keras中的深宽模型问题

我正在努力学习在线教程,并为Keras中广泛而深入的模型编写代码。然而,我在合并两个模型时遇到了问题

wide = Sequential()
wide.add(Dense(1, input_dim=X_train.shape[1], kernel_initializer ='uniform', activation='relu'))

deep = Sequential()
deep.add(Dense(1, input_dim=X_train.shape[1], kernel_initializer ='uniform', activation='relu'))
deep.add(Dense(100, activation='relu'))
deep.add(Dense(50, activation='relu'))
deep.add(Dense(1, activation='linear'))

model = Sequential()
model.add(Merge([wide, deep], mode='concat', concat_axis=1))
model.add(Dense(1, activation='linear'))

出现以下警告:

model = Sequential()
model.add(Merge([wide, deep], mode='concat', concat_axis=1))
__main__:2: UserWarning: The `Merge` layer is deprecated and will be removed after 08/2017. Use instead layers from `keras.layers.merge`, e.g. `add`, `concatenate`, etc

警告信息告诉我该怎么做,但我还没有弄清楚如何将这两个模型结合起来。

我尝试过以下不同的方法,但不断出现错误。

from keras.layers import add
model = Sequential()

model.add([wide, deep])
Traceback (most recent call last):

  File "<ipython-input-428-3e81d6d35c6f>", line 1, in <module>
    model.add([wide, deep])

  File "/Users/abrahammathew/anaconda3/lib/python3.6/site-packages/keras/models.py", line 430, in add
    'Found: ' + str(layer))

TypeError: The added layer must be an instance of class Layer. Found: [<keras.models.Sequential object at 0x1a32876cc0>, <keras.models.Sequential object at 0x1a328761d0>]

有谁能告诉我如何用keras制作宽深模型吗。