Hi,
Could can pass nn.Modules as arguments to the forward function.
If you don’t want gradients to be computed, you can use the torch.no_grad context manager:
def forward(self, hNet001, x):
    with torch.no_grad():    
        y = hNet001(x)
    x = self.layer1(x)
    x = self.layer2(x)
    x = torch.cat((x, y), 1)
    x = self.layer(x)
    return x