Commit Graph

90 Commits

Author SHA1 Message Date
mrq
b2907ae7e0 seems that my PromEmbedding/RespEmbedding doesn't actually work all that well, naively using dedicated MultiEmbeddings for AR/NAR in the monolithic model is the best way to go 2023-09-08 01:03:24 -05:00
mrq
67617d7d69 also cull frozen_params in the params optimizer receives to reduce VRAM it consumes 2023-09-07 18:27:02 -05:00
mrq
8837bc34d7 added option to specify parameters to freeze per-model in YAML (because I need to see about committing atrocities with convering an AR into an AR+NAR) 2023-09-07 18:19:51 -05:00
mrq
c47fc3274e added backwards compat flag 2023-09-07 17:12:17 -05:00
mrq
ab5134f385 tweaks and fixes 2023-09-07 17:08:38 -05:00
mrq
b2c2dec291 added homebrewed per-RVQ-bin embedding solutions 2023-09-07 16:48:02 -05:00
mrq
e7a67410d1 oops 2023-09-07 09:14:03 -05:00
mrq
712808494f added support for optional prodigy optimizer (https://github.com/konstmish/prodigy) although it consumes a lot more VRAM per parameter 2023-09-06 20:33:16 -05:00
mrq
7ce06432fd fixed the AR+NAR dual model, the resp_emb has to be split up (classifier might too) 2023-09-06 19:33:39 -05:00
mrq
100ca6b7d0 added option to use SGD optimizer through the YAML, added option to pass in additional optimizer parameters through the YAML, added experimental unified AR+NAR model (does not seem fruitful in testing) 2023-09-06 18:58:35 -05:00
mrq
451726fdd5 added ability to disable activation checkpointing through the YAML (it is very VRAM intensive at double layer size) 2023-09-05 15:38:21 -05:00
mrq
143aee7526 removed dedicated interleaved AR code 2023-09-03 22:47:03 -05:00
mrq
2f9cd0842f merged dedicated interleaved AR code with the normal AR code 2023-09-03 22:46:08 -05:00
mrq
3a6bd50322 haha 2023-09-03 21:36:58 -05:00
mrq
c56ce033d9 work on an interleaved AR (spoiler: it does not work) 2023-09-03 21:27:58 -05:00
mrq
8a6c203277 added per-speaker samplers 2023-09-03 21:27:13 -05:00
mrq
81b05dabb9 accurate epoch metric is now reported (based on samples processed / length of dataset's paths, rather than naive assumptions) 2023-09-03 08:03:36 -05:00
mrq
922404285c fixed segfault from tts-c task token exceeding being too big (inserted it in the hypothetical svc task token because in reality that is never ever going to be a feasible task to train against) 2023-09-02 19:25:43 -05:00
mrq
4613781e23 integrated plot script, added tts-c task token to help the model be able to mix between normal VALL-E and VALL-E continuous 2023-09-02 16:29:53 -05:00
mrq
f7e942ec99 modified plotting script to be more agnostic to X 2023-09-02 13:59:43 -05:00
mrq
71e68a8528 tweaked tts-continuous task 2023-09-02 13:39:17 -05:00
mrq
21e5d250cc fixed up plot script that I forgot about 2023-09-02 13:31:04 -05:00
mrq
57db3ccfa8 shuffled VALL-E continuous as a task tts-c instead, logic fixes for it 2023-09-02 12:23:40 -05:00
mrq
2f06166ddd cleanups 2023-09-01 21:33:51 -05:00
mrq
e40c0d34a0 somewhat got recurrent forward working (it's as accurate as chunkwise forward: it's not accurate at all), added option to use AMP instead of blanket setting the weight's dtype 2023-09-01 20:58:29 -05:00
mrq
2bc2d08b09 (need to verify) added modifying model size and config bool to align with VALL-E continuous' methodology 2023-09-01 17:19:34 -05:00
mrq
5c8694db8e nasty bandaid if there's no validation dataset specified during training (for example, during finetunes) 2023-08-30 18:23:05 -05:00
mrq
7f4388e591 added total samples processed and tokens processed (len of text tokens + len of target response tokens) 2023-08-28 11:02:45 -05:00
mrq
87c4bfedba added ability to mark models as disabled for training, and hotloading them for eval/validation (useful if training only one model, or training a model per GPU) 2023-08-27 12:26:12 -05:00
mrq
165a1154e0 Undo naive=False test flag, this shouldn't have made its way in 2023-08-26 22:00:43 -05:00
mrq
78378ed1ce overhauled dataloading code to be marginally faster, mostly cleaned up, and can leverage a metadata json to help things out 2023-08-26 19:53:23 -05:00
mrq
7b3be3d7bf added helper scripts to process LibriTTS/LibriLight, detect duplicate speaker+books between them, and script to directly phonemize and quantize LibriTTS 2023-08-26 10:21:12 -05:00
mrq
16e0020901 disabled chunkwise_recurrent for 2x speed gains (I suppose it has been working the entire time, but I have not been properly grabbing things, and this might explain why the output is bad) 2023-08-25 19:50:19 -05:00
mrq
6455a2f9d7 I think I fixed a bug? 2023-08-24 23:33:36 -05:00
mrq
f3fbed5ffd updated notices tailored for windows / low VRAM cards 2023-08-24 17:19:10 -05:00
mrq
0517d620b8 fixes with the local backend 2023-08-24 17:05:56 -05:00
mrq
00ad4af651 updated draconian requirement for espeak-ng to be installed and the env var set to the dll for Windows 2023-08-24 14:57:01 -05:00
mrq
b6c9686f7d Do not install DeepSpeed under Windows (to-do: default backend to use local if on Windows) 2023-08-24 14:27:36 -05:00
mrq
22904a8639 more oversights fixed because I've been using a cached dataloader forever now and didn't catch these problems 2023-08-24 10:25:33 -05:00
mrq
5873c27f1a ops 2023-08-24 09:20:47 -05:00
mrq
501a857d5d ops 2023-08-23 17:03:25 -05:00
mrq
4585824cd3 tweaks, including exporting on save/quit 2023-08-23 16:43:03 -05:00
mrq
d106598403 do not utilize diskcache if a config yaml is not loaded 2023-08-23 11:02:15 -05:00
mrq
524d289c9c Forgot to re-add in setting the weight's dtype on model load 2023-08-22 22:57:23 -05:00
mrq
9c5a33bfd2 added repo with my weights so far 2023-08-22 13:09:44 -05:00
mrq
7b1b82e0e5 inferencing cleanup 2023-08-20 21:36:02 -05:00
mrq
a47029065b I don't know if the lack of start/stop tokens being added was causing my inference tests to fail, but it seems better now 2023-08-20 19:21:54 -05:00
mrq
736c077282 ops 2023-08-20 13:42:18 -05:00
mrq
b105f6211e added ability to export weights mid-training to avoid CBT to yank the weights while the training script is running 2023-08-20 13:39:58 -05:00
mrq
fc576010ce wrapped saving the checkpoint in a try/catch so I can stop waking up to the damn trainer crashing because it ran out of disk space; I'd much rather it keep training to give me time to eventually clear up disk space rather than it silently restarting on its own 2023-08-20 06:29:17 -05:00