class_docstr: Experimental evolution-strategy-like algorithm
  The behavior is going to evolve
class_docstr_tok: ["Experimental","evolution-strategy-like","algorithm","The","behavior","is","going","to","evolve"]
code: def _select(self) -> None:
      choices = self._waiting + (
          []
          if self._config.only_offsprings
          else list(self._population.values())
      )
      if self._rank_method is not None and self.num_objectives > 1:
          choices_rank = self._rank_method(
              choices, n_selected=self._config.popsize
          )
          choices = [x for x in choices if x.uid in choices_rank]
      else:
          choices.sort(key=base._loss)
      self._population = {
          x.uid: x for x in choices[: self._config.popsize]
      }
      self._uid_queue.clear()
      self._waiting.clear()
      for uid in self._population:
          self._uid_queue.tell(uid)
  
file_path: nevergrad/nevergrad/optimization/es.py
imports: import warnings
  import nevergrad.common.typing
  from nevergrad.parametrization import parameter
  from nevergrad.optimization.utils import UidQueue
  from .None import base
  from .multiobjective import nsga2
label_desc: Use image node_id 4 for calling the _EvolutionStrategy obj's underlying member method code with example usage: obj._select() without return types