Hi guys, I am pretty much a newbie here. I need to feed a time series to a RNN. Now, I am having problems with getting the data in the right form to feed it to torch.nn.rnn.

My data is structured in the following way: I have two signals, sampled at 10000 Hz, and a target with the same sampling. These are stored in numpy arrays, say x1, x2, y. I have 128 seconds of data, therefore 128*10000 points for each input and for the output. Now, I want to feed the RNN network a 1 second long time series, before computing the gradient and going on to feed the next second.

torch.nn.rnn needs the tensors to have three dimensions, how should I put together the input arrays x1, x2 and reshape them along with the target y? I know it is trivial, but I am a bit confused about it. Say x1, x2, y are [1, 1280000] numpy arrays to begin with.