audit: conservatively count predictor arithmetic

1 files changed, 13 insertions, 2 deletions

diff --git a/sdil/conv.py b/sdil/conv.py
index cc4c7c6..ea62e95 100644
--- a/sdil/conv.py
+++ b/sdil/conv.py
@@ -662,8 +662,19 @@ class CIFARKPMixedTrafficResNet(CIFARKPResNet):
 
     @property
     def predictor_elementwise_ops_per_example(self):
-        # Residual, centering, moments, normalization, and affine updates.
-        return 12 * self.mixed_units_per_example
+        # Conservative count for traffic/prediction, centering, reductions,
+        # normalized moments, residual power, and affine parameter updates.
+        return 24 * self.mixed_units_per_example
+
+    @property
+    def traffic_calibration_elementwise_ops_per_example(self):
+        # Two RMS measurements, gain application, and achieved-ratio audit.
+        return 8 * self.mixed_units_per_example
+
+    @property
+    def predictor_audit_elementwise_ops_per_example(self):
+        # Traffic/prediction/residual construction and two power reductions.
+        return 10 * self.mixed_units_per_example
 
     @torch.no_grad()
     def traffic_fields(self, hiddens):