That might be part of my confusion. From what I understand from our convo above and another thread I started, seq_length would be the size of the window I want to use to predict, in my case 5. If I use input_dim=1 in the LSTMNet constructor I will get a model that takes a sequence of length 1 --> 128 --> 1, which would take the last observation (a window of size 1) to predict the next step, and not 5 like I want.
Unless I have it backwards and seq_length is the number of features (1) and input_dim the window size (5)?