* 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
* initial commit
* support download, data prep, and fbank
* on-the-fly feature extraction by default
* support BPE based lang
* support HLG for BPE
* small fix
* small fix
* chunked feature extraction by default
* Compute features for GigaSpeech by splitting the manifest.
* Fixes after review.
* Split manifests into 2000 pieces.
* set audio duration mismatch tolerance to 0.01
* small fix
* add conformer training recipe
* Add conformer.py without pre-commit checking
* lazy loading and use SingleCutSampler
* DynamicBucketingSampler
* use KaldifeatFbank to compute fbank for musan
* use pretrained language model and lexicon
* use 3gram to decode, 4gram to rescore
* Add decode.py
* Update .flake8
* Delete compute_fbank_gigaspeech.py
* Use BucketingSampler for valid and test dataloader
* Update params in train.py
* Use bpe_500
* update params in decode.py
* Decrease num_paths while CUDA OOM
* Added README
* Update RESULTS
* black
* Decrease num_paths while CUDA OOM
* Decode with post-processing
* Update results
* Remove lazy_load option
* Use default `storage_type`
* Keep the original tolerance
* Use split-lazy
* black
* Update pretrained model
Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>
* update icefall/__init__.py to import more common functions.
* update icefall/__init__.py
* make imports style consistent.
* exclude black check for icefall/__init__.py in pyproject.toml.
* Adding diagnostics code...
* Move diagnostics code from local dir to the shared icefall dir
* Remove the diagnostics code in the local dir
* Update docs of arguments, and remove stats_types() function in TensorDiagnosticOptions object.
* Update docs of arguments.
* Add copyright information.
* Corrected the time in copyright information.
Co-authored-by: Daniel Povey <dpovey@gmail.com>
