def watch(self, new_target):
print("watching new target...")
self.backlog_counter = 0
self.target = new_target
self.roots = OrderedSet()
types = OrderedSet()
for e in itertools.chain(all_exps(new_target), *[all_exps(h) for h in self.hints]):
if isinstance(e, ELambda):
continue
for pool in ALL_POOLS:
exp = e
if pool == STATE_POOL:
exp = strip_EStateVar(e)
fvs = free_vars(exp)
if all(v in self.legal_free_vars for v in fvs) and self.is_legal_in_pool(exp, pool):
_on_exp(exp, "new root", pool_name(pool))
exp._root = True
self.roots.add((exp, pool))
if pool == STATE_POOL and all(v in self.state_vars for v in fvs):
self.roots.add((EStateVar(exp).with_type(exp.type), RUNTIME_POOL))
types.add(exp.type)
else:
_on_exp(exp, "rejected root", pool_name(pool))
for b in self.binders:
types.add(b.type)
for t in types:
self.roots.add((construct_value(t), RUNTIME_POOL))
self.roots = list(self.roots)
self.roots.sort(key = lambda tup: tup[0].size())
self._watches = group_by(
enumerate_fragments2(new_target),
k=lambda ctx: (ctx.pool, ctx.e.type),
v=lambda ctxs: sorted(ctxs, key=lambda ctx: -ctx.e.size()))
print("done!")
def visit_EListComprehension(self, e):
collection_types = OrderedSet()
with self.scope():
for clause in e.clauses:
self.visit(clause)
if isinstance(clause, syntax.CPull) and clause.e.type is not DEFAULT_TYPE:
collection_types.add(clause.e.type)
self.visit(e.e)
if all(isinstance(t, syntax.TList) for t in collection_types):
e.type = syntax.TList(e.e.type)
else:
e.type = syntax.TBag(e.e.type)
def cleanup(self):
"""
Remove unused state, queries, and updates.
"""
# sort of like mark-and-sweep
queries_to_keep = OrderedSet(q.name for q in self.query_specs
if q.visibility == Visibility.Public)
state_vars_to_keep = OrderedSet()
changed = True
while changed:
changed = False
for qname in list(queries_to_keep):
if qname in self.query_impls:
for sv in free_vars(self.query_impls[qname]):
if sv not in state_vars_to_keep:
state_vars_to_keep.add(sv)
changed = True
for e in all_exps(self.query_impls[qname].ret):
if isinstance(e, ECall):
if e.func not in queries_to_keep:
queries_to_keep.add(e.func)
changed = True
for op in self.op_specs:
for ((ht, op_name), code) in self.handle_updates.items():
if op.name == op_name:
for qname in _queries_used_by(code):
if qname not in queries_to_keep:
queries_to_keep.add(qname)
changed = True
for sv in state_vars_to_keep:
for qname in _queries_used_by(self.updates[(sv, op.name)]):
if qname not in queries_to_keep:
queries_to_keep.add(qname)
changed = True
# remove old specs
for q in list(self.query_specs):
if q.name not in queries_to_keep:
self.query_specs.remove(q)
# remove old implementations
for qname in list(self.query_impls.keys()):
if qname not in queries_to_keep:
del self.query_impls[qname]
# remove old state vars
self.concrete_state = [
v for v in self.concrete_state
if any(v[0] in free_vars(q) for q in self.query_impls.values())
]
# remove old method implementations
for k in list(self.updates.keys()):
v, op_name = k
if v not in [var for (var, exp) in self.concrete_state]:
del self.updates[k]
def max_storage_size(e, freebies: [Exp] = []):
sizes = OrderedSet()
for x in all_exps(e):
if isinstance(x, EStateVar):
sizes.add(storage_size(x.e, freebies))
return max_of(*sizes, type=INT)
class Learner(object):
def __init__(self, target, assumptions, binders, state_vars, args, legal_free_vars, examples, cost_model, builder, stop_callback, hints, solver):
self.binders = OrderedSet(binders)
self.state_vars = OrderedSet(state_vars)
self.args = OrderedSet(args)
self.legal_free_vars = legal_free_vars
self.stop_callback = stop_callback
self.cost_model = cost_model
self.builder = builder
self.seen = SeenSet()
self.assumptions = assumptions
self.hints = list(hints)
self.solver = solver
self.reset(examples)
self.watch(target)
def compare_costs(self, c1, c2):
self._on_cost_cmp()
solver = self.solver
if solver is not None:
return c1.compare_to(c2, solver=solver)
else:
return c1.compare_to(c2, assumptions=self.assumptions)
def reset(self, examples):
_fates.clear()
self.cache = Cache(binders=self.binders, args=self.args)
self.current_size = -1
self.examples = list(examples)
self.all_examples = instantiate_examples(self.examples, self.binders)
self.seen.clear()
self.builder_iter = ()
self.last_progress = 0
self.backlog = None
self.backlog_counter = 0
self._start_minor_it()
def _check_seen_wf(self):
if enforce_seen_wf.value:
for (e, pool, fp, size, cost) in self.seen.items():
fpnow = self._fingerprint(e)
if fp != fpnow:
print("#" * 40)
print(pprint(e))
print(fp)
print(fpnow)
assert False
def is_legal_in_pool(self, e, pool):
try:
return exp_wf(e, state_vars=self.state_vars, args=self.args, pool=pool, assumptions=self.assumptions)
except ExpIsNotWf as exc:
return False
def watch(self, new_target):
print("watching new target...")
self.backlog_counter = 0
self.target = new_target
self.roots = OrderedSet()
types = OrderedSet()
for e in itertools.chain(all_exps(new_target), *[all_exps(h) for h in self.hints]):
if isinstance(e, ELambda):
continue
for pool in ALL_POOLS:
exp = e
if pool == STATE_POOL:
exp = strip_EStateVar(e)
fvs = free_vars(exp)
if all(v in self.legal_free_vars for v in fvs) and self.is_legal_in_pool(exp, pool):
_on_exp(exp, "new root", pool_name(pool))
exp._root = True
self.roots.add((exp, pool))
if pool == STATE_POOL and all(v in self.state_vars for v in fvs):
self.roots.add((EStateVar(exp).with_type(exp.type), RUNTIME_POOL))
types.add(exp.type)
else:
_on_exp(exp, "rejected root", pool_name(pool))
for b in self.binders:
types.add(b.type)
for t in types:
self.roots.add((construct_value(t), RUNTIME_POOL))
self.roots = list(self.roots)
self.roots.sort(key = lambda tup: tup[0].size())
self._watches = group_by(
enumerate_fragments2(new_target),
k=lambda ctx: (ctx.pool, ctx.e.type),
v=lambda ctxs: sorted(ctxs, key=lambda ctx: -ctx.e.size()))
print("done!")
def _fingerprint(self, e):
self.fpcount += 1
# bs = tuple(sorted(free_vars(e) & self.binders))
bs = (len(free_vars(e) & self.binders),)
return fingerprint(e, self.all_examples) + bs
def _watched_contexts(self, pool, type):
return self._watches.get((pool, type), ())
# return sorted(list(enumerate_fragments2(self.target)), key=lambda ctx: -ctx.e.size())
def _possible_replacements(self, e, pool, cost):
"""
Yields watched expressions that appear as worse versions of the given
expression. There may be more than one.
"""
# return
free_binders = OrderedSet(v for v in free_vars(e) if v in self.binders)
for ctx in self._watched_contexts(pool, e.type):
watched_e = ctx.e
p = ctx.pool
r = ctx.replace_e_with
assert e.type == watched_e.type
assert p == pool
_on_exp(e, "considering replacement of", watched_e)
# if e.type != watched_e.type:
# # _on_exp(e, "wrong type")
# continue
# if p != pool:
# # _on_exp(e, "wrong pool")
# continue
if e == watched_e:
# _on_exp(e, "no change")
continue
unbound_binders = [b for b in free_binders if b not in ctx.bound_vars]
if unbound_binders:
_on_exp(e, "skipped exp with free binders", ", ".join(b.id for b in unbound_binders))
continue
if CHECK_SUBST_COST:
watched_cost = self.cost_model.cost(watched_e, pool=pool)
ordering = self.compare_costs(cost, watched_cost)
if ordering == Cost.WORSE:
_on_exp(e, "skipped worse replacement", pool_name(pool), watched_e)
continue
if ordering == Cost.UNORDERED:
_on_exp(e, "skipped equivalent replacement", pool_name(pool), watched_e)
# print(" e1 = {!r}".format(e))
# print(" e2 = {!r}".format(watched_e))
continue
# assert all(eval_bulk(self.assumptions, self.all_examples))
if all(eval_bulk(EEq(self.target, r(e)), self.all_examples)):
yield (watched_e, e, ctx.facts, r)
else:
_on_exp(e, "visited pointless replacement", watched_e)
def pre_optimize(self, e, pool):
"""
Optimize `e` by replacing its subexpressions with the best cached
versions available (or leaving them untouched if they are new).
"""
if not hasattr(e, "_accel"):
return e
top_level = e
class V(BottomUpRewriter):
def visit_EStateVar(_, e):
return EStateVar(self.pre_optimize(e.e, STATE_POOL)).with_type(e.type)
def visit_ELambda(_, e):
if e.arg not in self.binders and e.arg in free_vars(e.body):
# Derp! Someone made an expression that uses an illegal
# binder. There is no way to compute a fingerprint for the
# body, unfortunately, so we just stop here.
return e
return ELambda(e.arg, super().visit_ADT(e.body)) # optimize children
def visit_Exp(_, e): # do not shadow `self`
if e is top_level:
return super().visit_ADT(e) # optimize children
fp = self._fingerprint(e)
prev = self.seen.find_one(pool, fp)
if prev is None:
return super().visit_ADT(e) # optimize children
prev_exp, prev_size, prev_cost = prev
if prev_exp == e:
return prev_exp
cost = self.cost_model.cost(e, pool)
ordering = self.compare_costs(cost, prev_cost)
if ordering == Cost.BETTER:
return super().visit_ADT(e) # optimize children
else:
# NOTE: no need to optimize children; if it is cached, then
# it is presumably already the best possible.
# if not alpha_equivalent(e, prev_exp):
# print("*** rewriting {} to {}".format(pprint(e), pprint(prev_exp)), file=sys.stderr)
return prev_exp
res = None
try:
res = V().visit(e)
assert exp_wf(res, state_vars=self.state_vars, args=self.args, pool=pool, assumptions=self.assumptions)
if hasattr(e, "_tag"):
res._tag = e._tag
return res
except:
traceback.print_exc(file=sys.stdout)
print("FAILED TO PREOPTIMIZE {} ---> {}".format(pprint(e), pprint(res)))
print(repr(e))
return e
def _start_minor_it(self):
now = datetime.datetime.now()
if hasattr(self, "mstart"):
duration = now - self.mstart
print("> minor duration: {}".format(duration))
print("> next() calls: {}".format(self.ncount))
print("> total exps: {}".format(self.ecount))
print("> exps/s: {}".format(self.ecount / duration.total_seconds()))
print("> cost comparisons: {}".format(self.ccount))
print("> fingerprints: {}".format(self.fpcount))
if self.current_size >= 0:
print("minor iteration {}, |cache|={}".format(self.current_size, len(self.cache)))
self.mstart = now
self.ecount = 0
self.ccount = 0
self.fpcount = 0
self.ncount = 0
def _on_exp(self, e, pool):
# print("next() <<< {p:10} {e}".format(e=pprint(e), p=pool_name(pool)))
self.ecount += 1
def _on_cost_cmp(self):
self.ccount += 1
def next(self):
target_cost = self.cost_model.cost(self.target, RUNTIME_POOL)
self.ncount += 1
while True:
if self.backlog is not None:
if self.stop_callback():
raise StopException()
(e, pool, cost) = self.backlog
improvements = list(self._possible_replacements(e, pool, cost))
if self.backlog_counter < len(improvements):
i = improvements[self.backlog_counter]
self.backlog_counter += 1
return i
else:
self.backlog = None
self.backlog_counter = 0
for (e, pool) in self.builder_iter:
self._on_exp(e, pool)
if self.stop_callback():
raise StopException()
# # Stopgap measure... long story --Calvin
# bad = False
# for x in all_exps(e):
# if isinstance(x, EStateVar):
# if any(v not in self.state_vars for v in free_vars(x.e)):
# bad = True
# _on_exp(e, "skipping due to illegal free vars under EStateVar")
# if bad:
# continue
new_e = self.pre_optimize(e, pool) if preopt.value else e
if new_e is not e:
_on_exp(e, "preoptimized", new_e)
e = new_e
cost = self.cost_model.cost(e, pool)
if pool == RUNTIME_POOL and (self.cost_model.is_monotonic() or hyperaggressive_culling.value) and self.compare_costs(cost, target_cost) == Cost.WORSE:
_on_exp(e, "too expensive", cost, target_cost)
continue
fp = self._fingerprint(e)
prev = list(self.seen.find_all(pool, fp))
should_add = True
if not prev:
_on_exp(e, "new", pool_name(pool))
elif any(alpha_equivalent(e, ee) for (ee, _, _) in prev):
_on_exp(e, "duplicate")
should_add = False
else:
better_than = None
worse_than = None
for prev_exp, prev_size, prev_cost in prev:
self._on_cost_cmp()
ordering = self.compare_costs(cost, prev_cost)
assert ordering in (Cost.WORSE, Cost.BETTER, Cost.UNORDERED)
if enforce_strong_progress.value and ordering != Cost.WORSE:
bad = find_one(all_exps(e), lambda ee: alpha_equivalent(ee, prev_exp))
if bad:
_on_exp(e, "failed strong progress requirement", bad)
should_add = False
break
_on_exp(e, ordering, pool_name(pool), prev_exp)
if ordering == Cost.UNORDERED:
continue
elif ordering == Cost.BETTER:
better_than = (prev_exp, prev_size, prev_cost)
_on_exp(prev_exp, "found better alternative", e)
self.cache.evict(prev_exp, size=prev_size, pool=pool)
self.seen.remove(prev_exp, pool, fp)
if (self.cost_model.is_monotonic() or hyperaggressive_culling.value) and hyperaggressive_eviction.value:
for (cached_e, size, p) in list(self.cache):
if p != pool:
continue
if prev_exp in all_exps(cached_e):
_on_exp(cached_e, "evicted since it contains", prev_exp)
self.cache.evict(cached_e, size=size, pool=pool)
else:
should_add = False
worse_than = (prev_exp, prev_size, prev_cost)
# break
if worse_than and better_than:
print("Uh-oh! Strange cost relationship between")
print(" (1) this exp: {}".format(pprint(e)))
print(" (2) prev. A: {}".format(pprint(worse_than[0])))
print(" (2) prev. B: {}".format(pprint(better_than[0])))
print("e1 = {}".format(repr(e)))
print("e2 = {}".format(repr(worse_than[0])))
print("e3 = {}".format(repr(better_than[0])))
print("(1) vs (2): {}".format(cost.compare_to(worse_than[2], self.assumptions)))
print("(2) vs (3): {}".format(worse_than[2].compare_to(better_than[2], self.assumptions)))
print("(3) vs (1): {}".format(better_than[2].compare_to(cost, self.assumptions)))
# raise Exception("insane cost model behavior")
if should_add:
self.cache.add(e, pool=pool, size=self.current_size)
self.seen.add(e, pool, fp, self.current_size, cost)
self.last_progress = self.current_size
else:
continue
for pr in self._possible_replacements(e, pool, cost):
self.backlog = (e, pool, cost)
self.backlog_counter = 1
return pr
if self.last_progress < (self.current_size+1) // 2:
raise NoMoreImprovements("hit termination condition")
self.current_size += 1
self.builder_iter = self.builder.build(self.cache, self.current_size)
if self.current_size == 0:
self.builder_iter = itertools.chain(self.builder_iter, list(self.roots))
for f, ct in sorted(_fates.items(), key=lambda x: x[1], reverse=True):
print(" {:6} | {}".format(ct, f))
_fates.clear()
self._start_minor_it()
