


'''simple docstring'''






import os
from collections import deque

import torch
from torch.utils.data import Dataset






class    __snake_case       (   _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    def __init__(   self    :  Optional[Any]    ,						lowerCamelCase    :  List[Any]=""    ,						lowerCamelCase    :  List[str]="train"		)   ->  Dict:
      assert os.path.isdir(lowerCamelCase		)

      lowerCAmelCase_			:      List[str]			=   []
      lowerCAmelCase_			:      List[str]			=   os.listdir(lowerCamelCase		)
      for story_filename in story_filenames_list:
        if "summary" in story_filename:
          continue
        lowerCAmelCase_			:      Dict			=   os.path.join(lowerCamelCase    ,						lowerCamelCase		)
        if not os.path.isfile(lowerCamelCase		):
          continue
        self.documents.append(lowerCamelCase		)

    def __len__(   self    :  Tuple		)   ->  Any:
      return len(self.documents		)





    def __getitem__(   self    :  Union[str, Any]    ,						lowerCamelCase    :  Union[str, Any]		)   ->  Dict:
      lowerCAmelCase_			:      Tuple			=   self.documents[idx]
      lowerCAmelCase_			:      Union[str, Any]			=   document_path.split("""/"""		)[-1]
      with open(lowerCamelCase    ,						encoding="""utf-8"""		) as source:
        lowerCAmelCase_			:      Any			=   source.read()
        lowerCAmelCase_,							lowerCAmelCase_			:      int			=   process_story(lowerCamelCase		)
      return document_name, story_lines, summary_lines







def 				UpperCamelCase_			(    A__					:   Any					):
  '''simple docstring'''





  lowerCAmelCase_			:      int			=   list(filter(lambda A__					: len(A__					) != 0							,    [line.strip() for line in raw_story.split("""\n"""					)]					)					)

  # for some unknown reason some lines miss a period, add it
  lowerCAmelCase_			:      str			=   [_add_missing_period(A__					) for line in nonempty_lines]

  # gather article lines
  lowerCAmelCase_			:      Union[str, Any]			=   []
  lowerCAmelCase_			:      List[Any]			=   deque(A__					)
  while True:
    try:
      lowerCAmelCase_			:      Any			=   lines.popleft()
      if element.startswith("""@highlight"""					):
        break
      story_lines.append(A__					)
    except IndexError:
      # if "@highlight" is absent from the file we pop
      # all elements until there is None, raising an exception.
      return story_lines, []

    # gather summary lines
  lowerCAmelCase_			:      Optional[int]			=   list(filter(lambda A__					: not t.startswith("""@highlight"""					)							,    A__					)					)

  return story_lines, summary_lines







def 				UpperCamelCase_			(    A__					:   Optional[int]					):
  '''simple docstring'''





  lowerCAmelCase_			:      Tuple			=   [""".""", """!""", """?""", """...""", """'""", """`""", """\"""", """\u2019""", """\u2019""", """)"""]
  if line.startswith("""@highlight"""					):
    return line
  if line[-1] in END_TOKENS:
    return line
  return line + "."







def 				UpperCamelCase_			(    A__					:   int							,    A__					:   Tuple							,    A__					:   str					):
  '''simple docstring'''





  if len(A__					) > block_size:
    return sequence[:block_size]
  else:
    sequence.extend([pad_token_id] * (block_size - len(A__					))					)
    return sequence







def 				UpperCamelCase_			(    A__					:   Dict							,    A__					:   List[Any]					):
  '''simple docstring'''





  lowerCAmelCase_			:      List[str]			=   torch.ones_like(A__					)
  lowerCAmelCase_			:      int			=   sequence == pad_token_id
  lowerCAmelCase_			:      Optional[Any]			=   0
  return mask







def 				UpperCamelCase_			(    A__					:   List[str]							,    A__					:   Dict							,    A__					:   List[str]					):
  '''simple docstring'''





  lowerCAmelCase_			:      Union[str, Any]			=   [tokenizer.encode(A__					) for line in story_lines]
  lowerCAmelCase_			:      Any			=   [token for sentence in story_lines_token_ids for token in sentence]
  lowerCAmelCase_			:      Tuple			=   [tokenizer.encode(A__					) for line in summary_lines]
  lowerCAmelCase_			:      Optional[Any]			=   [token for sentence in summary_lines_token_ids for token in sentence]

  return story_token_ids, summary_token_ids







def 				UpperCamelCase_			(    A__					:   Optional[Any]							,    A__					:   Dict					):
  '''simple docstring'''





  lowerCAmelCase_			:      List[Any]			=   []
  for sequence in batch:
    lowerCAmelCase_			:      str			=   -1
    lowerCAmelCase_			:      Tuple			=   []
    for s in sequence:
      if s == separator_token_id:
        sentence_num += 1
      embeddings.append(sentence_num % 2					)
    batch_embeddings.append(A__					)
  return torch.tensor(A__					)







'''simple docstring'''






def 				UpperCamelCase_			(    A__					:   str							,    A__					:   list[str]					):
  '''simple docstring'''





  lowerCAmelCase_			:      Dict			=   """"""
  for word_or_phrase in separated:
    if not isinstance(A__							,    A__					):
      raise Exception("""join() accepts only strings to be joined"""					)
    joined += word_or_phrase + separator
  return joined.strip(A__					)


if __name__ == "__main__":
  from doctest import testmod

  testmod()



