def visualize()

in captum/insights/attr_vis/features.py [0:0]

• 14 lines of code
• 4 McCabe index (conditional complexity)

    def visualize(self, attribution, data, contribution_frac) -> FeatureOutput:
        attribution = attribution.squeeze(0)
        data = data.squeeze(0)

        # L-2 norm, if norm is 0, all attr elements are 0
        l2_norm = attribution.norm()
        normalized_attribution = safe_div(attribution, l2_norm)

        modified = [x * 100 for x in normalized_attribution.tolist()]

        base = [f"{c}: {d:.2f}" for c, d in zip(self.categories, data.tolist())]
        return FeatureOutput(
            name=self.name,
            base=base,
            modified=modified,
            type=self.visualization_type(),
            contribution=contribution_frac,
        )