






'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


a_					= logging.get_logger(__name__)

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

a_					= {
    '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'
        ),
    }
}

a_					= {
    '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,
}






class      __SCREAMING_SNAKE_CASE      (			lowerCamelCase				):
 snake_case_  							=							VOCAB_FILES_NAMES
 snake_case_  							=							PRETRAINED_VOCAB_FILES_MAP
 snake_case_  							=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 snake_case_  							=							["""input_ids""", """attention_mask"""]
 snake_case_  							=							[]




 def __init__(      self	:							Any					,      __lowercase	:							Union[str, Any]					,      __lowercase	:							Tuple="<unk>"					,      __lowercase	:							Optional[Any]="<s>"					,      __lowercase	:							List[str]="</s>"					,      __lowercase	:							Dict="<pad>"					,      __lowercase	:							Dict="[SEP]"					,      __lowercase	:							Union[str, Any]="[MASK]"					,      __lowercase	:							Dict="[CLS]"					,      __lowercase	:							Optional[Dict[str, Any]] = None					,      **__lowercase	:							str					,      )	->						None:
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=AddedToken(__lowercase					,      lstrip=__lowercase					,      rstrip=__lowercase      ) if isinstance(__lowercase					,      __lowercase      ) else bos_token
       SCREAMING_SNAKE_CASE__     :				List[str]									=AddedToken(__lowercase					,      lstrip=__lowercase					,      rstrip=__lowercase      ) if isinstance(__lowercase					,      __lowercase      ) else eos_token
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=AddedToken(__lowercase					,      lstrip=__lowercase					,      rstrip=__lowercase      ) if isinstance(__lowercase					,      __lowercase      ) else unk_token
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=AddedToken(__lowercase					,      lstrip=__lowercase					,      rstrip=__lowercase      ) if isinstance(__lowercase					,      __lowercase      ) else pad_token
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=AddedToken(__lowercase					,      lstrip=__lowercase					,      rstrip=__lowercase      ) if isinstance(__lowercase					,      __lowercase      ) else cls_token
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=AddedToken(__lowercase					,      lstrip=__lowercase					,      rstrip=__lowercase      ) if isinstance(__lowercase					,      __lowercase      ) else sep_token

       # Mask token behave like a normal word, i.e. include the space before it
       SCREAMING_SNAKE_CASE__     :				str									=AddedToken(__lowercase					,      lstrip=__lowercase					,      rstrip=__lowercase      ) if isinstance(__lowercase					,      __lowercase      ) else mask_token

       SCREAMING_SNAKE_CASE__     :				List[str]									={} if sp_model_kwargs is None else sp_model_kwargs

       super().__init__(
           bos_token=__lowercase					,      eos_token=__lowercase					,      unk_token=__lowercase					,      pad_token=__lowercase					,      sep_token=__lowercase					,      mask_token=__lowercase					,      cls_token=__lowercase					,      sp_model_kwargs=self.sp_model_kwargs					,      **__lowercase					,      )

       SCREAMING_SNAKE_CASE__     :				Dict									=vocab_file

       SCREAMING_SNAKE_CASE__     :				Tuple									=spm.SentencePieceProcessor(**self.sp_model_kwargs      )
       self.sp_model.Load(__lowercase      )




 @property
 def      __magic_name__	(      self	:							Union[str, Any]      )	->						List[str]:
       return self.sp_model.get_piece_size()




 def      __magic_name__	(      self	:							Dict      )	->						Dict:
       SCREAMING_SNAKE_CASE__     :				Tuple									={self.convert_ids_to_tokens(__lowercase      ): i for i in range(self.vocab_size      )}
       vocab.update(self.added_tokens_encoder      )
       return vocab




 def __getstate__(      self	:							str      )	->						Tuple:
       SCREAMING_SNAKE_CASE__     :				Tuple									=self.__dict__.copy()
       SCREAMING_SNAKE_CASE__     :				Dict									=None
       return state




 def __setstate__(      self	:							str					,      __lowercase	:							Any      )	->						Any:
       SCREAMING_SNAKE_CASE__     :				Tuple									=d

       # for backward compatibility
       if not hasattr(self					,      '''sp_model_kwargs'''      ):
             SCREAMING_SNAKE_CASE__     :				Optional[int]									={}

       SCREAMING_SNAKE_CASE__     :				List[Any]									=spm.SentencePieceProcessor(**self.sp_model_kwargs      )
       self.sp_model.Load(self.vocab_file      )




 def      __magic_name__	(      self	:							Optional[int]					,      __lowercase	:							str      )	->						List[str]:
       return self.sp_model.encode(__lowercase					,      out_type=__lowercase      )




 def      __magic_name__	(      self	:							int					,      __lowercase	:							Any      )	->						List[str]:
       return self.sp_model.piece_to_id(__lowercase      )




 def      __magic_name__	(      self	:							Dict					,      __lowercase	:							int      )	->						int:
       SCREAMING_SNAKE_CASE__     :				Optional[int]									=self.sp_model.IdToPiece(__lowercase      )
       return token




 def      __magic_name__	(      self	:							List[str]					,      __lowercase	:							Optional[int]      )	->						Union[str, Any]:
       SCREAMING_SNAKE_CASE__     :				Tuple									=[]
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=''''''
       SCREAMING_SNAKE_CASE__     :				Optional[int]									=False
       for token in tokens:
             # make sure that special tokens are not decoded using sentencepiece model
             if token in self.all_special_tokens:
                   if not prev_is_special:
                         out_string += " "
                   out_string += self.sp_model.decode(__lowercase      ) + token
                   SCREAMING_SNAKE_CASE__     :				Optional[Any]									=True
                   SCREAMING_SNAKE_CASE__     :				Tuple									=[]
             else:
                   current_sub_tokens.append(__lowercase      )
                   SCREAMING_SNAKE_CASE__     :				List[str]									=False
       out_string += self.sp_model.decode(__lowercase      )
       return out_string.strip()




 def      __magic_name__	(      self	:							List[str]					,      __lowercase	:							List[int]					,      __lowercase	:							bool = False					,      __lowercase	:							bool = None					,      __lowercase	:							bool = True					,      **__lowercase	:							Tuple					,      )	->						str:
       SCREAMING_SNAKE_CASE__     :				Dict									=kwargs.pop('''use_source_tokenizer'''					,      __lowercase      )

       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=self.convert_ids_to_tokens(__lowercase					,      skip_special_tokens=__lowercase      )

       # To avoid mixing byte-level and unicode for byte-level BPT
       # we need to build string separately for added tokens and byte-level tokens
       # cf. https://github.com/huggingface/transformers/issues/1133
       SCREAMING_SNAKE_CASE__     :				List[str]									=[]
       SCREAMING_SNAKE_CASE__     :				List[Any]									=[]
       for token in filtered_tokens:
             if skip_special_tokens and token in self.all_special_ids:
                   continue
             if token in self.added_tokens_encoder:
                   if current_sub_text:
                         sub_texts.append(self.convert_tokens_to_string(__lowercase      )      )
                         SCREAMING_SNAKE_CASE__     :				str									=[]
                   sub_texts.append(__lowercase      )
             else:
                   current_sub_text.append(__lowercase      )
       if current_sub_text:
             sub_texts.append(self.convert_tokens_to_string(__lowercase      )      )

       # Mimic the behavior of the Rust tokenizer:
       # No space before [MASK] and [SEP]
       if spaces_between_special_tokens:
             SCREAMING_SNAKE_CASE__     :				str									=re.sub(r''' (\[(MASK|SEP)\])'''					,      r'''\1'''					,      ''' '''.join(__lowercase      )      )
       else:
             SCREAMING_SNAKE_CASE__     :				List[str]									=''''''.join(__lowercase      )

       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=(
           clean_up_tokenization_spaces
           if clean_up_tokenization_spaces is not None
           else self.clean_up_tokenization_spaces
       )
       if clean_up_tokenization_spaces:
             SCREAMING_SNAKE_CASE__     :				int									=self.clean_up_tokenization(__lowercase      )
             return clean_text
       else:
             return text




 def      __magic_name__	(      self	:							List[str]					,      __lowercase	:							str					,      __lowercase	:							Optional[str] = None      )	->						Tuple[str]:
       if not os.path.isdir(__lowercase      ):
             logger.error(F"Vocabulary path ({save_directory}) should be a directory"      )
             return
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=os.path.join(
           __lowercase					,      (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )

       if os.path.abspath(self.vocab_file      ) != os.path.abspath(__lowercase      ) and os.path.isfile(self.vocab_file      ):
             copyfile(self.vocab_file					,      __lowercase      )
       elif not os.path.isfile(self.vocab_file      ):
             with open(__lowercase					,      '''wb'''      ) as fi:
                   SCREAMING_SNAKE_CASE__     :				Optional[int]									=self.sp_model.serialized_model_proto()
                   fi.write(__lowercase      )

       return (out_vocab_file,)




 def      __magic_name__	(      self	:							Union[str, Any]					,      __lowercase	:							List[int]					,      __lowercase	:							Optional[List[int]] = None      )	->						List[int]:
       if token_ids_a is None:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=[self.cls_token_id]
       SCREAMING_SNAKE_CASE__     :				int									=[self.sep_token_id]
       return cls + token_ids_a + sep + token_ids_a + sep




 def      __magic_name__	(      self	:							Any					,      __lowercase	:							List[int]					,      __lowercase	:							Optional[List[int]] = None					,      __lowercase	:							bool = False      )	->						List[int]:
       if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=__lowercase					,      token_ids_a=__lowercase					,      already_has_special_tokens=__lowercase      )

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




 def      __magic_name__	(      self	:							Optional[int]					,      __lowercase	:							List[int]					,      __lowercase	:							Optional[List[int]] = None      )	->						List[int]:
       SCREAMING_SNAKE_CASE__     :				str									=[self.sep_token_id]
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=[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]







'''simple docstring'''
def  _a(  UpperCamelCase__				:						Optional[int],	UpperCamelCase__				:						int							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__     :				Optional[int]									=0
      SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=len(UpperCamelCase__							) - 1

      while left <= right:
            # avoid divided by 0 during interpolation
            if sorted_collection[left] == sorted_collection[right]:
                  if sorted_collection[left] == item:
                        return left
                  else:
                        return None

            SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=left + ((item - sorted_collection[left]) * (right - left)) // (
                sorted_collection[right] - sorted_collection[left]
            )

            # out of range check
            if point < 0 or point >= len(UpperCamelCase__							):
                  return None

            SCREAMING_SNAKE_CASE__     :				Optional[int]									=sorted_collection[point]
            if current_item == item:
                  return point
            else:
                  if point < left:
                        SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=left
                        SCREAMING_SNAKE_CASE__     :				Optional[Any]									=point
                  elif point > right:
                        SCREAMING_SNAKE_CASE__     :				Optional[int]									=right
                        SCREAMING_SNAKE_CASE__     :				Tuple									=point
                  else:
                        if item < current_item:
                              SCREAMING_SNAKE_CASE__     :				str									=point - 1
                        else:
                              SCREAMING_SNAKE_CASE__     :				Tuple									=point + 1
      return None





def  _a(  UpperCamelCase__				:						List[str],	UpperCamelCase__				:						Optional[Any],	UpperCamelCase__				:						Union[str, Any],	UpperCamelCase__				:						Union[str, Any]							):




      '''simple docstring'''






      if sorted_collection[left] == sorted_collection[right]:
            if sorted_collection[left] == item:
                  return left
            else:
                  return None

      SCREAMING_SNAKE_CASE__     :				Dict									=left + ((item - sorted_collection[left]) * (right - left)) // (
          sorted_collection[right] - sorted_collection[left]
      )

      # out of range check
      if point < 0 or point >= len(UpperCamelCase__							):
            return None

      if sorted_collection[point] == item:
            return point
      elif point < left:
            return interpolation_search_by_recursion(UpperCamelCase__,	UpperCamelCase__,	UpperCamelCase__,	UpperCamelCase__							)
      elif point > right:
            return interpolation_search_by_recursion(UpperCamelCase__,	UpperCamelCase__,	UpperCamelCase__,	UpperCamelCase__							)
      else:
            if sorted_collection[point] > item:
                  return interpolation_search_by_recursion(
                      UpperCamelCase__,	UpperCamelCase__,	UpperCamelCase__,	point - 1							)
            else:
                  return interpolation_search_by_recursion(
                      UpperCamelCase__,	UpperCamelCase__,	point + 1,	UpperCamelCase__							)





def  _a(  UpperCamelCase__				:						Dict							):




      '''simple docstring'''






      if collection != sorted(UpperCamelCase__							):
            raise ValueError('''Collection must be ascending sorted'''							)
      return True


if __name__ == "__main__":
  import sys
  a_					= 0
  if debug == 1:
    a_					= [1_0, 3_0, 4_0, 4_5, 5_0, 6_6, 7_7, 9_3]
    try:
      __assert_sorted(collection)
    except ValueError:
      sys.exit('Sequence must be ascending sorted to apply interpolation search')
    a_					= 6_7

  a_					= interpolation_search(collection, target)
  if result is not None:
    print(F'''{target} found at positions: {result}''')
  else:
    print('Not found')