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import py
from rpython.translator.translator import TranslationContext, graphof
from rpython.translator.backendopt.all import backend_optimizations
from rpython.translator.simplify import get_graph, transform_dead_op_vars
from rpython.flowspace.model import Block, Constant, summary
from rpython.conftest import option
def translate(func, argtypes, backend_optimize=True):
t = TranslationContext()
t.buildannotator().build_types(func, argtypes)
t.buildrtyper().specialize()
if backend_optimize:
backend_optimizations(t)
if option.view:
t.view()
return graphof(t, func), t
def test_remove_ovfcheck_1():
# check that ovfcheck() is handled
from rpython.rlib.rarithmetic import ovfcheck
def f(x):
try:
return ovfcheck(x*2)
except OverflowError:
return -42
graph, _ = translate(f, [int])
assert len(graph.startblock.operations) == 1
assert graph.startblock.operations[0].opname == 'int_mul_ovf'
assert len(graph.startblock.exits) == 2
assert [link.target.operations for link in graph.startblock.exits] == \
[(), ()]
def test_remove_ovfcheck_bug():
# check that ovfcheck() is correctly handled even if there is no
# try:except: immediately around it
from rpython.rlib.rarithmetic import ovfcheck
def f(x):
return ovfcheck(x*2) - 1
graph, _ = translate(f, [int])
assert len(graph.startblock.operations) == 2
assert graph.startblock.operations[0].opname == 'int_mul_ovf'
assert graph.startblock.operations[1].opname == 'int_sub'
def test_remove_ovfcheck_floordiv():
# check that ovfcheck() is handled even if the operation raises
# and catches another exception too, here ZeroDivisionError
from rpython.rlib.rarithmetic import ovfcheck
def f(x, y):
try:
return ovfcheck(x // y)
except OverflowError:
return -42
except ZeroDivisionError:
return -43
graph, _ = translate(f, [int, int], backend_optimize=False)
assert len(graph.startblock.operations) == 1
assert graph.startblock.operations[0].opname == 'direct_call'
assert 'int_py_div_ovf_zer' in repr(
graph.startblock.operations[0].args[0].value)
assert len(graph.startblock.exits) == 3
assert [link.target.operations for link in graph.startblock.exits[1:]] == \
[(), ()]
def test_remove_ovfcheck_floordiv_2():
# check that ovfcheck() is handled even if the operation raises
# and catches only another exception, here ZeroDivisionError
from rpython.rlib.rarithmetic import ovfcheck
def f(x, y):
try:
return ovfcheck(x // y)
except ZeroDivisionError:
return -43
graph, _ = translate(f, [int, int], backend_optimize=False)
assert len(graph.startblock.operations) == 1
assert graph.startblock.operations[0].opname == 'direct_call'
assert 'int_py_div_ovf_zer' in repr(
graph.startblock.operations[0].args[0].value)
assert len(graph.startblock.exits) == 3
assert [link.target.operations for link in graph.startblock.exits[1:]] == \
[(), ()]
def test_remove_direct_call_without_side_effects():
def f(x):
return x + 123
def g(x):
a = f(x)
return x * 12
graph, _ = translate(g, [int])
assert len(graph.startblock.operations) == 1
def test_dont_remove_external_calls():
import os
def f(x):
os.close(x)
graph, _ = translate(f, [int])
assert len(graph.startblock.operations) > 0
def test_remove_recursive_call():
def rec(a):
if a <= 1:
return 0
else:
return rec(a - 1) + 1
def f(x):
a = rec(x)
return x + 12
graph, _ = translate(f, [int])
assert len(graph.startblock.operations) == 1
def test_remove_call_with_indirect_call():
def f1(x):
return x + 1
def f2(x):
return x + 2
def g(x):
if x == 32:
f = f1
else:
f = f2
return f(x)
def h(x):
a = g(x)
return x + 42
graph, t = translate(h, [int])
assert len(graph.startblock.operations) == 1
def test_dont_remove_if_exception_guarded():
def f(x):
a = {} #do some stuff to prevent inlining
a['123'] = 123
a['1123'] = 1234
return x + 1
def g(x):
try:
a = f(x)
except OverflowError:
raise
else:
return 1
graph, _ = translate(g, [int])
assert graph.startblock.operations[-1].opname == 'direct_call'
def test_remove_identical_variables():
def g(code):
pc = 0
while pc < len(code):
pc += 1
return pc
graph = TranslationContext().buildflowgraph(g)
for block in graph.iterblocks():
assert len(block.inputargs) <= 2 # at most 'pc' and 'code'
def test_get_graph():
import os
def list_basic_ops(i, j):
l = [1,2,3]
l.insert(0, 42)
del l[1]
l.append(i)
listlen = len(l)
l.extend(l)
del l[listlen:]
l += [5,6]
l[1] = i
return l[j]
def external_function():
return os.system("ls")
graph, t = translate(list_basic_ops, [int, int], False)
for block in graph.iterblocks():
for op in block.operations:
if op.opname == "direct_call":
print op
graph = get_graph(op.args[0], t)
assert graph is not None
# an external function in RPython turns currently into
# a call to a wrapper function which itself contains the
# real call to a graph-less external ll function, so
# we check recursively
graph, t = translate(external_function, [], False)
found = []
def walkgraph(graph):
for block in graph.iterblocks():
for op in block.operations:
if op.opname == "direct_call":
print op
subgraph = get_graph(op.args[0], t)
if subgraph is None:
# ignore 'get_errno' and 'set_errno', and
# 'RPyGilRelease' and 'RPyGilAcquire'
if ('et_errno' not in repr(op.args[0]) and
'RPyGil' not in repr(op.args[0])):
found.append(op)
else:
walkgraph(subgraph)
walkgraph(graph)
assert len(found) == 1
def addone(x):
return x + 1
def test_huge_func():
g = None
gstring = "def g(x):\n%s%s" % (" x = x + 1\n" * 1000, " return x\n")
exec gstring
assert g(1) == 1001
# does not crash: previously join_blocks would barf on this
graph, t = translate(g, [int])
def test_join_blocks_cleans_links():
from rpython.rtyper.lltypesystem import lltype
from rpython.flowspace.model import Constant
from rpython.translator.backendopt.removenoops import remove_same_as
def f(x):
return bool(x + 2)
def g(x):
if f(x):
return 1
else:
return 2
graph, t = translate(g, [int], backend_optimize=False)
fgraph = graphof(t, f)
fgraph.startblock.exits[0].args = [Constant(True, lltype.Bool)]
# does not crash: previously join_blocks would barf on this
remove_same_as(graph)
backend_optimizations(t)
def test_transform_dead_op_vars_bug():
from rpython.rtyper.llinterp import LLInterpreter, LLException
exc = ValueError()
def f1():
raise exc # this function used to be considered side-effects-free
def f2():
f1() # <- so this call was removed
graph, t = translate(f2, [], backend_optimize=False)
transform_dead_op_vars(graph, t)
interp = LLInterpreter(t.rtyper)
e = py.test.raises(LLException, 'interp.eval_graph(graph, [])')
assert 'ValueError' in str(e.value)
class TestDetectListComprehension:
def check(self, f1, expected):
t = TranslationContext(list_comprehension_operations=True)
graph = t.buildflowgraph(f1)
if option.view:
graph.show()
assert summary(graph) == expected
def test_simple(self):
def f1(l):
return [x*17 for x in l]
self.check(f1, {
'newlist': 1,
'iter': 1,
'next': 1,
'mul': 1,
'getattr': 1,
'simple_call': 1,
'hint': 2,
})
def test_with_exc(self):
def g(x):
return x * 17
def free_some_stuff():
pass
def f1(l):
try:
return [g(x) for x in l]
finally:
free_some_stuff()
self.check(f1, {
'newlist': 1,
'iter': 1,
'next': 1,
'getattr': 1,
'simple_call': 4,
'hint': 2,
})
def test_canraise_before_iter(self):
def g(l):
return l
def f1(l):
try:
return [x*17 for x in g(l)]
except ValueError:
return []
self.check(f1, {
'newlist': 2,
'iter': 1,
'next': 1,
'mul': 1,
'getattr': 1,
'simple_call': 2,
'hint': 2,
})
def test_iterate_over_list(self):
def wrap(elem):
return elem
def f(i):
new_l = []
l = range(4)
for elem in l:
new_l.append(wrap(elem))
return new_l
self.check(f, {
'hint': 2,
'newlist': 1,
'iter': 1,
'next': 1,
'getattr': 1,
'simple_call': 3,
})
class TestLLSpecializeListComprehension:
typesystem = 'lltype'
def specialize(self, func, argtypes):
from rpython.rtyper.llinterp import LLInterpreter
t = TranslationContext(list_comprehension_operations=True)
t.buildannotator().build_types(func, argtypes)
if option.view:
t.view()
t.buildrtyper().specialize()
backend_optimizations(t)
if option.view:
t.view()
graph = graphof(t, func)
interp = LLInterpreter(t.rtyper)
return interp, graph
def no_resize(self, graph, expect_resize=0):
found_resize = 0
for block in graph.iterblocks():
for op in block.operations:
if op.opname == 'direct_call':
if 'list_resize' in repr(op.args[0]):
found_resize += 1
assert found_resize == expect_resize
def test_simple(self):
def main(n):
lst = [x*17 for x in range(n)]
return lst[5]
interp, graph = self.specialize(main, [int])
res = interp.eval_graph(graph, [10])
assert res == 5 * 17
self.no_resize(graph)
def test_str2list(self):
def main(n):
lst = [c for c in str(n)]
return len(lst)
interp, graph = self.specialize(main, [int])
res = interp.eval_graph(graph, [1091283])
assert res == 7
self.no_resize(graph)
def test_simple_non_exact(self):
def main(n):
lst = [x*17 for x in range(n) if x < 5]
return len(lst)
interp, graph = self.specialize(main, [int])
res = interp.eval_graph(graph, [10])
assert res == 5
self.no_resize(graph, expect_resize=1)
# the non-exactness disables preallocating now, for sanity
def test_mutated_after_listcomp(self):
def main(n):
lst = [x*17 for x in range(n)]
lst.append(-42)
return lst[5]
interp, graph = self.specialize(main, [int])
res = interp.eval_graph(graph, [10])
assert res == 5 * 17
res = interp.eval_graph(graph, [5])
assert res == -42
self.no_resize(graph, expect_resize=1) # after the loop
def test_two_loops(self):
def main(n, m):
lst1 = []
lst2 = []
for i in range(n):
lst1.append(i)
for i in range(m):
lst2.append(i)
sum = 0
for i in lst1:
sum += i
for i in lst2:
sum -= i
return sum
interp, graph = self.specialize(main, [int, int])
res = interp.eval_graph(graph, [8, 3])
assert res == 28 - 3
self.no_resize(graph)
def test_dict(self):
def main(n, m):
d = {n: m, m: n}
lst = [i*17 for i in d]
return len(lst) + lst[0] + lst[-1]
interp, graph = self.specialize(main, [int, int])
res = interp.eval_graph(graph, [8, 5])
assert res == 2 + 8 * 17 + 5 * 17
res = interp.eval_graph(graph, [4, 4])
assert res == 1 + 4 * 17 + 4 * 17
self.no_resize(graph)
def test_list_iterator(self):
# for now, this is not optimized as a list comp
def main(n):
r = range(n)
lst = [i*17 for i in iter(r)]
return lst[5]
interp, graph = self.specialize(main, [int])
res = interp.eval_graph(graph, [8])
assert res == 5 * 17
def test_list_iterator_mutated_after_listcomp(self):
# for now, this is not optimized as a list comp
def main(n):
r = range(n)
lst = [i*17 for i in iter(r)]
lst.append(42)
return lst[5]
interp, graph = self.specialize(main, [int])
res = interp.eval_graph(graph, [8])
assert res == 5 * 17
def test_dict_iterator(self):
# for now, this is not optimized as a list comp
def main(n, m):
d = {n: m, m: n}
lst = [i*17 for i in d.iterkeys()]
return len(lst) + lst[0] + lst[-1]
interp, graph = self.specialize(main, [int, int])
res = interp.eval_graph(graph, [8, 5])
assert res == 2 + 8 * 17 + 5 * 17
res = interp.eval_graph(graph, [4, 4])
assert res == 1 + 4 * 17 + 4 * 17
def test_iterate_over_constant(self):
CONST = range(10)
def main(n):
lst = [x*17 for x in CONST]
return lst[5]
interp, graph = self.specialize(main, [int])
res = interp.eval_graph(graph, [10])
assert res == 5 * 17
self.no_resize(graph)
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