* 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>
We are using multiple machines to do various experiments. It makes
life easier to know which experiment is running on which machine
if we also log the IP and hostname of the machine.
* Update RESULTS using vocab size 500, att rate 0.8
* Update README.
* Refactoring.
Since FSAs in an Nbest object are linear in structure, we can
add the scores of a path to compute the total scores.
* Update documentation.
* Change default vocab size from 5000 to 500.
* Add a note about the CUDA OOM error.
Some users consider this kind of OOM as an error during decoding,
but actually it is not. This pull request clarifies that.
* Fix style issues.
* Use new APIs with k2.RaggedTensor
* Fix style issues.
* Update the installation doc, saying it requires at least k2 v1.7
* Extract framewise alignment information using CTC decoding.
* Print environment information.
Print information about k2, lhotse, PyTorch, and icefall.
* Fix CI.
* Fix CI.
* Compute framewise alignment information of the LibriSpeech dataset.
* Update comments for the time to compute alignments of train-960.
* Preserve cut id in mix cut transformer.
* Minor fixes.
* Add doc about how to extract framewise alignments.
* Update index.rst (AS->ASR)
* Update conformer_ctc.rst (pretraind->pretrained)
* Fix some spelling errors.
* Fix some spelling errors.
* Use LossRecord to record and print loss in the training process
* Change the name "LossRecord" to "MetricsTracker"
* Rename lattice_score_scale to nbest_scale.
* Support pure CTC decoding requiring neither a lexicion nor an n-gram LM.
* Fix style issues.
* Fix a typo.
* Minor fixes.
* Refactor decode.py to make it more readable and more modular.
* Fix an error.
Nbest.fsa should always have token IDs as labels and
word IDs as aux_labels.
* Add nbest decoding.
* Compute edit distance with k2.
* Refactor nbest-oracle.
* Add rescore with nbest lists.
* Add whole-lattice rescoring.
* Add rescoring with attention decoder.
* Refactoring.
* Fixes after refactoring.
* Fix a typo.
* Minor fixes.
* Replace [] with () for shapes.
* Use k2 v1.9
* Use Levenshtein graphs/alignment from k2 v1.9
* [doc] Require k2 >= v1.9
* Minor fixes.
