





'''simple docstring'''






import os
from collections import deque

import torch
from torch.utils.data import Dataset




class  UpperCAmelCase     (			snake_case_   ):




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

            _lowerCAmelCase							     =							[]
            _lowerCAmelCase							     =							os.listdir(__snake_case  )
            for story_filename in story_filenames_list:
                  if "summary" in story_filename:
                        continue
                  _lowerCAmelCase							     =							os.path.join(__snake_case			,			__snake_case  )
                  if not os.path.isfile(__snake_case  ):
                        continue
                  self.documents.append(__snake_case  )




      def __len__(			self			: str  )				->      List[Any]:
            return len(self.documents  )




      def __getitem__(			self			: List[Any]			,			__snake_case			: Dict  )				->      Dict:
            _lowerCAmelCase							     =							self.documents[idx]
            _lowerCAmelCase							     =							document_path.split("""/"""  )[-1]
            with open(__snake_case			,			encoding="""utf-8"""  ) as source:
                  _lowerCAmelCase							     =							source.read()
                  _lowerCAmelCase     ,							_lowerCAmelCase							     =							process_story(__snake_case  )
            return document_name, story_lines, summary_lines




def    UpperCamelCase__      (		lowerCAmelCase  ):





      """simple docstring"""


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

      # for some unknown reason some lines miss a period, add it
      _lowerCAmelCase							     =							[_add_missing_period(lowerCAmelCase  ) for line in nonempty_lines]

      # gather article lines
      _lowerCAmelCase							     =							[]
      _lowerCAmelCase							     =							deque(lowerCAmelCase  )
      while True:
            try:
                  _lowerCAmelCase							     =							lines.popleft()
                  if element.startswith("""@highlight"""  ):
                        break
                  story_lines.append(lowerCAmelCase  )
            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							     =							list(filter(lambda lowerCAmelCase  : not t.startswith("""@highlight"""  )							,	lowerCAmelCase  )  )

      return story_lines, summary_lines
def    UpperCamelCase__      (		lowerCAmelCase  ):





      """simple docstring"""


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





      """simple docstring"""


      if len(lowerCAmelCase  ) > block_size:
            return sequence[:block_size]
      else:
            sequence.extend([pad_token_id] * (block_size - len(lowerCAmelCase  ))  )
            return sequence
def    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase							     =							torch.ones_like(lowerCAmelCase  )
      _lowerCAmelCase							     =							sequence == pad_token_id
      _lowerCAmelCase							     =							0
      return mask
def    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase							,	lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase							     =							[tokenizer.encode(lowerCAmelCase  ) for line in story_lines]
      _lowerCAmelCase							     =							[token for sentence in story_lines_token_ids for token in sentence]
      _lowerCAmelCase							     =							[tokenizer.encode(lowerCAmelCase  ) for line in summary_lines]
      _lowerCAmelCase							     =							[token for sentence in summary_lines_token_ids for token in sentence]

      return story_token_ids, summary_token_ids





def    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase							     =							[]
      for sequence in batch:
            _lowerCAmelCase							     =							-1
            _lowerCAmelCase							     =							[]
            for s in sequence:
                  if s == separator_token_id:
                        sentence_num += 1
                  embeddings.append(sentence_num % 2  )
            batch_embeddings.append(lowerCAmelCase  )
      return torch.tensor(lowerCAmelCase  )








"""simple docstring"""




UpperCAmelCase__      :    Any    							= '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

UpperCAmelCase__      :    Any    							= [{'type': 'code', 'content': INSTALL_CONTENT}]
UpperCAmelCase__      :    Optional[int]    							= {
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}




