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未验证 提交 b9aeb681 编写于 作者: Z Zhang Ting 提交者： GitHub
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remove EIGEN_MAX_CPP_VER=11, test=develop (#25309)

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cmake/configure.cmake
浏览文件 @ b9aeb681
...@@ -70,10 +70,6 @@ endif() ...@@ -70,10 +70,6 @@ endif()
if(WITH_GPU) if(WITH_GPU)
add_definitions(-DPADDLE_WITH_CUDA) add_definitions(-DPADDLE_WITH_CUDA)
add_definitions(-DEIGEN_USE_GPU) add_definitions(-DEIGEN_USE_GPU)
# The compiler fully support const expressions since c++14,
# but Eigen use some const expressions such as std::max and std::min, which are not supported in c++11
# use following definition to set EIGEN_HAS_CONSTEXPR=0 to avoid compilation error in c++11
add_definitions(-DEIGEN_MAX_CPP_VER=11)
FIND_PACKAGE(CUDA REQUIRED) FIND_PACKAGE(CUDA REQUIRED)
......
cmake/external/eigen.cmake
浏览文件 @ b9aeb681
...@@ -49,9 +49,14 @@ elseif(LINUX) ...@@ -49,9 +49,14 @@ elseif(LINUX)
# refer to: https://gitlab.com/libeigen/eigen/-/blob/4da2c6b1974827b1999bab652a3d4703e1992d26/Eigen/src/Core/arch/SSE/PacketMath.h#L33-60 # refer to: https://gitlab.com/libeigen/eigen/-/blob/4da2c6b1974827b1999bab652a3d4703e1992d26/Eigen/src/Core/arch/SSE/PacketMath.h#L33-60
# add -fabi-version=4 could avoid above error, but will cause "double free corruption" when compile with gcc8 # add -fabi-version=4 could avoid above error, but will cause "double free corruption" when compile with gcc8
# so use following patch to solve compilation error with different version of gcc. # so use following patch to solve compilation error with different version of gcc.
file(TO_NATIVE_PATH ${PADDLE_SOURCE_DIR}/patches/eigen/Geometry_SSE.h native_src) file(TO_NATIVE_PATH ${PADDLE_SOURCE_DIR}/patches/eigen/Geometry_SSE.h native_src1)
file(TO_NATIVE_PATH ${EIGEN_SOURCE_DIR}/Eigen/src/Geometry/arch/Geometry_SSE.h native_dst) file(TO_NATIVE_PATH ${EIGEN_SOURCE_DIR}/Eigen/src/Geometry/arch/Geometry_SSE.h native_dst1)
set(EIGEN_PATCH_COMMAND cp ${native_src} ${native_dst}) # The compiler fully support const expressions since c++14,
# but Eigen use some const expressions such as std::max and std::min, which are not supported in c++11
# add patch to avoid compilation error in c++11
file(TO_NATIVE_PATH ${PADDLE_SOURCE_DIR}/patches/eigen/MathFunctions.h native_src2)
file(TO_NATIVE_PATH ${EIGEN_SOURCE_DIR}/Eigen/src/Core/MathFunctions.h native_dst2)
set(EIGEN_PATCH_COMMAND cp ${native_src1} ${native_dst1} && cp ${native_src2} ${native_dst2})
endif() endif()
set(EIGEN_INCLUDE_DIR ${EIGEN_SOURCE_DIR}) set(EIGEN_INCLUDE_DIR ${EIGEN_SOURCE_DIR})
......
patches/eigen/MathFunctions.h 0 → 100644
浏览文件 @ b9aeb681
// 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 <jacob.benoit.1@gmail.com>
//
// 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<T>::type is a typedef for it.
* - otherwise, global_math_functions_filtering_base<T>::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<Derived>.
* So we must make sure to use sin_impl<ArrayBase<Derived> > and not
* sin_impl<Derived>, 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 <typename T, typename dummy = void>
struct global_math_functions_filtering_base {
typedef T type;
};
template <typename T>
struct always_void {
typedef void type;
};
template <typename T>
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 <typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
struct real_default_impl {
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar& x) { return x; }
};
template <typename Scalar>
struct real_default_impl<Scalar, true> {
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar& x) {
using std::real;
return real(x);
}
};
template <typename Scalar>
struct real_impl : real_default_impl<Scalar> {};
#if defined(EIGEN_GPU_COMPILE_PHASE)
template <typename T>
struct real_impl<std::complex<T>> {
typedef T RealScalar;
EIGEN_DEVICE_FUNC
static inline T run(const std::complex<T>& x) { return x.real(); }
};
#endif
template <typename Scalar>
struct real_retval {
typedef typename NumTraits<Scalar>::Real type;
};
/****************************************************************************
* Implementation of imag *
****************************************************************************/
template <typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
struct imag_default_impl {
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar&) { return RealScalar(0); }
};
template <typename Scalar>
struct imag_default_impl<Scalar, true> {
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar& x) {
using std::imag;
return imag(x);
}
};
template <typename Scalar>
struct imag_impl : imag_default_impl<Scalar> {};
#if defined(EIGEN_GPU_COMPILE_PHASE)
template <typename T>
struct imag_impl<std::complex<T>> {
typedef T RealScalar;
EIGEN_DEVICE_FUNC
static inline T run(const std::complex<T>& x) { return x.imag(); }
};
#endif
template <typename Scalar>
struct imag_retval {
typedef typename NumTraits<Scalar>::Real type;
};
/****************************************************************************
* Implementation of real_ref *
****************************************************************************/
template <typename Scalar>
struct real_ref_impl {
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar& run(Scalar& x) {
return reinterpret_cast<RealScalar*>(&x)[0];
}
EIGEN_DEVICE_FUNC
static inline const RealScalar& run(const Scalar& x) {
return reinterpret_cast<const RealScalar*>(&x)[0];
}
};
template <typename Scalar>
struct real_ref_retval {
typedef typename NumTraits<Scalar>::Real& type;
};
/****************************************************************************
* Implementation of imag_ref *
****************************************************************************/
template <typename Scalar, bool IsComplex>
struct imag_ref_default_impl {
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar& run(Scalar& x) {
return reinterpret_cast<RealScalar*>(&x)[1];
}
EIGEN_DEVICE_FUNC
static inline const RealScalar& run(const Scalar& x) {
return reinterpret_cast<RealScalar*>(&x)[1];
}
};
template <typename Scalar>
struct imag_ref_default_impl<Scalar, false> {
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 <typename Scalar>
struct imag_ref_impl
: imag_ref_default_impl<Scalar, NumTraits<Scalar>::IsComplex> {};
template <typename Scalar>
struct imag_ref_retval {
typedef typename NumTraits<Scalar>::Real& type;
};
/****************************************************************************
* Implementation of conj *
****************************************************************************/
template <typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
struct conj_default_impl {
EIGEN_DEVICE_FUNC
static inline Scalar run(const Scalar& x) { return x; }
};
template <typename Scalar>
struct conj_default_impl<Scalar, true> {
EIGEN_DEVICE_FUNC
static inline Scalar run(const Scalar& x) {
using std::conj;
return conj(x);
}
};
template <typename Scalar>
struct conj_impl : conj_default_impl<Scalar> {};
#if defined(EIGEN_GPU_COMPILE_PHASE)
template <typename T>
struct conj_impl<std::complex<T>> {
EIGEN_DEVICE_FUNC
static inline std::complex<T> run(const std::complex<T>& x) {
return std::complex<T>(x.real(), -x.imag());
}
};
#endif
template <typename Scalar>
struct conj_retval {
typedef Scalar type;
};
/****************************************************************************
* Implementation of abs2 *
****************************************************************************/
template <typename Scalar, bool IsComplex>
struct abs2_impl_default {
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar& x) { return x * x; }
};
template <typename Scalar>
struct abs2_impl_default<Scalar, true> // IsComplex
{
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar& x) {
return x.real() * x.real() + x.imag() * x.imag();
}
};
template <typename Scalar>
struct abs2_impl {
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar& x) {
return abs2_impl_default<Scalar, NumTraits<Scalar>::IsComplex>::run(x);
}
};
template <typename Scalar>
struct abs2_retval {
typedef typename NumTraits<Scalar>::Real type;
};
/****************************************************************************
* Implementation of norm1 *
****************************************************************************/
template <typename Scalar, bool IsComplex>
struct norm1_default_impl;
template <typename Scalar>
struct norm1_default_impl<Scalar, true> {
typedef typename NumTraits<Scalar>::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 <typename Scalar>
struct norm1_default_impl<Scalar, false> {
EIGEN_DEVICE_FUNC
static inline Scalar run(const Scalar& x) {
EIGEN_USING_STD_MATH(abs);
return abs(x);
}
};
template <typename Scalar>
struct norm1_impl : norm1_default_impl<Scalar, NumTraits<Scalar>::IsComplex> {};
template <typename Scalar>
struct norm1_retval {
typedef typename NumTraits<Scalar>::Real type;
};
/****************************************************************************
* Implementation of hypot *
****************************************************************************/
template <typename Scalar>
struct hypot_impl;
template <typename Scalar>
struct hypot_retval {
typedef typename NumTraits<Scalar>::Real type;
};
/****************************************************************************
* Implementation of cast *
****************************************************************************/
template <typename OldType, typename NewType>
struct cast_impl {
EIGEN_DEVICE_FUNC
static inline NewType run(const OldType& x) {
return static_cast<NewType>(x);
}
};
// here, for once, we're plainly returning NewType: we don't want cast to do
// weird things.
template <typename OldType, typename NewType>
EIGEN_DEVICE_FUNC inline NewType cast(const OldType& x) {
return cast_impl<OldType, NewType>::run(x);
}
/****************************************************************************
* Implementation of round *
****************************************************************************/
#if EIGEN_HAS_CXX11_MATH
template <typename Scalar>
struct round_impl {
EIGEN_DEVICE_FUNC
static inline Scalar run(const Scalar& x) {
EIGEN_STATIC_ASSERT((!NumTraits<Scalar>::IsComplex),
NUMERIC_TYPE_MUST_BE_REAL)
EIGEN_USING_STD_MATH(round);
return round(x);
}
};
#else
template <typename Scalar>
struct round_impl {
EIGEN_DEVICE_FUNC
static inline Scalar run(const Scalar& x) {
EIGEN_STATIC_ASSERT((!NumTraits<Scalar>::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 <typename Scalar>
struct round_retval {
typedef Scalar type;
};
/****************************************************************************
* Implementation of rint *
****************************************************************************/
template <typename Scalar>
struct rint_impl {
EIGEN_DEVICE_FUNC
static inline Scalar run(const Scalar& x) {
EIGEN_STATIC_ASSERT((!NumTraits<Scalar>::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<double> {
EIGEN_DEVICE_FUNC
static inline double run(const double& x) { return ::rint(x); }
};
template <>
struct rint_impl<float> {
EIGEN_DEVICE_FUNC
static inline float run(const float& x) { return ::rintf(x); }
};
#endif
template <typename Scalar>
struct rint_retval {
typedef Scalar type;
};
/****************************************************************************
* Implementation of arg *
****************************************************************************/
#if EIGEN_HAS_CXX11_MATH
template <typename Scalar>
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 <typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
struct arg_default_impl {
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar& x) {
return (x < Scalar(0)) ? Scalar(EIGEN_PI) : Scalar(0);
}
};
template <typename Scalar>
struct arg_default_impl<Scalar, true> {
typedef typename NumTraits<Scalar>::Real RealScalar;
EIGEN_DEVICE_FUNC
static inline RealScalar run(const Scalar& x) {
EIGEN_USING_STD_MATH(arg);
return arg(x);
}
};
template <typename Scalar>
struct arg_impl : arg_default_impl<Scalar> {};
#endif
template <typename Scalar>
struct arg_retval {
typedef typename NumTraits<Scalar>::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 <typename Scalar>
EIGEN_DEVICE_FUNC inline Scalar expm1(const Scalar& x) {
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
typedef typename NumTraits<Scalar>::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 <typename Scalar>
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 <typename RealScalar>
struct expm1_impl<std::complex<RealScalar>> {
EIGEN_DEVICE_FUNC static inline std::complex<RealScalar> run(
const std::complex<RealScalar>& 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<RealScalar>::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<RealScalar>(real_part, er * s);
}
};
template <typename Scalar>
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 <typename Scalar>
EIGEN_DEVICE_FUNC inline Scalar log1p(const Scalar& x) {
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
typedef typename NumTraits<Scalar>::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 <typename Scalar>
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 <typename RealScalar>
struct log1p_impl<std::complex<RealScalar>> {
EIGEN_DEVICE_FUNC static inline std::complex<RealScalar> run(
const std::complex<RealScalar>& x) {
EIGEN_STATIC_ASSERT_NON_INTEGER(RealScalar)
return std_fallback::log1p(x);
}
};
template <typename Scalar>
struct log1p_retval {
typedef Scalar type;
};
/****************************************************************************
* Implementation of pow *
****************************************************************************/
template <typename ScalarX,
typename ScalarY,
bool IsInteger =
NumTraits<ScalarX>::IsInteger&& NumTraits<ScalarY>::IsInteger>
struct pow_impl {
// typedef Scalar retval;
typedef typename ScalarBinaryOpTraits<
ScalarX,
ScalarY,
internal::scalar_pow_op<ScalarX, ScalarY>>::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 <typename ScalarX, typename ScalarY>
struct pow_impl<ScalarX, ScalarY, true> {
typedef ScalarX result_type;
static EIGEN_DEVICE_FUNC inline ScalarX run(ScalarX x, ScalarY y) {
ScalarX res(1);
eigen_assert(!NumTraits<ScalarY>::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 <typename Scalar, bool IsComplex, bool IsInteger>
struct random_default_impl {};
template <typename Scalar>
struct random_impl : random_default_impl<Scalar,
NumTraits<Scalar>::IsComplex,
NumTraits<Scalar>::IsInteger> {};
template <typename Scalar>
struct random_retval {
typedef Scalar type;
};
template <typename Scalar>
inline EIGEN_MATHFUNC_RETVAL(random, Scalar)
random(const Scalar& x, const Scalar& y);
template <typename Scalar>
inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random();
template <typename Scalar>
struct random_default_impl<Scalar, false, false> {
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<Scalar>::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 <unsigned int n, int lower, int upper>
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 <unsigned int n,
int lower = 0,
int upper = sizeof(unsigned int) * CHAR_BIT - 1,
int selector = meta_floor_log2_selector<n, lower, upper>::value>
struct meta_floor_log2 {};
template <unsigned int n, int lower, int upper>
struct meta_floor_log2<n, lower, upper, meta_floor_log2_move_down> {
enum {
value = meta_floor_log2<
n,
lower,
meta_floor_log2_selector<n, lower, upper>::middle>::value
};
};
template <unsigned int n, int lower, int upper>
struct meta_floor_log2<n, lower, upper, meta_floor_log2_move_up> {
enum {
value = meta_floor_log2<n,
meta_floor_log2_selector<n, lower, upper>::middle,
upper>::value
};
};
template <unsigned int n, int lower, int upper>
struct meta_floor_log2<n, lower, upper, meta_floor_log2_terminate> {
enum {
value = (n >= ((unsigned int)(1) << (lower + 1))) ? lower + 1 : lower
};
};
template <unsigned int n, int lower, int upper>
struct meta_floor_log2<n, lower, upper, meta_floor_log2_bogus> {
// no value, error at compile time
};
template <typename Scalar>
struct random_default_impl<Scalar, false, true> {
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<Scalar>::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<Scalar>::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<Scalar>::IsSigned
? (1 << (EIGEN_PLAIN_ENUM_MIN(rand_bits, scalar_bits) - 1))
: 0};
return Scalar((std::rand() >> shift) - offset);
#endif
}
};
template <typename Scalar>
struct random_default_impl<Scalar, true, false> {
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<Scalar>::Real RealScalar;
return Scalar(random<RealScalar>(), random<RealScalar>());
}
};
template <typename Scalar>
inline EIGEN_MATHFUNC_RETVAL(random, Scalar)
random(const Scalar& x, const Scalar& y) {
return EIGEN_MATHFUNC_IMPL(random, Scalar)::run(x, y);
}
template <typename Scalar>
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 <typename T>
EIGEN_DEVICE_FUNC
typename internal::enable_if<internal::is_integral<T>::value, bool>::type
isnan_impl(const T&) {
return false;
}
template <typename T>
EIGEN_DEVICE_FUNC
typename internal::enable_if<internal::is_integral<T>::value, bool>::type
isinf_impl(const T&) {
return false;
}
template <typename T>
EIGEN_DEVICE_FUNC
typename internal::enable_if<internal::is_integral<T>::value, bool>::type
isfinite_impl(const T&) {
return true;
}
template <typename T>
EIGEN_DEVICE_FUNC
typename internal::enable_if<(!internal::is_integral<T>::value) &&
(!NumTraits<T>::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<T>::highest() && x >= NumTraits<T>::lowest();
#endif
}
template <typename T>
EIGEN_DEVICE_FUNC
typename internal::enable_if<(!internal::is_integral<T>::value) &&
(!NumTraits<T>::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<T>::highest() || x < NumTraits<T>::lowest();
#endif
}
template <typename T>
EIGEN_DEVICE_FUNC
typename internal::enable_if<(!internal::is_integral<T>::value) &&
(!NumTraits<T>::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 <typename T>
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 <typename T>
EIGEN_DEVICE_FUNC bool isfinite_impl(const std::complex<T>& x);
template <typename T>
EIGEN_DEVICE_FUNC bool isnan_impl(const std::complex<T>& x);
template <typename T>
EIGEN_DEVICE_FUNC bool isinf_impl(const std::complex<T>& x);
template <typename T>
T generic_fast_tanh_float(const T& a_x);
} // end namespace internal
/****************************************************************************
* Generic math functions *
****************************************************************************/
namespace numext {
#if (!defined(EIGEN_GPUCC))
template <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename Scalar>
EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(real, Scalar)
real(const Scalar& x) {
return EIGEN_MATHFUNC_IMPL(real, Scalar)::run(x);
}
template <typename Scalar>
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<Scalar>::run(x);
}
template <typename Scalar>
EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(real_ref, Scalar)
real_ref(Scalar& x) {
return EIGEN_MATHFUNC_IMPL(real_ref, Scalar)::run(x);
}
template <typename Scalar>
EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(imag, Scalar)
imag(const Scalar& x) {
return EIGEN_MATHFUNC_IMPL(imag, Scalar)::run(x);
}
template <typename Scalar>
EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(arg, Scalar)
arg(const Scalar& x) {
return EIGEN_MATHFUNC_IMPL(arg, Scalar)::run(x);
}
template <typename Scalar>
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<Scalar>::run(x);
}
template <typename Scalar>
EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(imag_ref, Scalar)
imag_ref(Scalar& x) {
return EIGEN_MATHFUNC_IMPL(imag_ref, Scalar)::run(x);
}
template <typename Scalar>
EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(conj, Scalar)
conj(const Scalar& x) {
return EIGEN_MATHFUNC_IMPL(conj, Scalar)::run(x);
}
template <typename Scalar>
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 <typename T>
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 <typename Scalar>
EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(norm1, Scalar)
norm1(const Scalar& x) {
return EIGEN_MATHFUNC_IMPL(norm1, Scalar)::run(x);
}
template <typename Scalar>
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 <typename Scalar>
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 <typename ScalarX, typename ScalarY>
EIGEN_DEVICE_FUNC inline
typename internal::pow_impl<ScalarX, ScalarY>::result_type
pow(const ScalarX& x, const ScalarY& y) {
return internal::pow_impl<ScalarX, ScalarY>::run(x, y);
}
#if defined(SYCL_DEVICE_ONLY)
SYCL_SPECIALIZE_FLOATING_TYPES_BINARY(pow, pow)
#endif
template <typename T>
EIGEN_DEVICE_FUNC bool(isnan)(const T& x) {
return internal::isnan_impl(x);
}
template <typename T>
EIGEN_DEVICE_FUNC bool(isinf)(const T& x) {
return internal::isinf_impl(x);
}
template <typename T>
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 <typename Scalar>
EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(rint, Scalar)
rint(const Scalar& x) {
return EIGEN_MATHFUNC_IMPL(rint, Scalar)::run(x);
}
template <typename Scalar>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
typename internal::enable_if<NumTraits<T>::IsSigned ||
NumTraits<T>::IsComplex,
typename NumTraits<T>::Real>::type
abs(const T& x) {
EIGEN_USING_STD_MATH(abs);
return abs(x);
}
template <typename T>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
typename internal::enable_if<!(NumTraits<T>::IsSigned ||
NumTraits<T>::IsComplex),
typename NumTraits<T>::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<float>& x) {
return ::hypotf(x.real(), x.imag());
}
template <>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double abs(
const std::complex<double>& x) {
return ::hypot(x.real(), x.imag());
}
#endif
template <typename T>
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<float> exp(
const std::complex<float>& x) {
float com = ::expf(x.real());
float res_real = com * ::cosf(x.imag());
float res_imag = com * ::sinf(x.imag());
return std::complex<float>(res_real, res_imag);
}
template <>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::complex<double> exp(
const std::complex<double>& x) {
double com = ::exp(x.real());
double res_real = com * ::cos(x.imag());
double res_imag = com * ::sin(x.imag());
return std::complex<double>(res_real, res_imag);
}
#endif
template <typename Scalar>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
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 <typename T>
EIGEN_DEVICE_FUNC bool isfinite_impl(const std::complex<T>& x) {
return (numext::isfinite)(numext::real(x)) &&
(numext::isfinite)(numext::imag(x));
}
template <typename T>
EIGEN_DEVICE_FUNC bool isnan_impl(const std::complex<T>& x) {
return (numext::isnan)(numext::real(x)) || (numext::isnan)(numext::imag(x));
}
template <typename T>
EIGEN_DEVICE_FUNC bool isinf_impl(const std::complex<T>& x) {
return ((numext::isinf)(numext::real(x)) ||
(numext::isinf)(numext::imag(x))) &&
(!(numext::isnan)(x));
}
/****************************************************************************
* Implementation of fuzzy comparisons *
****************************************************************************/
template <typename Scalar, bool IsComplex, bool IsInteger>
struct scalar_fuzzy_default_impl {};
template <typename Scalar>
struct scalar_fuzzy_default_impl<Scalar, false, false> {
typedef typename NumTraits<Scalar>::Real RealScalar;
template <typename OtherScalar>
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 <typename Scalar>
struct scalar_fuzzy_default_impl<Scalar, false, true> {
typedef typename NumTraits<Scalar>::Real RealScalar;
template <typename OtherScalar>
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 <typename Scalar>
struct scalar_fuzzy_default_impl<Scalar, true, false> {
typedef typename NumTraits<Scalar>::Real RealScalar;
template <typename OtherScalar>
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 <typename Scalar>
struct scalar_fuzzy_impl
: scalar_fuzzy_default_impl<Scalar,
NumTraits<Scalar>::IsComplex,
NumTraits<Scalar>::IsInteger> {};
template <typename Scalar, typename OtherScalar>
EIGEN_DEVICE_FUNC inline bool isMuchSmallerThan(
const Scalar& x,
const OtherScalar& y,
const typename NumTraits<Scalar>::Real& precision =
NumTraits<Scalar>::dummy_precision()) {
return scalar_fuzzy_impl<Scalar>::template isMuchSmallerThan<OtherScalar>(
x, y, precision);
}
template <typename Scalar>
EIGEN_DEVICE_FUNC inline bool isApprox(
const Scalar& x,
const Scalar& y,
const typename NumTraits<Scalar>::Real& precision =
NumTraits<Scalar>::dummy_precision()) {
return scalar_fuzzy_impl<Scalar>::isApprox(x, y, precision);
}
template <typename Scalar>
EIGEN_DEVICE_FUNC inline bool isApproxOrLessThan(
const Scalar& x,
const Scalar& y,
const typename NumTraits<Scalar>::Real& precision =
NumTraits<Scalar>::dummy_precision()) {
return scalar_fuzzy_impl<Scalar>::isApproxOrLessThan(x, y, precision);
}
/******************************************
*** The special case of the bool type ***
******************************************/
template <>
struct random_impl<bool> {
static inline bool run() { return random<int>(0, 1) == 0 ? false : true; }
};
template <>
struct scalar_fuzzy_impl<bool> {
typedef bool RealScalar;
template <typename OtherScalar>
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
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