, 3), stride=(1, 1), padding=(1, 1))
    #         (13): ReLU(inplace)
    #         (14): Conv2d (256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    #         (15): ReLU(inplace)
    #         (16): MaxPool2d(kernel_size=(2, 2), stride=(2, 2), dilation=(1, 1))
    relevant, irrelevant = propagate_conv_linear(relevant, irrelevant, mods[10])
    scores.append((relevant.clone(), irrelevant.clone()))
    relevant, irrelevant = propagate_relu(relevant, irrelevant, mods[11])
    relevant, irrelevan