(self, x)
| 26 | nn.ReLU(True)) |
| 27 | |
| 28 | def forward(self, x): |
| 29 | x = self.features(x) |
| 30 | |
| 31 | # Transpose the output from features to |
| 32 | # remain compatible with vggish embeddings |
| 33 | x = torch.transpose(x, 1, 3) |
| 34 | x = torch.transpose(x, 1, 2) |
| 35 | x = x.contiguous() |
| 36 | x = x.view(x.size(0), -1) |
| 37 | |
| 38 | return x |
| 39 | # return self.embeddings(x) |
| 40 | |
| 41 | |
| 42 | class Postprocessor(nn.Module): |