

def     UpperCAmelCase_       (						_A				,		_A				,		_A    ):





     '''simple docstring'''




     def update_area_of_max_square(_A				,		_A    ) -> int:
          # BASE CASE
          if row >= rows or col >= cols:
               return 0

          SCREAMING_SNAKE_CASE__   =   update_area_of_max_square(_A				,		col + 1    )
          SCREAMING_SNAKE_CASE__   =   update_area_of_max_square(row + 1				,		col + 1    )
          SCREAMING_SNAKE_CASE__   =   update_area_of_max_square(row + 1				,		_A    )

          if mat[row][col]:
               SCREAMING_SNAKE_CASE__   =   1 + min([right, diagonal, down]    )
               SCREAMING_SNAKE_CASE__   =   max(largest_square_area[0]				,		_A    )
               return sub_problem_sol
          else:
               return 0

     SCREAMING_SNAKE_CASE__   =   [0]
     update_area_of_max_square(0				,		0    )
     return largest_square_area[0]
def     UpperCAmelCase_       (						_A				,		_A				,		_A    ):





     '''simple docstring'''




     def update_area_of_max_square_using_dp_array(
         _A				,		_A				,		_A    ) -> int:
          if row >= rows or col >= cols:
               return 0
          if dp_array[row][col] != -1:
               return dp_array[row][col]

          SCREAMING_SNAKE_CASE__   =   update_area_of_max_square_using_dp_array(_A				,		col + 1				,		_A    )
          SCREAMING_SNAKE_CASE__   =   update_area_of_max_square_using_dp_array(row + 1				,		col + 1				,		_A    )
          SCREAMING_SNAKE_CASE__   =   update_area_of_max_square_using_dp_array(row + 1				,		_A				,		_A    )

          if mat[row][col]:
               SCREAMING_SNAKE_CASE__   =   1 + min([right, diagonal, down]    )
               SCREAMING_SNAKE_CASE__   =   max(largest_square_area[0]				,		_A    )
               SCREAMING_SNAKE_CASE__   =   sub_problem_sol
               return sub_problem_sol
          else:
               return 0

     SCREAMING_SNAKE_CASE__   =   [0]
     SCREAMING_SNAKE_CASE__   =   [[-1] * cols for _ in range(_A    )]
     update_area_of_max_square_using_dp_array(0				,		0				,		_A    )

     return largest_square_area[0]
def     UpperCAmelCase_       (						_A				,		_A				,		_A    ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   [[0] * (cols + 1) for _ in range(rows + 1    )]
     SCREAMING_SNAKE_CASE__   =   0
     for row in range(rows - 1				,		-1				,		-1    ):
          for col in range(cols - 1				,		-1				,		-1    ):
               SCREAMING_SNAKE_CASE__   =   dp_array[row][col + 1]
               SCREAMING_SNAKE_CASE__   =   dp_array[row + 1][col + 1]
               SCREAMING_SNAKE_CASE__   =   dp_array[row + 1][col]

               if mat[row][col] == 1:
                    SCREAMING_SNAKE_CASE__   =   1 + min(_A				,		_A				,		_A    )
                    SCREAMING_SNAKE_CASE__   =   max(dp_array[row][col]				,		_A    )
               else:
                    SCREAMING_SNAKE_CASE__   =   0

     return largest_square_area
def     UpperCAmelCase_       (						_A				,		_A				,		_A    ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   [0] * (cols + 1)
     SCREAMING_SNAKE_CASE__   =   [0] * (cols + 1)
     SCREAMING_SNAKE_CASE__   =   0
     for row in range(rows - 1				,		-1				,		-1    ):
          for col in range(cols - 1				,		-1				,		-1    ):
               SCREAMING_SNAKE_CASE__   =   current_row[col + 1]
               SCREAMING_SNAKE_CASE__   =   next_row[col + 1]
               SCREAMING_SNAKE_CASE__   =   next_row[col]

               if mat[row][col] == 1:
                    SCREAMING_SNAKE_CASE__   =   1 + min(_A				,		_A				,		_A    )
                    SCREAMING_SNAKE_CASE__   =   max(current_row[col]				,		_A    )
               else:
                    SCREAMING_SNAKE_CASE__   =   0
          SCREAMING_SNAKE_CASE__   =   current_row

     return largest_square_area


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       print(largest_square_area_in_matrix_bottom_up(2, 2, [[1, 1], [1, 1]]))





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


_SCREAMING_SNAKE_CASE					:  Any             =      logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE					:  Optional[Any]             =      {
    '''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 	UpperCAmelCase__		(	A__	):






  """simple docstring"""


  a									= "vivit"






  def __init__(							self						:		str     ,       __lowerCamelCase						:		List[Any]=224     ,       __lowerCamelCase						:		Optional[int]=32     ,       __lowerCamelCase						:		Tuple=[2, 16, 16]     ,       __lowerCamelCase						:		Union[str, Any]=3     ,       __lowerCamelCase						:		Optional[Any]=768     ,       __lowerCamelCase						:		Any=12     ,       __lowerCamelCase						:		Optional[Any]=12     ,       __lowerCamelCase						:		List[str]=3072     ,       __lowerCamelCase						:		Any="gelu_fast"     ,       __lowerCamelCase						:		Union[str, Any]=0.0     ,       __lowerCamelCase						:		int=0.0     ,       __lowerCamelCase						:		str=0.02     ,       __lowerCamelCase						:		Any=1e-06     ,       __lowerCamelCase						:		Dict=True     ,       **__lowerCamelCase						:		Any     ,       )		->							List[str]:
       SCREAMING_SNAKE_CASE__   =   hidden_size
       SCREAMING_SNAKE_CASE__   =   num_hidden_layers
       SCREAMING_SNAKE_CASE__   =   num_attention_heads
       SCREAMING_SNAKE_CASE__   =   intermediate_size
       SCREAMING_SNAKE_CASE__   =   hidden_act
       SCREAMING_SNAKE_CASE__   =   hidden_dropout_prob
       SCREAMING_SNAKE_CASE__   =   attention_probs_dropout_prob
       SCREAMING_SNAKE_CASE__   =   initializer_range
       SCREAMING_SNAKE_CASE__   =   layer_norm_eps

       SCREAMING_SNAKE_CASE__   =   image_size
       SCREAMING_SNAKE_CASE__   =   num_frames
       SCREAMING_SNAKE_CASE__   =   tubelet_size
       SCREAMING_SNAKE_CASE__   =   num_channels
       SCREAMING_SNAKE_CASE__   =   qkv_bias

       super().__init__(**__lowerCamelCase )


