(self, pretrain=False, use_layer2=False)
| 158 | |
| 159 | class SimpleResNetEncoder2(nn.Module): |
| 160 | def __init__(self, pretrain=False, use_layer2=False): |
| 161 | super().__init__() |
| 162 | resnet = models.resnet18(pretrained=pretrain) |
| 163 | nets = [] |
| 164 | net_names = ['conv1', 'bn1', 'relu', 'maxpool', 'layer1'] |
| 165 | if use_layer2: |
| 166 | net_names.append('layer2') |
| 167 | for net in net_names: |
| 168 | nets.append(getattr(resnet, net)) |
| 169 | self.resnet = nn.Sequential(*nets) |
| 170 | |
| 171 | def forward(self, x): |
| 172 | x = self.resnet(x) |