- 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
* print out timestamps during decoding
* add word-level alignments
* support to compute mean symbol delay with word-level alignments
* print variance of symbol delay
* update doc
* support to compute delay for pruned_transducer_stateless4
* fix bug
* add doc
* Sort result to make it more convenient to compare decoding results
* Add cut_id to recognition results
* add cut_id to results for all recipes
* Fix torch.jit.script
* Fix comments
* Minor fixes
* Fix torch.jit.tracing for Pytorch version before v1.9.0
* support streaming in conformer
* Add more documents
* support streaming on pruned_transducer_stateless2; add delay penalty; fixes for decode states
* Minor fixes
* streaming for pruned_transducer_stateless4
* Fix conv cache error, support async streaming decoding
* Fix style
* Fix style
* Fix style
* Add torch.jit.export
* mask the initial cache
* Cutting off invalid frames of encoder_embed output
* fix relative positional encoding in streaming decoding for compution saving
* Minor fixes
* Minor fixes
* Minor fixes
* Minor fixes
* Minor fixes
* Fix jit export for torch 1.6
* Minor fixes for streaming decoding
* Minor fixes on decode stream
* move model parameters to train.py
* make states in forward streaming optional
* update pretrain to support streaming model
* update results.md
* update tensorboard and pre-models
* fix typo
* Fix tests
* remove unused arguments
* add streaming decoding ci
* Minor fix
* Minor fix
* disable right context by default
* Add fast_beam_search_nbest.
* Fix CI errors.
* Fix CI errors.
* More fixes.
* Small fixes.
* Support using log_add in LG decoding with fast_beam_search.
* Support LG decoding in pruned_transducer_stateless
* Support LG for pruned_transducer_stateless2.
* Support LG for fast beam search.
* Minor fixes.
* update RESULT.md about pruned_transducer_stateless4
* Update RESULT.md
This PR is only to update RESULT.md about pruned_transducer_stateless4.
* set default value of --use-averaged-model to True
* update RESULTS.md and add decode command
* minor fix
* update export.py
* add uploaded files links
* update link
* fix typos
* Copy files for editing.
* Add random combine from #229.
* Minor fixes.
* Pass model parameters from the command line.
* Fix warnings.
* Fix warnings.
* Update readme.
* Rename to avoid conflicts.
* Update results.
* Add CI for pruned_transducer_stateless5
* Typo fixes.
* Remove random combiner.
* Update decode.py and train.py to use periodically averaged models.
* Minor fixes.
* Revert to use random combiner.
* Update results.
* Minor fixes.
* keep model_avg on cpu
* explicitly convert model_avg to cpu
* minor fix
* remove device convertion for model_avg
* modify usage of the model device in train.py
* change model.device to next(model.parameters()).device for decoding
* assert params.start_epoch>0
* assert params.start_epoch>0, params.start_epoch
* First upload of model average codes.
* minor fix
* update decode file
* update .flake8
* rename pruned_transducer_stateless3 to pruned_transducer_stateless4
* change epoch number counter starting from 1 instead of 0
* minor fix of pruned_transducer_stateless4/train.py
* refactor the checkpoint.py
* minor fix, update docs, and modify the epoch number to count from 1 in the pruned_transducer_stateless4/decode.py
* update author info
* add docs of the scaling in function average_checkpoints_with_averaged_model
