Comments (3)
@adefossez good catch... will add this soon.
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Sounds good! I assume then you actually don't use double precision for Open Unmix despite the note in the comments?
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I remember when we ported this @aliutkus had problems getting stable results with float32, thus requiring doubles. Then we were able to fix this at some point (either this or the torch implementations improved over time)....
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Related Issues (20)
- Running umxhq on a large test track (Georgia Wonder - Siren) blows up memory >64GB HOT 11
- SDR performance regression since version 1.0.0 HOT 6
- --help option seems to be broken in v1.2.1 HOT 3
- Error when training. HOT 1
- RuntimeError: "reflection_pad1d_out_template" not implemented for 'Short' : when using separate(...) method HOT 7
- Training Hardware and Issue HOT 11
- Use of Transformers/Attention
- Validation Error HOT 3
- Model download is very slow HOT 2
- multichannel generalized Wiener filter question HOT 1
- Gaps in the resulting audio file in the umxse model HOT 20
- TypeError: umx() got an unexpected keyword argument 'target'
- There was a problem running the openunmix tutorial in colab!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! HOT 1
- How VRAM-hungry is umx supposed to be? HOT 2
- Size difference between umxhq and umxl HOT 2
- Training by trackfolder_fix dataset with bad result HOT 7
- Cannot download 'umx' or 'umxhq' model HOT 6
- AttributeError: module 'openunmix' has no attribute 'Separator' HOT 2
- Cannot Figure Out How to Use without CLI, Docs Do Not Help HOT 2
- ζ沑ζε―δΎmatlabδ½Ώη¨ηηζ¬ HOT 1
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