code: def __iter__(self) -> Iterator[Any]:
      num_workers = self.world_size
      worker_info = torch.utils.data.get_worker_info()
      if worker_info is not None:
          num_workers *= worker_info.num_workers
  
      # TODO: this is weird as it drops more elements than it should
      num_take = self.num_take // num_workers
  
      for i, data in enumerate(self.source_datapipe):
          if i < num_take:
              yield data
          else:
              break
  
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 TakerDataPipe obj's underlying member method code with example usage: obj.__iter__() without return types