Changelog

June 2022

• Added support for BYO Dataset

May 2022

• Added multi-hot categorical features
• Added triton inference
• Updated model architecture figure
• Updated NVTabular to v0.7.1
• Updated readme numbers

November 2021

• Refresh release with performance optimizations
• Updated NVTabular to v0.6.1
• Replaced native TF dataloader with NVTabular counterpart
• Removed spark CPU preprocessing
• Updated readme numbers
• Changed V100 cards from 16GB to 32GB

February 2021

• Initial release

Known issues

• In this model the TF32 precision can in some cases be as fast as the FP16 precision on Ampere GPUs. This is because TF32 also uses Tensor Cores and doesn't need any additional logic such as maintaining FP32 master weights and casts. However, please note that W&D is, by modern recommender standards, a very small model. Larger models should still have significant benefits of using FP16 math.