Thanks for the reply. Using the same conv layer for different inputs would not only use the same weights but also same bias. To share only the weights, is disabling bias in conv layers and adding an additional linear layer with learnable bias the right way? Also, is batch norm implementation in pytorch different when compared to lasagne?