xref: /aosp_15_r20/external/eigen/unsupported/test/special_packetmath.cpp (revision bf2c37156dfe67e5dfebd6d394bad8b2ab5804d4)
1*bf2c3715SXin Li // This file is part of Eigen, a lightweight C++ template library
2*bf2c3715SXin Li // for linear algebra.
3*bf2c3715SXin Li //
4*bf2c3715SXin Li // Copyright (C) 2008-2009 Gael Guennebaud <[email protected]>
5*bf2c3715SXin Li // Copyright (C) 2006-2008 Benoit Jacob <[email protected]>
6*bf2c3715SXin Li //
7*bf2c3715SXin Li // This Source Code Form is subject to the terms of the Mozilla
8*bf2c3715SXin Li // Public License v. 2.0. If a copy of the MPL was not distributed
9*bf2c3715SXin Li // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
10*bf2c3715SXin Li 
11*bf2c3715SXin Li #include <limits>
12*bf2c3715SXin Li #include "packetmath_test_shared.h"
13*bf2c3715SXin Li #include "../Eigen/SpecialFunctions"
14*bf2c3715SXin Li 
packetmath_real()15*bf2c3715SXin Li template<typename Scalar,typename Packet> void packetmath_real()
16*bf2c3715SXin Li {
17*bf2c3715SXin Li   using std::abs;
18*bf2c3715SXin Li   typedef internal::packet_traits<Scalar> PacketTraits;
19*bf2c3715SXin Li   const int PacketSize = internal::unpacket_traits<Packet>::size;
20*bf2c3715SXin Li 
21*bf2c3715SXin Li   const int size = PacketSize*4;
22*bf2c3715SXin Li   EIGEN_ALIGN_MAX Scalar data1[PacketSize*4];
23*bf2c3715SXin Li   EIGEN_ALIGN_MAX Scalar data2[PacketSize*4];
24*bf2c3715SXin Li   EIGEN_ALIGN_MAX Scalar ref[PacketSize*4];
25*bf2c3715SXin Li 
26*bf2c3715SXin Li #if EIGEN_HAS_C99_MATH
27*bf2c3715SXin Li   {
28*bf2c3715SXin Li     data1[0] = std::numeric_limits<Scalar>::quiet_NaN();
29*bf2c3715SXin Li     test::packet_helper<internal::packet_traits<Scalar>::HasLGamma,Packet> h;
30*bf2c3715SXin Li     h.store(data2, internal::plgamma(h.load(data1)));
31*bf2c3715SXin Li     VERIFY((numext::isnan)(data2[0]));
32*bf2c3715SXin Li   }
33*bf2c3715SXin Li   if (internal::packet_traits<Scalar>::HasErf) {
34*bf2c3715SXin Li     data1[0] = std::numeric_limits<Scalar>::quiet_NaN();
35*bf2c3715SXin Li     test::packet_helper<internal::packet_traits<Scalar>::HasErf,Packet> h;
36*bf2c3715SXin Li     h.store(data2, internal::perf(h.load(data1)));
37*bf2c3715SXin Li     VERIFY((numext::isnan)(data2[0]));
38*bf2c3715SXin Li   }
39*bf2c3715SXin Li   {
40*bf2c3715SXin Li     data1[0] = std::numeric_limits<Scalar>::quiet_NaN();
41*bf2c3715SXin Li     test::packet_helper<internal::packet_traits<Scalar>::HasErfc,Packet> h;
42*bf2c3715SXin Li     h.store(data2, internal::perfc(h.load(data1)));
43*bf2c3715SXin Li     VERIFY((numext::isnan)(data2[0]));
44*bf2c3715SXin Li   }
45*bf2c3715SXin Li   {
46*bf2c3715SXin Li     for (int i=0; i<size; ++i) {
47*bf2c3715SXin Li       data1[i] = internal::random<Scalar>(Scalar(0),Scalar(1));
48*bf2c3715SXin Li     }
49*bf2c3715SXin Li     CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasNdtri, numext::ndtri, internal::pndtri);
50*bf2c3715SXin Li   }
51*bf2c3715SXin Li #endif  // EIGEN_HAS_C99_MATH
52*bf2c3715SXin Li 
53*bf2c3715SXin Li   // For bessel_i*e and bessel_j*, the valid range is negative reals.
54*bf2c3715SXin Li   {
55*bf2c3715SXin Li     const int max_exponent = numext::mini(std::numeric_limits<Scalar>::max_exponent10-1, 6);
56*bf2c3715SXin Li     for (int i=0; i<size; ++i)
57*bf2c3715SXin Li     {
58*bf2c3715SXin Li       data1[i] = internal::random<Scalar>(Scalar(-1),Scalar(1)) * Scalar(std::pow(Scalar(10), internal::random<Scalar>(Scalar(-max_exponent),Scalar(max_exponent))));
59*bf2c3715SXin Li       data2[i] = internal::random<Scalar>(Scalar(-1),Scalar(1)) * Scalar(std::pow(Scalar(10), internal::random<Scalar>(Scalar(-max_exponent),Scalar(max_exponent))));
60*bf2c3715SXin Li     }
61*bf2c3715SXin Li 
62*bf2c3715SXin Li     CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_i0e, internal::pbessel_i0e);
63*bf2c3715SXin Li     CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_i1e, internal::pbessel_i1e);
64*bf2c3715SXin Li     CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_j0, internal::pbessel_j0);
65*bf2c3715SXin Li     CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_j1, internal::pbessel_j1);
66*bf2c3715SXin Li   }
67*bf2c3715SXin Li 
68*bf2c3715SXin Li   // Use a smaller data range for the bessel_i* as these can become very large.
69*bf2c3715SXin Li   // Following #1693, we also restrict this range further to avoid inf's due to
70*bf2c3715SXin Li   // differences in pexp and exp.
71*bf2c3715SXin Li   for (int i=0; i<size; ++i) {
72*bf2c3715SXin Li       data1[i] = internal::random<Scalar>(Scalar(0.01),Scalar(1)) *
73*bf2c3715SXin Li                   Scalar(std::pow(Scalar(9), internal::random<Scalar>(Scalar(-1),Scalar(2))));
74*bf2c3715SXin Li       data2[i] = internal::random<Scalar>(Scalar(0.01),Scalar(1)) *
75*bf2c3715SXin Li                   Scalar(std::pow(Scalar(9), internal::random<Scalar>(Scalar(-1),Scalar(2))));
76*bf2c3715SXin Li   }
77*bf2c3715SXin Li   CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_i0, internal::pbessel_i0);
78*bf2c3715SXin Li   CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_i1, internal::pbessel_i1);
79*bf2c3715SXin Li 
80*bf2c3715SXin Li 
81*bf2c3715SXin Li   // y_i, and k_i are valid for x > 0.
82*bf2c3715SXin Li   {
83*bf2c3715SXin Li     const int max_exponent = numext::mini(std::numeric_limits<Scalar>::max_exponent10-1, 5);
84*bf2c3715SXin Li     for (int i=0; i<size; ++i)
85*bf2c3715SXin Li     {
86*bf2c3715SXin Li       data1[i] = internal::random<Scalar>(Scalar(0.01),Scalar(1)) * Scalar(std::pow(Scalar(10), internal::random<Scalar>(Scalar(-2),Scalar(max_exponent))));
87*bf2c3715SXin Li       data2[i] = internal::random<Scalar>(Scalar(0.01),Scalar(1)) * Scalar(std::pow(Scalar(10), internal::random<Scalar>(Scalar(-2),Scalar(max_exponent))));
88*bf2c3715SXin Li     }
89*bf2c3715SXin Li   }
90*bf2c3715SXin Li 
91*bf2c3715SXin Li   // TODO(srvasude): Re-enable this test once properly investigated why the
92*bf2c3715SXin Li   // scalar and vector paths differ.
93*bf2c3715SXin Li   // CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_y0, internal::pbessel_y0);
94*bf2c3715SXin Li   CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_y1, internal::pbessel_y1);
95*bf2c3715SXin Li   CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_k0e, internal::pbessel_k0e);
96*bf2c3715SXin Li   CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_k1e, internal::pbessel_k1e);
97*bf2c3715SXin Li 
98*bf2c3715SXin Li   // Following #1693, we restrict the range for exp to avoid zeroing out too
99*bf2c3715SXin Li   // fast.
100*bf2c3715SXin Li   for (int i=0; i<size; ++i) {
101*bf2c3715SXin Li       data1[i] = internal::random<Scalar>(Scalar(0.01),Scalar(1)) *
102*bf2c3715SXin Li                   Scalar(std::pow(Scalar(9), internal::random<Scalar>(Scalar(-1),Scalar(2))));
103*bf2c3715SXin Li       data2[i] = internal::random<Scalar>(Scalar(0.01),Scalar(1)) *
104*bf2c3715SXin Li                   Scalar(std::pow(Scalar(9), internal::random<Scalar>(Scalar(-1),Scalar(2))));
105*bf2c3715SXin Li   }
106*bf2c3715SXin Li   CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_k0, internal::pbessel_k0);
107*bf2c3715SXin Li   CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_k1, internal::pbessel_k1);
108*bf2c3715SXin Li 
109*bf2c3715SXin Li 
110*bf2c3715SXin Li   for (int i=0; i<size; ++i) {
111*bf2c3715SXin Li       data1[i] = internal::random<Scalar>(Scalar(0.01),Scalar(1)) *
112*bf2c3715SXin Li                   Scalar(std::pow(Scalar(10), internal::random<Scalar>(Scalar(-1),Scalar(2))));
113*bf2c3715SXin Li       data2[i] = internal::random<Scalar>(Scalar(0.01),Scalar(1)) *
114*bf2c3715SXin Li                   Scalar(std::pow(Scalar(10), internal::random<Scalar>(Scalar(-1),Scalar(2))));
115*bf2c3715SXin Li   }
116*bf2c3715SXin Li 
117*bf2c3715SXin Li #if EIGEN_HAS_C99_MATH && (EIGEN_COMP_CXXVER >= 11)
118*bf2c3715SXin Li   CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasLGamma, std::lgamma, internal::plgamma);
119*bf2c3715SXin Li   CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasErf, std::erf, internal::perf);
120*bf2c3715SXin Li   CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasErfc, std::erfc, internal::perfc);
121*bf2c3715SXin Li #endif
122*bf2c3715SXin Li 
123*bf2c3715SXin Li }
124*bf2c3715SXin Li 
125*bf2c3715SXin Li namespace Eigen {
126*bf2c3715SXin Li namespace test {
127*bf2c3715SXin Li 
128*bf2c3715SXin Li template<typename Scalar,typename PacketType, bool IsComplex, bool IsInteger>
129*bf2c3715SXin Li struct runall {
runEigen::test::runall130*bf2c3715SXin Li   static void run() {
131*bf2c3715SXin Li     packetmath_real<Scalar,PacketType>();
132*bf2c3715SXin Li   }
133*bf2c3715SXin Li };
134*bf2c3715SXin Li 
135*bf2c3715SXin Li }
136*bf2c3715SXin Li }
137*bf2c3715SXin Li 
EIGEN_DECLARE_TEST(special_packetmath)138*bf2c3715SXin Li EIGEN_DECLARE_TEST(special_packetmath)
139*bf2c3715SXin Li {
140*bf2c3715SXin Li   g_first_pass = true;
141*bf2c3715SXin Li   for(int i = 0; i < g_repeat; i++) {
142*bf2c3715SXin Li 
143*bf2c3715SXin Li     CALL_SUBTEST_1( test::runner<float>::run() );
144*bf2c3715SXin Li     CALL_SUBTEST_2( test::runner<double>::run() );
145*bf2c3715SXin Li     CALL_SUBTEST_3( test::runner<Eigen::half>::run() );
146*bf2c3715SXin Li     CALL_SUBTEST_4( test::runner<Eigen::bfloat16>::run() );
147*bf2c3715SXin Li     g_first_pass = false;
148*bf2c3715SXin Li   }
149*bf2c3715SXin Li }
150