| import torch | |
| import torch.nn as nn | |
| from rscd.models.backbones.lgpnet.BFE_DPN import BFExtractor | |
| class LGPNet_a(nn.Module): | |
| def __init__(self): | |
| super().__init__() | |
| self.backbone = BFExtractor(n_channels=3, n_classes=2) | |
| def forward(self, xA, xB): | |
| list = [] # 0: out1,1: out2,2: feat1,3: feat2 | |
| out1, feat1 = self.backbone(xA) | |
| out2, feat2 = self.backbone(xB) | |
| list.append(out1) | |
| list.append(out2) | |
| list.append(feat1) | |
| list.append(feat2) | |
| return list | |