Current version of predict function creates overlapping batch 1st element' indexes for train and test X and y_history tensors. Last item from X in train is first item in X in test. And due to mentioned in issue #4 gap between y_hist and y_targ there is one sequence missing in last chunk of splitted y_pred: i.e. we have dummy dataset with numbers as targs from 1 to 60, out last item in last batch would be 58 with y_targ = [60] leaving time window with 59 number out of party
Current version of predict function creates overlapping batch 1st element' indexes for train and test X and y_history tensors. Last item from X in train is first item in X in test. And due to mentioned in issue #4 gap between y_hist and y_targ there is one sequence missing in last chunk of splitted y_pred: i.e. we have dummy dataset with numbers as targs from 1 to 60, out last item in last batch would be 58 with y_targ = [60] leaving time window with 59 number out of party