




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


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

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

class 		lowercase_       (	lowerCAmelCase__				):
					__UpperCamelCase     	= "vilt"




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


									'''simple docstring'''


									super().__init__(tie_word_embeddings=_lowercase,     **_lowercase)

									__lowerCAmelCase					=  vocab_size
									__lowerCAmelCase					=  type_vocab_size
									__lowerCAmelCase					=  modality_type_vocab_size
									__lowerCAmelCase					=  max_position_embeddings

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

									__lowerCAmelCase					=  image_size
									__lowerCAmelCase					=  patch_size
									__lowerCAmelCase					=  num_channels
									__lowerCAmelCase					=  qkv_bias
									__lowerCAmelCase					=  max_image_length
									__lowerCAmelCase					=  num_images











'''simple docstring'''





import math
from decimal import Decimal, getcontext


def 					UpperCamelCase						(	snake_case = 4_00_00_00 ):




   '''simple docstring'''

   try:
      SCREAMING_SNAKE_CASE__      :					List[Any]							    =			int(snake_case )
   except (TypeError, ValueError):
      raise TypeError('''Parameter n must be int or castable to int.''' )
   if n <= 0:
      raise ValueError('''Parameter n must be greater than or equal to one.''' )
   SCREAMING_SNAKE_CASE__      :					Optional[int]							    =			1_00
   SCREAMING_SNAKE_CASE__      :					int							    =			(Decimal(5 ) ** Decimal(0.5 ) + 1) / Decimal(2 )

   SCREAMING_SNAKE_CASE__      :					int							    =			(math.floor(math.log(n * (phi + 2)						,  snake_case ) - 1 ) // 3) * 3 + 2
   SCREAMING_SNAKE_CASE__      :					int							    =			Decimal(round(phi ** Decimal(index + 1 ) ) ) / (phi + 2)
   SCREAMING_SNAKE_CASE__      :					Any							    =			num // 2
   return int(snake_case )


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

