(self, x)
| 205 | Norm2d(reduction_dim), nn.ReLU(inplace=True)) |
| 206 | |
| 207 | def forward(self, x): |
| 208 | x_size = x.size() |
| 209 | |
| 210 | img_features = self.img_pooling(x) |
| 211 | img_features = self.img_conv(img_features) |
| 212 | img_features = Upsample(img_features, x_size[2:]) |
| 213 | out = img_features |
| 214 | |
| 215 | for f in self.features: |
| 216 | y = f(x) |
| 217 | out = torch.cat((out, y), 1) |
| 218 | return out |
| 219 | |
| 220 | |
| 221 | class ASPP_edge(AtrousSpatialPyramidPoolingModule): |
nothing calls this directly
no test coverage detected