|
e40c0d34a0
|
somewhat got recurrent forward working (it's as accurate as chunkwise forward: it's not accurate at all), added option to use AMP instead of blanket setting the weight's dtype
|
2023-09-01 20:58:29 -05:00 |
|
|
2bc2d08b09
|
(need to verify) added modifying model size and config bool to align with VALL-E continuous' methodology
|
2023-09-01 17:19:34 -05:00 |
|
|
87c4bfedba
|
added ability to mark models as disabled for training, and hotloading them for eval/validation (useful if training only one model, or training a model per GPU)
|
2023-08-27 12:26:12 -05:00 |
|
|
165a1154e0
|
Undo naive=False test flag, this shouldn't have made its way in
|
2023-08-26 22:00:43 -05:00 |
|
|
78378ed1ce
|
overhauled dataloading code to be marginally faster, mostly cleaned up, and can leverage a metadata json to help things out
|
2023-08-26 19:53:23 -05:00 |
|
|
00ad4af651
|
updated draconian requirement for espeak-ng to be installed and the env var set to the dll for Windows
|
2023-08-24 14:57:01 -05:00 |
|
|
4585824cd3
|
tweaks, including exporting on save/quit
|
2023-08-23 16:43:03 -05:00 |
|
|
d106598403
|
do not utilize diskcache if a config yaml is not loaded
|
2023-08-23 11:02:15 -05:00 |
|
|
7b1b82e0e5
|
inferencing cleanup
|
2023-08-20 21:36:02 -05:00 |
|
|
736c077282
|
ops
|
2023-08-20 13:42:18 -05:00 |
|
|
2d1a9f10c0
|
nightmare of spaghetti that might break compat; mechanism to increase RVQ bins of an existing model without retraining, keeps sampled proms/resps at max RVQ level and trim off excess levels according to what model receives them, some other things I already forgot (I really hope no one else has weights being baked right now)
|
2023-08-19 15:06:33 -05:00 |
|
|
f7f6d3bf6d
|
validated that SpeechX tasks cse and nse works, added a method to test each task by invoking python3 -m vall_e.data --action=tasks --tasks='sr,se,cse,nse'
|
2023-08-19 09:50:07 -05:00 |
|
|
8f42c578c9
|
setting up for allowing training for a partial amount of the speechx tasks (do NOT try this at home yet without a proper model, as performance is predecated on having a solid base vall-e model for the tasks
|
2023-08-19 00:16:08 -05:00 |
|
|
ae9d38aa31
|
forgot to have it pull from specified noise to the hdf5 dataset
|
2023-08-18 23:57:07 -05:00 |
|
|
77292c42f9
|
tested the training preparation for tasks ns, sr, and tse (I don't expect it to go well with only 2 RVQ bins)
|
2023-08-18 23:55:40 -05:00 |
|
|
bbb0563b3d
|
pseudocode polyfill stub some other flavor of working on adding the tasks
|
2023-08-18 22:22:13 -05:00 |
|
|
fb4e816823
|
oops
|
2023-08-18 21:11:19 -05:00 |
|
|
2a71486cb6
|
preparing for SpeechX extensions
|
2023-08-18 20:58:07 -05:00 |
|
|
ced31fd9b7
|
removed the sampler as it's very misleading
|
2023-08-18 14:47:48 -05:00 |
|
|
ee58db746f
|
actually make the evaluation dataset shuffled for sample_type=speaker
|
2023-08-17 15:04:45 -05:00 |
|
|
d7152fc7b9
|
added pruning of old checkpoints if specified (cfg.trainer.keep_last_checkpoints)
|
2023-08-16 20:12:12 -05:00 |
|
|
44c08d828e
|
added sample_type that samples from speakers to truly balance an epoch by speakers rather than the entire dataset and a sampler that tries to balance by speakers
|
2023-08-16 19:39:21 -05:00 |
|
|
1e3e1d9315
|
tweaks
|
2023-08-15 21:58:16 -05:00 |
|
|
13571380be
|
made exporter make more sense
|
2023-08-13 22:56:28 -05:00 |
|
|
d7deaf6def
|
distributed training works now (hopefully)
|
2023-08-13 22:07:45 -05:00 |
|
|
d89568a96e
|
some fixes for the local framework
|
2023-08-05 03:22:15 +00:00 |
|
|
5970f254e3
|
some fixes for the local framework
|
2023-08-05 02:17:30 +00:00 |
|
|
608c1970eb
|
ops
|
2023-08-03 20:36:19 -05:00 |
|
|
c85101403f
|
big cleanup
|
2023-08-03 20:26:36 -05:00 |
|
|
f6597e2dfe
|
adjustments
|
2023-08-02 18:36:26 -05:00 |
|
|
bf8cedc9dd
|
Rewrite init
|
2023-08-02 21:53:35 +00:00 |
|