ai-content-maker/.venv/Lib/site-packages/numba/tests/test_interpreter.py

1155 lines
30 KiB
Python

"""
Test bytecode fixes provided in interpreter.py
"""
import unittest
from numba import jit, njit, objmode, typeof, literally
from numba.extending import overload
from numba.core import types
from numba.core.errors import UnsupportedError
from numba.tests.support import (
TestCase,
MemoryLeakMixin,
skip_unless_py10_or_later,
)
@njit
def sum_jit_func(
arg0=0,
arg1=0,
arg2=0,
arg3=0,
arg4=0,
arg5=0,
arg6=0,
arg7=0,
arg8=0,
arg9=0,
arg10=0,
arg11=0,
arg12=0,
arg13=0,
arg14=0,
arg15=0,
arg16=0,
arg17=0,
arg18=0,
arg19=0,
arg20=0,
arg21=0,
arg22=0,
arg23=0,
arg24=0,
arg25=0,
arg26=0,
arg27=0,
arg28=0,
arg29=0,
arg30=0,
arg31=0,
arg32=0,
arg33=0,
arg34=0,
arg35=0,
arg36=0,
arg37=0,
arg38=0,
arg39=0,
arg40=0,
arg41=0,
arg42=0,
arg43=0,
arg44=0,
arg45=0,
arg46=0,
):
return (
arg0
+ arg1
+ arg2
+ arg3
+ arg4
+ arg5
+ arg6
+ arg7
+ arg8
+ arg9
+ arg10
+ arg11
+ arg12
+ arg13
+ arg14
+ arg15
+ arg16
+ arg17
+ arg18
+ arg19
+ arg20
+ arg21
+ arg22
+ arg23
+ arg24
+ arg25
+ arg26
+ arg27
+ arg28
+ arg29
+ arg30
+ arg31
+ arg32
+ arg33
+ arg34
+ arg35
+ arg36
+ arg37
+ arg38
+ arg39
+ arg40
+ arg41
+ arg42
+ arg43
+ arg44
+ arg45
+ arg46
)
class TestCallFunctionExPeepHole(MemoryLeakMixin, TestCase):
"""
gh #7812
Tests that check a peephole optimization for Function calls
in Python 3.10. The bytecode changes when
(n_args / 2) + n_kws > 15, which moves the arguments from
the stack into a tuple and dictionary.
This peephole optimization updates the IR to use the original format.
There are different paths when n_args > 30 and n_args <= 30 and when
n_kws > 15 and n_kws <= 15.
"""
THRESHOLD_ARGS = 31
THRESHOLD_KWS = 16
def gen_func(self, n_args, n_kws):
"""
Generates a function that calls sum_jit_func
with the desired number of args and kws.
"""
param_list = [f"arg{i}" for i in range(n_args + n_kws)]
args_list = []
for i in range(n_args + n_kws):
# Call a function on every 5th argument to ensure
# we test function calls.
if i % 5 == 0:
arg_val = f"pow(arg{i}, 2)"
else:
arg_val = f"arg{i}"
args_list.append(arg_val)
total_params = ", ".join(param_list)
func_text = f"def impl({total_params}):\n"
func_text += " return sum_jit_func(\n"
for i in range(n_args):
func_text += f" {args_list[i]},\n"
for i in range(n_args, n_args + n_kws):
func_text += f" {param_list[i]}={args_list[i]},\n"
func_text += " )\n"
local_vars = {}
exec(func_text, {"sum_jit_func": sum_jit_func}, local_vars)
return local_vars["impl"]
@skip_unless_py10_or_later
def test_all_args(self):
"""
Tests calling a function when n_args > 30 and
n_kws = 0. This shouldn't use the peephole, but
it should still succeed.
"""
total_args = [i for i in range(self.THRESHOLD_ARGS)]
f = self.gen_func(self.THRESHOLD_ARGS, 0)
py_func = f
cfunc = njit()(f)
a = py_func(*total_args)
b = cfunc(*total_args)
self.assertEqual(a, b)
@skip_unless_py10_or_later
def test_all_kws(self):
"""
Tests calling a function when n_kws > 15 and
n_args = 0.
"""
total_args = [i for i in range(self.THRESHOLD_KWS)]
f = self.gen_func(0, self.THRESHOLD_KWS)
py_func = f
cfunc = njit()(f)
a = py_func(*total_args)
b = cfunc(*total_args)
self.assertEqual(a, b)
@skip_unless_py10_or_later
def test_small_args_small_kws(self):
"""
Tests calling a function when (n_args / 2) + n_kws > 15,
but n_args <= 30 and n_kws <= 15
"""
used_args = self.THRESHOLD_ARGS - 1
used_kws = self.THRESHOLD_KWS - 1
total_args = [i for i in range((used_args) + (used_kws))]
f = self.gen_func(used_args, used_kws)
py_func = f
cfunc = njit()(f)
a = py_func(*total_args)
b = cfunc(*total_args)
self.assertEqual(a, b)
@skip_unless_py10_or_later
def test_small_args_large_kws(self):
"""
Tests calling a function when (n_args / 2) + n_kws > 15,
but n_args <= 30 and n_kws > 15
"""
used_args = self.THRESHOLD_ARGS - 1
used_kws = self.THRESHOLD_KWS
total_args = [i for i in range((used_args) + (used_kws))]
f = self.gen_func(used_args, used_kws)
py_func = f
cfunc = njit()(f)
a = py_func(*total_args)
b = cfunc(*total_args)
self.assertEqual(a, b)
@skip_unless_py10_or_later
def test_large_args_small_kws(self):
"""
Tests calling a function when (n_args / 2) + n_kws > 15,
but n_args > 30 and n_kws <= 15
"""
used_args = self.THRESHOLD_ARGS
used_kws = self.THRESHOLD_KWS - 1
total_args = [i for i in range((used_args) + (used_kws))]
f = self.gen_func(used_args, used_kws)
py_func = f
cfunc = njit()(f)
a = py_func(*total_args)
b = cfunc(*total_args)
self.assertEqual(a, b)
@skip_unless_py10_or_later
def test_large_args_large_kws(self):
"""
Tests calling a function when (n_args / 2) + n_kws > 15,
but n_args > 30 and n_kws > 15
"""
used_args = self.THRESHOLD_ARGS
used_kws = self.THRESHOLD_KWS
total_args = [i for i in range((used_args) + (used_kws))]
f = self.gen_func(used_args, used_kws)
py_func = f
cfunc = njit()(f)
a = py_func(*total_args)
b = cfunc(*total_args)
self.assertEqual(a, b)
@skip_unless_py10_or_later
def test_large_kws_objmode(self):
"""
Tests calling an objectmode function with > 15 return values.
"""
def py_func():
return (
0,
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
)
@njit
def objmode_func():
"""
Wrapper to call py_func from objmode. This tests
large kws with objmode. If the definition for the
call is not properly updated this test will fail.
"""
with objmode(
a='int64',
b='int64',
c='int64',
d='int64',
e='int64',
f='int64',
g='int64',
h='int64',
i='int64',
j='int64',
k='int64',
l='int64',
m='int64',
n='int64',
o='int64',
p='int64',
):
(
a,
b,
c,
d,
e,
f,
g,
h,
i,
j,
k,
l,
m,
n,
o,
p
) = py_func()
return (
a
+ b
+ c
+ d
+ e
+ f
+ g
+ h
+ i
+ j
+ k
+ l
+ m
+ n
+ o
+ p
)
a = sum(list(py_func()))
b = objmode_func()
self.assertEqual(a, b)
@skip_unless_py10_or_later
def test_large_args_inline_controlflow(self):
"""
Tests generating large args when one of the inputs
has inlined controlflow.
"""
def inline_func(flag):
return sum_jit_func(
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1 if flag else 2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
arg41=1,
)
with self.assertRaises(UnsupportedError) as raises:
njit()(inline_func)(False)
self.assertIn(
'You can resolve this issue by moving the control flow out',
str(raises.exception)
)
@skip_unless_py10_or_later
def test_large_args_noninlined_controlflow(self):
"""
Tests generating large args when one of the inputs
has the change suggested in the error message
for inlined control flow.
"""
def inline_func(flag):
a_val = 1 if flag else 2
return sum_jit_func(
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
a_val,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
arg41=1,
)
py_func = inline_func
cfunc = njit()(inline_func)
a = py_func(False)
b = cfunc(False)
self.assertEqual(a, b)
@skip_unless_py10_or_later
def test_all_args_inline_controlflow(self):
"""
Tests generating only large args when one of the inputs
has inlined controlflow. This requires a special check
inside peep_hole_call_function_ex_to_call_function_kw
because it usually only handles varkwargs.
"""
def inline_func(flag):
return sum_jit_func(
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1 if flag else 2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
)
with self.assertRaises(UnsupportedError) as raises:
njit()(inline_func)(False)
self.assertIn(
'You can resolve this issue by moving the control flow out',
str(raises.exception)
)
@skip_unless_py10_or_later
def test_all_args_noninlined_controlflow(self):
"""
Tests generating large args when one of the inputs
has the change suggested in the error message
for inlined control flow.
"""
def inline_func(flag):
a_val = 1 if flag else 2
return sum_jit_func(
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
a_val,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
)
py_func = inline_func
cfunc = njit()(inline_func)
a = py_func(False)
b = cfunc(False)
self.assertEqual(a, b)
@skip_unless_py10_or_later
def test_large_kws_inline_controlflow(self):
"""
Tests generating large kws when one of the inputs
has inlined controlflow.
"""
def inline_func(flag):
return sum_jit_func(
arg0=1,
arg1=1,
arg2=1,
arg3=1,
arg4=1,
arg5=1,
arg6=1,
arg7=1,
arg8=1,
arg9=1,
arg10=1,
arg11=1,
arg12=1,
arg13=1,
arg14=1,
arg15=1 if flag else 2,
)
with self.assertRaises(UnsupportedError) as raises:
njit()(inline_func)(False)
self.assertIn(
'You can resolve this issue by moving the control flow out',
str(raises.exception)
)
@skip_unless_py10_or_later
def test_large_kws_noninlined_controlflow(self):
"""
Tests generating large kws when one of the inputs
has the change suggested in the error message
for inlined control flow.
"""
def inline_func(flag):
a_val = 1 if flag else 2
return sum_jit_func(
arg0=1,
arg1=1,
arg2=1,
arg3=1,
arg4=1,
arg5=1,
arg6=1,
arg7=1,
arg8=1,
arg9=1,
arg10=1,
arg11=1,
arg12=1,
arg13=1,
arg14=1,
arg15=a_val,
)
py_func = inline_func
cfunc = njit()(inline_func)
a = py_func(False)
b = cfunc(False)
self.assertEqual(a, b)
class TestLargeConstDict(TestCase, MemoryLeakMixin):
"""
gh #7894
Tests that check a peephole optimization for constant
dictionaries in Python 3.10. The bytecode changes when
number of elements > 15, which splits the constant dictionary
into multiple dictionaries that are joined by a DICT_UPDATE
bytecode instruction.
This optimization modifies the IR to rejoin dictionaries
and remove the DICT_UPDATE generated code. This then allows
code that depends on literal dictionaries or literal keys
to succeed.
"""
@skip_unless_py10_or_later
def test_large_heterogeneous_const_dict(self):
"""
Tests that a function with a large heterogeneous constant
dictionary remains a constant.
"""
def const_func():
# D is a heterogeneous dictionary
# so this code can only compile if
# d is constant.
d = {
"A": 1,
"B": 1,
"C": 1,
"D": 1,
"E": 1,
"F": 1,
"G": 1,
"H": 1,
"I": 1,
"J": 1,
"K": 1,
"L": 1,
"M": 1,
"N": 1,
"O": 1,
"P": 1,
"Q": 1,
"R": 1,
"S": 'a',
}
return d["S"]
py_func = const_func
cfunc = njit()(const_func)
a = py_func()
b = cfunc()
self.assertEqual(a, b)
@skip_unless_py10_or_later
def test_large_heterogeneous_LiteralStrKeyDict_literal_values(self):
"""Check the literal values for a LiteralStrKeyDict requiring
optimizations because it is heterogeneous.
"""
def bar(d):
...
@overload(bar)
def ol_bar(d):
a = {
"A": 1,
"B": 1,
"C": 1,
"D": 1,
"E": 1,
"F": 1,
"G": 1,
"H": 1,
"I": 1,
"J": 1,
"K": 1,
"L": 1,
"M": 1,
"N": 1,
"O": 1,
"P": 1,
"Q": 1,
"R": 1,
"S": 'a',
}
def specific_ty(z):
return types.literal(z) if types.maybe_literal(z) else typeof(z)
expected = {types.literal(x): specific_ty(y) for x, y in a.items()}
self.assertTrue(isinstance(d, types.LiteralStrKeyDict))
self.assertEqual(d.literal_value, expected)
self.assertEqual(hasattr(d, 'initial_value'), False)
return lambda d: d
@njit
def foo():
# D is a heterogeneous dictionary
# so this code can only compile if
# d has the correct literal values.
d = {
"A": 1,
"B": 1,
"C": 1,
"D": 1,
"E": 1,
"F": 1,
"G": 1,
"H": 1,
"I": 1,
"J": 1,
"K": 1,
"L": 1,
"M": 1,
"N": 1,
"O": 1,
"P": 1,
"Q": 1,
"R": 1,
"S": 'a',
}
bar(d)
foo()
@skip_unless_py10_or_later
def test_large_heterogeneous_const_keys_dict(self):
"""
Tests that a function with a large heterogeneous constant
dictionary remains a constant.
"""
def const_keys_func(a):
# D is a heterogeneous dictionary
# so this code can only compile if
# d has constant keys.
d = {
"A": 1,
"B": 1,
"C": 1,
"D": 1,
"E": 1,
"F": 1,
"G": 1,
"H": 1,
"I": 1,
"J": 1,
"K": 1,
"L": 1,
"M": 1,
"N": 1,
"O": 1,
"P": 1,
"Q": 1,
"R": 1,
"S": a,
}
return d["S"]
py_func = const_keys_func
cfunc = njit()(const_keys_func)
# str to make the dictionary heterogeneous.
value = "a_string"
a = py_func(value)
b = cfunc(value)
self.assertEqual(a, b)
@skip_unless_py10_or_later
def test_large_dict_mutation_not_carried(self):
"""Checks that the optimization for large dictionaries
do not incorrectly update initial values due to other
mutations.
"""
def bar(d):
...
@overload(bar)
def ol_bar(d):
a = {
"A": 1,
"B": 1,
"C": 1,
"D": 1,
"E": 1,
"F": 1,
"G": 1,
"H": 1,
"I": 1,
"J": 1,
"K": 1,
"L": 1,
"M": 1,
"N": 1,
"O": 1,
"P": 1,
"Q": 1,
"R": 1,
"S": 7,
}
if d.initial_value is None:
return lambda d: literally(d)
self.assertTrue(isinstance(d, types.DictType))
self.assertEqual(d.initial_value, a)
return lambda d: d
@njit
def foo():
# This dictionary is mutated, check the initial_value carries
# correctly and is not mutated
d = {
"A": 1,
"B": 1,
"C": 1,
"D": 1,
"E": 1,
"F": 1,
"G": 1,
"H": 1,
"I": 1,
"J": 1,
"K": 1,
"L": 1,
"M": 1,
"N": 1,
"O": 1,
"P": 1,
"Q": 1,
"R": 1,
"S": 7,
}
d['X'] = 4
bar(d)
foo()
@skip_unless_py10_or_later
def test_usercode_update_use_d2(self):
"""
Tests an example using a regular update is
not modified by the optimization.
"""
def check_before(x):
pass
def check_after(x):
pass
checked_before = False
checked_after = False
@overload(check_before, prefer_literal=True)
def ol_check_before(d):
nonlocal checked_before
# Typing iteration from d1.update(d2)
# may reset the initial values to None,
# so we only check on the first iteration.
if not checked_before:
checked_before = True
a = {
"a": 1,
"b": 2,
"c": 3,
}
self.assertTrue(isinstance(d, types.DictType))
self.assertEqual(d.initial_value, a)
return lambda d: None
@overload(check_after, prefer_literal=True)
def ol_check_after(d):
nonlocal checked_after
# Typing iteration from d1.update(d2)
# may reset the initial values to None,
# so we only check on the first iteration.
if not checked_after:
checked_after = True
self.assertTrue(isinstance(d, types.DictType))
self.assertTrue(d.initial_value is None)
return lambda d: None
def const_dict_func():
"""
Dictionary update between two constant
dictionaries. This verifies d2 doesn't
get incorrectly removed.
"""
d1 = {
"a": 1,
"b": 2,
"c": 3,
}
d2 = {
"d": 4,
"e": 4
}
check_before(d1)
d1.update(d2)
check_after(d1)
# Create a use of d2 in a new block.
if len(d1) > 4:
return d2
return d1
py_func = const_dict_func
cfunc = njit()(const_dict_func)
a = py_func()
b = cfunc()
self.assertEqual(a, b)
@skip_unless_py10_or_later
def test_large_const_dict_inline_controlflow(self):
"""
Tests generating a large dictionary when one of
the inputs requires inline control flow
has the change suggested in the error message
for inlined control flow.
"""
def inline_func(a, flag):
# D is a heterogeneous dictionary
# so this code can only compile if
# d has constant keys.
d = {
"A": 1,
"B": 1,
"C": 1,
"D": 1,
"E": 1,
"F": 1,
"G": 1,
"H": 1 if flag else 2,
"I": 1,
"J": 1,
"K": 1,
"L": 1,
"M": 1,
"N": 1,
"O": 1,
"P": 1,
"Q": 1,
"R": 1,
"S": a,
}
return d["S"]
with self.assertRaises(UnsupportedError) as raises:
njit()(inline_func)("a_string", False)
self.assertIn(
'You can resolve this issue by moving the control flow out',
str(raises.exception)
)
@skip_unless_py10_or_later
def test_large_const_dict_noninline_controlflow(self):
"""
Tests generating large constant dict when one of the
inputs has the change suggested in the error message
for inlined control flow.
"""
def non_inline_func(a, flag):
# D is a heterogeneous dictionary
# so this code can only compile if
# d has constant keys.
val = 1 if flag else 2
d = {
"A": 1,
"B": 1,
"C": 1,
"D": 1,
"E": 1,
"F": 1,
"G": 1,
"H": val,
"I": 1,
"J": 1,
"K": 1,
"L": 1,
"M": 1,
"N": 1,
"O": 1,
"P": 1,
"Q": 1,
"R": 1,
"S": a,
}
return d["S"]
py_func = non_inline_func
cfunc = njit()(non_inline_func)
value = "a_string"
a = py_func(value, False)
b = cfunc(value, False)
self.assertEqual(a, b)
@skip_unless_py10_or_later
def test_fuse_twice_literal_values(self):
"""
Tests that the correct literal values are generated
for a dictionary that produces two DICT_UPDATE
bytecode entries for the same dictionary.
"""
def bar(d):
...
@overload(bar)
def ol_bar(d):
a = {
"a1" : 1,
"a2" : 2,
"a3" : 3,
"a4" : 4,
"a5" : 5,
"a6" : 6,
"a7" : 7,
"a8" : 8,
"a9" : 9,
"a10" : 10,
"a11" : 11,
"a12" : 12,
"a13" : 13,
"a14" : 14,
"a15" : 15,
"a16" : 16,
"a17" : 17,
"a18" : 18,
"a19" : 19,
"a20" : 20,
"a21" : 21,
"a22" : 22,
"a23" : 23,
"a24" : 24,
"a25" : 25,
"a26" : 26,
"a27" : 27,
"a28" : 28,
"a29" : 29,
"a30" : 30,
"a31" : 31,
"a32" : 32,
"a33" : 33,
"a34" : 34, # 34 items is the limit of
# (LOAD_CONST + MAP_ADD)^n + DICT_UPDATE
"a35" : 35, # 35 Generates an additional BUILD_MAP + DICT_UPDATE
}
if d.initial_value is None:
return lambda d: literally(d)
self.assertTrue(isinstance(d, types.DictType))
self.assertEqual(d.initial_value, a)
return lambda d: d
@njit
def foo():
# This dictionary is mutated, check the initial_value carries
# correctly and is not mutated
d = {
"a1" : 1,
"a2" : 2,
"a3" : 3,
"a4" : 4,
"a5" : 5,
"a6" : 6,
"a7" : 7,
"a8" : 8,
"a9" : 9,
"a10" : 10,
"a11" : 11,
"a12" : 12,
"a13" : 13,
"a14" : 14,
"a15" : 15,
"a16" : 16,
"a17" : 17,
"a18" : 18,
"a19" : 19,
"a20" : 20,
"a21" : 21,
"a22" : 22,
"a23" : 23,
"a24" : 24,
"a25" : 25,
"a26" : 26,
"a27" : 27,
"a28" : 28,
"a29" : 29,
"a30" : 30,
"a31" : 31,
"a32" : 32,
"a33" : 33,
"a34" : 34, # 34 items is the limit of
# (LOAD_CONST + MAP_ADD)^n + DICT_UPDATE
"a35" : 35, # 35 Generates an additional BUILD_MAP + DICT_UPDATE
}
bar(d)
foo()
class TestListExtendInStarArgNonTupleIterable(MemoryLeakMixin, TestCase):
"""Test `fn(pos_arg0, pos_arg1, *args)` where args is a non-tuple iterable.
Python 3.9+ will generate LIST_EXTEND bytecode to combine the positional
arguments with the `*args`.
See #8059
NOTE: At the moment, there are no meaningful tests for NoPython because the
lack of support for `tuple(iterable)` for most iterable types.
"""
def test_list_extend_forceobj(self):
def consumer(*x):
return x
@jit(forceobj=True)
def foo(x):
return consumer(1, 2, *x)
got = foo("ijo")
expect = foo.py_func("ijo")
self.assertEqual(got, (1, 2, "i", "j", "o"))
self.assertEqual(got, expect)
if __name__ == "__main__":
unittest.main()