code: def __iter__(self) -> Iterator[Union[Tuple[K, D], D]]:
      for mapping in self.datapipe:
          yield from iter(
              mapping.values() if self.drop_key else mapping.items()
          )
  
imports: import csv
  import functools
  import pathlib
  import pickle
  from typing import Any, BinaryIO, Callable, Dict, IO, Iterator, List, Sequence, Sized, Tuple, TypeVar, Union
  import torch
  import torch.distributed
  import torch.utils.data
  from torchdata.datapipes.iter import IoPathFileLister, IoPathFileOpener, IterDataPipe, ShardingFilter, Shuffler
  from torchvision.prototype.utils._internal import fromfile
label_desc: Use image node_id 2 for calling the MappingIterator obj's underlying member method code with example usage: obj.__iter__() without return types