Activations are measured for all layers in one pass, as the cost is only a bit more RAM to hold the results; no significant cost in inference time. This is done for measuring compliance and refusal activations. Directional difference is computed within each layer.
For intervention/ablation, the YML file allows an N-to-M mapping. I can pick 3-4 (notionally high relevance) layer measurements to apply to sequential chunks, with the heuristic that the source measurement layer being closer to the target intervention layer will hopefully limit unwanted side-effects. One could apply each refusal measurement to the same layer, but that approach doesn't provide the most effective ablation in my experience. There's something deeper going on which I've not yet been able to characterize.
