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

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github-actions[bot] 2024-04-21 16:46:13 +00:00
parent b06cdcce32
commit 35bfdccfb2
3 changed files with 28 additions and 15 deletions
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2
gui_v1.py
View File

@ -356,7 +356,7 @@ if __name__ == "__main__":
enable_events=True, enable_events=True,
), ),
], ],
[ [
sg.Text(i18n("共振偏移")), sg.Text(i18n("共振偏移")),
sg.Slider( sg.Slider(
range=(-5, 5), range=(-5, 5),

21
infer/lib/infer_pack/models.py
View File

@ -249,12 +249,17 @@ class Generator(torch.nn.Module):
if gin_channels != 0: if gin_channels != 0:
self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1) self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
def forward(self, x: torch.Tensor, g: Optional[torch.Tensor] = None, n_res: Optional[torch.Tensor] = None): def forward(
self,
x: torch.Tensor,
g: Optional[torch.Tensor] = None,
n_res: Optional[torch.Tensor] = None,
):
if n_res is not None: if n_res is not None:
assert isinstance(n_res, torch.Tensor) assert isinstance(n_res, torch.Tensor)
n = int(n_res.item()) n = int(n_res.item())
if n != x.shape[-1]: if n != x.shape[-1]:
x = F.interpolate(x, size=n, mode='linear') x = F.interpolate(x, size=n, mode="linear")
x = self.conv_pre(x) x = self.conv_pre(x)
if g is not None: if g is not None:
x = x + self.cond(g) x = x + self.cond(g)
@ -533,16 +538,22 @@ class GeneratorNSF(torch.nn.Module):
self.lrelu_slope = modules.LRELU_SLOPE self.lrelu_slope = modules.LRELU_SLOPE
def forward(self, x, f0, g: Optional[torch.Tensor] = None, n_res: Optional[torch.Tensor] = None): def forward(
self,
x,
f0,
g: Optional[torch.Tensor] = None,
n_res: Optional[torch.Tensor] = None,
):
har_source, noi_source, uv = self.m_source(f0, self.upp) har_source, noi_source, uv = self.m_source(f0, self.upp)
har_source = har_source.transpose(1, 2) har_source = har_source.transpose(1, 2)
if n_res is not None: if n_res is not None:
assert isinstance(n_res, torch.Tensor) assert isinstance(n_res, torch.Tensor)
n = int(n_res.item()) n = int(n_res.item())
if n * self.upp != har_source.shape[-1]: if n * self.upp != har_source.shape[-1]:
har_source = F.interpolate(har_source, size=n*self.upp, mode='linear') har_source = F.interpolate(har_source, size=n * self.upp, mode="linear")
if n != x.shape[-1]: if n != x.shape[-1]:
x = F.interpolate(x, size=n, mode='linear') x = F.interpolate(x, size=n, mode="linear")
x = self.conv_pre(x) x = self.conv_pre(x)
if g is not None: if g is not None:
x = x + self.cond(g) x = x + self.cond(g)

4
infer/lib/rtrvc.py
View File

@ -446,7 +446,9 @@ class RVC:
new_freq=self.tgt_sr // 100, new_freq=self.tgt_sr // 100,
dtype=torch.float32, dtype=torch.float32,
).to(self.device) ).to(self.device)
infered_audio = self.resample_kernel[upp_res](infered_audio[: ,: return_length * upp_res]) infered_audio = self.resample_kernel[upp_res](
infered_audio[:, : return_length * upp_res]
)
t5 = ttime() t5 = ttime()
printt( printt(
"Spent time: fea = %.3fs, index = %.3fs, f0 = %.3fs, model = %.3fs", "Spent time: fea = %.3fs, index = %.3fs, f0 = %.3fs, model = %.3fs",