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3019c88799
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separate mask token and stop token because this might cause issues
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2025-02-23 11:36:32 -06:00 |
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6634d07576
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added muon optimizer through kludge hacks because it necessitates a second optimizer in tandum that seems to only sometimes work with deepspeed
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2025-02-23 11:22:13 -06:00 |
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67a6009555
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(finally) added parallel AR for cfg.model.version >= 7 (nvidia/audio-codec-44khz is being a pain and it might require training purely AR first......)
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2025-02-23 08:31:03 -06:00 |
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ab0abd2b12
|
fixes fixes fixes (a quarter of my recently processed audio returned zero'd tensors......)
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2025-02-22 09:07:33 -06:00 |
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13c3a08853
|
nevermind thats slow
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2025-02-14 16:35:17 -06:00 |
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285e493b12
|
ugh..........
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2025-02-14 16:24:34 -06:00 |
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a65c8144f4
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with the amount of tweaks I keep making I could have probably had the nvidia/audio-codec-44khz model realized already......
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2025-02-13 18:38:40 -06:00 |
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e3becec0e8
|
more better-er loss calc I suppose
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2025-02-13 12:49:53 -06:00 |
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e8f182b634
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cleaned up loss calc code (it REALLY hates ignore_loss_for_inputs, but is fine with splitting with loss factors)
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2025-02-13 09:35:27 -06:00 |
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319ca09a4f
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cleanup
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2025-02-12 23:36:32 -06:00 |
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b52c5c5d80
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this seems to work in testing
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2025-02-12 16:16:04 -06:00 |
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e029a8804d
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ironically none of this cruft gets the loss lower than the original way
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2025-02-12 11:17:00 -06:00 |
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4b31f5c808
|
this seems preferable
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2025-02-12 00:36:50 -06:00 |
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04fef5dad5
|
agony
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2025-02-12 00:18:24 -06:00 |
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075ffef68a
|
ugh
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2025-02-09 13:02:51 -06:00 |
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47eb498046
|
more tweaks
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2025-02-06 23:26:26 -06:00 |
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79c504c278
|
cleaned up encode/decode functions to make them a little more coherent, added option to batch encode/decode (would have been very nice in the past, but this should speed things up for me when i fall for the latest meme codec)
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2025-02-05 20:54:31 -06:00 |
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bb2ebe1ca2
|
fixed issues that may rise from updating transformers with attention, added nvidia/audio-codec-44khz backend support (by gutting everything necessary because I do NOT want to install more dependencies
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2025-02-04 20:30:07 -06:00 |
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0841f366e8
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I should really just grab modelling_llama wholesale (fix for the adapted attention class)
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2025-01-28 21:55:05 -06:00 |
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e5f9da2221
|
oops
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2025-01-21 11:59:24 -06:00 |
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69c1d2991f
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updated mixtral backend (need this for something else)
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2025-01-20 21:50:56 -06:00 |
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1a26f789a5
|
added option to playback audio directly, removed no-phonemize option since I swear it worked in testing but it doesn't actually work
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2025-01-12 21:52:49 -06:00 |
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3ab11bdc7b
|
oops
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2025-01-05 23:53:17 -06:00 |
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b445f4abb6
|
experimental
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2025-01-05 19:05:00 -06:00 |
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2e6a7625e4
|
experimental
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2025-01-05 12:47:03 -06:00 |
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9b0d2ccbe1
|
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2024-12-26 21:42:17 -06:00 |
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59f56ad099
|
cleaup
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2024-12-24 23:14:32 -06:00 |
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82e8592f2a
|
working vall_e.cpp
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2024-12-24 17:54:48 -06:00 |
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497bdfc67b
|
more work (the wall is non-causal decoding......)
|
2024-12-22 20:11:31 -06:00 |
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5f289db275
|
ugh
|
2024-12-22 16:15:24 -06:00 |
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0d4329d2e3
|
sanity cleanup
|
2024-12-22 15:05:45 -06:00 |
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353e478e68
|
agony
|
2024-12-21 22:52:10 -06:00 |
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91caf00212
|
ugh
|
2024-12-20 17:13:37 -06:00 |
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59bf6b8b33
|
exposed additional task (ns, sr, vc) (vc is experimental)
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2024-12-20 11:15:29 -06:00 |
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e7e7f48043
|
livid
|
2024-12-19 19:25:27 -06:00 |
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c2c6d912ac
|
actually do speaker verification
|
2024-12-17 10:11:14 -06:00 |
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c2e17e287b
|
really shoddy voice conversion implementation (it sort of works...)
|
2024-12-16 22:54:53 -06:00 |
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8515038968
|
imagine my disappointment when the epoch finished just for it to throw an exception
|
2024-12-16 18:28:01 -06:00 |
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4a65ac9eb7
|
oops
|
2024-12-15 17:21:51 -06:00 |
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9a62e3b824
|
APOLLO cringe (doesn't want to work with deepspeed)
|
2024-12-12 00:31:58 -06:00 |
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cddf8ca814
|
sort batches to try and reduce number of padded tokens in batched inference (also commented out F5 samples getting added to the demo page because I would have to regenerate them)
|
2024-12-11 22:45:38 -06:00 |
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6468e5d124
|
lol
|
2024-12-11 19:10:32 -06:00 |
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3ef8894290
|
oops
|
2024-12-08 15:24:21 -06:00 |
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1d460b9fe3
|
logic fixes, I feel like output is better? (also NAR can have a temperature, I imagine it couldn't because it was having a causal masked passed to it for the longest time before I caught it a month ago)
|
2024-12-08 14:52:47 -06:00 |
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5d80a2d0d4
|
fixed NAR-len issues with non-english maybe (langs weren't being passed), added interface to inference in batches through tts.batched_inference (no support for rolling context/prefixes because there's no way to do that), demo page uses batched inferencing now
|
2024-12-07 19:21:05 -06:00 |
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61ed662856
|
ACTUALLY actually fix KD-loss (the -inf in the logits was caused by cringecode)
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2024-12-07 12:31:54 -06:00 |
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34a66e1052
|
agnostified KD
|
2024-12-06 23:53:46 -06:00 |
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953d3eb030
|
ugh
|
2024-12-06 22:35:30 -06:00 |
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42fafbaaca
|
actually fixed knowledge distillation because of errant -inf logits causing problems and needed to be filtered (and splitting text language / output audio language because it helps)
|
2024-12-06 21:55:20 -06:00 |
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23d402bf01
|
added knowledge distillation in the trainer (sadly it is not agnostic because of the grave mistake of further processing the batch within the forward pass, so subsequent calls do not match......)
|
2024-12-05 23:05:52 -06:00 |
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93d27be539
|
rolling context finally (use last N utterances as the prefix for the next gen), option to split input text prompt by sentences instead of lines (or no splitting)
|
2024-12-04 20:31:44 -06:00 |
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9dff68c0c5
|
NAR-len tweaks (remasks a small amount of tokens per step, it seems to help with reducing the number of steps needed some of the time?, disable CFG for the first half to speed things up)
|
2024-12-04 09:30:29 -06:00 |
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cf97560e70
|
minimum CFG of 3 for NAR-len because it seems the model will auto-default to NAR-len now
|
2024-12-03 19:40:05 -06:00 |
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ca31da0a95
|
sageattn (forgot to bother with testing this the other day, seems ifne)
|
2024-12-03 15:14:57 -06:00 |
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|
84a05acb6d
|
touch ups in docs
|
2024-12-02 19:10:42 -06:00 |
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dcaf38b359
|
fixed training tqdm being stubborn
|
2024-11-23 09:45:23 -06:00 |
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41d7c30ea5
|
added much cleaner non-causal mask generation
|
2024-11-22 19:43:32 -06:00 |
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c99a74e834
|
actually generate a causal mask because it seems sometimes it does not actually generate one because it makes assumptions
|
2024-11-22 18:30:24 -06:00 |
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ccee5fc11c
|
that was actually all pointless since sdpa always had an attention mask fed to it and does not need is_causal to implicitly generate one
|
2024-11-22 16:51:50 -06:00 |
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4aa685e749
|
what has science done
|
2024-11-22 16:45:40 -06:00 |
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147219a5e0
|
huge oversight in the attention masking......... (i realized I have not been providing a non-causal mask to non-causal tasks)
|
2024-11-22 13:44:43 -06:00 |
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24d888c47c
|
temporarily dropping support for xformers because it's breaking when using an attention mask (which i dont remember commenting it out when being passed), default to not use wandb because it's being a pain when doing tests and not actual sessionsS)
|
2024-11-22 11:29:12 -06:00 |
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|
8aafae91fd
|
dont use timeembedding
|
2024-11-21 23:14:52 -06:00 |
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|
2cef97e43f
|
cleanup
|
2024-11-21 23:08:43 -06:00 |
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|
67f7bad168
|
added mixed modality AR+NAR-len to generate a short prefix through the AR, then inference with said prefix through the NAR-len (need to experiment with it more to ensure that the masked off tokens are the only tokens getting updated)
|
2024-11-20 14:22:12 -06:00 |
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b1369e7824
|
better modality selection (pick AR+NAR by default for the ar+nar model, pick NAR-len by default for the nar-len model), lowered default CFG because it makes the AR+NAR output sped up (but can't be too low since it's required for the NAR-len)
|
2024-11-19 18:51:17 -06:00 |
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190a917b3e
|
I did it.
|
2024-11-19 12:24:33 -06:00 |
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0e621354e7
|
cleaned up classifier-free guidance logit processing (in order to try and cope with a bad nar-len model)
|
2024-11-19 10:30:05 -06:00 |
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|
5ba80686e1
|
two weeks of agony concludes
|
2024-11-18 21:29:28 -06:00 |
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|
2b29790173
|
oops
|
2024-11-18 14:12:26 -06:00 |
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|
6cfdf94bf9
|
swap priority to use nar-len if available, added notes
|
2024-11-18 09:40:04 -06:00 |
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069b27570f
|
set option to set training masking ratio (I don't think for tts a fixed masking ratio is beneficial since the magic of the AR+NAR is being able to still reference the prior sequence of tokens for predicting things)
|
2024-11-17 17:04:07 -06:00 |
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88d840218d
|
default set cfg strength to 3.0 since the reference model is updated
|
2024-11-17 10:23:40 -06:00 |
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|
|
a3e1fa3518
|
ugh
|
2024-11-17 09:28:33 -06:00 |
|
|
|
23fdba0c98
|
tweaks and changes
|
2024-11-16 15:49:06 -06:00 |
|
|
|
2fbeacfe92
|
ugh
|
2024-11-14 22:18:33 -06:00 |
|
|
|
39096f8ff3
|
redid loss calculation to be cleaner, and position ID generation, and other things (I might need to train the NAR-len from scratch and not resume from an existing checkpoint.........)
|
2024-11-14 22:17:47 -06:00 |
|
|
|
e412e98125
|
ugh
|
2024-11-14 07:34:22 -06:00 |
|
|
|
c00fc18b62
|
actually use the right embedding for nar-len
|
2024-11-13 18:04:04 -06:00 |
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|
|
3ea8a610d6
|
fix STT
|
2024-11-13 14:27:15 -06:00 |
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|
910033343c
|
overhauled how the right resp level / classifier gets picked to avoid cringemath
|
2024-11-13 13:31:17 -06:00 |
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|
269648605e
|
move NAR-len rvq level 0 to separate embedding
|
2024-11-13 11:38:58 -06:00 |
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|
be83ddabaa
|
better causal-ness for split loss calc, and also do masking for NAR-len for it
|
2024-11-13 10:17:52 -06:00 |
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|
|
6b76419123
|
ugh
|
2024-11-13 09:54:20 -06:00 |
|
|
|
ad7cfffc00
|
NAR-len RVQ-0 was being trained causally.............
|
2024-11-13 09:43:50 -06:00 |
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|
8286aa54c8
|
do not pass timestep token/embedding since it doesn't seem to matter at all after all, fixed training masking rate to 80% because a paper said so
|
2024-11-13 09:07:10 -06:00 |
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|
0f2584eba7
|
new meme sampler PogChamp new meme sampler PogChamp (it sort of helps?)
|
2024-11-12 22:30:09 -06:00 |
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|
|
663f07038d
|
haha... (do not create a token dropout/noise mask when not training (this sadly didnt fix NAR-len output))
|
2024-11-12 16:41:58 -06:00 |
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|
|
b09328069e
|
actually do CFG sampling for base AR+NAR tasks
|
2024-11-12 13:42:39 -06:00 |
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|
|
2495a7ef67
|
Fixed STT in the web UI
|
2024-11-12 12:49:53 -06:00 |
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|
|
8927bad7bc
|
actually fixed rep pen (for ar and nar, it seems to help with nar unmasking)
|
2024-11-11 21:40:19 -06:00 |
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|
|
b1f4db39c8
|
threw in CFG sampling for normal model as well to experiment with
|
2024-11-11 20:27:38 -06:00 |
|
|
|
2f56696506
|
overhauled inference/sampler kwargs to stop being a bloated mess
|
2024-11-11 20:21:16 -06:00 |
|
|
|
a748e223ce
|
tweaks
|
2024-11-11 12:40:41 -06:00 |
|
|
|
48490757da
|
fixes
|
2024-11-10 20:37:50 -06:00 |
|
|
|
9def34cd66
|
lol
|
2024-11-10 12:48:41 -06:00 |
|
|
|
9cb0b6901b
|
unified nar.py into ar_nar.py
|
2024-11-10 12:19:48 -06:00 |
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|
a9d2faf2d7
|
all I can do now until I wait for the model to (re)train for pure NAR
|
2024-11-09 22:57:34 -06:00 |
|
|
|
ad7e290a5e
|
ugh (ROCm seems to silently clamp any token value >= logits.shape[-1] for loss calculation, while cuda will throw an assert, making it hard to find this dumb fuckup)
|
2024-11-09 19:40:02 -06:00 |
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|
943fe70c10
|
I don't know why this fixes an assert thrown but it does
|
2024-11-09 19:04:13 -06:00 |
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