
'''simple docstring'''







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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
  from .tokenization_big_bird import BigBirdTokenizer
else:
  __lowerCAmelCase         =    None

__lowerCAmelCase         =    logging.get_logger(__name__)
__lowerCAmelCase         =    {"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

__lowerCAmelCase         =    {
    """vocab_file""": {
        """google/bigbird-roberta-base""": """https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model""",
        """google/bigbird-roberta-large""": (
            """https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"""
        ),
        """google/bigbird-base-trivia-itc""": (
            """https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"""
        ),
    },
    """tokenizer_file""": {
        """google/bigbird-roberta-base""": (
            """https://huggingface.co/google/bigbird-roberta-base/resolve/main/tokenizer.json"""
        ),
        """google/bigbird-roberta-large""": (
            """https://huggingface.co/google/bigbird-roberta-large/resolve/main/tokenizer.json"""
        ),
        """google/bigbird-base-trivia-itc""": (
            """https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/tokenizer.json"""
        ),
    },
}

__lowerCAmelCase         =    {
    """google/bigbird-roberta-base""": 4_0_9_6,
    """google/bigbird-roberta-large""": 4_0_9_6,
    """google/bigbird-base-trivia-itc""": 4_0_9_6,
}


__lowerCAmelCase         =    """▁"""







class UpperCAmelCase__	( lowercase__	):





  """simple docstring"""

  __UpperCAmelCase				:				List[Any]   =					VOCAB_FILES_NAMES
  __UpperCAmelCase				:				Any   =					PRETRAINED_VOCAB_FILES_MAP
  __UpperCAmelCase				:				Union[str, Any]   =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  __UpperCAmelCase				:				Any   =					BigBirdTokenizer
  __UpperCAmelCase				:				Tuple   =					['''input_ids''', '''attention_mask''']
  __UpperCAmelCase				:				List[int]   =					[]


  def __init__(		self      :     int							,_a      :     List[Any]=None							,_a      :     List[Any]=None							,_a      :     Tuple="<unk>"							,_a      :     Tuple="<s>"							,_a      :     Union[str, Any]="</s>"							,_a      :     Dict="<pad>"							,_a      :     Dict="[SEP]"							,_a      :     Union[str, Any]="[MASK]"							,_a      :     Optional[Any]="[CLS]"							,**_a      :     Union[str, Any]							,):


     '''simple docstring'''






     _a				:	int			=   AddedToken(_a							,lstrip=_a							,rstrip=_a       ) if isinstance(_a							,_a       ) else bos_token
     _a				:	List[str]			=   AddedToken(_a							,lstrip=_a							,rstrip=_a       ) if isinstance(_a							,_a       ) else eos_token
     _a				:	Optional[Any]			=   AddedToken(_a							,lstrip=_a							,rstrip=_a       ) if isinstance(_a							,_a       ) else unk_token
     _a				:	Union[str, Any]			=   AddedToken(_a							,lstrip=_a							,rstrip=_a       ) if isinstance(_a							,_a       ) else pad_token
     _a				:	Any			=   AddedToken(_a							,lstrip=_a							,rstrip=_a       ) if isinstance(_a							,_a       ) else cls_token
     _a				:	Tuple			=   AddedToken(_a							,lstrip=_a							,rstrip=_a       ) if isinstance(_a							,_a       ) else sep_token

     # Mask token behave like a normal word, i.e. include the space before it
     _a				:	List[Any]			=   AddedToken(_a							,lstrip=_a							,rstrip=_a       ) if isinstance(_a							,_a       ) else mask_token

     super().__init__(
         _a							,tokenizer_file=_a							,bos_token=_a							,eos_token=_a							,unk_token=_a							,sep_token=_a							,pad_token=_a							,cls_token=_a							,mask_token=_a							,**_a							,)

     _a				:	Union[str, Any]			=   vocab_file
     _a				:	Union[str, Any]			=   False if not self.vocab_file else True


  def   __lowercase		(		self      :     List[Any]							,_a      :     List[int]							,_a      :     Optional[List[int]] = None       ):


     '''simple docstring'''






     _a				:	Tuple			=   [self.sep_token_id]
     _a				:	Tuple			=   [self.cls_token_id]
     if token_ids_a is None:
        return cls + token_ids_a + sep
     return cls + token_ids_a + sep + token_ids_a + sep


  def   __lowercase		(		self      :     Optional[int]							,_a      :     List[int]							,_a      :     Optional[List[int]] = None							,_a      :     bool = False       ):


     '''simple docstring'''






     if already_has_special_tokens:
        if token_ids_a is not None:
           raise ValueError(
               'You should not supply a second sequence if the provided sequence of '
               'ids is already formatted with special tokens for the model.'       )
        return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

     if token_ids_a is None:
        return [1] + ([0] * len(_a       )) + [1]
     return [1] + ([0] * len(_a       )) + [1] + ([0] * len(_a       )) + [1]


  def   __lowercase		(		self      :     List[Any]							,_a      :     List[int]							,_a      :     Optional[List[int]] = None       ):


     '''simple docstring'''






     _a				:	str			=   [self.sep_token_id]
     _a				:	List[str]			=   [self.cls_token_id]

     if token_ids_a is None:
        return len(cls + token_ids_a + sep       ) * [0]
     return len(cls + token_ids_a + sep       ) * [0] + len(token_ids_a + sep       ) * [1]


  def   __lowercase		(		self      :     str							,_a      :     str							,_a      :     Optional[str] = None       ):


     '''simple docstring'''






     if not self.can_save_slow_tokenizer:
        raise ValueError(
            'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
            'tokenizer.'       )

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

     if os.path.abspath(self.vocab_file       ) != os.path.abspath(_a       ):
        copyfile(self.vocab_file							,_a       )

     return (out_vocab_file,)





'''simple docstring'''







from __future__ import annotations

__lowerCAmelCase         =    [-1_0, -5, 0, 5, 5.1, 1_1, 1_3, 2_1, 3, 4, -2_1, -1_0, -5, -1, 0]
__lowerCAmelCase         =    [-5, 0, 5, 5.1, 1_1, 1_3, 2_1, -1, 4, -1, -1_0, -5, -1, 0, -1]





def 					UpperCAmelCase_		(__a      :    list[float] ):






   """simple docstring"""

   _a				:	Optional[int]			=   []
   _a				:	int			=   len(__a )

   for i in range(__a ):
      _a				:	float			=   -1
      for j in range(i + 1 ,	__a ):
         if arr[i] < arr[j]:
            _a				:	Any			=   arr[j]
            break
      result.append(__a )
   return result





def 					UpperCAmelCase_		(__a      :    list[float] ):






   """simple docstring"""

   _a				:	Tuple			=   []
   for i, outer in enumerate(__a ):
      _a				:	float			=   -1
      for inner in arr[i + 1 :]:
         if outer < inner:
            _a				:	Dict			=   inner
            break
      result.append(__a )
   return result





def 					UpperCAmelCase_		(__a      :    list[float] ):






   """simple docstring"""

   _a				:	int			=   len(__a )
   _a				:	list[float]			=   []
   _a				:	list[float]			=   [-1] * arr_size

   for index in reversed(range(__a ) ):
      if stack:
         while stack[-1] <= arr[index]:
            stack.pop()
            if not stack:
               break
      if stack:
         _a				:	Dict			=   stack[-1]
      stack.append(arr[index] )
   return result


if __name__ == "__main__":
  from doctest import testmod
  from timeit import timeit

  testmod()
  print(next_greatest_element_slow(arr))
  print(next_greatest_element_fast(arr))
  print(next_greatest_element(arr))

  __lowerCAmelCase         =    (
      """from __main__ import arr, next_greatest_element_slow, """
      """next_greatest_element_fast, next_greatest_element"""
  )
  print(
      """next_greatest_element_slow():""",
      timeit("""next_greatest_element_slow(arr)""", setup=setup),
  )
  print(
      """next_greatest_element_fast():""",
      timeit("""next_greatest_element_fast(arr)""", setup=setup),
  )
  print(
      """     next_greatest_element():""",
      timeit("""next_greatest_element(arr)""", setup=setup),
  )



