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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_border_index(I, shape, size):
 """ Get flattened indices for the border of the region I. Parameters I : np.ndarray(dtype=int) indices in the flattened region. size : int region size (technically computable from shape argument) shape : tuple(int, int) region shape Returns ------- J : np.ndarray(dtype=int) indices orthogonally and diagonally bordering I """


    J = get_adjacent_index(I, shape, size)

    # instead of setdiff?
    # border = np.zeros(size)
    # border[J] = 1
    # border[I] = 0
    # J, = np.where(border)

    return np.setdiff1d(J, I)