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gradient-based saliency maps to support different activations #6057

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wyli opened this issue Feb 23, 2023 · 0 comments · May be fixed by #7070
Open

gradient-based saliency maps to support different activations #6057

wyli opened this issue Feb 23, 2023 · 0 comments · May be fixed by #7070
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@wyli
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wyli commented Feb 23, 2023 

class GuidedBackpropGrad(VanillaGrad):
   

    def __call__(self, x: torch.Tensor, index: torch.Tensor | int | None = None, **kwargs) -> torch.Tensor:
        with replace_modules_temp(self.model, "relu", _GradReLU(), strict_match=False):
            return super().__call__(x, index, **kwargs)

I think the method tries to look for "relu" layers and replace it with a grad-hooked customised one. This assumingly might not work with other activation functions. this is a feature request to support different activation functions, SiLU for instance.

Originally posted by @trinhdhk in #6012 (reply in thread)
@JupiLogy JupiLogy linked a pull request Sep 30, 2023 that will close this issue
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6057guided backprop silu JupiLogy/MONAI
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