Closed ralgond closed 8 months ago
@ralgond you can ignore the warning, it is telling that the it applies projection and it will be projected to the item_id embedding dimension which is 64 by default. Note that you can also change this embedding dimension if you want.
So how can I change the item embedding dimension?
you can add it here: inputs = tr.TabularSequenceFeatures.from_schema(...)
as an argument of embedding_dims
.
Please see this ticket as well.
closing this due to low activity.
Projecting inputs of NextItemPredictionTask to'64' As weight tying requires the input dimension '320' to be equal to the item-id embedding dimension '64'. Should I care the warning?
Details
I found a warning on this example page:
https://nvidia-merlin.github.io/Transformers4Rec/stable/examples/end-to-end-session-based/02-End-to-end-session-based-with-Yoochoose-PyT.html
Should I care the warning?
Thank you.