To me it still seems that one of these 3 dimensions is redundant. Because if I use, say, a 5 dimensional timeseries and I want to train it in a batched version, then I split that into junks. If the total timeseries had 1000 timepoints and my batches have size 100, then I would only require input tensors of (100, 5) as I understand it… But I would feed 10 of these tensors during one epoch to the LSTM