Commit Graph

116 Commits

Author SHA1 Message Date
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
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
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
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
mrq
934672252b feverish cleanup 2024-06-03 21:28:49 -05:00
mrq
7feeb944a0 probably insane with even entertaining going this route 2024-06-03 20:26:27 -05:00
mrq
b482ca19ff added model config option to set KV head count for MQA/GQA instead of MHA for llama-based models (i think its very negligible both ways on such a small model size) 2024-05-31 19:32:37 -05:00
mrq
e15c6c74c3 correctness 2024-05-30 20:50:45 -05:00
mrq
da473295b7 better way to compute per-segment losses 2024-05-28 19:29:54 -05:00
mrq
6c49ad06a3 forgot to reinclude mult by loss factors 2024-05-27 20:40:21 -05:00
mrq
b82f0d5c0c finally nailed the issue that caused logging to break on one machine but not another (bitnet includes zetascale which is a parasite that will break logging) 2024-05-27 19:47:58 -05:00
mrq
c0ac84c795 uh 2024-05-27 19:05:56 -05:00
mrq
197d517181 ugh 2024-05-27 17:09:35 -05:00
mrq
5af6f41c94 added loss calcs against prom (requires the right settings for not shit results, disabled by default) 2024-05-27 08:43:00 -05:00
mrq
458b95d196 added option to split between text loss and audio loss (to-do: document this better), because it may or may not be a problem with LLaMA-backed models because my loss hovers around 3.9 / 56% accuracy despite sounding decent at the moment 2024-05-19 11:23:56 -05:00
mrq
917eeb40d2 ughhh 2024-05-12 08:22:39 -05:00
mrq
9910c75d5a checkpointing for bitnet impl 2024-05-12 07:52:54 -05:00
mrq
14709ac67f ughh 2024-05-12 07:30:59 -05:00
mrq
a755eb3c62 ugh 2024-05-11 17:34:45 -05:00
mrq
88e9b9caff local ddp fix 2024-05-11 17:29:01 -05:00
mrq
3337c69e5a leverage between xformers and torch.backends.cuda.sdp_kernel for attention 2024-05-11 17:14:05 -05:00
mrq
d33c7bb7cf ugh 2024-05-11 16:47:19 -05:00
mrq
2109712e5b resolve deprecation warning that doesn't show on my old training rig but does on my new one 2024-05-09 23:25:44 -05:00
mrq
1547de5020 haha... 2024-05-09 23:15:52 -05:00
mrq
0d5d545a40 crammed in DAdaptation (doesn't seem worth it) and ScheduleFree (forgot I wanted to weeks ago, seems promising), optimization wrapper cleanup, test trainer changes, etc. 2024-05-09 20:28:20 -05:00
mrq
33b7f81b94 small cleanups 2024-05-04 22:37:22 -05:00
mrq
253441b750 forgot to disable verbose flag 2024-05-04 13:13:52 -05:00
mrq
3dca1125f5 implemented xformers in HF's Llama (because theres no flash attention for Volta cards) 2024-05-04 13:07:45 -05:00
mrq
ffa200eec7 added option to specify frames per second for the given audio representation (Encodec is 75Hz, DAC is 41Hz (at 24K sources)) 2024-05-04 12:05:41 -05:00
mrq
b5d1456a09 backwards compat for my shitty old weights (was testing if disabling AudioEmbedding summing magically made things better (it did not)) 2024-04-29 22:14:01 -05:00
mrq
5120ffdda7 god it would be nice to know the best way to handle audio embeddings, because I genuinely don't know without skimming through papers or devoting X amount of GPU hours in training 2024-04-29 18:24:05 -05:00