Is it possible to build a CNN like the following easily in Pytorch?
X_train[0:99] -> Con1 -> Conv2 - MaxPool  / + X[99:105] -> linear1 -> linear2 ->Ouput
As in we are adding more information to the fully connected layers than simply what the conv layers tell us. For example imagine doing NLP on movie reviews but you know the type of movie and you know which actors were in it etc would you be able to add that information to the fully connected layers while having the conv layers analyze the actual sentences of the review.
Is this possible? Any examples I could look at ? Is it worth trying out this technique?