l2_attack_black.py 文件源码

def coordinate_Newton(losses, indice, grad, hess, batch_size, mt_arr, vt_arr, real_modifier, up, down, lr, adam_epoch, beta1, beta2, proj):
    # def sign(x):
    #     return np.piecewise(x, [x < 0, x >= 0], [-1, 1])
    cur_loss = losses[0]
    for i in range(batch_size):
        grad[i] = (losses[i*2+1] - losses[i*2+2]) / 0.0002 
        hess[i] = (losses[i*2+1] - 2 * cur_loss + losses[i*2+2]) / (0.0001 * 0.0001)
    # print("New epoch:")
    # print('grad', grad)
    # print('hess', hess)
    # hess[hess < 0] = 1.0
    # hess[np.abs(hess) < 0.1] = sign(hess[np.abs(hess) < 0.1]) * 0.1
    # negative hessian cannot provide second order information, just do a gradient descent
    hess[hess < 0] = 1.0
    # hessian too small, could be numerical problems
    hess[hess < 0.1] = 0.1
    # print(hess)
    m = real_modifier.reshape(-1)
    old_val = m[indice] 
    old_val -= lr * grad / hess
    # set it back to [-0.5, +0.5] region
    if proj:
        old_val = np.maximum(np.minimum(old_val, up[indice]), down[indice])
    # print('delta', old_val - m[indice])
    m[indice] = old_val
    # print(m[indice])