ptrblck:

ase, I assume you would like to treat each input combination as an “input index”, which would need a mapping. However, these


Hi, thanks a lot for answering!
So, the first part of your understanding is correct, u, i, and c are different embeddings and unique_uic contains the 101 unique values of all three tensors, which are used to create dense embedding tensors of the shape [101, 64].
Lets say that u always go from range 0-900 , i go from 901 - 2579, and c 2580-2697. In each iteration it is fed to the network a batch of [99,3], which are triplets of indexes which have interacted. For example:
        [ 820, 1802, 2694], --> user 820 have interacted with item 1802 under context 2694
        [ 820, 2578, 2694],

If I just get the embeddings of those 101 “nodes” in shape [101,64], what I would like to know is how to come back to the original triplet shapes but instead of stacking indexes, stacking their corresponding embeddings. Thus, just asking how to go from those [101, 64] embeddings to a shape [99, 3, 64] embeddings, taking into account that, in those 101 unique embeddings, there are 3 different nodes (for this example the first one is a user, the last one context and the 99 in the middle are items but it can be completely different – so the shape of unique_uic is completely variant).
Thank you so much again!