code: def set_reporter(self, reporter) -> None:
      super().set_reporter(reporter)
      if self._assign_reporter_function:
          self._assign_reporter_function(self._trainers, reporter)
      else:
          # By default, assume CompoundReporter with the same
          # number of reporters as trainers
          assert len(self._trainers) == len(
              reporter._reporters
          ), f"{len(self._trainers)} != {len(reporter._reporters)}"
          for t, r in zip(self._trainers, reporter._reporters):
              t.set_reporter(r)
  
imports: import bisect
  import functools
  import itertools
  from collections import OrderedDict
  from typing import Dict, List, Tuple
  import torch.nn
  from pytorch_lightning.loops.optimization.optimizer_loop import ClosureResult
  from reagent.core.utils import lazy_property
  from .reagent_lightning_module import ReAgentLightningModule
label_desc: Use image node_id 3 for calling the MultiStageTrainer obj's underlying member method code with example usage: obj.set_reporter(reporter) without return types