use syncnet to compute perception loss
| 266 | |
| 267 | |
| 268 | class SyncNetPerception(nn.Module): |
| 269 | """ |
| 270 | use syncnet to compute perception loss |
| 271 | """ |
| 272 | |
| 273 | def __init__(self, pretrain_path): |
| 274 | super(SyncNetPerception, self).__init__() |
| 275 | self.model = SyncNet(15, 29, 128) |
| 276 | print("load lip sync model : {}".format(pretrain_path)) |
| 277 | self.model.load_state_dict(torch.load(pretrain_path)["state_dict"]["net"]) |
| 278 | for param in self.model.parameters(): |
| 279 | param.requires_grad = False |
| 280 | self.model.eval() |
| 281 | |
| 282 | def forward(self, image, audio): |
| 283 | score = self.model(image, audio) |
| 284 | return score |