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