def METHOD_NAME(self, inputs, **kwargs):
    x, a, i = self.get_inputs(inputs)
    # Select leaders
    lap = laplacian(a)
    v = ops.modal_dot(lap, x)
    v = tf.norm(v, axis=-1, keepdims=1)
    row = a.indices[:, 0]
    col = a.indices[:, 1]
    leader_check = tf.cast(tf.gather(v, row) >= tf.gather(v, col), tf.int32)
    leader_mask = ops.scatter_prod(leader_check[:, 0], row, self.n_nodes)
    leader_mask = tf.cast(leader_mask, tf.bool)
    return self.pool(x, a, i, leader_mask=leader_mask)