





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


_UpperCAmelCase				:       int	   =				logging.get_logger(__name__)

_UpperCAmelCase				:       Tuple	   =				{
    """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    lowerCAmelCase							(					__UpperCamelCase			):
 UpperCAmelCase__													=		"""vivit"""
 def __init__(      self  :      Optional[int]			,     UpperCAmelCase  :      List[Any]=224			,     UpperCAmelCase  :      List[str]=32			,     UpperCAmelCase  :      Optional[int]=[2, 16, 16]			,     UpperCAmelCase  :      int=3			,     UpperCAmelCase  :      int=768			,     UpperCAmelCase  :      List[str]=12			,     UpperCAmelCase  :      int=12			,     UpperCAmelCase  :      List[Any]=3072			,     UpperCAmelCase  :      Optional[Any]="gelu_fast"			,     UpperCAmelCase  :      Any=0.0			,     UpperCAmelCase  :      int=0.0			,     UpperCAmelCase  :      Optional[int]=0.0_2			,     UpperCAmelCase  :      Tuple=1e-06			,     UpperCAmelCase  :      Optional[int]=True			,     **UpperCAmelCase  :      Dict			,     )			->	str:
     lowerCamelCase__    :      Any					 =		hidden_size
     lowerCamelCase__    :      List[str]					 =		num_hidden_layers
     lowerCamelCase__    :      Dict					 =		num_attention_heads
     lowerCamelCase__    :      List[Any]					 =		intermediate_size
     lowerCamelCase__    :      Any					 =		hidden_act
     lowerCamelCase__    :      Tuple					 =		hidden_dropout_prob
     lowerCamelCase__    :      Union[str, Any]					 =		attention_probs_dropout_prob
     lowerCamelCase__    :      Optional[int]					 =		initializer_range
     lowerCamelCase__    :      Dict					 =		layer_norm_eps

     lowerCamelCase__    :      int					 =		image_size
     lowerCamelCase__    :      Any					 =		num_frames
     lowerCamelCase__    :      Optional[Any]					 =		tubelet_size
     lowerCamelCase__    :      Tuple					 =		num_channels
     lowerCamelCase__    :      Any					 =		qkv_bias

     super().__init__(**UpperCAmelCase	)












def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase = 100_0000 )			->     int:
    lowerCamelCase__    :      int					 =		limit + 1
    lowerCamelCase__    :      Optional[Any]					 =		[0] * limit
    for first_term in range(1						,	_UpperCAmelCase ):
        for n in range(_UpperCAmelCase						,	_UpperCAmelCase						,	_UpperCAmelCase ):
            lowerCamelCase__    :      Optional[Any]					 =		first_term + n / first_term
            if common_difference % 4:  # d must be divisble by 4
                continue
            else:
                common_difference /= 4
                if (
                    first_term > common_difference
                    and first_term < 4 * common_difference
                ):  # since x,y,z are positive integers
                    frequency[n] += 1  # so z>0 and a>d ,also 4d<a

    lowerCamelCase__    :      List[str]					 =		sum(1 for x in frequency[1:limit] if x == 10 )

    return count


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





