(self, inputs)
| 660 | self.proj = nn.Linear(128, gin_channels) |
| 661 | |
| 662 | def forward(self, inputs): |
| 663 | N = inputs.size(0) |
| 664 | out = inputs.view(N, 1, -1, self.spec_channels) # [N, 1, Ty, n_freqs] |
| 665 | for conv in self.convs: |
| 666 | out = conv(out) |
| 667 | # out = wn(out) |
| 668 | out = F.relu(out) # [N, 128, Ty//2^K, n_mels//2^K] |
| 669 | |
| 670 | out = out.transpose(1, 2) # [N, Ty//2^K, 128, n_mels//2^K] |
| 671 | T = out.size(1) |
| 672 | N = out.size(0) |
| 673 | out = out.contiguous().view(N, T, -1) # [N, Ty//2^K, 128*n_mels//2^K] |
| 674 | |
| 675 | self.gru.flatten_parameters() |
| 676 | memory, out = self.gru(out) # out --- [1, N, 128] |
| 677 | |
| 678 | return self.proj(out.squeeze(0)).unsqueeze(-1) |
| 679 | |
| 680 | def calculate_channels(self, L, kernel_size, stride, pad, n_convs): |
| 681 | for i in range(n_convs): |
nothing calls this directly
no outgoing calls
no test coverage detected