code: def _try_combine_with_redispatch(self, observation, action):
      if (
          (
              observation.line_status[45] == False
              or observation.line_status[56] == False
          )
          and action != self.do_nothing_action
          and self.redispatch_cnt < self.max_redispatch_cnt
          and action.impact_on_objects()["topology"]["changed"]
      ):
          (
              obs_simulate,
              reward_simulate,
              done_simulate,
              info_simulate,
          ) = observation.simulate(action)
          observation._obs_env._reset_to_orig_state()
          assert (
              not info_simulate["is_illegal"]
              and not info_simulate["is_ambiguous"]
          )
  
          origin_rho = 10.0
          if not done_simulate:
              origin_rho = obs_simulate.rho.max()
  
          least_rho = origin_rho
          best_action = None
          for redispatch_action in self.redispatch_actions:
              combine_action = self.action_space.from_vect(
                  action.to_vect() + redispatch_action.to_vect()
              )
              (
                  obs_simulate,
                  reward_simulate,
                  done_simulate,
                  info_simulate,
              ) = observation.simulate(combine_action)
              observation._obs_env._reset_to_orig_state()
              assert (
                  not info_simulate["is_illegal"]
                  and not info_simulate["is_ambiguous"]
              )
  
              max_rho = 10.0
              if not done_simulate:
                  max_rho = obs_simulate.rho.max()
              if max_rho < least_rho:
                  least_rho = max_rho
                  best_action = combine_action
  
          if least_rho < origin_rho:
              action = best_action
              self.redispatch_cnt += 1
  
      return action
  
imports: import torch
  import numpy
  import pickle
  import os
  from grid2op.Agent import BaseAgent
  from copy import deepcopy
  from powernet_model import CombinedActionModel, UnitaryActionModel
  from utils import FeatureProcessor, UnitaryFeatureProcessor
label_desc: Use image node_id 5 for calling the RLAgent obj's underlying member method code with example usage: obj._try_combine_with_redispatch(observation, action) and returns: action