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Fix arm32 float division and related bugs
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2873916f1c
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@ -956,57 +956,6 @@ template<> EIGEN_STRONG_INLINE Packet2ul pmul<Packet2ul>(const Packet2ul& a, con
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vdup_n_u64(vgetq_lane_u64(a, 1)*vgetq_lane_u64(b, 1)));
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vdup_n_u64(vgetq_lane_u64(a, 1)*vgetq_lane_u64(b, 1)));
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}
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}
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template<> EIGEN_STRONG_INLINE Packet2f pdiv<Packet2f>(const Packet2f& a, const Packet2f& b)
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{
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#if EIGEN_ARCH_ARM64
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return vdiv_f32(a,b);
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#else
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Packet2f inv, restep, div;
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// NEON does not offer a divide instruction, we have to do a reciprocal approximation
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// However NEON in contrast to other SIMD engines (AltiVec/SSE), offers
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// a reciprocal estimate AND a reciprocal step -which saves a few instructions
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// vrecpeq_f32() returns an estimate to 1/b, which we will finetune with
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// Newton-Raphson and vrecpsq_f32()
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inv = vrecpe_f32(b);
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// This returns a differential, by which we will have to multiply inv to get a better
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// approximation of 1/b.
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restep = vrecps_f32(b, inv);
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inv = vmul_f32(restep, inv);
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// Finally, multiply a by 1/b and get the wanted result of the division.
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div = vmul_f32(a, inv);
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return div;
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#endif
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}
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template<> EIGEN_STRONG_INLINE Packet4f pdiv<Packet4f>(const Packet4f& a, const Packet4f& b)
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{
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#if EIGEN_ARCH_ARM64
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return vdivq_f32(a,b);
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#else
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Packet4f inv, restep, div;
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// NEON does not offer a divide instruction, we have to do a reciprocal approximation
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// However NEON in contrast to other SIMD engines (AltiVec/SSE), offers
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// a reciprocal estimate AND a reciprocal step -which saves a few instructions
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// vrecpeq_f32() returns an estimate to 1/b, which we will finetune with
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// Newton-Raphson and vrecpsq_f32()
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inv = vrecpeq_f32(b);
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// This returns a differential, by which we will have to multiply inv to get a better
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// approximation of 1/b.
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restep = vrecpsq_f32(b, inv);
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inv = vmulq_f32(restep, inv);
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// Finally, multiply a by 1/b and get the wanted result of the division.
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div = vmulq_f32(a, inv);
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return div;
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#endif
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}
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template<> EIGEN_STRONG_INLINE Packet4c pdiv<Packet4c>(const Packet4c& /*a*/, const Packet4c& /*b*/)
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template<> EIGEN_STRONG_INLINE Packet4c pdiv<Packet4c>(const Packet4c& /*a*/, const Packet4c& /*b*/)
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{
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{
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eigen_assert(false && "packet integer division are not supported by NEON");
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eigen_assert(false && "packet integer division are not supported by NEON");
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@ -3362,26 +3311,115 @@ template<> EIGEN_STRONG_INLINE Packet4ui psqrt(const Packet4ui& a) {
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return res;
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return res;
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}
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}
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EIGEN_STRONG_INLINE Packet4f prsqrt_float_unsafe(const Packet4f& a) {
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// Compute approximate reciprocal sqrt.
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// Does not correctly handle +/- 0 or +inf
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float32x4_t result = vrsqrteq_f32(a);
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result = vmulq_f32(vrsqrtsq_f32(vmulq_f32(a, result), result), result);
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result = vmulq_f32(vrsqrtsq_f32(vmulq_f32(a, result), result), result);
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return result;
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}
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EIGEN_STRONG_INLINE Packet2f prsqrt_float_unsafe(const Packet2f& a) {
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// Compute approximate reciprocal sqrt.
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// Does not correctly handle +/- 0 or +inf
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float32x2_t result = vrsqrte_f32(a);
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result = vmul_f32(vrsqrts_f32(vmul_f32(a, result), result), result);
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result = vmul_f32(vrsqrts_f32(vmul_f32(a, result), result), result);
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return result;
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}
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template<typename Packet> Packet prsqrt_float_common(const Packet& a) {
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const Packet cst_zero = pzero(a);
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const Packet cst_inf = pset1<Packet>(NumTraits<float>::infinity());
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Packet return_zero = pcmp_eq(a, cst_inf);
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Packet return_inf = pcmp_eq(a, cst_zero);
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Packet result = prsqrt_float_unsafe(a);
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result = pselect(return_inf, por(cst_inf, a), result);
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result = pandnot(result, return_zero);
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return result;
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}
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template<> EIGEN_STRONG_INLINE Packet4f prsqrt(const Packet4f& a) {
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template<> EIGEN_STRONG_INLINE Packet4f prsqrt(const Packet4f& a) {
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// Do Newton iterations for 1/sqrt(x).
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return prsqrt_float_common(a);
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return generic_rsqrt_newton_step<Packet4f, /*Steps=*/2>::run(a, vrsqrteq_f32(a));
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}
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}
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template<> EIGEN_STRONG_INLINE Packet2f prsqrt(const Packet2f& a) {
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template<> EIGEN_STRONG_INLINE Packet2f prsqrt(const Packet2f& a) {
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// Compute approximate reciprocal sqrt.
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return prsqrt_float_common(a);
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return generic_rsqrt_newton_step<Packet2f, /*Steps=*/2>::run(a, vrsqrte_f32(a));
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}
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template<> EIGEN_STRONG_INLINE Packet4f preciprocal<Packet4f>(const Packet4f& a)
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{
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// Compute approximate reciprocal.
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float32x4_t result = vrecpeq_f32(a);
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result = vmulq_f32(vrecpsq_f32(a, result), result);
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result = vmulq_f32(vrecpsq_f32(a, result), result);
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return result;
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}
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template<> EIGEN_STRONG_INLINE Packet2f preciprocal<Packet2f>(const Packet2f& a)
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{
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// Compute approximate reciprocal.
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float32x2_t result = vrecpe_f32(a);
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result = vmul_f32(vrecps_f32(a, result), result);
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result = vmul_f32(vrecps_f32(a, result), result);
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return result;
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}
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}
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// Unfortunately vsqrt_f32 is only available for A64.
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// Unfortunately vsqrt_f32 is only available for A64.
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#if EIGEN_ARCH_ARM64
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#if EIGEN_ARCH_ARM64
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template<> EIGEN_STRONG_INLINE Packet4f psqrt(const Packet4f& _x){return vsqrtq_f32(_x);}
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template<> EIGEN_STRONG_INLINE Packet4f psqrt(const Packet4f& a) { return vsqrtq_f32(a); }
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template<> EIGEN_STRONG_INLINE Packet2f psqrt(const Packet2f& _x){return vsqrt_f32(_x); }
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template<> EIGEN_STRONG_INLINE Packet2f psqrt(const Packet2f& a) { return vsqrt_f32(a); }
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template<> EIGEN_STRONG_INLINE Packet4f pdiv(const Packet4f& a, const Packet4f& b) { return vdivq_f32(a, b); }
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template<> EIGEN_STRONG_INLINE Packet2f pdiv(const Packet2f& a, const Packet2f& b) { return vdiv_f32(a, b); }
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#else
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#else
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template<> EIGEN_STRONG_INLINE Packet4f psqrt(const Packet4f& a) {
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template<typename Packet>
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return generic_sqrt_newton_step<Packet4f>::run(a, prsqrt(a));
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EIGEN_STRONG_INLINE Packet psqrt_float_common(const Packet& a) {
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const Packet cst_zero = pzero(a);
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const Packet cst_inf = pset1<Packet>(NumTraits<float>::infinity());
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Packet result = pmul(a, prsqrt_float_unsafe(a));
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Packet a_is_zero = pcmp_eq(a, cst_zero);
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Packet a_is_inf = pcmp_eq(a, cst_inf);
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Packet return_a = por(a_is_zero, a_is_inf);
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result = pselect(return_a, a, result);
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return result;
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}
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}
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template<> EIGEN_STRONG_INLINE Packet4f psqrt(const Packet4f& a) {
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return psqrt_float_common(a);
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}
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template<> EIGEN_STRONG_INLINE Packet2f psqrt(const Packet2f& a) {
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template<> EIGEN_STRONG_INLINE Packet2f psqrt(const Packet2f& a) {
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return generic_sqrt_newton_step<Packet2f>::run(a, prsqrt(a));
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return psqrt_float_common(a);
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}
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template<typename Packet>
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EIGEN_STRONG_INLINE Packet pdiv_float_common(const Packet& a, const Packet& b) {
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// if b is large, NEON intrinsics will flush preciprocal(b) to zero
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// avoid underflow with the following manipulation:
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// a / b = f * (a * reciprocal(f * b))
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const Packet cst_one = pset1<Packet>(1.0f);
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const Packet cst_quarter = pset1<Packet>(0.25f);
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const Packet cst_thresh = pset1<Packet>(NumTraits<float>::highest() / 4.0f);
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Packet b_will_underflow = pcmp_le(cst_thresh, pabs(b));
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Packet f = pselect(b_will_underflow, cst_quarter, cst_one);
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Packet result = pmul(f, pmul(a, preciprocal(pmul(b, f))));
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return result;
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}
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template<> EIGEN_STRONG_INLINE Packet4f pdiv<Packet4f>(const Packet4f& a, const Packet4f& b) {
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return pdiv_float_common(a, b);
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}
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template<> EIGEN_STRONG_INLINE Packet2f pdiv<Packet2f>(const Packet2f& a, const Packet2f& b) {
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return pdiv_float_common(a, b);
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}
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}
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#endif
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#endif
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@ -47,7 +47,7 @@ std::vector<Scalar> special_values() {
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const Scalar sqrt2 = Scalar(std::sqrt(2));
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const Scalar sqrt2 = Scalar(std::sqrt(2));
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const Scalar inf = Eigen::NumTraits<Scalar>::infinity();
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const Scalar inf = Eigen::NumTraits<Scalar>::infinity();
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const Scalar nan = Eigen::NumTraits<Scalar>::quiet_NaN();
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const Scalar nan = Eigen::NumTraits<Scalar>::quiet_NaN();
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const Scalar denorm_min = std::numeric_limits<Scalar>::denorm_min();
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const Scalar denorm_min = EIGEN_ARCH_ARM ? zero : std::numeric_limits<Scalar>::denorm_min();
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const Scalar min = (std::numeric_limits<Scalar>::min)();
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const Scalar min = (std::numeric_limits<Scalar>::min)();
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const Scalar max = (std::numeric_limits<Scalar>::max)();
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const Scalar max = (std::numeric_limits<Scalar>::max)();
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const Scalar max_exp = (static_cast<Scalar>(int(Eigen::NumTraits<Scalar>::max_exponent())) * Scalar(EIGEN_LN2)) / eps;
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const Scalar max_exp = (static_cast<Scalar>(int(Eigen::NumTraits<Scalar>::max_exponent())) * Scalar(EIGEN_LN2)) / eps;
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@ -97,6 +97,12 @@ void binary_op_test(std::string name, Fn fun, RefFn ref) {
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for (Index j = 0; j < lhs.cols(); ++j) {
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for (Index j = 0; j < lhs.cols(); ++j) {
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Scalar e = static_cast<Scalar>(ref(lhs(i,j), rhs(i,j)));
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Scalar e = static_cast<Scalar>(ref(lhs(i,j), rhs(i,j)));
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Scalar a = actual(i, j);
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Scalar a = actual(i, j);
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#if EIGEN_ARCH_ARM
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// Work around NEON flush-to-zero mode
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// if ref returns denormalized value and Eigen returns 0, then skip the test
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int ref_fpclass = std::fpclassify(e);
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if (a == Scalar(0) && ref_fpclass == FP_SUBNORMAL) continue;
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#endif
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bool success = (a==e) || ((numext::isfinite)(e) && internal::isApprox(a, e, tol)) || ((numext::isnan)(a) && (numext::isnan)(e));
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bool success = (a==e) || ((numext::isfinite)(e) && internal::isApprox(a, e, tol)) || ((numext::isnan)(a) && (numext::isnan)(e));
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if ((a == a) && (e == e)) success &= (bool)numext::signbit(e) == (bool)numext::signbit(a);
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if ((a == a) && (e == e)) success &= (bool)numext::signbit(e) == (bool)numext::signbit(a);
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all_pass &= success;
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all_pass &= success;
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@ -767,7 +773,12 @@ template<typename ArrayType> void array_real(const ArrayType& m)
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m3(rows, cols),
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m3(rows, cols),
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m4 = m1;
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m4 = m1;
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m4 = (m4.abs()==Scalar(0)).select(Scalar(1),m4);
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// avoid denormalized values so verification doesn't fail on platforms that don't support them
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// denormalized behavior is tested elsewhere (unary_op_test, binary_ops_test)
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const Scalar min = (std::numeric_limits<Scalar>::min)();
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m1 = (m1.abs()<min).select(Scalar(0),m1);
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m2 = (m2.abs()<min).select(Scalar(0),m2);
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m4 = (m4.abs()<min).select(Scalar(1),m4);
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Scalar s1 = internal::random<Scalar>();
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Scalar s1 = internal::random<Scalar>();
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@ -808,6 +819,7 @@ template<typename ArrayType> void array_real(const ArrayType& m)
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// avoid inf and NaNs so verification doesn't fail
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// avoid inf and NaNs so verification doesn't fail
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m3 = m4.abs();
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m3 = m4.abs();
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VERIFY_IS_APPROX(m3.sqrt(), sqrt(abs(m3)));
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VERIFY_IS_APPROX(m3.sqrt(), sqrt(abs(m3)));
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VERIFY_IS_APPROX(m3.rsqrt(), Scalar(1)/sqrt(abs(m3)));
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VERIFY_IS_APPROX(m3.rsqrt(), Scalar(1)/sqrt(abs(m3)));
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VERIFY_IS_APPROX(rsqrt(m3), Scalar(1)/sqrt(abs(m3)));
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VERIFY_IS_APPROX(rsqrt(m3), Scalar(1)/sqrt(abs(m3)));
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@ -754,7 +754,7 @@ void packetmath_test_IEEE_corner_cases(const RefFunctorT& ref_fun,
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}
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}
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// Test for subnormals.
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// Test for subnormals.
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if (Cond && std::numeric_limits<Scalar>::has_denorm == std::denorm_present) {
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if (Cond && std::numeric_limits<Scalar>::has_denorm == std::denorm_present && !EIGEN_ARCH_ARM) {
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for (int scale = 1; scale < 5; ++scale) {
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for (int scale = 1; scale < 5; ++scale) {
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// When EIGEN_FAST_MATH is 1 we relax the conditions slightly, and allow the function
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// When EIGEN_FAST_MATH is 1 we relax the conditions slightly, and allow the function
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@ -912,12 +912,14 @@ void packetmath_real() {
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CHECK_CWISE1_BYREF1_IF(PacketTraits::HasExp, REF_FREXP, internal::pfrexp);
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CHECK_CWISE1_BYREF1_IF(PacketTraits::HasExp, REF_FREXP, internal::pfrexp);
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if (PacketTraits::HasExp) {
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if (PacketTraits::HasExp) {
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// Check denormals:
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// Check denormals:
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#if !EIGEN_ARCH_ARM
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for (int j=0; j<3; ++j) {
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for (int j=0; j<3; ++j) {
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data1[0] = Scalar(std::ldexp(1, NumTraits<Scalar>::min_exponent()-j));
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data1[0] = Scalar(std::ldexp(1, NumTraits<Scalar>::min_exponent()-j));
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CHECK_CWISE1_BYREF1_IF(PacketTraits::HasExp, REF_FREXP, internal::pfrexp);
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CHECK_CWISE1_BYREF1_IF(PacketTraits::HasExp, REF_FREXP, internal::pfrexp);
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data1[0] = -data1[0];
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data1[0] = -data1[0];
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CHECK_CWISE1_BYREF1_IF(PacketTraits::HasExp, REF_FREXP, internal::pfrexp);
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CHECK_CWISE1_BYREF1_IF(PacketTraits::HasExp, REF_FREXP, internal::pfrexp);
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}
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}
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#endif
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// zero
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// zero
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data1[0] = Scalar(0);
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data1[0] = Scalar(0);
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@ -113,25 +113,6 @@ template<int OtherStorage, typename SparseMatrixType> void sparse_permutations(c
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res_d = p.inverse()*mat_d;
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res_d = p.inverse()*mat_d;
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VERIFY(res.isApprox(res_d) && "inv(p)*mat");
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VERIFY(res.isApprox(res_d) && "inv(p)*mat");
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// test non-plaintype expressions that require additional temporary
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const Scalar alpha(2.34);
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res_d = p * (alpha * mat_d);
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VERIFY_TEMPORARY_COUNT( res = p * (alpha * mat), 2);
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VERIFY( res.isApprox(res_d) && "p*(alpha*mat)" );
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res_d = (alpha * mat_d) * p;
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VERIFY_TEMPORARY_COUNT( res = (alpha * mat) * p, 2);
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VERIFY( res.isApprox(res_d) && "(alpha*mat)*p" );
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res_d = p.inverse() * (alpha * mat_d);
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VERIFY_TEMPORARY_COUNT( res = p.inverse() * (alpha * mat), 2);
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VERIFY( res.isApprox(res_d) && "inv(p)*(alpha*mat)" );
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res_d = (alpha * mat_d) * p.inverse();
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VERIFY_TEMPORARY_COUNT( res = (alpha * mat) * p.inverse(), 2);
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VERIFY( res.isApprox(res_d) && "(alpha*mat)*inv(p)" );
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//
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//
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VERIFY( is_sorted( (p * mat * p.inverse()).eval() ));
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VERIFY( is_sorted( (p * mat * p.inverse()).eval() ));
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