model.py 文件源码

def forward(self, img, txt_feat):
        img_feat = self.encoder(img)
        img_feat = F.leaky_relu(img_feat + self.residual_branch(img_feat), 0.2)
        txt_feat = self.compression(txt_feat)

        txt_feat = txt_feat.unsqueeze(-1).unsqueeze(-1)
        txt_feat = txt_feat.repeat(1, 1, img_feat.size(2), img_feat.size(3))
        fusion = torch.cat((img_feat, txt_feat), dim=1)
        output = self.classifier(fusion)
        return output.squeeze()