mirror of https://github.com/python/cpython
Issue #29282: Backed out changeset b33012ef1417
This commit is contained in:
Mark Dickinson
parent
d1b230e48b
commit
5e65cd39df
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@ -57,21 +57,6 @@ Number-theoretic and representation functions
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If *x* is not a float, delegates to ``x.__floor__()``, which should return an
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:class:`~numbers.Integral` value.
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.. function:: fma(x, y, z)
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Fused multiply-add operation. Return ``(x * y) + z``, computed as though with
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infinite precision and range followed by a single round to the ``float``
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format. This operation often provides better accuracy than the direct
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expression ``(x * y) + z``.
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This function follows the specification of the fusedMultiplyAdd operation
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described in the IEEE 754-2008 standard. The standard leaves one case
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implementation-defined, namely the result of ``fma(0, inf, nan)``
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and ``fma(inf, 0, nan)``. In these cases, ``math.fma`` returns a NaN,
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and does not raise any exception.
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.. versionadded:: 3.7
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.. function:: fmod(x, y)
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@ -100,15 +100,6 @@ The :const:`~unittest.mock.sentinel` attributes now preserve their identity
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when they are :mod:`copied <copy>` or :mod:`pickled <pickle>`.
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(Contributed by Serhiy Storchaka in :issue:`20804`.)
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math module
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-----------
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A new function :func:`~math.fma` for fused multiply-add operations has been
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added. This function computes ``x * y + z`` with only a single round, and so
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avoids any intermediate loss of precision. It wraps the ``fma`` function
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provided by C99, and follows the specification of the IEEE 754-2008
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"fusedMultiplyAdd" operation for special cases.
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Optimizations
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=============
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@ -4,7 +4,6 @@
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from test.support import run_unittest, verbose, requires_IEEE_754
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from test import support
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import unittest
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import itertools
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import math
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import os
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import platform
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@ -1411,244 +1410,11 @@ class IsCloseTests(unittest.TestCase):
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self.assertAllNotClose(fraction_examples, rel_tol=1e-9)
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class FMATests(unittest.TestCase):
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""" Tests for math.fma. """
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def test_fma_nan_results(self):
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# Selected representative values.
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values = [
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-math.inf, -1e300, -2.3, -1e-300, -0.0,
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0.0, 1e-300, 2.3, 1e300, math.inf, math.nan
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]
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# If any input is a NaN, the result should be a NaN, too.
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for a, b in itertools.product(values, repeat=2):
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self.assertIsNaN(math.fma(math.nan, a, b))
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self.assertIsNaN(math.fma(a, math.nan, b))
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self.assertIsNaN(math.fma(a, b, math.nan))
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def test_fma_infinities(self):
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# Cases involving infinite inputs or results.
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positives = [1e-300, 2.3, 1e300, math.inf]
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finites = [-1e300, -2.3, -1e-300, -0.0, 0.0, 1e-300, 2.3, 1e300]
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non_nans = [-math.inf, -2.3, -0.0, 0.0, 2.3, math.inf]
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# ValueError due to inf * 0 computation.
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for c in non_nans:
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for infinity in [math.inf, -math.inf]:
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for zero in [0.0, -0.0]:
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with self.assertRaises(ValueError):
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math.fma(infinity, zero, c)
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with self.assertRaises(ValueError):
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math.fma(zero, infinity, c)
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# ValueError when a*b and c both infinite of opposite signs.
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for b in positives:
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with self.assertRaises(ValueError):
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math.fma(math.inf, b, -math.inf)
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with self.assertRaises(ValueError):
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math.fma(math.inf, -b, math.inf)
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with self.assertRaises(ValueError):
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math.fma(-math.inf, -b, -math.inf)
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with self.assertRaises(ValueError):
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math.fma(-math.inf, b, math.inf)
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with self.assertRaises(ValueError):
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math.fma(b, math.inf, -math.inf)
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with self.assertRaises(ValueError):
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math.fma(-b, math.inf, math.inf)
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with self.assertRaises(ValueError):
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math.fma(-b, -math.inf, -math.inf)
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with self.assertRaises(ValueError):
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math.fma(b, -math.inf, math.inf)
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# Infinite result when a*b and c both infinite of the same sign.
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for b in positives:
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self.assertEqual(math.fma(math.inf, b, math.inf), math.inf)
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self.assertEqual(math.fma(math.inf, -b, -math.inf), -math.inf)
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self.assertEqual(math.fma(-math.inf, -b, math.inf), math.inf)
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self.assertEqual(math.fma(-math.inf, b, -math.inf), -math.inf)
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self.assertEqual(math.fma(b, math.inf, math.inf), math.inf)
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self.assertEqual(math.fma(-b, math.inf, -math.inf), -math.inf)
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self.assertEqual(math.fma(-b, -math.inf, math.inf), math.inf)
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self.assertEqual(math.fma(b, -math.inf, -math.inf), -math.inf)
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# Infinite result when a*b finite, c infinite.
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for a, b in itertools.product(finites, finites):
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self.assertEqual(math.fma(a, b, math.inf), math.inf)
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self.assertEqual(math.fma(a, b, -math.inf), -math.inf)
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# Infinite result when a*b infinite, c finite.
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for b, c in itertools.product(positives, finites):
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self.assertEqual(math.fma(math.inf, b, c), math.inf)
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self.assertEqual(math.fma(-math.inf, b, c), -math.inf)
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self.assertEqual(math.fma(-math.inf, -b, c), math.inf)
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self.assertEqual(math.fma(math.inf, -b, c), -math.inf)
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self.assertEqual(math.fma(b, math.inf, c), math.inf)
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self.assertEqual(math.fma(b, -math.inf, c), -math.inf)
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self.assertEqual(math.fma(-b, -math.inf, c), math.inf)
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self.assertEqual(math.fma(-b, math.inf, c), -math.inf)
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def test_fma_zero_result(self):
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nonnegative_finites = [0.0, 1e-300, 2.3, 1e300]
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# Zero results from exact zero inputs.
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for b in nonnegative_finites:
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self.assertIsPositiveZero(math.fma(0.0, b, 0.0))
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self.assertIsPositiveZero(math.fma(0.0, b, -0.0))
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self.assertIsNegativeZero(math.fma(0.0, -b, -0.0))
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self.assertIsPositiveZero(math.fma(0.0, -b, 0.0))
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self.assertIsPositiveZero(math.fma(-0.0, -b, 0.0))
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self.assertIsPositiveZero(math.fma(-0.0, -b, -0.0))
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self.assertIsNegativeZero(math.fma(-0.0, b, -0.0))
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self.assertIsPositiveZero(math.fma(-0.0, b, 0.0))
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self.assertIsPositiveZero(math.fma(b, 0.0, 0.0))
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self.assertIsPositiveZero(math.fma(b, 0.0, -0.0))
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self.assertIsNegativeZero(math.fma(-b, 0.0, -0.0))
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self.assertIsPositiveZero(math.fma(-b, 0.0, 0.0))
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self.assertIsPositiveZero(math.fma(-b, -0.0, 0.0))
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self.assertIsPositiveZero(math.fma(-b, -0.0, -0.0))
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self.assertIsNegativeZero(math.fma(b, -0.0, -0.0))
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self.assertIsPositiveZero(math.fma(b, -0.0, 0.0))
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# Exact zero result from nonzero inputs.
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self.assertIsPositiveZero(math.fma(2.0, 2.0, -4.0))
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self.assertIsPositiveZero(math.fma(2.0, -2.0, 4.0))
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self.assertIsPositiveZero(math.fma(-2.0, -2.0, -4.0))
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self.assertIsPositiveZero(math.fma(-2.0, 2.0, 4.0))
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# Underflow to zero.
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tiny = 1e-300
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self.assertIsPositiveZero(math.fma(tiny, tiny, 0.0))
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self.assertIsNegativeZero(math.fma(tiny, -tiny, 0.0))
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self.assertIsPositiveZero(math.fma(-tiny, -tiny, 0.0))
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self.assertIsNegativeZero(math.fma(-tiny, tiny, 0.0))
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self.assertIsPositiveZero(math.fma(tiny, tiny, -0.0))
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self.assertIsNegativeZero(math.fma(tiny, -tiny, -0.0))
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self.assertIsPositiveZero(math.fma(-tiny, -tiny, -0.0))
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self.assertIsNegativeZero(math.fma(-tiny, tiny, -0.0))
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# Corner case where rounding the multiplication would
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# give the wrong result.
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x = float.fromhex('0x1p-500')
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y = float.fromhex('0x1p-550')
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z = float.fromhex('0x1p-1000')
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self.assertIsNegativeZero(math.fma(x-y, x+y, -z))
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self.assertIsPositiveZero(math.fma(y-x, x+y, z))
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self.assertIsNegativeZero(math.fma(y-x, -(x+y), -z))
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self.assertIsPositiveZero(math.fma(x-y, -(x+y), z))
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def test_fma_overflow(self):
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a = b = float.fromhex('0x1p512')
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c = float.fromhex('0x1p1023')
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# Overflow from multiplication.
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with self.assertRaises(OverflowError):
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math.fma(a, b, 0.0)
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self.assertEqual(math.fma(a, b/2.0, 0.0), c)
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# Overflow from the addition.
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with self.assertRaises(OverflowError):
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math.fma(a, b/2.0, c)
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# No overflow, even though a*b overflows a float.
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self.assertEqual(math.fma(a, b, -c), c)
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# Extreme case: a * b is exactly at the overflow boundary, so the
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# tiniest offset makes a difference between overflow and a finite
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# result.
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a = float.fromhex('0x1.ffffffc000000p+511')
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b = float.fromhex('0x1.0000002000000p+512')
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c = float.fromhex('0x0.0000000000001p-1022')
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with self.assertRaises(OverflowError):
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math.fma(a, b, 0.0)
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with self.assertRaises(OverflowError):
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math.fma(a, b, c)
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self.assertEqual(math.fma(a, b, -c),
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float.fromhex('0x1.fffffffffffffp+1023'))
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# Another extreme case: here a*b is about as large as possible subject
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# to math.fma(a, b, c) being finite.
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a = float.fromhex('0x1.ae565943785f9p+512')
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b = float.fromhex('0x1.3094665de9db8p+512')
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c = float.fromhex('0x1.fffffffffffffp+1023')
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self.assertEqual(math.fma(a, b, -c), c)
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def test_fma_single_round(self):
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a = float.fromhex('0x1p-50')
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self.assertEqual(math.fma(a - 1.0, a + 1.0, 1.0), a*a)
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def test_random(self):
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# A collection of randomly generated inputs for which the naive FMA
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# (with two rounds) gives a different result from a singly-rounded FMA.
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# tuples (a, b, c, expected)
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test_values = [
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('0x1.694adde428b44p-1', '0x1.371b0d64caed7p-1',
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'0x1.f347e7b8deab8p-4', '0x1.19f10da56c8adp-1'),
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('0x1.605401ccc6ad6p-2', '0x1.ce3a40bf56640p-2',
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'0x1.96e3bf7bf2e20p-2', '0x1.1af6d8aa83101p-1'),
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('0x1.e5abd653a67d4p-2', '0x1.a2e400209b3e6p-1',
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'0x1.a90051422ce13p-1', '0x1.37d68cc8c0fbbp+0'),
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('0x1.f94e8efd54700p-2', '0x1.123065c812cebp-1',
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'0x1.458f86fb6ccd0p-1', '0x1.ccdcee26a3ff3p-1'),
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('0x1.bd926f1eedc96p-1', '0x1.eee9ca68c5740p-1',
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'0x1.960c703eb3298p-2', '0x1.3cdcfb4fdb007p+0'),
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('0x1.27348350fbccdp-1', '0x1.3b073914a53f1p-1',
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'0x1.e300da5c2b4cbp-1', '0x1.4c51e9a3c4e29p+0'),
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('0x1.2774f00b3497bp-1', '0x1.7038ec336bff0p-2',
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'0x1.2f6f2ccc3576bp-1', '0x1.99ad9f9c2688bp-1'),
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('0x1.51d5a99300e5cp-1', '0x1.5cd74abd445a1p-1',
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'0x1.8880ab0bbe530p-1', '0x1.3756f96b91129p+0'),
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('0x1.73cb965b821b8p-2', '0x1.218fd3d8d5371p-1',
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'0x1.d1ea966a1f758p-2', '0x1.5217b8fd90119p-1'),
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('0x1.4aa98e890b046p-1', '0x1.954d85dff1041p-1',
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'0x1.122b59317ebdfp-1', '0x1.0bf644b340cc5p+0'),
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('0x1.e28f29e44750fp-1', '0x1.4bcc4fdcd18fep-1',
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'0x1.fd47f81298259p-1', '0x1.9b000afbc9995p+0'),
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('0x1.d2e850717fe78p-3', '0x1.1dd7531c303afp-1',
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'0x1.e0869746a2fc2p-2', '0x1.316df6eb26439p-1'),
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('0x1.cf89c75ee6fbap-2', '0x1.b23decdc66825p-1',
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'0x1.3d1fe76ac6168p-1', '0x1.00d8ea4c12abbp+0'),
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('0x1.3265ae6f05572p-2', '0x1.16d7ec285f7a2p-1',
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'0x1.0b8405b3827fbp-1', '0x1.5ef33c118a001p-1'),
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('0x1.c4d1bf55ec1a5p-1', '0x1.bc59618459e12p-2',
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'0x1.ce5b73dc1773dp-1', '0x1.496cf6164f99bp+0'),
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('0x1.d350026ac3946p-1', '0x1.9a234e149a68cp-2',
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'0x1.f5467b1911fd6p-2', '0x1.b5cee3225caa5p-1'),
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]
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for a_hex, b_hex, c_hex, expected_hex in test_values:
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a = float.fromhex(a_hex)
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b = float.fromhex(b_hex)
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c = float.fromhex(c_hex)
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expected = float.fromhex(expected_hex)
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self.assertEqual(math.fma(a, b, c), expected)
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self.assertEqual(math.fma(b, a, c), expected)
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# Custom assertions.
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def assertIsNaN(self, value):
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self.assertTrue(
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math.isnan(value),
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msg="Expected a NaN, got {!r}".format(value)
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)
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def assertIsPositiveZero(self, value):
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self.assertTrue(
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value == 0 and math.copysign(1, value) > 0,
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msg="Expected a positive zero, got {!r}".format(value)
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)
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def assertIsNegativeZero(self, value):
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self.assertTrue(
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value == 0 and math.copysign(1, value) < 0,
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msg="Expected a negative zero, got {!r}".format(value)
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)
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def test_main():
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from doctest import DocFileSuite
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suite = unittest.TestSuite()
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suite.addTest(unittest.makeSuite(MathTests))
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suite.addTest(unittest.makeSuite(IsCloseTests))
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suite.addTest(unittest.makeSuite(FMATests))
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suite.addTest(DocFileSuite("ieee754.txt"))
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run_unittest(suite)
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@ -215,9 +215,6 @@ Core and Builtins
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Library
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-------
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- Issue #29282: Added new math.fma function, wrapping C99's fma
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operation.
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- Issue #29197: Removed deprecated function ntpath.splitunc().
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- Issue #29210: Removed support of deprecated argument "exclude" in
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@ -80,40 +80,6 @@ PyDoc_STRVAR(math_factorial__doc__,
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#define MATH_FACTORIAL_METHODDEF \
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{"factorial", (PyCFunction)math_factorial, METH_O, math_factorial__doc__},
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PyDoc_STRVAR(math_fma__doc__,
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"fma($module, x, y, z, /)\n"
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"--\n"
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"\n"
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"Fused multiply-add operation. Compute (x * y) + z with a single round.");
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#define MATH_FMA_METHODDEF \
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{"fma", (PyCFunction)math_fma, METH_FASTCALL, math_fma__doc__},
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static PyObject *
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math_fma_impl(PyObject *module, double x, double y, double z);
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static PyObject *
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math_fma(PyObject *module, PyObject **args, Py_ssize_t nargs, PyObject *kwnames)
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{
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PyObject *return_value = NULL;
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double x;
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double y;
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double z;
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if (!_PyArg_ParseStack(args, nargs, "ddd:fma",
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&x, &y, &z)) {
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goto exit;
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}
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if (!_PyArg_NoStackKeywords("fma", kwnames)) {
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goto exit;
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}
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return_value = math_fma_impl(module, x, y, z);
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exit:
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return return_value;
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}
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PyDoc_STRVAR(math_trunc__doc__,
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"trunc($module, x, /)\n"
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"--\n"
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@ -570,4 +536,4 @@ math_isclose(PyObject *module, PyObject **args, Py_ssize_t nargs, PyObject *kwna
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exit:
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return return_value;
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}
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/*[clinic end generated code: output=f428e1075d00c334 input=a9049054013a1b77]*/
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/*[clinic end generated code: output=71806f73a5c4bf0b input=a9049054013a1b77]*/
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@ -1595,47 +1595,6 @@ math_factorial(PyObject *module, PyObject *arg)
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}
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/*[clinic input]
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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=2ae8bb2a6e0f8b77]*/
|
||||
{
|
||||
double r;
|
||||
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.trunc
|
||||
|
||||
|
|
@ -2265,7 +2224,6 @@ 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
|
||||
|
|
|
|||
Loading…
Reference in New Issue