Commit Graph

10 Commits

Author SHA1 Message Date
Enno Hermann 1f27f994a1 refactor(utils): remove duplicate set_partial_state_dict 2024-11-21 11:53:35 +01:00
Enno Hermann 2df9bfa78e
refactor: handle deprecation of torch.cuda.amp.autocast (#144)
torch.cuda.amp.autocast(args...) and torch.cpu.amp.autocast(args...) will be
deprecated. Please use torch.autocast("cuda", args...) or torch.autocast("cpu",
args...) instead.

https://pytorch.org/docs/stable/amp.html
2024-11-09 18:37:08 +01:00
Enno Hermann da82d55329 refactor: use load_fsspec from trainer
Made automatically with:
rg "from TTS.utils.io import load_fsspec" --files-with-matches | xargs sed -i 's/from TTS.utils.io import load_fsspec/from trainer.io import load_fsspec/g'
2024-06-29 15:07:10 +02:00
Enno Hermann b6ab85a050 fix: use logging instead of print statements
Fixes #1691
2024-04-03 15:19:45 +02:00
Edresson Casanova 16b9862252
Fix Speaker Consistency Loss (SCL) (#2364) 2023-02-27 09:14:00 +03:00
Eren Gölge 8cb1433e6e
Cache fsspec downloads (#2132)
* Cache fsspec downloaded files

* Use diff paths for test

* Make fsspec caching optional

* Decom GPU docker tests

* Make progress bar optional for better CI log

* Check path local
2022-11-09 22:12:48 +01:00
Edresson Casanova 096b35f639
Add VCTK speaker encoder recipe (#1912) 2022-08-26 16:19:03 +02:00
Eren Gölge d46fbc240c
Introduce numpy and torch transforms (#1705)
* Refactor audio processing functions

* Add tests for numpy transforms

* Fix imports

* Fix imports2
2022-08-08 11:57:50 +02:00
Eren Gölge 0870a4faa2
Make style (#1405) 2022-03-16 12:13:55 +01:00
Edresson Casanova f81892483d
REBASED: Transform Speaker Encoder in a Generic Encoder and Implement Emotion Encoder training support (#1349)
* 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
2022-03-11 14:43:40 +01:00