code: def on_train_batch_start(self, batch, batch_idx, *args, **kwargs):
      return self.training_module.on_train_batch_start(
          batch, batch_idx, *args, **kwargs
      )
  
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 27 for calling the BaseOneShotLightningModule obj's underlying member method code with example usage: obj.on_train_batch_start(batch, batch_idx) and returns: self