Adding document vector doc2ec to seq2seq model In general we use word2vec for word embedding in seq2seq model, is it possible to add the document vector from Doc2vec with the input words , I mean using the tag of the document as a word and its vector for emending : the picture will explain mu point a view  

default seq2seq 


My opinion


the doc_tag is followed by its original words so will that improve my seq2seq model ( logically ) ?
The purpose of the encoder (green part) is to determine this document vector, so if you want to provide it yourself use the decoder and feed the embedding as the initial state. 

I suppose you could use your embedding as a prior for the encoder output. One alternative to your suggestion, which might work, is to use the embeddings as an MSE regularizer to the encoder output.