(self, x)
| 208 | self.ese = eSEModule(concat_ch) |
| 209 | |
| 210 | def forward(self, x): |
| 211 | |
| 212 | identity_feat = x |
| 213 | |
| 214 | output = [] |
| 215 | output.append(x) |
| 216 | if self.depthwise and self.isReduced: |
| 217 | x = self.conv_reduction(x) |
| 218 | for layer in self.layers: |
| 219 | x = layer(x) |
| 220 | output.append(x) |
| 221 | |
| 222 | x = torch.cat(output, dim=1) |
| 223 | xt = self.concat(x) |
| 224 | |
| 225 | xt = self.ese(xt) |
| 226 | |
| 227 | if self.identity: |
| 228 | xt = xt + identity_feat |
| 229 | |
| 230 | return xt |
| 231 | |
| 232 | |
| 233 | class _OSA_stage(nn.Sequential): |
nothing calls this directly
no outgoing calls
no test coverage detected