





import os
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": "sentencepiece.bpe.model"}

__A     =    {
    "vocab_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model",
    }
}

__A     =    {
    "camembert-base": 512,
}

__A     =    "▁"



class        _SCREAMING_SNAKE_CASE						(     __SCREAMING_SNAKE_CASE   ):







 '''simple docstring'''
 lowercase_		=      VOCAB_FILES_NAMES
 lowercase_		=      PRETRAINED_VOCAB_FILES_MAP
 lowercase_		=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase_		=      ["input_ids", "attention_mask"]

 def __init__(self    :       str	,			UpperCAmelCase_    :       Optional[Any]	,			UpperCAmelCase_    :       List[Any]="<s>"	,			UpperCAmelCase_    :       List[Any]="</s>"	,			UpperCAmelCase_    :       Optional[Any]="</s>"	,			UpperCAmelCase_    :       Optional[int]="<s>"	,			UpperCAmelCase_    :       Optional[int]="<unk>"	,			UpperCAmelCase_    :       Dict="<pad>"	,			UpperCAmelCase_    :       Any="<mask>"	,			UpperCAmelCase_    :       Optional[int]=["<s>NOTUSED", "</s>NOTUSED"]	,			UpperCAmelCase_    :       Optional[Dict[str, Any]] = None	,			**UpperCAmelCase_    :       Dict	,			)	->None:



   '''simple docstring'''



   lowerCamelCase__:				str        =AddedToken(UpperCAmelCase_	,			lstrip=UpperCAmelCase_	,			rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_	,			UpperCAmelCase_) else mask_token

   lowerCamelCase__:				Any        ={} if sp_model_kwargs is None else sp_model_kwargs

   super().__init__(
       bos_token=UpperCAmelCase_	,			eos_token=UpperCAmelCase_	,			unk_token=UpperCAmelCase_	,			sep_token=UpperCAmelCase_	,			cls_token=UpperCAmelCase_	,			pad_token=UpperCAmelCase_	,			mask_token=UpperCAmelCase_	,			additional_special_tokens=UpperCAmelCase_	,			sp_model_kwargs=self.sp_model_kwargs	,			**UpperCAmelCase_	,			)
   lowerCamelCase__:				Union[str, Any]        =spm.SentencePieceProcessor(**self.sp_model_kwargs)
   self.sp_model.Load(str(UpperCAmelCase_))
   lowerCamelCase__:				Union[str, Any]        =vocab_file
   # HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
   # sentencepiece vocabulary (this is the case for <s> and </s>
   lowerCamelCase__:				str        ={"<s>NOTUSED": 0, "<pad>": 1, "</s>NOTUSED": 2, "<unk>": 3}
   lowerCamelCase__:				Dict        =len(self.fairseq_tokens_to_ids)
   lowerCamelCase__:				str        =len(self.sp_model) + len(self.fairseq_tokens_to_ids)
   lowerCamelCase__:				int        ={v: k for k, v in self.fairseq_tokens_to_ids.items()}

 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[int]	,			UpperCAmelCase_    :       List[int]	,			UpperCAmelCase_    :       Optional[List[int]] = None)	->List[int]:



   '''simple docstring'''



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

 def 							SCREAMING_SNAKE_CASE_ (self    :       Union[str, Any]	,			UpperCAmelCase_    :       List[int]	,			UpperCAmelCase_    :       Optional[List[int]] = None	,			UpperCAmelCase_    :       bool = False)	->List[int]:



   '''simple docstring'''



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

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

 def 							SCREAMING_SNAKE_CASE_ (self    :       List[Any]	,			UpperCAmelCase_    :       List[int]	,			UpperCAmelCase_    :       Optional[List[int]] = None)	->List[int]:



   '''simple docstring'''



   lowerCamelCase__:				Optional[Any]        =[self.sep_token_id]
   lowerCamelCase__:				Optional[int]        =[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 + sep + token_ids_a + sep) * [0]

 @property
 def 							SCREAMING_SNAKE_CASE_ (self    :       Optional[int])	->Tuple:



   '''simple docstring'''



   return len(self.fairseq_tokens_to_ids) + len(self.sp_model)

 def 							SCREAMING_SNAKE_CASE_ (self    :       List[Any])	->Any:



   '''simple docstring'''



   lowerCamelCase__:				Dict        ={self.convert_ids_to_tokens(UpperCAmelCase_): i for i in range(self.vocab_size)}
   vocab.update(self.added_tokens_encoder)
   return vocab

 def 							SCREAMING_SNAKE_CASE_ (self    :       str	,			UpperCAmelCase_    :       str)	->List[str]:



   '''simple docstring'''



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

 def 							SCREAMING_SNAKE_CASE_ (self    :       Dict	,			UpperCAmelCase_    :       Dict)	->Dict:



   '''simple docstring'''



   if token in self.fairseq_tokens_to_ids:
     return self.fairseq_tokens_to_ids[token]
   elif self.sp_model.PieceToId(UpperCAmelCase_) == 0:
     # Convert sentence piece unk token to fairseq unk token index
     return self.unk_token_id
   return self.fairseq_offset + self.sp_model.PieceToId(UpperCAmelCase_)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Tuple	,			UpperCAmelCase_    :       Optional[Any])	->Union[str, Any]:



   '''simple docstring'''



   if index in self.fairseq_ids_to_tokens:
     return self.fairseq_ids_to_tokens[index]
   return self.sp_model.IdToPiece(index - self.fairseq_offset)

 def 							SCREAMING_SNAKE_CASE_ (self    :       Tuple	,			UpperCAmelCase_    :       Tuple)	->Optional[Any]:



   '''simple docstring'''



   lowerCamelCase__:				Dict        =[]
   lowerCamelCase__:				Union[str, Any]        =""
   lowerCamelCase__:				Dict        =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(UpperCAmelCase_) + token
       lowerCamelCase__:				Dict        =True
       lowerCamelCase__:				Union[str, Any]        =[]
     else:
       current_sub_tokens.append(UpperCAmelCase_)
       lowerCamelCase__:				Optional[Any]        =False
   out_string += self.sp_model.decode(UpperCAmelCase_)
   return out_string.strip()

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



   '''simple docstring'''



   lowerCamelCase__:				Optional[Any]        =self.__dict__.copy()
   lowerCamelCase__:				Any        =None
   return state

 def __setstate__(self    :       List[str]	,			UpperCAmelCase_    :       int)	->Union[str, Any]:



   '''simple docstring'''



   lowerCamelCase__:				Tuple        =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 							SCREAMING_SNAKE_CASE_ (self    :       str	,			UpperCAmelCase_    :       str	,			UpperCAmelCase_    :       Optional[str] = None)	->Tuple[str]:



   '''simple docstring'''



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

   if os.path.abspath(self.vocab_file) != os.path.abspath(UpperCAmelCase_) and os.path.isfile(self.vocab_file):
     copyfile(self.vocab_file	,			UpperCAmelCase_)
   elif not os.path.isfile(self.vocab_file):
     with open(UpperCAmelCase_	,			"wb") as fi:
       lowerCamelCase__:				Optional[Any]        =self.sp_model.serialized_model_proto()
       fi.write(UpperCAmelCase_)

   return (out_vocab_file,)








from math import pow





def 					lowerCAmelCase_			(	__a     ,   __a     ,   __a     ,   __a     ,   __a     ,   )					->		tuple[int, int]:







  """simple docstring"""





  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

  lowerCamelCase__:				Optional[Any]        =int(pow(__a     ,   __a		)		)
  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
    lowerCamelCase__  , lowerCamelCase__:				int        =backtrack(
        __a     ,   __a     ,   current_number + 1     ,   __a     ,   __a		)
    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.
    lowerCamelCase__  , lowerCamelCase__:				Dict        =backtrack(
        __a     ,   __a     ,   current_number + 1     ,   __a     ,   __a		)
  return current_sum, solutions_count





def 					lowerCAmelCase_			(	__a     ,   __a		)					->		int:







  """simple docstring"""





  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(__a     ,   __a     ,   1     ,   0     ,   0		)[1]  # Return the solutions_count


if __name__ == "__main__":
     import doctest

     doctest.testmod()

