






import os
import unicodedata
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 SPIECE_UNDERLINE, logging


lowercase__				:      Union[str, Any]	   = logging.get_logger(__name__)

lowercase__				:      List[str]	   = {"vocab_file": "spiece.model"}

lowercase__				:      int	   = {
    "vocab_file": {
        "TsinghuaAI/CPM-Generate": "https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model",
    }
}




class       a__	( __SCREAMING_SNAKE_CASE				):







     def __init__(     self  ,		A  ,		A=False  ,		A=True  ,		A=False  ,		A="<s>"  ,		A="</s>"  ,		A="<unk>"  ,		A="<sep>"  ,		A="<pad>"  ,		A="<cls>"  ,		A="<mask>"  ,		A=["<eop>", "<eod>"]  ,		A = None  ,		**A  ,		)  ->   None:



          '''simple docstring'''



          a     =				AddedToken(UpperCamelCase__  ,		lstrip=UpperCamelCase__  ,		rstrip=UpperCamelCase__			) if isinstance(UpperCamelCase__  ,		UpperCamelCase__			) else mask_token

          a     =				{} if sp_model_kwargs is None else sp_model_kwargs

          super().__init__(
              do_lower_case=UpperCamelCase__  ,		remove_space=UpperCamelCase__  ,		keep_accents=UpperCamelCase__  ,		bos_token=UpperCamelCase__  ,		eos_token=UpperCamelCase__  ,		unk_token=UpperCamelCase__  ,		sep_token=UpperCamelCase__  ,		pad_token=UpperCamelCase__  ,		cls_token=UpperCamelCase__  ,		mask_token=UpperCamelCase__  ,		additional_special_tokens=UpperCamelCase__  ,		sp_model_kwargs=self.sp_model_kwargs  ,		**UpperCamelCase__  ,		)

          a     =				3

          a     =				do_lower_case
          a     =				remove_space
          a     =				keep_accents
          a     =				vocab_file

          a     =				spm.SentencePieceProcessor(**self.sp_model_kwargs			)
          self.sp_model.Load(UpperCamelCase__			)

          try:
               import jieba
          except ModuleNotFoundError as error:
               raise error.__class__(
                   "You need to install jieba to use CpmTokenizer or CpmTokenizerFast. "
                   "See https://pypi.org/project/jieba/ for installation."			)
          a     =				jieba
          a     =				str.maketrans(" \n"  ,		"\u2582\u2583"			)







     @property
     # Copied from transformers.models.xlnet.tokenization_xlnet.XLNetTokenizer.vocab_size
     def       lowerCAmelCase_    (     self			)  ->   List[str]:



          '''simple docstring'''



          return len(self.sp_model			)







     def       lowerCAmelCase_    (     self			)  ->   Dict:



          '''simple docstring'''



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







     def __getstate__(     self			)  ->   str:



          '''simple docstring'''



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







     def __setstate__(     self  ,		A			)  ->   Dict:



          '''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       lowerCAmelCase_    (     self  ,		A			)  ->   List[Any]:



          '''simple docstring'''



          if self.remove_space:
               a     =				''' '''.join(inputs.strip().split()			)
          else:
               a     =				inputs
          a     =				outputs.replace("``"  ,		"\""			).replace("\'\'"  ,		"\""			)

          if not self.keep_accents:
               a     =				unicodedata.normalize("NFKD"  ,		UpperCamelCase__			)
               a     =				''''''.join([c for c in outputs if not unicodedata.combining(UpperCamelCase__			)]			)
          if self.do_lower_case:
               a     =				outputs.lower()

          return outputs







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



          '''simple docstring'''



          a     =				self.preprocess_text(UpperCamelCase__			)
          a     =				self.sp_model.encode(UpperCamelCase__  ,		out_type=UpperCamelCase__			)
          a     =				[]
          for piece in pieces:
               if len(UpperCamelCase__			) > 1 and piece[-1] == str(","			) and piece[-2].isdigit():
                    a     =				self.sp_model.EncodeAsPieces(piece[:-1].replace(UpperCamelCase__  ,		""			)			)
                    if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
                         if len(cur_pieces[0]			) == 1:
                              a     =				cur_pieces[1:]
                         else:
                              a     =				cur_pieces[0][1:]
                    cur_pieces.append(piece[-1]			)
                    new_pieces.extend(UpperCamelCase__			)
               else:
                    new_pieces.append(UpperCamelCase__			)

          return new_pieces







     def       lowerCAmelCase_    (     self  ,		A			)  ->   Tuple:



          '''simple docstring'''



          return self.sp_model.PieceToId(UpperCamelCase__			)







     def       lowerCAmelCase_    (     self  ,		A			)  ->   Optional[int]:



          '''simple docstring'''



          return self.sp_model.IdToPiece(UpperCamelCase__			)







     def       lowerCAmelCase_    (     self  ,		A			)  ->   str:



          '''simple docstring'''



          a     =				''''''.join(UpperCamelCase__			).replace(UpperCamelCase__  ,		" "			).strip()
          return out_string







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



          '''simple docstring'''



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







     def       lowerCAmelCase_    (     self  ,		A  ,		A = None  ,		A = 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 not None:
               return ([0] * len(UpperCamelCase__			)) + [1] + ([0] * len(UpperCamelCase__			)) + [1, 1]
          return ([0] * len(UpperCamelCase__			)) + [1, 1]







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



          '''simple docstring'''



          a     =				[self.sep_token_id]
          a     =				[2]

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







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



          '''simple docstring'''



          if not os.path.isdir(UpperCamelCase__			):
               logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''			)
               return
          a     =				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:
                    a     =				self.sp_model.serialized_model_proto()
                    fi.write(UpperCamelCase__			)

          return (out_vocab_file,)







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



          '''simple docstring'''



          a     =				super()._decode(*UpperCamelCase__  ,		**UpperCamelCase__			)
          a     =				text.replace(" "  ,		""			).replace("\u2582"  ,		" "			).replace("\u2583"  ,		"\n"			)
          return text







from math import isqrt

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase)      ->					bool:
     return all(number % divisor != 0 for divisor in range(2		, isqrt(__UpperCamelCase) + 1))

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase = 10**6)      ->					int:
     a     =				0
     a     =				1
     a     =				7
     while prime_candidate < max_prime:
          primes_count += is_prime(__UpperCamelCase)

          cube_index += 1
          prime_candidate += 6 * cube_index

     return primes_count


if __name__ == "__main__":
   print(F'{solution() = }')

