* Rename Speaker encoder module to encoder
* Add a generic emotion dataset formatter
* Transform the Speaker Encoder dataset to a generic dataset and create emotion encoder config
* Add class map in emotion config
* Add Base encoder config
* Add evaluation encoder script
* Fix the bug in plot_embeddings
* Enable Weight decay for encoder training
* Add argumnet to disable storage
* Add Perfect Sampler and remove storage
* Add evaluation during encoder training
* Fix lint checks
* Remove useless config parameter
* Active evaluation in speaker encoder test and use multispeaker dataset for this test
* Unit tests fixs
* Remove useless tests for speedup the aux_tests
* Use get_optimizer in Encoder
* Add BaseEncoder Class
* Fix the unitests
* Add Perfect Batch Sampler unit test
* Add compute encoder accuracy in a function
* Add support for voice conversion inference
* Cache d_vectors_by_speaker for fast inference using a bigger speakers.json
* Rebase bug fix
* Use the average d-vector for inference
* Fix the bug in find unique chars script
* Add OpenBible formatter
Co-authored-by: Eren Gölge <erogol@hotmail.com>
* Add support for voice conversion inference
* Cache d_vectors_by_speaker for fast inference using a bigger speakers.json
* Rebase bug fix
* Use the average d-vector for inference
* Fix the bug in split_dataset
* Make eval_split_size configurable
* Change test_loader to use load_tts_samples function
* Change eval_split_portion to eval_split_size and permits to set the absolute number of samples in eval
* Fix samplers unit test
* Add data unit test on GitHub workflow
commit d3e477875a7e46a101fcf95a1794442823750fe2
Author: George Rousssos <25833833+george-roussos@users.noreply.github.com>
Date: Wed Nov 3 10:16:12 2021 +0000
Read .wav for GST conditioning from CL
commit 074e6d0874d3b34fb6a4991fc17d66dccd413fbb
Author: George Rousssos <25833833+george-roussos@users.noreply.github.com>
Date: Fri Oct 29 14:43:47 2021 +0100
Fix GST during inference in Tacotron2
commit fdece14585ab5a36eed1061a9a838d8e48aa6882
Author: George Rousssos <25833833+george-roussos@users.noreply.github.com>
Date: Wed Nov 3 10:16:12 2021 +0000
Read .wav for GST conditioning from CL
commit cd29e21b8d0a541ee298d2bf5f67223ad60be38f
Author: George Rousssos <25833833+george-roussos@users.noreply.github.com>
Date: Fri Oct 29 14:43:47 2021 +0100
Fix GST during inference in Tacotron2
commit 908ce39370eadcc9fa8510cdb26c9ead87305427
Author: George Rousssos <25833833+george-roussos@users.noreply.github.com>
Date: Fri Oct 29 12:49:37 2021 +0100
Make trim_db value negative
commit 1008a2e0f72fa7ca7f0307424f570386f2f16d42
Author: George Rousssos <25833833+george-roussos@users.noreply.github.com>
Date: Fri Oct 29 12:22:24 2021 +0100
Set find_endpoint db threshold in config.json
1. Use a single Gradscaler for all the optimizers
2. Save terminal logs to a file. In DDP mode, each worker creates `trainer_N_log.txt`.
3. Fixes to allow only the main worker (rank==0) writing to Tensorboard
4. Pass parameters owned by the target optimizer to the grad_clip_norm
* Allow saving / loading checkpoints from cloud paths
Allows saving and loading checkpoints directly from cloud paths like
Amazon S3 (s3://) and Google Cloud Storage (gs://) by using fsspec.
Note: The user will have to install the relevant dependency for each
protocol. Otherwise fsspec will fail and specify which dependency is
missing.
* Append suffix _fsspec to save/load function names
* Add a lower bound to the fsspec dependency
Skips the 0 major version.
* Add missing changes from refactor
* Use fsspec for remaining artifacts
* Add test case with path requiring fsspec
* Avoid writing logs to file unless output_path is local
* Document the possibility of using paths supported by fsspec
* Fix style and lint
* Add missing lint fixes
* Add type annotations to new functions
* Use Coqpit method for converting config to dict
* Fix type annotation in semi-new function
* Add return type for load_fsspec
* Fix bug where fs not always created
* Restore the experiment removal functionality