

def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     int   ,      SCREAMING_SNAKE_CASE__      :     int   ,      SCREAMING_SNAKE_CASE__      :     list[list[int]]				)							->				int:





    '''simple docstring'''






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

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

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

    A__   				=       [0]
    update_area_of_max_square(0   ,      0				)
    return largest_square_area[0]
def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     int   ,      SCREAMING_SNAKE_CASE__      :     int   ,      SCREAMING_SNAKE_CASE__      :     list[list[int]]				)							->				int:





    '''simple docstring'''






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

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

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

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

    return largest_square_area[0]
def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     int   ,      SCREAMING_SNAKE_CASE__      :     int   ,      SCREAMING_SNAKE_CASE__      :     list[list[int]]				)							->				int:





    '''simple docstring'''






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

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

    return largest_square_area
def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     int   ,      SCREAMING_SNAKE_CASE__      :     int   ,      SCREAMING_SNAKE_CASE__      :     list[list[int]]				)							->				int:





    '''simple docstring'''






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

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




import random
def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     list   ,      SCREAMING_SNAKE_CASE__      :     str				)							->				tuple:





    '''simple docstring'''






    A__				,						A__				,						A__   				=       [], [], []
    for element in data:
        if element < pivot:
            less.append(SCREAMING_SNAKE_CASE__				)
        elif element > pivot:
            greater.append(SCREAMING_SNAKE_CASE__				)
        else:
            equal.append(SCREAMING_SNAKE_CASE__				)
    return less, equal, greater

def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     list   ,      SCREAMING_SNAKE_CASE__      :     int				)							->				str:





    '''simple docstring'''






    if index >= len(SCREAMING_SNAKE_CASE__				) or index < 0:
        return None

    A__   				=       items[random.randint(0   ,      len(SCREAMING_SNAKE_CASE__				) - 1				)]
    A__   				=       0
    A__				,						A__				,						A__   				=       _partition(SCREAMING_SNAKE_CASE__   ,      SCREAMING_SNAKE_CASE__				)
    A__   				=       len(SCREAMING_SNAKE_CASE__				)
    A__   				=       len(SCREAMING_SNAKE_CASE__				)

    # index is the pivot
    if m <= index < m + count:
        return pivot
    # must be in smaller
    elif m > index:
        return quick_select(SCREAMING_SNAKE_CASE__   ,      SCREAMING_SNAKE_CASE__				)
    # must be in larger
    else:
        return quick_select(SCREAMING_SNAKE_CASE__   ,      index - (m + count)				)

