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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2016 Eugene Brevdo <ebrevdo@gmail.com>
// Copyright (C) 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_SPECIALFUNCTIONS_FUNCTORS_H
#define EIGEN_SPECIALFUNCTIONS_FUNCTORS_H
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
/** \internal
* \brief Template functor to compute the incomplete gamma function igamma(a, x)
*
* \sa class CwiseBinaryOp, Cwise::igamma
*/
template <typename Scalar>
struct scalar_igamma_op : binary_op_base<Scalar, Scalar> {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& a, const Scalar& x) const {
using numext::igamma;
return igamma(a, x);
}
template <typename Packet>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& x) const {
return internal::pigamma(a, x);
}
};
template <typename Scalar>
struct functor_traits<scalar_igamma_op<Scalar> > {
enum {
// Guesstimate
Cost = 20 * NumTraits<Scalar>::MulCost + 10 * NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasIGamma
};
};
/** \internal
* \brief Template functor to compute the derivative of the incomplete gamma
* function igamma_der_a(a, x)
*
* \sa class CwiseBinaryOp, Cwise::igamma_der_a
*/
template <typename Scalar>
struct scalar_igamma_der_a_op {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& a, const Scalar& x) const {
using numext::igamma_der_a;
return igamma_der_a(a, x);
}
template <typename Packet>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& x) const {
return internal::pigamma_der_a(a, x);
}
};
template <typename Scalar>
struct functor_traits<scalar_igamma_der_a_op<Scalar> > {
enum {
// 2x the cost of igamma
Cost = 40 * NumTraits<Scalar>::MulCost + 20 * NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasIGammaDerA
};
};
/** \internal
* \brief Template functor to compute the derivative of the sample
* of a Gamma(alpha, 1) random variable with respect to the parameter alpha
* gamma_sample_der_alpha(alpha, sample)
*
* \sa class CwiseBinaryOp, Cwise::gamma_sample_der_alpha
*/
template <typename Scalar>
struct scalar_gamma_sample_der_alpha_op {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& alpha, const Scalar& sample) const {
using numext::gamma_sample_der_alpha;
return gamma_sample_der_alpha(alpha, sample);
}
template <typename Packet>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& alpha, const Packet& sample) const {
return internal::pgamma_sample_der_alpha(alpha, sample);
}
};
template <typename Scalar>
struct functor_traits<scalar_gamma_sample_der_alpha_op<Scalar> > {
enum {
// 2x the cost of igamma, minus the lgamma cost (the lgamma cancels out)
Cost = 30 * NumTraits<Scalar>::MulCost + 15 * NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasGammaSampleDerAlpha
};
};
/** \internal
* \brief Template functor to compute the complementary incomplete gamma function igammac(a, x)
*
* \sa class CwiseBinaryOp, Cwise::igammac
*/
template <typename Scalar>
struct scalar_igammac_op : binary_op_base<Scalar, Scalar> {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& a, const Scalar& x) const {
using numext::igammac;
return igammac(a, x);
}
template <typename Packet>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& x) const {
return internal::pigammac(a, x);
}
};
template <typename Scalar>
struct functor_traits<scalar_igammac_op<Scalar> > {
enum {
// Guesstimate
Cost = 20 * NumTraits<Scalar>::MulCost + 10 * NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasIGammac
};
};
/** \internal
* \brief Template functor to compute the incomplete beta integral betainc(a, b, x)
*
*/
template <typename Scalar>
struct scalar_betainc_op {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& x, const Scalar& a,
const Scalar& b) const {
using numext::betainc;
return betainc(x, a, b);
}
template <typename Packet>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet packetOp(const Packet& x, const Packet& a, const Packet& b) const {
return internal::pbetainc(x, a, b);
}
};
template <typename Scalar>
struct functor_traits<scalar_betainc_op<Scalar> > {
enum {
// Guesstimate
Cost = 400 * NumTraits<Scalar>::MulCost + 400 * NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasBetaInc
};
};
/** \internal
* \brief Template functor to compute the natural log of the absolute
* value of Gamma of a scalar
* \sa class CwiseUnaryOp, Cwise::lgamma()
*/
template <typename Scalar>
struct scalar_lgamma_op {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& a) const {
using numext::lgamma;
return lgamma(a);
}
typedef typename packet_traits<Scalar>::type Packet;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a) const { return internal::plgamma(a); }
};
template <typename Scalar>
struct functor_traits<scalar_lgamma_op<Scalar> > {
enum {
// Guesstimate
Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasLGamma
};
};
/** \internal
* \brief Template functor to compute psi, the derivative of lgamma of a scalar.
* \sa class CwiseUnaryOp, Cwise::digamma()
*/
template <typename Scalar>
struct scalar_digamma_op {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& a) const {
using numext::digamma;
return digamma(a);
}
typedef typename packet_traits<Scalar>::type Packet;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a) const { return internal::pdigamma(a); }
};
template <typename Scalar>
struct functor_traits<scalar_digamma_op<Scalar> > {
enum {
// Guesstimate
Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasDiGamma
};
};
/** \internal
* \brief Template functor to compute the Riemann Zeta function of two arguments.
* \sa class CwiseUnaryOp, Cwise::zeta()
*/
template <typename Scalar>
struct scalar_zeta_op {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& x, const Scalar& q) const {
using numext::zeta;
return zeta(x, q);
}
typedef typename packet_traits<Scalar>::type Packet;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& x, const Packet& q) const {
return internal::pzeta(x, q);
}
};
template <typename Scalar>
struct functor_traits<scalar_zeta_op<Scalar> > {
enum {
// Guesstimate
Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasZeta
};
};
/** \internal
* \brief Template functor to compute the polygamma function.
* \sa class CwiseUnaryOp, Cwise::polygamma()
*/
template <typename Scalar>
struct scalar_polygamma_op {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& n, const Scalar& x) const {
using numext::polygamma;
return polygamma(n, x);
}
typedef typename packet_traits<Scalar>::type Packet;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& n, const Packet& x) const {
return internal::ppolygamma(n, x);
}
};
template <typename Scalar>
struct functor_traits<scalar_polygamma_op<Scalar> > {
enum {
// Guesstimate
Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasPolygamma
};
};
/** \internal
* \brief Template functor to compute the error function of a scalar
* \sa class CwiseUnaryOp, ArrayBase::erf()
*/
template <typename Scalar>
struct scalar_erf_op {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& a) const { return numext::erf(a); }
template <typename Packet>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& x) const {
return perf(x);
}
};
template <typename Scalar>
struct functor_traits<scalar_erf_op<Scalar> > {
enum {
PacketAccess = packet_traits<Scalar>::HasErf,
Cost = (PacketAccess
#ifdef EIGEN_VECTORIZE_FMA
// TODO(rmlarsen): Move the FMA cost model to a central location.
// Haswell can issue 2 add/mul/madd per cycle.
// 10 pmadd, 2 pmul, 1 div, 2 other
? (2 * NumTraits<Scalar>::AddCost + 7 * NumTraits<Scalar>::MulCost +
scalar_div_cost<Scalar, packet_traits<Scalar>::HasDiv>::value)
#else
? (12 * NumTraits<Scalar>::AddCost + 12 * NumTraits<Scalar>::MulCost +
scalar_div_cost<Scalar, packet_traits<Scalar>::HasDiv>::value)
#endif
// Assume for simplicity that this is as expensive as an exp().
: (functor_traits<scalar_exp_op<Scalar> >::Cost))
};
};
/** \internal
* \brief Template functor to compute the Complementary Error Function
* of a scalar
* \sa class CwiseUnaryOp, Cwise::erfc()
*/
template <typename Scalar>
struct scalar_erfc_op {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& a) const {
using numext::erfc;
return erfc(a);
}
typedef typename packet_traits<Scalar>::type Packet;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a) const { return internal::perfc(a); }
};
template <typename Scalar>
struct functor_traits<scalar_erfc_op<Scalar> > {
enum {
// Guesstimate
Cost = 10 * NumTraits<Scalar>::MulCost + 5 * NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasErfc
};
};
/** \internal
* \brief Template functor to compute the Inverse of the normal distribution
* function of a scalar
* \sa class CwiseUnaryOp, Cwise::ndtri()
*/
template <typename Scalar>
struct scalar_ndtri_op {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(const Scalar& a) const {
using numext::ndtri;
return ndtri(a);
}
typedef typename packet_traits<Scalar>::type Packet;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a) const { return internal::pndtri(a); }
};
template <typename Scalar>
struct functor_traits<scalar_ndtri_op<Scalar> > {
enum {
// On average, We are evaluating rational functions with degree N=9 in the
// numerator and denominator. This results in 2*N additions and 2*N
// multiplications.
Cost = 18 * NumTraits<Scalar>::MulCost + 18 * NumTraits<Scalar>::AddCost,
PacketAccess = packet_traits<Scalar>::HasNdtri
};
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_SPECIALFUNCTIONS_FUNCTORS_H