
import os
from collections import deque

import torch
from torch.utils.data import Dataset

class __snake_case		(				lowerCAmelCase					):
    def __init__(  self		,snake_case=""		,snake_case="train"				):



           '''simple docstring'''







           assert os.path.isdir(snake_case				)

           lowercase							:					Tuple	     =				[]
           lowercase							:					str	     =				os.listdir(snake_case				)
           for story_filename in story_filenames_list:
                  if "summary" in story_filename:
                         continue
                  lowercase							:					Union[str, Any]	     =				os.path.join(snake_case		,snake_case				)
                  if not os.path.isfile(snake_case				):
                         continue
                  self.documents.append(snake_case				)
    def __len__(  self				):



           '''simple docstring'''







           return len(self.documents				)
    def __getitem__(  self		,snake_case				):



           '''simple docstring'''







           lowercase							:					Any	     =				self.documents[idx]
           lowercase							:					Union[str, Any]	     =				document_path.split("""/"""				)[-1]
           with open(snake_case		,encoding="""utf-8"""				) as source:
                  lowercase							:					Optional[int]	     =				source.read()
                  lowercase     ,      lowercase							:					List[Any]	     =				process_story(snake_case				)
           return document_name, story_lines, summary_lines







def 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   Any:
       lowercase							:					Any	     =				list(filter(lambda SCREAMING_SNAKE_CASE__    : len(SCREAMING_SNAKE_CASE__    ) != 0 ,     [line.strip() for line in raw_story.split("""\n"""    )]    )    )

       # for some unknown reason some lines miss a period, add it
       lowercase							:					Dict	     =				[_add_missing_period(SCREAMING_SNAKE_CASE__    ) for line in nonempty_lines]

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

       return story_lines, summary_lines







def 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   int:
       lowercase							:					Dict	     =				[""".""", """!""", """?""", """...""", """'""", """`""", """\"""", """\u2019""", """\u2019""", """)"""]
       if line.startswith("""@highlight"""    ):
              return line
       if line[-1] in END_TOKENS:
              return line
       return line + "."







def 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )			->   int:
       if len(SCREAMING_SNAKE_CASE__    ) > block_size:
              return sequence[:block_size]
       else:
              sequence.extend([pad_token_id] * (block_size - len(SCREAMING_SNAKE_CASE__    ))    )
              return sequence







def 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )			->   Tuple:
       lowercase							:					Union[str, Any]	     =				torch.ones_like(SCREAMING_SNAKE_CASE__    )
       lowercase							:					List[str]	     =				sequence == pad_token_id
       lowercase							:					Optional[Any]	     =				0
       return mask







def 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )			->   List[str]:
       lowercase							:					List[str]	     =				[tokenizer.encode(SCREAMING_SNAKE_CASE__    ) for line in story_lines]
       lowercase							:					Tuple	     =				[token for sentence in story_lines_token_ids for token in sentence]
       lowercase							:					Tuple	     =				[tokenizer.encode(SCREAMING_SNAKE_CASE__    ) for line in summary_lines]
       lowercase							:					Tuple	     =				[token for sentence in summary_lines_token_ids for token in sentence]

       return story_token_ids, summary_token_ids







def 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )			->   Optional[int]:
       lowercase							:					Optional[Any]	     =				[]
       for sequence in batch:
              lowercase							:					int	     =				-1
              lowercase							:					Optional[int]	     =				[]
              for s in sequence:
                     if s == separator_token_id:
                            sentence_num += 1
                     embeddings.append(sentence_num % 2    )
              batch_embeddings.append(SCREAMING_SNAKE_CASE__    )
       return torch.tensor(SCREAMING_SNAKE_CASE__    )


from __future__ import annotations

import numpy as np







def 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   tuple[np.ndarray, np.ndarray]:
       lowercase     ,      lowercase							:					Dict	     =				np.shape(SCREAMING_SNAKE_CASE__    )
       if rows != columns:
              lowercase							:					str	     =				(
                  """'table' has to be of square shaped array but got a """
                  f"{rows}x{columns} array:\n{table}"
              )
              raise ValueError(SCREAMING_SNAKE_CASE__    )

       lowercase							:					Any	     =				np.zeros((rows, columns)    )
       lowercase							:					int	     =				np.zeros((rows, columns)    )
       for i in range(SCREAMING_SNAKE_CASE__    ):
              for j in range(SCREAMING_SNAKE_CASE__    ):
                     lowercase							:					Optional[int]	     =				sum(lower[i][k] * upper[k][j] for k in range(SCREAMING_SNAKE_CASE__    )    )
                     if upper[j][j] == 0:
                            raise ArithmeticError("""No LU decomposition exists"""    )
                     lowercase							:					str	     =				(table[i][j] - total) / upper[j][j]
              lowercase							:					Optional[Any]	     =				1
              for j in range(SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    ):
                     lowercase							:					Any	     =				sum(lower[i][k] * upper[k][j] for k in range(SCREAMING_SNAKE_CASE__    )    )
                     lowercase							:					Tuple	     =				table[i][j] - total
       return lower, upper


if __name__ == "__main__":
  import doctest

  doctest.testmod()
