keras-vis
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saliency + guided backprop + all filters + linear activation + VGG16 gives zero gradients
not sure why but the combination of guided backprop + filter_indices=None (all filters) + linear final activation gives me zero gradients for VGG16. you can see this in the demo notebook.
i now also see this sometimes with softmax