Commit Graph

97 Commits

Author SHA1 Message Date
mrq
769f67dcfe actually fix validation of phonemes in the symmap 2024-09-21 12:19:34 -05:00
mrq
b5bec0c9ce oops, turns out these are not split by speaker names already........ (also added sampling the dataset in the webui for easy viewing) 2024-09-18 20:19:46 -05:00
mrq
84647f588a more tweaks 2024-09-18 16:43:57 -05:00
mrq
ebac1db16c maybe final tweaks, I really needed to unify my json read/write and orjson is proven to be fast enough for me to try and rely on it more 2024-09-17 22:57:04 -05:00
mrq
a9fbe81f98 oops 2024-09-17 15:25:12 -05:00
mrq
94cf81d38c tweak 2024-09-05 23:21:18 -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
3a65cc4b22 fix issue with sft and shared tensors... 2024-08-04 19:56:21 -05:00
mrq
2cb465018b implicitly load either normal pickled weights or safetensors on loading the model 2024-08-03 23:34:18 -05:00
mrq
c09133d00f added safetensors support (with metadata) and feed whatever torch.load/torch.save into it 2024-08-03 23:15:20 -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
ab673e0426 add cap for NAR-len training, to avoid any weird cases in early training where it'll just mess up and generate long lengths 2024-08-03 21:00:32 -05:00
mrq
4d2b88b164 throw exception if training, but no model is set to train (because i ran into this wondering what the hell was happening) 2024-08-03 20:51:23 -05:00
mrq
7a77978096 oversight with using resize_modules 2024-08-02 20:28:49 -05:00
mrq
808a79ebaf oops 2024-08-01 22:56:04 -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
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
e33c4b0cb1 oops 2024-07-22 19:38:39 -05:00
mrq
75b04686f8 added prom-less training / inferencing, some other things 2024-07-22 19:36:07 -05:00
mrq
c2b8035e74 oops, kept forgetting to actually pass in lang/tone tokens (despite not really using these at the moment) 2024-07-18 14:18:34 -05:00
mrq
312a8e3ead add shuffle to samplers that can support it 2024-06-30 11:36:46 -05:00
mrq
2808f881c8 cleaned up subjugated audio embedding into a flag, flag can also have it include the original, underlying embedding as well (it seems to do better when set to inclusive) 2024-06-29 21:46:35 -05:00
mrq
c4dd523b6f change from chunk-slicing paths for distributed dataloader to instead interleave 2024-06-29 10:10:35 -05:00
mrq
dd40463803 limit eval size because the training batch size seems to be used for the eval dataloader, somehow (bandaid) 2024-06-29 09:11:28 -05:00
mrq
83075c1505 sort duration buckets to ensure that paths sorted-by-duration are actually sorted by duration (because i didnt know that python dicts can have non-strings as keys), added batching samples based on total duration to ensure best training throughput 2024-06-28 22:28:54 -05:00
mrq
8fffb94964 backport fix from tortoise_tts with local trainer + loading state when training lora 2024-06-25 13:41:29 -05:00
mrq
726a4b613f naive, rudimentary DeepSpeed support (just live with the LoRA weights living with the original weights, they can be split later) 2024-06-17 13:17:24 -05:00
mrq
31f71fa134 sampler update (some brainworm just never actually had a sampler for sample_type=path) 2024-06-14 16:55:40 -05:00
mrq
132a02c48b sanity cleanup, backup config yaml for each log file 2024-06-09 11:22:52 -05:00
mrq
4ade2b60ee ugh 2024-06-06 21:57:11 -05:00
mrq
fcac9503e2 cleanup 2024-06-06 13:08:02 -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
c1fcd889d5 reverted automatically disabling split loss calc, since it seems that it's actually cacling loss on prom causes the oddities, maybe 2024-06-01 12:34:59 -05:00
mrq
8cf176ab46 ugh 2024-06-01 10:46:42 -05:00
mrq
d0ebce6bac ugh 2024-06-01 10:30:13 -05:00
mrq
39bc019142 actually save per-rank sampler states 2024-06-01 09:46:32 -05:00
mrq
85f9684720 some cleanup 2024-05-25 17:46:52 -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
0b6499601b sanitizing 2024-05-11 16:31:05 -05:00
mrq
bd0a36ba8d I swear I keep seeing tqdm flicker back a number 2024-05-10 18:36:01 -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
277dcec484 apparently I got an error for trying to serialize an errant tensor that made its way into the json, this could be remedied easily with recursively traversing the dict and coercing any objects to primitives, but I'm tired and I just want to start training and nap 2024-05-04 12:33:43 -05:00
mrq
c494894261 simple DDP wrapper (for my NVlink test) 2024-05-04 11:48:26 -05:00
mrq
a7b43b98b5 renamed cfg.bitsandbytes to cfg.optimizations (and having it serve as cfg.optimizations.bitsandbytes) 2024-05-02 20:08:59 -05:00
mrq
467fa1c5ee wrapper fixes 2024-04-16 10:19:02 -05:00