GitLab

* example pipeline, initial commit.

* removing notebook conversion artifacts.

* remove extra comments. lint.

* addressing some feedback.

* main function.

* defining args in function.

* refactor.

* lint.

* checkpoint.

* clean version to start with.

* adding more parameters.

* lint.

* cleaning full version.

* check for not None.

* cleaning.

* back -l 160

* black.

* fix runtime error.

* removing some print statements.

* add help to command line. add progress bar option.

* grouping librispeech-specific transform in subclass.

* typo.

* fix concatenation.

* typo.

* black. tqdm.

* missing transpose.

* renaming variables.

* sum cer and wer

* clip norm.

* second signal handler removed.

* cosmetic.

* default to no checkpoint.

* remove non_blocking.

* adadelta works better than sgd.

* anomaly detection.

* moving dataset to separate file.

* lint.

* move to separate module: languagemodel, decoder, metric.

* flush=True.

* renaming decoder.

* CTC Decoders.

* flush=True.

* pass length for viterbi decoder.

* progress bar. relative path.

* generalize transition matrix to n-gram. progress bar.

* choice of decoder.

* collate func.

* remove signal handling.

* adding distributed.

* lint.

* normalize w/r to length of dataset, and w/r to total number characters.

* relative cer/wer.

* clip grad parameter. momentum back but not yet used.

* Switch to SGD.

* choice of optimizer.

* scheduler.

* move to utils file.

* metric log, and utils file.

* rename metric_logger.

* stderr and stdout. simpler metric logger.

* replace by logging.

* adding time measurement in metric logger.

* fix duplicate name. remove tqdm. keep track of epoch instead and iteration instead.

* rename main file. and add readme.

* refactor distributed.

* swap example and output in readme.

* remove time from logger.

* check non-empty tensor input.

* typo in variable name and log update.

* typo.

* compute cer/wer in training too.

* typo.

* add back slurm signal capture to resubmit job.

* update levinstein distance.

* adding tests for levenstein distance.

* record error rate during iteration.

* metric logger using setitem.

* moving signal break to end of loop and return loss so far.

* typo.

* add citation.

* change default to best run.

* adding other experiment with decoders.

* remove other decoders than greedy.

* Revert "remove other decoders than greedy."

This reverts commit fb114372e89e317bf48d0b1f846c60bca8efe1ac.

* changing name of folfder.

* remove other decoders, and unused dataset class.

* rename functions to align with other pipeline.

* pick which parts to train with.

* adding specaugment to validation. note that caching prevents randomization from happening in validation.

* updating readme.

* typo in metric logging.

* Revert "typo in metric logging."

This reverts commit acac245eec250f61d2039a67933d3c01f1975ce9.

* Revert "Revert "typo in metric logging.""

This reverts commit 2c80d9691ed401044da734c40df3715dba92d0db.

* update metric logger.

* simplify metric logger implementation.

* use json dumps instead.

* group metric together.

* move function.

* lint.

* quick summary of files in folder.

* pass clip_grad explictly.

* typo in default dataset name.

* option to disable logger.

* ergonomics for distributed.

* reminder about signal handler.

* minor refactor of main in main.

* replace by not_main_rank.

* raising error if parameter not supported.

* move model before invoking DDP.

* changing log level. using python 2 style string for logging.

* dynamic augmentations.

* update metric log.

batch cer/wer metric. correct typo in time. adding other dimensions in metric.

* save learning rate even if function not available.

* add type option to model.

* add adamw.

* reduce lr on validation step or training step.

* specify hop-length and win-length.

* normalize option.

* rename parameter.

* add dropout and tweak to number of channels.

* copy model in pipeline folder for experimentation.

* fix scheduler stepping.

* fix input_type and num_features.

* waveform mode changes shape more.

* adding best character error rate with current implementation of model with mfcc.

* comment update.

* remove signal. remove custom wav2letter model.

* remove comment.

* simpler import with pandas.