




import os
from collections import deque

import torch
from torch.utils.data import Dataset

class     __a(	_a  ):






    """simple docstring"""





    def __init__( self  ,_SCREAMING_SNAKE_CASE=""  ,_SCREAMING_SNAKE_CASE="train"    )					->						Tuple:
         assert os.path.isdir(_SCREAMING_SNAKE_CASE    )

         UpperCAmelCase_     :				Dict  =     []
         UpperCAmelCase_     :				Union[str, Any]  =     os.listdir(_SCREAMING_SNAKE_CASE    )
         for story_filename in story_filenames_list:
              if "summary" in story_filename:
                   continue
              UpperCAmelCase_     :				int  =     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    )					->						Tuple:
         return len(self.documents    )





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







def lowerCamelCase__  (     _lowercase ):

     '''simple docstring'''


     UpperCAmelCase_     :				str  =     list(filter(lambda _lowercase : len(_lowercase ) != 0					,		[line.strip() for line in raw_story.split('''\n''' )] ) )

     # for some unknown reason some lines miss a period, add it
     UpperCAmelCase_     :				Union[str, Any]  =     [_add_missing_period(_lowercase ) for line in nonempty_lines]

     # gather article lines
     UpperCAmelCase_     :				Union[str, Any]  =     []
     UpperCAmelCase_     :				Any  =     deque(_lowercase )
     while True:
          try:
               UpperCAmelCase_     :				Union[str, Any]  =     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
     UpperCAmelCase_     :				int  =     list(filter(lambda _lowercase : not t.startswith('''@highlight''' )					,		_lowercase ) )

     return story_lines, summary_lines







def lowerCamelCase__  (     _lowercase ):

     '''simple docstring'''


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







def lowerCamelCase__  (     _lowercase					,		_lowercase					,		_lowercase ):

     '''simple docstring'''


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







def lowerCamelCase__  (     _lowercase					,		_lowercase ):

     '''simple docstring'''


     UpperCAmelCase_     :				Optional[Any]  =     torch.ones_like(_lowercase )
     UpperCAmelCase_     :				Tuple  =     sequence == pad_token_id
     UpperCAmelCase_     :				Union[str, Any]  =     0
     return mask







def lowerCamelCase__  (     _lowercase					,		_lowercase					,		_lowercase ):

     '''simple docstring'''


     UpperCAmelCase_     :				List[Any]  =     [tokenizer.encode(_lowercase ) for line in story_lines]
     UpperCAmelCase_     :				Tuple  =     [token for sentence in story_lines_token_ids for token in sentence]
     UpperCAmelCase_     :				int  =     [tokenizer.encode(_lowercase ) for line in summary_lines]
     UpperCAmelCase_     :				List[str]  =     [token for sentence in summary_lines_token_ids for token in sentence]

     return story_token_ids, summary_token_ids







def lowerCamelCase__  (     _lowercase					,		_lowercase ):

     '''simple docstring'''


     UpperCAmelCase_     :				List[Any]  =     []
     for sequence in batch:
          UpperCAmelCase_     :				str  =     -1
          UpperCAmelCase_     :				Optional[Any]  =     []
          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 )



"""simple docstring"""


import baseaa


def _lowerCamelCase      (						_UpperCamelCase ):

			'''simple docstring'''




			return baseaa.baaencode(string.encode("utf-8" ) )


def _lowerCamelCase      (						_UpperCamelCase ):

			'''simple docstring'''




			return baseaa.baadecode(_UpperCamelCase ).decode("utf-8" )


if __name__ == "__main__":
	A	:  List[str]            =     "Hello World!"
	A	:  Any            =     baseaa_encode(test)
	print(encoded)

	A	:  List[Any]            =     baseaa_decode(encoded)
	print(decoded)




