I am doing late fusion of features extracted by two large resnet.
After that, the classifier on the concatenated features can be run in the second GPU?
Will that be slow?
How to combine data parallel and model parallel?
(say if i have 4 gpu)
   def forward(self, x):
         
        x1= self.resnet_1(x[:,0:3,:,:]).cuda(0)
        x2= self.resnet_2(x[:,3:6,:,:]).cuda(1)

        flat  = torch.cat([x1, x2],1).cuda(???)
        logit = self.fc(flat).cuda(???) 
        return logit