使用来自 keras 模型的预测作为另一个 keras 模型内的层

Question

Suppose we have a model already trained for some task can we use that models prediction as a lambda layer inside another model? I am thinking something in the following format:

pretrained_model=get_Model()    #Loaded from a different file
pretrained_model.load_weights('pretrained_model_weights.h5')

base_model = VGG16(weights = 'imagenet',include_top=False,input_shape (240,320,3))

for layer in base_model.layers:
    layer.trainable = True

img_input=base_model.input
encoded=base_model.output

pretrained_model_output=Lambda(lambda x: pretrained_model.predict(img_input))

#Then run pretrained_model_output through an architecture that gives same output size as base_model.output and then 

concat = Concatenate([img_input,Output_Convolutions_pretrained_model_output],axis=-1)

#then feed this through another block in the model

Is something like this viable in Keras?

Answer 1

这比您想象的要容易得多，您只需要执行以下操作：

pretrained_model_output= pretrained_model(img_input)