


'''simple docstring'''



import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


A__		:					List[str]												=  logging.get_logger(__name__)

A__		:					Any												=  """▁"""

A__		:					Tuple												=  {"""vocab_file""": """vocab.txt""", """sentencepiece_model_ckpt""": """sentencepiece.bpe.model"""}

A__		:					Dict												=  {
    """sentencepiece_model_file""": """sentencepiece.bpe.model""",
    """vocab_file""": """vocab.txt""",
}

A__		:					Union[str, Any]												=  {
    """vocab_file""": {
        """ernie-m-base""": """https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/vocab.txt""",
        """ernie-m-large""": """https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/vocab.txt""",
    },
    """sentencepiece_model_file""": {
        """ernie-m-base""": """https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/sentencepiece.bpe.model""",
        """ernie-m-large""": """https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/sentencepiece.bpe.model""",
    },
}

A__		:					Optional[Any]												=  {
    """ernie-m-base""": 514,
    """ernie-m-large""": 514,
}

A__		:					Union[str, Any]												=  {
    """ernie-m-base""": {"""do_lower_case""": False},
    """ernie-m-large""": {"""do_lower_case""": False},
}





class    UpperCAmelCase_  (_UpperCAmelCase  ):





    """simple docstring"""






    lowerCamelCase  :					List[str]							     =			["input_ids"]

    lowerCamelCase  :					Optional[Any]							     =			VOCAB_FILES_NAMES
    lowerCamelCase  :					Any							     =			PRETRAINED_INIT_CONFIGURATION
    lowerCamelCase  :					Any							     =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowerCamelCase  :					Dict							     =			PRETRAINED_VOCAB_FILES_MAP
    lowerCamelCase  :					List[str]							     =			RESOURCE_FILES_NAMES







    def __init__(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_=None			,     SCREAMING_SNAKE_CASE_=False			,     SCREAMING_SNAKE_CASE_="utf8"			,     SCREAMING_SNAKE_CASE_="[UNK]"			,     SCREAMING_SNAKE_CASE_="[SEP]"			,     SCREAMING_SNAKE_CASE_="[PAD]"			,     SCREAMING_SNAKE_CASE_="[CLS]"			,     SCREAMING_SNAKE_CASE_="[MASK]"			,     SCREAMING_SNAKE_CASE_ = None			,     **SCREAMING_SNAKE_CASE_			,     )				->     None:
         # Mask token behave like a normal word, i.e. include the space before it and
         # is included in the raw text, there should be a match in a non-normalized sentence.

         __lowerCamelCase   :	Dict								=		{} if sp_model_kwargs is None else sp_model_kwargs
         super().__init__(
             do_lower_case=SCREAMING_SNAKE_CASE_			,     unk_token=SCREAMING_SNAKE_CASE_			,     sep_token=SCREAMING_SNAKE_CASE_			,     pad_token=SCREAMING_SNAKE_CASE_			,     cls_token=SCREAMING_SNAKE_CASE_			,     mask_token=SCREAMING_SNAKE_CASE_			,     vocab_file=SCREAMING_SNAKE_CASE_			,     encoding=SCREAMING_SNAKE_CASE_			,     sp_model_kwargs=self.sp_model_kwargs			,     **SCREAMING_SNAKE_CASE_			,     )
         __lowerCamelCase   :	Any								=		do_lower_case
         __lowerCamelCase   :	Union[str, Any]								=		sentencepiece_model_ckpt
         __lowerCamelCase   :	Dict								=		spm.SentencePieceProcessor(**self.sp_model_kwargs	)
         self.sp_model.Load(SCREAMING_SNAKE_CASE_	)

         # to mimic paddlenlp.transformers.ernie_m.tokenizer.ErnieMTokenizer functioning
         if vocab_file is not None:
              __lowerCamelCase   :	Dict								=		self.load_vocab(filepath=SCREAMING_SNAKE_CASE_	)
         else:
              __lowerCamelCase   :	int								=		{self.sp_model.id_to_piece(SCREAMING_SNAKE_CASE_	): id for id in range(self.sp_model.get_piece_size()	)}
         __lowerCamelCase   :	Optional[Any]								=		{v: k for k, v in self.vocab.items()}







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_	)				->     Optional[int]:
         if text is None:
              return None

         __lowerCamelCase   :	Tuple								=		self.tokenize(SCREAMING_SNAKE_CASE_	)
         __lowerCamelCase				,       __lowerCamelCase   :	int								=		'', []

         for i, ch in enumerate(SCREAMING_SNAKE_CASE_	):
              if ch in self.SP_CHAR_MAPPING:
                   __lowerCamelCase   :	Tuple								=		self.SP_CHAR_MAPPING.get(SCREAMING_SNAKE_CASE_	)
              else:
                   __lowerCamelCase   :	Dict								=		unicodedata.normalize('NFKC'			,     SCREAMING_SNAKE_CASE_	)
              if self.is_whitespace(SCREAMING_SNAKE_CASE_	):
                   continue
              normalized_text += ch
              char_mapping.extend([i] * len(SCREAMING_SNAKE_CASE_	)	)

         __lowerCamelCase				,       __lowerCamelCase				,       __lowerCamelCase   :	List[Any]								=		normalized_text, [], 0

         if self.do_lower_case:
              __lowerCamelCase   :	str								=		text.lower()

         for token in split_tokens:
              if token[:1] == "▁":
                   __lowerCamelCase   :	Tuple								=		token[1:]
              __lowerCamelCase   :	Optional[Any]								=		text[offset:].index(SCREAMING_SNAKE_CASE_	) + offset
              __lowerCamelCase   :	Dict								=		start + len(SCREAMING_SNAKE_CASE_	)

              token_mapping.append((char_mapping[start], char_mapping[end - 1] + 1)	)
              __lowerCamelCase   :	List[Any]								=		end
         return token_mapping







    @property
    def       lowercase_				(							self	)				->     str:
         return len(self.vocab	)







    def       lowercase_				(							self	)				->     Union[str, Any]:
         return dict(self.vocab			,     **self.added_tokens_encoder	)







    def __getstate__(							self	)				->     int:
         __lowerCamelCase   :	List[Any]								=		self.__dict__.copy()
         __lowerCamelCase   :	Tuple								=		None
         return state







    def __setstate__(							self			,     SCREAMING_SNAKE_CASE_	)				->     List[str]:
         __lowerCamelCase   :	int								=		d

         # for backward compatibility
         if not hasattr(self			,     'sp_model_kwargs'	):
              __lowerCamelCase   :	str								=		{}

         __lowerCamelCase   :	List[Any]								=		spm.SentencePieceProcessor(**self.sp_model_kwargs	)
         self.sp_model.Load(self.sentencepiece_model_ckpt	)







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_	)				->     int:
         return "".join((self.SP_CHAR_MAPPING.get(SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_	) for c in text)	)







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_=False			,     SCREAMING_SNAKE_CASE_=64			,     SCREAMING_SNAKE_CASE_=0.1	)				->     int:

         if self.sp_model_kwargs.get('enable_sampling'	) is True:
              __lowerCamelCase   :	Optional[int]								=		True
         if self.sp_model_kwargs.get('alpha'	) is not None:
              __lowerCamelCase   :	Union[str, Any]								=		self.sp_model_kwargs.get('alpha'	)
         if self.sp_model_kwargs.get('nbest_size'	) is not None:
              __lowerCamelCase   :	Any								=		self.sp_model_kwargs.get('nbest_size'	)

         if not enable_sampling:
              __lowerCamelCase   :	Dict								=		self.sp_model.EncodeAsPieces(SCREAMING_SNAKE_CASE_	)
         else:
              __lowerCamelCase   :	Union[str, Any]								=		self.sp_model.SampleEncodeAsPieces(SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_	)
         __lowerCamelCase   :	Union[str, Any]								=		[]
         for pi, piece in enumerate(SCREAMING_SNAKE_CASE_	):
              if piece == SPIECE_UNDERLINE:
                   if not pieces[pi + 1].startswith(SCREAMING_SNAKE_CASE_	) and pi != 0:
                        new_pieces.append(SCREAMING_SNAKE_CASE_	)
                        continue
                   else:
                        continue
              __lowerCamelCase   :	Dict								=		0
              for i, chunk in enumerate(SCREAMING_SNAKE_CASE_	):
                   if chunk == SPIECE_UNDERLINE:
                        continue
                   if self.is_ch_char(SCREAMING_SNAKE_CASE_	) or self.is_punct(SCREAMING_SNAKE_CASE_	):
                        if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
                             new_pieces.append(piece[lst_i:i]	)
                        new_pieces.append(SCREAMING_SNAKE_CASE_	)
                        __lowerCamelCase   :	Union[str, Any]								=		i + 1
                   elif chunk.isdigit() and i > 0 and not piece[i - 1].isdigit():
                        if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
                             new_pieces.append(piece[lst_i:i]	)
                        __lowerCamelCase   :	int								=		i
                   elif not chunk.isdigit() and i > 0 and piece[i - 1].isdigit():
                        if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
                             new_pieces.append(piece[lst_i:i]	)
                        __lowerCamelCase   :	int								=		i
              if len(SCREAMING_SNAKE_CASE_	) > lst_i:
                   new_pieces.append(piece[lst_i:]	)
         return new_pieces







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_	)				->     Any:
         __lowerCamelCase   :	Any								=		''.join(SCREAMING_SNAKE_CASE_	).replace(SCREAMING_SNAKE_CASE_			,     ' '	).strip()
         return out_string







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_	)				->     Union[str, Any]:
         __lowerCamelCase   :	List[Any]								=		self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_	)
         __lowerCamelCase   :	Tuple								=		''.join(SCREAMING_SNAKE_CASE_	).replace(SCREAMING_SNAKE_CASE_			,     ' '	).strip()
         return out_string







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_	)				->     Dict:
         return self.vocab.get(SCREAMING_SNAKE_CASE_			,     self.vocab.get(self.unk_token	)	)







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_	)				->     Union[str, Any]:
         return self.reverse_vocab.get(SCREAMING_SNAKE_CASE_			,     self.unk_token	)







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_=None	)				->     List[str]:
         if token_ids_a is None:
              return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         __lowerCamelCase   :	int								=		[self.cls_token_id]
         __lowerCamelCase   :	int								=		[self.sep_token_id]
         return _cls + token_ids_a + _sep + _sep + token_ids_a + _sep







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_=None	)				->     Any:
         if offset_mapping_a is None:
              return [(0, 0)] + offset_mapping_a + [(0, 0)]

         return [(0, 0)] + offset_mapping_a + [(0, 0), (0, 0)] + offset_mapping_a + [(0, 0)]







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_=None			,     SCREAMING_SNAKE_CASE_=False	)				->     Optional[Any]:

         if already_has_special_tokens:
              if token_ids_a is not None:
                   raise ValueError(
                       'You should not supply a second sequence if the provided sequence of '
                       'ids is already formatted with special tokens for the model.'	)
              return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

         if token_ids_a is not None:
              return [1] + ([0] * len(SCREAMING_SNAKE_CASE_	)) + [1, 1] + ([0] * len(SCREAMING_SNAKE_CASE_	)) + [1]
         return [1] + ([0] * len(SCREAMING_SNAKE_CASE_	)) + [1]







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_ = None	)				->     List[int]:
         # called when `add_special_tokens` is True, so align with `build_inputs_with_special_tokens` method
         if token_ids_a is None:
              # [CLS] X [SEP]
              return (len(SCREAMING_SNAKE_CASE_	) + 2) * [0]

         # [CLS] A [SEP] [SEP] B [SEP]
         return [0] * (len(SCREAMING_SNAKE_CASE_	) + 1) + [1] * (len(SCREAMING_SNAKE_CASE_	) + 3)







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_	)				->     Dict:
         if "\u4e00" <= char <= "\u9fff":
              return True
         return False







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_	)				->     int:
         if ("a" <= char <= "z") or ("A" <= char <= "Z"):
              return True
         return False







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_	)				->     Tuple:
         if char in ",;:.?!~，；：。？！《》【】":
              return True
         return False







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_	)				->     Tuple:
         if char == " " or char == "\t" or char == "\n" or char == "\r":
              return True
         if len(SCREAMING_SNAKE_CASE_	) == 1:
              __lowerCamelCase   :	int								=		unicodedata.category(SCREAMING_SNAKE_CASE_	)
              if cat == "Zs":
                   return True
         return False







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_	)				->     int:
         __lowerCamelCase   :	Dict								=		{}
         with io.open(SCREAMING_SNAKE_CASE_			,     'r'			,     encoding='utf-8'	) as f:
              for index, line in enumerate(SCREAMING_SNAKE_CASE_	):
                   __lowerCamelCase   :	Optional[int]								=		line.rstrip('\n'	)
                   __lowerCamelCase   :	List[Any]								=		int(SCREAMING_SNAKE_CASE_	)

         return token_to_idx







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_ = None	)				->     Tuple[str]:
         __lowerCamelCase   :	Tuple								=		0
         if os.path.isdir(SCREAMING_SNAKE_CASE_	):
              __lowerCamelCase   :	str								=		os.path.join(
                  SCREAMING_SNAKE_CASE_			,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)
         else:
              __lowerCamelCase   :	str								=		(filename_prefix + '-' if filename_prefix else '') + save_directory
         with open(SCREAMING_SNAKE_CASE_			,     'w'			,     encoding='utf-8'	) as writer:
              for token, token_index in sorted(self.vocab.items()			,     key=lambda SCREAMING_SNAKE_CASE_	: kv[1]	):
                   if index != token_index:
                        logger.warning(
                            f'Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive.'
                            ' Please check that the vocabulary is not corrupted!'	)
                        __lowerCamelCase   :	Dict								=		token_index
                   writer.write(token + '\n'	)
                   index += 1

         __lowerCamelCase   :	str								=		os.path.join(SCREAMING_SNAKE_CASE_			,     'sentencepiece.bpe.model'	)
         with open(SCREAMING_SNAKE_CASE_			,     'wb'	) as fi:
              __lowerCamelCase   :	Tuple								=		self.sp_model.serialized_model_proto()
              fi.write(SCREAMING_SNAKE_CASE_	)

         return (vocab_file,)










'''simple docstring'''



from math import isqrt



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



def 			UpperCAmelCase__					(	UpperCAmelCase_    :				int = 10**6							)     ->		int:
     __lowerCamelCase   :	Optional[Any]								=		0
     __lowerCamelCase   :	Optional[int]								=		1
     __lowerCamelCase   :	List[str]								=		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() = }''')






