bfeeny:

So if you are going from an LSTM with an input_size of say 30,000 into a single Linear layer, that is going to be a many-to-one. Even if later you come out of that Linear layer into say 30,000 features, from an LSTM perspective, its considered “many-to-one” correct?


Please look at figure 1 in this article 9 to correct your understanding of what many-to-many/many-to-one exactly means.



 bfeeny:

So if you were to do “many to many” where you would actually use the output and not just h_n, then what you would need to do, is iterate over output, and setup say for example a Linear output (or some other output type_ for each of the timesteps that exist inside of the output. Does that sound right?


Right on the money.



 bfeeny:

A problem I working with now I am taking 30495 features and trying to predict 30490 features, I thought that was “many to many”, but I built my model as LSTM->single FC layer, so I guess thats really many-to-one. It would seem Seq2Seq is a better model, but I just don’t know much about those and have found very little on just regular many to many LSTMs (examples, etc) out there.


Although I don’t understand your task fully, I can tell that you want to build a many-to-many LSTM model.