

'''simple docstring'''



import os
from collections import deque

import torch
from torch.utils.data import Dataset



class lowerCamelCase			(  a__						):



			'''simple docstring'''






			def __init__(				self	:						Dict		,      lowerCAmelCase_	:						int=""		,      lowerCAmelCase_	:						Optional[int]="train"			)      ->		Tuple:





									'''simple docstring'''
									assert os.path.isdir(SCREAMING_SNAKE_CASE_			)

									A__					:       Optional[int]     =[]
									A__					:       str     =os.listdir(SCREAMING_SNAKE_CASE_			)
									for story_filename in story_filenames_list:
															if "summary" in story_filename:
																					continue
															A__					:       List[Any]     =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	:						str			)      ->		List[Any]:





									'''simple docstring'''
									return len(self.documents			)



			def __getitem__(				self	:						Optional[Any]		,      lowerCAmelCase_	:						List[str]			)      ->		Optional[int]:





									'''simple docstring'''
									A__					:       Any     =self.documents[idx]
									A__					:       Tuple     =document_path.split("""/"""			)[-1]
									with open(SCREAMING_SNAKE_CASE_		,      encoding="""utf-8"""			) as source:
															A__					:       List[str]     =source.read()
															A__					:       str     =process_story(SCREAMING_SNAKE_CASE_			)
									return document_name, story_lines, summary_lines


def 						__lowerCamelCase	(       __snake_case					:		int	)	->							Optional[Any]:






						"""simple docstring"""





						A__					:       Union[str, Any]     =list(filter(lambda __snake_case	: len(snake_case__	) != 0,		[line.strip() for line in raw_story.split("""\n"""	)]	)	)

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

						# gather article lines
						A__					:       List[str]     =[]
						A__					:       Union[str, Any]     =deque(snake_case__	)
						while True:
												try:
																		A__					:       Tuple     =lines.popleft()
																		if element.startswith("""@highlight"""	):
																								break
																		story_lines.append(snake_case__	)
												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
						A__					:       List[str]     =list(filter(lambda __snake_case	: not t.startswith("""@highlight"""	),		snake_case__	)	)

						return story_lines, summary_lines
def 						__lowerCamelCase	(       __snake_case					:		Optional[Any]	)	->							Optional[Any]:






						"""simple docstring"""





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






						"""simple docstring"""





						if len(snake_case__	) > block_size:
												return sequence[:block_size]
						else:
												sequence.extend([pad_token_id] * (block_size - len(snake_case__	))	)
												return sequence
def 						__lowerCamelCase	(       __snake_case					:		Optional[Any],		__snake_case					:		Tuple	)	->							Union[str, Any]:






						"""simple docstring"""





						A__					:       Optional[Any]     =torch.ones_like(snake_case__	)
						A__					:       List[Any]     =sequence == pad_token_id
						A__					:       List[str]     =0
						return mask
def 						__lowerCamelCase	(       __snake_case					:		Optional[int],		__snake_case					:		str,		__snake_case					:		Optional[Any]	)	->							List[Any]:






						"""simple docstring"""





						A__					:       Dict     =[tokenizer.encode(snake_case__	) for line in story_lines]
						A__					:       Any     =[token for sentence in story_lines_token_ids for token in sentence]
						A__					:       Optional[int]     =[tokenizer.encode(snake_case__	) for line in summary_lines]
						A__					:       Any     =[token for sentence in summary_lines_token_ids for token in sentence]

						return story_token_ids, summary_token_ids
def 						__lowerCamelCase	(       __snake_case					:		Any,		__snake_case					:		Dict	)	->							str:






						"""simple docstring"""





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


'''simple docstring'''



from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def 						__lowerCamelCase	(       __snake_case					:		int	)	->							int:






						"""simple docstring"""





						A__					:       List[Any]     =prime_factors(__snake_case	)
						if is_square_free(__snake_case	):
												return -1 if len(__snake_case	) % 2 else 1
						return 0


if __name__ == "__main__":
		import doctest

		doctest.testmod()

