class_docstr: A wrapper that allows to run TuRBO optimizer. Its arguments are described under smac.main.turbo.TuRBOSMBO
code: def _init_optimizer(
      self,
      length_init=0.8,
      length_min=0.5**8,
      length_max=1.6,
      success_tol=3,
      failure_tol_min=4,
      n_init_x_params=2,
      n_candidate_max=5000,
  ) -> None:
      self.optimizer = TuRBOSMBO(
          length_init=length_init,
          length_min=length_min,
          length_max=length_max,
          success_tol=success_tol,
          failure_tol_min=failure_tol_min,
          n_init_x_params=n_init_x_params,
          n_candidate_max=n_candidate_max,
          scenario=self._scenario,
          stats=self.stats,
          runner=self.runner,
          initial_design=self.initial_design,
          runhistory=self.runhistory,
          runhistory_encoder=self.runhistory_encoder,
          intensifier=self.intensifier,
          model=self.model,
          acquisition_function=self.acquisition_function,
          acquisition_optimizer=self.acquisition_optimizer,
          random_design=self.random_design,
          seed=self.seed,
      )
  
file_path: SMAC3/tests/test_main/_test_turbo.py
imports: import unittest
  import numpy
  from smac.facade.blackbox_facade import BlackBoxFacade
  from smac.main.turbo import TuRBOSMBO
  from smac.runhistory.runhistory import RunHistory
  from smac.runner.abstract_runner import StatusType
  from smac.scenario import Scenario
  from smac.utils import _test_helpers
label_desc: Use image node_id 1 for calling the TuRBOFacade obj's underlying member method code with example usage: obj._init_optimizer(length_init, length_min, length_max, success_tol, failure_tol_min, n_init_x_params, n_candidate_max) without return types