code: def __init__(self, source_datapipe: IterDataPipe) -> None:
      super().__init__(source_datapipe)
      self.rank = 0
      self.world_size = 1
      if dist.is_available() and dist.is_initialized():
          self.rank = dist.get_rank()
          self.world_size = dist.get_world_size()
      self.apply_sharding(self.world_size, self.rank)
  
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 1 to create a new SharderDataPipe object from inherited base classes: ShardingFilter with example: obj = SharderDataPipe(source_datapipe)