def forward(self, source, target): loss = torch.FloatTensor([0]).to(source.device) source = self.features(source) source = source.view(source.size(0), -1) source = self.classifier(source) if self.training == True: target = self.features(target) target = target.view(target.size(0), -1) target = self.classifier(target) loss += mmd.mmd_rbf_noaccelerate(source, target) source = self.cls_fc(source) return source, loss, target
def forward(self, source, target): #Hack for Multiple GPU... loss = torch.zeros(1, device=source.device) source = self.sharedNet(source) if self.training == True: target = self.sharedNet(target) # loss += mmd.mmd_rbf_accelerate(source, target) loss = mmd.mmd_rbf_noaccelerate(source, target) target = self.cls_fc(target) source = self.cls_fc(source) return source, loss, target