(self, mels)
| 77 | self.relu = nn.ReLU() |
| 78 | |
| 79 | def forward(self, mels): |
| 80 | self.lstm.flatten_parameters() |
| 81 | _, (hidden, _) = self.lstm(mels.transpose(-1, -2)) |
| 82 | embeds_raw = self.relu(self.linear(hidden[-1])) |
| 83 | return embeds_raw / torch.norm(embeds_raw, dim=1, keepdim=True) |
| 84 | |
| 85 | |
| 86 | class MELEncoder(nn.Module): |
nothing calls this directly
no outgoing calls
no test coverage detected