如何使用BFGS优化器实现NN

Question

这是我尝试过的：

def loss(W):
    weightsList1 = [np.zeros((25,20)), np.zeros(20)]
    for i in range(20):
        for j in range(25):
            weightsList1[0][j,i] = W[i][j]
        weightsList1[1][i] = W[i][25]

    model.layers[0].set_weights(weightsList1)
    weightsList2 = [np.zeros((20,1)), np.zeros(1)]

    for i in range(20):
        weightsList2[0][i,0] = W[0][i]

    weightsList2[1][0] = W[0][20]
    model.layers[1].set_weights(weightsList2)
    preds = model.predict(X)
    mse = np.sum(np.square(np.subtract(preds,Y)))/len(X[:,0])

    return mse


V = np.random.randn(20,26)*0.01
res = minimize(loss, x0=V, method = 'BFGS', options={'eps': 1e-6,'disp': True})

但是出现以下错误：

  

IndexError：标量变量的索引无效。