




from ...configuration_utils import PretrainedConfig
from ...utils import logging


a_										=       logging.get_logger(__name__)

a_										=       {
    "dandelin/vilt-b32-mlm": "https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json"
}

class 	_lowerCamelCase  (     _SCREAMING_SNAKE_CASE				):

      """simple docstring"""

      lowerCAmelCase__     :	List[str]      =   "vilt"







      def __init__(       self   :	Tuple	,    snake_case   :	int=30522	,    snake_case   :	Any=2	,    snake_case   :	Tuple=2	,    snake_case   :	Optional[int]=40	,    snake_case   :	int=768	,    snake_case   :	List[str]=12	,    snake_case   :	int=12	,    snake_case   :	Any=3072	,    snake_case   :	Tuple="gelu"	,    snake_case   :	Dict=0.0	,    snake_case   :	Dict=0.0	,    snake_case   :	int=0.02	,    snake_case   :	Dict=1E-12	,    snake_case   :	Optional[int]=384	,    snake_case   :	Union[str, Any]=32	,    snake_case   :	Optional[Any]=3	,    snake_case   :	Dict=True	,    snake_case   :	Tuple=-1	,    snake_case   :	str=False	,    snake_case   :	str=-1	,    **snake_case   :	List[Any]	,    ):
          super().__init__(tie_word_embeddings=snake_case	,    **snake_case			)

          __UpperCamelCase											=  vocab_size
          __UpperCamelCase											=  type_vocab_size
          __UpperCamelCase											=  modality_type_vocab_size
          __UpperCamelCase											=  max_position_embeddings

          __UpperCamelCase											=  hidden_size
          __UpperCamelCase											=  num_hidden_layers
          __UpperCamelCase											=  num_attention_heads
          __UpperCamelCase											=  intermediate_size
          __UpperCamelCase											=  hidden_act
          __UpperCamelCase											=  hidden_dropout_prob
          __UpperCamelCase											=  attention_probs_dropout_prob
          __UpperCamelCase											=  initializer_range
          __UpperCamelCase											=  layer_norm_eps

          __UpperCamelCase											=  image_size
          __UpperCamelCase											=  patch_size
          __UpperCamelCase											=  num_channels
          __UpperCamelCase											=  qkv_bias
          __UpperCamelCase											=  max_image_length
          __UpperCamelCase											=  num_images












def    __SCREAMING_SNAKE_CASE				(					lowercase_ )    ->		int:

    """simple docstring"""


    if not isinstance(lowercase_   ,       lowercase_ ):
        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    __SCREAMING_SNAKE_CASE				(					lowercase_ )    ->		int:

    """simple docstring"""


    if not isinstance(lowercase_   ,       lowercase_ ):
        raise TypeError('''dynamic_lucas_number accepts only integer arguments.''' )
    __UpperCamelCase						, __UpperCamelCase											=  2, 1
    for _ in range(lowercase_ ):
        __UpperCamelCase						, __UpperCamelCase											=  b, a + b
    return a


if __name__ == "__main__":
 from doctest import testmod

 testmod()
 a_										=       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)))






