code: def _internal_provide_recommendation(
      self,
  ) -> tp.Optional[tp.ArrayLike]:
      if self.stupid:
          return self._internal_ask()
      elif self.archive:
          if self.recommendation_rule == "average_of_best":
              return avg_of_k_best(self.archive, "dimfourth")
          if self.recommendation_rule == "average_of_exp_best":
              return avg_of_k_best(self.archive, "exp")
          if self.recommendation_rule == "average_of_hull_best":
              return avg_of_k_best(self.archive, "hull")
      return None
  
imports: import copy
  import numpy
  from scipy.spatial import ConvexHull
  import nevergrad.common.typing
  from nevergrad.parametrization import parameter
  from nevergrad.parametrization import transforms
  from .None import sequences
  from .None import base
  from .base import IntOrParameter
  from .None import utils
label_desc: Use image node_id 3 for calling the _RandomSearch obj's underlying member method code with example usage: obj._internal_provide_recommendation() and returns: None, self, avg_of_k_best, avg_of_k_best, avg_of_k_best