The simplest approach would be to use torch.cat them together along the feature dimension (dim=2). Have a linear layer with the appropriate number of outputs towards the top of the model. Then on prediction, you can torch.cat the outputs of the model with the next timestep’s extrinsic features.
Best regards
Thomas