I am sure the output is the same.
But after training both the models on CUB dataset,  myModel6 gets  2.1%  increase in classification accuracy compared to the other model. I just want to know, why is that? are the weights being updated similarly in both the models? Are there any differences?
def forward(self, x, labels=None, return_cam=False):
        batch_size = x.shape[0]
        x1 = self.features(x)
        x1 = self.conv6(x1)
        x1 = self.relu(x1)
        x1 = self.conv7(x1)
        x1 = self.relu(x1)
        
        x2 = self.features(x)
        x2 = self.conv8(x2)
        x2 = self.relu(x2)
        x2 = self.conv9(x2)
        x2 = self.relu(x2)

        x3 = self.features(x)
        x3 = self.conv10(x3)
        x3 = self.relu(x3)
        x3 = self.conv11(x3)
        x3 = self.relu(x3)

        x = x1 + x2 + x3

(I am sorry if i am bothering you.)