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v3sovits模型推理支持webui传语速参数调整合成语速

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v3sovits模型推理支持webui传语速参数调整合成语速
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RVC-Boss 2025-02-28 16:50:35 +08:00 committed by GitHub
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commit a32a2b8934
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1 changed files with 7 additions and 3 deletions
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GPT_SoVITS/module/models.py
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@ -1251,7 +1251,7 @@ class SynthesizerTrnV3(nn.Module):
return cfm_loss
@torch.no_grad()
def decode_encp(self, codes,text, refer,ge=None):
def decode_encp(self, codes,text, refer,ge=None,speed=1):
# print(2333333,refer.shape)
# ge=None
if(ge==None):
@ -1259,13 +1259,17 @@ class SynthesizerTrnV3(nn.Module):
refer_mask = torch.unsqueeze(commons.sequence_mask(refer_lengths, refer.size(2)), 1).to(refer.dtype)
ge = self.ref_enc(refer[:,:704] * refer_mask, refer_mask)
y_lengths = torch.LongTensor([int(codes.size(2)*2)]).to(codes.device)
y_lengths1 = torch.LongTensor([int(codes.size(2)*2.5*1.5)]).to(codes.device)
if speed==1:
sizee=int(codes.size(2)*2.5*1.5)
else:
sizee=int(codes.size(2)*2.5*1.5/speed)+1
y_lengths1 = torch.LongTensor([sizee]).to(codes.device)
text_lengths = torch.LongTensor([text.size(-1)]).to(text.device)
quantized = self.quantizer.decode(codes)
if self.semantic_frame_rate == '25hz':
quantized = F.interpolate(quantized, scale_factor=2, mode="nearest")##BCT
x, m_p, logs_p, y_mask = self.enc_p(quantized, y_lengths, text, text_lengths, ge)
x, m_p, logs_p, y_mask = self.enc_p(quantized, y_lengths, text, text_lengths, ge,speed)
fea=self.bridge(x)
fea = F.interpolate(fea, scale_factor=1.875, mode="nearest")##BCT
####more wn paramter to learn mel