





'''simple docstring'''

import math

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

def 						__magic_name__       (							__UpperCAmelCase = 10001      )						->					int:

   '''simple docstring'''







   try:
      __SCREAMING_SNAKE_CASE      							=       int(__UpperCAmelCase      )
   except (TypeError, ValueError):
      raise TypeError("""Parameter nth must be int or castable to int."""      ) from None
   if nth <= 0:
      raise ValueError("""Parameter nth must be greater than or equal to one."""      )
   __SCREAMING_SNAKE_CASE      							=       []
   __SCREAMING_SNAKE_CASE      							=       2
   while len(__UpperCAmelCase      ) < nth:
      if is_prime(__UpperCAmelCase      ):
         primes.append(__UpperCAmelCase      )
         num += 1
      else:
         num += 1
   return primes[len(__UpperCAmelCase      ) - 1]


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












'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

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


a        =						logging.get_logger(__name__)

a        =						{
    "camembert-base": "https://huggingface.co/camembert-base/resolve/main/config.json",
    "umberto-commoncrawl-cased-v1": (
        "https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"
    ),
    "umberto-wikipedia-uncased-v1": (
        "https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"
    ),
}







class __a (   _snake_case			):
   __UpperCamelCase   : Tuple	      =	'camembert'





   def __init__(					self				:			int				,lowerCamelCase				:			List[Any]=3_0522				,lowerCamelCase				:			List[Any]=768				,lowerCamelCase				:			str=12				,lowerCamelCase				:			List[str]=12				,lowerCamelCase				:			Optional[Any]=3072				,lowerCamelCase				:			Tuple="gelu"				,lowerCamelCase				:			List[str]=0.1				,lowerCamelCase				:			Tuple=0.1				,lowerCamelCase				:			Union[str, Any]=512				,lowerCamelCase				:			Dict=2				,lowerCamelCase				:			Tuple=0.02				,lowerCamelCase				:			List[Any]=1E-1_2				,lowerCamelCase				:			Union[str, Any]=1				,lowerCamelCase				:			Optional[Any]=0				,lowerCamelCase				:			List[Any]=2				,lowerCamelCase				:			List[str]="absolute"				,lowerCamelCase				:			int=True				,lowerCamelCase				:			Any=None				,**lowerCamelCase				:			Optional[Any]				,):

      '''simple docstring'''

      super().__init__(pad_token_id=lowerCamelCase				,bos_token_id=lowerCamelCase				,eos_token_id=lowerCamelCase				,**lowerCamelCase    )

      __SCREAMING_SNAKE_CASE      							=       vocab_size
      __SCREAMING_SNAKE_CASE      							=       hidden_size
      __SCREAMING_SNAKE_CASE      							=       num_hidden_layers
      __SCREAMING_SNAKE_CASE      							=       num_attention_heads
      __SCREAMING_SNAKE_CASE      							=       hidden_act
      __SCREAMING_SNAKE_CASE      							=       intermediate_size
      __SCREAMING_SNAKE_CASE      							=       hidden_dropout_prob
      __SCREAMING_SNAKE_CASE      							=       attention_probs_dropout_prob
      __SCREAMING_SNAKE_CASE      							=       max_position_embeddings
      __SCREAMING_SNAKE_CASE      							=       type_vocab_size
      __SCREAMING_SNAKE_CASE      							=       initializer_range
      __SCREAMING_SNAKE_CASE      							=       layer_norm_eps
      __SCREAMING_SNAKE_CASE      							=       position_embedding_type
      __SCREAMING_SNAKE_CASE      							=       use_cache
      __SCREAMING_SNAKE_CASE      							=       classifier_dropout







class __a (   _snake_case			):





   @property
   def      UpperCAmelCase__     (					self				:			Optional[Any]    ):

      '''simple docstring'''

      if self.task == "multiple-choice":
         __SCREAMING_SNAKE_CASE      							=       {0: """batch""", 1: """choice""", 2: """sequence"""}
      else:
         __SCREAMING_SNAKE_CASE      							=       {0: """batch""", 1: """sequence"""}
      return OrderedDict(
          [
              ("""input_ids""", dynamic_axis),
              ("""attention_mask""", dynamic_axis),
          ]    )





