, 1))
    #         (18): ReLU(inplace)
    #         (19): Conv2d (512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    #         (20): ReLU(inplace)
    #         (21): Conv2d (512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    #         (22): ReLU(inplace)
    #         (23): MaxPool2d(kernel_size=(2, 2), stride=(2, 2), dilation=(1, 1))
    relevant, irrelevant = propagate_conv_linear(relevant, irrelevant, mods[17])
    scores.append((relevant.clone(), irrelevant.clone()))
    r