[","``","a__b__c","''","]","This","class","serves","as","a","base","for","HyperparameterSamples","and","HyperparameterSpace"]
code: def is_empty(self) -> bool:
      return len(self) == 0 or len(self.to_flat_dict()) == 0
  
imports: import typing
  from collections import Counter, OrderedDict, defaultdict
  from copy import copy
  from typing import Any, Dict, Iterable, List, Set, Union
  from neuraxle.hyperparams.distributions import FixedHyperparameter, HPSampledValue, HyperparameterDistribution
  from neuraxle.hyperparams.scipy_distributions import ScipyContinuousDistributionWrapper, ScipyDiscreteDistributionWrapper
  from scipy.stats import rv_continuous, rv_discrete
  from scipy.stats._distn_infrastructure import rv_generic
label_desc: Use image node_id 18 for calling the RecursiveDict obj's underlying member method code with example usage: obj.is_empty() and returns: unknown