code: def _internal_tell_not_asked(
      self, candidate: p.Parameter, loss: float
  ) -> None:
      next_id = self.trials.new_trial_ids(1)
      new_trial = hyperopt.rand.suggest(
          next_id,
          self.domain,
          self.trials,
          self._rng.randint(2**31 - 1),
      )
      self.trials.insert_trial_docs(new_trial)
      self.trials.refresh()
      tid = next_id[0]
  
      if self._transform:
          data = candidate.get_standardized_data(
              reference=self.parametrization
          )
          data = self._transform.forward(data)
          self.trials._dynamic_trials[tid]["misc"]["vals"] = {
              f"x_{i}": [data[i]] for i in range(len(data))
          }
      else:
          null_config: dict = {
              k: []
              for k in self.trials._dynamic_trials[tid]["misc"][
                  "vals"
              ].keys()
          }
          new_vals: dict = _hp_parametrization_to_dict(
              candidate, default=null_config
          )
          self.trials._dynamic_trials[tid]["misc"]["vals"] = new_vals
  
      self.trials.refresh()
      candidate._meta["trial_id"] = tid
      self._internal_tell_candidate(candidate, loss)
  
imports: import numpy
  from .None import base
  from .base import IntOrParameter
  import nevergrad.common.typing
  from nevergrad.parametrization import transforms
  from nevergrad.parametrization import parameter
  import hyperopt
  from hyperopt import hp, Trials, Domain, tpe
label_desc: Use image node_id 4 for calling the _HyperOpt obj's underlying member method code with example usage: obj._internal_tell_not_asked(candidate, loss) without return types