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AttributeError: 'MaxPool2D' object has no attribute 'set_scoring_mode'
I am using a VGG16 model with "include_top=False" i.e. having Maxpool2D as its last layer. Is Maxpool2D as the target layer not possible or it is just not implemented?
Just not implemented. If you were to conduct interpretation, would you do it with respect to a single neuron in the maxpooling output? Or would you do it with respect to some combination of output neurons?
On Thu, Jun 6, 2019 at 2:01 AM Muskaan Jain [email protected] wrote:
I am using a VGG16 model with "include_top=False" i.e. having Maxpool2D as its last layer. Is Maxpool2D as the target layer not possible or it is just not implemented?
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with some combination of output neurons.
Nice running into you at ISMB yesterday! To recap, all the backpropagation-based interpretation methods rely on a single output at which to start the backprop. My recommendation is that for interpretation, you could add a fully-connected neuron that encodes the combination of maxpooling neurons you are interested in, and then do interpretation with respect to that fully-connected neuron. If you run into issues of particular architectures not being supported, you could also use DeepSHAP (a combination of DeepLIFT + the SHAP method): https://github.com/kundajelab/deeplift#my-model-architecture-is-not-supported-by-this-deeplift-implementation-what-should-i-do