

import itertools
import os
import re


lowercase			:				List[Any]   =     re.compile(r"([A-Z]+)([A-Z][a-z])")
lowercase			:				str   =     re.compile(r"([a-z\d])([A-Z])")

lowercase			:				Tuple   =     re.compile(r"(?<!_)_(?!_)")
lowercase			:				Union[str, Any]   =     re.compile(r"(_{2,})")

lowercase			:				Dict   =     r"^\w+(\.\w+)*$"

lowercase			:				List[str]   =     r"<>:/\|?*"






def        snake_case__		(    lowerCamelCase_		):
							A      :					Any      		=					_uppercase_uppercase_re.sub(r'''\1_\2'''     ,				lowerCamelCase_		)
							A      :					Any      		=					_lowercase_uppercase_re.sub(r'''\1_\2'''     ,				lowerCamelCase_		)
							return name.lower()






def        snake_case__		(    lowerCamelCase_		):
							A      :					str      		=					_single_underscore_re.split(lowerCamelCase_		)
							A      :					Dict      		=					[_multiple_underscores_re.split(lowerCamelCase_		) for n in name]
							return "".join(n.capitalize() for n in itertools.chain.from_iterable(lowerCamelCase_		) if n != ''''''		)






def        snake_case__		(    lowerCamelCase_		):
							if os.path.basename(lowerCamelCase_		) != name:
														raise ValueError(F'Should be a dataset name, not a path: {name}'		)
							return camelcase_to_snakecase(lowerCamelCase_		)






def        snake_case__		(    lowerCamelCase_     ,				lowerCamelCase_		):
							if os.path.basename(lowerCamelCase_		) != name:
														raise ValueError(F'Should be a dataset name, not a path: {name}'		)
							if not re.match(_split_re     ,				lowerCamelCase_		):
														raise ValueError(F'Split name should match \'{_split_re}\'\' but got \'{split}\'.'		)
							return F'{filename_prefix_for_name(lowerCamelCase_		)}-{split}'






def        snake_case__		(    lowerCamelCase_     ,				lowerCamelCase_     ,				lowerCamelCase_     ,				lowerCamelCase_=None		):
							A      :					str      		=					filename_prefix_for_split(lowerCamelCase_     ,				lowerCamelCase_		)
							if filetype_suffix:
														prefix += F'.{filetype_suffix}'
							A      :					Optional[Any]      		=					os.path.join(lowerCamelCase_     ,				lowerCamelCase_		)
							return F'{filepath}*'






def        snake_case__		(    lowerCamelCase_     ,				lowerCamelCase_     ,				lowerCamelCase_     ,				lowerCamelCase_=None     ,				lowerCamelCase_=None		):
							A      :					int      		=					filename_prefix_for_split(lowerCamelCase_     ,				lowerCamelCase_		)
							A      :					Optional[int]      		=					os.path.join(lowerCamelCase_     ,				lowerCamelCase_		)

							if shard_lengths:
														A      :					Optional[int]      		=					len(lowerCamelCase_		)
														A      :					Optional[int]      		=					[F'{prefix}-{shard_id:05d}-of-{num_shards:05d}' for shard_id in range(lowerCamelCase_		)]
														if filetype_suffix:
																					A      :					List[Any]      		=					[filename + F'.{filetype_suffix}' for filename in filenames]
														return filenames
							else:
														A      :					Tuple      		=					prefix
														if filetype_suffix:
																					filename += F'.{filetype_suffix}'
														return [filename]







"""simple docstring"""



import os
from collections import deque

import torch
from torch.utils.data import Dataset
class 						__UpperCAmelCase    (__A     ):







			'''simple docstring'''





			def __init__(			self   ,      snake_case_=""   ,      snake_case_="train"							):







										'''simple docstring'''


										assert os.path.isdir(snake_case_							)

										A__       :     Dict								=			[]
										A__       :     Optional[Any]								=			os.listdir(snake_case_							)
										for story_filename in story_filenames_list:
																	if "summary" in story_filename:
																								continue
																	A__       :     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'''


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





def  _A(		lowerCAmelCase							):
							A__       :     Optional[int]								=			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
							A__       :     List[str]								=			[_add_missing_period(lowerCAmelCase							) for line in nonempty_lines]

							# gather article lines
							A__       :     Union[str, Any]								=			[]
							A__       :     Optional[Any]								=			deque(lowerCAmelCase							)
							while True:
														try:
																					A__       :     List[str]								=			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
							A__       :     List[str]								=			list(filter(lambda lowerCAmelCase							: not t.startswith("""@highlight"""							)			,  lowerCAmelCase							)							)

							return story_lines, summary_lines

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

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

def  _A(		lowerCAmelCase			,  lowerCAmelCase							):
							A__       :     Any								=			torch.ones_like(lowerCAmelCase							)
							A__       :     Any								=			sequence == pad_token_id
							A__       :     Any								=			0
							return mask

def  _A(		lowerCAmelCase			,  lowerCAmelCase			,  lowerCAmelCase							):
							A__       :     Dict								=			[tokenizer.encode(lowerCAmelCase							) for line in story_lines]
							A__       :     Any								=			[token for sentence in story_lines_token_ids for token in sentence]
							A__       :     List[str]								=			[tokenizer.encode(lowerCAmelCase							) for line in summary_lines]
							A__       :     int								=			[token for sentence in summary_lines_token_ids for token in sentence]

							return story_token_ids, summary_token_ids



def  _A(		lowerCAmelCase			,  lowerCAmelCase							):
							A__       :     str								=			[]
							for sequence in batch:
														A__       :     List[Any]								=			-1
														A__       :     Dict								=			[]
														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							)





