Ethanfel
5f29b225b7
ComfyUI nodes for UniverSR (ICASSP 2026) — vocoder-free audio super-resolution (8/12/16/24 kHz → 48 kHz) via flow matching. - UniverSR Model Loader: presets auto-download to models/universr, plus local dir / raw .pth (from_local) loading, with caching. - UniverSR Super-Resolution: chunked overlap-add for long audio, per-channel stereo, seed control with global-RNG isolation, wet/dry blend, and an optional before/after spectrogram. - Vendors the universr inference package under vendor/ (prefers an installed copy); only extra dep beyond ComfyUI's stack is torchdiffeq. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
10 lines
278 B
Python
10 lines
278 B
Python
import torch
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import torch.nn.functional as F
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def flow_matching_loss(predicted_vf: torch.Tensor, target_vf: torch.Tensor) -> torch.Tensor:
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"""
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Flow matching loss; L2 loss between estimated and target vector field.
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"""
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return F.mse_loss(predicted_vf, target_vf)
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