Comments (2)
Hi @guohaoghp , I think the RNN should be attached to the encoder for handling the timely input. The decoder will output result for every time step. If you want to visualize the output from the encoder, I think you have to use the return at the last time step.
The RNN code would be similar to this code: https://github.com/MorvanZhou/PyTorch-Tutorial/blob/master/tutorial-contents/402_RNN_classifier.py
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Thanks a lot for your reply, it helps a lot.
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