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problem.py
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problem.py
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#
# Copyright 2020, Data61, CSIRO (ABN 41 687 119 230)
#
# SPDX-License-Identifier: BSD-2-Clause
#
from syntax import (Expr, mk_var, Node, true_term, false_term,
fresh_name, word32T, word8T, mk_eq, mk_word32, builtinTs)
import syntax
from target_objects import functions, pairings, trace, printout
import sys
import logic
from logic import azip
class Abort(Exception):
pass
last_problem = [None]
class Problem:
def __init__ (self, pairing, name = None):
if name == None:
name = pairing.name
self.name = 'Problem (%s)' % name
self.pairing = pairing
self.nodes = {}
self.vs = {}
self.next_node_name = 1
self.preds = {}
self.loop_data = {}
self.node_tags = {}
self.node_tag_revs = {}
self.inline_scripts = {}
self.entries = []
self.outputs = {}
self.tarjan_order = []
self.loop_var_analysis_cache = {}
self.known_eqs = {}
self.cached_analysis = {}
self.hook_tag_hints = {}
last_problem[0] = self
def fail_msg (self):
return 'FAILED %s (size %05d)' % (self.name, len(self.nodes))
def alloc_node (self, tag, detail, loop_id = None, hint = None):
name = self.next_node_name
self.next_node_name = name + 1
self.node_tags[name] = (tag, detail)
self.node_tag_revs.setdefault ((tag, detail), [])
self.node_tag_revs[(tag, detail)].append (name)
if loop_id != None:
self.loop_data[name] = ('Mem', loop_id)
return name
def fresh_var (self, name, typ):
name = fresh_name (name, self.vs, typ)
return mk_var (name, typ)
def clone_function (self, fun, tag):
self.nodes = {}
self.vs = syntax.get_vars (fun)
for n in fun.reachable_nodes ():
self.nodes[n] = fun.nodes[n]
detail = (fun.name, n)
self.node_tags[n] = (tag, detail)
self.node_tag_revs.setdefault ((tag, detail), [])
self.node_tag_revs[(tag, detail)].append (n)
self.outputs[tag] = fun.outputs
self.entries = [(fun.entry, tag, fun.name, fun.inputs)]
self.next_node_name = max (self.nodes.keys () + [2]) + 1
self.inline_scripts[tag] = []
def add_function (self, fun, tag, node_renames, loop_id = None):
if not fun.entry:
printout ('Aborting %s: underspecified %s' % (
self.name, fun.name))
raise Abort ()
node_renames.setdefault('Ret', 'Ret')
node_renames.setdefault('Err', 'Err')
new_node_renames = {}
vs = syntax.get_vars (fun)
vs = dict ([(v, fresh_name (v, self.vs, vs[v])) for v in vs])
ns = fun.reachable_nodes ()
check_no_symbols ([fun.nodes[n] for n in ns])
for n in ns:
assert n not in node_renames
node_renames[n] = self.alloc_node (tag, (fun.name, n),
loop_id = loop_id, hint = n)
new_node_renames[n] = node_renames[n]
for n in ns:
self.nodes[node_renames[n]] = syntax.copy_rename (
fun.nodes[n], (vs, node_renames))
return (new_node_renames, vs)
def add_entry_function (self, fun, tag):
(ns, vs) = self.add_function (fun, tag, {})
entry = ns[fun.entry]
args = [(vs[v], typ) for (v, typ) in fun.inputs]
rets = [(vs[v], typ) for (v, typ) in fun.outputs]
self.entries.append((entry, tag, fun.name, args))
self.outputs[tag] = rets
self.inline_scripts[tag] = []
return (args, rets, entry)
def get_entry_details (self, tag):
[(e, t, fname, args)] = [(e, t, fname, args)
for (e, t, fname, args) in self.entries if t == tag]
return (e, fname, args)
def get_entry (self, tag):
(e, fname, args) = self.get_entry_details (tag)
return e
def tags (self):
return self.outputs.keys ()
def entry_exit_renames (self, tags = None):
"""computes the rename set of a function's formal parameters
to the actual input/output variable names at the various entry
and exit points"""
mk = lambda xs, ys: dict ([(x[0], y[0]) for (x, y) in
azip (xs, ys)])
renames = {}
if tags == None:
tags = self.tags ()
for tag in tags:
(_, fname, args) = self.get_entry_details (tag)
fun = functions[fname]
out = self.outputs[tag]
renames[tag + '_IN'] = mk (fun.inputs, args)
renames[tag + '_OUT'] = mk (fun.outputs, out)
return renames
def redirect_conts (self, reds):
for node in self.nodes.itervalues():
if node.kind == 'Cond':
node.left = reds.get(node.left, node.left)
node.right = reds.get(node.right, node.right)
else:
node.cont = reds.get(node.cont, node.cont)
def do_analysis (self):
self.cached_analysis.clear ()
self.compute_preds ()
self.do_loop_analysis ()
def mk_node_graph (self, node_subset = None):
if node_subset == None:
node_subset = self.nodes
return dict ([(n, [c for c in self.nodes[n].get_conts ()
if c in node_subset])
for n in node_subset])
def do_loop_analysis (self):
entries = [e for (e, tag, nm, args) in self.entries]
self.loop_data = {}
graph = self.mk_node_graph ()
comps = logic.tarjan (graph, entries)
self.tarjan_order = []
for (head, tail) in comps:
self.tarjan_order.append (head)
self.tarjan_order.extend (tail)
if not tail and head not in graph[head]:
continue
trace ('Loop (%d, %s)' % (head, tail))
loop_set = set (tail)
loop_set.add (head)
r = self.force_single_loop_return (head, loop_set)
if r != None:
tail.append (r)
loop_set.add (r)
self.tarjan_order.append (r)
self.compute_preds ()
self.loop_data[head] = ('Head', loop_set)
for t in tail:
self.loop_data[t] = ('Mem', head)
# put this in first-to-last order.
self.tarjan_order.reverse ()
def check_no_inner_loops (self):
for loop in self.loop_heads ():
check_no_inner_loop (self, loop)
def force_single_loop_return (self, head, loop_set):
rets = [n for n in self.preds[head] if n in loop_set]
if (len (rets) == 1 and rets[0] != head and
self.nodes[rets[0]].is_noop ()):
return None
r = self.alloc_node (self.node_tags[head][0],
'LoopReturn', loop_id = head)
self.nodes[r] = Node ('Basic', head, [])
for r2 in rets:
self.nodes[r2] = syntax.copy_rename (self.nodes[r2],
({}, {head: r}))
return r
def splittable_points (self, n):
"""splittable points are points which when removed, the loop
'splits' and ceases to be a loop.
equivalently, the set of splittable points is the intersection
of all sub-loops of the loop."""
head = self.loop_id (n)
assert head != None
k = ('Splittables', head)
if k in self.cached_analysis:
return self.cached_analysis[k]
# check if the head point is a split (the inner loop
# check does exactly that)
if has_inner_loop (self, head):
head = logic.get_one_loop_splittable (self,
self.loop_body (head))
if head == None:
return set ()
splits = self.get_loop_splittables (head)
self.cached_analysis[k] = splits
return splits
def get_loop_splittables (self, head):
loop_set = self.loop_body (head)
splittable = dict ([(n, False) for n in loop_set])
arc = [head]
n = head
while True:
ns = [n2 for n2 in self.nodes[n].get_conts ()
if n2 in loop_set]
ns2 = [x for x in ns if x == head or x not in arc]
#n = ns[0]
n = ns2[0]
arc.append (n)
splittable[n] = True
if n == head:
break
last_descs = {}
for i in range (len (arc)):
last_descs[arc[i]] = i
def last_desc (n):
if n in last_descs:
return last_descs[n]
n2s = [n2 for n2 in self.nodes[n].get_conts()
if n2 in loop_set]
last_descs[n] = None
for n2 in n2s:
x = last_desc(n2)
if last_descs[n] == None or x >= last_descs[n]:
last_descs[n] = x
return last_descs[n]
for i in range (len (arc)):
max_arc = max ([last_desc (n)
for n in self.nodes[arc[i]].get_conts ()
if n in loop_set])
for j in range (i + 1, max_arc):
splittable[arc[j]] = False
return set ([n for n in splittable if splittable[n]])
def loop_heads (self):
return [n for n in self.loop_data
if self.loop_data[n][0] == 'Head']
def loop_id (self, n):
if n not in self.loop_data:
return None
elif self.loop_data[n][0] == 'Head':
return n
else:
assert self.loop_data[n][0] == 'Mem'
return self.loop_data[n][1]
def loop_body (self, n):
head = self.loop_id (n)
return self.loop_data[head][1]
def compute_preds (self):
self.preds = logic.compute_preds (self.nodes)
def var_dep_outputs (self, n):
return self.outputs[self.node_tags[n][0]]
def compute_var_dependencies (self):
if 'var_dependencies' in self.cached_analysis:
return self.cached_analysis['var_dependencies']
var_deps = logic.compute_var_deps (self.nodes,
self.var_dep_outputs, self.preds)
var_deps2 = dict ([(n, dict ([(v, None)
for v in var_deps.get (n, [])]))
for n in self.nodes])
self.cached_analysis['var_dependencies'] = var_deps2
return var_deps2
def get_loop_var_analysis (self, var_deps, n):
head = self.loop_id (n)
assert head, n
assert n in self.splittable_points (n)
loop_sort = tuple (sorted (self.loop_body (head)))
node_data = [(self.nodes[n2], sorted (self.preds[n]),
sorted (var_deps[n2].keys ()))
for n2 in loop_sort]
k = (n, loop_sort)
data = (node_data, n)
if k in self.loop_var_analysis_cache:
for (data2, va) in self.loop_var_analysis_cache[k]:
if data2 == data:
return va
va = logic.compute_loop_var_analysis (self, var_deps, n)
group = self.loop_var_analysis_cache.setdefault (k, [])
group.append ((data, va))
del group[:-10]
return va
def save_graph (self, fname):
cols = mk_graph_cols (self.node_tags)
save_graph (self.nodes, fname, cols = cols,
node_tags = self.node_tags)
def save_graph_summ (self, fname):
node_ids = {}
def is_triv (n):
if n not in self.nodes:
return False
if len (self.preds[n]) != 1:
return False
node = self.nodes[n]
if node.kind == 'Basic':
return (True, node.cont)
elif node.kind == 'Cond' and node.right == 'Err':
return (True, node.left)
else:
return False
for n in self.nodes:
if n in node_ids:
continue
ns = []
while is_triv (n):
ns.append (n)
n = is_triv (n)[1]
for n2 in ns:
node_ids[n2] = n
nodes = {}
for n in self.nodes:
if is_triv (n):
continue
nodes[n] = syntax.copy_rename (self.nodes[n],
({}, node_ids))
cols = mk_graph_cols (self.node_tags)
save_graph (nodes, fname, cols = cols,
node_tags = self.node_tags)
def serialise (self):
ss = ['Problem']
for (n, tag, fname, inputs) in self.entries:
xs = ['Entry', '%d' % n, tag, fname,
'%d' % len (inputs)]
for (nm, typ) in inputs:
xs.append (nm)
typ.serialise (xs)
xs.append ('%d' % len (self.outputs[tag]))
for (nm, typ) in self.outputs[tag]:
xs.append (nm)
typ.serialise (xs)
ss.append (' '.join (xs))
for n in self.nodes:
xs = ['%d' % n]
self.nodes[n].serialise (xs)
ss.append (' '.join (xs))
ss.append ('EndProblem')
return ss
def save_serialise (self, fname):
ss = self.serialise ()
f = open (fname, 'w')
for s in ss:
f.write (s + '\n')
f.close ()
def pad_merge_points (self):
self.compute_preds ()
arcs = [(pred, n) for n in self.preds
if len (self.preds[n]) > 1
if n in self.nodes
for pred in self.preds[n]
if (self.nodes[pred].kind != 'Basic'
or self.nodes[pred].upds != [])]
for (pred, n) in arcs:
(tag, _) = self.node_tags[pred]
name = self.alloc_node (tag, 'MergePadding')
self.nodes[name] = Node ('Basic', n, [])
self.nodes[pred] = syntax.copy_rename (self.nodes[pred],
({}, {n: name}))
def function_call_addrs (self):
return [(n, self.nodes[n].fname)
for n in self.nodes if self.nodes[n].kind == 'Call']
def function_calls (self):
return set ([fn for (n, fn) in self.function_call_addrs ()])
def get_extensions (self):
if 'extensions' in self.cached_analysis:
return self.cached_analysis['extensions']
extensions = set ()
for node in self.nodes.itervalues ():
extensions.update (syntax.get_extensions (node))
self.cached_analysis['extensions'] = extensions
return extensions
def replay_inline_script (self, tag, script):
for (detail, idx, fname) in script:
n = self.node_tag_revs[(tag, detail)][idx]
assert self.nodes[n].kind == 'Call', self.nodes[n]
assert self.nodes[n].fname == fname, self.nodes[n]
inline_at_point (self, n, do_analysis = False)
if script:
self.do_analysis ()
def is_reachable_from (self, source, target):
'''discover if graph addr "target" is reachable
from starting node "source"'''
k = ('is_reachable_from', source)
if k in self.cached_analysis:
reachable = self.cached_analysis[k]
if target in reachable:
return reachable[target]
reachable = {}
visit = [source]
while visit:
n = visit.pop ()
if n not in self.nodes:
continue
for n2 in self.nodes[n].get_conts ():
if n2 not in reachable:
reachable[n2] = True
visit.append (n2)
for n in list (self.nodes) + ['Ret', 'Err']:
if n not in reachable:
reachable[n] = False
self.cached_analysis[k] = reachable
return reachable[target]
def is_reachable_without (self, cutpoint, target):
'''discover if graph addr "target" is reachable
without visiting node "cutpoint"
(an oddity: cutpoint itself is considered reachable)'''
k = ('is_reachable_without', cutpoint)
if k in self.cached_analysis:
reachable = self.cached_analysis[k]
if target in reachable:
return reachable[target]
reachable = dict ([(self.get_entry (t), True)
for t in self.tags ()])
for n in self.tarjan_order + ['Ret', 'Err']:
if n in reachable:
continue
reachable[n] = bool ([pred for pred in self.preds[n]
if pred != cutpoint
if reachable.get (pred) == True])
self.cached_analysis[k] = reachable
return reachable[target]
def deserialise (name, lines):
assert lines[0] == 'Problem', lines[0]
assert lines[-1] == 'EndProblem', lines[-1]
i = 1
# not easy to reconstruct pairing
p = Problem (pairing = None, name = name)
while lines[i].startswith ('Entry'):
bits = lines[i].split ()
en = int (bits[1])
tag = bits[2]
fname = bits[3]
(n, inputs) = syntax.parse_list (syntax.parse_lval, bits, 4)
(n, outputs) = syntax.parse_list (syntax.parse_lval, bits, n)
assert n == len (bits), (n, bits)
p.entries.append ((en, tag, fname, inputs))
p.outputs[tag] = outputs
i += 1
for i in range (i, len (lines) - 1):
bits = lines[i].split ()
n = int (bits[0])
node = syntax.parse_node (bits, 1)
p.nodes[n] = node
return p
# trivia
def check_no_symbols (nodes):
import pseudo_compile
symbs = pseudo_compile.nodes_symbols (nodes)
if not symbs:
return
printout ('Aborting %s: undefined symbols %s' % (self.name, symbs))
raise Abort ()
# printing of problem graphs
def sanitise_str (s):
return s.replace ('"', '_').replace ("'", "_").replace (' ', '')
def graph_name (nodes, node_tags, n, prev=None):
if type (n) == str:
return 't_%s_%d' % (n, prev)
if n not in nodes:
return 'unknown_%d' % n
if n not in node_tags:
ident = '%d' % n
else:
(tag, details) = node_tags[n]
if len (details) > 1 and logic.is_int (details[1]):
ident = '%d_%s_%s_0x%x' % (n, tag,
details[0], details[1])
elif type (details) != str:
details = '_'.join (map (str, details))
ident = '%d_%s_%s' % (n, tag, details)
else:
ident = '%d_%s_%s' % (n, tag, details)
ident = sanitise_str (ident)
node = nodes[n]
if node.kind == 'Call':
return 'fcall_%s' % ident
if node.kind == 'Cond':
return ident
if node.kind == 'Basic':
return 'ass_%s' % ident
assert not 'node kind understood'
def graph_node_tooltip (nodes, n):
if n == 'Err':
return 'Error point'
if n == 'Ret':
return 'Return point'
node = nodes[n]
if node.kind == 'Call':
return "%s: call to '%s'" % (n, sanitise_str (node.fname))
if node.kind == 'Cond':
return '%s: conditional node' % n
if node.kind == 'Basic':
var_names = [sanitise_str (x[0][0]) for x in node.upds]
return '%s: assignment to [%s]' % (n, ', '.join (var_names))
assert not 'node kind understood'
def graph_edges (nodes, n):
node = nodes[n]
if node.is_noop ():
return [(node.get_conts () [0], 'N')]
elif node.kind == 'Cond':
return [(node.left, 'T'), (node.right, 'F')]
else:
return [(node.cont, 'C')]
def get_graph_font (n, col):
font = 'fontname = "Arial", fontsize = 20, penwidth=3'
if col:
font = font + ', color=%s, fontcolor=%s' % (col, col)
return font
def get_graph_loops (nodes):
graph = dict ([(n, [c for c in nodes[n].get_conts ()
if type (c) != str]) for n in nodes])
graph['ENTRY'] = list (nodes)
comps = logic.tarjan (graph, ['ENTRY'])
comp_ids = {}
for (head, tail) in comps:
comp_ids[head] = head
for n in tail:
comp_ids[n] = head
loops = set ([(n, n2) for n in graph for n2 in graph[n]
if comp_ids[n] == comp_ids[n2]])
return loops
def make_graph (nodes, cols, node_tags = {}, entries = []):
graph = []
graph.append ('digraph foo {')
loops = get_graph_loops (nodes)
for n in nodes:
n_nm = graph_name (nodes, node_tags, n)
f = get_graph_font (n, cols.get (n))
graph.append ('%s [%s\n label="%s"\n tooltip="%s"];' % (n,
f, n_nm, graph_node_tooltip (nodes, n)))
for (c, l) in graph_edges (nodes, n):
if c in ['Ret', 'Err']:
c_nm = '%s_%s' % (c, n)
if c == 'Ret':
f2 = f + ', shape=doubleoctagon'
else:
f2 = f + ', shape=Mdiamond'
graph.append ('%s [label="%s", %s];'
% (c_nm, c, f2))
else:
c_nm = c
ft = f
if (n, c) in loops:
ft = f + ', penwidth=6'
graph.append ('%s -> %s [label=%s, %s];' % (
n, c_nm, l, ft))
for (i, (n, tag, inps)) in enumerate (entries):
f = get_graph_font (n, cols.get (n))
nm1 = tag + ' ENTRY_POINT'
nm2 = 'entry_point_%d' % i
graph.extend (['%s -> %s [%s];' % (nm2, n, f),
'%s [label = "%s", shape=none, %s];' % (nm2, nm1, f)])
graph.append ('}')
return graph
def print_graph (nodes, cols = {}, entries = []):
for line in make_graph (nodes, cols, entries):
print line
def save_graph (nodes, fname, cols = {}, entries = [], node_tags = {}):
f = open (fname, 'w')
for line in make_graph (nodes, cols = cols, node_tags = node_tags,
entries = entries):
f.write (line + '\n')
f.close ()
def mk_graph_cols (node_tags):
known_cols = {'C': "forestgreen", 'ASM_adj': "darkblue",
'ASM': "darkorange"}
cols = {}
for n in node_tags:
if node_tags[n][0] in known_cols:
cols[n] = known_cols[node_tags[n][0]]
return cols
def make_graph_with_eqs (p, invis = False):
if invis:
invis_s = ', style=invis'
else:
invis_s = ''
cols = mk_graph_cols (p.node_tags)
graph = make_graph (p.nodes, cols = cols)
graph.pop ()
for k in p.known_eqs:
if k == 'Hyps':
continue
(n_vc_x, tag_x) = k
nm1 = graph_name (p.nodes, p.node_tags, n_vc_x[0])
for (x, n_vc_y, tag_y, y, hyps) in p.known_eqs[k]:
nm2 = graph_name (p.nodes, p.node_tags, n_vc_y[0])
graph.extend ([('%s -> %s [ dir = back, color = blue, '
'penwidth = 3, weight = 0 %s ]')
% (nm2, nm1, invis_s)])
graph.append ('}')
return graph
def save_graph_with_eqs (p, fname = 'diagram.dot', invis = False):
graph = make_graph_with_eqs (p, invis = invis)
f = open (fname, 'w')
for s in graph:
f.write (s + '\n')
f.close ()
def get_problem_vars (p):
inout = set.union (* ([set(xs) for xs in p.outputs.itervalues ()]
+ [set (args) for (_, _, _, args) in p.entries]))
vs = dict(inout)
for node in p.nodes.itervalues():
syntax.get_node_vars(node, vs)
return vs
def is_trivial_fun (fun):
for node in fun.nodes.itervalues ():
if node.is_noop ():
continue
if node.kind == 'Call':
return False
elif node.kind == 'Basic':
for (lv, v) in node.upds:
if v.kind not in ['Var', 'Num']:
return False
elif node.kind == 'Cond':
if node.cond.kind != 'Var' and node.cond not in [
true_term, false_term]:
return False
return True
last_alt_nodes = [0]
def avail_val (vs, typ):
for (nm, typ2) in vs:
if typ2 == typ:
return mk_var (nm, typ2)
return logic.default_val (typ)
def inline_at_point (p, n, do_analysis = True):
node = p.nodes[n]
if node.kind != 'Call':
return
f_nm = node.fname
fun = functions[f_nm]
(tag, detail) = p.node_tags[n]
idx = p.node_tag_revs[(tag, detail)].index (n)
p.inline_scripts[tag].append ((detail, idx, f_nm))
trace ('Inlining %s into %s' % (f_nm, p.name))
if n in p.loop_data:
trace (' inlining into loop %d!' % p.loop_id (n))
ex = p.alloc_node (tag, (f_nm, 'RetToCaller'))
(ns, vs) = p.add_function (fun, tag, {'Ret': ex})
en = ns[fun.entry]
inp_lvs = [(vs[v], typ) for (v, typ) in fun.inputs]
p.nodes[n] = Node ('Basic', en, azip (inp_lvs, node.args))
out_vs = [mk_var (vs[v], typ) for (v, typ) in fun.outputs]
p.nodes[ex] = Node ('Basic', node.cont, azip (node.rets, out_vs))
p.cached_analysis.clear ()
if do_analysis:
p.do_analysis ()
trace ('Problem size now %d' % len(p.nodes))
sys.stdin.flush ()
return ns.values ()
def loop_body_inner_loops (p, head, loop_body):
loop_set_all = set (loop_body)
loop_set = loop_set_all - set ([head])
graph = dict([(n, [c for c in p.nodes[n].get_conts ()
if c in loop_set])
for n in loop_set_all])
comps = logic.tarjan (graph, [head])
assert sum ([1 + len (t) for (_, t) in comps]) == len (loop_set_all)
return [comp for comp in comps if comp[1]]
def loop_inner_loops (p, head):
k = ('inner_loop_set', head)
if k in p.cached_analysis:
return p.cached_analysis[k]
res = loop_body_inner_loops (p, head, p.loop_body (head))
p.cached_analysis[k] = res
return res
def loop_heads_including_inner (p):
heads = p.loop_heads ()
check = [(head, p.loop_body (head)) for head in heads]
while check:
(head, body) = check.pop ()
comps = loop_body_inner_loops (p, head, body)
heads.extend ([head for (head, _) in comps])
check.extend ([(head, [head] + list (body))
for (head, body) in comps])
return heads
def check_no_inner_loop (p, head):
subs = loop_inner_loops (p, head)
if subs:
printout ('Aborting %s, complex loop' % p.name)
trace (' sub-loops %s of loop at %s' % (subs, head))
for (h, _) in subs:
trace (' head %d tagged %s' % (h, p.node_tags[h]))
raise Abort ()
def has_inner_loop (p, head):
return bool (loop_inner_loops (p, head))
def fun_has_inner_loop (f):
p = f.as_problem (Problem)
p.do_analysis ()
return bool ([head for head in p.loop_heads ()
if has_inner_loop (p, head)])
def loop_var_analysis (p, head, tail):
# getting the set of variables that go round the loop
nodes = set (tail)
nodes.add (head)
used_vs = set ([])
created_vs_at = {}
visit = []
def process_node (n, created):
if p.nodes[n].is_noop ():
lvals = set ([])
else:
vs = syntax.get_node_rvals (p.nodes[n])
for rv in vs.iteritems ():
if rv not in created:
used_vs.add (rv)
lvals = set (p.nodes[n].get_lvals ())
created = set.union (created, lvals)
created_vs_at[n] = created
visit.extend (p.nodes[n].get_conts ())
process_node (head, set ([]))
while visit:
n = visit.pop ()
if (n not in nodes) or (n in created_vs_at):
continue
if not all ([pr in created_vs_at for pr in p.preds[n]]):
continue
pre_created = [created_vs_at[pr] for pr in p.preds[n]]
process_node (n, set.union (* pre_created))
final_pre_created = [created_vs_at[pr] for pr in p.preds[head]
if pr in nodes]
created = set.union (* final_pre_created)
loop_vs = set.intersection (created, used_vs)
trace ('Loop vars at head: %s' % loop_vs)
return loop_vs