- Introduce unified AMP helpers (create_grad_scaler, torch_autocast) to handle
deprecations in PyTorch ≥2.3.0
- Replace direct uses of torch.cuda.amp.GradScaler and torch.cuda.amp.autocast
with the new utilities across all training and inference scripts
- Update all torch.load calls to include weights_only=False for compatibility with
newer PyTorch versions
* support transformer LM
* show number of parameters during training
* update docstring
* testing files for ppl calculation
* add lm wrampper for rnn and transformer LM
* apply lm wrapper in lm shallow fusion
* small updates
* update decode.py to support LM fusion and LODR
* add export.py
* update CI and workflow
* update decoding results
* fix CI
* remove transformer LM from CI test
* Add utility for shallow fusion
* test batch size == 1 without shallow fusion
* Use shallow fusion for modified-beam-search
* Modified beam search with ngram rescoring
* Fix code according to review
Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>