






"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowerCAmelCase         =							logging.get_logger(__name__)

_lowerCAmelCase         =							{
    "google/vivit-b-16x2-kinetics400": (
        "https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"
    ),
    # See all Vivit models at https://huggingface.co/models?filter=vivit
}



class      SCREAMING_SNAKE_CASE  (				_SCREAMING_SNAKE_CASE						):





	"""simple docstring"""




	_A       :				Tuple    =				"""vivit"""





	def __init__(self     ,     lowerCAmelCase_=224     ,     lowerCAmelCase_=32     ,     lowerCAmelCase_=[2, 16, 16]     ,     lowerCAmelCase_=3     ,     lowerCAmelCase_=768     ,     lowerCAmelCase_=12     ,     lowerCAmelCase_=12     ,     lowerCAmelCase_=3072     ,     lowerCAmelCase_="gelu_fast"     ,     lowerCAmelCase_=0.0     ,     lowerCAmelCase_=0.0     ,     lowerCAmelCase_=0.02     ,     lowerCAmelCase_=1e-0_6     ,     lowerCAmelCase_=True     ,     **lowerCAmelCase_     ,     ):
		A_		:						List[Any]	    =   hidden_size
		A_		:						Dict	    =   num_hidden_layers
		A_		:						Any	    =   num_attention_heads
		A_		:						Optional[Any]	    =   intermediate_size
		A_		:						List[str]	    =   hidden_act
		A_		:						int	    =   hidden_dropout_prob
		A_		:						Optional[Any]	    =   attention_probs_dropout_prob
		A_		:						List[str]	    =   initializer_range
		A_		:						List[str]	    =   layer_norm_eps

		A_		:						Any	    =   image_size
		A_		:						Union[str, Any]	    =   num_frames
		A_		:						Optional[int]	    =   tubelet_size
		A_		:						Optional[Any]	    =   num_channels
		A_		:						List[str]	    =   qkv_bias

		super().__init__(**lowerCAmelCase_							)









"""simple docstring"""
import math






def 			__UpperCamelCase	(		snake_case__   ,   snake_case__					):
	if (
	    not isinstance(snake_case__   ,   (int, float)					)
	    or power_factor < -1
	    or power_factor > 1
	):
		raise ValueError("""power_factor must be a valid float value between -1 and 1."""					)
	return apparent_power * power_factor






def 			__UpperCamelCase	(		snake_case__   ,   snake_case__					):
	if (
	    not isinstance(snake_case__   ,   (int, float)					)
	    or power_factor < -1
	    or power_factor > 1
	):
		raise ValueError("""power_factor must be a valid float value between -1 and 1."""					)
	return apparent_power * math.sqrt(1 - power_factor**2					)


if __name__ == "__main__":
							import doctest

							doctest.testmod()

