code: def __init__(self, preconfigured_hp_samples: HyperparameterSamples):
      self.preconfigured_hp_samples = preconfigured_hp_samples
  
imports: import copy
  import itertools
  import math
  import operator
  import random
  import warnings
  from abc import ABC, abstractmethod
  from collections import OrderedDict
  from functools import reduce
  from typing import Any, List, Set, Tuple
  from neuraxle.hyperparams.distributions import ContinuousHyperparameterDistribution, DiscreteHyperparameterDistribution
  from neuraxle.hyperparams.space import FlatDict, HyperparameterSamples, HyperparameterSpace
  from neuraxle.metaopt.data.reporting import RoundReport
label_desc: Use image node_id 1 to create a new HyperparameterSamplerStub object from inherited base classes: BaseHyperparameterOptimizer with example: obj = HyperparameterSamplerStub(preconfigured_hp_samples)