Thanks for your help!
I used 16 features, so a “history” on each timestep, but the sequence size is 100. I could also set the feature size to 1, to make it more clear. I hoped having some history in the feature vector would be beneficial.
Now, that I look at it, I think the position encoding is missing. I thought this was incorporated in the nn.Transformer() block.
So I guess I have to define a positional encoding module, and then do out = tf_model.forward(positional_encoder.forward(src),positional_encoder.forward(target))
And then some decoder?
Or don’t I have to do the positional encoding on the target?
Thanks!