fumiama/Retrieval-based-Voice-Conversion-WebUI
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chore(format): run black on dev (#46)

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Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
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github-actions[bot]
2024-06-13 00:44:04 +09:00
committed by GitHub
parent 8ac5597a3f
commit 83144868e1
1 changed files with 6 additions and 7 deletions
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13
rvc/f0/rmvpe.py
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@@ -21,10 +21,10 @@ class RMVPE(F0Predictor):
device: str, device: str,
use_jit=False, use_jit=False,
): ):
hop_length=160 hop_length = 160
f0_min=30 f0_min = 30
f0_max=8000 f0_max = 8000
sampling_rate=16000 sampling_rate = 16000
super().__init__(hop_length, f0_min, f0_max, sampling_rate) super().__init__(hop_length, f0_min, f0_max, sampling_rate)
@@ -55,6 +55,7 @@ class RMVPE(F0Predictor):
providers=["DmlExecutionProvider"], providers=["DmlExecutionProvider"],
) )
else: else:
def get_jit_model(): def get_jit_model():
jit_model_path = model_path.rstrip(".pth") jit_model_path = model_path.rstrip(".pth")
jit_model_path += ".half.jit" if is_half else ".jit" jit_model_path += ".half.jit" if is_half else ".jit"
@@ -110,9 +111,7 @@ class RMVPE(F0Predictor):
p_len = wav.shape[0] // self.hop_length p_len = wav.shape[0] // self.hop_length
if not torch.is_tensor(wav): if not torch.is_tensor(wav):
wav = torch.from_numpy(wav) wav = torch.from_numpy(wav)
mel = self.mel_extractor( mel = self.mel_extractor(wav.float().to(self.device).unsqueeze(0), center=True)
wav.float().to(self.device).unsqueeze(0), center=True
)
hidden = self._mel2hidden(mel) hidden = self._mel2hidden(mel)
if "privateuseone" not in str(self.device): if "privateuseone" not in str(self.device):
hidden = hidden.squeeze(0).cpu().numpy() hidden = hidden.squeeze(0).cpu().numpy()