code: def training_step(
      self, batch, batch_idx: int, optimizer_idx: int = 0
  ):
      trainer_idx, offset = self._optimizer_step_to_trainer_idx[
          optimizer_idx
      ]
      epoch_trainer_idx = self._get_trainer_idx_from_epoch()
      assert (
          trainer_idx == epoch_trainer_idx
      ), f"Got {trainer_idx}; expected {epoch_trainer_idx}"
      return self._trainers[trainer_idx].training_step(
          batch, batch_idx, optimizer_idx - offset
      )
  
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 12 for calling the MultiStageTrainer obj's underlying member method code with example usage: obj.training_step(batch, batch_idx, optimizer_idx) and returns: self