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Diffstat (limited to 'src/3rdparty/eigen/Eigen/src/Core/functors/UnaryFunctors.h')
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diff --git a/src/3rdparty/eigen/Eigen/src/Core/functors/UnaryFunctors.h b/src/3rdparty/eigen/Eigen/src/Core/functors/UnaryFunctors.h new file mode 100644 index 000000000..16136d185 --- /dev/null +++ b/src/3rdparty/eigen/Eigen/src/Core/functors/UnaryFunctors.h @@ -0,0 +1,1131 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2016 Gael Guennebaud <gael.guennebaud@inria.fr> +// +// 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_UNARY_FUNCTORS_H +#define EIGEN_UNARY_FUNCTORS_H + +namespace Eigen { + +namespace internal { + +/** \internal + * \brief Template functor to compute the opposite of a scalar + * + * \sa class CwiseUnaryOp, MatrixBase::operator- + */ +template<typename Scalar> struct scalar_opposite_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_opposite_op) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return -a; } + template<typename Packet> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const + { return internal::pnegate(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_opposite_op<Scalar> > +{ enum { + Cost = NumTraits<Scalar>::AddCost, + PacketAccess = packet_traits<Scalar>::HasNegate }; +}; + +/** \internal + * \brief Template functor to compute the absolute value of a scalar + * + * \sa class CwiseUnaryOp, Cwise::abs + */ +template<typename Scalar> struct scalar_abs_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_abs_op) + typedef typename NumTraits<Scalar>::Real result_type; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return numext::abs(a); } + template<typename Packet> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const + { return internal::pabs(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_abs_op<Scalar> > +{ + enum { + Cost = NumTraits<Scalar>::AddCost, + PacketAccess = packet_traits<Scalar>::HasAbs + }; +}; + +/** \internal + * \brief Template functor to compute the score of a scalar, to chose a pivot + * + * \sa class CwiseUnaryOp + */ +template<typename Scalar> struct scalar_score_coeff_op : scalar_abs_op<Scalar> +{ + typedef void Score_is_abs; +}; +template<typename Scalar> +struct functor_traits<scalar_score_coeff_op<Scalar> > : functor_traits<scalar_abs_op<Scalar> > {}; + +/* Avoid recomputing abs when we know the score and they are the same. Not a true Eigen functor. */ +template<typename Scalar, typename=void> struct abs_knowing_score +{ + EIGEN_EMPTY_STRUCT_CTOR(abs_knowing_score) + typedef typename NumTraits<Scalar>::Real result_type; + template<typename Score> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a, const Score&) const { return numext::abs(a); } +}; +template<typename Scalar> struct abs_knowing_score<Scalar, typename scalar_score_coeff_op<Scalar>::Score_is_abs> +{ + EIGEN_EMPTY_STRUCT_CTOR(abs_knowing_score) + typedef typename NumTraits<Scalar>::Real result_type; + template<typename Scal> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const Scal&, const result_type& a) const { return a; } +}; + +/** \internal + * \brief Template functor to compute the squared absolute value of a scalar + * + * \sa class CwiseUnaryOp, Cwise::abs2 + */ +template<typename Scalar> struct scalar_abs2_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_abs2_op) + typedef typename NumTraits<Scalar>::Real result_type; + EIGEN_DEVICE_FUNC + EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return numext::abs2(a); } + template<typename Packet> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const + { return internal::pmul(a,a); } +}; +template<typename Scalar> +struct functor_traits<scalar_abs2_op<Scalar> > +{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasAbs2 }; }; + +/** \internal + * \brief Template functor to compute the conjugate of a complex value + * + * \sa class CwiseUnaryOp, MatrixBase::conjugate() + */ +template<typename Scalar> struct scalar_conjugate_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_conjugate_op) + EIGEN_DEVICE_FUNC + EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return numext::conj(a); } + template<typename Packet> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const { return internal::pconj(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_conjugate_op<Scalar> > +{ + enum { + Cost = 0, + // Yes the cost is zero even for complexes because in most cases for which + // the cost is used, conjugation turns to be a no-op. Some examples: + // cost(a*conj(b)) == cost(a*b) + // cost(a+conj(b)) == cost(a+b) + // <etc. + // If we don't set it to zero, then: + // A.conjugate().lazyProduct(B.conjugate()) + // will bake its operands. We definitely don't want that! + PacketAccess = packet_traits<Scalar>::HasConj + }; +}; + +/** \internal + * \brief Template functor to compute the phase angle of a complex + * + * \sa class CwiseUnaryOp, Cwise::arg + */ +template<typename Scalar> struct scalar_arg_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_arg_op) + typedef typename NumTraits<Scalar>::Real result_type; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return numext::arg(a); } + template<typename Packet> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const + { return internal::parg(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_arg_op<Scalar> > +{ + enum { + Cost = NumTraits<Scalar>::IsComplex ? 5 * NumTraits<Scalar>::MulCost : NumTraits<Scalar>::AddCost, + PacketAccess = packet_traits<Scalar>::HasArg + }; +}; +/** \internal + * \brief Template functor to cast a scalar to another type + * + * \sa class CwiseUnaryOp, MatrixBase::cast() + */ +template<typename Scalar, typename NewType> +struct scalar_cast_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_cast_op) + typedef NewType result_type; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const NewType operator() (const Scalar& a) const { return cast<Scalar, NewType>(a); } +}; +template<typename Scalar, typename NewType> +struct functor_traits<scalar_cast_op<Scalar,NewType> > +{ enum { Cost = is_same<Scalar, NewType>::value ? 0 : NumTraits<NewType>::AddCost, PacketAccess = false }; }; + +/** \internal + * \brief Template functor to arithmetically shift a scalar right by a number of bits + * + * \sa class CwiseUnaryOp, MatrixBase::shift_right() + */ +template<typename Scalar, int N> +struct scalar_shift_right_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_shift_right_op) + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const + { return a >> N; } + template<typename Packet> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const + { return internal::parithmetic_shift_right<N>(a); } +}; +template<typename Scalar, int N> +struct functor_traits<scalar_shift_right_op<Scalar,N> > +{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasShift }; }; + +/** \internal + * \brief Template functor to logically shift a scalar left by a number of bits + * + * \sa class CwiseUnaryOp, MatrixBase::shift_left() + */ +template<typename Scalar, int N> +struct scalar_shift_left_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_shift_left_op) + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const + { return a << N; } + template<typename Packet> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const + { return internal::plogical_shift_left<N>(a); } +}; +template<typename Scalar, int N> +struct functor_traits<scalar_shift_left_op<Scalar,N> > +{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasShift }; }; + +/** \internal + * \brief Template functor to extract the real part of a complex + * + * \sa class CwiseUnaryOp, MatrixBase::real() + */ +template<typename Scalar> +struct scalar_real_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_real_op) + typedef typename NumTraits<Scalar>::Real result_type; + EIGEN_DEVICE_FUNC + EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return numext::real(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_real_op<Scalar> > +{ enum { Cost = 0, PacketAccess = false }; }; + +/** \internal + * \brief Template functor to extract the imaginary part of a complex + * + * \sa class CwiseUnaryOp, MatrixBase::imag() + */ +template<typename Scalar> +struct scalar_imag_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_op) + typedef typename NumTraits<Scalar>::Real result_type; + EIGEN_DEVICE_FUNC + EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return numext::imag(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_imag_op<Scalar> > +{ enum { Cost = 0, PacketAccess = false }; }; + +/** \internal + * \brief Template functor to extract the real part of a complex as a reference + * + * \sa class CwiseUnaryOp, MatrixBase::real() + */ +template<typename Scalar> +struct scalar_real_ref_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_real_ref_op) + typedef typename NumTraits<Scalar>::Real result_type; + EIGEN_DEVICE_FUNC + EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return numext::real_ref(*const_cast<Scalar*>(&a)); } +}; +template<typename Scalar> +struct functor_traits<scalar_real_ref_op<Scalar> > +{ enum { Cost = 0, PacketAccess = false }; }; + +/** \internal + * \brief Template functor to extract the imaginary part of a complex as a reference + * + * \sa class CwiseUnaryOp, MatrixBase::imag() + */ +template<typename Scalar> +struct scalar_imag_ref_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_ref_op) + typedef typename NumTraits<Scalar>::Real result_type; + EIGEN_DEVICE_FUNC + EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return numext::imag_ref(*const_cast<Scalar*>(&a)); } +}; +template<typename Scalar> +struct functor_traits<scalar_imag_ref_op<Scalar> > +{ enum { Cost = 0, PacketAccess = false }; }; + +/** \internal + * + * \brief Template functor to compute the exponential of a scalar + * + * \sa class CwiseUnaryOp, Cwise::exp() + */ +template<typename Scalar> struct scalar_exp_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_exp_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::exp(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pexp(a); } +}; +template <typename Scalar> +struct functor_traits<scalar_exp_op<Scalar> > { + enum { + PacketAccess = packet_traits<Scalar>::HasExp, + // The following numbers are based on the AVX implementation. +#ifdef EIGEN_VECTORIZE_FMA + // Haswell can issue 2 add/mul/madd per cycle. + Cost = + (sizeof(Scalar) == 4 + // float: 8 pmadd, 4 pmul, 2 padd/psub, 6 other + ? (8 * NumTraits<Scalar>::AddCost + 6 * NumTraits<Scalar>::MulCost) + // double: 7 pmadd, 5 pmul, 3 padd/psub, 1 div, 13 other + : (14 * NumTraits<Scalar>::AddCost + + 6 * NumTraits<Scalar>::MulCost + + scalar_div_cost<Scalar,packet_traits<Scalar>::HasDiv>::value)) +#else + Cost = + (sizeof(Scalar) == 4 + // float: 7 pmadd, 6 pmul, 4 padd/psub, 10 other + ? (21 * NumTraits<Scalar>::AddCost + 13 * NumTraits<Scalar>::MulCost) + // double: 7 pmadd, 5 pmul, 3 padd/psub, 1 div, 13 other + : (23 * NumTraits<Scalar>::AddCost + + 12 * NumTraits<Scalar>::MulCost + + scalar_div_cost<Scalar,packet_traits<Scalar>::HasDiv>::value)) +#endif + }; +}; + +/** \internal + * + * \brief Template functor to compute the exponential of a scalar - 1. + * + * \sa class CwiseUnaryOp, ArrayBase::expm1() + */ +template<typename Scalar> struct scalar_expm1_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_expm1_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::expm1(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pexpm1(a); } +}; +template <typename Scalar> +struct functor_traits<scalar_expm1_op<Scalar> > { + enum { + PacketAccess = packet_traits<Scalar>::HasExpm1, + Cost = functor_traits<scalar_exp_op<Scalar> >::Cost // TODO measure cost of expm1 + }; +}; + +/** \internal + * + * \brief Template functor to compute the logarithm of a scalar + * + * \sa class CwiseUnaryOp, ArrayBase::log() + */ +template<typename Scalar> struct scalar_log_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_log_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::log(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::plog(a); } +}; +template <typename Scalar> +struct functor_traits<scalar_log_op<Scalar> > { + enum { + PacketAccess = packet_traits<Scalar>::HasLog, + Cost = + (PacketAccess + // The following numbers are based on the AVX implementation. +#ifdef EIGEN_VECTORIZE_FMA + // 8 pmadd, 6 pmul, 8 padd/psub, 16 other, can issue 2 add/mul/madd per cycle. + ? (20 * NumTraits<Scalar>::AddCost + 7 * NumTraits<Scalar>::MulCost) +#else + // 8 pmadd, 6 pmul, 8 padd/psub, 20 other + ? (36 * NumTraits<Scalar>::AddCost + 14 * NumTraits<Scalar>::MulCost) +#endif + // Measured cost of std::log. + : sizeof(Scalar)==4 ? 40 : 85) + }; +}; + +/** \internal + * + * \brief Template functor to compute the logarithm of 1 plus a scalar value + * + * \sa class CwiseUnaryOp, ArrayBase::log1p() + */ +template<typename Scalar> struct scalar_log1p_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_log1p_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::log1p(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::plog1p(a); } +}; +template <typename Scalar> +struct functor_traits<scalar_log1p_op<Scalar> > { + enum { + PacketAccess = packet_traits<Scalar>::HasLog1p, + Cost = functor_traits<scalar_log_op<Scalar> >::Cost // TODO measure cost of log1p + }; +}; + +/** \internal + * + * \brief Template functor to compute the base-10 logarithm of a scalar + * + * \sa class CwiseUnaryOp, Cwise::log10() + */ +template<typename Scalar> struct scalar_log10_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_log10_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { EIGEN_USING_STD(log10) return log10(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::plog10(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_log10_op<Scalar> > +{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasLog10 }; }; + +/** \internal + * + * \brief Template functor to compute the base-2 logarithm of a scalar + * + * \sa class CwiseUnaryOp, Cwise::log2() + */ +template<typename Scalar> struct scalar_log2_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_log2_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return Scalar(EIGEN_LOG2E) * numext::log(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::plog2(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_log2_op<Scalar> > +{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasLog }; }; + +/** \internal + * \brief Template functor to compute the square root of a scalar + * \sa class CwiseUnaryOp, Cwise::sqrt() + */ +template<typename Scalar> struct scalar_sqrt_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_sqrt_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::sqrt(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::psqrt(a); } +}; +template <typename Scalar> +struct functor_traits<scalar_sqrt_op<Scalar> > { + enum { +#if EIGEN_FAST_MATH + // The following numbers are based on the AVX implementation. + Cost = (sizeof(Scalar) == 8 ? 28 + // 4 pmul, 1 pmadd, 3 other + : (3 * NumTraits<Scalar>::AddCost + + 5 * NumTraits<Scalar>::MulCost)), +#else + // The following numbers are based on min VSQRT throughput on Haswell. + Cost = (sizeof(Scalar) == 8 ? 28 : 14), +#endif + PacketAccess = packet_traits<Scalar>::HasSqrt + }; +}; + +// Boolean specialization to eliminate -Wimplicit-conversion-floating-point-to-bool warnings. +template<> struct scalar_sqrt_op<bool> { + EIGEN_EMPTY_STRUCT_CTOR(scalar_sqrt_op) + EIGEN_DEPRECATED EIGEN_DEVICE_FUNC inline bool operator() (const bool& a) const { return a; } + template <typename Packet> + EIGEN_DEPRECATED EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return a; } +}; +template <> +struct functor_traits<scalar_sqrt_op<bool> > { + enum { Cost = 1, PacketAccess = packet_traits<bool>::Vectorizable }; +}; + +/** \internal + * \brief Template functor to compute the reciprocal square root of a scalar + * \sa class CwiseUnaryOp, Cwise::rsqrt() + */ +template<typename Scalar> struct scalar_rsqrt_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_rsqrt_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::rsqrt(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::prsqrt(a); } +}; + +template<typename Scalar> +struct functor_traits<scalar_rsqrt_op<Scalar> > +{ enum { + Cost = 5 * NumTraits<Scalar>::MulCost, + PacketAccess = packet_traits<Scalar>::HasRsqrt + }; +}; + +/** \internal + * \brief Template functor to compute the cosine of a scalar + * \sa class CwiseUnaryOp, ArrayBase::cos() + */ +template<typename Scalar> struct scalar_cos_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_cos_op) + EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return numext::cos(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pcos(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_cos_op<Scalar> > +{ + enum { + Cost = 5 * NumTraits<Scalar>::MulCost, + PacketAccess = packet_traits<Scalar>::HasCos + }; +}; + +/** \internal + * \brief Template functor to compute the sine of a scalar + * \sa class CwiseUnaryOp, ArrayBase::sin() + */ +template<typename Scalar> struct scalar_sin_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_sin_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::sin(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::psin(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_sin_op<Scalar> > +{ + enum { + Cost = 5 * NumTraits<Scalar>::MulCost, + PacketAccess = packet_traits<Scalar>::HasSin + }; +}; + + +/** \internal + * \brief Template functor to compute the tan of a scalar + * \sa class CwiseUnaryOp, ArrayBase::tan() + */ +template<typename Scalar> struct scalar_tan_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_tan_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::tan(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::ptan(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_tan_op<Scalar> > +{ + enum { + Cost = 5 * NumTraits<Scalar>::MulCost, + PacketAccess = packet_traits<Scalar>::HasTan + }; +}; + +/** \internal + * \brief Template functor to compute the arc cosine of a scalar + * \sa class CwiseUnaryOp, ArrayBase::acos() + */ +template<typename Scalar> struct scalar_acos_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_acos_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::acos(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pacos(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_acos_op<Scalar> > +{ + enum { + Cost = 5 * NumTraits<Scalar>::MulCost, + PacketAccess = packet_traits<Scalar>::HasACos + }; +}; + +/** \internal + * \brief Template functor to compute the arc sine of a scalar + * \sa class CwiseUnaryOp, ArrayBase::asin() + */ +template<typename Scalar> struct scalar_asin_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_asin_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::asin(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pasin(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_asin_op<Scalar> > +{ + enum { + Cost = 5 * NumTraits<Scalar>::MulCost, + PacketAccess = packet_traits<Scalar>::HasASin + }; +}; + + +/** \internal + * \brief Template functor to compute the atan of a scalar + * \sa class CwiseUnaryOp, ArrayBase::atan() + */ +template<typename Scalar> struct scalar_atan_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_atan_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::atan(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::patan(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_atan_op<Scalar> > +{ + enum { + Cost = 5 * NumTraits<Scalar>::MulCost, + PacketAccess = packet_traits<Scalar>::HasATan + }; +}; + +/** \internal + * \brief Template functor to compute the tanh of a scalar + * \sa class CwiseUnaryOp, ArrayBase::tanh() + */ +template <typename Scalar> +struct scalar_tanh_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_tanh_op) + EIGEN_DEVICE_FUNC inline const Scalar operator()(const Scalar& a) const { return numext::tanh(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& x) const { return ptanh(x); } +}; + +template <typename Scalar> +struct functor_traits<scalar_tanh_op<Scalar> > { + enum { + PacketAccess = packet_traits<Scalar>::HasTanh, + Cost = ( (EIGEN_FAST_MATH && is_same<Scalar,float>::value) +// The following numbers are based on the AVX implementation, +#ifdef EIGEN_VECTORIZE_FMA + // Haswell can issue 2 add/mul/madd per cycle. + // 9 pmadd, 2 pmul, 1 div, 2 other + ? (2 * NumTraits<Scalar>::AddCost + + 6 * NumTraits<Scalar>::MulCost + + scalar_div_cost<Scalar,packet_traits<Scalar>::HasDiv>::value) +#else + ? (11 * NumTraits<Scalar>::AddCost + + 11 * NumTraits<Scalar>::MulCost + + scalar_div_cost<Scalar,packet_traits<Scalar>::HasDiv>::value) +#endif + // This number assumes a naive implementation of tanh + : (6 * NumTraits<Scalar>::AddCost + + 3 * NumTraits<Scalar>::MulCost + + 2 * scalar_div_cost<Scalar,packet_traits<Scalar>::HasDiv>::value + + functor_traits<scalar_exp_op<Scalar> >::Cost)) + }; +}; + +#if EIGEN_HAS_CXX11_MATH +/** \internal + * \brief Template functor to compute the atanh of a scalar + * \sa class CwiseUnaryOp, ArrayBase::atanh() + */ +template <typename Scalar> +struct scalar_atanh_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_atanh_op) + EIGEN_DEVICE_FUNC inline const Scalar operator()(const Scalar& a) const { return numext::atanh(a); } +}; + +template <typename Scalar> +struct functor_traits<scalar_atanh_op<Scalar> > { + enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; +}; +#endif + +/** \internal + * \brief Template functor to compute the sinh of a scalar + * \sa class CwiseUnaryOp, ArrayBase::sinh() + */ +template<typename Scalar> struct scalar_sinh_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_sinh_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::sinh(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::psinh(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_sinh_op<Scalar> > +{ + enum { + Cost = 5 * NumTraits<Scalar>::MulCost, + PacketAccess = packet_traits<Scalar>::HasSinh + }; +}; + +#if EIGEN_HAS_CXX11_MATH +/** \internal + * \brief Template functor to compute the asinh of a scalar + * \sa class CwiseUnaryOp, ArrayBase::asinh() + */ +template <typename Scalar> +struct scalar_asinh_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_asinh_op) + EIGEN_DEVICE_FUNC inline const Scalar operator()(const Scalar& a) const { return numext::asinh(a); } +}; + +template <typename Scalar> +struct functor_traits<scalar_asinh_op<Scalar> > { + enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; +}; +#endif + +/** \internal + * \brief Template functor to compute the cosh of a scalar + * \sa class CwiseUnaryOp, ArrayBase::cosh() + */ +template<typename Scalar> struct scalar_cosh_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_cosh_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { return numext::cosh(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pcosh(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_cosh_op<Scalar> > +{ + enum { + Cost = 5 * NumTraits<Scalar>::MulCost, + PacketAccess = packet_traits<Scalar>::HasCosh + }; +}; + +#if EIGEN_HAS_CXX11_MATH +/** \internal + * \brief Template functor to compute the acosh of a scalar + * \sa class CwiseUnaryOp, ArrayBase::acosh() + */ +template <typename Scalar> +struct scalar_acosh_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_acosh_op) + EIGEN_DEVICE_FUNC inline const Scalar operator()(const Scalar& a) const { return numext::acosh(a); } +}; + +template <typename Scalar> +struct functor_traits<scalar_acosh_op<Scalar> > { + enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; +}; +#endif + +/** \internal + * \brief Template functor to compute the inverse of a scalar + * \sa class CwiseUnaryOp, Cwise::inverse() + */ +template<typename Scalar> +struct scalar_inverse_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_inverse_op) + EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return Scalar(1)/a; } + template<typename Packet> + EIGEN_DEVICE_FUNC inline const Packet packetOp(const Packet& a) const + { return internal::pdiv(pset1<Packet>(Scalar(1)),a); } +}; +template <typename Scalar> +struct functor_traits<scalar_inverse_op<Scalar> > { + enum { + PacketAccess = packet_traits<Scalar>::HasDiv, + Cost = scalar_div_cost<Scalar, PacketAccess>::value + }; +}; + +/** \internal + * \brief Template functor to compute the square of a scalar + * \sa class CwiseUnaryOp, Cwise::square() + */ +template<typename Scalar> +struct scalar_square_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_square_op) + EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return a*a; } + template<typename Packet> + EIGEN_DEVICE_FUNC inline const Packet packetOp(const Packet& a) const + { return internal::pmul(a,a); } +}; +template<typename Scalar> +struct functor_traits<scalar_square_op<Scalar> > +{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; }; + +// Boolean specialization to avoid -Wint-in-bool-context warnings on GCC. +template<> +struct scalar_square_op<bool> { + EIGEN_EMPTY_STRUCT_CTOR(scalar_square_op) + EIGEN_DEPRECATED EIGEN_DEVICE_FUNC inline bool operator() (const bool& a) const { return a; } + template<typename Packet> + EIGEN_DEPRECATED EIGEN_DEVICE_FUNC inline const Packet packetOp(const Packet& a) const + { return a; } +}; +template<> +struct functor_traits<scalar_square_op<bool> > +{ enum { Cost = 0, PacketAccess = packet_traits<bool>::Vectorizable }; }; + +/** \internal + * \brief Template functor to compute the cube of a scalar + * \sa class CwiseUnaryOp, Cwise::cube() + */ +template<typename Scalar> +struct scalar_cube_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_cube_op) + EIGEN_DEVICE_FUNC inline Scalar operator() (const Scalar& a) const { return a*a*a; } + template<typename Packet> + EIGEN_DEVICE_FUNC inline const Packet packetOp(const Packet& a) const + { return internal::pmul(a,pmul(a,a)); } +}; +template<typename Scalar> +struct functor_traits<scalar_cube_op<Scalar> > +{ enum { Cost = 2*NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; }; + +// Boolean specialization to avoid -Wint-in-bool-context warnings on GCC. +template<> +struct scalar_cube_op<bool> { + EIGEN_EMPTY_STRUCT_CTOR(scalar_cube_op) + EIGEN_DEPRECATED EIGEN_DEVICE_FUNC inline bool operator() (const bool& a) const { return a; } + template<typename Packet> + EIGEN_DEPRECATED EIGEN_DEVICE_FUNC inline const Packet packetOp(const Packet& a) const + { return a; } +}; +template<> +struct functor_traits<scalar_cube_op<bool> > +{ enum { Cost = 0, PacketAccess = packet_traits<bool>::Vectorizable }; }; + +/** \internal + * \brief Template functor to compute the rounded value of a scalar + * \sa class CwiseUnaryOp, ArrayBase::round() + */ +template<typename Scalar> struct scalar_round_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_round_op) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return numext::round(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pround(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_round_op<Scalar> > +{ + enum { + Cost = NumTraits<Scalar>::MulCost, + PacketAccess = packet_traits<Scalar>::HasRound + }; +}; + +/** \internal + * \brief Template functor to compute the floor of a scalar + * \sa class CwiseUnaryOp, ArrayBase::floor() + */ +template<typename Scalar> struct scalar_floor_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_floor_op) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return numext::floor(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pfloor(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_floor_op<Scalar> > +{ + enum { + Cost = NumTraits<Scalar>::MulCost, + PacketAccess = packet_traits<Scalar>::HasFloor + }; +}; + +/** \internal + * \brief Template functor to compute the rounded (with current rounding mode) value of a scalar + * \sa class CwiseUnaryOp, ArrayBase::rint() + */ +template<typename Scalar> struct scalar_rint_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_rint_op) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return numext::rint(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::print(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_rint_op<Scalar> > +{ + enum { + Cost = NumTraits<Scalar>::MulCost, + PacketAccess = packet_traits<Scalar>::HasRint + }; +}; + +/** \internal + * \brief Template functor to compute the ceil of a scalar + * \sa class CwiseUnaryOp, ArrayBase::ceil() + */ +template<typename Scalar> struct scalar_ceil_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_ceil_op) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return numext::ceil(a); } + template <typename Packet> + EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::pceil(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_ceil_op<Scalar> > +{ + enum { + Cost = NumTraits<Scalar>::MulCost, + PacketAccess = packet_traits<Scalar>::HasCeil + }; +}; + +/** \internal + * \brief Template functor to compute whether a scalar is NaN + * \sa class CwiseUnaryOp, ArrayBase::isnan() + */ +template<typename Scalar> struct scalar_isnan_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_isnan_op) + typedef bool result_type; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { +#if defined(SYCL_DEVICE_ONLY) + return numext::isnan(a); +#else + return (numext::isnan)(a); +#endif + } +}; +template<typename Scalar> +struct functor_traits<scalar_isnan_op<Scalar> > +{ + enum { + Cost = NumTraits<Scalar>::MulCost, + PacketAccess = false + }; +}; + +/** \internal + * \brief Template functor to check whether a scalar is +/-inf + * \sa class CwiseUnaryOp, ArrayBase::isinf() + */ +template<typename Scalar> struct scalar_isinf_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_isinf_op) + typedef bool result_type; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { +#if defined(SYCL_DEVICE_ONLY) + return numext::isinf(a); +#else + return (numext::isinf)(a); +#endif + } +}; +template<typename Scalar> +struct functor_traits<scalar_isinf_op<Scalar> > +{ + enum { + Cost = NumTraits<Scalar>::MulCost, + PacketAccess = false + }; +}; + +/** \internal + * \brief Template functor to check whether a scalar has a finite value + * \sa class CwiseUnaryOp, ArrayBase::isfinite() + */ +template<typename Scalar> struct scalar_isfinite_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_isfinite_op) + typedef bool result_type; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { +#if defined(SYCL_DEVICE_ONLY) + return numext::isfinite(a); +#else + return (numext::isfinite)(a); +#endif + } +}; +template<typename Scalar> +struct functor_traits<scalar_isfinite_op<Scalar> > +{ + enum { + Cost = NumTraits<Scalar>::MulCost, + PacketAccess = false + }; +}; + +/** \internal + * \brief Template functor to compute the logical not of a boolean + * + * \sa class CwiseUnaryOp, ArrayBase::operator! + */ +template<typename Scalar> struct scalar_boolean_not_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_not_op) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool operator() (const bool& a) const { return !a; } +}; +template<typename Scalar> +struct functor_traits<scalar_boolean_not_op<Scalar> > { + enum { + Cost = NumTraits<bool>::AddCost, + PacketAccess = false + }; +}; + +/** \internal + * \brief Template functor to compute the signum of a scalar + * \sa class CwiseUnaryOp, Cwise::sign() + */ +template<typename Scalar,bool is_complex=(NumTraits<Scalar>::IsComplex!=0), bool is_integer=(NumTraits<Scalar>::IsInteger!=0) > struct scalar_sign_op; +template<typename Scalar> +struct scalar_sign_op<Scalar, false, true> { + EIGEN_EMPTY_STRUCT_CTOR(scalar_sign_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const + { + return Scalar( (a>Scalar(0)) - (a<Scalar(0)) ); + } + //TODO + //template <typename Packet> + //EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::psign(a); } +}; + +template<typename Scalar> +struct scalar_sign_op<Scalar, false, false> { + EIGEN_EMPTY_STRUCT_CTOR(scalar_sign_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const + { + return (numext::isnan)(a) ? a : Scalar( (a>Scalar(0)) - (a<Scalar(0)) ); + } + //TODO + //template <typename Packet> + //EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::psign(a); } +}; + +template<typename Scalar, bool is_integer> +struct scalar_sign_op<Scalar,true, is_integer> { + EIGEN_EMPTY_STRUCT_CTOR(scalar_sign_op) + EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const + { + typedef typename NumTraits<Scalar>::Real real_type; + real_type aa = numext::abs(a); + if (aa==real_type(0)) + return Scalar(0); + aa = real_type(1)/aa; + return Scalar(a.real()*aa, a.imag()*aa ); + } + //TODO + //template <typename Packet> + //EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::psign(a); } +}; +template<typename Scalar> +struct functor_traits<scalar_sign_op<Scalar> > +{ enum { + Cost = + NumTraits<Scalar>::IsComplex + ? ( 8*NumTraits<Scalar>::MulCost ) // roughly + : ( 3*NumTraits<Scalar>::AddCost), + PacketAccess = packet_traits<Scalar>::HasSign + }; +}; + +/** \internal + * \brief Template functor to compute the logistic function of a scalar + * \sa class CwiseUnaryOp, ArrayBase::logistic() + */ +template <typename T> +struct scalar_logistic_op { + EIGEN_EMPTY_STRUCT_CTOR(scalar_logistic_op) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T operator()(const T& x) const { + return packetOp(x); + } + + template <typename Packet> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE + Packet packetOp(const Packet& x) const { + const Packet one = pset1<Packet>(T(1)); + return pdiv(one, padd(one, pexp(pnegate(x)))); + } +}; + +#ifndef EIGEN_GPU_COMPILE_PHASE +/** \internal + * \brief Template specialization of the logistic function for float. + * + * Uses just a 9/10-degree rational interpolant which + * interpolates 1/(1+exp(-x)) - 0.5 up to a couple of ulps in the range + * [-9, 18]. Below -9 we use the more accurate approximation + * 1/(1+exp(-x)) ~= exp(x), and above 18 the logistic function is 1 withing + * one ulp. The shifted logistic is interpolated because it was easier to + * make the fit converge. + * + */ +template <> +struct scalar_logistic_op<float> { + EIGEN_EMPTY_STRUCT_CTOR(scalar_logistic_op) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float operator()(const float& x) const { + return packetOp(x); + } + + template <typename Packet> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE + Packet packetOp(const Packet& _x) const { + const Packet cutoff_lower = pset1<Packet>(-9.f); + const Packet lt_mask = pcmp_lt<Packet>(_x, cutoff_lower); + const bool any_small = predux_any(lt_mask); + + // The upper cut-off is the smallest x for which the rational approximation evaluates to 1. + // Choosing this value saves us a few instructions clamping the results at the end. +#ifdef EIGEN_VECTORIZE_FMA + const Packet cutoff_upper = pset1<Packet>(15.7243833541870117f); +#else + const Packet cutoff_upper = pset1<Packet>(15.6437711715698242f); +#endif + const Packet x = pmin(_x, cutoff_upper); + + // The monomial coefficients of the numerator polynomial (odd). + const Packet alpha_1 = pset1<Packet>(2.48287947061529e-01f); + const Packet alpha_3 = pset1<Packet>(8.51377133304701e-03f); + const Packet alpha_5 = pset1<Packet>(6.08574864600143e-05f); + const Packet alpha_7 = pset1<Packet>(1.15627324459942e-07f); + const Packet alpha_9 = pset1<Packet>(4.37031012579801e-11f); + + // The monomial coefficients of the denominator polynomial (even). + const Packet beta_0 = pset1<Packet>(9.93151921023180e-01f); + const Packet beta_2 = pset1<Packet>(1.16817656904453e-01f); + const Packet beta_4 = pset1<Packet>(1.70198817374094e-03f); + const Packet beta_6 = pset1<Packet>(6.29106785017040e-06f); + const Packet beta_8 = pset1<Packet>(5.76102136993427e-09f); + const Packet beta_10 = pset1<Packet>(6.10247389755681e-13f); + + // Since the polynomials are odd/even, we need x^2. + const Packet x2 = pmul(x, x); + + // Evaluate the numerator polynomial p. + Packet p = pmadd(x2, alpha_9, alpha_7); + p = pmadd(x2, p, alpha_5); + p = pmadd(x2, p, alpha_3); + p = pmadd(x2, p, alpha_1); + p = pmul(x, p); + + // Evaluate the denominator polynomial q. + Packet q = pmadd(x2, beta_10, beta_8); + q = pmadd(x2, q, beta_6); + q = pmadd(x2, q, beta_4); + q = pmadd(x2, q, beta_2); + q = pmadd(x2, q, beta_0); + // Divide the numerator by the denominator and shift it up. + const Packet logistic = padd(pdiv(p, q), pset1<Packet>(0.5f)); + if (EIGEN_PREDICT_FALSE(any_small)) { + const Packet exponential = pexp(_x); + return pselect(lt_mask, exponential, logistic); + } else { + return logistic; + } + } +}; +#endif // #ifndef EIGEN_GPU_COMPILE_PHASE + +template <typename T> +struct functor_traits<scalar_logistic_op<T> > { + enum { + // The cost estimate for float here here is for the common(?) case where + // all arguments are greater than -9. + Cost = scalar_div_cost<T, packet_traits<T>::HasDiv>::value + + (internal::is_same<T, float>::value + ? NumTraits<T>::AddCost * 15 + NumTraits<T>::MulCost * 11 + : NumTraits<T>::AddCost * 2 + + functor_traits<scalar_exp_op<T> >::Cost), + PacketAccess = + packet_traits<T>::HasAdd && packet_traits<T>::HasDiv && + (internal::is_same<T, float>::value + ? packet_traits<T>::HasMul && packet_traits<T>::HasMax && + packet_traits<T>::HasMin + : packet_traits<T>::HasNegate && packet_traits<T>::HasExp) + }; +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_FUNCTORS_H |