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A fix
Browse files
radtts.py
CHANGED
@@ -688,9 +688,7 @@ class RADTTS(torch.nn.Module):
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if dur is None:
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# get token durations
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z_dur = torch.
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torch.empty(batch_size, 1, n_tokens), dtype=torch.float32
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)
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if use_cuda:
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z_dur = z_dur.cuda()
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@@ -746,10 +744,14 @@ class RADTTS(torch.nn.Module):
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if f0 is None:
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n_f0_feature_channels = 2 if self.use_first_order_features else 1
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z_f0 =
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torch.randn(
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)
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if use_cuda:
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z_f0 = z_f0.cuda()
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@@ -772,10 +774,14 @@ class RADTTS(torch.nn.Module):
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if energy_avg is None:
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n_energy_feature_channels = 2 if self.use_first_order_features else 1
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z_energy_avg =
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torch.randn(
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)
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if use_cuda:
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if dur is None:
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# get token durations
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z_dur = torch.empty(batch_size, 1, n_tokens, dtype=torch.float32)
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if use_cuda:
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z_dur = z_dur.cuda()
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if f0 is None:
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n_f0_feature_channels = 2 if self.use_first_order_features else 1
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z_f0 = (
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torch.randn(
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batch_size,
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n_f0_feature_channels,
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max_n_frames,
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dtype=torch.float32,
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)
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* sigma_f0
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)
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if use_cuda:
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z_f0 = z_f0.cuda()
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if energy_avg is None:
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n_energy_feature_channels = 2 if self.use_first_order_features else 1
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z_energy_avg = (
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torch.randn(
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batch_size,
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n_energy_feature_channels,
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max_n_frames,
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dtype=torch.float32,
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)
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* sigma_energy
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)
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if use_cuda:
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