Solved by god_sp33d in post #16 
              
              
                I think you can do it, lets say you are using a resnet50 
model = models.resnet50(pretrained=True)
inp = model.fc.in_features
bottle_neck = nn.Linear(inp, 256)

classifier1 = nn.Linear(256, 10)
classifier2 = nn.Linear(256, 10)

class Flatten(nn.Module):
    def forward(self, x):
       x = x.view(x.…