我正在使用 Keras 库来创建神经网络。我有一个 iPython Notebook 来加载训练数据、初始化网络并“拟合”神经网络的权重。最后，我使用 save_weights() 方法保存权重。代码如下：
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation
from keras.optimizers import SGD
from keras.regularizers import l2
from keras.callbacks import History
[...]
input_size = data_X.shape[1]
output_size = data_Y.shape[1]
hidden_size = 100
learning_rate = 0.01
num_epochs = 100
batch_size = 75
model = Sequential()
model.add(Dense(hidden_size, input_dim=input_size, init='uniform'))
model.add(Activation('tanh'))
model.add(Dropout(0.2))
model.add(Dense(hidden_size))
model.add(Activation('tanh'))
model.add(Dropout(0.2))
model.add(Dense(output_size))
model.add(Activation('tanh'))
sgd = SGD(lr=learning_rate, decay=1e-6, momentum=0.9, nesterov=True)
model.compile(loss='mse', optimizer=sgd)
model.fit(X_NN_part1, Y_NN_part1, batch_size=batch_size, nb_epoch=num_epochs, validation_data=(X_NN_part2, Y_NN_part2), callbacks=[history])
y_pred = model.predict(X_NN_part2) # works well
model.save_weights('keras_w')
然后，在另一个 iPython Notebook 中，我只想使用这些权重并预测给定输入的一些输出值。我初始化相同的神经网络，然后加载权重。
# same headers
input_size = 37
output_size = 40
hidden_size = 100
model = Sequential()
model.add(Dense(hidden_size, input_dim=input_size, init='uniform'))
model.add(Activation('tanh'))
model.add(Dropout(0.2))
model.add(Dense(hidden_size))
model.add(Activation('tanh'))
model.add(Dropout(0.2))
model.add(Dense(output_size))
model.add(Activation('tanh'))
model.load_weights('keras_w')
#no error until here
y_pred = model.predict(X_nn)
问题在于，显然 load_weights 方法不足以拥有功能模型。我收到一个错误：
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-17-e6d32bc0d547> in <module>()
1
----> 2 y_pred = model.predict(X_nn)
C:\XXXXXXX\Local\Continuum\Anaconda\lib\site-packages\keras\models.pyc in predict(self, X, batch_size, verbose)
491 def predict(self, X, batch_size=128, verbose=0):
492 X = standardize_X(X)
--> 493 return self._predict_loop(self._predict, X, batch_size, verbose)[0]
494
495 def predict_proba(self, X, batch_size=128, verbose=1):
AttributeError: 'Sequential' object has no attribute '_predict'
任何想法？非常感谢。