hey! @D_Liebman been a while I hope you discovered the answer elsewhere, but if you’re going to change the size of the encoder hidden state you have to change the number of channels the attention and decoder rnn  layers expect as well. Additionally, you will have to reshape the encoder hidden layer so that the size is doubled only on the channel dimension. I haven’t seem much literature on addition vs concat, but intuitively since the gradients can flow through both operations the info is getting passed either way. Also, empirically I haven’t noticed much difference in my small scale experiments so I tend to stick with addition, as it makes the dimensions much cleaner. As a counter point, of course, harvard nlp and https://arxiv.org/pdf/1703.03906.pdf 14, and most of the google papers seem to use concat.