Full Changelog: v0.2.0...v0.2.1
Changes:
- Addition of CVM Plugin:
- Based on the CVM plugin in PCTR-DNN, we have integrated and tested its functionality within our TN environment. The plugin extends embeddings by incorporating exposure and click data of features into the training process. During the forward propagation, while retrieving feature embeddings from the sparse table, the exposure and click values of the features are also fetched and included as two additional output columns. In the backward propagation, the show/click counts for the batch are propagated back to the sparse table along with the gradients.
- Normalization Enhancements with PCTRDNN Statistics Logic:
- We have introduced new statistical logic in the normalization process. This includes calculating incremental counts and sums, as well as computing the incremental variance as (data - mean).sqrt().
- Removal of Environment Variable Control for Sparse Initialization:
- To reduce performance overhead, we have eliminated the use of environment variables for controlling the initialization of sparse data structures.