





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


SCREAMING_SNAKE_CASE_						       =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_						       =	"""▁"""

SCREAMING_SNAKE_CASE_						       =	{"""vocab_file""": """sentencepiece.bpe.model""", """monolingual_vocab_file""": """dict.txt"""}

SCREAMING_SNAKE_CASE_						       =	{
    """vocab_file""": {
        """vinai/bartpho-syllable""": """https://huggingface.co/vinai/bartpho-syllable/resolve/main/sentencepiece.bpe.model""",
    },
    """monolingual_vocab_file""": {
        """vinai/bartpho-syllable""": """https://huggingface.co/vinai/bartpho-syllable/resolve/main/dict.txt""",
    },
}

SCREAMING_SNAKE_CASE_						       =	{"""vinai/bartpho-syllable""": 1_0_2_4}

class 		UpperCamelCase__			(				lowerCAmelCase_       ):



     '''simple docstring'''

     __snake_case   :     Any		     =      VOCAB_FILES_NAMES
     __snake_case   :     Optional[int]		     =      PRETRAINED_VOCAB_FILES_MAP
     __snake_case   :     Tuple		     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __snake_case   :     Union[str, Any]		     =      ["input_ids", "attention_mask"]






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




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						AddedToken(lowerCamelCase__						,lstrip=lowerCamelCase__						,rstrip=lowerCamelCase__	) if isinstance(lowerCamelCase__						,lowerCamelCase__	) else mask_token

           SCREAMING_SNAKE_CASE		=						{} if sp_model_kwargs is None else sp_model_kwargs

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

           SCREAMING_SNAKE_CASE		=						vocab_file
           SCREAMING_SNAKE_CASE		=						monolingual_vocab_file
           SCREAMING_SNAKE_CASE		=						spm.SentencePieceProcessor(**self.sp_model_kwargs	)
           self.sp_model.Load(str(lowerCamelCase__	)	)

           # Load the reduced vocab

           # Keep order of special tokens for backward compatibility
           SCREAMING_SNAKE_CASE		=						{}
           SCREAMING_SNAKE_CASE		=						0
           for token in [bos_token, pad_token, eos_token, unk_token, sep_token, cls_token]:
                 if str(lowerCamelCase__	) not in self.fairseq_tokens_to_ids:
                       SCREAMING_SNAKE_CASE		=						cnt
                       cnt += 1
           with open(lowerCamelCase__						,"""r"""						,encoding="""utf-8"""	) as f:
                 for line in f.readlines():
                       SCREAMING_SNAKE_CASE		=						line.strip().split()[0]
                       SCREAMING_SNAKE_CASE		=						len(self.fairseq_tokens_to_ids	)
           if str(lowerCamelCase__	) not in self.fairseq_tokens_to_ids:
                 SCREAMING_SNAKE_CASE		=						len(self.fairseq_tokens_to_ids	)

           SCREAMING_SNAKE_CASE		=						{v: k for k, v in self.fairseq_tokens_to_ids.items()}






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




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						self.__dict__.copy()
           SCREAMING_SNAKE_CASE		=						None
           SCREAMING_SNAKE_CASE		=						self.sp_model.serialized_model_proto()
           return state






     def __setstate__(							self						:   Dict						,lowerCamelCase__						:   Any	)					->		Dict:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						d

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

           SCREAMING_SNAKE_CASE		=						spm.SentencePieceProcessor(**self.sp_model_kwargs	)
           self.sp_model.LoadFromSerializedProto(self.sp_model_proto	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   List[Any]						,lowerCamelCase__						:   List[int]						,lowerCamelCase__						:   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]
           SCREAMING_SNAKE_CASE		=						[self.cls_token_id]
           SCREAMING_SNAKE_CASE		=						[self.sep_token_id]
           return cls + token_ids_a + sep + sep + token_ids_a + sep






     def     SCREAMING_SNAKE_CASE__  (							self						:   str						,lowerCamelCase__						:   List[int]						,lowerCamelCase__						:   Optional[List[int]] = None						,lowerCamelCase__						:   bool = 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, 1] + ([0] * len(lowerCamelCase__	)) + [1]






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




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						[self.sep_token_id]
           SCREAMING_SNAKE_CASE		=						[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						:   Tuple	)					->		int:




           '''simple docstring'''


           return len(self.fairseq_ids_to_tokens	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   Tuple	)					->		Optional[Any]:




           '''simple docstring'''


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






     def     SCREAMING_SNAKE_CASE__  (							self						:   Union[str, Any]						,lowerCamelCase__						:   str	)					->		List[str]:




           '''simple docstring'''


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






     def     SCREAMING_SNAKE_CASE__  (							self						:   Tuple						,lowerCamelCase__						:   Dict	)					->		Union[str, Any]:




           '''simple docstring'''


           if token in self.fairseq_tokens_to_ids:
                 return self.fairseq_tokens_to_ids[token]
           else:
                 return self.unk_token_id






     def     SCREAMING_SNAKE_CASE__  (							self						:   int						,lowerCamelCase__						:   List[Any]	)					->		Dict:




           '''simple docstring'''


           return self.fairseq_ids_to_tokens[index]






     def     SCREAMING_SNAKE_CASE__  (							self						:   Optional[int]						,lowerCamelCase__						:   Dict	)					->		List[str]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						"""""".join(lowerCamelCase__	).replace(lowerCamelCase__						,""" """	).strip()
           return out_string






     def     SCREAMING_SNAKE_CASE__  (							self						:   Optional[int]						,lowerCamelCase__						:   str						,lowerCamelCase__						:   Optional[str] = None	)					->		Tuple[str]:




           '''simple docstring'''


           if not os.path.isdir(lowerCamelCase__	):
                 logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""	)
                 return
           SCREAMING_SNAKE_CASE		=						os.path.join(
               lowerCamelCase__						,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]	)
           SCREAMING_SNAKE_CASE		=						os.path.join(
               lowerCamelCase__						,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""monolingual_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:
                       SCREAMING_SNAKE_CASE		=						self.sp_model.serialized_model_proto()
                       fi.write(lowerCamelCase__	)

           if os.path.abspath(self.monolingual_vocab_file	) != os.path.abspath(
               lowerCamelCase__	) and os.path.isfile(self.monolingual_vocab_file	):
                 copyfile(self.monolingual_vocab_file						,lowerCamelCase__	)
           elif not os.path.isfile(self.monolingual_vocab_file	):
                 with open(lowerCamelCase__						,"""w"""						,encoding="""utf-8"""	) as fp:
                       for token in self.fairseq_tokens_to_ids:
                             if token not in self.all_special_tokens:
                                   fp.write(F"""{str(lowerCamelCase__	)} \n"""	)

           return out_vocab_file, out_monolingual_vocab_file









from __future__ import annotations

import math



def        __lowercase       (				_SCREAMING_SNAKE_CASE     )			->       bool:


      '''simple docstring'''


      if 1 < number < 4:
            # 2 and 3 are primes
            return True
      elif number < 2 or number % 2 == 0 or number % 3 == 0:
            # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
            return False

      # All primes number are in format of 6k +/- 1
      for i in range(5			,						int(math.sqrt(_SCREAMING_SNAKE_CASE     ) + 1     )			,						6     ):
            if number % i == 0 or number % (i + 2) == 0:
                  return False
      return True



def        __lowercase       (				_SCREAMING_SNAKE_CASE     )			->       list[int]:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						str(_SCREAMING_SNAKE_CASE     )
      SCREAMING_SNAKE_CASE		=						[n]
      for i in range(1			,						len(_SCREAMING_SNAKE_CASE     )     ):
            list_nums.append(int(str_num[i:]     )     )
            list_nums.append(int(str_num[:-i]     )     )
      return list_nums



def        __lowercase       (				_SCREAMING_SNAKE_CASE     )			->       bool:


      '''simple docstring'''


      if len(str(_SCREAMING_SNAKE_CASE     )     ) > 3:
            if not is_prime(int(str(_SCREAMING_SNAKE_CASE     )[-3:]     )     ) or not is_prime(int(str(_SCREAMING_SNAKE_CASE     )[:3]     )     ):
                  return False
      return True



def        __lowercase       (				_SCREAMING_SNAKE_CASE = 11     )			->       list[int]:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						[]
      SCREAMING_SNAKE_CASE		=						13
      while len(_SCREAMING_SNAKE_CASE     ) != count:
            if validate(_SCREAMING_SNAKE_CASE     ):
                  SCREAMING_SNAKE_CASE		=						list_truncated_nums(_SCREAMING_SNAKE_CASE     )
                  if all(is_prime(_SCREAMING_SNAKE_CASE     ) for i in list_nums     ):
                        list_truncated_primes.append(_SCREAMING_SNAKE_CASE     )
            num += 2
      return list_truncated_primes



def        __lowercase       (				)			->       int:


      '''simple docstring'''


      return sum(compute_truncated_primes(11     )     )


if __name__ == "__main__":
      print(F'''{sum(compute_truncated_primes(1_1)) = }''')


