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d6cd848c32
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goodbye nvidia/audio-codec-44khz, crossed fingers for DAC again
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2025-04-06 21:05:29 -05:00 |
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1e22519d94
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diagnosed both hf/llama.cpp versions to probably just being a faulty export method (to-do: migrate vall_e.models.base to vall_e.export --hf)
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2025-04-05 22:05:39 -05:00 |
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c34763769a
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ugh
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2025-04-05 18:58:25 -05:00 |
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b6692ce3de
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ugh
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2025-04-05 18:20:46 -05:00 |
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4a909ceff8
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temp fix for vall_e.cpp demask scoring regression
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2025-04-05 11:04:26 -05:00 |
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44260f7445
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tweaks
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2025-04-05 10:27:07 -05:00 |
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0ede3bfc12
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updated vall_e.cpp, but i could have sworn it worked much better than this......
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2025-04-05 01:22:51 -05:00 |
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28d39ef962
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should not be working late
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2025-04-03 23:32:58 -05:00 |
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bfe70e9d56
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ugh
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2025-04-03 23:26:00 -05:00 |
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2e93438867
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reintroduced sampler_type = speaker because I think this might salvage the nemo model to have better speaker similarities
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2025-04-03 19:01:10 -05:00 |
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caad99ab78
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fix for bsz>1 because I forgot the old implementation implicitly handles this
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2025-04-02 17:17:37 -05:00 |
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068dbdb785
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ugh
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2025-04-02 17:05:16 -05:00 |
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0e995dbf2c
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is this my last cope (falling back to explicit duration prediction, as this regression just won't go away) (also the smaller model was lobotomized because of my ROCm setup having a botched SDPA for who knows why)
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2025-04-02 17:01:24 -05:00 |
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7a0956863d
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oops
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2025-03-31 21:11:43 -05:00 |
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a1184586ef
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should never have trusted mse_loss, it never works
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2025-03-31 20:59:13 -05:00 |
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99f251c768
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slight tweaks to condition-less NS/SR
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2025-03-30 10:37:40 -05:00 |
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478aea0e8c
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tweaks
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2025-03-28 19:49:54 -05:00 |
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6ae282e090
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re-added noise dataloader sampler whatever for the old implementation's other tasks that require it
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2025-03-28 15:07:06 -05:00 |
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90b3509404
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I'll just cope and say I cannot apply segmented attention masks to the smaller model as it's too trained on not doing it, and the regression came from dumb python aliasing rules
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2025-03-27 13:27:51 -05:00 |
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2fd82a7a22
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cannot get segmented mask to actually work without gradients exploding (need to find a different way to do duration prediction...)
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2025-03-27 00:51:41 -05:00 |
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4d777b5618
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add remark that segmented attention actually might be broken (for some reason this only emerged recently, need to investigate)
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2025-03-26 12:08:47 -05:00 |
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09e9438941
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ugh
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2025-03-25 23:24:01 -05:00 |
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8641c87611
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nothing could go wrong part 2 (reverted and rewrote commits since there was a nasty regression)
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2025-03-25 23:06:16 -05:00 |
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aa8b32d97e
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added more notes (although I could have sworn I have had more notes that i can't recall)
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2025-03-25 18:53:06 -05:00 |
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df5b870908
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added remark about not using sliding attention
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2025-03-22 12:44:34 -05:00 |
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02a8bcbe29
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fixed errant index error (although it makes me wonder if my segmented masking is still flawed)
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2025-03-21 23:41:34 -05:00 |
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d1d91295b3
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add segmented sliding attention, also found a bug with prom-less segments in the attention mask generation.........
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2025-03-21 19:05:49 -05:00 |
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589cfb0e18
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yuge speedup because of a dumb oversight
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2025-03-20 17:39:41 -05:00 |
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8068f24e35
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cleaned up parallel nar, i think it's slightly faster but even the smallest model is still slower than ar+nar-len-llama-8...
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2025-03-20 15:56:15 -05:00 |
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9a7458cf17
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fixed inferencing since I did delete the len_emb, some more notes on the model since it seems I just had bad experimental settings
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2025-03-19 22:41:48 -05:00 |
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61de653ad9
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now causal training should work again
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2025-03-19 14:20:19 -05:00 |
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85b9dd47c1
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ugh
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2025-03-19 13:31:50 -05:00 |
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81acd565b3
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re-enable these
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2025-03-18 20:59:33 -05:00 |
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5479d2eacc
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more tweaks to the new implementation (properly trim the len stuff to save some params, decoder to d_ffn expansion to 2 to maybe also make it faster, etc.)
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2025-03-18 19:34:37 -05:00 |
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9a8a8e3195
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off by one bateman
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2025-03-18 08:40:43 -05:00 |
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0280e72257
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ugh
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2025-03-17 21:49:45 -05:00 |
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b0dba9db07
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this may bite me in the ass
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2025-03-17 21:46:50 -05:00 |
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2dfef693c4
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comments for clarity
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2025-03-16 11:30:23 -05:00 |
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c5475ebc91
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another dataloader optimization
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2025-03-15 20:18:58 -05:00 |
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bee2688dea
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ugh
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2025-03-15 16:50:21 -05:00 |
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2053580838
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updated dataloader to hopefully reduce RAM usage
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2025-03-15 13:14:37 -05:00 |
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9cfbf94b1c
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config-ify the len_loss_factor
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2025-03-14 20:30:48 -05:00 |
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ca8cc15271
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more tweaks (vall_e.webui --yaml still breaks things, --model needs to deduce what audio backend now that im supporting other ones again // added easy top-sampler settings back for new implementation)
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2025-03-14 20:18:25 -05:00 |
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6ee505cffd
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fixed dac
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2025-03-12 23:17:27 -05:00 |
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ba5f3d19b4
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use the FSQ-targeted encoder/decodede whole-ly as it works for EnCodec too, as the RVQ-targeted encoder/decoder doesnt (and some notes)
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2025-03-12 22:47:19 -05:00 |
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2ccf1b5740
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actually do duration prediction
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2025-03-11 22:14:54 -05:00 |
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5c512717a6
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len prediction for new model (and remove logit normalization since it kills inferencing)
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2025-03-11 20:33:09 -05:00 |
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5f98543d4d
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ughh
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2025-03-10 21:18:57 -05:00 |
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8ac03aac8a
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ugh
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2025-03-10 21:14:56 -05:00 |
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5670fcb23f
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hopefully the final tweaks needed for this bastard of a model
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2025-03-10 20:59:11 -05:00 |
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