If sequences shorter than input_size are automatically padded with 0 at the beginning, and future exogenous variables are also automatically padded with 0 at the beginning (is this true?), in order to distinguish those zeros from real zeros of the time series, could it make sense to create a "real_data" exogenous variable with value 1 for the time series points, so that its value is automatically set to 0 for padding data and we can tell to the model that padding data have real_data=0 and true data have real_data=1? Basically we would set that variable to 1 for all time series points and then leverage the all-zero padding to create real_data=0. Could the scaler (e.g. robust) negatively impact this "real_data" indicator since future exogenous variables get scaled? Is the exogenous variables scaling performed before or after the automatic zero-padding? Thanks