(self, x, x_lengths, g=None)
| 402 | self.norm = modules.LayerNorm(out_channels) |
| 403 | |
| 404 | def forward(self, x, x_lengths, g=None): |
| 405 | x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to( |
| 406 | x.dtype |
| 407 | ) |
| 408 | x = self.pre(x) * x_mask |
| 409 | x = self.enc(x, x_mask, g=g) |
| 410 | out = self.proj(x) * x_mask |
| 411 | out = self.norm(out) |
| 412 | return out |
| 413 | |
| 414 | |
| 415 | class Generator(torch.nn.Module): |
nothing calls this directly
no outgoing calls
no test coverage detected