I’m not sure I understand the use case completely, so feel free to correct me 
Based on your description you are dealing with 3 different tensors, u, i, and c.
unique_uic contains the 101 unique values of all three tensors and is used in some way to create dense embedding tensors of the shape [101, 64], i.e. 101 tensors (one for each input index) with a feature dimension of 64.
Now you would like to concatenate the three input tensors and feed to this embedding?
If that’s the case, I assume you would like to treat each input combination as an “input index”, which would need a mapping. However, these three tensors could create more combinations than the number of unique values, so how would you deal with it?
u and c only contain a static value, but is this always the case in your workflow?