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63cc9cf37a
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added compat flags for torchscale because the maintainer for torchscale broke compat for existing models
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2023-10-05 16:39:46 -05:00 |
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153f8b293c
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added min-x and min-y arguments to plot.py, helper script to download from my existing checkpoint
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2023-10-04 19:41:37 -05:00 |
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d12877ee09
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added option to set probability of selecting the AR during training under a monolithic AR+NAR, added some more to-dos while I have them in mind
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2023-10-02 16:52:42 -05:00 |
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c0b25541e3
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restructured some things with the model to remove dead weights
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2023-09-20 19:10:59 -05:00 |
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d07c63b9d8
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unified more things with training the AR+NAR monolothic model
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2023-09-12 15:54:41 -05:00 |
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40ef34e1ca
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this embedding class definitely works, and migrating from the previous embedding weights seems to work.
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2023-09-11 14:13:42 -05:00 |
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671dca88ee
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throw error when no reference audio is provided in the web UI because someone keeps doing that in the HF space
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2023-09-10 15:50:50 -05:00 |
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c74fe2f718
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tweaks to web UI
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2023-09-09 22:27:20 -05:00 |
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f69aad9c65
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some day I'll get it right
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2023-09-08 15:36:26 -05:00 |
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8837bc34d7
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added option to specify parameters to freeze per-model in YAML (because I need to see about committing atrocities with convering an AR into an AR+NAR)
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2023-09-07 18:19:51 -05:00 |
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c47fc3274e
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added backwards compat flag
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2023-09-07 17:12:17 -05:00 |
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e7a67410d1
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oops
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2023-09-07 09:14:03 -05:00 |
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100ca6b7d0
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added option to use SGD optimizer through the YAML, added option to pass in additional optimizer parameters through the YAML, added experimental unified AR+NAR model (does not seem fruitful in testing)
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2023-09-06 18:58:35 -05:00 |
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451726fdd5
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added ability to disable activation checkpointing through the YAML (it is very VRAM intensive at double layer size)
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2023-09-05 15:38:21 -05:00 |
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2f9cd0842f
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merged dedicated interleaved AR code with the normal AR code
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2023-09-03 22:46:08 -05:00 |
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8a6c203277
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added per-speaker samplers
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2023-09-03 21:27:13 -05:00 |
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57db3ccfa8
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shuffled VALL-E continuous as a task tts-c instead, logic fixes for it
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2023-09-02 12:23:40 -05:00 |
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2f06166ddd
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cleanups
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2023-09-01 21:33:51 -05:00 |
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e40c0d34a0
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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
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2023-09-01 20:58:29 -05:00 |
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2bc2d08b09
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(need to verify) added modifying model size and config bool to align with VALL-E continuous' methodology
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2023-09-01 17:19:34 -05:00 |
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87c4bfedba
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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)
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2023-08-27 12:26:12 -05:00 |
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165a1154e0
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Undo naive=False test flag, this shouldn't have made its way in
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2023-08-26 22:00:43 -05:00 |
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78378ed1ce
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overhauled dataloading code to be marginally faster, mostly cleaned up, and can leverage a metadata json to help things out
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2023-08-26 19:53:23 -05:00 |
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00ad4af651
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updated draconian requirement for espeak-ng to be installed and the env var set to the dll for Windows
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2023-08-24 14:57:01 -05:00 |
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4585824cd3
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tweaks, including exporting on save/quit
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2023-08-23 16:43:03 -05:00 |
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d106598403
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do not utilize diskcache if a config yaml is not loaded
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2023-08-23 11:02:15 -05:00 |
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7b1b82e0e5
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inferencing cleanup
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2023-08-20 21:36:02 -05:00 |
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736c077282
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ops
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2023-08-20 13:42:18 -05:00 |
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2d1a9f10c0
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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)
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2023-08-19 15:06:33 -05:00 |
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f7f6d3bf6d
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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'
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2023-08-19 09:50:07 -05:00 |
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8f42c578c9
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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
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2023-08-19 00:16:08 -05:00 |
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ae9d38aa31
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forgot to have it pull from specified noise to the hdf5 dataset
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2023-08-18 23:57:07 -05:00 |
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77292c42f9
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tested the training preparation for tasks ns, sr, and tse (I don't expect it to go well with only 2 RVQ bins)
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2023-08-18 23:55:40 -05:00 |
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bbb0563b3d
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pseudocode polyfill stub some other flavor of working on adding the tasks
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2023-08-18 22:22:13 -05:00 |
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fb4e816823
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oops
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2023-08-18 21:11:19 -05:00 |
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2a71486cb6
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preparing for SpeechX extensions
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2023-08-18 20:58:07 -05:00 |
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ced31fd9b7
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removed the sampler as it's very misleading
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2023-08-18 14:47:48 -05:00 |
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ee58db746f
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actually make the evaluation dataset shuffled for sample_type=speaker
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2023-08-17 15:04:45 -05:00 |
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d7152fc7b9
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added pruning of old checkpoints if specified (cfg.trainer.keep_last_checkpoints)
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2023-08-16 20:12:12 -05:00 |
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44c08d828e
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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
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2023-08-16 19:39:21 -05:00 |
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1e3e1d9315
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tweaks
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2023-08-15 21:58:16 -05:00 |
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13571380be
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made exporter make more sense
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2023-08-13 22:56:28 -05:00 |
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d7deaf6def
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distributed training works now (hopefully)
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2023-08-13 22:07:45 -05:00 |
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d89568a96e
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some fixes for the local framework
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2023-08-05 03:22:15 +00:00 |
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5970f254e3
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some fixes for the local framework
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2023-08-05 02:17:30 +00:00 |
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608c1970eb
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ops
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2023-08-03 20:36:19 -05:00 |
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c85101403f
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big cleanup
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2023-08-03 20:26:36 -05:00 |
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f6597e2dfe
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adjustments
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2023-08-02 18:36:26 -05:00 |
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bf8cedc9dd
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Rewrite init
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2023-08-02 21:53:35 +00:00 |
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