(self, Input)
| 218 | self.fc_pose = nn.Linear(1280, feat_dim) |
| 219 | |
| 220 | def forward(self, Input): |
| 221 | x = self.feature_extractor(Input) |
| 222 | x = self.avgpool(x) |
| 223 | x = x.reshape(x.size(0), -1) |
| 224 | predict = self.fc_pose(x) |
| 225 | # pdb.set_trace() |
| 226 | return predict |
| 227 | |
| 228 | # PoseNet (SE(3)) w/ resnet34 backnone. We found dropout layer is unnecessary, so we set droprate as 0 in reported results. |
| 229 | class PoseNet_res34(nn.Module): |
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