使用keras加载模型并为其参数分配新值 [英] Using keras to load model and assign new values to its parameters

问题描述

我正在尝试使用keras来存储模型，然后将其加载以进行重新训练.我的问题是在加载模型时如何将学习率设置为新值?
这是我的代码:

I am trying to use keras to store a model and then load it to retrain. My question is how do I set the learning rate to a new value when loading a model?
Here are my code:

# Save a model
model = Sequential()
model.add(Dense(64, kernel_initializer='uniform', input_shape=(10,)))
model.add(Activation('tanh'))
model.add(Activation('softmax'))
# learning rate is 0.001
sgd = optimizers.SGD(lr=0.001, decay=1e-6, momentum=0.9, nesterov=True)
model.compile(loss='mean_squared_error', optimizer=sgd)
model.fit_generator(...)
model.save()

然后加载模型

model = load_model(model)
# Change the model's parameters here. Set the learning rate to 0.01.
model.fit_generator(...)

谢谢.

推荐答案

我想我找到了答案:

from keras import backend as K
# To get learning rate
print(K.get_value(model.optimizer.lr))
# To set learning rate
K.set_value(model.optimizer.lr, 0.001)
keras.__version__ # 2.0.2

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