def add_query(self, q : Query):
"""
Given a query in terms of abstract state, add an initial concrete
implementation.
"""
print("Adding query {}...".format(q.name))
self.query_specs.append(q)
fvs = free_vars(q)
# initial rep
qargs = set(EVar(a).with_type(t) for (a, t) in q.args)
rep, ret = tease_apart(wrap_naked_statevars(q.ret, self.abstract_state))
self.set_impl(q, rep, ret)
def run(self):
print("STARTING IMPROVEMENT JOB {}".format(self.q.name))
os.makedirs(log_dir.value, exist_ok=True)
with open(os.path.join(log_dir.value, "{}.log".format(self.q.name)),
"w",
buffering=LINE_BUFFER_MODE) as f:
sys.stdout = f
print("STARTING IMPROVEMENT JOB {}".format(self.q.name))
print(pprint(self.q))
if nice_children.value:
os.nice(20)
ctx = RootCtx(
state_vars=self.state,
args=[EVar(v).with_type(t) for (v, t) in self.q.args],
funcs=self.funcs)
cost_model = CostModel(
funcs=ctx.funcs(),
assumptions=EAll(self.assumptions),
freebies=[h.e for h in self.hints if isinstance(h, EStateVar)])
try:
for expr in itertools.chain(
(self.q.ret, ),
core.improve(target=self.q.ret,
assumptions=EAll(self.assumptions),
context=ctx,
hints=self.hints,
stop_callback=lambda: self.stop_requested,
cost_model=cost_model)):
new_rep, new_ret = tease_apart(expr)
self.k(new_rep, new_ret)
print("PROVED OPTIMALITY FOR {}".format(self.q.name))
except core.StopException:
print("stopping synthesis of {}".format(self.q.name))
return
def run(self):
print("STARTING IMPROVEMENT JOB {} (|examples|={})".format(
self.q.name, len(self.examples or ())))
os.makedirs(log_dir.value, exist_ok=True)
with open(os.path.join(log_dir.value, "{}.log".format(self.q.name)),
"w",
buffering=LINE_BUFFER_MODE) as f:
sys.stdout = f
print("STARTING IMPROVEMENT JOB {} (|examples|={})".format(
self.q.name, len(self.examples or ())))
print(pprint(self.q))
if nice_children.value:
os.nice(20)
all_types = self.ctx.all_types
n_binders = 1
done = False
expr = ETuple(
(EAll(self.assumptions),
self.q.ret)).with_type(TTuple((BOOL, self.q.ret.type)))
while not done:
binders = []
for t in all_types:
# if isinstance(t, TBag):
# binders += [fresh_var(t.t) for i in range(n_binders)]
for i in range(n_binders):
b = fresh_var(t)
binders.append(b)
try:
core.fixup_binders(expr, binders, throw=True)
done = True
except:
pass
n_binders += 1
binders = [
fresh_var(t) for t in all_types if is_scalar(t)
for i in range(n_binders)
]
print("Using {} binders".format(n_binders))
relevant_state_vars = [
v for v in self.state if v in free_vars(EAll(self.assumptions))
| free_vars(self.q.ret)
]
used_vars = free_vars(self.q.ret)
for a in self.q.assumptions:
used_vars |= free_vars(a)
args = [EVar(v).with_type(t) for (v, t) in self.q.args]
args = [a for a in args if a in used_vars]
b = BinderBuilder(binders, relevant_state_vars, args)
if accelerate.value:
b = AcceleratedBuilder(b, binders, relevant_state_vars, args)
try:
for expr in itertools.chain(
(self.q.ret, ),
core.improve(
target=self.q.ret,
assumptions=EAll(self.assumptions),
hints=self.hints,
examples=self.examples,
binders=binders,
state_vars=relevant_state_vars,
args=args,
cost_model=CompositeCostModel(),
builder=b,
stop_callback=lambda: self.stop_requested)):
new_rep, new_ret = tease_apart(expr)
self.k(new_rep, new_ret)
print("PROVED OPTIMALITY FOR {}".format(self.q.name))
except core.StopException:
print("stopping synthesis of {}".format(self.q.name))
return