Commit Graph

244 Commits

Author SHA1 Message Date
mrq
31e8b7edb8 tweaks and fixes for lora stuffs 2024-09-08 18:05:21 -05:00
mrq
54203c059d validated rep pen for STT (sometimes needed to wrangle the model) 2024-09-08 08:30:30 -05:00
mrq
6a967f91b9 oops 2024-09-07 22:13:49 -05:00
mrq
4bd9bb39c8 webui for STT (still need to bake the model to handle it better, a few hours so far has it generate what looks like a normal transcription but does not correlate to the audio right now) 2024-09-06 15:13:04 -05:00
mrq
d33a906119 cleanup for AR_NAR inferencing to allow both TTS and STT tasks simultaneously (need to have training eval do this to though) 2024-09-06 14:30:12 -05:00
mrq
341e19162b fixes, again 2024-09-06 11:41:41 -05:00
mrq
94cf81d38c tweak 2024-09-05 23:21:18 -05:00
mrq
413097f5f7 fixes 2024-09-05 21:42:59 -05:00
mrq
54547b74d8 experimental implementation of STT (need to actually test on a model, test trainer seems to work) 2024-09-05 20:43:20 -05:00
mrq
168e203942 ugh 2024-08-30 14:39:07 -05:00
mrq
685f4faec0 ugh 2024-08-30 10:46:26 -05:00
mrq
32287710a2 moved prints to use logger, edited readme (fused_attn doesnt seem stable for training) 2024-08-29 13:27:16 -05:00
mrq
d423bc03c2 fixed attentions for MoE 2024-08-27 17:02:42 -05:00
mrq
b7b99a25f1 added ability to specify attention backend for CLI and webui (because im tired of editing the yaml) 2024-08-26 19:33:51 -05:00
mrq
0d706ec6a1 added fused_attn (triton-based fused attention) and simply just query for flash_attn under rocm 2024-08-26 19:13:34 -05:00
mrq
6b0891448c pain (some shit to try and get some flash attention for ROCm (gfx1100) through triton fused attention but no good) 2024-08-25 20:07:27 -05:00
mrq
40e1799adc fixed xformers and flash_attn to actually work now 2024-08-19 01:03:35 -05:00
mrq
29c35528e5 the sooner I accept there's no FA for V100s the sooner I'll go to bed 2024-08-18 23:54:33 -05:00
mrq
d636edd3a2 added flash_attn LlamaAttention (including flash_attn==1.0.9) 2024-08-18 20:51:14 -05:00
mrq
2a1794c084 ughghghhhh 2024-08-09 21:15:01 -05:00
mrq
ed373957e2 maybe not 2024-08-09 11:38:08 -05:00
mrq
d04f6911b4 oops 2024-08-08 19:38:55 -05:00
mrq
949339a3fa do not include SDPA attention if there's no available SDPA backends 2024-08-06 20:42:39 -05:00
mrq
7cdfa3dc0c updated process_datasets.py, added argparsing so I can mostly stop manually editing things, and some other cleanup 2024-08-05 15:59:25 -05:00
mrq
debcc93e7e add adapted MixtralAttention for when I make a bad decision to actually train a MoE 2024-08-04 22:03:22 -05:00
mrq
10aaf840e7 added export option to convert Llama to MixtralMoE for another dumb experiment 2024-08-04 20:25:06 -05:00
mrq
3a65cc4b22 fix issue with sft and shared tensors... 2024-08-04 19:56:21 -05:00
mrq
23f3b56fda oops 2024-08-04 08:18:57 -05:00
mrq
6a733eb2ed changed torch.Tensor().to(device, dtype) to just torch.tensor(..., device, dtype) because it's been bothering my autism that I'm creating tensors then converting rather than creating with the right device/dtype, some 'optimization' to compile the model but it doesnt seem to do anything useful 2024-08-03 22:10:21 -05:00
mrq
d0a5c7eca2 more coping with the NAR len 2024-08-03 20:23:36 -05:00
mrq
11fa3da665 some cleanup, fixed the wrapper attention to explicitly use other sdpa backends 2024-08-03 19:51:00 -05:00
mrq
9564ecda43 wrapper attention class for other sdpa backends + xformers seems to have broke... 2024-08-03 15:12:11 -05:00
mrq
9e1989be1b tweaked initial NAR pass's initial token embeddings to use a different value, or osmething 2024-08-03 09:01:37 -05:00
mrq
26f74c5739 somehow fixed non-unified position IDs for the NAR-len 2024-08-03 08:43:42 -05:00
mrq
66407e5bdb tweaks for the NAR-len model, maybe 2024-08-03 08:40:39 -05:00
mrq
97c5241bef fixes, throw an exception when using NAR only model with non-unified position IDs, since for some reason it outputs garbage for the NAR 2024-08-02 22:25:49 -05:00
mrq
443422ecb5 ugh, finally got some form of offloading working (need to test if it works on different GPUs, but GPU and CPU offloading seems to work in the test trainer) 2024-08-01 22:43:39 -05:00
mrq
c9ec6b28ef it actually wasn't working because Engines.__init__() automatically moves the entire module to the requested device, which was being called after offloading the model in the test trainer (and it seems I cant do it without injecting a bunch of shit in modeling_llama.py) 2024-08-01 20:56:28 -05:00
mrq
b4c895114c naive model offloading support (handles automatically splitting parts of the model to requested device per memory constraints, either inferred or requested in the yaml, input tensors are automatically migrated to the right device, it SEEMS to work for training under the test trainer when split between GPU and CPU) (this was specifically only because that Flux imagegen model released so I can test it there) 2024-08-01 20:12:06 -05:00
mrq
387358bc8a fixes for the NAR-len model, and documentation some config options, and a better way to handle resizing modules on state_dict load 2024-07-31 20:35:09 -05:00
mrq
07f8e2ad06 added option to set the causal size (how many tokens to sample per AR step), but requires the model to be trained for this (which explains why recurrent chunk sampling just doesn't work for the retnet tests, obvious in hindsight) 2024-07-30 20:53:51 -05:00
mrq
ebf848d249 possible speedup for samplers that require a list of previous tokens (the DRY sampler made me realize that I should copy the tolist() thing from the rep pen sampler for everything else) 2024-07-29 20:23:26 -05:00
mrq
55b0121b1a trying (and failing) to nail a weird regression in fancier attentions 2024-07-29 19:53:37 -05:00
mrq
c2f5b916fc added what I think is DRY sampling 2024-07-29 19:15:07 -05:00
mrq
ce8bb1e4f7 sanity cleanups with weird off-by-one-ness, cleaned up and validated vall_e.models.experimental works again 2024-07-27 15:36:05 -05:00
mrq
06e948aec1 suppress warning on exit about distributed not being cleaned up (because I updated my system) 2024-07-25 16:50:47 -05:00
mrq
1acb0e9c84 added experimental training setting to perform token dropout to MAYBE compensate for errors from the preceding RVQ level (two types: token error offset, token dropout embedding replace) 2024-07-24 19:35:17 -05:00
mrq
188d116222 some weird fixes for an equally weird regression with LoRA loading 2024-07-22 20:47:24 -05:00
mrq
75b04686f8 added prom-less training / inferencing, some other things 2024-07-22 19:36:07 -05:00
mrq
e19aa643a6 cleaned up demo page creation, added option to pass in RVQ level sampling distribution for training 2024-07-21 19:12:03 -05:00