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python/dune/perftool/sumfact/vectorization.py

@@ -89,7 +89,7 @@ def target_costfunction(sf):
     # The cost of a kernel is given by the difference to the desired target cost.
     # Pitfall: The target cost needs to be weighed to account for this being called
     # on subsets and not on a full vectorization strategy!
-    all_sf, _ = filter_active_inactive_sumfacts()
+    _, all_sf, _ = filter_active_inactive_sumfacts()
     total = len(all_sf)
     target = float(get_form_option("vectorization_target"))
     realcost = costmodel(sf)
@@ -169,7 +169,7 @@ def filter_active_inactive_sumfacts():
     # All sum factorization kernels that get used
     active_sumfacts = [i for i in all_sumfacts if i.stage == 3 or i in basis_sumfacts]
 
-    return active_sumfacts, inactive_sumfacts
+    return all_sumfacts, active_sumfacts, inactive_sumfacts
 
 
 def decide_vectorization_strategy():
@@ -179,7 +179,7 @@ def decide_vectorization_strategy():
     """
     logger = logging.getLogger(__name__)
 
-    active_sumfacts, inactive_sumfacts = filter_active_inactive_sumfacts()
+    all_sumfacts, active_sumfacts, inactive_sumfacts = filter_active_inactive_sumfacts()
 
     # If no vectorization is needed, abort now
     if get_form_option("vectorization_strategy") == "none" or (get_global_context_value("form_type") == "jacobian" and not get_form_option("vectorization_jacobians")):
@@ -215,8 +215,7 @@ def decide_vectorization_strategy():
     sfdict = add_to_frozendict(sfdict, {sf: 0 for sf in inactive_sumfacts})
 
     # Register the results
-    from itertools import chain
-    for sf in chain(active_sumfacts, inactive_sumfacts):
+    for sf in all_sumfacts:
         _cache_vectorization_info(sf, sfdict[sf])