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Note that this published code does not include the modeling of output label dependencies. One may add a loop function as in the rnn_decoder function in TensorFlow seq2seq.py example to feed emitted label embedding back to RNN state. Alternatively, sequence level optimization can be performed by adding a CRF layer on top of the RNN outputs.
Excuse me!
I have read the paper, and find the current predicted tag was pointed to the next step as described in Figure3.
But in this code, I cant find any code about this operation.
Is your picture wrong?
Looking forward your reply!
Thank you very much!
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