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_tell_candidate(
      self, candidate: p.Parameter, loss: float
  ) -> None:
      if self._config.offsprings is None:
          uid = candidate.heritage["lineage"]
          self._uid_queue.tell(uid)
          parent_value = (
              float("inf")
              if uid not in self._population
              else base._loss(self._population[uid])
          )
          if loss < parent_value:
              self._population[uid] = candidate
      else:
          no_parent = (
              next(iter(candidate.parents_uids), "#no_parent#")
              not in self._population
          )
          if no_parent and len(self._population) < self._config.popsize:
              self._population[candidate.uid] = candidate
              self._uid_queue.tell(candidate.uid)
          else:
              self._waiting.append(candidate)
          if len(self._waiting) >= self._config.offsprings:
              self._select()
  
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 3 for calling the _EvolutionStrategy obj's underlying member method code with example usage: obj._internal_tell_candidate(candidate, loss) without return types