Commit Graph

182 Commits

Author SHA1 Message Date
mrq
dced595391 more cleanup 2024-06-30 11:00:12 -05:00
mrq
bc2a6fa756 sanity cleanup: moved experimental features under its own thing 2024-06-30 10:37:33 -05:00
mrq
b21f74a5c5 added summing of external embeddings (at this point i dont think any amount of cope bandaids will get DAC to train nicely, I think the RVQ levels the NAR tends add too much noise if they're not accurate) 2024-06-29 23:42:30 -05:00
mrq
793ccb16fb ugh 2024-06-29 22:14:35 -05:00
mrq
2808f881c8 cleaned up subjugated audio embedding into a flag, flag can also have it include the original, underlying embedding as well (it seems to do better when set to inclusive) 2024-06-29 21:46:35 -05:00
mrq
ec5eaebcbc experimental method of using DACs quantizer ""embeddings"" to see if it helps with model quality 2024-06-29 19:46:11 -05:00
mrq
a8718d35a4 nasty bandaid because some of my DAC dataset only has 8 RVQ levels instead of the full 9 2024-06-29 10:16:37 -05:00
mrq
591d3ac848 have eval dataloader use eval batch size for batchedordersampler 2024-06-28 22:44:00 -05:00
mrq
83075c1505 sort duration buckets to ensure that paths sorted-by-duration are actually sorted by duration (because i didnt know that python dicts can have non-strings as keys), added batching samples based on total duration to ensure best training throughput 2024-06-28 22:28:54 -05:00
mrq
8a986eb480 load exported LoRA weights if exists (to-do: make a better LoRA loading mechanism) 2024-06-18 21:45:46 -05:00
mrq
2bfe786ebd ban stop token for NAR levels (because sometimes it gets sampled and causes problems) 2024-06-17 22:14:43 -05:00
mrq
7cfb78fa64 enable LoRA for targetted RVQ levels (to experiment with, seems to help) 2024-06-17 21:45:03 -05:00
mrq
7047fcc6e2 actually make deepspeed work with LoRAs 2024-06-17 13:55:37 -05:00
mrq
1d159b1476 updated export routine to split LoRA weights from the state dict (should work with deepspeed) 2024-06-17 13:28:18 -05:00
mrq
bd0bc10ec0 added LoRA policy to decide what layer of the model gets adapted based on simple inclusion/exclusion terms 2024-06-17 13:05:06 -05:00
mrq
be051d9544 added other LoRA method using parametrization rather than linear injection 2024-06-17 09:58:34 -05:00
mrq
45a39fb79f very rudimentary lora support (no deepspeed support, tested training and saving but not loading yet) 2024-06-17 00:09:16 -05:00
mrq
19410a919e ugh 2024-06-15 12:29:03 -05:00
mrq
d343bde09b residual_in_fp32=False for mamba arch backends because it breaks the classifier (output projection / lm head / what-have-you) under AMP 2024-06-15 12:08:03 -05:00
mrq
ccb14c06ef mamba2-hf using vasqu/mamba2-torch because it lets me use mamba2 without triton ops (training with my 4xV100s are not happy with mamba2 because of triton) 2024-06-14 19:42:17 -05:00
mrq
83eab4fa59 actually going for the suggested "2x layers, no intermediate scaling" is wrong for VALL-E, directly copying the normal transformer structure fixes mamba2 performance in the test trainer 2024-06-13 20:08:22 -05:00
mrq
26da24fd8d mamba updated to fix that pesky NaN error during training 2024-06-13 12:38:33 -05:00
mrq
bcf3910a17 the NAR only dream is dead (it just won't work) 2024-06-12 19:49:47 -05:00
mrq
a9353cf9fa ugh 2024-06-12 00:14:29 -05:00
mrq
cca542a4c0 ugh 2024-06-11 23:59:28 -05:00
mrq
65a8960305 option to split classifier per-level instead of sharing one (at this point I'm just scrambling to try and cope with training a DAC model, the NAR is being a pain) 2024-06-11 22:28:59 -05:00
mrq
a7a6e0ac76 validated that inferencing works, changed some defaults (NAR benefits from greedy sampling) 2024-06-09 17:11:38 -05:00
mrq
132a02c48b sanity cleanup, backup config yaml for each log file 2024-06-09 11:22:52 -05:00
mrq
80f9530840 ugh 2024-06-09 01:43:44 -05:00
mrq
5c732b72ee ugh 2024-06-08 20:34:00 -05:00
mrq
8d068fa3f9 reticulating splines 2024-06-08 20:30:15 -05:00
mrq
b072f9b96b fixes 2024-06-08 16:01:34 -05:00
mrq
58fb0a84db added experimental NAR only model (inferences text length, need more experimenting), AudioEmbedding logic cleanup (I still think it's being done wrong) 2024-06-08 15:42:02 -05:00
mrq
7d6fff24f9 un-tensor'd quant_level marker since it doesn't need to be one (I forgot why I had it as one but nothing seems to need it as a tensor that didn't already make it one) 2024-06-07 20:46:22 -05:00
mrq
b0158a61d5 fixed some logic errors with training (grabbing wrong quant level...) 2024-06-07 20:34:36 -05:00
mrq
eafa622be2 I forgot the actual reason I was cleaning things up was to re-include prom loss calculation (I realized the reason I did this was because of an prom embedding oversight, it seems to work now) 2024-06-07 20:29:25 -05:00
mrq
f9f309281a ugh 2024-06-06 20:55:27 -05:00
mrq
a5c90348d9 head hurt 2024-06-06 20:51:31 -05:00
mrq
516b0894d7 m 2024-06-06 19:41:26 -05:00
mrq
ee25d2e62e removed the need to supply targ_list + different AudioEmbedding + other things 2024-06-06 18:52:41 -05:00
mrq
fcac9503e2 cleanup 2024-06-06 13:08:02 -05:00
mrq
b2194b859a re-added loading multiple models because I'm now entertaining having split AR/NAR models again (and need a way to load both at once) 2024-06-06 09:48:43 -05:00
mrq
b05a905b95 ugh 2024-06-05 21:02:05 -05:00
mrq
4073656293 oops 2024-06-05 20:53:10 -05:00
mrq
ff6fe6f1bc cleanup 2024-06-05 20:30:43 -05:00
mrq
880b4ecd1b cleanup, putting some thoughts in comments before I forget about them 2024-06-05 19:50:06 -05:00
mrq
3cfc8a96bb oops 2024-06-05 10:30:04 -05:00
mrq
48cd1054f9 madness 2024-06-04 23:48:51 -05:00
mrq
9e3f2e300f experimental "just have a token for what rvq level we're on" that seems to help all models (mamba almost works, but it might just have to be relegated as a pure AR model) 2024-06-04 23:23:31 -05:00
mrq
e0886c5a78 re-added mamba as a possible non-experimental arch backend (test trainer will set it as AR only, doing any NAR tasks lobotomizes it) 2024-06-04 22:41:22 -05:00