def _get_single_output_relevance()

in captum/attr/_core/layer/layer_lrp.py [0:0]

• 19 lines of code
• 5 McCabe index (conditional complexity)

    def _get_single_output_relevance(self, layer, output):
        if self.attribute_to_layer_input:
            normalized_relevances = layer.rule.relevance_input
        else:
            normalized_relevances = layer.rule.relevance_output
        key_list = _sort_key_list(list(normalized_relevances.keys()), self.device_ids)
        normalized_relevances = _reduce_list(
            [normalized_relevances[device_id] for device_id in key_list]
        )

        if isinstance(normalized_relevances, tuple):
            return tuple(
                normalized_relevance
                * output.reshape((-1,) + (1,) * (normalized_relevance.dim() - 1))
                for normalized_relevance in normalized_relevances
            )
        else:
            return normalized_relevances * output.reshape(
                (-1,) + (1,) * (normalized_relevances.dim() - 1)
            )