With all due respect you don't appear to know much about what you are commenting about. There is a huge community of research and applications around rnn and al

With all due respect you don't appear to know much about what you are commenting about. There is a huge community of research and applications around rnn and all other architectures. Pytorch has an extremely vivid and fast growing codebase, across all neural architectures and applications, it's remarkable actually. One reason might be because it is simple an effective, including easy debugging. Another is because research now is much focused on new possibly complex and exotic architectures, new optimizers, inner guts and behavior understanding​, including theoretically. And it appears pytorch makes that easy. Don't throw it away too fast as a DL enthusiast :)