code: def _optimizer_step_to_trainer_idx(
      self,
  ) -> Dict[int, Tuple[int, int]]:
      mapping = {}
      offset = 0
  
      for i, t in enumerate(self._trainers):
          num_optimizing_steps = t._num_optimizing_steps
          for j in range(num_optimizing_steps):
              mapping[offset + j] = (i, offset)
          offset += num_optimizing_steps
  
      return mapping
  
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 4 for calling the MultiStageTrainer obj's underlying member method code with example usage: obj._optimizer_step_to_trainer_idx() and returns: mapping