code: def _internal_ask_candidate(self) -> p.Parameter:
      # Inspired from FMinIter class (hyperopt)
      next_id = self.trials.new_trial_ids(1)
      new_trial = tpe.suggest(
          next_id,
          self.domain,
          self.trials,
          self._rng.randint(2**31 - 1),
          **self.tpe_args,
      )[0]
      self.trials.insert_trial_doc(new_trial)
      self.trials.refresh()
  
      candidate = self.parametrization.spawn_child()
  
      if self._transform:
          data = np.array(
              [
                  new_trial["misc"]["vals"][f"x_{i}"][0]
                  for i in range(self.dimension)
              ]
          )
          candidate = candidate.set_standardized_data(
              self._transform.backward(data)
          )
  
          # For consistency, we need to update hyperopt history
          # when standardized data is changed
          if any(
              data
              != self._transform.forward(
                  candidate.get_standardized_data(
                      reference=self.parametrization
                  )
              )
          ):
              for it, val in enumerate(
                  self._transform.forward(
                      candidate.get_standardized_data(
                          reference=self.parametrization
                      )
                  )
              ):
                  self.trials._dynamic_trials[next_id[0]]["misc"][
                      "vals"
                  ][f"x_{it}"][0] = val
      else:
          spec = hyperopt.base.spec_from_misc(new_trial["misc"])
          config = hyperopt.space_eval(self.space, spec)
          candidate.value = _hp_dict_to_parametrization(config)
  
      candidate._meta["trial_id"] = new_trial["tid"]
      return candidate
  
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 2 for calling the _HyperOpt obj's underlying member method code with example usage: obj._internal_ask_candidate() and returns: candidate