mirror of
https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2025-10-07 23:48:48 +08:00
50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
import logging
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from functools import cache
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import torch
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from ..inference import inference
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from .download import download
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from .train import Enhancer, HParams
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import platform
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import pathlib
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# Check if the current system is Windows
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if platform.system() == 'Windows':
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# Make changes specific to Windows
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temp = pathlib.PosixPath
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pathlib.PosixPath = pathlib.WindowsPath
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logger = logging.getLogger(__name__)
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def load_enhancer(run_dir, device):
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if run_dir is None:
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run_dir = download()
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hp = HParams.load(run_dir)
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enhancer = Enhancer(hp)
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path = run_dir / "ds" / "G" / "default" / "mp_rank_00_model_states.pt"
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state_dict = torch.load(path, map_location="cpu")["module"]
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enhancer.load_state_dict(state_dict)
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enhancer.eval()
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enhancer.to(device)
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return enhancer
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@torch.inference_mode()
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def denoise(dwav, sr, device, run_dir=None):
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enhancer = load_enhancer(run_dir, device)
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return inference(model=enhancer.denoiser, dwav=dwav, sr=sr, device=device)
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@torch.inference_mode()
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def enhance(chunk_seconds, chunks_overlap,dwav, sr, device, nfe=32, solver="midpoint", lambd=0.5, tau=0.5, run_dir=None):
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assert 0 < nfe <= 128, f"nfe must be in (0, 128], got {nfe}"
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assert solver in ("midpoint", "rk4", "euler"), f"solver must be in ('midpoint', 'rk4', 'euler'), got {solver}"
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assert 0 <= lambd <= 1, f"lambd must be in [0, 1], got {lambd}"
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assert 0 <= tau <= 1, f"tau must be in [0, 1], got {tau}"
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enhancer = load_enhancer(run_dir, device)
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enhancer.configurate_(nfe=nfe, solver=solver, lambd=lambd, tau=tau)
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return inference(model=enhancer, chunk_seconds=chunk_seconds, overlap_seconds=chunks_overlap, dwav=dwav, sr=sr, device=device)
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