code: def load_model(self, tid, custom_objects=None):
          
          if tid is None:
              tid = self.best_trial_tid()
  
          model_path = self.get_trial(tid)["result"]["path"]["model"]
          return load_model(model_path, custom_objects=custom_objects)
docs: Load saved keras model of the trial.
  
          If tid = None, get the best model
  
          Not applicable for trials ran in cross validion (i.e. not applicable
          for `CompileFN.cv_n_folds is None`