Closed viswa-nvidia closed 1 year ago
@sararb @gabrielspmoreira can you flesh this out as best as possible in @marcromeyn's absence.
@gabrielspmoreira what does the architecture look like for the system for session based? Are we planning to use session generation to feed into a candidate generation stage?
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@gabrielspmoreira what does the architecture look like for the system for session based? Are we planning to use session generation to feed into a candidate generation stage?
@EvenOldridge the session-based recommendation works as a next-item prediction task. It can be seen as a retrieval model, where the query tower users a sequential model (e.g. RNN, Transformer) and outputs a query representation/vector. During inference, such vectors can be used to retrieve the similar items from ANN the same way a retrieval model does. So we believe we wouldn't need anything special on Merlin Systems related to the output of a session-based recommendation model. The main different is in the input, as such sequential models expect list features as input. NVTabular already supports processing and storing such list features as you know, but there might be some challenges on Systems building the Triton ensemble with list features support.
@karlhigley , is the systems section here updated. Pleaes review
It is up to date with the current state of our knowledge of the work
@marcromeyn , in one of the meetings, I made a note that this task is dependent on some tasks covered in RMP479-EMBEDDINGS initiative [RMP] Enable users to pass embedding tables directly into the input block in order to more easily support new functionality (non-trainable embeddings, different dimensions, model parallel, etc) . Is this correct ? which are these tasks. ? @EvenOldridge for vis.
@rnyak , please link the systems - multi hot related development
@oliverholworthy , please add the input output schema related tickets to this ticket
@viswa-nvidia For the saving method:
This is the parent issue for that:
We have implemented the save method to save input schema, but currently missing output schema.
Also identified an error in Merlin Models that may impact ability to serve Transformer-based models that affects issues with saving a model after loading.
@karlhigley , please add the Triton related PR ( serving signatures haven't matched up with what model expects ) in the ticket.
@rnyak to follow up with @radekosmulski for blocker ( 23.04 )
It was pointed out to me that we should be consistent about when we consider something done or not so I'm going to reopen this and move it to 22.05. @bbozkaya You've had the only remaining ticket (review the API) on your todo for the past two weeks with no progress. Is this something you're able to take on so that we can close the ticket. If not let us know and we can reassign.
Problem:
Session-based and sequential-based models are an active research area for providing personalized recommendations. Transformers4Rec library was built to support the definition of such architectures and the results of our experiments conducted in the T4Rec paper showed the effectiveness of Transformers in modeling short sequences observed in session-based tasks. The T4Rec library was also used to win various RecSys challenges. We also observe a growing interest and active engagement from customers in using Transformers4Rec.
T4Rec was not actively updated for several months as the team shifted its focus to developing the Merlin Model library. MM does not currently support sequential and session-based recsys architectures. MM should support these sequential architectures and provide all necessary support to our users so that they can build such effective models.
Goal:
Definition of Done
Have an example that serves TF session based model in conjunction with a NVT workflow where the session based models scores the whole catalog
Constraints:
Starting Point:
Training
Proposed API:
Inputs
Masking
RetrievalModel
Outputs
Port Sequence Architectures
Fixes for the GTC tutorial on session-based recommendation
Inference support
Save schema on model save
Session-base model can be used as a candidate generation model, for that we need the following options:
[x] NVIDIA-Merlin/models#736 Note: Make sure we can export the encoder block (Transformer or RNN) together with a SequenceSummary post layer as the query tower.
[x] NVIDIA-Merlin/models#735
Constraint: Provide information about input list features to Merlin System NVIDIA-Merlin/Merlin#489
Systems
Documentation
Examples
Small scale (see #352)
[x] https://github.com/NVIDIA-Merlin/systems/issues/135 ( Note: Ability to server session based depends on this work )
Blocker