How to create a RNN that is recursive within a mini-batch?

Source: stackoverflow.com --- Sunday, October 08, 2017
I built a graph in TensorFlow that is separated into two parts: part 1 takes a list of length N and it turns it into M consecutive Windows, which constitute my mini-batch. Minimal example: input [a,b,c,d,e,f] becomes [[a,b,c],[b,c,d],[c,d,e],[d,e,f]] part 2 operates on each window, so [[a,b,c],[b,c,d],[c,d,e],[d,e,f]] becomes [x1,x2,x3,x4]. No problems here. I would like to turn this graph into a recursive one by having the second part use the output of a previous window to compute its output, like so: part 2 takes [a,b,c] and a default x0 to produce x1, then [[b,c,d], x1] to output x2, then [[c,d,e], x2] to output x3 and so on. How do I achieve this? ...

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