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@ -16,7 +16,6 @@ from infer.lib.infer_pack.commons import get_padding, init_weights
has_xpu = bool(hasattr(torch, "xpu") and torch.xpu.is_available())
class TextEncoder256(nn.Module):
def __init__(
self,
@ -1096,7 +1095,6 @@ class SynthesizerTrnMs256NSFsid_nono(nn.Module):
head = int(z_p.shape[2] * (1.0 - rate.item()))
z_p = z_p[:, :, head:]
x_mask = x_mask[:, :, head:]
nsff0 = nsff0[:, head:]
z = self.flow(z_p, x_mask, g=g, reverse=True)
o = self.dec(z * x_mask, g=g)
return o, x_mask, (z, z_p, m_p, logs_p)
@ -1125,7 +1123,7 @@ class SynthesizerTrnMs768NSFsid_nono(nn.Module):
sr=None,
**kwargs
):
super(SynthesizerTrnMs768NSFsid_nono, self).__init__()
super(SynthesizerTrnMs768NSFsid_nono,self).__init__()
self.spec_channels = spec_channels
self.inter_channels = inter_channels
self.hidden_channels = hidden_channels
@ -1242,7 +1240,6 @@ class SynthesizerTrnMs768NSFsid_nono(nn.Module):
head = int(z_p.shape[2] * (1.0 - rate.item()))
z_p = z_p[:, :, head:]
x_mask = x_mask[:, :, head:]
nsff0 = nsff0[:, head:]
z = self.flow(z_p, x_mask, g=g, reverse=True)
o = self.dec(z * x_mask, g=g)
return o, x_mask, (z, z_p, m_p, logs_p)