





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenization_utils import JiebaPreTokenizer


lowercase    : Optional[int]    	=  logging.get_logger(__name__)

lowercase    : Union[str, Any]    	=  {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

lowercase    : Union[str, Any]    	=  {
    """vocab_file""": {
        """junnyu/roformer_chinese_small""": """https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/vocab.txt""",
        """junnyu/roformer_chinese_base""": """https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/vocab.txt""",
        """junnyu/roformer_chinese_char_small""": (
            """https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/vocab.txt"""
        ),
        """junnyu/roformer_chinese_char_base""": (
            """https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/vocab.txt"""
        ),
        """junnyu/roformer_small_discriminator""": (
            """https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/vocab.txt"""
        ),
        """junnyu/roformer_small_generator""": (
            """https://huggingface.co/junnyu/roformer_small_generator/resolve/main/vocab.txt"""
        ),
    }
}

lowercase    : str    	=  {
    """junnyu/roformer_chinese_small""": 1536,
    """junnyu/roformer_chinese_base""": 1536,
    """junnyu/roformer_chinese_char_small""": 512,
    """junnyu/roformer_chinese_char_base""": 512,
    """junnyu/roformer_small_discriminator""": 128,
    """junnyu/roformer_small_generator""": 128,
}


lowercase    : int    	=  {
    """junnyu/roformer_chinese_small""": {"""do_lower_case""": True},
    """junnyu/roformer_chinese_base""": {"""do_lower_case""": True},
    """junnyu/roformer_chinese_char_small""": {"""do_lower_case""": True},
    """junnyu/roformer_chinese_char_base""": {"""do_lower_case""": True},
    """junnyu/roformer_small_discriminator""": {"""do_lower_case""": True},
    """junnyu/roformer_small_generator""": {"""do_lower_case""": True},
}

class  __A(						__UpperCAmelCase ):
     __A	  =       VOCAB_FILES_NAMES
     __A	  =       PRETRAINED_VOCAB_FILES_MAP
     __A	  =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __A	  =       PRETRAINED_INIT_CONFIGURATION
     __A	  =       RoFormerTokenizer

     def __init__(      self,       A=None,       A=None,       A=True,       A="[UNK]",       A="[SEP]",       A="[PAD]",       A="[CLS]",       A="[MASK]",       A=True,       A=None,       **A,       ):





            """simple docstring"""

            super().__init__(
                A,       tokenizer_file=A,       do_lower_case=A,       unk_token=A,       sep_token=A,       pad_token=A,       cls_token=A,       mask_token=A,       tokenize_chinese_chars=A,       strip_accents=A,       **A,       )

            _UpperCamelCase              =						json.loads(self.backend_tokenizer.normalizer.__getstate__()      )
            if (
                pre_tok_state.get('''lowercase''',       A      ) != do_lower_case
                or pre_tok_state.get('''strip_accents''',       A      ) != strip_accents
            ):
                   _UpperCamelCase              =						getattr(A,       pre_tok_state.pop('''type'''      )      )
                   _UpperCamelCase              =						do_lower_case
                   _UpperCamelCase              =						strip_accents
                   _UpperCamelCase              =						pre_tok_class(**A      )

            _UpperCamelCase              =						do_lower_case

     def __getstate__(      self      ):





            """simple docstring"""

            _UpperCamelCase              =						self.__dict__.copy()
            _UpperCamelCase              =						BertPreTokenizer()
            return state

     def __setstate__(      self,       A      ):





            """simple docstring"""

            _UpperCamelCase              =						d
            _UpperCamelCase              =						self.__dict__['''_tokenizer'''].get_vocab()
            _UpperCamelCase              =						PreTokenizer.custom(JiebaPreTokenizer(A      )      )

     def 	_UpperCamelCase     (      self,       A,       A=None      ):





            """simple docstring"""

            _UpperCamelCase              =						[self.cls_token_id] + token_ids_a + [self.sep_token_id]

            if token_ids_a:
                   output += token_ids_a + [self.sep_token_id]

            return output

     def 	_UpperCamelCase     (      self,       A,       A = None      ):





            """simple docstring"""

            _UpperCamelCase              =						[self.sep_token_id]
            _UpperCamelCase              =						[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]

     def 	_UpperCamelCase     (      self,       A,       A = None      ):





            """simple docstring"""

            _UpperCamelCase              =						self._tokenizer.model.save(A,       name=A      )
            return tuple(A      )



     def 	_UpperCamelCase     (      self,       A,       A=None,       A=None,       A=False,       **A,       ):





            """simple docstring"""

            _UpperCamelCase              =						BertPreTokenizer()
            return super().save_pretrained(A,       A,       A,       A,       **A      )













from __future__ import annotations

import math


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):

       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(lowerCAmelCase					) + 1					)    ,       6					):
              if number % i == 0 or number % (i + 2) == 0:
                     return False
       return True


lowercase    : Tuple    	=  [num for num in range(3, 10_0001, 2) if not is_prime(num)]


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       if not isinstance(lowerCAmelCase    ,       lowerCAmelCase					):
              raise ValueError('''n must be an integer'''					)
       if n <= 0:
              raise ValueError('''n must be >= 0'''					)

       _UpperCamelCase              =						[]
       for num in range(len(lowerCAmelCase					)					):
              _UpperCamelCase              =						0
              while 2 * i * i <= odd_composites[num]:
                     _UpperCamelCase              =						odd_composites[num] - 2 * i * i
                     if is_prime(lowerCAmelCase					):
                            break
                     i += 1
              else:
                     list_nums.append(odd_composites[num]					)
                     if len(lowerCAmelCase					) == n:
                            return list_nums

       return []


def     SCREAMING_SNAKE_CASE			(      ):
       return compute_nums(1					)[0]


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






