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gh-131798: JIT: Further optimize _CALL_ISINSTANCE
for class tuples
#134543
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Original file line number | Diff line number | Diff line change |
---|---|---|
|
@@ -2191,17 +2191,154 @@ def testfunc(n): | |
self.assertNotIn("_TO_BOOL_BOOL", uops) | ||
self.assertIn("_GUARD_IS_TRUE_POP", uops) | ||
|
||
def test_call_isinstance_tuple_of_classes(self): | ||
def test_call_isinstance_tuple_of_classes_is_true(self): | ||
def testfunc(n): | ||
x = 0 | ||
for _ in range(n): | ||
# A tuple of classes is currently not optimized, | ||
# so this is only narrowed to bool: | ||
y = isinstance(42, (int, str)) | ||
if y: | ||
x += 1 | ||
return x | ||
|
||
res, ex = self._run_with_optimizer(testfunc, TIER2_THRESHOLD) | ||
self.assertEqual(res, TIER2_THRESHOLD) | ||
self.assertIsNotNone(ex) | ||
uops = get_opnames(ex) | ||
self.assertNotIn("_CALL_ISINSTANCE", uops) | ||
self.assertNotIn("_TO_BOOL_BOOL", uops) | ||
self.assertNotIn("_GUARD_IS_TRUE_POP", uops) | ||
self.assertIn("_BUILD_TUPLE", uops) | ||
self.assertIn("_POP_CALL_TWO_LOAD_CONST_INLINE_BORROW", uops) | ||
|
||
def test_call_isinstance_tuple_of_classes_is_false(self): | ||
def testfunc(n): | ||
x = 0 | ||
for _ in range(n): | ||
y = isinstance(42, (bool, str)) | ||
if not y: | ||
x += 1 | ||
return x | ||
|
||
res, ex = self._run_with_optimizer(testfunc, TIER2_THRESHOLD) | ||
self.assertEqual(res, TIER2_THRESHOLD) | ||
self.assertIsNotNone(ex) | ||
uops = get_opnames(ex) | ||
self.assertNotIn("_CALL_ISINSTANCE", uops) | ||
self.assertNotIn("_TO_BOOL_BOOL", uops) | ||
self.assertNotIn("_GUARD_IS_FALSE_POP", uops) | ||
self.assertIn("_BUILD_TUPLE", uops) | ||
self.assertIn("_POP_CALL_TWO_LOAD_CONST_INLINE_BORROW", uops) | ||
|
||
def test_call_isinstance_tuple_of_classes_true_unknown_1(self): | ||
def testfunc(n): | ||
x = 0 | ||
for _ in range(n): | ||
# One of the classes is unknown, but it comes | ||
# after a known class, so we can narrow to True | ||
y = isinstance(42, (int, eval('str'))) | ||
if y: | ||
x += 1 | ||
return x | ||
|
||
res, ex = self._run_with_optimizer(testfunc, TIER2_THRESHOLD) | ||
self.assertEqual(res, TIER2_THRESHOLD) | ||
self.assertIsNotNone(ex) | ||
uops = get_opnames(ex) | ||
self.assertNotIn("_CALL_ISINSTANCE", uops) | ||
self.assertNotIn("_TO_BOOL_BOOL", uops) | ||
self.assertNotIn("_GUARD_IS_FALSE_POP", uops) | ||
self.assertIn("_BUILD_TUPLE", uops) | ||
self.assertIn("_POP_CALL_TWO_LOAD_CONST_INLINE_BORROW", uops) | ||
|
||
def test_call_isinstance_tuple_of_classes_true_unknown_2(self): | ||
def testfunc(n): | ||
x = 0 | ||
for _ in range(n): | ||
# One of the classes is unknown, so we can't narrow | ||
# to True or False, only bool | ||
y = isinstance(42, (eval('str'), int)) | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I'm confused, why can't we narrow to There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Yep, that was a brainfart 😄 I somehow conflated narrowing to True/False with replacing the op, but we can obviously just narrow without removing the call as you said! |
||
if y: | ||
x += 1 | ||
return x | ||
|
||
res, ex = self._run_with_optimizer(testfunc, TIER2_THRESHOLD) | ||
self.assertEqual(res, TIER2_THRESHOLD) | ||
self.assertIsNotNone(ex) | ||
uops = get_opnames(ex) | ||
self.assertIn("_CALL_ISINSTANCE", uops) | ||
self.assertNotIn("_TO_BOOL_BOOL", uops) | ||
self.assertIn("_GUARD_IS_TRUE_POP", uops) | ||
|
||
def test_call_isinstance_tuple_of_classes_true_unknown_3(self): | ||
def testfunc(n): | ||
x = 0 | ||
for _ in range(n): | ||
# One of the classes is unknown, so we can't narrow | ||
# to True or False, only bool | ||
y = isinstance(42, (str, eval('int'))) | ||
if y: | ||
x += 1 | ||
return x | ||
|
||
res, ex = self._run_with_optimizer(testfunc, TIER2_THRESHOLD) | ||
self.assertEqual(res, TIER2_THRESHOLD) | ||
self.assertIsNotNone(ex) | ||
uops = get_opnames(ex) | ||
self.assertIn("_CALL_ISINSTANCE", uops) | ||
self.assertNotIn("_TO_BOOL_BOOL", uops) | ||
self.assertIn("_GUARD_IS_TRUE_POP", uops) | ||
|
||
def test_call_isinstance_tuple_of_classes_true_unknown_4(self): | ||
def testfunc(n): | ||
x = 0 | ||
for _ in range(n): | ||
# One of the classes is unknown, so we can't narrow | ||
# to True or False, only bool | ||
y = isinstance(42, (eval('int'), str)) | ||
if y: | ||
x += 1 | ||
return x | ||
|
||
res, ex = self._run_with_optimizer(testfunc, TIER2_THRESHOLD) | ||
self.assertEqual(res, TIER2_THRESHOLD) | ||
self.assertIsNotNone(ex) | ||
uops = get_opnames(ex) | ||
self.assertIn("_CALL_ISINSTANCE", uops) | ||
self.assertNotIn("_TO_BOOL_BOOL", uops) | ||
self.assertIn("_GUARD_IS_TRUE_POP", uops) | ||
|
||
def test_call_isinstance_empty_tuple(self): | ||
def testfunc(n): | ||
x = 0 | ||
for _ in range(n): | ||
y = isinstance(42, ()) | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I had to pause and think for a second to figure out what this would even do. Nice edge case. |
||
if not y: | ||
x += 1 | ||
return x | ||
|
||
res, ex = self._run_with_optimizer(testfunc, TIER2_THRESHOLD) | ||
self.assertEqual(res, TIER2_THRESHOLD) | ||
self.assertIsNotNone(ex) | ||
uops = get_opnames(ex) | ||
self.assertNotIn("_CALL_ISINSTANCE", uops) | ||
self.assertNotIn("_TO_BOOL_BOOL", uops) | ||
self.assertNotIn("_GUARD_IS_FALSE_POP", uops) | ||
self.assertNotIn("_POP_TOP_LOAD_CONST_INLINE_BORROW", uops) | ||
self.assertNotIn("_POP_CALL_LOAD_CONST_INLINE_BORROW", uops) | ||
self.assertNotIn("_POP_CALL_ONE_LOAD_CONST_INLINE_BORROW", uops) | ||
self.assertNotIn("_POP_CALL_TWO_LOAD_CONST_INLINE_BORROW", uops) | ||
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||
def test_call_isinstance_tuple_unknown_length(self): | ||
def testfunc(n): | ||
x = 0 | ||
for _ in range(n): | ||
# tuple with an unknown length, we only narrow to bool | ||
tup = tuple(eval('(int, str)')) | ||
y = isinstance(42, tup) | ||
if y: | ||
x += 1 | ||
return x | ||
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||
res, ex = self._run_with_optimizer(testfunc, TIER2_THRESHOLD) | ||
self.assertEqual(res, TIER2_THRESHOLD) | ||
self.assertIsNotNone(ex) | ||
|
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,2 @@ | ||
Optimize ``_CALL_ISINSTANCE`` in the JIT when the second argument is a tuple | ||
of classes. |
Original file line number | Diff line number | Diff line change | ||||
---|---|---|---|---|---|---|
|
@@ -956,14 +956,48 @@ dummy_func(void) { | |||||
// isinstance(inst, cls) where both inst and cls have | ||||||
// known types, meaning we can deduce either True or False | ||||||
|
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// The below check is equivalent to PyObject_TypeCheck(inst, cls) | ||||||
PyObject *out = Py_False; | ||||||
if (inst_type == cls_o || PyType_IsSubtype(inst_type, cls_o)) { | ||||||
out = Py_True; | ||||||
} | ||||||
sym_set_const(res, out); | ||||||
REPLACE_OP(this_instr, _POP_CALL_TWO_LOAD_CONST_INLINE_BORROW, 0, (uintptr_t)out); | ||||||
} | ||||||
else if (inst_type && sym_matches_type(cls, &PyTuple_Type)) { | ||||||
// isinstance(inst, tup) where inst has a known type and tup is a tuple. | ||||||
// We can deduce True if inst is an instance of at least one of | ||||||
// the items in the tuple. | ||||||
// We can deduce False if all items in the tuple have known types and | ||||||
// inst is not an instance of any of them. | ||||||
|
||||||
int length = sym_tuple_length(cls); | ||||||
if (length != -1) { | ||||||
// We cannot do anything about tuples with unknown length | ||||||
PyObject *out = Py_False; | ||||||
for (int i = 0; i < length; i++) { | ||||||
JitOptRef item = sym_tuple_getitem(ctx, cls, i); | ||||||
if (!sym_has_type(item)) { | ||||||
// There is an unknown item in the tuple. | ||||||
// It could potentially define its own __instancecheck__ | ||||||
// method so we can only deduce bool. | ||||||
out = NULL; | ||||||
break; | ||||||
|
break; | |
continue; |
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Yup, see #134543 (comment). I just needed to add some extra bookkeeping to know when we can replace the call and when not.
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Maybe add a comment explaining that this is to protect against metaclasses definine __instancecheck__
.
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How would you formulate it? I don't think of it as specifically a guard for __instancecheck__
but basically PyObject_TypeCheck
adapted to the JIT optimizer.
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We're not only checking that the object is a subclass of type
, we're also checking that it is an exact instance of type
itself. We care about this second condition because it guarantees that __instancecheck__
doesn't exist (otherwise we would need to look it up to check if it exists or not).
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Thanks for the clarification, I added a comment :)
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Wait, wouldn't this only work on something that is isinstance(x, type)
, like the actual type
itself, not any type like int
? Sorry, I'm confused!
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Hmm I don't believe so. If item
is e.g. int
then sym_matches_type(item, &PyType_Type)
should return true
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For example something like this seems to work:
JitOptRef ref_type = _Py_uop_sym_new_const(ctx, (PyObject *)&PyLong_Type);
TEST_PREDICATE(_Py_uop_sym_matches_type(ref_type, &PyType_Type), "int is not a type");
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That''s kinda strange. The code for _Py_uop_sym_matches_type
is:
_Py_uop_sym_get_type(sym) == typ
so it's a pointer comparison, not a subclass check.
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The subclass check is done after with PyType_IsSubtype
if that's what you mean? The current version of _CALL_ISINSTANCE
(which does not handle tuples) works the same way though. @brandtbucher, what do you think?
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_BUILD_TUPLE
is preventing us from optimizing out_POP_CALL_TWO_LOAD_CONST_INLINE_BORROW
.The bytecode is basically:
To optimize this, we'd need some special handling for
_BUILD_TUPLE
inremove_unneeded_uops
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Got it, might be worth looking into next if you're up for it! Could be tricky, though.