def to_canonical_IO(self):
self.equation = [
replace_all( eq, canonical_rules + canonicalIO_rules + simplify_rules ) \
for eq in self.equation
]
# Minimize number of nodes among:
# 1) as is,
# 2) applying minus to both sides, and
# 3) applying transpose to both sides
minimal = []
for eq in self.equation:
alternative_forms = [
eq,
simplify(
to_canonical(Equal([Minus([eq.lhs()]),
Minus([eq.rhs()])]))),
simplify(
to_canonical(
Equal([Transpose([eq.lhs()]),
Transpose([eq.rhs()])])))
]
_, new = min([(alt.num_nodes(), alt) for alt in alternative_forms])
minimal.append(new)
# Set minimal forms
self.equation = NList(minimal)
#
nodes = list(
itertools.chain(*[[node for node in eq.iterate_preorder()]
for eq in self.equation]))
self.operands = [op for op in self.operands if op in nodes]
def normalize_minus( expr ):
ld = PatternDot("ld")
md = PatternDot("md")
l = PatternStar("l")
r = PatternStar("r")
return replace_all( expr, [RewriteRule( Times([ ld, l, Minus([md]), r ]),
Replacement( lambda d: Times([ Minus([d["ld"]]), d["l"], d["md"], d["r"]]) )),
RewriteRule( Times([ Minus([Minus([ld])]), l ]),
Replacement( lambda d: Times([ d["ld"], d["l"]]) )),
RewriteRule( Minus([ Times([ ld, l ]) ]),
Replacement( lambda d: Times([ Minus([d["ld"]]), d["l"]]) )) ] )
def express_in_terms_of_input(self, assignments):
# In LU, there may be (overwritable) inputs as lhs
for a in assignments:
if a.children[0].children[0].isInput():
raise Exception
assignments = [
a for a in assignments if not a.children[0].children[0].isInput()
]
expand_rules = list(
itertools.chain(*self.expr_to_rule_lhs_rhs(assignments)))
new_ass = []
for expr in assignments:
new = copy.deepcopy(expr)
new.children[1] = simplify(
to_canonical(replace_all(new.children[1], expand_rules)))
new_ass.append(new)
return new_ass
def all_tilings( expr ):
ongoing = [ [expr] ]
while len( ongoing ) > 0:
alg = ongoing.pop()
to_tile = alg.pop()
if isOperand( to_tile ):
alg.append( to_tile )
yield alg
continue
to_tile = replace_all( copy.deepcopy( to_tile), grouping_rules )
for collection in reversed(instruction_set):
matched_in_this_level = False ### These are just control vars
### to avoid redundancies
for instr in collection:
for node in to_tile.iterate_preorder():
# To avoid redundancies
matched_this_node = [] ###
if isinstance( instr, tuple ): # A way to deactivate some for quick development/debugging?
continue
for _m in instr.match( node ):
matched_in_this_level = True ###
#_T = TOS.new_temp()
new = copy.deepcopy( to_tile )
#tile, new = instr.tile( new, _m, _T )
tile, new = instr.tile( new, node, _m )
lhs, rhs = tile.get_children()
if rhs not in matched_this_node: ###
matched_this_node.append( rhs ) ###
ongoing.append( alg[:] + [tile, new] )
# Set size of new temporary
lhs.children[0].size = rhs.get_size()
else:
# Aestetic. Simply to avoid missing T? values.
TOS.push_back_temp( )
TOS._TOS.unset_operand( tile.children[0].children[0] )
if matched_in_this_level: ###
break
def find_updates_v2(self, before, after):
# If a part is (partially) computed in the before and
# does not appear in the after or
# going from before to after requires undoing some computation
# it is potentially unstable, and more expensive: ignore
dict_bef = dict([(str(u.get_children()[0]), u) for u in before])
dict_aft = dict([(str(u.get_children()[0]), u) for u in after])
ignore = False
quadrant = None
for k, v in dict_bef.items():
if k not in dict_aft:
ignore = True
break
else:
rules = self.expr_to_rule_rhs_lhs([v])
rules = list(itertools.chain(*rules))
expr_copy = copy.deepcopy(dict_aft[k])
t = replace(expr_copy, rules)
#if v == replace( expr_copy, rules ):
if dict_aft[k] == t:
ignore = True
break
if ignore:
print("[INFO] Skipping invariant: %s" % reason)
return None
#
# Wrap outputs for before and after
WrapBefOut = WrapOutBef
for u in before:
u.children[0] = NList([WrapBefOut(l) for l in u.children[0]])
#
wrap_rules_after = []
for u in after:
u.children[0] = NList([WrapOutAft(l) for l in u.children[0]])
# replace before in after
wrap_rules_before = []
for u in before:
print(u)
lhs, rhs = u.get_children()
if len(lhs.children) > 1:
continue
rules = self.expr_to_rule_rhs_lhs([u])
wrap_rules_before.append(list(itertools.chain(*rules)))
#
for i, rule in enumerate(reversed(wrap_rules_before)):
idx = len(wrap_rules_before) - i - 1
for j in range(idx - 1, -1, -1):
for _rule in rule:
_rule.pattern = replace_all(_rule.pattern,
wrap_rules_before[j])
wrap_rules_before = list(itertools.chain(*wrap_rules_before))
#
for u in after:
_, rhs = u.get_children()
u.children[1] = simplify(
to_canonical(replace_all(copy.deepcopy(rhs),
wrap_rules_before)))
# replace after in after
done = False
while not done:
# replace after in after
wrap_rules_after = []
for u in after:
lhs, rhs = u.get_children()
if len(lhs.children) > 1:
wrap_rules_after.append([])
continue
rules = self.expr_to_rule_rhs_lhs([u])
wrap_rules_after.append(list(itertools.chain(*rules)))
#
after_top = [copy.deepcopy(u) for u in after]
for i, u in enumerate(after):
_, rhs = u.get_children()
rules = list(
itertools.chain.from_iterable(wrap_rules_after[:i] +
wrap_rules_after[i + 1:]))
u.children[1] = simplify(
to_canonical(replace_all(copy.deepcopy(rhs), rules)))
done = True
for top, bot in zip(after_top, after):
if top != bot:
done = False
break
# [TODO] Multiple lhss, won't work
updates = []
for u in after:
lhs, rhs = u.get_children()
lhs = lhs.children[0] # NList[op] -> op
if isinstance(rhs, WrapBefOut) and isinstance(lhs, WrapOutAft) and \
matchq(lhs.children[0], rhs.children[0]):
continue
updates.append(u)
#
tiled_updates = []
for u in updates:
print("* ", u)
tilings = list(tile_expr(u))
if len(tilings) > 1:
print("[WARNING] Multiple (%d) tilings for expression %s" %
(len(tilings), u))
print(" Discarding all but one")
tiled_updates.extend(tilings[0])
tiled_updates = sort(tiled_updates)
print("* Tiled update")
for t in tiled_updates:
print("* ", t)
# Drop WrapOutBef's
# Drop WrapOutAft's
s = PatternDot("s")
updates = []
for u in tiled_updates:
u = replace_all(
u, [RewriteRule(WrapOutAft(s), Replacement(lambda d: d["s"]))])
u = replace_all(
u, [RewriteRule(WrapOutBef(s), Replacement(lambda d: d["s"]))])
updates.append(u)
return updates
def find_updates(self, before, after):
# If a part is (partially) computed in the before and
# does not appear in the after or
# going from before to after requires undoing some computation
# it is potentially unstable, and more expensive: ignore
try:
before_finputs = self.express_in_terms_of_input(before)
after_finputs = self.express_in_terms_of_input(after)
except:
# [TODO] In LU's variant 5, parts of A appear as lhs's
return None
#
dict_bef = dict([(str(u.get_children()[0]), u)
for u in before_finputs])
dict_aft = dict([(str(u.get_children()[0]), u) for u in after_finputs])
same = []
ignore = False
for k, v in dict_bef.items():
if k in dict_aft and matchq(v, dict_aft[k]):
same.extend(v.children[0].children)
if k not in dict_aft:
ignore = True
reason = "%s not in %s" % (k, dict_aft.keys())
break
else:
rules = self.expr_to_rule_rhs_lhs([v])
rules = list(itertools.chain(*rules))
expr_copy = copy.deepcopy(dict_aft[k])
t = replace(expr_copy, rules)
#if v == replace( expr_copy, rules ):
if dict_aft[k] == t:
ignore = True
reason = "%s would require undoing job" % k
break
if ignore:
print("[INFO] Skipping invariant: %s" % reason)
return None
#
# Wrap outputs for before and after
WrapBefOut = WrapOutBef
lhss = []
for u in before:
lhss.extend(u.children[0])
u.children[0] = NList([WrapBefOut(l) for l in u.children[0]])
for u in before:
u.children[1] = replace(
u.children[1],
[RewriteRule(l, Replacement(WrapBefOut(l))) for l in lhss])
#
lhss = []
for u in after:
lhss.extend(u.children[0])
u.children[0] = NList([WrapOutAft(l) for l in u.children[0]])
wrap_rules_after = \
[
RewriteRule(l, Replacement(WrapBefOut(l))) if l in same else
RewriteRule(l, Replacement(WrapOutAft(l))) for l in lhss
]
for u in after:
u.children[1] = replace(u.children[1], wrap_rules_after)
# replace before in before
wrap_rules_before = []
for u in before:
lhs, rhs = u.get_children()
#if len(lhs.children) > 1:
#wrap_rules_before.append([])
#continue
rules = self.expr_to_rule_rhs_lhs([u])
wrap_rules_before.append(list(itertools.chain(*rules)))
#
new_rules = []
for i, rules in enumerate(wrap_rules_before):
new_rules.append([])
for rule in rules:
new_r = copy.deepcopy(rule)
new_r.pattern = replace_all(
new_r.pattern,
list(
itertools.chain.from_iterable(wrap_rules_before[:i] +
wrap_rules_before[i +
1:])))
if new_r.pattern != rule.pattern:
new_rules[-1].append(new_r)
for r1, r2 in zip(new_rules, wrap_rules_before):
r2.extend(r1)
#
wrap_rules_before = list(itertools.chain(*wrap_rules_before))
done = False
while not done:
after_top = [copy.deepcopy(u) for u in after]
for i, u in enumerate(after):
_, rhs = u.get_children()
u.children[1] = simplify(
to_canonical(
replace_all(copy.deepcopy(rhs), wrap_rules_before)))
done = True
for top, bot in zip(after_top, after):
if top != bot:
done = False
break
# replace after in after
done = False
while not done:
# replace after in after
wrap_rules_after = []
for u in after:
lhs, rhs = u.get_children()
#if len(lhs.children) > 1:
#wrap_rules_after.append([])
#continue
rules = self.expr_to_rule_rhs_lhs([u])
wrap_rules_after.append(list(itertools.chain(*rules)))
#
after_top = [copy.deepcopy(u) for u in after]
for i, u in enumerate(after):
_, rhs = u.get_children()
rules = list(
itertools.chain.from_iterable(wrap_rules_after[:i] +
wrap_rules_after[i + 1:]))
u.children[1] = simplify(
to_canonical(replace_all(copy.deepcopy(rhs), rules)))
done = True
for top, bot in zip(after_top, after):
if top != bot:
done = False
break
# [TODO] Multiple lhss, won't work
updates = []
for u in after:
lhs, rhs = u.get_children()
if len(lhs.children) == 1:
lhs = lhs.children[0] # NList[op] -> op
if isinstance(rhs, WrapBefOut) and isinstance(lhs, WrapOutAft) and \
matchq(lhs.children[0], rhs.children[0]):
continue
elif not isinstance(rhs,
NList): # multiple outputs/predicate in rhs,
# but not complete (otherwise it would be NList)
pass
else:
to_skip = True
for l, r in zip(lhs.children, rhs.children):
if not( isinstance(r, WrapBefOut) and isinstance(l, WrapOutAft) and \
matchq(l.children[0], r.children[0]) ):
to_skip = False
break
if to_skip:
continue
updates.append(u)
#
tiled_updates = []
for u in updates:
print("* ", u)
tilings = list(tile_expr(u))
if len(tilings) > 1:
print("[WARNING] Multiple (%d) tilings for expression %s" %
(len(tilings), u))
print(" Discarding all but one")
tiled_updates.extend(tilings[0])
tiled_updates = sort(tiled_updates)
print("* Tiled update")
for t in tiled_updates:
print("* ", t)
# Drop WrapOutBef's
# Drop WrapOutAft's
s = PatternDot("s")
updates = []
for u in tiled_updates:
u = replace_all(
u, [RewriteRule(WrapOutAft(s), Replacement(lambda d: d["s"]))])
u = replace_all(
u, [RewriteRule(WrapOutBef(s), Replacement(lambda d: d["s"]))])
updates.append(u)
return updates
def generate_loop_based_algorithms(self):
print("* Generating Loop-based algorithms...")
self.algs = []
variant = 1
for pme, linvs in zip(self.pmes, self.linvs):
algs = []
for linv in linvs:
print("* ")
print("* Loop invariant", variant)
for expr in linv.expressions:
print("* ", expr)
print("* ")
trav, init_state, _ = linv.traversals[
0] # this would be another for loop
init = self.algorithm_initialization(init_state)
print("* Init")
#print( init_state )
print("* ", init)
s = PatternDot("s")
init = [
replace_all(i, [
RewriteRule(WrapOutBef(s),
Replacement(lambda d: d["s"]))
]) for i in init
]
print("* Before")
repart, before = self.generate_predicate_before(
pme, trav, linv.expressions, linv)
print("* After")
reversed_trav = dict([(k, (r * -1, c * -1))
for k, (r, c) in trav.items()])
cont_with, after = self.generate_predicate_before(
pme, reversed_trav, linv.expressions, linv)
# find updates
print("* Updates")
updates = self.find_updates(before, after)
if updates is None:
#variant += 1
continue
# Tile updates
for u in updates:
infer_properties(u)
final_updates = []
# [DIEGO] Fixing some output pieces being labeled as input
outputs = []
for u in updates:
lhs, rhs = u.children
for l in lhs:
if not l.isTemporary():
outputs.append(l)
l.set_property(OUTPUT)
#
for u in updates:
#[DIEGO] u.children[0].children[0].set_property( OUTPUT )
for node in u.children[1].iterate_preorder():
#if isinstance(node, Symbol):
if isinstance(node, Symbol) and node not in outputs:
node.set_property(INPUT)
#
#copy_u = replace( copy.deepcopy(u), known_ops_single )
copy_u = copy.deepcopy(u)
copy_u = tile_expr(copy.deepcopy(copy_u))[0] # One tiling
final_updates.extend(copy_u)
if len(updates) == 0:
print("No updates!! Should only happen in copy")
continue
algs.append(
Algorithm(linv, variant, init, repart, cont_with, before,
after, final_updates))
algs[-1].prepare_for_code_generation()
variant += 1
self.algs.append(algs)
def learn_pattern(self):
inops = [op for op in self.operands if op.isInput()]
outops = [op for op in self.operands if op.isOutput()]
#
single_assignment = len( self.equation.children ) == 1 and \
isinstance(self.equation.children[0].children[0], Symbol) # eq.lhs.single_entry_in_NL
#
op_to_pattern = [
RewriteRule(op, Replacement("PatternDot(%s.name)" % op.name))
for op in self.operands
]
pattern = NList([
replace_all(copy.deepcopy(eq), op_to_pattern)
for eq in self.equation
])
if single_assignment:
props_str = [
symbol_props_to_constraints_no_io(op) for op in self.operands
]
constraint = Constraint(" and ".join(
[prop for prop in props_str if prop]))
else:
constraint = Constraint(" and ".join(
[symbol_props_to_constraints(op) for op in self.operands]))
# [TODO] Tuple for get_size
replacement = Replacement(
"Equal([ NList([%s]), Predicate( \"%s\", [%s], [%s] ) ])" %
(", ".join([op.name for op in outops]), self.name, ", ".join([
op.name for op in inops
]), ", ".join(["%s.get_size()" % op.get_name() for op in outops])))
# [TODO] This should be part of the verbose option
print("* Learnt pattern")
print("* ", pattern, end="")
if constraint.to_eval:
print("with ", constraint.to_eval)
print(" --> ")
print("* ", replacement.to_eval)
print("**********************************")
# [TODO] Maybe sort known ops by specificity (a la mathematica)
#known_ops.insert( 0, RewriteRule( (pattern, constraint), replacement ) )
if single_assignment:
expr = pattern.children[0]
expr.children[0] = NList([expr.children[0]])
known_ops_single.insert(
0, RewriteRule((expr, constraint), replacement))
# With minus
replacement = Replacement(
"Equal([ NList([%s]), Minus([ Predicate( \"%s\", [%s], [%s] ) ]) ])"
% (", ".join([op.name for op in outops]), self.name, ", ".join(
[op.name for op in inops]), ", ".join(
["%s.get_size()" % op.get_name() for op in outops])))
expr = copy.deepcopy(expr)
expr.children[1] = Minus([expr.children[1]])
expr.children[1] = normalize_minus(copy.deepcopy(expr.children[1]))
known_ops_single.insert(
0, RewriteRule((expr, constraint), replacement))
#with open(os.path.join("OUTPUT", self.name+"_patterns"), "wb") as patt_f:
#pickle.dump( known_ops_single[1], patt_f )
#pickle.dump( known_ops_single[0], patt_f )
else:
known_ops.insert(0, RewriteRule((pattern, constraint),
replacement))
with open(os.path.join("OUTPUT", self.name + "_patterns"),
"wb") as patt_f:
pickle.dump(known_ops[0], patt_f)
pattern = Equal([
NList([PatternDot(op.get_name()) for op in outops]),
Predicate(self.name, [PatternDot(op.get_name()) for op in inops],
[op.get_size() for op in outops])
])
replacement = Replacement(equation2replacement(self.equation))
op_to_implicit.append(RewriteRule(pattern, replacement))
def simplify(expr):
return replace_all(expr, simplify_rules)
def to_canonicalIO(expr):
return replace_all(expr, canonical_rules + canonicalIO_rules)
def to_canonical(expr):
return replace_all(expr, canonical_rules + simplify_rules_base)