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Fix arm32 issues.

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(cherry picked from commit a73970a8640330c4908d68ef9257fd31a4fdae93)
This commit is contained in:
Antonio Sánchez 2024-01-23 22:04:55 +00:00 committed by C. Antonio Sanchez
parent f23b8c0d78
commit c23abcf25c
4 changed files with 34 additions and 14 deletions
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10
Eigen/src/Core/arch/Default/GenericPacketMathFunctions.h
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@ -642,10 +642,10 @@ Packet psincos_float(const Packet& _x)
PacketI y_int = preinterpret<PacketI>(y_round); // last 23 digits represent integer (if abs(x)<2^24) PacketI y_int = preinterpret<PacketI>(y_round); // last 23 digits represent integer (if abs(x)<2^24)
y = psub(y_round, cst_rounding_magic); // nearest integer to x*4/pi y = psub(y_round, cst_rounding_magic); // nearest integer to x*4/pi
// Reduce x by y octants to get: -Pi/4 <= x <= +Pi/4 // Subtract y * Pi/2 to reduce x to the interval -Pi/4 <= x <= +Pi/4
// using "Extended precision modular arithmetic" // using "Extended precision modular arithmetic"
#if defined(EIGEN_HAS_SINGLE_INSTRUCTION_MADD) #if defined(EIGEN_VECTORIZE_FMA)
// This version requires true FMA for high accuracy // This version requires true FMA for high accuracy.
// It provides a max error of 1ULP up to (with absolute_error < 5.9605e-08): // It provides a max error of 1ULP up to (with absolute_error < 5.9605e-08):
const float huge_th = ComputeSine ? 117435.992f : 71476.0625f; const float huge_th = ComputeSine ? 117435.992f : 71476.0625f;
x = pmadd(y, pset1<Packet>(-1.57079601287841796875f), x); x = pmadd(y, pset1<Packet>(-1.57079601287841796875f), x);
@ -915,7 +915,7 @@ void fast_twosum(const Packet& x, const Packet& y, Packet& s_hi, Packet& s_lo) {
s_lo = psub(y, t); s_lo = psub(y, t);
} }
#ifdef EIGEN_HAS_SINGLE_INSTRUCTION_MADD #ifdef EIGEN_VECTORIZE_FMA
// This function implements the extended precision product of // This function implements the extended precision product of
// a pair of floating point numbers. Given {x, y}, it computes the pair // a pair of floating point numbers. Given {x, y}, it computes the pair
// {p_hi, p_lo} such that x * y = p_hi + p_lo holds exactly and // {p_hi, p_lo} such that x * y = p_hi + p_lo holds exactly and
@ -966,7 +966,7 @@ void twoprod(const Packet& x, const Packet& y,
p_lo = pmadd(x_lo, y_lo, p_lo); p_lo = pmadd(x_lo, y_lo, p_lo);
} }
#endif // EIGEN_HAS_SINGLE_INSTRUCTION_MADD #endif // EIGEN_VECTORIZE_FMA
// This function implements Dekker's algorithm for the addition // This function implements Dekker's algorithm for the addition

17
Eigen/src/Core/arch/NEON/PacketMath.h
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@ -1089,12 +1089,15 @@ template<> EIGEN_STRONG_INLINE Packet2ul pdiv<Packet2ul>(const Packet2ul& /*a*/,
return pset1<Packet2ul>(0ULL); return pset1<Packet2ul>(0ULL);
} }
#ifdef EIGEN_VECTORIZE_FMA
#ifdef __ARM_FEATURE_FMA template <>
template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c) EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c) {
{ return vfmaq_f32(c,a,b); } return vfmaq_f32(c, a, b);
template<> EIGEN_STRONG_INLINE Packet2f pmadd(const Packet2f& a, const Packet2f& b, const Packet2f& c) }
{ return vfma_f32(c,a,b); } template <>
EIGEN_STRONG_INLINE Packet2f pmadd(const Packet2f& a, const Packet2f& b, const Packet2f& c) {
return vfma_f32(c, a, b);
}
#else #else
template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c) template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c)
{ {
@ -3782,7 +3785,7 @@ template<> EIGEN_STRONG_INLINE Packet2d pmul<Packet2d>(const Packet2d& a, const
template<> EIGEN_STRONG_INLINE Packet2d pdiv<Packet2d>(const Packet2d& a, const Packet2d& b) { return vdivq_f64(a,b); } template<> EIGEN_STRONG_INLINE Packet2d pdiv<Packet2d>(const Packet2d& a, const Packet2d& b) { return vdivq_f64(a,b); }
#ifdef __ARM_FEATURE_FMA #ifdef EIGEN_VECTORIZE_FMA
// See bug 936. See above comment about FMA for float. // See bug 936. See above comment about FMA for float.
template<> EIGEN_STRONG_INLINE Packet2d pmadd(const Packet2d& a, const Packet2d& b, const Packet2d& c) template<> EIGEN_STRONG_INLINE Packet2d pmadd(const Packet2d& a, const Packet2d& b, const Packet2d& c)
{ return vfmaq_f64(c,a,b); } { return vfmaq_f64(c,a,b); }

9
Eigen/src/Core/util/ConfigureVectorization.h
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@ -367,6 +367,7 @@
#define EIGEN_VECTORIZE #define EIGEN_VECTORIZE
#define EIGEN_VECTORIZE_VSX 1 #define EIGEN_VECTORIZE_VSX 1
#define EIGEN_VECTORIZE_FMA
#include <altivec.h> #include <altivec.h>
// We need to #undef all these ugly tokens defined in <altivec.h> // We need to #undef all these ugly tokens defined in <altivec.h>
// => use __vector instead of vector // => use __vector instead of vector
@ -378,6 +379,7 @@
#define EIGEN_VECTORIZE #define EIGEN_VECTORIZE
#define EIGEN_VECTORIZE_ALTIVEC #define EIGEN_VECTORIZE_ALTIVEC
#define EIGEN_VECTORIZE_FMA
#include <altivec.h> #include <altivec.h>
// We need to #undef all these ugly tokens defined in <altivec.h> // We need to #undef all these ugly tokens defined in <altivec.h>
// => use __vector instead of vector // => use __vector instead of vector
@ -438,7 +440,12 @@
#include <arm_fp16.h> #include <arm_fp16.h>
#endif #endif
#if defined(__F16C__) && (!defined(EIGEN_GPUCC) && (!EIGEN_COMP_CLANG || EIGEN_COMP_CLANG>=380)) // Enable FMA for ARM.
#if defined(__ARM_FEATURE_FMA)
#define EIGEN_VECTORIZE_FMA
#endif
#if defined(__F16C__) && !defined(EIGEN_GPUCC) && (!EIGEN_COMP_CLANG_STRICT || EIGEN_COMP_CLANG>=380)
// We can use the optimized fp16 to float and float to fp16 conversion routines // We can use the optimized fp16 to float and float to fp16 conversion routines
#define EIGEN_HAS_FP16_C #define EIGEN_HAS_FP16_C

12
test/array_cwise.cpp
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@ -72,7 +72,17 @@ void pow_test() {
for (int j = 0; j < num_cases; ++j) { for (int j = 0; j < num_cases; ++j) {
Scalar e = static_cast<Scalar>(std::pow(x(i,j), y(i,j))); Scalar e = static_cast<Scalar>(std::pow(x(i,j), y(i,j)));
Scalar a = actual(i, j); Scalar a = actual(i, j);
bool success = (a==e) || ((numext::isfinite)(e) && internal::isApprox(a, e, tol)) || ((numext::isnan)(a) && (numext::isnan)(e)); #if EIGEN_ARCH_ARM
// Work around NEON flush-to-zero mode
// if ref returns a subnormal value and Eigen returns 0, then skip the test
if (a == Scalar(0) &&
(e > -(std::numeric_limits<Scalar>::min)() && e < (std::numeric_limits<Scalar>::min)() &&
e >= -std::numeric_limits<Scalar>::denorm_min() && e <= std::numeric_limits<Scalar>::denorm_min())) {
continue;
}
#endif
bool success = (a == e) || ((numext::isfinite)(e) && internal::isApprox(a, e, tol)) ||
((numext::isnan)(a) && (numext::isnan)(e));
all_pass &= success; all_pass &= success;
if (!success) { if (!success) {
std::cout << "pow(" << x(i,j) << "," << y(i,j) << ") = " << a << " != " << e << std::endl; std::cout << "pow(" << x(i,j) << "," << y(i,j) << ") = " << a << " != " << e << std::endl;