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Merge pull request #4 from Stardust-minus/fix-gan-dur

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修正Dur GAN
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Stardust·减
2023-08-30 09:51:42 +08:00
committed by GitHub
parent 441ad781f2 d15e1d339b
commit 20529f6e17
2 changed files with 2 additions and 3 deletions
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1
models.py
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@@ -669,7 +669,6 @@ class SynthesizerTrn(nn.Module):
l_length_sdp = self.sdp(x, x_mask, w, g=g) l_length_sdp = self.sdp(x, x_mask, w, g=g)
l_length_sdp = l_length_sdp / torch.sum(x_mask) l_length_sdp = l_length_sdp / torch.sum(x_mask)
logw_ = torch.log(w + 1e-6) * x_mask logw_ = torch.log(w + 1e-6) * x_mask
logw = self.dp(x, x_mask, g=g) logw = self.dp(x, x_mask, g=g)
l_length_dp = torch.sum((logw - logw_) ** 2, [1, 2]) / torch.sum(x_mask) # for averaging l_length_dp = torch.sum((logw - logw_) ** 2, [1, 2]) / torch.sum(x_mask) # for averaging

4
train_ms.py
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@@ -255,7 +255,7 @@ def train_and_evaluate(rank, epoch, hps, nets, optims, schedulers, scaler, loade
loss_disc, losses_disc_r, losses_disc_g = discriminator_loss(y_d_hat_r, y_d_hat_g) loss_disc, losses_disc_r, losses_disc_g = discriminator_loss(y_d_hat_r, y_d_hat_g)
loss_disc_all = loss_disc loss_disc_all = loss_disc
if net_dur_disc is not None: if net_dur_disc is not None:
y_dur_hat_r, y_dur_hat_g = net_dur_disc(hidden_x.detach(), x_mask.detach(), logw.detach(), logw_.detach()) y_dur_hat_r, y_dur_hat_g = net_dur_disc(hidden_x.detach(), x_mask.detach(), logw_.detach(), logw.detach())
with autocast(enabled=False): with autocast(enabled=False):
# TODO: I think need to mean using the mask, but for now, just mean all # TODO: I think need to mean using the mask, but for now, just mean all
loss_dur_disc, losses_dur_disc_r, losses_dur_disc_g = discriminator_loss(y_dur_hat_r, y_dur_hat_g) loss_dur_disc, losses_dur_disc_r, losses_dur_disc_g = discriminator_loss(y_dur_hat_r, y_dur_hat_g)
@@ -276,7 +276,7 @@ def train_and_evaluate(rank, epoch, hps, nets, optims, schedulers, scaler, loade
# Generator # Generator
y_d_hat_r, y_d_hat_g, fmap_r, fmap_g = net_d(y, y_hat) y_d_hat_r, y_d_hat_g, fmap_r, fmap_g = net_d(y, y_hat)
if net_dur_disc is not None: if net_dur_disc is not None:
y_dur_hat_r, y_dur_hat_g = net_dur_disc(hidden_x, x_mask, logw, logw_) y_dur_hat_r, y_dur_hat_g = net_dur_disc(hidden_x, x_mask, logw_, logw)
with autocast(enabled=False): with autocast(enabled=False):
loss_dur = torch.sum(l_length.float()) loss_dur = torch.sum(l_length.float())
loss_mel = F.l1_loss(y_mel, y_hat_mel) * hps.train.c_mel loss_mel = F.l1_loss(y_mel, y_hat_mel) * hps.train.c_mel