Hi!
Solved!
Just had to indert the two databases to the dataset as:
learn_dataset = torch.utils.data.TensorDataset(train, ts_train, y_train)
learn_loader = torch.utils.data.DataLoader(learn_dataset, batch_size = batch_size, shuffle=True)
for train, ts_train, labels in learn_loader:
output = model(train, ts_train)

Thanks for the answers. I have a followup regarding Datasets for these kind of networks.
I have two Data sets I’m working with, one is a time-series and the other is continues and binary data. Each training example has one of each.
I would you recommend building a Dataset that can be used for a network that has concat in it? It seems that all the examples on Datasets work with only one kind of input.