




import os
from collections import deque

import torch
from torch.utils.data import Dataset



class    lowercase_		(_a ):



						def __init__(			self	:   Dict					,							snake_case__	:   str=""					,							snake_case__	:   List[Any]="train"  ):

								"""simple docstring"""

								assert os.path.isdir(_SCREAMING_SNAKE_CASE  )

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



						def __len__(			self	:   Dict  ):

								"""simple docstring"""

								return len(self.documents  )






						def __getitem__(			self	:   List[Any]					,							snake_case__	:   List[Any]  ):

								"""simple docstring"""

								SCREAMING_SNAKE_CASE_					      =							self.documents[idx]
								SCREAMING_SNAKE_CASE_					      =							document_path.split('/'  )[-1]
								with open(_SCREAMING_SNAKE_CASE					,							encoding='utf-8'  ) as source:
										SCREAMING_SNAKE_CASE_					      =							source.read()
										SCREAMING_SNAKE_CASE_					      =							process_story(_SCREAMING_SNAKE_CASE  )
								return document_name, story_lines, summary_lines


def 					_a							(					lowerCAmelCase )->	List[str]:
		SCREAMING_SNAKE_CASE_					      =							list(filter(lambda lowerCAmelCase : len(_lowercase ) != 0    ,						[line.strip() for line in raw_story.split('\n' )] ) )

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

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

		return story_lines, summary_lines


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


def 					_a							(					lowerCAmelCase    ,						lowerCAmelCase    ,						lowerCAmelCase )->	str:


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


def 					_a							(					lowerCAmelCase    ,						lowerCAmelCase )->	List[Any]:
		SCREAMING_SNAKE_CASE_					      =							torch.ones_like(_lowercase )
		SCREAMING_SNAKE_CASE_					      =							sequence == pad_token_id
		SCREAMING_SNAKE_CASE_					      =							0
		return mask


def 					_a							(					lowerCAmelCase    ,						lowerCAmelCase    ,						lowerCAmelCase )->	Dict:
		SCREAMING_SNAKE_CASE_					      =							[tokenizer.encode(_lowercase ) for line in story_lines]
		SCREAMING_SNAKE_CASE_					      =							[token for sentence in story_lines_token_ids for token in sentence]
		SCREAMING_SNAKE_CASE_					      =							[tokenizer.encode(_lowercase ) for line in summary_lines]
		SCREAMING_SNAKE_CASE_					      =							[token for sentence in summary_lines_token_ids for token in sentence]

		return story_token_ids, summary_token_ids




def 					_a							(					lowerCAmelCase    ,						lowerCAmelCase )->	Union[str, Any]:
		SCREAMING_SNAKE_CASE_					      =							[]
		for sequence in batch:
				SCREAMING_SNAKE_CASE_					      =							-1
				SCREAMING_SNAKE_CASE_					      =							[]
				for s in sequence:
						if s == separator_token_id:
								sentence_num += 1
						embeddings.append(sentence_num % 2 )
				batch_embeddings.append(_lowercase )
		return torch.tensor(_lowercase )





def lowerCamelCase__  (     ):

     '''simple docstring'''


     UpperCAmelCase_     :				Dict  =     0
     for i in range(1					,		1001 ):
          total += i**i
     return str(_lowercase )[-10:]


if __name__ == "__main__":
     print(solution())