


"""simple docstring"""







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


__lowercase    					=      logging.get_logger(__name__)

__lowercase    					=      {
    """facebook/timesformer""": """https://huggingface.co/facebook/timesformer/resolve/main/config.json""",
}






class 						_A  (  _a  ):







    """simple docstring"""




    UpperCAmelCase       :							List[str]	=       """timesformer"""






    def __init__(					self				:    List[str]				, __UpperCAmelCase				:    Dict=224				, __UpperCAmelCase				:    str=16				, __UpperCAmelCase				:    Any=3				, __UpperCAmelCase				:    Optional[int]=8				, __UpperCAmelCase				:    Tuple=768				, __UpperCAmelCase				:    Optional[int]=12				, __UpperCAmelCase				:    Dict=12				, __UpperCAmelCase				:    Union[str, Any]=3072				, __UpperCAmelCase				:    Dict="gelu"				, __UpperCAmelCase				:    Tuple=0.0				, __UpperCAmelCase				:    Union[str, Any]=0.0				, __UpperCAmelCase				:    Optional[Any]=0.02				, __UpperCAmelCase				:    Dict=1e-6				, __UpperCAmelCase				:    Optional[Any]=True				, __UpperCAmelCase				:    Union[str, Any]="divided_space_time"				, __UpperCAmelCase				:    Any=0				, **__UpperCAmelCase				:    Union[str, Any]				, ):
      super().__init__(**__UpperCAmelCase)

      a						:		Optional[Any]      							=			image_size
      a						:		List[Any]      							=			patch_size
      a						:		Tuple      							=			num_channels
      a						:		Optional[int]      							=			num_frames

      a						:		int      							=			hidden_size
      a						:		Optional[Any]      							=			num_hidden_layers
      a						:		List[str]      							=			num_attention_heads
      a						:		List[str]      							=			intermediate_size
      a						:		Optional[Any]      							=			hidden_act
      a						:		int      							=			hidden_dropout_prob
      a						:		List[Any]      							=			attention_probs_dropout_prob
      a						:		int      							=			initializer_range
      a						:		Tuple      							=			layer_norm_eps
      a						:		Optional[int]      							=			qkv_bias

      a						:		str      							=			attention_type
      a						:		List[Any]      							=			drop_path_rate










"""simple docstring"""







from bisect import bisect
from itertools import accumulate


def      lowercase			(				A_  ,   A_  ,   A_  ,   A_       )->      Union[str, Any]:
  '''simple docstring'''







  a						:		Any      							=			sorted(zip(A_  ,   A_       )  ,   key=lambda A_       : x[0] / x[1]  ,   reverse=A_       )
  a							,		a						:		int      							=			[i[0] for i in r], [i[1] for i in r]
  a						:		Union[str, Any]      							=			list(accumulate(A_       )       )
  a						:		Optional[Any]      							=			bisect(A_  ,   A_       )
  return (
      0
      if k == 0
      else sum(vl[:k]       ) + (w - acc[k - 1]) * (vl[k]) / (wt[k])
      if k != n
      else sum(vl[:k]       )
  )


if __name__ == "__main__":
 import doctest

 doctest.testmod()






