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5 Commits

Author SHA1 Message Date
Fangjun Kuang
fba5e67d5e
Fix CI tests. (#1974) 
- 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
 2025-07-01 13:47:55 +08:00
Fangjun Kuang
8136ad775b
Use high_freq -400 in computing fbank features. (#1447) 
See also https://github.com/k2-fsa/sherpa-onnx/issues/514
 2024-01-04 13:59:32 +08:00
Zengwei Yao
b25c234c51
Add Zipformer-MMI (#746) 
* Minor fix to conformer-mmi

* Minor fixes

* Fix decode.py

* add training files

* train with ctc warmup

* add pruned_transducer_stateless7_mmi

* add zipformer_mmi/mmi_decode.py, using HP as decoding graph

* add mmi_decode.py

* remove pruned_transducer_stateless7_mmi

* rename zipformer_mmi/train_with_ctc.py as zipformer_mmi/train.py

* remove unused method

* rename mmi_decode.py

* add export.py pretrained.py jit_pretrained.py ...

* add RESULTS.md

* add CI test

* add docs

* add README.md

Co-authored-by: pkufool <wkang.pku@gmail.com>
 2022-12-11 21:30:39 +08:00
Zengwei Yao
8eb4b9d96d
Combining rnnt loss and k2-ctc loss for Dan's Zipformer (#683) 
* init files

* add ctc as auxiliary loss and ctc_decode.py

* tuning the scalar of HLG score for 1best, nbest and nbest-oracle

* rename to pruned_transducer_stateless7_ctc

* fix doc

* fix bug, recover the hlg scores

* modify ctc_decode.py, move out the hlg scale

* fix hlg_scale

* add export.py and pretrained.py, and so on

* upload files, update README.md and RESULTS.md

* add CI test
 2022-12-03 19:01:10 +08:00
Zengwei Yao
ece728d895
Apply delay penalty on k2 ctc loss (#669) 
* add init files

* fix bug, apply delay penalty

* fix decoding code and getting timestamps

* add option applying delay penalty on ctc log-prob

* fix bug of streaming decoding

* minor change for bpe-based case

* add test_model.py

* add README.md

* add CI
 2022-11-28 22:34:02 +08:00