// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2006-2010 Benoit Jacob // // This Source Code Form is subject to the terms of the Mozilla // Public License v. 2.0. If a copy of the MPL was not distributed // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. #ifndef EIGEN_MATHFUNCTIONS_H #define EIGEN_MATHFUNCTIONS_H // source: http://www.geom.uiuc.edu/~huberty/math5337/groupe/digits.html // TODO this should better be moved to NumTraits #define EIGEN_PI \ 3.141592653589793238462643383279502884197169399375105820974944592307816406L namespace Eigen { // On WINCE, std::abs is defined for int only, so let's defined our own // overloads: // This issue has been confirmed with MSVC 2008 only, but the issue might exist // for more recent versions too. #if EIGEN_OS_WINCE && EIGEN_COMP_MSVC && EIGEN_COMP_MSVC <= 1500 long abs(long x) { return (labs(x)); } double abs(double x) { return (fabs(x)); } float abs(float x) { return (fabsf(x)); } long double abs(long double x) { return (fabsl(x)); } #endif namespace internal { /** \internal \class global_math_functions_filtering_base * * What it does: * Defines a typedef 'type' as follows: * - if type T has a member typedef * Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl, then * global_math_functions_filtering_base::type is a typedef for it. * - otherwise, global_math_functions_filtering_base::type is a typedef for * T. * * How it's used: * To allow to defined the global math functions (like sin...) in certain * cases, like the Array expressions. * When you do sin(array1+array2), the object array1+array2 has a complicated * expression type, all what you want to know * is that it inherits ArrayBase. So we implement a partial specialization of * sin_impl for ArrayBase. * So we must make sure to use sin_impl > and not * sin_impl, otherwise our partial specialization * won't be used. How does sin know that? That's exactly what * global_math_functions_filtering_base tells it. * * How it's implemented: * SFINAE in the style of enable_if. Highly susceptible of breaking compilers. * With GCC, it sure does work, but if you replace * the typename dummy by an integer template parameter, it doesn't work * anymore! */ template struct global_math_functions_filtering_base { typedef T type; }; template struct always_void { typedef void type; }; template struct global_math_functions_filtering_base< T, typename always_void< typename T::Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl>:: type> { typedef typename T::Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl type; }; #define EIGEN_MATHFUNC_IMPL(func, scalar) \ Eigen::internal::func##_impl< \ typename Eigen::internal::global_math_functions_filtering_base< \ scalar>::type> #define EIGEN_MATHFUNC_RETVAL(func, scalar) \ typename Eigen::internal::func##_retval< \ typename Eigen::internal::global_math_functions_filtering_base< \ scalar>::type>::type /**************************************************************************** * Implementation of real * ****************************************************************************/ template ::IsComplex> struct real_default_impl { typedef typename NumTraits::Real RealScalar; EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { return x; } }; template struct real_default_impl { typedef typename NumTraits::Real RealScalar; EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { using std::real; return real(x); } }; template struct real_impl : real_default_impl {}; #if defined(EIGEN_GPU_COMPILE_PHASE) template struct real_impl> { typedef T RealScalar; EIGEN_DEVICE_FUNC static inline T run(const std::complex& x) { return x.real(); } }; #endif template struct real_retval { typedef typename NumTraits::Real type; }; /**************************************************************************** * Implementation of imag * ****************************************************************************/ template ::IsComplex> struct imag_default_impl { typedef typename NumTraits::Real RealScalar; EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar&) { return RealScalar(0); } }; template struct imag_default_impl { typedef typename NumTraits::Real RealScalar; EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { using std::imag; return imag(x); } }; template struct imag_impl : imag_default_impl {}; #if defined(EIGEN_GPU_COMPILE_PHASE) template struct imag_impl> { typedef T RealScalar; EIGEN_DEVICE_FUNC static inline T run(const std::complex& x) { return x.imag(); } }; #endif template struct imag_retval { typedef typename NumTraits::Real type; }; /**************************************************************************** * Implementation of real_ref * ****************************************************************************/ template struct real_ref_impl { typedef typename NumTraits::Real RealScalar; EIGEN_DEVICE_FUNC static inline RealScalar& run(Scalar& x) { return reinterpret_cast(&x)[0]; } EIGEN_DEVICE_FUNC static inline const RealScalar& run(const Scalar& x) { return reinterpret_cast(&x)[0]; } }; template struct real_ref_retval { typedef typename NumTraits::Real& type; }; /**************************************************************************** * Implementation of imag_ref * ****************************************************************************/ template struct imag_ref_default_impl { typedef typename NumTraits::Real RealScalar; EIGEN_DEVICE_FUNC static inline RealScalar& run(Scalar& x) { return reinterpret_cast(&x)[1]; } EIGEN_DEVICE_FUNC static inline const RealScalar& run(const Scalar& x) { return reinterpret_cast(&x)[1]; } }; template struct imag_ref_default_impl { EIGEN_DEVICE_FUNC static inline Scalar run(Scalar&) { return Scalar(0); } EIGEN_DEVICE_FUNC static inline const Scalar run(const Scalar&) { return Scalar(0); } }; template struct imag_ref_impl : imag_ref_default_impl::IsComplex> {}; template struct imag_ref_retval { typedef typename NumTraits::Real& type; }; /**************************************************************************** * Implementation of conj * ****************************************************************************/ template ::IsComplex> struct conj_default_impl { EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { return x; } }; template struct conj_default_impl { EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { using std::conj; return conj(x); } }; template struct conj_impl : conj_default_impl {}; #if defined(EIGEN_GPU_COMPILE_PHASE) template struct conj_impl> { EIGEN_DEVICE_FUNC static inline std::complex run(const std::complex& x) { return std::complex(x.real(), -x.imag()); } }; #endif template struct conj_retval { typedef Scalar type; }; /**************************************************************************** * Implementation of abs2 * ****************************************************************************/ template struct abs2_impl_default { typedef typename NumTraits::Real RealScalar; EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { return x * x; } }; template struct abs2_impl_default // IsComplex { typedef typename NumTraits::Real RealScalar; EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { return x.real() * x.real() + x.imag() * x.imag(); } }; template struct abs2_impl { typedef typename NumTraits::Real RealScalar; EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { return abs2_impl_default::IsComplex>::run(x); } }; template struct abs2_retval { typedef typename NumTraits::Real type; }; /**************************************************************************** * Implementation of norm1 * ****************************************************************************/ template struct norm1_default_impl; template struct norm1_default_impl { typedef typename NumTraits::Real RealScalar; EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { EIGEN_USING_STD_MATH(abs); return abs(x.real()) + abs(x.imag()); } }; template struct norm1_default_impl { EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { EIGEN_USING_STD_MATH(abs); return abs(x); } }; template struct norm1_impl : norm1_default_impl::IsComplex> {}; template struct norm1_retval { typedef typename NumTraits::Real type; }; /**************************************************************************** * Implementation of hypot * ****************************************************************************/ template struct hypot_impl; template struct hypot_retval { typedef typename NumTraits::Real type; }; /**************************************************************************** * Implementation of cast * ****************************************************************************/ template struct cast_impl { EIGEN_DEVICE_FUNC static inline NewType run(const OldType& x) { return static_cast(x); } }; // here, for once, we're plainly returning NewType: we don't want cast to do // weird things. template EIGEN_DEVICE_FUNC inline NewType cast(const OldType& x) { return cast_impl::run(x); } /**************************************************************************** * Implementation of round * ****************************************************************************/ #if EIGEN_HAS_CXX11_MATH template struct round_impl { EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { EIGEN_STATIC_ASSERT((!NumTraits::IsComplex), NUMERIC_TYPE_MUST_BE_REAL) EIGEN_USING_STD_MATH(round); return round(x); } }; #else template struct round_impl { EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { EIGEN_STATIC_ASSERT((!NumTraits::IsComplex), NUMERIC_TYPE_MUST_BE_REAL) EIGEN_USING_STD_MATH(floor); EIGEN_USING_STD_MATH(ceil); return (x > Scalar(0)) ? floor(x + Scalar(0.5)) : ceil(x - Scalar(0.5)); } }; #endif template struct round_retval { typedef Scalar type; }; /**************************************************************************** * Implementation of rint * ****************************************************************************/ template struct rint_impl { EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { EIGEN_STATIC_ASSERT((!NumTraits::IsComplex), NUMERIC_TYPE_MUST_BE_REAL) #if EIGEN_HAS_CXX11_MATH EIGEN_USING_STD_MATH(rint); #endif return rint(x); } }; #if !EIGEN_HAS_CXX11_MATH template <> struct rint_impl { EIGEN_DEVICE_FUNC static inline double run(const double& x) { return ::rint(x); } }; template <> struct rint_impl { EIGEN_DEVICE_FUNC static inline float run(const float& x) { return ::rintf(x); } }; #endif template struct rint_retval { typedef Scalar type; }; /**************************************************************************** * Implementation of arg * ****************************************************************************/ #if EIGEN_HAS_CXX11_MATH template struct arg_impl { EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { #if defined(EIGEN_HIP_DEVICE_COMPILE) // HIP does not seem to have a native device side implementation for the // math routine "arg" using std::arg; #else EIGEN_USING_STD_MATH(arg); #endif return arg(x); } }; #else template ::IsComplex> struct arg_default_impl { typedef typename NumTraits::Real RealScalar; EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { return (x < Scalar(0)) ? Scalar(EIGEN_PI) : Scalar(0); } }; template struct arg_default_impl { typedef typename NumTraits::Real RealScalar; EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { EIGEN_USING_STD_MATH(arg); return arg(x); } }; template struct arg_impl : arg_default_impl {}; #endif template struct arg_retval { typedef typename NumTraits::Real type; }; /**************************************************************************** * Implementation of expm1 * ****************************************************************************/ // This implementation is based on GSL Math's expm1. namespace std_fallback { // fallback expm1 implementation in case there is no expm1(Scalar) function in // namespace of Scalar, // or that there is no suitable std::expm1 function available. Implementation // attributed to Kahan. See: http://www.plunk.org/~hatch/rightway.php. template EIGEN_DEVICE_FUNC inline Scalar expm1(const Scalar& x) { EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar) typedef typename NumTraits::Real RealScalar; EIGEN_USING_STD_MATH(exp); Scalar u = exp(x); if (numext::equal_strict(u, Scalar(1))) { return x; } Scalar um1 = u - RealScalar(1); if (numext::equal_strict(um1, Scalar(-1))) { return RealScalar(-1); } EIGEN_USING_STD_MATH(log); Scalar logu = log(u); return numext::equal_strict(u, logu) ? u : (u - RealScalar(1)) * x / logu; } } template struct expm1_impl { EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar) #if EIGEN_HAS_CXX11_MATH using std::expm1; #else using std_fallback::expm1; #endif return expm1(x); } }; // Specialization for complex types that are not supported by std::expm1. template struct expm1_impl> { EIGEN_DEVICE_FUNC static inline std::complex run( const std::complex& x) { EIGEN_STATIC_ASSERT_NON_INTEGER(RealScalar) RealScalar xr = x.real(); RealScalar xi = x.imag(); // expm1(z) = exp(z) - 1 // = exp(x + i * y) - 1 // = exp(x) * (cos(y) + i * sin(y)) - 1 // = exp(x) * cos(y) - 1 + i * exp(x) * sin(y) // Imag(expm1(z)) = exp(x) * sin(y) // Real(expm1(z)) = exp(x) * cos(y) - 1 // = exp(x) * cos(y) - 1. // = expm1(x) + exp(x) * (cos(y) - 1) // = expm1(x) + exp(x) * (2 * sin(y / 2) ** 2) // TODO better use numext::expm1 and numext::sin (but that would require // forward declarations or moving this specialization down). RealScalar erm1 = expm1_impl::run(xr); RealScalar er = erm1 + RealScalar(1.); EIGEN_USING_STD_MATH(sin); RealScalar sin2 = sin(xi / RealScalar(2.)); sin2 = sin2 * sin2; RealScalar s = sin(xi); RealScalar real_part = erm1 - RealScalar(2.) * er * sin2; return std::complex(real_part, er * s); } }; template struct expm1_retval { typedef Scalar type; }; /**************************************************************************** * Implementation of log1p * ****************************************************************************/ namespace std_fallback { // fallback log1p implementation in case there is no log1p(Scalar) function in // namespace of Scalar, // or that there is no suitable std::log1p function available template EIGEN_DEVICE_FUNC inline Scalar log1p(const Scalar& x) { EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar) typedef typename NumTraits::Real RealScalar; EIGEN_USING_STD_MATH(log); Scalar x1p = RealScalar(1) + x; Scalar log_1p = log(x1p); const bool is_small = numext::equal_strict(x1p, Scalar(1)); const bool is_inf = numext::equal_strict(x1p, log_1p); return (is_small || is_inf) ? x : x * (log_1p / (x1p - RealScalar(1))); } } template struct log1p_impl { EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar) #if EIGEN_HAS_CXX11_MATH using std::log1p; #else using std_fallback::log1p; #endif return log1p(x); } }; // Specialization for complex types that are not supported by std::log1p. template struct log1p_impl> { EIGEN_DEVICE_FUNC static inline std::complex run( const std::complex& x) { EIGEN_STATIC_ASSERT_NON_INTEGER(RealScalar) return std_fallback::log1p(x); } }; template struct log1p_retval { typedef Scalar type; }; /**************************************************************************** * Implementation of pow * ****************************************************************************/ template ::IsInteger&& NumTraits::IsInteger> struct pow_impl { // typedef Scalar retval; typedef typename ScalarBinaryOpTraits< ScalarX, ScalarY, internal::scalar_pow_op>::ReturnType result_type; static EIGEN_DEVICE_FUNC inline result_type run(const ScalarX& x, const ScalarY& y) { EIGEN_USING_STD_MATH(pow); return pow(x, y); } }; template struct pow_impl { typedef ScalarX result_type; static EIGEN_DEVICE_FUNC inline ScalarX run(ScalarX x, ScalarY y) { ScalarX res(1); eigen_assert(!NumTraits::IsSigned || y >= 0); if (y & 1) res *= x; y >>= 1; while (y) { x *= x; if (y & 1) res *= x; y >>= 1; } return res; } }; /**************************************************************************** * Implementation of random * ****************************************************************************/ template struct random_default_impl {}; template struct random_impl : random_default_impl::IsComplex, NumTraits::IsInteger> {}; template struct random_retval { typedef Scalar type; }; template inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random(const Scalar& x, const Scalar& y); template inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random(); template struct random_default_impl { static inline Scalar run(const Scalar& x, const Scalar& y) { return x + (y - x) * Scalar(std::rand()) / Scalar(RAND_MAX); } static inline Scalar run() { return run(Scalar(NumTraits::IsSigned ? -1 : 0), Scalar(1)); } }; enum { meta_floor_log2_terminate, meta_floor_log2_move_up, meta_floor_log2_move_down, meta_floor_log2_bogus }; template struct meta_floor_log2_selector { enum { middle = (lower + upper) / 2, value = (upper <= lower + 1) ? int(meta_floor_log2_terminate) : (n < (1 << middle)) ? int(meta_floor_log2_move_down) : (n == 0) ? int(meta_floor_log2_bogus) : int(meta_floor_log2_move_up) }; }; template ::value> struct meta_floor_log2 {}; template struct meta_floor_log2 { enum { value = meta_floor_log2< n, lower, meta_floor_log2_selector::middle>::value }; }; template struct meta_floor_log2 { enum { value = meta_floor_log2::middle, upper>::value }; }; template struct meta_floor_log2 { enum { value = (n >= ((unsigned int)(1) << (lower + 1))) ? lower + 1 : lower }; }; template struct meta_floor_log2 { // no value, error at compile time }; template struct random_default_impl { static inline Scalar run(const Scalar& x, const Scalar& y) { if (y <= x) return x; // ScalarU is the unsigned counterpart of Scalar, possibly Scalar itself. typedef typename make_unsigned::type ScalarU; // ScalarX is the widest of ScalarU and unsigned int. // We'll deal only with ScalarX and unsigned int below thus avoiding signed // types and arithmetic and signed overflows (which are undefined behavior). typedef typename conditional<(ScalarU(-1) > unsigned(-1)), ScalarU, unsigned>::type ScalarX; // The following difference doesn't overflow, provided our integer types are // two's // complement and have the same number of padding bits in signed and // unsigned variants. // This is the case in most modern implementations of C++. ScalarX range = ScalarX(y) - ScalarX(x); ScalarX offset = 0; ScalarX divisor = 1; ScalarX multiplier = 1; const unsigned rand_max = RAND_MAX; if (range <= rand_max) divisor = (rand_max + 1) / (range + 1); else multiplier = 1 + range / (rand_max + 1); // Rejection sampling. do { offset = (unsigned(std::rand()) * multiplier) / divisor; } while (offset > range); return Scalar(ScalarX(x) + offset); } static inline Scalar run() { #ifdef EIGEN_MAKING_DOCS return run(Scalar(NumTraits::IsSigned ? -10 : 0), Scalar(10)); #else enum { rand_bits = meta_floor_log2<(unsigned int)(RAND_MAX) + 1>::value, scalar_bits = sizeof(Scalar) * CHAR_BIT, shift = EIGEN_PLAIN_ENUM_MAX(0, int(rand_bits) - int(scalar_bits)), offset = NumTraits::IsSigned ? (1 << (EIGEN_PLAIN_ENUM_MIN(rand_bits, scalar_bits) - 1)) : 0}; return Scalar((std::rand() >> shift) - offset); #endif } }; template struct random_default_impl { static inline Scalar run(const Scalar& x, const Scalar& y) { return Scalar(random(x.real(), y.real()), random(x.imag(), y.imag())); } static inline Scalar run() { typedef typename NumTraits::Real RealScalar; return Scalar(random(), random()); } }; template inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random(const Scalar& x, const Scalar& y) { return EIGEN_MATHFUNC_IMPL(random, Scalar)::run(x, y); } template inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random() { return EIGEN_MATHFUNC_IMPL(random, Scalar)::run(); } // Implementation of is* functions // std::is* do not work with fast-math and gcc, std::is* are available on MSVC // 2013 and newer, as well as in clang. #if (EIGEN_HAS_CXX11_MATH && \ !(EIGEN_COMP_GNUC_STRICT && __FINITE_MATH_ONLY__)) || \ (EIGEN_COMP_MSVC >= 1800) || (EIGEN_COMP_CLANG) #define EIGEN_USE_STD_FPCLASSIFY 1 #else #define EIGEN_USE_STD_FPCLASSIFY 0 #endif template EIGEN_DEVICE_FUNC typename internal::enable_if::value, bool>::type isnan_impl(const T&) { return false; } template EIGEN_DEVICE_FUNC typename internal::enable_if::value, bool>::type isinf_impl(const T&) { return false; } template EIGEN_DEVICE_FUNC typename internal::enable_if::value, bool>::type isfinite_impl(const T&) { return true; } template EIGEN_DEVICE_FUNC typename internal::enable_if<(!internal::is_integral::value) && (!NumTraits::IsComplex), bool>::type isfinite_impl(const T& x) { #if defined(EIGEN_GPU_COMPILE_PHASE) return (::isfinite)(x); #elif EIGEN_USE_STD_FPCLASSIFY using std::isfinite; return isfinite EIGEN_NOT_A_MACRO(x); #else return x <= NumTraits::highest() && x >= NumTraits::lowest(); #endif } template EIGEN_DEVICE_FUNC typename internal::enable_if<(!internal::is_integral::value) && (!NumTraits::IsComplex), bool>::type isinf_impl(const T& x) { #if defined(EIGEN_GPU_COMPILE_PHASE) return (::isinf)(x); #elif EIGEN_USE_STD_FPCLASSIFY using std::isinf; return isinf EIGEN_NOT_A_MACRO(x); #else return x > NumTraits::highest() || x < NumTraits::lowest(); #endif } template EIGEN_DEVICE_FUNC typename internal::enable_if<(!internal::is_integral::value) && (!NumTraits::IsComplex), bool>::type isnan_impl(const T& x) { #if defined(EIGEN_GPU_COMPILE_PHASE) return (::isnan)(x); #elif EIGEN_USE_STD_FPCLASSIFY using std::isnan; return isnan EIGEN_NOT_A_MACRO(x); #else return x != x; #endif } #if (!EIGEN_USE_STD_FPCLASSIFY) #if EIGEN_COMP_MSVC template EIGEN_DEVICE_FUNC bool isinf_msvc_helper(T x) { return _fpclass(x) == _FPCLASS_NINF || _fpclass(x) == _FPCLASS_PINF; } // MSVC defines a _isnan builtin function, but for double only EIGEN_DEVICE_FUNC inline bool isnan_impl(const long double& x) { return _isnan(x) != 0; } EIGEN_DEVICE_FUNC inline bool isnan_impl(const double& x) { return _isnan(x) != 0; } EIGEN_DEVICE_FUNC inline bool isnan_impl(const float& x) { return _isnan(x) != 0; } EIGEN_DEVICE_FUNC inline bool isinf_impl(const long double& x) { return isinf_msvc_helper(x); } EIGEN_DEVICE_FUNC inline bool isinf_impl(const double& x) { return isinf_msvc_helper(x); } EIGEN_DEVICE_FUNC inline bool isinf_impl(const float& x) { return isinf_msvc_helper(x); } #elif (defined __FINITE_MATH_ONLY__ && __FINITE_MATH_ONLY__ && EIGEN_COMP_GNUC) #if EIGEN_GNUC_AT_LEAST(5, 0) #define EIGEN_TMP_NOOPT_ATTRIB \ EIGEN_DEVICE_FUNC inline __attribute__((optimize("no-finite-math-only"))) #else // NOTE the inline qualifier and noinline attribute are both needed: the former // is to avoid linking issue (duplicate symbol), // while the second prevent too aggressive optimizations in fast-math mode: #define EIGEN_TMP_NOOPT_ATTRIB \ EIGEN_DEVICE_FUNC inline \ __attribute__((noinline, optimize("no-finite-math-only"))) #endif template <> EIGEN_TMP_NOOPT_ATTRIB bool isnan_impl(const long double& x) { return __builtin_isnan(x); } template <> EIGEN_TMP_NOOPT_ATTRIB bool isnan_impl(const double& x) { return __builtin_isnan(x); } template <> EIGEN_TMP_NOOPT_ATTRIB bool isnan_impl(const float& x) { return __builtin_isnan(x); } template <> EIGEN_TMP_NOOPT_ATTRIB bool isinf_impl(const double& x) { return __builtin_isinf(x); } template <> EIGEN_TMP_NOOPT_ATTRIB bool isinf_impl(const float& x) { return __builtin_isinf(x); } template <> EIGEN_TMP_NOOPT_ATTRIB bool isinf_impl(const long double& x) { return __builtin_isinf(x); } #undef EIGEN_TMP_NOOPT_ATTRIB #endif #endif // The following overload are defined at the end of this file template EIGEN_DEVICE_FUNC bool isfinite_impl(const std::complex& x); template EIGEN_DEVICE_FUNC bool isnan_impl(const std::complex& x); template EIGEN_DEVICE_FUNC bool isinf_impl(const std::complex& x); template T generic_fast_tanh_float(const T& a_x); } // end namespace internal /**************************************************************************** * Generic math functions * ****************************************************************************/ namespace numext { #if (!defined(EIGEN_GPUCC)) template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T mini(const T& x, const T& y) { EIGEN_USING_STD_MATH(min); return min EIGEN_NOT_A_MACRO(x, y); } template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T maxi(const T& x, const T& y) { EIGEN_USING_STD_MATH(max); return max EIGEN_NOT_A_MACRO(x, y); } #else template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T mini(const T& x, const T& y) { return y < x ? y : x; } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float mini(const float& x, const float& y) { return fminf(x, y); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double mini(const double& x, const double& y) { return fmin(x, y); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE long double mini(const long double& x, const long double& y) { #if defined(EIGEN_HIPCC) // no "fminl" on HIP yet return (x < y) ? x : y; #else return fminl(x, y); #endif } template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T maxi(const T& x, const T& y) { return x < y ? y : x; } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float maxi(const float& x, const float& y) { return fmaxf(x, y); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double maxi(const double& x, const double& y) { return fmax(x, y); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE long double maxi(const long double& x, const long double& y) { #if defined(EIGEN_HIPCC) // no "fmaxl" on HIP yet return (x > y) ? x : y; #else return fmaxl(x, y); #endif } #endif #if defined(SYCL_DEVICE_ONLY) #define SYCL_SPECIALIZE_SIGNED_INTEGER_TYPES_BINARY(NAME, FUNC) \ SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_char) \ SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_short) \ SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_int) \ SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_long) #define SYCL_SPECIALIZE_SIGNED_INTEGER_TYPES_UNARY(NAME, FUNC) \ SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_char) \ SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_short) \ SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_int) \ SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_long) #define SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_BINARY(NAME, FUNC) \ SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_uchar) \ SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_ushort) \ SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_uint) \ SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_ulong) #define SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_UNARY(NAME, FUNC) \ SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_uchar) \ SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_ushort) \ SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_uint) \ SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_ulong) #define SYCL_SPECIALIZE_INTEGER_TYPES_BINARY(NAME, FUNC) \ SYCL_SPECIALIZE_SIGNED_INTEGER_TYPES_BINARY(NAME, FUNC) \ SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_BINARY(NAME, FUNC) #define SYCL_SPECIALIZE_INTEGER_TYPES_UNARY(NAME, FUNC) \ SYCL_SPECIALIZE_SIGNED_INTEGER_TYPES_UNARY(NAME, FUNC) \ SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_UNARY(NAME, FUNC) #define SYCL_SPECIALIZE_FLOATING_TYPES_BINARY(NAME, FUNC) \ SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_float) \ SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_double) #define SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(NAME, FUNC) \ SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_float) \ SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_double) #define SYCL_SPECIALIZE_FLOATING_TYPES_UNARY_FUNC_RET_TYPE( \ NAME, FUNC, RET_TYPE) \ SYCL_SPECIALIZE_GEN_UNARY_FUNC(NAME, FUNC, RET_TYPE, cl::sycl::cl_float) \ SYCL_SPECIALIZE_GEN_UNARY_FUNC(NAME, FUNC, RET_TYPE, cl::sycl::cl_double) #define SYCL_SPECIALIZE_GEN_UNARY_FUNC(NAME, FUNC, RET_TYPE, ARG_TYPE) \ template <> \ EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE RET_TYPE NAME(const ARG_TYPE& x) { \ return cl::sycl::FUNC(x); \ } #define SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, TYPE) \ SYCL_SPECIALIZE_GEN_UNARY_FUNC(NAME, FUNC, TYPE, TYPE) #define SYCL_SPECIALIZE_GEN1_BINARY_FUNC( \ NAME, FUNC, RET_TYPE, ARG_TYPE1, ARG_TYPE2) \ template <> \ EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE RET_TYPE NAME(const ARG_TYPE1& x, \ const ARG_TYPE2& y) { \ return cl::sycl::FUNC(x, y); \ } #define SYCL_SPECIALIZE_GEN2_BINARY_FUNC(NAME, FUNC, RET_TYPE, ARG_TYPE) \ SYCL_SPECIALIZE_GEN1_BINARY_FUNC(NAME, FUNC, RET_TYPE, ARG_TYPE, ARG_TYPE) #define SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, TYPE) \ SYCL_SPECIALIZE_GEN2_BINARY_FUNC(NAME, FUNC, TYPE, TYPE) SYCL_SPECIALIZE_INTEGER_TYPES_BINARY(mini, min) SYCL_SPECIALIZE_FLOATING_TYPES_BINARY(mini, fmin) SYCL_SPECIALIZE_INTEGER_TYPES_BINARY(maxi, max) SYCL_SPECIALIZE_FLOATING_TYPES_BINARY(maxi, fmax) #endif template EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(real, Scalar) real(const Scalar& x) { return EIGEN_MATHFUNC_IMPL(real, Scalar)::run(x); } template EIGEN_DEVICE_FUNC inline typename internal::add_const_on_value_type< EIGEN_MATHFUNC_RETVAL(real_ref, Scalar)>::type real_ref(const Scalar& x) { return internal::real_ref_impl::run(x); } template EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(real_ref, Scalar) real_ref(Scalar& x) { return EIGEN_MATHFUNC_IMPL(real_ref, Scalar)::run(x); } template EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(imag, Scalar) imag(const Scalar& x) { return EIGEN_MATHFUNC_IMPL(imag, Scalar)::run(x); } template EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(arg, Scalar) arg(const Scalar& x) { return EIGEN_MATHFUNC_IMPL(arg, Scalar)::run(x); } template EIGEN_DEVICE_FUNC inline typename internal::add_const_on_value_type< EIGEN_MATHFUNC_RETVAL(imag_ref, Scalar)>::type imag_ref(const Scalar& x) { return internal::imag_ref_impl::run(x); } template EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(imag_ref, Scalar) imag_ref(Scalar& x) { return EIGEN_MATHFUNC_IMPL(imag_ref, Scalar)::run(x); } template EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(conj, Scalar) conj(const Scalar& x) { return EIGEN_MATHFUNC_IMPL(conj, Scalar)::run(x); } template EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(abs2, Scalar) abs2(const Scalar& x) { return EIGEN_MATHFUNC_IMPL(abs2, Scalar)::run(x); } EIGEN_DEVICE_FUNC inline bool abs2(bool x) { return x; } template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T absdiff(const T& x, const T& y) { return x > y ? x - y : y - x; } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float absdiff(const float& x, const float& y) { return fabsf(x - y); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double absdiff(const double& x, const double& y) { return fabs(x - y); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE long double absdiff( const long double& x, const long double& y) { #if defined(EIGEN_HIPCC) // no "fabsl" on HIP yet return (x > y) ? x : y; #else return fabsl(x - y); #endif } template EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(norm1, Scalar) norm1(const Scalar& x) { return EIGEN_MATHFUNC_IMPL(norm1, Scalar)::run(x); } template EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(hypot, Scalar) hypot(const Scalar& x, const Scalar& y) { return EIGEN_MATHFUNC_IMPL(hypot, Scalar)::run(x, y); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_BINARY(hypot, hypot) #endif template EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(log1p, Scalar) log1p(const Scalar& x) { return EIGEN_MATHFUNC_IMPL(log1p, Scalar)::run(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(log1p, log1p) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float log1p(const float& x) { return ::log1pf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double log1p(const double& x) { return ::log1p(x); } #endif template EIGEN_DEVICE_FUNC inline typename internal::pow_impl::result_type pow(const ScalarX& x, const ScalarY& y) { return internal::pow_impl::run(x, y); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_BINARY(pow, pow) #endif template EIGEN_DEVICE_FUNC bool(isnan)(const T& x) { return internal::isnan_impl(x); } template EIGEN_DEVICE_FUNC bool(isinf)(const T& x) { return internal::isinf_impl(x); } template EIGEN_DEVICE_FUNC bool(isfinite)(const T& x) { return internal::isfinite_impl(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY_FUNC_RET_TYPE(isnan, isnan, bool) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY_FUNC_RET_TYPE(isinf, isinf, bool) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY_FUNC_RET_TYPE(isfinite, isfinite, bool) #endif template EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(rint, Scalar) rint(const Scalar& x) { return EIGEN_MATHFUNC_IMPL(rint, Scalar)::run(x); } template EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(round, Scalar) round(const Scalar& x) { return EIGEN_MATHFUNC_IMPL(round, Scalar)::run(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(round, round) #endif template EIGEN_DEVICE_FUNC T(floor)(const T& x) { EIGEN_USING_STD_MATH(floor); return floor(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(floor, floor) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float floor(const float& x) { return ::floorf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double floor(const double& x) { return ::floor(x); } #endif template EIGEN_DEVICE_FUNC T(ceil)(const T& x) { EIGEN_USING_STD_MATH(ceil); return ceil(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(ceil, ceil) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float ceil(const float& x) { return ::ceilf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double ceil(const double& x) { return ::ceil(x); } #endif /** Log base 2 for 32 bits positive integers. * Conveniently returns 0 for x==0. */ inline int log2(int x) { eigen_assert(x >= 0); unsigned int v(x); static const int table[32] = {0, 9, 1, 10, 13, 21, 2, 29, 11, 14, 16, 18, 22, 25, 3, 30, 8, 12, 20, 28, 15, 17, 24, 7, 19, 27, 23, 6, 26, 5, 4, 31}; v |= v >> 1; v |= v >> 2; v |= v >> 4; v |= v >> 8; v |= v >> 16; return table[(v * 0x07C4ACDDU) >> 27]; } /** \returns the square root of \a x. * * It is essentially equivalent to * \code using std::sqrt; return sqrt(x); \endcode * but slightly faster for float/double and some compilers (e.g., gcc), thanks * to * specializations when SSE is enabled. * * It's usage is justified in performance critical functions, like * norm/normalize. */ template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T sqrt(const T& x) { EIGEN_USING_STD_MATH(sqrt); return sqrt(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(sqrt, sqrt) #endif template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T log(const T& x) { EIGEN_USING_STD_MATH(log); return log(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(log, log) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float log(const float& x) { return ::logf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double log(const double& x) { return ::log(x); } #endif template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE typename internal::enable_if::IsSigned || NumTraits::IsComplex, typename NumTraits::Real>::type abs(const T& x) { EIGEN_USING_STD_MATH(abs); return abs(x); } template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE typename internal::enable_if::IsSigned || NumTraits::IsComplex), typename NumTraits::Real>::type abs(const T& x) { return x; } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_INTEGER_TYPES_UNARY(abs, abs) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(abs, fabs) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float abs(const float& x) { return ::fabsf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double abs(const double& x) { return ::fabs(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float abs(const std::complex& x) { return ::hypotf(x.real(), x.imag()); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double abs( const std::complex& x) { return ::hypot(x.real(), x.imag()); } #endif template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T exp(const T& x) { EIGEN_USING_STD_MATH(exp); return exp(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(exp, exp) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float exp(const float& x) { return ::expf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double exp(const double& x) { return ::exp(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::complex exp( const std::complex& x) { float com = ::expf(x.real()); float res_real = com * ::cosf(x.imag()); float res_imag = com * ::sinf(x.imag()); return std::complex(res_real, res_imag); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::complex exp( const std::complex& x) { double com = ::exp(x.real()); double res_real = com * ::cos(x.imag()); double res_imag = com * ::sin(x.imag()); return std::complex(res_real, res_imag); } #endif template EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(expm1, Scalar) expm1(const Scalar& x) { return EIGEN_MATHFUNC_IMPL(expm1, Scalar)::run(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(expm1, expm1) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float expm1(const float& x) { return ::expm1f(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double expm1(const double& x) { return ::expm1(x); } #endif template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T cos(const T& x) { EIGEN_USING_STD_MATH(cos); return cos(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(cos, cos) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float cos(const float& x) { return ::cosf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double cos(const double& x) { return ::cos(x); } #endif template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T sin(const T& x) { EIGEN_USING_STD_MATH(sin); return sin(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(sin, sin) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float sin(const float& x) { return ::sinf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double sin(const double& x) { return ::sin(x); } #endif template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T tan(const T& x) { EIGEN_USING_STD_MATH(tan); return tan(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(tan, tan) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float tan(const float& x) { return ::tanf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double tan(const double& x) { return ::tan(x); } #endif template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T acos(const T& x) { EIGEN_USING_STD_MATH(acos); return acos(x); } #if EIGEN_HAS_CXX11_MATH template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T acosh(const T& x) { EIGEN_USING_STD_MATH(acosh); return acosh(x); } #endif #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(acos, acos) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(acosh, acosh) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float acos(const float& x) { return ::acosf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double acos(const double& x) { return ::acos(x); } #endif template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T asin(const T& x) { EIGEN_USING_STD_MATH(asin); return asin(x); } #if EIGEN_HAS_CXX11_MATH template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T asinh(const T& x) { EIGEN_USING_STD_MATH(asinh); return asinh(x); } #endif #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(asin, asin) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(asinh, asinh) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float asin(const float& x) { return ::asinf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double asin(const double& x) { return ::asin(x); } #endif template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T atan(const T& x) { EIGEN_USING_STD_MATH(atan); return atan(x); } #if EIGEN_HAS_CXX11_MATH template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T atanh(const T& x) { EIGEN_USING_STD_MATH(atanh); return atanh(x); } #endif #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(atan, atan) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(atanh, atanh) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float atan(const float& x) { return ::atanf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double atan(const double& x) { return ::atan(x); } #endif template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T cosh(const T& x) { EIGEN_USING_STD_MATH(cosh); return cosh(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(cosh, cosh) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float cosh(const float& x) { return ::coshf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double cosh(const double& x) { return ::cosh(x); } #endif template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T sinh(const T& x) { EIGEN_USING_STD_MATH(sinh); return sinh(x); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(sinh, sinh) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float sinh(const float& x) { return ::sinhf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double sinh(const double& x) { return ::sinh(x); } #endif template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T tanh(const T& x) { EIGEN_USING_STD_MATH(tanh); return tanh(x); } #if (!defined(EIGEN_GPUCC)) && EIGEN_FAST_MATH && !defined(SYCL_DEVICE_ONLY) EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float tanh(float x) { return internal::generic_fast_tanh_float(x); } #endif #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(tanh, tanh) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float tanh(const float& x) { return ::tanhf(x); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double tanh(const double& x) { return ::tanh(x); } #endif template EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T fmod(const T& a, const T& b) { EIGEN_USING_STD_MATH(fmod); return fmod(a, b); } #if defined(SYCL_DEVICE_ONLY) SYCL_SPECIALIZE_FLOATING_TYPES_BINARY(fmod, fmod) #endif #if defined(EIGEN_GPUCC) template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float fmod(const float& a, const float& b) { return ::fmodf(a, b); } template <> EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double fmod(const double& a, const double& b) { return ::fmod(a, b); } #endif #if defined(SYCL_DEVICE_ONLY) #undef SYCL_SPECIALIZE_SIGNED_INTEGER_TYPES_BINARY #undef SYCL_SPECIALIZE_SIGNED_INTEGER_TYPES_UNARY #undef SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_BINARY #undef SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_UNARY #undef SYCL_SPECIALIZE_INTEGER_TYPES_BINARY #undef SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_UNARY #undef SYCL_SPECIALIZE_FLOATING_TYPES_BINARY #undef SYCL_SPECIALIZE_FLOATING_TYPES_UNARY #undef SYCL_SPECIALIZE_FLOATING_TYPES_UNARY_FUNC_RET_TYPE #undef SYCL_SPECIALIZE_GEN_UNARY_FUNC #undef SYCL_SPECIALIZE_UNARY_FUNC #undef SYCL_SPECIALIZE_GEN1_BINARY_FUNC #undef SYCL_SPECIALIZE_GEN2_BINARY_FUNC #undef SYCL_SPECIALIZE_BINARY_FUNC #endif } // end namespace numext namespace internal { template EIGEN_DEVICE_FUNC bool isfinite_impl(const std::complex& x) { return (numext::isfinite)(numext::real(x)) && (numext::isfinite)(numext::imag(x)); } template EIGEN_DEVICE_FUNC bool isnan_impl(const std::complex& x) { return (numext::isnan)(numext::real(x)) || (numext::isnan)(numext::imag(x)); } template EIGEN_DEVICE_FUNC bool isinf_impl(const std::complex& x) { return ((numext::isinf)(numext::real(x)) || (numext::isinf)(numext::imag(x))) && (!(numext::isnan)(x)); } /**************************************************************************** * Implementation of fuzzy comparisons * ****************************************************************************/ template struct scalar_fuzzy_default_impl {}; template struct scalar_fuzzy_default_impl { typedef typename NumTraits::Real RealScalar; template EIGEN_DEVICE_FUNC static inline bool isMuchSmallerThan( const Scalar& x, const OtherScalar& y, const RealScalar& prec) { return numext::abs(x) <= numext::abs(y) * prec; } EIGEN_DEVICE_FUNC static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar& prec) { return numext::abs(x - y) <= numext::mini(numext::abs(x), numext::abs(y)) * prec; } EIGEN_DEVICE_FUNC static inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y, const RealScalar& prec) { return x <= y || isApprox(x, y, prec); } }; template struct scalar_fuzzy_default_impl { typedef typename NumTraits::Real RealScalar; template EIGEN_DEVICE_FUNC static inline bool isMuchSmallerThan(const Scalar& x, const Scalar&, const RealScalar&) { return x == Scalar(0); } EIGEN_DEVICE_FUNC static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar&) { return x == y; } EIGEN_DEVICE_FUNC static inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y, const RealScalar&) { return x <= y; } }; template struct scalar_fuzzy_default_impl { typedef typename NumTraits::Real RealScalar; template EIGEN_DEVICE_FUNC static inline bool isMuchSmallerThan( const Scalar& x, const OtherScalar& y, const RealScalar& prec) { return numext::abs2(x) <= numext::abs2(y) * prec * prec; } EIGEN_DEVICE_FUNC static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar& prec) { return numext::abs2(x - y) <= numext::mini(numext::abs2(x), numext::abs2(y)) * prec * prec; } }; template struct scalar_fuzzy_impl : scalar_fuzzy_default_impl::IsComplex, NumTraits::IsInteger> {}; template EIGEN_DEVICE_FUNC inline bool isMuchSmallerThan( const Scalar& x, const OtherScalar& y, const typename NumTraits::Real& precision = NumTraits::dummy_precision()) { return scalar_fuzzy_impl::template isMuchSmallerThan( x, y, precision); } template EIGEN_DEVICE_FUNC inline bool isApprox( const Scalar& x, const Scalar& y, const typename NumTraits::Real& precision = NumTraits::dummy_precision()) { return scalar_fuzzy_impl::isApprox(x, y, precision); } template EIGEN_DEVICE_FUNC inline bool isApproxOrLessThan( const Scalar& x, const Scalar& y, const typename NumTraits::Real& precision = NumTraits::dummy_precision()) { return scalar_fuzzy_impl::isApproxOrLessThan(x, y, precision); } /****************************************** *** The special case of the bool type *** ******************************************/ template <> struct random_impl { static inline bool run() { return random(0, 1) == 0 ? false : true; } }; template <> struct scalar_fuzzy_impl { typedef bool RealScalar; template EIGEN_DEVICE_FUNC static inline bool isMuchSmallerThan(const bool& x, const bool&, const bool&) { return !x; } EIGEN_DEVICE_FUNC static inline bool isApprox(bool x, bool y, bool) { return x == y; } EIGEN_DEVICE_FUNC static inline bool isApproxOrLessThan(const bool& x, const bool& y, const bool&) { return (!x) || y; } }; } // end namespace internal } // end namespace Eigen #endif // EIGEN_MATHFUNCTIONS_H