[RMP] Update GTC Recommender to leverage Merlin Systems and new Merlin capabilities

Problem:

GTC Recommender was built through custom code and shortcuts. We would like to leverage Merlin to make the deployment of the GTC Recommender much more easily.

Definition of Done

New Functionality

• Ability to update Workflows when the item catalog changes (is this anything other than retraining it?)
• TopK functionality (in the model or in the pipeline?)

Models

Transformers4Rec

NVTabular

• Operator for mapping between key values (Likely a modification to categorify to support an existing mapping)
• Operators for manipulating embeddings in NVT (e.g. concat) in order to build pre-trained embedding tables
• Reverse Categorify mapping
• Separate slicing and padding operators

Dataloader

• Merging pre-trained embeddings in the dataloaders (https://github.com/NVIDIA-Merlin/Merlin/issues/211)

Systems

• Merging pre-trained embeddings at serving time (https://github.com/NVIDIA-Merlin/Merlin/issues/211)
• Filtering
  - [ ] Attribute-based filtering (e.g. language)
  - [ ] Per-user filtering (e.g. for sessions a user is already registered for)
  - [ ] De-duplication
• Ordering
  - [ ] Attribute-based re-ordering policies (e.g. by timestamp)

Deliverables

• Blog post
• Updated model that leverages tabular features
• Tensorflow based version of the model
• Examples of GTC Recommender workflow
• Work with GTC team to onboard them and add Merlin to NVIDIA on-demand

Constraints:

• Pytorch and Tensorflow

Starting Point:

Existing GTC Recommender is our foundation for this work.