





def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:Tuple   )      ->   int:
 if not head:
  return True
 # split the list to two parts
 __lowerCAmelCase ,					__lowerCAmelCase					:	Optional[int]      =       head.next, head
 while fast and fast.next:
  __lowerCAmelCase					:	Any      =       fast.next.next
  __lowerCAmelCase					:	Tuple      =       slow.next
 __lowerCAmelCase					:	Union[str, Any]      =       slow.next
 __lowerCAmelCase					:	Optional[int]      =       None  # Don't forget here! But forget still works!
 # reverse the second part
 __lowerCAmelCase					:	Tuple      =       None
 while second:
  __lowerCAmelCase					:	int      =       second.next
  __lowerCAmelCase					:	Optional[Any]      =       node
  __lowerCAmelCase					:	List[str]      =       second
  __lowerCAmelCase					:	Optional[Any]      =       nxt
 # compare two parts
 # second part has the same or one less node
 while node:
  if node.val != head.val:
   return False
  __lowerCAmelCase					:	Any      =       node.next
  __lowerCAmelCase					:	Optional[int]      =       head.next
 return True






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:List[Any]   )      ->   List[Any]:
 if not head or not head.next:
  return True

 # 1. Get the midpoint (slow)
 __lowerCAmelCase					:	str      =       head
 while fast and fast.next:
  __lowerCAmelCase ,					__lowerCAmelCase					:	List[Any]      =       fast.next.next, slow.next

 # 2. Push the second half into the stack
 __lowerCAmelCase					:	Optional[Any]      =       [slow.val]
 while slow.next:
  __lowerCAmelCase					:	List[str]      =       slow.next
  stack.append(slow.val   )

 # 3. Comparison
 while stack:
  if stack.pop() != cur.val:
   return False
  __lowerCAmelCase					:	Optional[int]      =       cur.next

 return True







def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:Optional[int]   )      ->   Dict:
 if not head or not head.next:
  return True
 __lowerCAmelCase					:	List[str]      =       {}
 __lowerCAmelCase					:	str      =       0
 while head:
  if head.val in d:
   d[head.val].append(SCREAMING_SNAKE_CASE   )
  else:
   __lowerCAmelCase					:	Optional[Any]      =       [pos]
  __lowerCAmelCase					:	Any      =       head.next
  pos += 1
 __lowerCAmelCase					:	List[str]      =       pos - 1
 __lowerCAmelCase					:	int      =       0
 for v in d.values():
  if len(SCREAMING_SNAKE_CASE   ) % 2 != 0:
   middle += 1
  else:
   __lowerCAmelCase					:	int      =       0
   for i in range(0   ,   len(SCREAMING_SNAKE_CASE   )   ):
    if v[i] + v[len(SCREAMING_SNAKE_CASE   ) - 1 - step] != checksum:
     return False
    step += 1
  if middle > 1:
   return False
 return True






import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_UpperCAmelCase             =							'▁'

_UpperCAmelCase             =							{'vocab_file': 'spiece.model'}

_UpperCAmelCase             =							{
    'vocab_file': {'google/pegasus-xsum': 'https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model'}
}

_UpperCAmelCase             =							{
    'google/pegasus-xsum': 512,
}


_UpperCAmelCase             =							logging.get_logger(__name__)






class        snake_case_    (		__lowercase						):
  A_      							=   VOCAB_FILES_NAMES

  A_      							=   VOCAB_FILES_NAMES
  A_      							=   PRETRAINED_VOCAB_FILES_MAP
  A_      							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  A_      							=   ['input_ids', 'attention_mask']






  def __init__(							self			:					List[Any]       ,  _snake_case			:					Union[str, Any]       ,  _snake_case			:					Union[str, Any]="<pad>"       ,  _snake_case			:					int="</s>"       ,  _snake_case			:					Any="<unk>"       ,  _snake_case			:					Union[str, Any]="<mask_2>"       ,  _snake_case			:					Any="<mask_1>"       ,  _snake_case			:					Optional[int]=None       ,  _snake_case			:					List[str]=103       ,  _snake_case			:					Optional[Dict[str, Any]] = None       ,  **_snake_case			:					Optional[int]       ,  )->None:






   '''simple docstring'''

   __lowerCAmelCase					:	Union[str, Any]      =       offset
   if additional_special_tokens is not None:
    if not isinstance(_snake_case       ,  _snake_case      ):
     raise TypeError(
         F'''additional_special_tokens should be of type {type(_snake_case      )}, but is'''
         F''' {type(_snake_case      )}'''      )

    __lowerCAmelCase					:	List[str]      =       (
        ([mask_token_sent] + additional_special_tokens)
        if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
        else additional_special_tokens
    )
    # fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
    additional_special_tokens_extended += [
        F'''<unk_{i}>''' for i in range(len(_snake_case      )       ,  self.offset - 1      )
    ]

    if len(set(_snake_case      )      ) != len(_snake_case      ):
     raise ValueError(
         """Please make sure that the provided additional_special_tokens do not contain an incorrectly"""
         F''' shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}.'''      )
    __lowerCAmelCase					:	Dict      =       additional_special_tokens_extended
   else:
    __lowerCAmelCase					:	Tuple      =       [mask_token_sent] if mask_token_sent is not None else []
    additional_special_tokens += [F'''<unk_{i}>''' for i in range(2       ,  self.offset      )]

   __lowerCAmelCase					:	Optional[int]      =       {} if sp_model_kwargs is None else sp_model_kwargs

   super().__init__(
       eos_token=_snake_case       ,  unk_token=_snake_case       ,  mask_token=_snake_case       ,  pad_token=_snake_case       ,  mask_token_sent=_snake_case       ,  offset=_snake_case       ,  additional_special_tokens=_snake_case       ,  sp_model_kwargs=self.sp_model_kwargs       ,  **_snake_case       ,  )
   __lowerCAmelCase					:	Optional[Any]      =       mask_token_sent
   __lowerCAmelCase					:	Any      =       vocab_file
   __lowerCAmelCase					:	Any      =       spm.SentencePieceProcessor(**self.sp_model_kwargs      )
   self.sp_model.Load(_snake_case      )

   # add special tokens to encoder dict
   __lowerCAmelCase					:	Dict[int, str]      =       {
       0: self.pad_token,
       1: self.eos_token,
   }

   if self.mask_token_sent is not None:
    self.encoder.update(
        {
            2: self.mask_token_sent,
            3: self.mask_token,
        }      )

   if self.offset > 0:
    # entries 2-104 are only used for pretraining and called <mask_1>, <mask_2>, unk_2, ...unk_102
    # mask_token_sent is already added to list -> so start at 1
    self.encoder.update({i + 3: additional_special_tokens[i] for i in range(1       ,  self.offset - 1      )}      )

   __lowerCAmelCase					:	Dict[str, int]      =       {v: k for k, v in self.encoder.items()}






  @property
  def 				UpperCAmelCase__						(							self			:					str      )->int:






   '''simple docstring'''

   return len(self.sp_model      ) + self.offset






  def 				UpperCAmelCase__						(							self			:					Dict      )->Dict[str, int]:






   '''simple docstring'''

   __lowerCAmelCase					:	Tuple      =       {self.convert_ids_to_tokens(_snake_case      ): i for i in range(self.vocab_size      )}
   vocab.update(self.added_tokens_encoder      )
   return vocab






  def __getstate__(							self			:					Optional[int]      )->str:






   '''simple docstring'''

   __lowerCAmelCase					:	Optional[Any]      =       self.__dict__.copy()
   __lowerCAmelCase					:	Union[str, Any]      =       None
   return state






  def __setstate__(							self			:					Any       ,  _snake_case			:					str      )->Any:






   '''simple docstring'''

   __lowerCAmelCase					:	str      =       d

   # for backward compatibility
   if not hasattr(self       ,  """sp_model_kwargs"""      ):
    __lowerCAmelCase					:	Any      =       {}

   __lowerCAmelCase					:	Optional[int]      =       spm.SentencePieceProcessor(**self.sp_model_kwargs      )
   self.sp_model.Load(self.vocab_file      )






  def 				UpperCAmelCase__						(							self			:					Dict       ,  _snake_case			:					str      )->List[str]:






   '''simple docstring'''

   return self.sp_model.encode(_snake_case       ,  out_type=_snake_case      )






  def 				UpperCAmelCase__						(							self			:					Tuple       ,  _snake_case			:					str      )->int:






   '''simple docstring'''

   if token in self.decoder:
    return self.decoder[token]
   elif token in self.added_tokens_decoder:
    return self.added_tokens_decoder[token]
   __lowerCAmelCase					:	Any      =       self.sp_model.piece_to_id(_snake_case      )
   return sp_id + self.offset






  def 				UpperCAmelCase__						(							self			:					List[Any]       ,  _snake_case			:					int      )->str:






   '''simple docstring'''

   if index in self.encoder:
    return self.encoder[index]
   elif index in self.added_tokens_encoder:
    return self.added_tokens_encoder[index]
   else:
    __lowerCAmelCase					:	Optional[int]      =       self.sp_model.IdToPiece(index - self.offset      )
   return token






  def 				UpperCAmelCase__						(							self			:					Union[str, Any]       ,  _snake_case			:					Optional[int]      )->List[str]:






   '''simple docstring'''

   __lowerCAmelCase					:	Any      =       []
   __lowerCAmelCase					:	Dict      =       """"""
   for token in tokens:
    # make sure that special tokens are not decoded using sentencepiece model
    if token in self.all_special_tokens:
     out_string += self.sp_model.decode(_snake_case      ) + token
     __lowerCAmelCase					:	int      =       []
    else:
     current_sub_tokens.append(_snake_case      )
   out_string += self.sp_model.decode(_snake_case      )
   return out_string.strip()






  def 				UpperCAmelCase__						(							self			:					Optional[int]       ,  _snake_case			:					Dict=False      )->int:






   '''simple docstring'''

   return 1






  def 				UpperCAmelCase__						(							self			:					Tuple       ,  _snake_case			:					Tuple      )->str:






   '''simple docstring'''

   __lowerCAmelCase					:	List[Any]      =       set(self.all_special_ids      )  # call it once instead of inside list comp
   all_special_ids.remove(self.unk_token_id      )  # <unk> is only sometimes special

   return [1 if x in all_special_ids else 0 for x in seq]






  def 				UpperCAmelCase__						(							self			:					List[str]       ,  _snake_case			:					List       ,  _snake_case			:					Optional[List] = None       ,  _snake_case			:					bool = False      )->List[int]:






   '''simple docstring'''

   if already_has_special_tokens:
    return self._special_token_mask(_snake_case      )
   elif token_ids_a is None:
    return self._special_token_mask(_snake_case      ) + [1]
   else:
    return self._special_token_mask(token_ids_a + token_ids_a      ) + [1]






  def 				UpperCAmelCase__						(							self			:					Any       ,  _snake_case			:					Union[str, Any]       ,  _snake_case			:					Tuple=None      )->List[int]:






   '''simple docstring'''

   if token_ids_a is None:
    return token_ids_a + [self.eos_token_id]
   # We don't expect to process pairs, but leave the pair logic for API consistency
   return token_ids_a + token_ids_a + [self.eos_token_id]






  def 				UpperCAmelCase__						(							self			:					Any       ,  _snake_case			:					str       ,  _snake_case			:					Optional[str] = None      )->Tuple[str]:






   '''simple docstring'''

   if not os.path.isdir(_snake_case      ):
    logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''      )
    return
   __lowerCAmelCase					:	Optional[int]      =       os.path.join(
       _snake_case       ,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]      )

   if os.path.abspath(self.vocab_file      ) != os.path.abspath(_snake_case      ) and os.path.isfile(self.vocab_file      ):
    copyfile(self.vocab_file       ,  _snake_case      )
   elif not os.path.isfile(self.vocab_file      ):
    with open(_snake_case       ,  """wb"""      ) as fi:
     __lowerCAmelCase					:	Tuple      =       self.sp_model.serialized_model_proto()
     fi.write(_snake_case      )

   return (out_vocab_file,)