code: def extract_batch_size(batch: BType) -> int:
      """Unpack a batch to find a ``torch.Tensor``.
  
      Returns:
          ``len(tensor)`` when found, or ``1`` when it hits an empty or non iterable.
  
      """
      error_msg = (
          "We could not infer the batch_size from the batch. Either simplify its structure"
          " or provide the batch_size as `self.log(..., batch_size=batch_size)`."
      )
      batch_size = None
      try:
          for bs in _extract_batch_size(batch):
              if batch_size is None:
                  batch_size = bs
              elif batch_size != bs:
                  warning_cache.warn(
                      "Trying to infer the `batch_size` from an ambiguous collection. The batch size we"
                      f" found is {batch_size}. To avoid any miscalculations, use `self.log(..., batch_size=batch_size)`."
                  )
                  break
      except RecursionError:
          raise RecursionError(error_msg)
  
      if batch_size is None:
          raise MisconfigurationException(error_msg)
  
      return batch_size
  
imports: import inspect
  from dataclasses import fields
  from typing import Any, Dict, Generator, Iterable, Mapping, Optional, Sized, Tuple, Union
  import torch
  from lightning_utilities.core.apply_func import is_dataclass_instance
  from torch import Tensor
  from torch.utils.data import BatchSampler, DataLoader, IterableDataset, RandomSampler, Sampler, SequentialSampler
  from typing_extensions import TypeGuard
  import lightning.pytorch
  from lightning.fabric.utilities.data import _reinstantiate_wrapped_cls, _replace_value_in_saved_args, has_iterable_dataset, sized_len
  from lightning.pytorch.overrides.distributed import _IndexBatchSamplerWrapper
  from lightning.pytorch.trainer.states import RunningStage
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.rank_zero import WarningCache, rank_zero_warn
label_desc: Use image node_id 2 for calling a global function with example usage: extract_batch_size(batch) and returns: batch_size