* Fixed bug related to yourtts speaker embeddings issue
* Reverted code for base_tts
* Bug fix on VITS d_vector_file type
* Ignore the test speakers on YourTTS recipe
* Add speaker encoder model and config on YourTTS recipe to easily do zero-shot inference
* Update YourTTS config file
* Update ModelManager._update_path to deal with list attributes
* Fix lint checks
* Remove unused code
* Fix unit tests
* Reset name_to_id to get the right speaker ids on load_embeddings_from_list_of_files
* Set weighted_sampler_multipliers as an empty dict to prevent users' mistakes
Co-authored-by: Edresson Casanova <edresson1@gmail.com>
* Update BaseDatasetConfig
- Add dataset_name
- Chane name to formatter_name
* Update compute_embedding
- Allow entering dataset by args
- Use released model by default
- Use the new key format
* Update loading
* Update recipes
* Update other dep code
* Update tests
* Fixup
* Load multiple embedding files
* Fix argument names in dep code
* Update docs
* Fix argument name
* Fix linter
* 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
* Add alphas to control language and speaker balancer
* Add docs for speaker and language samplers
* Change the Samplers weights to float for save memory
* Change the test_samplers to unittest format
* Add get_sampler method in BaseTTS
* Fix rebase issues
* Add language and speaker samplers support for DDP training
* Rename distributed sampler wrapper
* Remove the DistributedSamplerWrapper and use the one from Trainer
* Bugfix after rebase
* Move the samplers config to tts config
* 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