(self, x)
| 133 | return nn.Sequential(*layers) |
| 134 | |
| 135 | def forward(self, x): |
| 136 | features = [] |
| 137 | |
| 138 | x = self.conv1(x) |
| 139 | x = self.bn1(x) |
| 140 | x = self.relu(x) |
| 141 | x = self.maxpool(x) |
| 142 | |
| 143 | x = self.layer1(x) |
| 144 | features.append(x) |
| 145 | x = self.layer2(x) |
| 146 | features.append(x) |
| 147 | x = self.layer3(x) |
| 148 | features.append(x) |
| 149 | x = self.layer4(x) |
| 150 | features.append(x) |
| 151 | |
| 152 | return features |
| 153 | |
| 154 | |
| 155 | def resnet18(pretrained=True, **kwargs): |
no test coverage detected