

from __future__ import annotations

import math
from itertools import permutations





def  _snake_case		(snake_case_					:     int  )							->		bool:

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





def  _snake_case		(snake_case_					:     int = 7  )							->		int:
  __UpperCAmelCase	:  Dict		=     ''.join(str(snake_case_  ) for i in range(1    ,       n + 1  )  )
  __UpperCAmelCase	:  Any		=     [int(''.join(snake_case_  )  ) for i in permutations(snake_case_    ,       snake_case_  )]
  __UpperCAmelCase	:  Dict		=     [num for num in perm_list if is_prime(snake_case_  )]
  return max(snake_case_  ) if pandigitals else 0


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












from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


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

UpperCAmelCase_       : int							=    {
    """google/electra-small-generator""": """https://huggingface.co/google/electra-small-generator/resolve/main/config.json""",
    """google/electra-base-generator""": """https://huggingface.co/google/electra-base-generator/resolve/main/config.json""",
    """google/electra-large-generator""": """https://huggingface.co/google/electra-large-generator/resolve/main/config.json""",
    """google/electra-small-discriminator""": (
        """https://huggingface.co/google/electra-small-discriminator/resolve/main/config.json"""
    ),
    """google/electra-base-discriminator""": (
        """https://huggingface.co/google/electra-base-discriminator/resolve/main/config.json"""
    ),
    """google/electra-large-discriminator""": (
        """https://huggingface.co/google/electra-large-discriminator/resolve/main/config.json"""
    ),
}





class   lowercase__     (				__A	):
  __UpperCamelCase						  =	"""electra"""







  def __init__(						self     ,    _lowercase=30_522     ,    _lowercase=128     ,    _lowercase=256     ,    _lowercase=12     ,    _lowercase=4     ,    _lowercase=1_024     ,    _lowercase="gelu"     ,    _lowercase=0.1     ,    _lowercase=0.1     ,    _lowercase=512     ,    _lowercase=2     ,    _lowercase=0.02     ,    _lowercase=1e-12     ,    _lowercase="first"     ,    _lowercase=True     ,    _lowercase="gelu"     ,    _lowercase=0.1     ,    _lowercase=0     ,    _lowercase="absolute"     ,    _lowercase=True     ,    _lowercase=None     ,    **_lowercase     ,    ):
       super().__init__(pad_token_id=_lowercase     ,    **_lowercase    )

       lowerCAmelCase_       :							Dict			 =		vocab_size
       lowerCAmelCase_       :							Tuple			 =		embedding_size
       lowerCAmelCase_       :							Any			 =		hidden_size
       lowerCAmelCase_       :							Optional[Any]			 =		num_hidden_layers
       lowerCAmelCase_       :							Union[str, Any]			 =		num_attention_heads
       lowerCAmelCase_       :							List[str]			 =		intermediate_size
       lowerCAmelCase_       :							Union[str, Any]			 =		hidden_act
       lowerCAmelCase_       :							Any			 =		hidden_dropout_prob
       lowerCAmelCase_       :							Optional[Any]			 =		attention_probs_dropout_prob
       lowerCAmelCase_       :							int			 =		max_position_embeddings
       lowerCAmelCase_       :							Optional[int]			 =		type_vocab_size
       lowerCAmelCase_       :							Dict			 =		initializer_range
       lowerCAmelCase_       :							Any			 =		layer_norm_eps

       lowerCAmelCase_       :							str			 =		summary_type
       lowerCAmelCase_       :							Optional[int]			 =		summary_use_proj
       lowerCAmelCase_       :							Optional[int]			 =		summary_activation
       lowerCAmelCase_       :							int			 =		summary_last_dropout
       lowerCAmelCase_       :							str			 =		position_embedding_type
       lowerCAmelCase_       :							Optional[int]			 =		use_cache
       lowerCAmelCase_       :							Tuple			 =		classifier_dropout





class   lowercase__     (				__A	):







  @property
  def 						UpperCAmelCase__		(						self    ):
       if self.task == "multiple-choice":
            lowerCAmelCase_       :							Optional[int]			 =		{0: """batch""", 1: """choice""", 2: """sequence"""}
       else:
            lowerCAmelCase_       :							Any			 =		{0: """batch""", 1: """sequence"""}
       return OrderedDict(
           [
               ("""input_ids""", dynamic_axis),
               ("""attention_mask""", dynamic_axis),
               ("""token_type_ids""", dynamic_axis),
           ]    )
