old_contents: from torchtext.utils import (
      download_from_url,
      extract_archive,
  )
  from torchtext.data.datasets_utils import (
      _RawTextIterableDataset,
      _wrap_split_argument,
      _add_docstring_header,
      _find_match,
      _create_dataset_directory,
      _create_data_from_csv,
  )
  import os
  
  URL = 'https://drive.google.com/uc?export=download&id=0Bz8a_Dbh9QhbZlU4dXhHTFhZQU0'
  
  MD5 = 'f7ddfafed1033f68ec72b9267863af6c'
  
  NUM_LINES = {
      'train': 650000,
      'test': 50000,
  }
  
  _PATH = 'yelp_review_full_csv.tar.gz'
  
  DATASET_NAME = "YelpReviewFull"
  
  
  @_add_docstring_header(num_lines=NUM_LINES, num_classes=5)
  @_create_dataset_directory(dataset_name=DATASET_NAME)
  @_wrap_split_argument(('train', 'test'))
  def YelpReviewFull(root, split):
      dataset_tar = download_from_url(URL, root=root,
                                      path=os.path.join(root, _PATH),
                                      hash_value=MD5, hash_type='md5')
      extracted_files = extract_archive(dataset_tar)
  
      path = _find_match(split + '.csv', extracted_files)
      return _RawTextIterableDataset(DATASET_NAME, NUM_LINES[split],
                                     _create_data_from_csv(path))
  
new_contents: from torchtext._internal.module_utils import is_module_available
  from typing import Union, Tuple
  
  if is_module_available("torchdata"):
      from torchdata.datapipes.iter import FileOpener, GDriveReader, IterableWrapper
  
  from torchtext.data.datasets_utils import (
      _wrap_split_argument,
      _add_docstring_header,
      _create_dataset_directory,
  )
  
  import os
  
  URL = 'https://drive.google.com/uc?export=download&id=0Bz8a_Dbh9QhbZlU4dXhHTFhZQU0'
  
  MD5 = 'f7ddfafed1033f68ec72b9267863af6c'
  
  NUM_LINES = {
      'train': 650000,
      'test': 50000,
  }
  
  _PATH = 'yelp_review_full_csv.tar.gz'
  
  DATASET_NAME = "YelpReviewFull"
  
  _EXTRACTED_FILES = {
      'train': os.path.join('yelp_review_full_csv', 'train.csv'),
      'test': os.path.join('yelp_review_full_csv', 'test.csv'),
  }
  
  
  @_add_docstring_header(num_lines=NUM_LINES, num_classes=5)
  @_create_dataset_directory(dataset_name=DATASET_NAME)
  @_wrap_split_argument(('train', 'test'))
  def YelpReviewFull(root: str, split: Union[Tuple[str], str]):
      if not is_module_available("torchdata"):
          raise ModuleNotFoundError("Package `torchdata` not found. Please install following instructions at `https://github.com/pytorch/data`")
  
      url_dp = IterableWrapper([URL])
  
      cache_dp = url_dp.on_disk_cache(
          filepath_fn=lambda x: os.path.join(root, _PATH),
          hash_dict={os.path.join(root, _PATH): MD5}, hash_type="md5"
      )
      cache_dp = GDriveReader(cache_dp).end_caching(mode="wb", same_filepath_fn=True)
      cache_dp = FileOpener(cache_dp, mode="b")
  
      extracted_files = cache_dp.read_from_tar()
  
      filter_extracted_files = extracted_files.filter(lambda x: _EXTRACTED_FILES[split] in x[0])
  
      return filter_extracted_files.parse_csv().map(fn=lambda t: (int(t[0]), " ".join(t[1:])))
  
subject: migrate YelpReviewFull to datapipes. (#1507)