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b922f35b6b
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added documentation on how these new sampling parameters are very iffy and you really need to know what you are doing to use them because this is audio generation and not text generation
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2023-09-08 20:43:36 -05:00 |
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14c78bae39
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added lots of sampling options (top-k/top-p, repetition penalty, length penalty)
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2023-09-08 20:30:54 -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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b2907ae7e0
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seems that my PromEmbedding/RespEmbedding doesn't actually work all that well, naively using dedicated MultiEmbeddings for AR/NAR in the monolithic model is the best way to go
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2023-09-08 01:03:24 -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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ab5134f385
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tweaks and fixes
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2023-09-07 17:08:38 -05:00 |
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b2c2dec291
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added homebrewed per-RVQ-bin embedding solutions
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2023-09-07 16:48:02 -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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712808494f
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added support for optional prodigy optimizer (https://github.com/konstmish/prodigy) although it consumes a lot more VRAM per parameter
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2023-09-06 20:33:16 -05:00 |
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7ce06432fd
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fixed the AR+NAR dual model, the resp_emb has to be split up (classifier might too)
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2023-09-06 19:33:39 -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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143aee7526
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removed dedicated interleaved AR code
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2023-09-03 22:47:03 -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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3a6bd50322
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haha
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2023-09-03 21:36:58 -05:00 |
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c56ce033d9
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work on an interleaved AR (spoiler: it does not work)
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2023-09-03 21:27:58 -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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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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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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16e0020901
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disabled chunkwise_recurrent for 2x speed gains (I suppose it has been working the entire time, but I have not been properly grabbing things, and this might explain why the output is bad)
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2023-08-25 19:50:19 -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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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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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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2af09d0bef
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fixed that mysterious discepancy between the reported losses (I am so freaking mad, my piss is boiling, I had to interrupt halfway through an epoch)
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2023-08-05 15:25:41 -05:00 |
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0a524f1d59
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reticulating splines
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2023-08-03 21:39:00 -05:00 |
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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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2e03e5ac93
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Fixed an issue with having fairseq installed at all will brick logging
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2023-08-02 22:57:10 -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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7a06b27a9c
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Tweaks
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2023-08-02 22:06:39 +00:00 |
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