Eigen/src/Core/functors/BinaryFunctors.h

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2010 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/.
// SPDX-License-Identifier: MPL-2.0

#ifndef EIGEN_BINARY_FUNCTORS_H
#define EIGEN_BINARY_FUNCTORS_H

// IWYU pragma: private
#include "../InternalHeaderCheck.h"

namespace Eigen {

namespace internal {

//---------- associative binary functors ----------

template <typename Arg1, typename Arg2>
struct binary_op_base {
  using first_argument_type = Arg1;
  using second_argument_type = Arg2;
};

/** \internal
 * \brief Template functor to compute the sum of two scalars
 *
 * \sa class CwiseBinaryOp, MatrixBase::operator+, class VectorwiseOp, DenseBase::sum()
 */
template <typename LhsScalar, typename RhsScalar>
struct scalar_sum_op : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = typename ScalarBinaryOpTraits<LhsScalar, RhsScalar, scalar_sum_op>::ReturnType;
#ifdef EIGEN_SCALAR_BINARY_OP_PLUGIN
  scalar_sum_op(){EIGEN_SCALAR_BINARY_OP_PLUGIN}
#endif
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type
  operator()(const LhsScalar& a, const RhsScalar& b) const {
    return a + b;
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    return internal::padd(a, b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type predux(const Packet& a) const {
    return internal::predux(a);
  }
};
template <typename LhsScalar, typename RhsScalar>
struct functor_traits<scalar_sum_op<LhsScalar, RhsScalar>> {
  enum {
    Cost = (int(NumTraits<LhsScalar>::AddCost) + int(NumTraits<RhsScalar>::AddCost)) / 2,  // rough estimate!
    PacketAccess = std::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasAdd &&
                   packet_traits<RhsScalar>::HasAdd
    // TODO: vectorize mixed sum
  };
};

// Addition commutes for arithmetic and complex scalars. A user-defined Scalar may define a
// non-commutative operator+ (e.g. concatenation), so it keeps the order-preserving default.
template <typename Scalar>
struct functor_is_commutative<scalar_sum_op<Scalar, Scalar>>
    : bool_constant<is_arithmetic<Scalar>::value || NumTraits<Scalar>::IsComplex> {};

template <>
EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE bool scalar_sum_op<bool, bool>::operator()(const bool& a,
                                                                                           const bool& b) const {
  return a | b;
}

/** \internal
 * \brief Template functor to compute the product of two scalars
 *
 * \sa class CwiseBinaryOp, Cwise::operator*(), class VectorwiseOp, MatrixBase::redux()
 */
template <typename LhsScalar, typename RhsScalar>
struct scalar_product_op : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = typename ScalarBinaryOpTraits<LhsScalar, RhsScalar, scalar_product_op>::ReturnType;
#ifdef EIGEN_SCALAR_BINARY_OP_PLUGIN
  scalar_product_op(){EIGEN_SCALAR_BINARY_OP_PLUGIN}
#endif
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type
  operator()(const LhsScalar& a, const RhsScalar& b) const {
    return internal::mul(a, b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    return internal::pmul(a, b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type predux(const Packet& a) const {
    return internal::predux_mul(a);
  }
};
template <typename LhsScalar, typename RhsScalar>
struct functor_traits<scalar_product_op<LhsScalar, RhsScalar>> {
  enum {
    Cost = (int(NumTraits<LhsScalar>::MulCost) + int(NumTraits<RhsScalar>::MulCost)) / 2,  // rough estimate!
    PacketAccess = std::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasMul &&
                   packet_traits<RhsScalar>::HasMul
    // TODO: vectorize mixed product
  };
};

// Multiplication commutes for arithmetic and complex scalars, but not for every user-defined
// Scalar (e.g. quaternion-like or matrix-like types).
template <typename Scalar>
struct functor_is_commutative<scalar_product_op<Scalar, Scalar>>
    : bool_constant<is_arithmetic<Scalar>::value || NumTraits<Scalar>::IsComplex> {};

// Same as scalar_product_op, but its scalar path uses pmul instead of operator*. For complex scalars
// pmul is Eigen's explicit (non-Annex-G) complex multiply, so this avoids std::complex::operator*,
// which GCC lowers to the slow libgcc __mul?c3 call. The packet path (packetOp/predux) is inherited
// unchanged -- it already uses pmul -- so the vectorized reduction and its precision are identical to
// scalar_product_op (this only matters for the non-vectorized scalar tail). Used by the coeff-based
// product's coeff(); pmul requires matching operand types, so mixed types fall back to operator*
// (which is cheap for real*complex and never hits the complex*complex libcall).
template <typename LhsScalar, typename RhsScalar>
struct fast_mult_op : scalar_product_op<LhsScalar, RhsScalar> {
  using result_type = typename scalar_product_op<LhsScalar, RhsScalar>::result_type;
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type operator()(const LhsScalar& a, const RhsScalar& b) const {
    return mul(a, b, bool_constant<std::is_same<LhsScalar, RhsScalar>::value>());
  }

 private:
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type mul(const LhsScalar& a, const RhsScalar& b, std::true_type) const {
    return pmul(a, b);
  }
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type mul(const LhsScalar& a, const RhsScalar& b, std::false_type) const {
    return a * b;
  }
};
template <typename LhsScalar, typename RhsScalar>
struct functor_traits<fast_mult_op<LhsScalar, RhsScalar>> : functor_traits<scalar_product_op<LhsScalar, RhsScalar>> {};

template <>
EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE bool scalar_product_op<bool, bool>::operator()(const bool& a,
                                                                                               const bool& b) const {
  return a & b;
}

/** \internal
 * \brief Template functor to compute the conjugate product of two scalars
 *
 * This is a short cut for conj(x) * y which is needed for optimization purpose; in Eigen2 support mode, this becomes x
 * * conj(y)
 */
template <typename LhsScalar, typename RhsScalar>
struct scalar_conj_product_op : binary_op_base<LhsScalar, RhsScalar> {
  enum { Conj = NumTraits<LhsScalar>::IsComplex };

  using result_type = typename ScalarBinaryOpTraits<LhsScalar, RhsScalar, scalar_conj_product_op>::ReturnType;

  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type operator()(const LhsScalar& a, const RhsScalar& b) const {
    return conj_helper<LhsScalar, RhsScalar, Conj, false>().pmul(a, b);
  }

  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    return conj_helper<Packet, Packet, Conj, false>().pmul(a, b);
  }
};
template <typename LhsScalar, typename RhsScalar>
struct functor_traits<scalar_conj_product_op<LhsScalar, RhsScalar>> {
  enum {
    Cost = NumTraits<LhsScalar>::MulCost,
    PacketAccess = std::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasMul
  };
};

/** \internal
 * \brief Template functor to compute the min of two scalars
 *
 * \sa class CwiseBinaryOp, MatrixBase::cwiseMin, class VectorwiseOp, MatrixBase::minCoeff()
 */
template <typename LhsScalar, typename RhsScalar, int NaNPropagation>
struct scalar_min_op : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = typename ScalarBinaryOpTraits<LhsScalar, RhsScalar, scalar_min_op>::ReturnType;
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type operator()(const LhsScalar& a, const RhsScalar& b) const {
    return internal::pmin<NaNPropagation>(a, b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    return internal::pmin<NaNPropagation>(a, b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type predux(const Packet& a) const {
    return internal::predux_min<NaNPropagation>(a);
  }
};

template <typename LhsScalar, typename RhsScalar, int NaNPropagation>
struct functor_traits<scalar_min_op<LhsScalar, RhsScalar, NaNPropagation>> {
  enum {
    Cost = (NumTraits<LhsScalar>::AddCost + NumTraits<RhsScalar>::AddCost) / 2,
    PacketAccess = std::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasMin
  };
};

// min/max commute for arithmetic scalars only: PropagateNumbers and PropagateNaN treat NaN
// operands symmetrically, PropagateFast leaves NaN results unspecified, and -0.0/+0.0 ties may
// already resolve either way in the packet reduction paths. A custom scalar is excluded even
// though it compares with operator<, because the generic std::min/std::max keep the first
// operand when values compare equivalent, and equivalent custom values may be observably
// distinct (e.g. carry a payload the comparison ignores).
template <typename Scalar, int NaNPropagation>
struct functor_is_commutative<scalar_min_op<Scalar, Scalar, NaNPropagation>> : is_arithmetic<Scalar> {};

/** \internal
 * \brief Template functor to compute the max of two scalars
 *
 * \sa class CwiseBinaryOp, MatrixBase::cwiseMax, class VectorwiseOp, MatrixBase::maxCoeff()
 */
template <typename LhsScalar, typename RhsScalar, int NaNPropagation>
struct scalar_max_op : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = typename ScalarBinaryOpTraits<LhsScalar, RhsScalar, scalar_max_op>::ReturnType;
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type operator()(const LhsScalar& a, const RhsScalar& b) const {
    return internal::pmax<NaNPropagation>(a, b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    return internal::pmax<NaNPropagation>(a, b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type predux(const Packet& a) const {
    return internal::predux_max<NaNPropagation>(a);
  }
};

template <typename LhsScalar, typename RhsScalar, int NaNPropagation>
struct functor_traits<scalar_max_op<LhsScalar, RhsScalar, NaNPropagation>> {
  enum {
    Cost = (NumTraits<LhsScalar>::AddCost + NumTraits<RhsScalar>::AddCost) / 2,
    PacketAccess = std::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasMax
  };
};

template <typename Scalar, int NaNPropagation>
struct functor_is_commutative<scalar_max_op<Scalar, Scalar, NaNPropagation>> : is_arithmetic<Scalar> {};

/** \internal
 * \brief Template functors for comparison of two scalars
 * \todo Implement packet-comparisons
 */
template <typename LhsScalar, typename RhsScalar, ComparisonName cmp, bool UseTypedComparators = false>
struct scalar_cmp_op;

template <typename LhsScalar, typename RhsScalar, ComparisonName cmp, bool UseTypedComparators>
struct functor_traits<scalar_cmp_op<LhsScalar, RhsScalar, cmp, UseTypedComparators>> {
  enum {
    Cost = (NumTraits<LhsScalar>::AddCost + NumTraits<RhsScalar>::AddCost) / 2,
    PacketAccess = (UseTypedComparators || std::is_same<LhsScalar, bool>::value) &&
                   std::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasCmp
  };
};

template <typename LhsScalar, typename RhsScalar, bool UseTypedComparators>
struct scalar_cmp_op<LhsScalar, RhsScalar, cmp_EQ, UseTypedComparators> : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = std::conditional_t<UseTypedComparators, LhsScalar, bool>;
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type operator()(const LhsScalar& a, const RhsScalar& b) const {
    return result_type(a == b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    const Packet cst_one = pset1<Packet>(result_type(true));
    return pand(pcmp_eq(a, b), cst_one);
  }
};

template <typename LhsScalar, typename RhsScalar, bool UseTypedComparators>
struct scalar_cmp_op<LhsScalar, RhsScalar, cmp_LT, UseTypedComparators> : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = std::conditional_t<UseTypedComparators, LhsScalar, bool>;
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type operator()(const LhsScalar& a, const RhsScalar& b) const {
    return result_type(a < b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    const Packet cst_one = pset1<Packet>(result_type(true));
    return pand(pcmp_lt(a, b), cst_one);
  }
};

template <typename LhsScalar, typename RhsScalar, bool UseTypedComparators>
struct scalar_cmp_op<LhsScalar, RhsScalar, cmp_LE, UseTypedComparators> : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = std::conditional_t<UseTypedComparators, LhsScalar, bool>;
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type operator()(const LhsScalar& a, const RhsScalar& b) const {
    return result_type(a <= b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    const Packet cst_one = pset1<Packet>(result_type(true));
    return pand(cst_one, pcmp_le(a, b));
  }
};

template <typename LhsScalar, typename RhsScalar, bool UseTypedComparators>
struct scalar_cmp_op<LhsScalar, RhsScalar, cmp_GT, UseTypedComparators> : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = std::conditional_t<UseTypedComparators, LhsScalar, bool>;
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type operator()(const LhsScalar& a, const RhsScalar& b) const {
    return result_type(a > b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    const Packet cst_one = pset1<Packet>(result_type(true));
    return pand(cst_one, pcmp_lt(b, a));
  }
};

template <typename LhsScalar, typename RhsScalar, bool UseTypedComparators>
struct scalar_cmp_op<LhsScalar, RhsScalar, cmp_GE, UseTypedComparators> : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = std::conditional_t<UseTypedComparators, LhsScalar, bool>;
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type operator()(const LhsScalar& a, const RhsScalar& b) const {
    return result_type(a >= b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    const Packet cst_one = pset1<Packet>(result_type(true));
    return pand(cst_one, pcmp_le(b, a));
  }
};

template <typename LhsScalar, typename RhsScalar, bool UseTypedComparators>
struct scalar_cmp_op<LhsScalar, RhsScalar, cmp_UNORD, UseTypedComparators> : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = std::conditional_t<UseTypedComparators, LhsScalar, bool>;
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type operator()(const LhsScalar& a, const RhsScalar& b) const {
    return result_type(!(a <= b || b <= a));
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    const Packet cst_one = pset1<Packet>(result_type(true));
    return pandnot(cst_one, por(pcmp_le(a, b), pcmp_le(b, a)));
  }
};

template <typename LhsScalar, typename RhsScalar, bool UseTypedComparators>
struct scalar_cmp_op<LhsScalar, RhsScalar, cmp_NEQ, UseTypedComparators> : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = std::conditional_t<UseTypedComparators, LhsScalar, bool>;
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type operator()(const LhsScalar& a, const RhsScalar& b) const {
    return result_type(a != b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    const Packet cst_one = pset1<Packet>(result_type(true));
    return pandnot(cst_one, pcmp_eq(a, b));
  }
};

/** \internal
 * \brief Template functor to compute the hypot of two \b positive \b and \b real scalars
 *
 * \sa MatrixBase::stableNorm(), class Redux
 */
template <typename Scalar>
struct scalar_hypot_op<Scalar, Scalar> : binary_op_base<Scalar, Scalar> {
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar operator()(const Scalar& x, const Scalar& y) const {
    // This functor is used by hypotNorm only for which it is faster to first apply abs
    // on all coefficients prior to reduction through hypot.
    // This way we avoid calling abs on positive and real entries, and this also permits
    // to seamlessly handle complexes. Otherwise we would have to handle both real and complexes
    // through the same functor...
    return internal::positive_real_hypot(x, y);
  }
};
template <typename Scalar>
struct functor_traits<scalar_hypot_op<Scalar, Scalar>> {
  enum {
    Cost = 3 * NumTraits<Scalar>::AddCost + 2 * NumTraits<Scalar>::MulCost + 2 * scalar_div_cost<Scalar, false>::value,
    PacketAccess = false
  };
};

/** \internal
 * \brief Template functor to compute the pow of two scalars
 * See the specification of pow in https://en.cppreference.com/w/cpp/numeric/math/pow
 */
template <typename Scalar, typename Exponent>
struct scalar_pow_op : binary_op_base<Scalar, Exponent> {
  using result_type = typename ScalarBinaryOpTraits<Scalar, Exponent, scalar_pow_op>::ReturnType;
#ifdef EIGEN_SCALAR_BINARY_OP_PLUGIN
  scalar_pow_op() {
    using LhsScalar = Scalar;
    using RhsScalar = Exponent;
    EIGEN_SCALAR_BINARY_OP_PLUGIN
  }
#endif

  EIGEN_DEVICE_FUNC constexpr inline result_type operator()(const Scalar& a, const Exponent& b) const {
    return numext::pow(a, b);
  }

  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    return generic_pow(a, b);
  }
};

template <typename Scalar, typename Exponent>
struct functor_traits<scalar_pow_op<Scalar, Exponent>> {
  enum {
    Cost = 5 * NumTraits<Scalar>::MulCost,
    PacketAccess = (!NumTraits<Scalar>::IsComplex && !NumTraits<Scalar>::IsInteger && packet_traits<Scalar>::HasPow)
  };
};

//---------- non associative binary functors ----------

/** \internal
 * \brief Template functor to compute the difference of two scalars
 *
 * \sa class CwiseBinaryOp, MatrixBase::operator-
 */
template <typename LhsScalar, typename RhsScalar>
struct scalar_difference_op : binary_op_base<LhsScalar, RhsScalar> {
  EIGEN_STATIC_ASSERT((!std::is_same<LhsScalar, bool>::value || !std::is_same<RhsScalar, bool>::value),
                      BOOLEAN_SUBTRACTION_IS_NOT_SUPPORTED__CAST_TO_A_SIGNED_INTEGER_TYPE)
  using result_type = typename ScalarBinaryOpTraits<LhsScalar, RhsScalar, scalar_difference_op>::ReturnType;
#ifdef EIGEN_SCALAR_BINARY_OP_PLUGIN
  scalar_difference_op(){EIGEN_SCALAR_BINARY_OP_PLUGIN}
#endif
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type
  operator()(const LhsScalar& a, const RhsScalar& b) const {
    return a - b;
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    return internal::psub(a, b);
  }
};
template <typename LhsScalar, typename RhsScalar>
struct functor_traits<scalar_difference_op<LhsScalar, RhsScalar>> {
  enum {
    Cost = (int(NumTraits<LhsScalar>::AddCost) + int(NumTraits<RhsScalar>::AddCost)) / 2,
    PacketAccess = std::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasSub &&
                   packet_traits<RhsScalar>::HasSub
  };
};

template <typename Packet, bool IsInteger = NumTraits<typename unpacket_traits<Packet>::type>::IsInteger>
struct maybe_raise_div_by_zero {
  static EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE void run(Packet x) { EIGEN_UNUSED_VARIABLE(x); }
};

#ifndef EIGEN_GPU_COMPILE_PHASE
template <typename Packet>
struct maybe_raise_div_by_zero<Packet, true> {
  static EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE void run(Packet x) {
    if (EIGEN_PREDICT_FALSE(predux_any(pcmp_eq(x, pzero(x))))) {
      // Use volatile variables to force a division by zero, which will
      // result in the default platform behaviour (usually SIGFPE).
      volatile typename unpacket_traits<Packet>::type zero = 0;
      volatile typename unpacket_traits<Packet>::type val = 1;
      val = val / zero;
    }
  }
};
#endif

/** \internal
 * \brief Template functor to compute the quotient of two scalars
 *
 * \sa class CwiseBinaryOp, Cwise::operator/()
 */
template <typename LhsScalar, typename RhsScalar>
struct scalar_quotient_op : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = typename ScalarBinaryOpTraits<LhsScalar, RhsScalar, scalar_quotient_op>::ReturnType;
#ifdef EIGEN_SCALAR_BINARY_OP_PLUGIN
  scalar_quotient_op(){EIGEN_SCALAR_BINARY_OP_PLUGIN}
#endif
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type
  operator()(const LhsScalar& a, const RhsScalar& b) const {
    return numext::divide(a, b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    return internal::pdiv(a, b);
  }
};
template <typename LhsScalar, typename RhsScalar>
struct functor_traits<scalar_quotient_op<LhsScalar, RhsScalar>> {
  using result_type = typename scalar_quotient_op<LhsScalar, RhsScalar>::result_type;
  enum {
    PacketAccess = std::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasDiv &&
                   packet_traits<RhsScalar>::HasDiv,
    Cost = scalar_div_cost<result_type, PacketAccess>::value
  };
};

// Packet16b is currently Eigen's only Boolean packet. Its loads contain valid bool objects, and its casts,
// comparisons, and Boolean packet operations canonicalize every lane to 0 or 1. The direct bitwise fast paths below
// rely on this invariant.

/** \internal
 * \brief Template functor to compute the modulus of two integer scalars
 *
 * \sa class CwiseBinaryOp, ArrayBase::operator%()
 */
template <typename LhsScalar, typename RhsScalar>
struct scalar_modulus_op : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = typename ScalarBinaryOpTraits<LhsScalar, RhsScalar, scalar_modulus_op>::ReturnType;
  static constexpr bool Enable = std::is_same<LhsScalar, RhsScalar>::value && NumTraits<LhsScalar>::IsInteger;
  EIGEN_STATIC_ASSERT(Enable, "LhsScalar and RhsScalar must be the same integer type")
#ifdef EIGEN_SCALAR_BINARY_OP_PLUGIN
  scalar_modulus_op(){EIGEN_SCALAR_BINARY_OP_PLUGIN}
#endif
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type
  operator()(const LhsScalar& a, const RhsScalar& b) const {
    return a % b;
  }
};
template <typename LhsScalar, typename RhsScalar>
struct functor_traits<scalar_modulus_op<LhsScalar, RhsScalar>> {
  using result_type = typename scalar_modulus_op<LhsScalar, RhsScalar>::result_type;
  static constexpr bool PacketAccess = false;
  static constexpr int Cost = scalar_div_cost<result_type, false>::value;
};

/** \internal
 * \brief Template functor to compute the and of two scalars as if they were booleans
 *
 * \sa class CwiseBinaryOp, ArrayBase::operator&&
 */
template <typename Scalar>
struct scalar_boolean_and_op {
  using result_type = Scalar;
  // `false` any value `a` that satisfies `a == Scalar(0)`
  // `true` is the complement of `false`
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar operator()(const Scalar& a, const Scalar& b) const {
    return Scalar((a != Scalar(0)) && (b != Scalar(0)));
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    EIGEN_IF_CONSTEXPR ((std::is_same<Scalar, bool>::value)) {
      return pand(a, b);
    } else {
      const Packet cst_one = pset1<Packet>(Scalar(true));
      // and(a,b) == !or(!a,!b)
      Packet not_a = pcmp_eq(a, pzero(a));
      Packet not_b = pcmp_eq(b, pzero(b));
      Packet a_nand_b = por(not_a, not_b);
      return pandnot(cst_one, a_nand_b);
    }
  }
};
// Keep bool logical functors eager so scalar evaluator loops remain branch-free.
template <>
EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE bool scalar_boolean_and_op<bool>::operator()(const bool& a,
                                                                                             const bool& b) const {
  return a & b;
}
template <typename Scalar>
struct functor_traits<scalar_boolean_and_op<Scalar>> {
  enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasCmp };
};

/** \internal
 * \brief Template functor to compute the or of two scalars as if they were booleans
 *
 * \sa class CwiseBinaryOp, ArrayBase::operator||
 */
template <typename Scalar>
struct scalar_boolean_or_op {
  using result_type = Scalar;
  // `false` any value `a` that satisfies `a == Scalar(0)`
  // `true` is the complement of `false`
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar operator()(const Scalar& a, const Scalar& b) const {
    return Scalar((a != Scalar(0)) || (b != Scalar(0)));
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    EIGEN_IF_CONSTEXPR ((std::is_same<Scalar, bool>::value)) {
      return por(a, b);
    } else {
      const Packet cst_one = pset1<Packet>(Scalar(true));
      // if or(a,b) == 0, then a == 0 and b == 0
      // or(a,b) == !nor(a,b)
      Packet a_nor_b = pcmp_eq(por(a, b), pzero(a));
      return pandnot(cst_one, a_nor_b);
    }
  }
};
template <>
EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE bool scalar_boolean_or_op<bool>::operator()(const bool& a,
                                                                                            const bool& b) const {
  return a | b;
}
template <typename Scalar>
struct functor_traits<scalar_boolean_or_op<Scalar>> {
  enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasCmp };
};

/** \internal
 * \brief Template functor to compute the xor of two scalars as if they were booleans
 *
 * \sa class CwiseBinaryOp, ArrayBase::operator^
 */
template <typename Scalar>
struct scalar_boolean_xor_op {
  using result_type = Scalar;
  // `false` any value `a` that satisfies `a == Scalar(0)`
  // `true` is the complement of `false`
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar operator()(const Scalar& a, const Scalar& b) const {
    return Scalar((a != Scalar(0)) != (b != Scalar(0)));
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    EIGEN_IF_CONSTEXPR ((std::is_same<Scalar, bool>::value)) {
      return pxor(a, b);
    } else {
      const Packet cst_one = pset1<Packet>(Scalar(true));
      // xor(a,b) == xor(!a,!b)
      Packet not_a = pcmp_eq(a, pzero(a));
      Packet not_b = pcmp_eq(b, pzero(b));
      Packet a_xor_b = pxor(not_a, not_b);
      return pand(cst_one, a_xor_b);
    }
  }
};
template <typename Scalar>
struct functor_traits<scalar_boolean_xor_op<Scalar>> {
  enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = packet_traits<Scalar>::HasCmp };
};

template <typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex>
struct bitwise_binary_impl {
  static constexpr size_t Size = sizeof(Scalar);
  using uint_t = typename numext::get_integer_by_size<Size>::unsigned_type;
  static EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar run_and(const Scalar& a, const Scalar& b) {
    uint_t a_as_uint = numext::bit_cast<uint_t, Scalar>(a);
    uint_t b_as_uint = numext::bit_cast<uint_t, Scalar>(b);
    uint_t result = a_as_uint & b_as_uint;
    return numext::bit_cast<Scalar, uint_t>(result);
  }
  static EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar run_or(const Scalar& a, const Scalar& b) {
    uint_t a_as_uint = numext::bit_cast<uint_t, Scalar>(a);
    uint_t b_as_uint = numext::bit_cast<uint_t, Scalar>(b);
    uint_t result = a_as_uint | b_as_uint;
    return numext::bit_cast<Scalar, uint_t>(result);
  }
  static EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar run_xor(const Scalar& a, const Scalar& b) {
    uint_t a_as_uint = numext::bit_cast<uint_t, Scalar>(a);
    uint_t b_as_uint = numext::bit_cast<uint_t, Scalar>(b);
    uint_t result = a_as_uint ^ b_as_uint;
    return numext::bit_cast<Scalar, uint_t>(result);
  }
};

template <typename Scalar>
struct bitwise_binary_impl<Scalar, true> {
  using Real = typename NumTraits<Scalar>::Real;
  static EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar run_and(const Scalar& a, const Scalar& b) {
    Real real_result = bitwise_binary_impl<Real>::run_and(numext::real(a), numext::real(b));
    Real imag_result = bitwise_binary_impl<Real>::run_and(numext::imag(a), numext::imag(b));
    return Scalar(real_result, imag_result);
  }
  static EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar run_or(const Scalar& a, const Scalar& b) {
    Real real_result = bitwise_binary_impl<Real>::run_or(numext::real(a), numext::real(b));
    Real imag_result = bitwise_binary_impl<Real>::run_or(numext::imag(a), numext::imag(b));
    return Scalar(real_result, imag_result);
  }
  static EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar run_xor(const Scalar& a, const Scalar& b) {
    Real real_result = bitwise_binary_impl<Real>::run_xor(numext::real(a), numext::real(b));
    Real imag_result = bitwise_binary_impl<Real>::run_xor(numext::imag(a), numext::imag(b));
    return Scalar(real_result, imag_result);
  }
};

/** \internal
 * \brief Template functor to compute the bitwise and of two scalars
 *
 * \sa class CwiseBinaryOp, ArrayBase::operator&
 */
template <typename Scalar>
struct scalar_bitwise_and_op {
  EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::RequireInitialization,
                      BITWISE OPERATIONS MAY ONLY BE PERFORMED ON PLAIN DATA TYPES)
  EIGEN_STATIC_ASSERT((!std::is_same<Scalar, bool>::value), DONT USE BITWISE OPS ON BOOLEAN TYPES)
  using result_type = Scalar;
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar operator()(const Scalar& a, const Scalar& b) const {
    return bitwise_binary_impl<Scalar>::run_and(a, b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    return pand(a, b);
  }
};
template <typename Scalar>
struct functor_traits<scalar_bitwise_and_op<Scalar>> {
  enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = true };
};

/** \internal
 * \brief Template functor to compute the bitwise or of two scalars
 *
 * \sa class CwiseBinaryOp, ArrayBase::operator|
 */
template <typename Scalar>
struct scalar_bitwise_or_op {
  EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::RequireInitialization,
                      BITWISE OPERATIONS MAY ONLY BE PERFORMED ON PLAIN DATA TYPES)
  EIGEN_STATIC_ASSERT((!std::is_same<Scalar, bool>::value), DONT USE BITWISE OPS ON BOOLEAN TYPES)
  using result_type = Scalar;
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar operator()(const Scalar& a, const Scalar& b) const {
    return bitwise_binary_impl<Scalar>::run_or(a, b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    return por(a, b);
  }
};
template <typename Scalar>
struct functor_traits<scalar_bitwise_or_op<Scalar>> {
  enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = true };
};

/** \internal
 * \brief Template functor to compute the bitwise xor of two scalars
 *
 * \sa class CwiseBinaryOp, ArrayBase::operator^
 */
template <typename Scalar>
struct scalar_bitwise_xor_op {
  EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::RequireInitialization,
                      BITWISE OPERATIONS MAY ONLY BE PERFORMED ON PLAIN DATA TYPES)
  EIGEN_STATIC_ASSERT((!std::is_same<Scalar, bool>::value), DONT USE BITWISE OPS ON BOOLEAN TYPES)
  using result_type = Scalar;
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar operator()(const Scalar& a, const Scalar& b) const {
    return bitwise_binary_impl<Scalar>::run_xor(a, b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    return pxor(a, b);
  }
};
template <typename Scalar>
struct functor_traits<scalar_bitwise_xor_op<Scalar>> {
  enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = true };
};

/** \internal
 * \brief Template functor to compute the absolute difference of two scalars
 *
 * \sa class CwiseBinaryOp, MatrixBase::absolute_difference
 */
template <typename LhsScalar, typename RhsScalar>
struct scalar_absolute_difference_op : binary_op_base<LhsScalar, RhsScalar> {
  using result_type = typename ScalarBinaryOpTraits<LhsScalar, RhsScalar, scalar_absolute_difference_op>::ReturnType;
#ifdef EIGEN_SCALAR_BINARY_OP_PLUGIN
  scalar_absolute_difference_op(){EIGEN_SCALAR_BINARY_OP_PLUGIN}
#endif
  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type
  operator()(const LhsScalar& a, const RhsScalar& b) const {
    return numext::absdiff(a, b);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a, const Packet& b) const {
    return internal::pabsdiff(a, b);
  }
};
template <typename LhsScalar, typename RhsScalar>
struct functor_traits<scalar_absolute_difference_op<LhsScalar, RhsScalar>> {
  enum {
    Cost = (NumTraits<LhsScalar>::AddCost + NumTraits<RhsScalar>::AddCost) / 2,
    PacketAccess = std::is_same<LhsScalar, RhsScalar>::value && packet_traits<LhsScalar>::HasAbsDiff
  };
};

template <typename LhsScalar, typename RhsScalar>
struct scalar_atan2_op {
  using Scalar = LhsScalar;

  static constexpr bool Enable =
      std::is_same<LhsScalar, RhsScalar>::value && !NumTraits<Scalar>::IsInteger && !NumTraits<Scalar>::IsComplex;
  EIGEN_STATIC_ASSERT(Enable, "LhsScalar and RhsScalar must be the same non-integer, non-complex type")

  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Scalar operator()(const Scalar& y, const Scalar& x) const {
    return numext::atan2(y, x);
  }
  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& y, const Packet& x) const {
    return internal::patan2(y, x);
  }
};

template <typename LhsScalar, typename RhsScalar>
struct functor_traits<scalar_atan2_op<LhsScalar, RhsScalar>> {
  using Scalar = LhsScalar;
  enum {
    PacketAccess = std::is_same<LhsScalar, RhsScalar>::value && packet_traits<Scalar>::HasATan &&
                   packet_traits<Scalar>::HasDiv && !NumTraits<Scalar>::IsInteger && !NumTraits<Scalar>::IsComplex,
    Cost = int(scalar_div_cost<Scalar, PacketAccess>::value) + int(functor_traits<scalar_atan_op<Scalar>>::Cost)
  };
};

//---------- binary functors bound to a constant, thus appearing as a unary functor ----------

// The following two classes permits to turn any binary functor into a unary one with one argument bound to a constant
// value. They are analogues to the removed std::binder1st/binder2nd and are also compatible with packetOp.
template <typename BinaryOp>
struct bind1st_op : BinaryOp {
  using first_argument_type = typename BinaryOp::first_argument_type;
  using second_argument_type = typename BinaryOp::second_argument_type;
  using result_type = typename BinaryOp::result_type;

  EIGEN_DEVICE_FUNC constexpr explicit bind1st_op(const first_argument_type& val) : m_value(val) {}

  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type operator()(const second_argument_type& b) const {
    return BinaryOp::operator()(m_value, b);
  }

  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& b) const {
    return BinaryOp::packetOp(internal::pset1<Packet>(m_value), b);
  }

  first_argument_type m_value;
};
template <typename BinaryOp>
struct functor_traits<bind1st_op<BinaryOp>> : functor_traits<BinaryOp> {};

template <typename BinaryOp>
struct bind2nd_op : BinaryOp {
  using first_argument_type = typename BinaryOp::first_argument_type;
  using second_argument_type = typename BinaryOp::second_argument_type;
  using result_type = typename BinaryOp::result_type;

  EIGEN_DEVICE_FUNC constexpr explicit bind2nd_op(const second_argument_type& val) : m_value(val) {}

  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE result_type operator()(const first_argument_type& a) const {
    return BinaryOp::operator()(a, m_value);
  }

  template <typename Packet>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packetOp(const Packet& a) const {
    return BinaryOp::packetOp(a, internal::pset1<Packet>(m_value));
  }

  second_argument_type m_value;
};
template <typename BinaryOp>
struct functor_traits<bind2nd_op<BinaryOp>> : functor_traits<BinaryOp> {};

}  // end namespace internal

}  // end namespace Eigen

#endif  // EIGEN_BINARY_FUNCTORS_H