[RMP] Add YouTube DNN ranking model to Merlin Models

Problem:

Merlin models doesn't support the popular YouTube DNN ranking model. In order to be useful to customers as a library support for commonly used models is required.

Goals:

• Add support for YouTube DNN ranking

Constraints:

Proposed starting point:

Reference Material

• YouTube Paper
• Original PR

Merlin Core

• Create a tag for example weights (to be used independently or in conjunction with Tags.TARGET)

Merlin Transforms (NVT)

• Create an operator for generating multiple powers of continuous features (square/root, cube/root, etc)?

Merlin Models

• Add a block for generating multiple powers of continuous features (square/root, cube/root, etc)?
• Update the dataloader to be able to handle example weights (return as part of the targets or create a new output?)
• Add support for example weights (using underlying Keras sample weight functionality?)
• Need to decide which part goes to data pre-processing vs models

Serving (Merlin Systems?)

• Figure out how to handle the exponential function used at serving time (and the unexplained W matrix)

Start with the linked YouTube paper and original PR, then review the Merlin Core, Merlin Transforms (NVT), Merlin Models, and Serving sections in the issue. Determine the design for example weights, power features, dataloader and model support, preprocessing boundaries, and serving behavior. Done means the YouTube DNN ranking model is supported across the required components.