def filter_layers()

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

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

    def filter_layers(self, layer_indices: list[int] | None) -> "ActivationsAndMetadata":
        """Returns a new ActivationsAndMetadata object with only the specified layer indices."""
        if layer_indices is None:
            return self
        else:
            return dataclasses.replace(
                self,
                activations_by_layer_index={
                    layer_index: activations
                    for layer_index, activations in self.activations_by_layer_index.items()
                    if layer_index in layer_indices or layer_index is None
                },
            )