code: 
  
  
  
  
  
  
  """simple docstring"""
  def        A	(							__snake_case:   int     )						->		int:
  
         """simple docstring"""
  
  
  
  
  
         if not isinstance(__snake_case   ,    __snake_case     ):
                raise TypeError('recursive_lucas_number accepts only integer arguments.'     )
         if n_th_number == 0:
                return 2
         if n_th_number == 1:
                return 1
  
         return recursive_lucas_number(n_th_number - 1     ) + recursive_lucas_number(
             n_th_number - 2     )
  
  
  def        A	(							__snake_case:   int     )						->		int:
  
         """simple docstring"""
  
  
  
  
  
         if not isinstance(__snake_case   ,    __snake_case     ):
                raise TypeError('dynamic_lucas_number accepts only integer arguments.'     )
         __magic_name__							,     __magic_name__										=						2, 1
         for _ in range(__snake_case     ):
                __magic_name__							,     __magic_name__										=						b, a + b
         return a
  
  
  if __name__ == "__main__":
   from doctest import testmod
  
   testmod()
   snake_case   :   Tuple    		=		int(input("""Enter the number of terms in lucas series:\n""").strip())
   print("""Using recursive function to calculate lucas series:""")
   print(""" """.join(str(recursive_lucas_number(i)) for i in range(n)))
   print("""\nUsing dynamic function to calculate lucas series:""")
   print(""" """.join(str(dynamic_lucas_number(i)) for i in range(n)))
style_context: 
  
  
  
  
  
  
  """simple docstring"""
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  snake_case   :   int    		=		logging.get_logger(__name__)
  
  snake_case   :   List[str]    		=		{
      """uw-madison/nystromformer-512""": """https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json""",
      # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
  }
  
  
  
  class 					UpperCamelCase__   (							a_):
  
  
  
  
  
  
  
      """simple docstring"""
      __UpperCAmelCase											=   """nystromformer"""
  
  
  
  
  
  
  
      def __init__(		self   :  Dict							,						UpperCamelCase_   :  Optional[Any]=3_0_0_0_0							,						UpperCamelCase_   :  Dict=7_6_8							,						UpperCamelCase_   :  Tuple=1_2							,						UpperCamelCase_   :  Any=1_2							,						UpperCamelCase_   :  List[str]=3_0_7_2							,						UpperCamelCase_   :  Tuple="gelu_new"							,						UpperCamelCase_   :  Optional[Any]=0.1							,						UpperCamelCase_   :  str=0.1							,						UpperCamelCase_   :  Tuple=5_1_0							,						UpperCamelCase_   :  Optional[int]=2							,						UpperCamelCase_   :  Optional[int]=6_4							,						UpperCamelCase_   :  Tuple=6_4							,						UpperCamelCase_   :  Optional[int]=6_5							,						UpperCamelCase_   :  Optional[int]=False							,						UpperCamelCase_   :  List[str]=0.02							,						UpperCamelCase_   :  List[Any]=1e-5							,						UpperCamelCase_   :  Union[str, Any]=1							,						UpperCamelCase_   :  Tuple=0							,						UpperCamelCase_   :  List[Any]=2							,						**UpperCamelCase_   :  str							,						):
  
  
  
  
  
             '''simple docstring'''
  
             __magic_name__										=						vocab_size
             __magic_name__										=						max_position_embeddings
             __magic_name__										=						hidden_size
             __magic_name__										=						num_hidden_layers
             __magic_name__										=						num_attention_heads
             __magic_name__										=						intermediate_size
             __magic_name__										=						hidden_act
             __magic_name__										=						hidden_dropout_prob
             __magic_name__										=						attention_probs_dropout_prob
             __magic_name__										=						initializer_range
             __magic_name__										=						type_vocab_size
             __magic_name__										=						segment_means_seq_len
             __magic_name__										=						num_landmarks
             __magic_name__										=						conv_kernel_size
             __magic_name__										=						inv_coeff_init_option
             __magic_name__										=						layer_norm_eps
             super().__init__(pad_token_id=UpperCamelCase_							,						bos_token_id=UpperCamelCase_							,						eos_token_id=UpperCamelCase_							,						**UpperCamelCase_   )