def test_jit_module_logging_level(self):
logger = logging.getLogger('numba.core.decorators')
# Test there's no logging for INFO level
logger.setLevel(logging.INFO)
with captured_logs(logger) as logs:
with create_temp_module(self.source_lines):
self.assertEqual(logs.getvalue(), '')
def test_jit_module_jit_options(self):
jit_options = {"nopython": True,
"nogil": False,
"error_model": "numpy",
"boundscheck": False,
}
with create_temp_module(self.source_lines,
**jit_options) as test_module:
self.assertEqual(test_module.inc.targetoptions, jit_options)
def test_create_temp_jitted_module_with_exception(self):
try:
sys_path_original = list(sys.path)
sys_modules_original = dict(sys.modules)
with create_temp_module(self.source_lines):
raise ValueError("Something went wrong!")
except ValueError:
# Test that modifications to sys.path / sys.modules are reverted
self.assertEqual(sys.path, sys_path_original)
self.assertEqual(sys.modules, sys_modules_original)
def test_create_temp_jitted_module(self):
sys_path_original = list(sys.path)
sys_modules_original = dict(sys.modules)
with create_temp_module(self.source_lines) as test_module:
temp_module_dir = os.path.dirname(test_module.__file__)
self.assertEqual(temp_module_dir, sys.path[0])
self.assertEqual(sys.path[1:], sys_path_original)
self.assertTrue(test_module.__name__ in sys.modules)
# Test that modifications to sys.path / sys.modules are reverted
self.assertEqual(sys.path, sys_path_original)
self.assertEqual(sys.modules, sys_modules_original)
def test_external_type(self):
with create_temp_module(self.source_lines) as test_module:
Foo, FooType = self.make_foo_type(test_module.FooType)
# sum of foo class instance and array return an array
# binary operation with foo class instance as one of args
@overload(operator.add)
def overload_foo_add(lhs, rhs):
if isinstance(lhs, FooType) and isinstance(rhs, types.Array):
def imp(lhs, rhs):
return np.array([lhs.value, rhs[0]])
return imp
# sum of 2 foo class instances return an array
# binary operation with 2 foo class instances as args
@overload(operator.add)
def overload_foo_add(lhs, rhs):
if isinstance(lhs, FooType) and isinstance(rhs, FooType):
def imp(lhs, rhs):
return np.array([lhs.value, rhs.value])
return imp
# neg of foo class instance return an array
# unary operation with foo class instance arg
@overload(operator.neg)
def overload_foo_neg(x):
if isinstance(x, FooType):
def imp(x):
return np.array([-x.value])
return imp
@njit
def arr_expr_sum1(x, y):
return Foo(x) + np.array([y])
@njit
def arr_expr_sum2(x, y):
return Foo(x) + Foo(y)
@njit
def arr_expr_neg(x):
return -Foo(x)
np.testing.assert_array_equal(arr_expr_sum1(0, 1), np.array([0,
1]))
np.testing.assert_array_equal(arr_expr_sum2(2, 3), np.array([2,
3]))
np.testing.assert_array_equal(arr_expr_neg(4), np.array([-4]))
def test_jit_module_logging_output(self):
logger = logging.getLogger('numba.core.decorators')
logger.setLevel(logging.DEBUG)
jit_options = {"nopython": True,
"error_model": "numpy",
}
with captured_logs(logger) as logs:
with create_temp_module(self.source_lines,
**jit_options) as test_module:
logs = logs.getvalue()
expected = ["Auto decorating function",
"from module {}".format(test_module.__name__),
"with jit and options: {}".format(jit_options)]
self.assertTrue(all(i in logs for i in expected))
def test_jit_module(self):
with create_temp_module(self.source_lines) as test_module:
self.assertIsInstance(test_module.inc, dispatcher.Dispatcher)
self.assertIsInstance(test_module.add, dispatcher.Dispatcher)
self.assertIsInstance(test_module.inc_add, dispatcher.Dispatcher)
self.assertTrue(test_module.mean is np.mean)
self.assertTrue(inspect.isclass(test_module.Foo))
# Test output of jitted functions is as expected
x, y = 1.7, 2.3
self.assertEqual(test_module.inc(x),
test_module.inc.py_func(x))
self.assertEqual(test_module.add(x, y),
test_module.add.py_func(x, y))
self.assertEqual(test_module.inc_add(x),
test_module.inc_add.py_func(x))
def test_mixin_against_real_example(self):
# See issue #4970, this checks that unicode eq/ne now ignores extension
# types.
with create_temp_module(self.source_lines) as test_module:
FooType = test_module.FooType
self.assertFalse(FooType().is_internal)
# set up an extension type
class Foo(object):
pass
register_model(FooType)(models.OpaqueModel)
@typeof_impl.register(Foo)
def _typ_foo(val, c):
return FooType()
@unbox(FooType)
def unbox_foo(typ, obj, c):
return NativeValue(c.context.get_dummy_value())
@overload(operator.eq)
def foo_eq(a, b):
if a == FooType():
return lambda a, b: "RAN CUSTOM EQ OVERLOAD"
@overload(operator.ne)
def foo_ne(a, b):
if a == FooType():
return lambda a, b: "RAN CUSTOM NE OVERLOAD"
@njit
def f(a):
return a == "A", a != "A"
self.assertEqual(("RAN CUSTOM EQ OVERLOAD",
"RAN CUSTOM NE OVERLOAD"),
f(Foo()))
def test_jit_module_jit_options_override(self):
source_lines = """
from numba import jit, jit_module
@jit(nogil=True, forceobj=True)
def inc(x):
return x + 1
def add(x, y):
return x + y
jit_module({jit_options})
"""
jit_options = {"nopython": True,
"error_model": "numpy",
"boundscheck": False,
}
with create_temp_module(source_lines=source_lines,
**jit_options) as test_module:
self.assertEqual(test_module.add.targetoptions, jit_options)
# Test that manual jit-wrapping overrides jit_module options
self.assertEqual(test_module.inc.targetoptions,
{'nogil': True, 'forceobj': True,
'boundscheck': None})
def test_externally_defined_type_is_external(self):
with create_temp_module(self.source_lines) as test_module:
FooType = test_module.FooType
self.assertFalse(FooType().is_internal)
# set up an extension type
class Foo(object):
pass
register_model(FooType)(models.OpaqueModel)
@typeof_impl.register(Foo)
def _typ_foo(val, c):
return FooType()
@unbox(FooType)
def unbox_foo(typ, obj, c):
return NativeValue(c.context.get_dummy_value())
# function to overload
def false_if_not_array(a):
pass
# Set up an overload which will accept all types irrespective of
# whether they are from Numba's closed type system
@overload(false_if_not_array)
def ol_false_if_not_array(a):
if isinstance(a, types.Array):
return lambda a: True
else:
return lambda a: False
@njit
def call_false_if_not_array(a):
return false_if_not_array(a)
self.assertTrue(call_false_if_not_array(np.zeros(10)))
self.assertFalse(call_false_if_not_array(10))
# The extension type was accepted
self.assertFalse(call_false_if_not_array(Foo()))
# Now do the same sort of overload but put in a guard based on the
# use of internal types
def false_if_not_array_closed_system(a):
pass
@overload(false_if_not_array_closed_system)
def ol_false_if_not_array_closed_system(a):
if a.is_internal: # guard
if isinstance(a, types.Array):
return lambda a: True
else:
return lambda a: False
@njit
def call_false_if_not_array_closed_system(a):
return false_if_not_array_closed_system(a)
self.assertTrue(call_false_if_not_array_closed_system(
np.zeros(10)))
self.assertFalse(call_false_if_not_array_closed_system(10))
with self.assertRaises(errors.TypingError) as raises:
call_false_if_not_array_closed_system(Foo())
estr = str(raises.exception)
self.assertIn(_header_lead, estr)
self.assertIn("false_if_not_array_closed_system", estr)
self.assertIn("(Foo)", estr)
