Solved by jpeg729 in post #4 
              
              
                What about this… 
result = None
input_downsampled = input
for i in range(3):
       if result is None:
            result = self.forward(model, input_downsampled)
       else:
            result = torch.cat([model, self.forward(model, input_downsampled)])
       if i != (2):
            input_downsa…