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Hello! Some questions ocurrs when I'm trying to run the code :
the models trained from multiple sources are merged by the code:
model.add(Merge(training_net, mode='concat')) (in line 950)
then what's the reason for the new input block in the code below
model.add(Dense(2, input_shape=(total_hid,))) (line 958)
what's more, Merge are discarded in keras 2.0 , new method is recommend like:
model = Model(inputs=[input,input2],outputs=[output,output2])
so should i try to merge the net as well as the input in line 958?
2.i wonder if something goes wrong with the code since some function ocurrs only once,such as they are defined but not used, besides it seems the rnn network is not complete , as far as the documents are concerned , there're only 2 Dense in function: get_rnn_fea()
Thanks a lot !
The text was updated successfully, but these errors were encountered:
First, please install the software dependecy as the readme.
model.add(Dense(2, input_shape=(total_hid,))) is the fully connected layer to the output layer. ideep was developed in 2016, i have no idea the Merge function in Keras 2.0. but it is better to install the required keras version as mentioned in readme file.
2. Yes, some fucntions were not used, i did not clean the code.
Hello! Some questions ocurrs when I'm trying to run the code :
model.add(Merge(training_net, mode='concat')) (in line 950)
then what's the reason for the new input block in the code below
model.add(Dense(2, input_shape=(total_hid,))) (line 958)
what's more, Merge are discarded in keras 2.0 , new method is recommend like:
model = Model(inputs=[input,input2],outputs=[output,output2])
so should i try to merge the net as well as the input in line 958?
2.i wonder if something goes wrong with the code since some function ocurrs only once,such as they are defined but not used, besides it seems the rnn network is not complete , as far as the documents are concerned , there're only 2 Dense in function: get_rnn_fea()
Thanks a lot !
The text was updated successfully, but these errors were encountered: