gh-73468: Add math.fma() function (#116667)

Added new math.fma() function, wrapping C99's ``fma()`` operation:
fused multiply-add function.

Co-authored-by: Mark Dickinson <mdickinson@enthought.com>
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Victor Stinner 2024-03-17 14:58:26 +01:00 committed by GitHub
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6 changed files with 371 additions and 1 deletions

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@ -82,6 +82,22 @@ Number-theoretic and representation functions
should return an :class:`~numbers.Integral` value.
.. function:: fma(x, y, z)
Fused multiply-add operation. Return ``(x * y) + z``, computed as though with
infinite precision and range followed by a single round to the ``float``
format. This operation often provides better accuracy than the direct
expression ``(x * y) + z``.
This function follows the specification of the fusedMultiplyAdd operation
described in the IEEE 754 standard. The standard leaves one case
implementation-defined, namely the result of ``fma(0, inf, nan)``
and ``fma(inf, 0, nan)``. In these cases, ``math.fma`` returns a NaN,
and does not raise any exception.
.. versionadded:: 3.13
.. function:: fmod(x, y)
Return ``fmod(x, y)``, as defined by the platform C library. Note that the

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@ -383,6 +383,16 @@ marshal
code objects which are incompatible between Python versions.
(Contributed by Serhiy Storchaka in :gh:`113626`.)
math
----
A new function :func:`~math.fma` for fused multiply-add operations has been
added. This function computes ``x * y + z`` with only a single round, and so
avoids any intermediate loss of precision. It wraps the ``fma()`` function
provided by C99, and follows the specification of the IEEE 754
"fusedMultiplyAdd" operation for special cases.
(Contributed by Mark Dickinson and Victor Stinner in :gh:`73468`.)
mmap
----

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@ -2613,6 +2613,244 @@ class IsCloseTests(unittest.TestCase):
self.assertAllNotClose(fraction_examples, rel_tol=1e-9)
class FMATests(unittest.TestCase):
""" Tests for math.fma. """
def test_fma_nan_results(self):
# Selected representative values.
values = [
-math.inf, -1e300, -2.3, -1e-300, -0.0,
0.0, 1e-300, 2.3, 1e300, math.inf, math.nan
]
# If any input is a NaN, the result should be a NaN, too.
for a, b in itertools.product(values, repeat=2):
self.assertIsNaN(math.fma(math.nan, a, b))
self.assertIsNaN(math.fma(a, math.nan, b))
self.assertIsNaN(math.fma(a, b, math.nan))
def test_fma_infinities(self):
# Cases involving infinite inputs or results.
positives = [1e-300, 2.3, 1e300, math.inf]
finites = [-1e300, -2.3, -1e-300, -0.0, 0.0, 1e-300, 2.3, 1e300]
non_nans = [-math.inf, -2.3, -0.0, 0.0, 2.3, math.inf]
# ValueError due to inf * 0 computation.
for c in non_nans:
for infinity in [math.inf, -math.inf]:
for zero in [0.0, -0.0]:
with self.assertRaises(ValueError):
math.fma(infinity, zero, c)
with self.assertRaises(ValueError):
math.fma(zero, infinity, c)
# ValueError when a*b and c both infinite of opposite signs.
for b in positives:
with self.assertRaises(ValueError):
math.fma(math.inf, b, -math.inf)
with self.assertRaises(ValueError):
math.fma(math.inf, -b, math.inf)
with self.assertRaises(ValueError):
math.fma(-math.inf, -b, -math.inf)
with self.assertRaises(ValueError):
math.fma(-math.inf, b, math.inf)
with self.assertRaises(ValueError):
math.fma(b, math.inf, -math.inf)
with self.assertRaises(ValueError):
math.fma(-b, math.inf, math.inf)
with self.assertRaises(ValueError):
math.fma(-b, -math.inf, -math.inf)
with self.assertRaises(ValueError):
math.fma(b, -math.inf, math.inf)
# Infinite result when a*b and c both infinite of the same sign.
for b in positives:
self.assertEqual(math.fma(math.inf, b, math.inf), math.inf)
self.assertEqual(math.fma(math.inf, -b, -math.inf), -math.inf)
self.assertEqual(math.fma(-math.inf, -b, math.inf), math.inf)
self.assertEqual(math.fma(-math.inf, b, -math.inf), -math.inf)
self.assertEqual(math.fma(b, math.inf, math.inf), math.inf)
self.assertEqual(math.fma(-b, math.inf, -math.inf), -math.inf)
self.assertEqual(math.fma(-b, -math.inf, math.inf), math.inf)
self.assertEqual(math.fma(b, -math.inf, -math.inf), -math.inf)
# Infinite result when a*b finite, c infinite.
for a, b in itertools.product(finites, finites):
self.assertEqual(math.fma(a, b, math.inf), math.inf)
self.assertEqual(math.fma(a, b, -math.inf), -math.inf)
# Infinite result when a*b infinite, c finite.
for b, c in itertools.product(positives, finites):
self.assertEqual(math.fma(math.inf, b, c), math.inf)
self.assertEqual(math.fma(-math.inf, b, c), -math.inf)
self.assertEqual(math.fma(-math.inf, -b, c), math.inf)
self.assertEqual(math.fma(math.inf, -b, c), -math.inf)
self.assertEqual(math.fma(b, math.inf, c), math.inf)
self.assertEqual(math.fma(b, -math.inf, c), -math.inf)
self.assertEqual(math.fma(-b, -math.inf, c), math.inf)
self.assertEqual(math.fma(-b, math.inf, c), -math.inf)
# gh-73468: On WASI and FreeBSD, libc fma() doesn't implement IEE 754-2008
# properly: it doesn't use the right sign when the result is zero.
@unittest.skipIf(support.is_wasi,
"WASI fma() doesn't implement IEE 754-2008 properly")
@unittest.skipIf(sys.platform.startswith('freebsd'),
"FreeBSD fma() doesn't implement IEE 754-2008 properly")
def test_fma_zero_result(self):
nonnegative_finites = [0.0, 1e-300, 2.3, 1e300]
# Zero results from exact zero inputs.
for b in nonnegative_finites:
self.assertIsPositiveZero(math.fma(0.0, b, 0.0))
self.assertIsPositiveZero(math.fma(0.0, b, -0.0))
self.assertIsNegativeZero(math.fma(0.0, -b, -0.0))
self.assertIsPositiveZero(math.fma(0.0, -b, 0.0))
self.assertIsPositiveZero(math.fma(-0.0, -b, 0.0))
self.assertIsPositiveZero(math.fma(-0.0, -b, -0.0))
self.assertIsNegativeZero(math.fma(-0.0, b, -0.0))
self.assertIsPositiveZero(math.fma(-0.0, b, 0.0))
self.assertIsPositiveZero(math.fma(b, 0.0, 0.0))
self.assertIsPositiveZero(math.fma(b, 0.0, -0.0))
self.assertIsNegativeZero(math.fma(-b, 0.0, -0.0))
self.assertIsPositiveZero(math.fma(-b, 0.0, 0.0))
self.assertIsPositiveZero(math.fma(-b, -0.0, 0.0))
self.assertIsPositiveZero(math.fma(-b, -0.0, -0.0))
self.assertIsNegativeZero(math.fma(b, -0.0, -0.0))
self.assertIsPositiveZero(math.fma(b, -0.0, 0.0))
# Exact zero result from nonzero inputs.
self.assertIsPositiveZero(math.fma(2.0, 2.0, -4.0))
self.assertIsPositiveZero(math.fma(2.0, -2.0, 4.0))
self.assertIsPositiveZero(math.fma(-2.0, -2.0, -4.0))
self.assertIsPositiveZero(math.fma(-2.0, 2.0, 4.0))
# Underflow to zero.
tiny = 1e-300
self.assertIsPositiveZero(math.fma(tiny, tiny, 0.0))
self.assertIsNegativeZero(math.fma(tiny, -tiny, 0.0))
self.assertIsPositiveZero(math.fma(-tiny, -tiny, 0.0))
self.assertIsNegativeZero(math.fma(-tiny, tiny, 0.0))
self.assertIsPositiveZero(math.fma(tiny, tiny, -0.0))
self.assertIsNegativeZero(math.fma(tiny, -tiny, -0.0))
self.assertIsPositiveZero(math.fma(-tiny, -tiny, -0.0))
self.assertIsNegativeZero(math.fma(-tiny, tiny, -0.0))
# Corner case where rounding the multiplication would
# give the wrong result.
x = float.fromhex('0x1p-500')
y = float.fromhex('0x1p-550')
z = float.fromhex('0x1p-1000')
self.assertIsNegativeZero(math.fma(x-y, x+y, -z))
self.assertIsPositiveZero(math.fma(y-x, x+y, z))
self.assertIsNegativeZero(math.fma(y-x, -(x+y), -z))
self.assertIsPositiveZero(math.fma(x-y, -(x+y), z))
def test_fma_overflow(self):
a = b = float.fromhex('0x1p512')
c = float.fromhex('0x1p1023')
# Overflow from multiplication.
with self.assertRaises(OverflowError):
math.fma(a, b, 0.0)
self.assertEqual(math.fma(a, b/2.0, 0.0), c)
# Overflow from the addition.
with self.assertRaises(OverflowError):
math.fma(a, b/2.0, c)
# No overflow, even though a*b overflows a float.
self.assertEqual(math.fma(a, b, -c), c)
# Extreme case: a * b is exactly at the overflow boundary, so the
# tiniest offset makes a difference between overflow and a finite
# result.
a = float.fromhex('0x1.ffffffc000000p+511')
b = float.fromhex('0x1.0000002000000p+512')
c = float.fromhex('0x0.0000000000001p-1022')
with self.assertRaises(OverflowError):
math.fma(a, b, 0.0)
with self.assertRaises(OverflowError):
math.fma(a, b, c)
self.assertEqual(math.fma(a, b, -c),
float.fromhex('0x1.fffffffffffffp+1023'))
# Another extreme case: here a*b is about as large as possible subject
# to math.fma(a, b, c) being finite.
a = float.fromhex('0x1.ae565943785f9p+512')
b = float.fromhex('0x1.3094665de9db8p+512')
c = float.fromhex('0x1.fffffffffffffp+1023')
self.assertEqual(math.fma(a, b, -c), c)
def test_fma_single_round(self):
a = float.fromhex('0x1p-50')
self.assertEqual(math.fma(a - 1.0, a + 1.0, 1.0), a*a)
def test_random(self):
# A collection of randomly generated inputs for which the naive FMA
# (with two rounds) gives a different result from a singly-rounded FMA.
# tuples (a, b, c, expected)
test_values = [
('0x1.694adde428b44p-1', '0x1.371b0d64caed7p-1',
'0x1.f347e7b8deab8p-4', '0x1.19f10da56c8adp-1'),
('0x1.605401ccc6ad6p-2', '0x1.ce3a40bf56640p-2',
'0x1.96e3bf7bf2e20p-2', '0x1.1af6d8aa83101p-1'),
('0x1.e5abd653a67d4p-2', '0x1.a2e400209b3e6p-1',
'0x1.a90051422ce13p-1', '0x1.37d68cc8c0fbbp+0'),
('0x1.f94e8efd54700p-2', '0x1.123065c812cebp-1',
'0x1.458f86fb6ccd0p-1', '0x1.ccdcee26a3ff3p-1'),
('0x1.bd926f1eedc96p-1', '0x1.eee9ca68c5740p-1',
'0x1.960c703eb3298p-2', '0x1.3cdcfb4fdb007p+0'),
('0x1.27348350fbccdp-1', '0x1.3b073914a53f1p-1',
'0x1.e300da5c2b4cbp-1', '0x1.4c51e9a3c4e29p+0'),
('0x1.2774f00b3497bp-1', '0x1.7038ec336bff0p-2',
'0x1.2f6f2ccc3576bp-1', '0x1.99ad9f9c2688bp-1'),
('0x1.51d5a99300e5cp-1', '0x1.5cd74abd445a1p-1',
'0x1.8880ab0bbe530p-1', '0x1.3756f96b91129p+0'),
('0x1.73cb965b821b8p-2', '0x1.218fd3d8d5371p-1',
'0x1.d1ea966a1f758p-2', '0x1.5217b8fd90119p-1'),
('0x1.4aa98e890b046p-1', '0x1.954d85dff1041p-1',
'0x1.122b59317ebdfp-1', '0x1.0bf644b340cc5p+0'),
('0x1.e28f29e44750fp-1', '0x1.4bcc4fdcd18fep-1',
'0x1.fd47f81298259p-1', '0x1.9b000afbc9995p+0'),
('0x1.d2e850717fe78p-3', '0x1.1dd7531c303afp-1',
'0x1.e0869746a2fc2p-2', '0x1.316df6eb26439p-1'),
('0x1.cf89c75ee6fbap-2', '0x1.b23decdc66825p-1',
'0x1.3d1fe76ac6168p-1', '0x1.00d8ea4c12abbp+0'),
('0x1.3265ae6f05572p-2', '0x1.16d7ec285f7a2p-1',
'0x1.0b8405b3827fbp-1', '0x1.5ef33c118a001p-1'),
('0x1.c4d1bf55ec1a5p-1', '0x1.bc59618459e12p-2',
'0x1.ce5b73dc1773dp-1', '0x1.496cf6164f99bp+0'),
('0x1.d350026ac3946p-1', '0x1.9a234e149a68cp-2',
'0x1.f5467b1911fd6p-2', '0x1.b5cee3225caa5p-1'),
]
for a_hex, b_hex, c_hex, expected_hex in test_values:
a = float.fromhex(a_hex)
b = float.fromhex(b_hex)
c = float.fromhex(c_hex)
expected = float.fromhex(expected_hex)
self.assertEqual(math.fma(a, b, c), expected)
self.assertEqual(math.fma(b, a, c), expected)
# Custom assertions.
def assertIsNaN(self, value):
self.assertTrue(
math.isnan(value),
msg="Expected a NaN, got {!r}".format(value)
)
def assertIsPositiveZero(self, value):
self.assertTrue(
value == 0 and math.copysign(1, value) > 0,
msg="Expected a positive zero, got {!r}".format(value)
)
def assertIsNegativeZero(self, value):
self.assertTrue(
value == 0 and math.copysign(1, value) < 0,
msg="Expected a negative zero, got {!r}".format(value)
)
def load_tests(loader, tests, pattern):
from doctest import DocFileSuite
tests.addTest(DocFileSuite(os.path.join("mathdata", "ieee754.txt")))

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@ -0,0 +1,2 @@
Added new :func:`math.fma` function, wrapping C99's ``fma()`` operation:
fused multiply-add function. Patch by Mark Dickinson and Victor Stinner.

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@ -204,6 +204,67 @@ PyDoc_STRVAR(math_log10__doc__,
#define MATH_LOG10_METHODDEF \
{"log10", (PyCFunction)math_log10, METH_O, math_log10__doc__},
PyDoc_STRVAR(math_fma__doc__,
"fma($module, x, y, z, /)\n"
"--\n"
"\n"
"Fused multiply-add operation.\n"
"\n"
"Compute (x * y) + z with a single round.");
#define MATH_FMA_METHODDEF \
{"fma", _PyCFunction_CAST(math_fma), METH_FASTCALL, math_fma__doc__},
static PyObject *
math_fma_impl(PyObject *module, double x, double y, double z);
static PyObject *
math_fma(PyObject *module, PyObject *const *args, Py_ssize_t nargs)
{
PyObject *return_value = NULL;
double x;
double y;
double z;
if (!_PyArg_CheckPositional("fma", nargs, 3, 3)) {
goto exit;
}
if (PyFloat_CheckExact(args[0])) {
x = PyFloat_AS_DOUBLE(args[0]);
}
else
{
x = PyFloat_AsDouble(args[0]);
if (x == -1.0 && PyErr_Occurred()) {
goto exit;
}
}
if (PyFloat_CheckExact(args[1])) {
y = PyFloat_AS_DOUBLE(args[1]);
}
else
{
y = PyFloat_AsDouble(args[1]);
if (y == -1.0 && PyErr_Occurred()) {
goto exit;
}
}
if (PyFloat_CheckExact(args[2])) {
z = PyFloat_AS_DOUBLE(args[2]);
}
else
{
z = PyFloat_AsDouble(args[2]);
if (z == -1.0 && PyErr_Occurred()) {
goto exit;
}
}
return_value = math_fma_impl(module, x, y, z);
exit:
return return_value;
}
PyDoc_STRVAR(math_fmod__doc__,
"fmod($module, x, y, /)\n"
"--\n"
@ -950,4 +1011,4 @@ math_ulp(PyObject *module, PyObject *arg)
exit:
return return_value;
}
/*[clinic end generated code: output=6b2eeaed8d8a76d5 input=a9049054013a1b77]*/
/*[clinic end generated code: output=9fe3f007f474e015 input=a9049054013a1b77]*/

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@ -2321,6 +2321,48 @@ math_log10(PyObject *module, PyObject *x)
}
/*[clinic input]
math.fma
x: double
y: double
z: double
/
Fused multiply-add operation.
Compute (x * y) + z with a single round.
[clinic start generated code]*/
static PyObject *
math_fma_impl(PyObject *module, double x, double y, double z)
/*[clinic end generated code: output=4fc8626dbc278d17 input=e3ad1f4a4c89626e]*/
{
double r = fma(x, y, z);
/* Fast path: if we got a finite result, we're done. */
if (Py_IS_FINITE(r)) {
return PyFloat_FromDouble(r);
}
/* Non-finite result. Raise an exception if appropriate, else return r. */
if (Py_IS_NAN(r)) {
if (!Py_IS_NAN(x) && !Py_IS_NAN(y) && !Py_IS_NAN(z)) {
/* NaN result from non-NaN inputs. */
PyErr_SetString(PyExc_ValueError, "invalid operation in fma");
return NULL;
}
}
else if (Py_IS_FINITE(x) && Py_IS_FINITE(y) && Py_IS_FINITE(z)) {
/* Infinite result from finite inputs. */
PyErr_SetString(PyExc_OverflowError, "overflow in fma");
return NULL;
}
return PyFloat_FromDouble(r);
}
/*[clinic input]
math.fmod
@ -4094,6 +4136,7 @@ static PyMethodDef math_methods[] = {
{"fabs", math_fabs, METH_O, math_fabs_doc},
MATH_FACTORIAL_METHODDEF
MATH_FLOOR_METHODDEF
MATH_FMA_METHODDEF
MATH_FMOD_METHODDEF
MATH_FREXP_METHODDEF
MATH_FSUM_METHODDEF