Thanks @julioasoto
Passing upto t - 2 to the encoder makes total sense. Passing t - 1 twice was bugging me too, but I carried on for the lack of an alternative. If I get the chance to retrain this model, I’ll use this approach and update what I find.
I tried passing encoder output to each decoder timestep in the attention model. This was my takeaway from the experiment - if the data has a good seasonality or any good DateTime pattern, the attention mech. gives a negligible improvement over the basic seq2seq architecture (this was the case in the store item dataset), on the messy time-series dataset adding attention mechanism did provide a good improvement.