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dcaf38b359
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fixed training tqdm being stubborn
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2024-11-23 09:45:23 -06:00 |
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88d840218d
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default set cfg strength to 3.0 since the reference model is updated
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2024-11-17 10:23:40 -06:00 |
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29e45be0b4
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tweaks to bucket sampling
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2024-11-13 11:09:24 -06:00 |
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b2eca271a8
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ugh
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2024-11-13 10:35:44 -06:00 |
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ad7cfffc00
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NAR-len RVQ-0 was being trained causally.............
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2024-11-13 09:43:50 -06:00 |
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976ee87f6f
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resume iteration step in tqdm trainer, warn to logger if the sampler state dict was invalidated
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2024-11-13 09:09:28 -06:00 |
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0f2584eba7
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new meme sampler PogChamp new meme sampler PogChamp (it sort of helps?)
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2024-11-12 22:30:09 -06:00 |
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2f56696506
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overhauled inference/sampler kwargs to stop being a bloated mess
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2024-11-11 20:21:16 -06:00 |
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354f8e059d
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store dataset hash alongside state dict so it can be ignored if mismatched
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2024-11-11 18:16:56 -06:00 |
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f7b8b1e825
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dropped subtrain dataloader since its useless to duplicate
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2024-11-11 17:00:49 -06:00 |
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cf9df71f2c
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use homwbrewed caching system for dataloader paths / durations (I'm pretty sure I am now triggering OOM killers with my entire dataset used)
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2024-11-11 16:32:08 -06:00 |
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a9d2faf2d7
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all I can do now until I wait for the model to (re)train for pure NAR
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2024-11-09 22:57:34 -06:00 |
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8eb9a4056b
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modified default arguments (ar temp = 0 and rep pen = 1.125 seems to be stable, at least given the few things i tested), do not pass top k/top p/min p to NAR even though technically none of those things should matter when greedy sampling
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2024-10-22 18:12:39 -05:00 |
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fc8dfd8617
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made greedy AR sampling viable (and preferable), with caveats (per comment in vall_e.models.ar_nar)
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2024-10-18 16:55:00 -05:00 |
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75b90be325
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cleaned up unused config flags, allow less strict yaml by pruning missing keys, renamed some dataset configs to be more unified
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2024-10-17 17:06:48 -05:00 |
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a507b769a1
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sped up inferencing by not doing .tolist() for rep pen / length pen (and a bug fix in the web UI from prev commit)
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2024-10-04 22:18:20 -05:00 |
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769f67dcfe
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actually fix validation of phonemes in the symmap
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2024-09-21 12:19:34 -05:00 |
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b5bec0c9ce
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oops, turns out these are not split by speaker names already........ (also added sampling the dataset in the webui for easy viewing)
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2024-09-18 20:19:46 -05:00 |
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84647f588a
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more tweaks
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2024-09-18 16:43:57 -05:00 |
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ebac1db16c
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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
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2024-09-17 22:57:04 -05:00 |
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a9fbe81f98
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oops
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2024-09-17 15:25:12 -05:00 |
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94cf81d38c
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tweak
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2024-09-05 23:21:18 -05:00 |
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32287710a2
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moved prints to use logger, edited readme (fused_attn doesnt seem stable for training)
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2024-08-29 13:27:16 -05:00 |
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3a65cc4b22
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fix issue with sft and shared tensors...
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2024-08-04 19:56:21 -05:00 |
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2cb465018b
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implicitly load either normal pickled weights or safetensors on loading the model
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2024-08-03 23:34:18 -05:00 |
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c09133d00f
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added safetensors support (with metadata) and feed whatever torch.load/torch.save into it
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2024-08-03 23:15:20 -05:00 |
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6a733eb2ed
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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
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2024-08-03 22:10:21 -05:00 |
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ab673e0426
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add cap for NAR-len training, to avoid any weird cases in early training where it'll just mess up and generate long lengths
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2024-08-03 21:00:32 -05:00 |
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4d2b88b164
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throw exception if training, but no model is set to train (because i ran into this wondering what the hell was happening)
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2024-08-03 20:51:23 -05:00 |
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7a77978096
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oversight with using resize_modules
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2024-08-02 20:28:49 -05:00 |
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808a79ebaf
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oops
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2024-08-01 22:56:04 -05:00 |
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443422ecb5
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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)
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2024-08-01 22:43:39 -05:00 |
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c9ec6b28ef
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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)
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2024-08-01 20:56:28 -05:00 |
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b4c895114c
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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)
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2024-08-01 20:12:06 -05:00 |
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ce8bb1e4f7
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sanity cleanups with weird off-by-one-ness, cleaned up and validated vall_e.models.experimental works again
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2024-07-27 15:36:05 -05:00 |
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06e948aec1
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suppress warning on exit about distributed not being cleaned up (because I updated my system)
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2024-07-25 16:50:47 -05:00 |
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e33c4b0cb1
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oops
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2024-07-22 19:38:39 -05:00 |
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75b04686f8
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added prom-less training / inferencing, some other things
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2024-07-22 19:36:07 -05:00 |
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c2b8035e74
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oops, kept forgetting to actually pass in lang/tone tokens (despite not really using these at the moment)
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2024-07-18 14:18:34 -05:00 |
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312a8e3ead
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add shuffle to samplers that can support it
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2024-06-30 11:36:46 -05:00 |
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2808f881c8
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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)
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2024-06-29 21:46:35 -05:00 |
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c4dd523b6f
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change from chunk-slicing paths for distributed dataloader to instead interleave
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2024-06-29 10:10:35 -05:00 |
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dd40463803
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limit eval size because the training batch size seems to be used for the eval dataloader, somehow (bandaid)
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2024-06-29 09:11:28 -05:00 |
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83075c1505
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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
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2024-06-28 22:28:54 -05:00 |
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8fffb94964
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backport fix from tortoise_tts with local trainer + loading state when training lora
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2024-06-25 13:41:29 -05:00 |
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726a4b613f
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naive, rudimentary DeepSpeed support (just live with the LoRA weights living with the original weights, they can be split later)
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2024-06-17 13:17:24 -05:00 |
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31f71fa134
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sampler update (some brainworm just never actually had a sampler for sample_type=path)
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2024-06-14 16:55:40 -05:00 |
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132a02c48b
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sanity cleanup, backup config yaml for each log file
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2024-06-09 11:22:52 -05:00 |
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4ade2b60ee
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ugh
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2024-06-06 21:57:11 -05:00 |
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fcac9503e2
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cleanup
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2024-06-06 13:08:02 -05:00 |
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