code: def search(self, nth_process, p_bar):
      self._setup_process(nth_process)
  
      gfo_wrapper_model = ObjectiveFunction(
          objective_function=self.objective_function,
          optimizer=self.gfo_optimizer,
          callbacks=self.callbacks,
          catch=self.catch,
          nth_process=self.nth_process,
      )
      gfo_wrapper_model.pass_through = self.pass_through
  
      memory_warm_start = self.hg_conv.conv_memory_warm_start(
          self.memory_warm_start
      )
  
      gfo_objective_function = gfo_wrapper_model(self.s_space())
  
      self.gfo_optimizer.init_search(
          gfo_objective_function,
          self.n_iter,
          self.max_time,
          self.max_score,
          self.early_stopping,
          self.memory,
          memory_warm_start,
          False,
      )
      for nth_iter in range(self.n_iter):
          if p_bar:
              p_bar.set_description(
                  "["
                  + str(nth_process)
                  + "] "
                  + str(self.objective_function.__name__)
                  + " ("
                  + self.optimizer_class.name
                  + ")",
              )
  
          self.gfo_optimizer.search_step(nth_iter)
          if self.gfo_optimizer.stop.check():
              break
  
          if p_bar:
              p_bar.set_postfix(
                  best_score=str(
                      gfo_wrapper_model.optimizer.score_best
                  ),
                  best_pos=str(gfo_wrapper_model.optimizer.pos_best),
                  best_iter=str(
                      gfo_wrapper_model.optimizer.p_bar._best_since_iter
                  ),
              )
  
              p_bar.update(1)
              p_bar.refresh()
  
      self.gfo_optimizer.finish_search()
  
      self.convert_results2hyper()
  
      self._add_result_attributes(
          self.best_para,
          self.best_score,
          self.gfo_optimizer.p_bar._best_since_iter,
          self.eval_times,
          self.iter_times,
          self.search_data,
          self.gfo_optimizer.random_seed,
      )
  
file_path: Hyperactive/hyperactive/optimizers/hyper_optimizer.py
imports: import numpy
  from .objective_function import ObjectiveFunction
  from .hyper_gradient_conv import HyperGradientConv
  from .optimizer_attributes import OptimizerAttributes
  from .constraint import Constraint
label_desc: Use image node_id 5 for calling the HyperOptimizer obj's underlying member method code with example usage: obj.search(nth_process, p_bar) without return types