(self, x, mask)
| 223 | self.LD = LocalDynamics(ngf*8) |
| 224 | |
| 225 | def forward(self, x, mask): |
| 226 | x0 = self.model_layer0(x) |
| 227 | x1 = self.model_layer1(x0) |
| 228 | if self.model_layer1norm._get_name() in self.norm_namebuffer: |
| 229 | x1 = self.model_layer1norm(x1, mask) |
| 230 | else: |
| 231 | x1 = self.model_layer1norm(x1) |
| 232 | x2 = self.model_layer2(x1) |
| 233 | if self.model_layer2norm._get_name() in self.norm_namebuffer: |
| 234 | x2 = self.model_layer2norm(x2, mask) |
| 235 | else: |
| 236 | x2 = self.model_layer2norm(x2) |
| 237 | x3 = self.model_layer3(x2) |
| 238 | if self.model_layer3norm._get_name() in self.norm_namebuffer: |
| 239 | x3 = self.model_layer3norm(x3, mask) |
| 240 | else: |
| 241 | x3 = self.model_layer3norm(x3) |
| 242 | |
| 243 | x4 = self.model_layer4(x3) |
| 244 | if self.model_layer4norm._get_name() in self.norm_namebuffer: |
| 245 | x4 = self.model_layer4norm(x4, mask) |
| 246 | else: |
| 247 | x4 = self.model_layer4norm(x4) |
| 248 | |
| 249 | x5 = self.model_layer5(x4) |
| 250 | if self.model_layer5norm._get_name() in self.norm_namebuffer: |
| 251 | x5 = self.model_layer5norm(x5, mask) |
| 252 | else: |
| 253 | x5 = self.model_layer5norm(x5) |
| 254 | |
| 255 | x6 = self.model_layer6(x5) |
| 256 | if self.model_layer6norm._get_name() in self.norm_namebuffer: |
| 257 | x6 = self.model_layer6norm(x6, mask) |
| 258 | else: |
| 259 | x6 = self.model_layer6norm(x6) |
| 260 | |
| 261 | |
| 262 | x71 = self.model_layer71(x6) |
| 263 | |
| 264 | x71 = self.LD(x71, mask) |
| 265 | |
| 266 | x72 = self.model_layer72(x71) |
| 267 | if self.model_layer72norm._get_name() in self.norm_namebuffer: |
| 268 | x72 = self.model_layer72norm(x72, mask) |
| 269 | else: |
| 270 | x72 = self.model_layer72norm(x72) |
| 271 | |
| 272 | x72 = torch.cat([x6, x72], 1) |
| 273 | |
| 274 | ox5 = self.model_layer8(x72) |
| 275 | if self.model_layer8norm._get_name() in self.norm_namebuffer: |
| 276 | ox5 = self.model_layer8norm(ox5, mask) |
| 277 | else: |
| 278 | ox5 = self.model_layer8norm(ox5) |
| 279 | |
| 280 | ox5 = torch.cat([x5, ox5], 1) |
| 281 | |
| 282 | ox4 = self.model_layer9(ox5) |
no outgoing calls
no test coverage detected