AttributeError: 'MaxPool2D' object has no attribute 'set_scoring_mode'

[MuskaanJain]

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?

[AvantiShri]

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 notifications@github.com 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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[MuskaanJain]

with some combination of output neurons.

[AvantiShri]

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