RecBole v0.1.2 Release Notes

• Highlights
• New Features
• Improvements
• Bug Fixes

Highlights

The RecBole v0.1.2 release includes a number of new features, model efficiency improvements and bug fixes. A few of the highlights include:

1. We add CI (Continuous Integration) to RecBole, which improves the efficiency and quality of our development.
2. We improve the efficiency of GNN-based general recommendation models(NGCF, GCMC, LightGCN, SpectralCF) by refactoring the construction of sparse interaction tensor. In this way, usage of GPU RAM can be greatly reduced.
3. Some bugs in models, trainer and data are fixed.

New Features

• Add gradient clipping. (#533)
• Add Dataset's attributes token2id and id2token.(#511)
• Add continuous integration. (#496)

Improvements

• Improve the efficiency of GNN-based general recommendation models (NGCF, GCMC, LightGCN, SpectralCF). (#525, #526)
• SequentialDataloader: add support for historical sequence of Non-SEQ features. (#547)

Bug Fixes

Model:

• Fix a bug in the DMF model: crash when training set contains item without interactive records. ( #505)

• Fix a bug in the TransRec model: this bug may cause runtime error. (#502)

Trainer:

• Fix a bug in the trainer: this bug may cause the NeuMF model to report an error if eval_batch_size=1.(#537)

• Fix the bug that some models don't work when epochs = 0. (#499)

Data:

• Fix wrong data type of time field in SequentialDataloader. (#551)

• Fix the bug of negative sample judgment in sampler. (#551)

• Fix the bug that kg_feat is empty when KGDataloader is in KGRS mode. (#551）