diff options
| author | Jan Buethe <jbuethe@amazon.de> | 2023-09-22 12:39:22 +0300 |
|---|---|---|
| committer | Jan Buethe <jbuethe@amazon.de> | 2023-09-22 12:39:22 +0300 |
| commit | 00580a63aa4d0f796bd9b11c7514fce7c09dcd94 (patch) | |
| tree | fd3d0c263e82d06035a95c67142e83155f8e14a3 | |
| parent | aad74fdfd6ffe7df1986cfb6f410f203c16ab094 (diff) | |
bugfix
| -rw-r--r-- | dnn/torch/osce/models/lavoce.py | 5 | ||||
| -rw-r--r-- | dnn/torch/osce/models/lavoce_400.py | 2 |
2 files changed, 4 insertions, 3 deletions
diff --git a/dnn/torch/osce/models/lavoce.py b/dnn/torch/osce/models/lavoce.py index 47b6d1e9..fcfdc8bf 100644 --- a/dnn/torch/osce/models/lavoce.py +++ b/dnn/torch/osce/models/lavoce.py @@ -89,6 +89,7 @@ class LaVoce(nn.Module): self.kernel_size = kernel_size self.preemph = preemph self.pulses = pulses + self.ftrans_k = ftrans_k assert self.FEATURE_FRAME_SIZE % self.FRAME_SIZE == 0 self.upsamp_factor = self.FEATURE_FRAME_SIZE // self.FRAME_SIZE @@ -145,7 +146,7 @@ class LaVoce(nn.Module): f = (2.0 * torch.pi / periods[:, sframe]).unsqueeze(-1) if self.pulses: - alpha = torch.cos(f) + alpha = torch.cos(f).view(batch_size, 1, 1) chunk_sin = torch.sin(f * progression + phase0).view(batch_size, 1, self.FRAME_SIZE) pulse_a = torch.relu(chunk_sin - alpha) / (1 - alpha) pulse_b = torch.relu(-chunk_sin - alpha) / (1 - alpha) @@ -186,7 +187,7 @@ class LaVoce(nn.Module): def feature_transform(self, f, layer): f = f.permute(0, 2, 1) - f = F.pad(f, [1, 0]) + f = F.pad(f, [self.ftrans_k - 1, 0]) f = torch.tanh(layer(f)) return f.permute(0, 2, 1) diff --git a/dnn/torch/osce/models/lavoce_400.py b/dnn/torch/osce/models/lavoce_400.py index e9a543cf..fe8263be 100644 --- a/dnn/torch/osce/models/lavoce_400.py +++ b/dnn/torch/osce/models/lavoce_400.py @@ -130,7 +130,7 @@ class LaVoce400(nn.Module): f = (2.0 * torch.pi / periods[:, sframe]).unsqueeze(-1) if self.pulses: - alpha = torch.cos(f) + alpha = torch.cos(f).view(batch_size, 1, 1) chunk_sin = torch.sin(f * progression + phase0).view(batch_size, 1, self.FRAME_SIZE) pulse_a = torch.relu(chunk_sin - alpha) / (1 - alpha) pulse_b = torch.relu(-chunk_sin - alpha) / (1 - alpha) |