Possibly breaking changes:

• Set global numpy seed (4a7cd58)
• Split in_proj_weight into separate k, v, q projections in MultiheadAttention (fdf4c3e)
• TransformerEncoder returns namedtuples instead of dict (27568a7)

New features:

• Add --fast-stat-sync option (e1ba32a)
• Add --empty-cache-freq option (315c463)
• Support criterions with parameters (ba5f829)

New papers:

• Simple and Effective Noisy Channel Modeling for Neural Machine Translation (49177c9)
• Levenshtein Transformer (86857a5, ...)
• Cross+Self-Attention for Transformer Models (4ac2c5f)
• Jointly Learning to Align and Translate with Transformer Models (1c66792)
• Reducing Transformer Depth on Demand with Structured Dropout (dabbef4)
• Unsupervised Cross-lingual Representation Learning at Scale (XLM-RoBERTa) (e23e5ea)
• BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension (a92bcda)
• CamemBERT: a French BERT (b31849a)

Speed improvements:

• Add CUDA kernels for LightConv and DynamicConv (f840564)
• Cythonization of various dataloading components (4fc3953, ...)
• Don't project mask tokens for MLM training (718677e)