neonbjb/tortoise-tts
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19 commits

Author SHA1 Message Date
manmay-nakhashi 5a9707d93c added deepspeed inference 2023-07-09 18:40:10 +05:30
James Betker 25dd04650c
Revert autocast "fix". 2023-04-02 04:04:18 -07:00
Sergey 4e990b4327
Update diffusion_decoder.py 
Chanhged import autocast from torch
 2023-03-29 13:20:18 +03:00
James Betker 5dc3e269b3
Merge pull request #233 from kianmeng/fix-typos 
Fix typos
 2023-01-17 18:24:24 -07:00
원빈 정 b3d67dcc6b Add reference of univnet implementation 2023-01-06 15:57:02 +09:00
Kian-Meng Ang 551fe655ff Fix typos 
Found via `codespell -S *.json -L splitted,nd,ser,broadcat`
 2023-01-06 11:04:36 +08:00
James Betker 958c6d2f73 Get rid of checkpointing 
It isn't needed in inference.
 2022-06-15 22:09:15 -06:00
Johan Nordberg d8f98c07b4 Remove some assumptions about working directory 
This allows cli tool to run when not standing in repository dir
 2022-05-29 01:10:19 +00:00
James Betker f56f3d5468 Fix import issue for CVVP 2022-05-26 08:44:20 -06:00
Johan Nordberg a52e3026ba Revive CVVP model 2022-05-25 10:22:50 +00:00
James Betker 8139afd0e5 Remove CVVP 
After training a similar model for a different purpose, I realized that
this model is faulty: the contrastive loss it uses only pays attention
to high-frequency details which do not contribute meaningfully to
output quality. I validated this by comparing a no-CVVP output with
a baseline using tts-scores and found no differences.
 2022-05-17 12:21:25 -06:00
James Betker ffd0238a16 v2.2 2022-05-06 00:11:10 -06:00
James Betker 29b2f36f55 Remove entmax dep 2022-05-02 21:43:14 -06:00
James Betker 8c7f709c12 k I think this works.. 2022-05-02 21:31:31 -06:00
James Betker 9acce239d3 fix paths 2022-05-02 20:56:28 -06:00
James Betker cdf44d7506 more fixes 2022-05-02 16:44:47 -06:00
James Betker 39ec1b0db5 Support totally random voices (and make fixes to previous changes) 2022-05-02 15:40:03 -06:00
James Betker 0ffc191408 Add support for extracting and feeding conditioning latents directly into the model 
- Adds a new script and API endpoints for doing this
- Reworks autoregressive and diffusion models so that the conditioning is computed separately (which will actually provide a mild performance boost)
- Updates README

This is untested. Need to do the following manual tests (and someday write unit tests for this behemoth before
it becomes a problem..)
1) Does get_conditioning_latents.py work?
2) Can I feed those latents back into the model by creating a new voice?
3) Can I still mix and match voices (both with conditioning latents and normal voices) with read.py?
 2022-05-01 17:25:18 -06:00
James Betker f7c8decfdb Move everything into the tortoise/ subdirectory 
For eventual packaging.
 2022-05-01 16:24:24 -06:00