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d343bde09b
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residual_in_fp32=False for mamba arch backends because it breaks the classifier (output projection / lm head / what-have-you) under AMP
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2024-06-15 12:08:03 -05:00 |
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ccb14c06ef
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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)
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2024-06-14 19:42:17 -05:00 |
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83eab4fa59
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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
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2024-06-13 20:08:22 -05:00 |
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26da24fd8d
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mamba updated to fix that pesky NaN error during training
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2024-06-13 12:38:33 -05:00 |
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cca542a4c0
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ugh
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2024-06-11 23:59:28 -05:00 |
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65a8960305
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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)
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2024-06-11 22:28:59 -05:00 |
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a7a6e0ac76
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validated that inferencing works, changed some defaults (NAR benefits from greedy sampling)
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2024-06-09 17:11:38 -05:00 |
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80f9530840
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ugh
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2024-06-09 01:43:44 -05:00 |
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5c732b72ee
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ugh
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2024-06-08 20:34:00 -05:00 |
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8d068fa3f9
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reticulating splines
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2024-06-08 20:30:15 -05:00 |
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b072f9b96b
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fixes
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2024-06-08 16:01:34 -05:00 |
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58fb0a84db
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added experimental NAR only model (inferences text length, need more experimenting), AudioEmbedding logic cleanup (I still think it's being done wrong)
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2024-06-08 15:42:02 -05:00 |
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7d6fff24f9
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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)
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2024-06-07 20:46:22 -05:00 |
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b0158a61d5
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fixed some logic errors with training (grabbing wrong quant level...)
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2024-06-07 20:34:36 -05:00 |
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eafa622be2
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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)
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2024-06-07 20:29:25 -05:00 |
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a5c90348d9
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head hurt
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2024-06-06 20:51:31 -05:00 |
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516b0894d7
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m
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2024-06-06 19:41:26 -05:00 |
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ee25d2e62e
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removed the need to supply targ_list + different AudioEmbedding + other things
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2024-06-06 18:52:41 -05:00 |
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b2194b859a
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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)
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2024-06-06 09:48:43 -05:00 |
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b05a905b95
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ugh
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2024-06-05 21:02:05 -05:00 |
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4073656293
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oops
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2024-06-05 20:53:10 -05:00 |
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ff6fe6f1bc
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cleanup
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2024-06-05 20:30:43 -05:00 |
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880b4ecd1b
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cleanup, putting some thoughts in comments before I forget about them
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2024-06-05 19:50:06 -05:00 |
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3cfc8a96bb
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oops
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2024-06-05 10:30:04 -05:00 |
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48cd1054f9
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madness
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2024-06-04 23:48:51 -05:00 |
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9e3f2e300f
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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)
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2024-06-04 23:23:31 -05:00 |
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e0886c5a78
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re-added mamba as a possible non-experimental arch backend (test trainer will set it as AR only, doing any NAR tasks lobotomizes it)
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2024-06-04 22:41:22 -05:00 |
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934672252b
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feverish cleanup
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2024-06-03 21:28:49 -05:00 |
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7feeb944a0
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probably insane with even entertaining going this route
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2024-06-03 20:26:27 -05:00 |
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b482ca19ff
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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)
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2024-05-31 19:32:37 -05:00 |
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e15c6c74c3
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correctness
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2024-05-30 20:50:45 -05:00 |
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da473295b7
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better way to compute per-segment losses
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2024-05-28 19:29:54 -05:00 |
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6c49ad06a3
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forgot to reinclude mult by loss factors
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2024-05-27 20:40:21 -05:00 |
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b82f0d5c0c
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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)
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2024-05-27 19:47:58 -05:00 |
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c0ac84c795
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uh
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2024-05-27 19:05:56 -05:00 |
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197d517181
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ugh
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2024-05-27 17:09:35 -05:00 |
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5af6f41c94
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added loss calcs against prom (requires the right settings for not shit results, disabled by default)
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2024-05-27 08:43:00 -05:00 |
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458b95d196
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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
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2024-05-19 11:23:56 -05:00 |
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917eeb40d2
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ughhh
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2024-05-12 08:22:39 -05:00 |
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9910c75d5a
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checkpointing for bitnet impl
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2024-05-12 07:52:54 -05:00 |
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14709ac67f
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ughh
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2024-05-12 07:30:59 -05:00 |
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a755eb3c62
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ugh
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2024-05-11 17:34:45 -05:00 |
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88e9b9caff
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local ddp fix
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2024-05-11 17:29:01 -05:00 |
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3337c69e5a
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leverage between xformers and torch.backends.cuda.sdp_kernel for attention
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2024-05-11 17:14:05 -05:00 |
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d33c7bb7cf
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ugh
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2024-05-11 16:47:19 -05:00 |
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2109712e5b
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resolve deprecation warning that doesn't show on my old training rig but does on my new one
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2024-05-09 23:25:44 -05:00 |
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1547de5020
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haha...
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2024-05-09 23:15:52 -05:00 |
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0d5d545a40
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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.
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2024-05-09 20:28:20 -05:00 |
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33b7f81b94
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small cleanups
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2024-05-04 22:37:22 -05:00 |
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253441b750
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forgot to disable verbose flag
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2024-05-04 13:13:52 -05:00 |
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