code: def _wrap_collate(collate: Callable, batch: List[Any]) -> Any:
      # Needed for learn2learn integration
      if len(batch) == 1 and isinstance(batch[0], list):
          batch = batch[0]
  
      metadata = [
          sample.pop(DataKeys.METADATA, None)
          if isinstance(sample, Mapping)
          else None
          for sample in batch
      ]
      metadata = (
          metadata if any(m is not None for m in metadata) else None
      )
  
      collated_batch = collate(batch)
  
      if metadata and isinstance(collated_batch, dict):
          collated_batch[DataKeys.METADATA] = metadata
      return collated_batch
  
imports: import functools
  from typing import Any, Callable, List, Mapping
  from torch.utils.data._utils.collate import default_collate
  from flash.core.data.io.input import DataKeys
label_desc: Use image node_id 1 for calling a global function with example usage: _wrap_collate(collate, batch) and returns: collated_batch