def do_mapping(src_int_rep, tgt_int_rep, src_pred_bins={}, tgt_pred_bins={}):
src_preds = get_predicates(src_int_rep.get_all_rules(), src_int_rep.get_roles())
tgt_preds = get_predicates(tgt_int_rep.get_all_rules(), tgt_int_rep.get_roles())
# 0 is the default bin that can map to anything else. All predicates that aren't
# assigned bins get 0
src_preds = [(p, src_pred_bins.get(p.get_name(), 0)) for p in src_preds]
tgt_preds = [(p, tgt_pred_bins.get(p.get_name(), 0)) for p in tgt_preds]
# a list whose elements record which commitments were made at each
# step, which commitments are suppressed, number of other rule matches
# invalidated, and the score
history = [] # [(partial map, rule match, suppressed, #invalidated, score)]
mapping = PartialMap.create(src_int_rep, src_preds, tgt_int_rep, tgt_preds)
history.append(CommitPoint(mapping))
best_map = None
legals_mapped = False
for x in range(1):
bottomed_out = False
while not bottomed_out:
next_mapping = mapping.copy()
if not legals_mapped:
sr, tr, invalidated, score = next_mapping.add_best_legal_rule_match()
if sr is None:
legals_mapped = True
continue
else:
sr, tr, bmap, score = next_mapping.get_best_rule_match()
if sr is None:
# there's no matches at this point, probably because they're all
# suppressed
history[-1].can_unroll = False
bottomed_out = True
continue
invalidated = next_mapping.add_rule_match(sr, tr, bmap)
history[-1].rule_match = (sr, tr)
history[-1].invalidated = invalidated
history[-1].score = score
if next_mapping.complete():
bottomed_out = True
num_matched = len(mapping.get_pred_matches())
# print "Matched %d out of %d source and %d target predicates" % \
# (num_matched, len(src_preds), len(tgt_preds))
if best_map == None:
best_map = next_mapping
# print 'best map score is now ', best_map.score()
else:
if best_map.score() < next_mapping.score():
best_map = next_mapping
# print 'best map score is now ', best_map.score()
else:
mapping = next_mapping
history.append(CommitPoint(mapping))
# okay, now we have to decide where to unroll to
# unroll to most invalidated
# unroll_i, invalidated = find_max(history, lambda x: x.invalidated)
# print "unrolling to %d, with %d invalidations" % (unroll_i, invalidated)
# unroll to most degrees of freedom
unroll_i, dof = find_max(history, lambda x: x.map.src_rdof(x.rule_match[0]))
# print "unrolling to %d, with %d dof" % (unroll_i, dof)
history = history[: unroll_i + 1]
mapping = history[unroll_i].map
history[unroll_i].suppress_last()
return best_map
def do_mapping(src_int_rep, tgt_int_rep, src_pred_bins = {}, tgt_pred_bins = {}):
src_preds = get_predicates(src_int_rep.get_all_rules(), src_int_rep.get_roles())
tgt_preds = get_predicates(tgt_int_rep.get_all_rules(), tgt_int_rep.get_roles())
src_pred_bins1 = src_pred_bins.copy()
tgt_pred_bins1 = tgt_pred_bins.copy()
# try the heuristic that any predicate that has a number is a different type from
# predicates that don't involve numbers
num_place_types = set([placetype.COORD, placetype.NUM_MAX, placetype.NUM_MIN, placetype.NUM])
for pred_set, type_bins in [(src_preds, src_pred_bins1), (tgt_preds, tgt_pred_bins1)]:
for p in pred_set:
if p not in type_bins and len(set(p.get_place_types()) & num_place_types) > 0:
type_bins[p] = 100
# 0 is the default bin that can map to anything else. All predicates that aren't
# assigned bins get 0
src_preds1 = [(p, src_pred_bins1.get(p, 0)) for p in src_preds]
tgt_preds1 = [(p, tgt_pred_bins1.get(p, 0)) for p in tgt_preds]
# a list whose elements record which commitments were made at each
# step, which commitments are suppressed, number of other rule matches
# invalidated, and the score
history = [] # [(partial map, rule match, suppressed, #invalidated, score)]
mapping = PartialMap.create(src_int_rep, src_preds1, tgt_int_rep, tgt_preds1)
history.append(CommitPoint(mapping))
best_map = None
for x in range(options.NUM_RETRIES):
bottomed_out = False
while not bottomed_out:
next_mapping = mapping.copy()
sr, tr, bmap, score = next_mapping.get_best_rule_match()
if sr is None:
# there's no matches at this point, probably because they're all
# suppressed
history[-1].can_unroll = False
bottomed_out = True
break
invalidated = next_mapping.add_rule_match(sr, tr, bmap)
history[-1].rule_match = (sr, tr)
history[-1].invalidated = invalidated
history[-1].score = score
if next_mapping.complete():
bottomed_out = True
num_matched = len(next_mapping.get_pred_matches())
#print "Matched %d out of %d source and %d target predicates" % \
# (num_matched, len(src_preds), len(tgt_preds))
if best_map == None:
best_map = next_mapping
#print 'best map score is now ', best_map.score()
else:
if best_map.score() < next_mapping.score():
best_map = next_mapping
#print 'best map score is now ', best_map.score()
else:
mapping = next_mapping
history.append(CommitPoint(mapping))
# okay, now we have to decide where to unroll to
# unroll to most invalidated
#unroll_i, invalidated = find_max(history, lambda x: x.invalidated)
#print "unrolling to %d, with %d invalidations" % (unroll_i, invalidated)
# unroll to most degrees of freedom
#unroll_i, dof = find_max(history, lambda x: x.map.src_rdof(x.rule_match[0]))
#print "unrolling to %d, with %d dof" % (unroll_i, dof)
unroll_i = 0
history = history[:unroll_i+1]
mapping = history[unroll_i].map
history[unroll_i].suppress_last()
print "UNROLL UNROLL UNROLL UNROLL UNROLL UNROLL UNROLL UNROLL"
return best_map
def do_mapping(src_int_rep, tgt_int_rep, src_pred_bins={}, tgt_pred_bins={}):
src_preds = get_predicates(src_int_rep.get_all_rules(),
src_int_rep.get_roles())
tgt_preds = get_predicates(tgt_int_rep.get_all_rules(),
tgt_int_rep.get_roles())
# 0 is the default bin that can map to anything else. All predicates that aren't
# assigned bins get 0
src_preds = [(p, src_pred_bins.get(p.get_name(), 0)) for p in src_preds]
tgt_preds = [(p, tgt_pred_bins.get(p.get_name(), 0)) for p in tgt_preds]
# a list whose elements record which commitments were made at each
# step, which commitments are suppressed, number of other rule matches
# invalidated, and the score
history = [
] # [(partial map, rule match, suppressed, #invalidated, score)]
mapping = PartialMap.create(src_int_rep, src_preds, tgt_int_rep, tgt_preds)
history.append(CommitPoint(mapping))
best_map = None
legals_mapped = False
for x in range(1):
bottomed_out = False
while not bottomed_out:
next_mapping = mapping.copy()
if not legals_mapped:
sr, tr, invalidated, score = next_mapping.add_best_legal_rule_match(
)
if sr is None:
legals_mapped = True
continue
else:
sr, tr, bmap, score = next_mapping.get_best_rule_match()
if sr is None:
# there's no matches at this point, probably because they're all
# suppressed
history[-1].can_unroll = False
bottomed_out = True
continue
invalidated = next_mapping.add_rule_match(sr, tr, bmap)
history[-1].rule_match = (sr, tr)
history[-1].invalidated = invalidated
history[-1].score = score
if next_mapping.complete():
bottomed_out = True
num_matched = len(mapping.get_pred_matches())
#print "Matched %d out of %d source and %d target predicates" % \
# (num_matched, len(src_preds), len(tgt_preds))
if best_map == None:
best_map = next_mapping
#print 'best map score is now ', best_map.score()
else:
if best_map.score() < next_mapping.score():
best_map = next_mapping
#print 'best map score is now ', best_map.score()
else:
mapping = next_mapping
history.append(CommitPoint(mapping))
# okay, now we have to decide where to unroll to
# unroll to most invalidated
#unroll_i, invalidated = find_max(history, lambda x: x.invalidated)
#print "unrolling to %d, with %d invalidations" % (unroll_i, invalidated)
# unroll to most degrees of freedom
unroll_i, dof = find_max(history,
lambda x: x.map.src_rdof(x.rule_match[0]))
#print "unrolling to %d, with %d dof" % (unroll_i, dof)
history = history[:unroll_i + 1]
mapping = history[unroll_i].map
history[unroll_i].suppress_last()
return best_map