Here is an example of RNN from scratch from  Pytorch docs (scroll down to example 2):
https://pytorch.org/tutorials/beginner/former_torchies/nnft_tutorial.html
However, I thought RNN was supposed to have a new feature input at each TIME_STEP instead of just  loading all of the features in at one time.
So using the example from the tutorial above:
instead of
batch = torch.randn(batch_size, 50)
being fed into with all 50 sequence features at one time, shouldn’t the sequence of features be feed in one at a time?
Would this involve some sort of Pytorch slicing?