
"""simple docstring"""







import os
from collections import deque

import torch
from torch.utils.data import Dataset




class 			A__	(     snake_case__):

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

   __lowerCAmelCase      :						Optional[Any]						      =				[]
   __lowerCAmelCase      :						List[Any]						      =				os.listdir(UpperCAmelCase_			)
   for story_filename in story_filenames_list:
    if "summary" in story_filename:
     continue
    __lowerCAmelCase      :						Dict						      =				os.path.join(UpperCAmelCase_	,		UpperCAmelCase_			)
    if not os.path.isfile(UpperCAmelCase_			):
     continue
    self.documents.append(UpperCAmelCase_			)

  def __len__(				self			):
   return len(self.documents			)







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



def    __lowerCAmelCase    (_UpperCamelCase		):
 __lowerCAmelCase      :						List[Any]						      =				list(filter(lambda _UpperCamelCase		: len(_UpperCAmelCase		) != 0	,  [line.strip() for line in raw_story.split('\n'		)]		)		)

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

 # gather article lines
 __lowerCAmelCase      :						Optional[Any]						      =				[]
 __lowerCAmelCase      :						Optional[int]						      =				deque(_UpperCAmelCase		)
 while True:
  try:
   __lowerCAmelCase      :						Dict						      =				lines.popleft()
   if element.startswith('@highlight'		):
    break
   story_lines.append(_UpperCAmelCase		)
  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
 __lowerCAmelCase      :						Union[str, Any]						      =				list(filter(lambda _UpperCamelCase		: not t.startswith('@highlight'		)	,  _UpperCAmelCase		)		)

 return story_lines, summary_lines
def    __lowerCAmelCase    (_UpperCamelCase		):
 __lowerCAmelCase      :						List[str]						      =				[".", "!", "?", "...", "'", "`", "\"", "\u2019", "\u2019", ")"]
 if line.startswith('@highlight'		):
  return line
 if line[-1] in END_TOKENS:
  return line
 return line + "."
def    __lowerCAmelCase    (_UpperCamelCase	,  _UpperCamelCase	,  _UpperCamelCase		):
 if len(_UpperCAmelCase		) > block_size:
  return sequence[:block_size]
 else:
  sequence.extend([pad_token_id] * (block_size - len(_UpperCAmelCase		))		)
  return sequence
def    __lowerCAmelCase    (_UpperCamelCase	,  _UpperCamelCase		):
 __lowerCAmelCase      :						Optional[int]						      =				torch.ones_like(_UpperCAmelCase		)
 __lowerCAmelCase      :						int						      =				sequence == pad_token_id
 __lowerCAmelCase      :						str						      =				0
 return mask
def    __lowerCAmelCase    (_UpperCamelCase	,  _UpperCamelCase	,  _UpperCamelCase		):
 __lowerCAmelCase      :						Optional[int]						      =				[tokenizer.encode(_UpperCAmelCase		) for line in story_lines]
 __lowerCAmelCase      :						Optional[Any]						      =				[token for sentence in story_lines_token_ids for token in sentence]
 __lowerCAmelCase      :						Optional[Any]						      =				[tokenizer.encode(_UpperCAmelCase		) for line in summary_lines]
 __lowerCAmelCase      :						Any						      =				[token for sentence in summary_lines_token_ids for token in sentence]

 return story_token_ids, summary_token_ids
def    __lowerCAmelCase    (_UpperCamelCase	,  _UpperCamelCase		):
 __lowerCAmelCase      :						Union[str, Any]						      =				[]
 for sequence in batch:
  __lowerCAmelCase      :						Union[str, Any]						      =				-1
  __lowerCAmelCase      :						Dict						      =				[]
  for s in sequence:
   if s == separator_token_id:
    sentence_num += 1
   embeddings.append(sentence_num % 2		)
  batch_embeddings.append(_UpperCAmelCase		)
 return torch.tensor(_UpperCAmelCase		)

"""simple docstring"""







def    __lowerCAmelCase    (_UpperCamelCase		):
	if len(_UpperCamelCase		) <= 1:
		return lst

	__lowerCAmelCase      :						str						      =				1

	while i < len(_UpperCamelCase		):
		if lst[i - 1] <= lst[i]:
			i += 1
		else:
			__lowerCAmelCase      ,       __lowerCAmelCase      :						List[Any]						      =				lst[i], lst[i - 1]
			i -= 1
			if i == 0:
				__lowerCAmelCase      :						int						      =				1

	return lst


if __name__ == "__main__":
							lowerCamelCase__        =		input("""Enter numbers separated by a comma:\n""").strip()
							lowerCamelCase__        =		[int(item) for item in user_input.split(""",""")]
							print(gnome_sort(unsorted))