code: def setup(
      self, stage: str = cast(str, None)
  ):  # add default value to be backward-compatible
      # redirect the access to trainer/log to this module
      # but note that we might be missing other attributes,
      # which could potentially be a problem
      self.training_module.trainer = self.trainer  # type: ignore
      self.training_module.log = self.log
  
      # Reset the optimizer progress (only once at the very beginning)
      self._optimizer_progress = 0
  
      return self.training_module.setup(stage)
  
imports: from __future__ import annotations
  import warnings
  from typing import Any, Iterable, List, cast, TYPE_CHECKING
  import torch.optim
  import torch.nn
  from torch.optim import Optimizer
  import nni.nas.nn.pytorch
  from nni.nas.evaluator.pytorch import LightningModule, Trainer
  from nni.mutable import Sample
  from .supermodule.base import BaseSuperNetModule
label_desc: Use image node_id 12 for calling the BaseOneShotLightningModule obj's underlying member method code with example usage: obj.setup(stage) and returns: self