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Modified sqrt/rsqrt for denormal handling.

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This commit is contained in:
Antonio Sánchez
2022-03-02 17:20:47 +00:00
parent 1c2690ed24
commit 9c07e201ff
4 changed files with 58 additions and 86 deletions
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48
test/packetmath.cpp
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@@ -682,6 +682,7 @@ void packetmath_test_IEEE_corner_cases(const RefFunctorT& ref_fun,
const FunctorT& fun) {
const int PacketSize = internal::unpacket_traits<Packet>::size;
const Scalar norm_min = (std::numeric_limits<Scalar>::min)();
const Scalar norm_max = (std::numeric_limits<Scalar>::max)();
constexpr int size = PacketSize * 2;
EIGEN_ALIGN_MAX Scalar data1[size];
@@ -694,37 +695,36 @@ void packetmath_test_IEEE_corner_cases(const RefFunctorT& ref_fun,
// Test for subnormals.
if (std::numeric_limits<Scalar>::has_denorm == std::denorm_present) {
// When EIGEN_FAST_MATH is 1 we relax the conditions slightly, and allow the function
// to return the same value for subnormals as the reference would return for zero with
// the same sign as the input.
// TODO(rmlarsen): Currently we ignore the error that occurs if the input is equal to
// denorm_min. Specifically, the term 0.5*x in the Newton iteration for reciprocal sqrt
// underflows to zero and the result ends up a factor of 2 too large.
#if EIGEN_FAST_MATH
// TODO(rmlarsen): Remove factor of 2 here if we can fix the underflow in reciprocal sqrt.
data1[0] = Scalar(2) * std::numeric_limits<Scalar>::denorm_min();
data1[1] = -data1[0];
test::packet_helper<Cond, Packet> h;
h.store(data2, fun(h.load(data1)));
for (int i=0; i < 2; ++i) {
const Scalar ref_zero = ref_fun(data1[i] < 0 ? -Scalar(0) : Scalar(0));
const Scalar ref_val = ref_fun(data1[i]);
// TODO(rmlarsen): Remove debug cruft.
// std::cerr << "x = " << data1[i] << "y = " << data2[i] << ", ref_val = " << ref_val << ", ref_zero " << ref_zero << std::endl;
VERIFY(((std::isnan)(data2[i]) && (std::isnan)(ref_val)) || data2[i] == ref_zero ||
verifyIsApprox(data2[i], ref_val));
for (int scale = 1; scale < 5; ++scale) {
// When EIGEN_FAST_MATH is 1 we relax the conditions slightly, and allow the function
// to return the same value for subnormals as the reference would return for zero with
// the same sign as the input.
#if EIGEN_FAST_MATH
data1[0] = Scalar(scale) * std::numeric_limits<Scalar>::denorm_min();
data1[1] = -data1[0];
test::packet_helper<Cond, Packet> h;
h.store(data2, fun(h.load(data1)));
for (int i=0; i < PacketSize; ++i) {
const Scalar ref_zero = ref_fun(data1[i] < 0 ? -Scalar(0) : Scalar(0));
const Scalar ref_val = ref_fun(data1[i]);
VERIFY(((std::isnan)(data2[i]) && (std::isnan)(ref_val)) || data2[i] == ref_zero ||
verifyIsApprox(data2[i], ref_val));
}
#else
CHECK_CWISE1_IF(Cond, ref_fun, fun);
#endif
}
#else
data1[0] = std::numeric_limits<Scalar>::denorm_min();
data1[1] = -data1[0];
CHECK_CWISE1_IF(Cond, ref_fun, fun);
#endif
}
// Test for smallest normalized floats.
data1[0] = norm_min;
data1[1] = -data1[0];
CHECK_CWISE1_IF(Cond, ref_fun, fun);
// Test for largest floats.
data1[0] = norm_max;
data1[1] = -data1[0];
CHECK_CWISE1_IF(Cond, ref_fun, fun);
// Test for zeros.
data1[0] = Scalar(0.0);