



'''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


lowercase							       =			logging.get_logger(__name__)

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

lowercase							       =			{
    '''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'''
        ),
    }
}

lowercase							       =			{
    '''google/bigbird-roberta-base''': 4_096,
    '''google/bigbird-roberta-large''': 4_096,
    '''google/bigbird-base-trivia-itc''': 4_096,
}







class 	UpperCAmelCase	(		__a):


 '''simple docstring'''




 __magic_name__					: int  =      VOCAB_FILES_NAMES
 __magic_name__					: Any  =      PRETRAINED_VOCAB_FILES_MAP
 __magic_name__					: Dict  =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __magic_name__					: int  =      ["input_ids", "attention_mask"]
 __magic_name__					: List[int]  =      []




 def __init__(   self							,  lowerCAmelCase_							,  lowerCAmelCase_="<unk>"							,  lowerCAmelCase_="<s>"							,  lowerCAmelCase_="</s>"							,  lowerCAmelCase_="<pad>"							,  lowerCAmelCase_="[SEP]"							,  lowerCAmelCase_="[MASK]"							,  lowerCAmelCase_="[CLS]"							,  lowerCAmelCase_ = None							,  **lowerCAmelCase_							,  ) ->      None:



      """simple docstring"""







      a_       		=AddedToken(lowerCAmelCase_							,  lstrip=lowerCAmelCase_							,  rstrip=lowerCAmelCase_) if isinstance(lowerCAmelCase_							,  lowerCAmelCase_) else bos_token
      a_       		=AddedToken(lowerCAmelCase_							,  lstrip=lowerCAmelCase_							,  rstrip=lowerCAmelCase_) if isinstance(lowerCAmelCase_							,  lowerCAmelCase_) else eos_token
      a_       		=AddedToken(lowerCAmelCase_							,  lstrip=lowerCAmelCase_							,  rstrip=lowerCAmelCase_) if isinstance(lowerCAmelCase_							,  lowerCAmelCase_) else unk_token
      a_       		=AddedToken(lowerCAmelCase_							,  lstrip=lowerCAmelCase_							,  rstrip=lowerCAmelCase_) if isinstance(lowerCAmelCase_							,  lowerCAmelCase_) else pad_token
      a_       		=AddedToken(lowerCAmelCase_							,  lstrip=lowerCAmelCase_							,  rstrip=lowerCAmelCase_) if isinstance(lowerCAmelCase_							,  lowerCAmelCase_) else cls_token
      a_       		=AddedToken(lowerCAmelCase_							,  lstrip=lowerCAmelCase_							,  rstrip=lowerCAmelCase_) if isinstance(lowerCAmelCase_							,  lowerCAmelCase_) else sep_token

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

      a_       		={} if sp_model_kwargs is None else sp_model_kwargs

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

      a_       		=vocab_file

      a_       		=spm.SentencePieceProcessor(**self.sp_model_kwargs)
      self.sp_model.Load(lowerCAmelCase_)




 @property
 def       lowercase_  (   self) ->      List[Any]:



      """simple docstring"""







      return self.sp_model.get_piece_size()




 def       lowercase_  (   self) ->      Optional[Any]:



      """simple docstring"""







      a_       		={self.convert_ids_to_tokens(lowerCAmelCase_): i for i in range(self.vocab_size)}
      vocab.update(self.added_tokens_encoder)
      return vocab




 def __getstate__(   self) ->      Optional[Any]:



      """simple docstring"""







      a_       		=self.__dict__.copy()
      a_       		=None
      return state




 def __setstate__(   self							,  lowerCAmelCase_) ->      List[Any]:



      """simple docstring"""







      a_       		=d

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

      a_       		=spm.SentencePieceProcessor(**self.sp_model_kwargs)
      self.sp_model.Load(self.vocab_file)




 def       lowercase_  (   self							,  lowerCAmelCase_) ->      List[str]:



      """simple docstring"""







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




 def       lowercase_  (   self							,  lowerCAmelCase_) ->      Any:



      """simple docstring"""







      return self.sp_model.piece_to_id(lowerCAmelCase_)




 def       lowercase_  (   self							,  lowerCAmelCase_) ->      Optional[Any]:



      """simple docstring"""







      a_       		=self.sp_model.IdToPiece(lowerCAmelCase_)
      return token




 def       lowercase_  (   self							,  lowerCAmelCase_) ->      Union[str, Any]:



      """simple docstring"""







      a_       		=[]
      a_       		=""
      a_       		=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(lowerCAmelCase_) + token
                a_       		=True
                a_       		=[]
           else:
                current_sub_tokens.append(lowerCAmelCase_)
                a_       		=False
      out_string += self.sp_model.decode(lowerCAmelCase_)
      return out_string.strip()




 def       lowercase_  (   self							,  lowerCAmelCase_							,  lowerCAmelCase_ = False							,  lowerCAmelCase_ = None							,  lowerCAmelCase_ = True							,  **lowerCAmelCase_							,  ) ->      str:



      """simple docstring"""







      a_       		=kwargs.pop("use_source_tokenizer"							,  lowerCAmelCase_)

      a_       		=self.convert_ids_to_tokens(lowerCAmelCase_							,  skip_special_tokens=lowerCAmelCase_)

      # 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
      a_       		=[]
      a_       		=[]
      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(lowerCAmelCase_))
                     a_       		=[]
                sub_texts.append(lowerCAmelCase_)
           else:
                current_sub_text.append(lowerCAmelCase_)
      if current_sub_text:
           sub_texts.append(self.convert_tokens_to_string(lowerCAmelCase_))

      # Mimic the behavior of the Rust tokenizer:
      # No space before [MASK] and [SEP]
      if spaces_between_special_tokens:
           a_       		=re.sub(r" (\[(MASK|SEP)\])"							,  r"\1"							,  " ".join(lowerCAmelCase_))
      else:
           a_       		="".join(lowerCAmelCase_)

      a_       		=(
          clean_up_tokenization_spaces
          if clean_up_tokenization_spaces is not None
          else self.clean_up_tokenization_spaces
      )
      if clean_up_tokenization_spaces:
           a_       		=self.clean_up_tokenization(lowerCAmelCase_)
           return clean_text
      else:
           return text




 def       lowercase_  (   self							,  lowerCAmelCase_							,  lowerCAmelCase_ = None) ->      Tuple[str]:



      """simple docstring"""







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

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

      return (out_vocab_file,)




 def       lowercase_  (   self							,  lowerCAmelCase_							,  lowerCAmelCase_ = None) ->      List[int]:



      """simple docstring"""







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




 def       lowercase_  (   self							,  lowerCAmelCase_							,  lowerCAmelCase_ = None							,  lowerCAmelCase_ = False) ->      List[int]:



      """simple docstring"""







      if already_has_special_tokens:
           return super().get_special_tokens_mask(
               token_ids_a=lowerCAmelCase_							,  token_ids_a=lowerCAmelCase_							,  already_has_special_tokens=lowerCAmelCase_)

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




 def       lowercase_  (   self							,  lowerCAmelCase_							,  lowerCAmelCase_ = None) ->      List[int]:



      """simple docstring"""







      a_       		=[self.sep_token_id]
      a_       		=[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'''


import os
from math import logaa






def  UpperCAmelCase_       (		lowercase__ = "base_exp.txt"       ):


     '''simple docstring'''







     a_       		=0
     a_       		=0
     for i, line in enumerate(open(os.path.join(os.path.dirname(lowercase__       )       ,	lowercase__       )       )       ):
          a_		,						a_       		=list(map(lowercase__       ,	line.split(","       )       )       )
          if x * logaa(lowercase__       ) > largest:
               a_       		=x * logaa(lowercase__       )
               a_       		=i + 1
     return result


if __name__ == "__main__":
  print(solution())


