




'''simple docstring'''



from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_openai import OpenAIGPTTokenizer


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

UpperCAmelCase_				:     Dict     			=						{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCAmelCase_				:     Any     			=						{
    '''vocab_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/vocab.json'''},
    '''merges_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/merges.txt'''},
    '''tokenizer_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/tokenizer.json'''},
}

UpperCAmelCase_				:     Any     			=						{
    '''openai-gpt''': 5_1_2,
}





class 			lowerCAmelCase      (       __lowerCAmelCase):
       __lowercase     :					Dict       				=	VOCAB_FILES_NAMES
       __lowercase     :					str       				=	PRETRAINED_VOCAB_FILES_MAP
       __lowercase     :					List[Any]       				=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __lowercase     :					Optional[int]       				=	['''input_ids''', '''attention_mask''']
       __lowercase     :					List[Any]       				=	OpenAIGPTTokenizer


       def __init__(      self			,     __SCREAMING_SNAKE_CASE=None			,     __SCREAMING_SNAKE_CASE=None			,     __SCREAMING_SNAKE_CASE=None			,     __SCREAMING_SNAKE_CASE="<unk>"			,     **__SCREAMING_SNAKE_CASE     )					->     int:



            '''simple docstring'''




            super().__init__(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     tokenizer_file=__SCREAMING_SNAKE_CASE			,     unk_token=__SCREAMING_SNAKE_CASE			,     **__SCREAMING_SNAKE_CASE     )


       @property
       def 					lowerCAmelCase					(      self     )					->     str:



            '''simple docstring'''




            return True




       def 					lowerCAmelCase					(      self			,     __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE = None     )					->     Tuple[str]:



            '''simple docstring'''




            __snake_case			    =     self._tokenizer.model.save(__SCREAMING_SNAKE_CASE			,     name=__SCREAMING_SNAKE_CASE     )
            return tuple(__SCREAMING_SNAKE_CASE     )












'''simple docstring'''



from __future__ import annotations

import math
from itertools import permutations







def 	_UpperCamelCase       (_lowerCamelCase							:   int		)->      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(_lowerCamelCase		) + 1		)      ,		6		):
          if number % i == 0 or number % (i + 2) == 0:
               return False
     return True







def 	_UpperCamelCase       (_lowerCamelCase							:   int = 7		)->      int:




     '''simple docstring'''





     __snake_case			    =     ''''''.join(str(_lowerCamelCase		) for i in range(1      ,		n + 1		)		)
     __snake_case			    =     [int(''''''.join(_lowerCamelCase		)		) for i in permutations(_lowerCamelCase      ,		_lowerCamelCase		)]
     __snake_case			    =     [num for num in perm_list if is_prime(_lowerCamelCase		)]
     return max(_lowerCamelCase		) if pandigitals else 0


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






