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 _internal_ask_candidate(self) -> p.Parameter:
      if self.num_ask < self._config.popsize:
          param = self.parametrization.sample()
          assert (
              param.uid == param.heritage["lineage"]
          )  # this is an assumption used below
          self._uid_queue.asked.add(param.uid)
          self._population[param.uid] = param
          return param
      uid = self._uid_queue.ask()
      param = self._population[uid].spawn_child()
      param.mutate()
      ratio = self._config.recombination_ratio
      if ratio and self._rng.rand() < ratio:
          selected = self._rng.choice(list(self._population))
          param.recombine(self._population[selected])
      return param
  
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 2 for calling the _EvolutionStrategy obj's underlying member method code with example usage: obj._internal_ask_candidate() and returns: param, param