fumiama/Retrieval-based-Voice-Conversion-WebUI
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optimize(uvr5): apply jit to spec_utils & fix flac save

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also fix #85
This commit is contained in:
源文雨
2024-11-28 23:19:05 +09:00
parent 4582d4b49a
commit 5969314e8d
11 changed files with 104 additions and 581 deletions
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11
infer/lib/uvr5_pack/lib_v5/layers.py
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@@ -22,7 +22,8 @@ class Conv2DBNActiv(nn.Module):
activ(),
)
def __call__(self, x):
@torch.inference_mode()
def forward(self, x):
return self.conv(x)
@@ -32,7 +33,8 @@ class Encoder(nn.Module):
self.conv1 = Conv2DBNActiv(nin, nout, ksize, stride, pad, activ=activ)
self.conv2 = Conv2DBNActiv(nout, nout, ksize, 1, pad, activ=activ)
def __call__(self, x):
@torch.inference_mode()
def forward(self, x):
h = self.conv1(x)
h = self.conv2(h)
@@ -48,7 +50,8 @@ class Decoder(nn.Module):
# self.conv2 = Conv2DBNActiv(nout, nout, ksize, 1, pad, activ=activ)
self.dropout = nn.Dropout2d(0.1) if dropout else None
def __call__(self, x, skip=None):
@torch.inference_mode()
def forward(self, x, skip=None):
x = F.interpolate(x, scale_factor=2, mode="bilinear", align_corners=True)
if skip is not None:
@@ -84,6 +87,7 @@ class ASPPModule(nn.Module):
self.bottleneck = Conv2DBNActiv(nout * 5, nout, 1, 1, 0, activ=activ)
self.dropout = nn.Dropout2d(0.1) if dropout else None
@torch.inference_mode()
def forward(self, x):
_, _, h, w = x.size()
feat1 = F.interpolate(
@@ -113,6 +117,7 @@ class LSTMModule(nn.Module):
nn.Linear(nout_lstm, nin_lstm), nn.BatchNorm1d(nin_lstm), nn.ReLU()
)
@torch.inference_mode()
def forward(self, x):
N, _, nbins, nframes = x.size()
h = self.conv(x)[:, 0] # N, nbins, nframes