Comments (3)
@dorpxam hey, so target
and raw_audio
are actually two different inputs
target
is the expected output for each of stems
and yea, we can refine the hyperparameters a bit more, let me get that done
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@lucidrains Oh, I look so dumb now. I hope you understand that my issues are not to criticize or call into question your work. I'm autodidact and learn step by step, so I often say rubbish bigger than me.
That the model is capable of generating the mask of a target from a source and based on a loss function, that makes sense. But generating multiple masks only based on a loss function without the targets being involved in the model is black magic for me :)
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@ZFTurbo the stem feature is working for your kaggle stuff?
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Related Issues (20)
- MelBand doesn't work with stereo HOT 7
- Hop length HOT 7
- Hidden dim in mask estimation module HOT 5
- Removed
- How to use it for audio source separation? HOT 2
- MLP design in MaskEstimator HOT 7
- Hardly to train with 8s length audio for batch size of 2 HOT 6
- Cut frequencies at half of the Nyquist in the MelBand model HOT 7
- Feature request: decouple the loss function of the forward function HOT 2
- Problem with DataParallel HOT 5
- MelRoformer parameters from paper HOT 16
- Gates in Attention module of bs_roformer.py HOT 5
- Linear Attention temperature initialization HOT 1
- Flash attention error in Linear Attention layer HOT 1
- Reproduce the results from the paper HOT 1
- Default time_transformer_depth HOT 1
- Input tensor size HOT 1
- Flash Attention support HOT 2
- [bad assertion] strange bottleneck performance HOT 1
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from bs-roformer.