




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


lowerCamelCase	:	str				=   logging.get_logger(__name__)

lowerCamelCase	:	Dict				=   {'vocab_file': 'spiece.model'}

lowerCamelCase	:	Optional[Any]				=   {
    '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'
        ),
    }
}

lowerCamelCase	:	Dict				=   {
    '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 						__lowercase		(UpperCamelCase__							):




      """simple docstring"""





      _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    ,				A    ,				A="<unk>"    ,				A="<s>"    ,				A="</s>"    ,				A="<pad>"    ,				A="[SEP]"    ,				A="[MASK]"    ,				A="[CLS]"    ,				A = None    ,				**A    ,				)		->    None:
         snake_case				:    Any           =	AddedToken(A    ,				lstrip=A    ,				rstrip=A     ) if isinstance(A    ,				A     ) else bos_token
         snake_case				:    str           =	AddedToken(A    ,				lstrip=A    ,				rstrip=A     ) if isinstance(A    ,				A     ) else eos_token
         snake_case				:    Optional[int]           =	AddedToken(A    ,				lstrip=A    ,				rstrip=A     ) if isinstance(A    ,				A     ) else unk_token
         snake_case				:    List[str]           =	AddedToken(A    ,				lstrip=A    ,				rstrip=A     ) if isinstance(A    ,				A     ) else pad_token
         snake_case				:    int           =	AddedToken(A    ,				lstrip=A    ,				rstrip=A     ) if isinstance(A    ,				A     ) else cls_token
         snake_case				:    Dict           =	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
         snake_case				:    Optional[int]           =	AddedToken(A    ,				lstrip=A    ,				rstrip=A     ) if isinstance(A    ,				A     ) else mask_token

         snake_case				:    List[Any]           =	{} if sp_model_kwargs is None else sp_model_kwargs

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

         snake_case				:    Any           =	vocab_file

         snake_case				:    int           =	spm.SentencePieceProcessor(**self.sp_model_kwargs     )
         self.sp_model.Load(A     )

      @property
      def      UpperCAmelCase				(				self     )		->    List[str]:
         return self.sp_model.get_piece_size()

      def      UpperCAmelCase				(				self     )		->    Optional[Any]:
         snake_case				:    str           =	{self.convert_ids_to_tokens(A     ): i for i in range(self.vocab_size     )}
         vocab.update(self.added_tokens_encoder     )
         return vocab

      def __getstate__(				self     )		->    Dict:
         snake_case				:    List[str]           =	self.__dict__.copy()
         snake_case				:    Optional[int]           =	None
         return state

      def __setstate__(				self    ,				A     )		->    Dict:
         snake_case				:    str           =	d

         # for backward compatibility
         if not hasattr(self    ,				"""sp_model_kwargs"""     ):
            snake_case				:    Union[str, Any]           =	{}

         snake_case				:    Tuple           =	spm.SentencePieceProcessor(**self.sp_model_kwargs     )
         self.sp_model.Load(self.vocab_file     )

      def      UpperCAmelCase				(				self    ,				A     )		->    List[str]:
         return self.sp_model.encode(A    ,				out_type=A     )

      def      UpperCAmelCase				(				self    ,				A     )		->    str:
         return self.sp_model.piece_to_id(A     )

      def      UpperCAmelCase				(				self    ,				A     )		->    Any:
         snake_case				:    List[Any]           =	self.sp_model.IdToPiece(A     )
         return token

      def      UpperCAmelCase				(				self    ,				A     )		->    List[str]:
         snake_case				:    Tuple           =	[]
         snake_case				:    Optional[Any]           =	""""""
         snake_case				:    Optional[Any]           =	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(A     ) + token
               snake_case				:    Optional[Any]           =	True
               snake_case				:    Optional[Any]           =	[]
            else:
               current_sub_tokens.append(A     )
               snake_case				:    Optional[Any]           =	False
         out_string += self.sp_model.decode(A     )
         return out_string.strip()

      def      UpperCAmelCase				(				self    ,				A    ,				A = False    ,				A = None    ,				A = True    ,				**A    ,				)		->    str:
         snake_case				:    Union[str, Any]           =	kwargs.pop("""use_source_tokenizer"""    ,				A     )

         snake_case				:    str           =	self.convert_ids_to_tokens(A    ,				skip_special_tokens=A     )

         # 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
         snake_case				:    Union[str, Any]           =	[]
         snake_case				:    Optional[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(A     )     )
                  snake_case				:    Optional[Any]           =	[]
               sub_texts.append(A     )
            else:
               current_sub_text.append(A     )
         if current_sub_text:
            sub_texts.append(self.convert_tokens_to_string(A     )     )

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

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

      def      UpperCAmelCase				(				self    ,				A    ,				A = None     )		->    Tuple[str]:
         if not os.path.isdir(A     ):
            logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""     )
            return
         snake_case				:    int           =	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     ) and os.path.isfile(self.vocab_file     ):
            copyfile(self.vocab_file    ,				A     )
         elif not os.path.isfile(self.vocab_file     ):
            with open(A    ,				"""wb"""     ) as fi:
               snake_case				:    Optional[int]           =	self.sp_model.serialized_model_proto()
               fi.write(A     )

         return (out_vocab_file,)

      def      UpperCAmelCase				(				self    ,				A    ,				A = None     )		->    List[int]:
         if token_ids_a is None:
            return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         snake_case				:    Optional[Any]           =	[self.cls_token_id]
         snake_case				:    str           =	[self.sep_token_id]
         return cls + token_ids_a + sep + token_ids_a + sep

      def      UpperCAmelCase				(				self    ,				A    ,				A = None    ,				A = False     )		->    List[int]:
         if already_has_special_tokens:
            return super().get_special_tokens_mask(
                token_ids_a=A    ,				token_ids_a=A    ,				already_has_special_tokens=A     )

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

      def      UpperCAmelCase				(				self    ,				A    ,				A = None     )		->    List[int]:
         snake_case				:    Optional[int]           =	[self.sep_token_id]
         snake_case				:    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]











from math import pow




def 						SCREAMING_SNAKE_CASE__ (   lowercase						,lowercase						,lowercase						,lowercase						,lowercase						,)  ->       tuple[int, int]:
   if current_sum == needed_sum:
      # If the sum of the powers is equal to needed_sum, then we have a solution.
      solutions_count += 1
      return current_sum, solutions_count

   snake_case				:    Union[str, Any]           =	int(pow(lowercase						,lowercase					)					)
   if current_sum + i_to_n <= needed_sum:
      # If the sum of the powers is less than needed_sum, then continue adding powers.
      current_sum += i_to_n
      snake_case     , snake_case				:    List[Any]           =	backtrack(
          lowercase						,lowercase						,current_number + 1						,lowercase						,lowercase					)
      current_sum -= i_to_n
   if i_to_n < needed_sum:
      # If the power of i is less than needed_sum, then try with the next power.
      snake_case     , snake_case				:    str           =	backtrack(
          lowercase						,lowercase						,current_number + 1						,lowercase						,lowercase					)
   return current_sum, solutions_count




def 						SCREAMING_SNAKE_CASE__ (   lowercase						,lowercase					)  ->       int:
   if not (1 <= needed_sum <= 1000 and 2 <= power <= 10):
      raise ValueError(
          """Invalid input\n"""
          """needed_sum must be between 1 and 1000, power between 2 and 10."""					)

   return backtrack(lowercase						,lowercase						,1						,0						,0					)[1]  # Return the solutions_count


if __name__ == "__main__":
       import doctest

       doctest.testmod()





