def __call__()

in neuron_explainer/activations/derived_scalars/locations.py [0:0]

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

    def __call__(self, layer_indices: list[LayerIndex]) -> list[LayerIndex | Literal["Dummy"]]:
        def _dummy_if_invalid(
            layer_index: LayerIndex, valid_indices: set[LayerIndex]
        ) -> LayerIndex | Literal["Dummy"]:
            if layer_index in valid_indices:
                return layer_index
            else:
                # this value represents the fact that the layer index is not needed for this computation
                # callers are free to use a dummy tensor in place of the activations at this layer index,
                # knowing that downstream DST calculations are intended to be independent of the activation
                # tensor provided at this layer index
                return "Dummy"

        assert all(layer_index is not None for layer_index in layer_indices)
        # source_layer_indices satisfy:
        # target_layer_indices = layer_indices
        # for target_layer_index, source_layer_index in zip(target_layer_indices, source_layer_indices):
        #    target_activations_by_layer_index[target_layer_index] = source_activations_by_layer_index[source_layer_index] # (or a dummy tensor, if the index is "Dummy")
        source_layer_indices = [layer_index + self.layer_index_offset for layer_index in layer_indices]  # type: ignore
        # 'invalid' layer indices are those not in starting_layer_indices; starting_layer_indices mapped to unneeded layer indices are considered "Unneeded"
        return [
            _dummy_if_invalid(source_layer_index, set(layer_indices))
            for source_layer_index in source_layer_indices
        ]