Thanks for the great toolbox!
I would like to build a encoder-LSTM-decoder network using your toolbox.
What would be best practice to train such a network, as to my understanding the input format for the encoder and decoder would differ from the LSTM, which would make it impossible to train the network in one go, correct?
Is it therefore possible to train the encoder and decoder networks separately and use the encoder output as input to the LSTM network for training. And after training stack the layers?
Thanks for the great toolbox!
I would like to build a encoder-LSTM-decoder network using your toolbox.
What would be best practice to train such a network, as to my understanding the input format for the encoder and decoder would differ from the LSTM, which would make it impossible to train the network in one go, correct?
Is it therefore possible to train the encoder and decoder networks separately and use the encoder output as input to the LSTM network for training. And after training stack the layers?