Eigen/src/Core/util/BlasUtil.h

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009-2010 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_BLASUTIL_H
#define EIGEN_BLASUTIL_H

// This file contains many lightweight helper classes used to
// implement and control fast level 2 and level 3 BLAS-like routines.

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

namespace Eigen {

namespace internal {

// forward declarations
template <typename LhsScalar, typename RhsScalar, typename Index, typename DataMapper, int mr, int nr,
          bool ConjugateLhs = false, bool ConjugateRhs = false>
struct gebp_kernel;

template <typename Scalar, typename Index, typename DataMapper, int nr, int StorageOrder, bool Conjugate = false,
          bool PanelMode = false>
struct gemm_pack_rhs;

template <typename Scalar, typename Index, typename DataMapper, int Pack1, int Pack2, typename Packet, int StorageOrder,
          bool Conjugate = false, bool PanelMode = false>
struct gemm_pack_lhs;

template <typename Index, typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs, typename RhsScalar,
          int RhsStorageOrder, bool ConjugateRhs, int ResStorageOrder, int ResInnerStride>
struct general_matrix_matrix_product;

template <typename Index, typename LhsScalar, typename LhsMapper, int LhsStorageOrder, bool ConjugateLhs,
          typename RhsScalar, typename RhsMapper, bool ConjugateRhs, int Version = Specialized>
struct general_matrix_vector_product;

template <typename From, typename To>
struct get_factor {
  EIGEN_DEVICE_FUNC constexpr static EIGEN_STRONG_INLINE To run(const From& x) { return To(x); }
};

template <typename Scalar>
struct get_factor<Scalar, typename NumTraits<Scalar>::Real> {
  EIGEN_DEVICE_FUNC constexpr static EIGEN_STRONG_INLINE typename NumTraits<Scalar>::Real run(const Scalar& x) {
    return numext::real(x);
  }
};

template <typename Scalar, typename Index>
class BlasVectorMapper {
 public:
  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE BlasVectorMapper(Scalar* data) : m_data(data) {}

  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE Scalar operator()(Index i) const { return m_data[i]; }
  template <typename Packet, int AlignmentType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet load(Index i) const {
    return ploadt<Packet, AlignmentType>(m_data + i);
  }

  template <typename Packet>
  EIGEN_DEVICE_FUNC bool aligned(Index i) const {
    return (std::uintptr_t(m_data + i) % sizeof(Packet)) == 0;
  }

 protected:
  Scalar* m_data;
};

template <typename Scalar, typename Index, int AlignmentType, int Incr = 1>
class BlasLinearMapper;

template <typename Scalar, typename Index, int AlignmentType>
class BlasLinearMapper<Scalar, Index, AlignmentType> {
 public:
  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE BlasLinearMapper(Scalar* data, Index incr = 1) : m_data(data) {
    EIGEN_ONLY_USED_FOR_DEBUG(incr);
    eigen_assert(incr == 1);
  }

  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void prefetch(Index i) const { internal::prefetch(&operator()(i)); }

  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE Scalar& operator()(Index i) const { return m_data[i]; }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketType loadPacket(Index i) const {
    return ploadt<PacketType, AlignmentType>(m_data + i);
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketType loadPacketPartial(Index i, Index n, Index offset = 0) const {
    return ploadt_partial<PacketType, AlignmentType>(m_data + i, n, offset);
  }

  template <typename PacketType, int AlignmentT>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketType load(Index i) const {
    return ploadt<PacketType, AlignmentT>(m_data + i);
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void storePacket(Index i, const PacketType& p) const {
    pstoret<Scalar, PacketType, AlignmentType>(m_data + i, p);
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void storePacketPartial(Index i, const PacketType& p, Index n,
                                                                Index offset = 0) const {
    pstoret_partial<Scalar, PacketType, AlignmentType>(m_data + i, p, n, offset);
  }

 protected:
  Scalar* m_data;
};

// Lightweight helper class to access matrix coefficients.
template <typename Scalar, typename Index, int StorageOrder, int AlignmentType = Unaligned, int Incr = 1>
class blas_data_mapper;

// TMP to help PacketBlock store implementation.
// There's currently no known use case for PacketBlock load.
// The default implementation assumes ColMajor order.
// It always store each packet sequentially one `stride` apart.
template <typename Index, typename Scalar, typename Packet, int n, int idx, int StorageOrder>
struct PacketBlockManagement {
  PacketBlockManagement<Index, Scalar, Packet, n, idx - 1, StorageOrder> pbm;
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void store(Scalar* to, const Index stride, Index i, Index j,
                                                   const PacketBlock<Packet, n>& block) const {
    pbm.store(to, stride, i, j, block);
    pstoreu<Scalar>(to + i + (j + idx) * stride, block.packet[idx]);
  }
};

// PacketBlockManagement specialization to take care of RowMajor order without ifs.
template <typename Index, typename Scalar, typename Packet, int n, int idx>
struct PacketBlockManagement<Index, Scalar, Packet, n, idx, RowMajor> {
  PacketBlockManagement<Index, Scalar, Packet, n, idx - 1, RowMajor> pbm;
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void store(Scalar* to, const Index stride, Index i, Index j,
                                                   const PacketBlock<Packet, n>& block) const {
    pbm.store(to, stride, i, j, block);
    pstoreu<Scalar>(to + j + (i + idx) * stride, block.packet[idx]);
  }
};

template <typename Index, typename Scalar, typename Packet, int n, int StorageOrder>
struct PacketBlockManagement<Index, Scalar, Packet, n, -1, StorageOrder> {
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void store(Scalar* to, const Index stride, Index i, Index j,
                                                   const PacketBlock<Packet, n>& block) const {
    EIGEN_UNUSED_VARIABLE(to);
    EIGEN_UNUSED_VARIABLE(stride);
    EIGEN_UNUSED_VARIABLE(i);
    EIGEN_UNUSED_VARIABLE(j);
    EIGEN_UNUSED_VARIABLE(block);
  }
};

template <typename Index, typename Scalar, typename Packet, int n>
struct PacketBlockManagement<Index, Scalar, Packet, n, -1, RowMajor> {
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void store(Scalar* to, const Index stride, Index i, Index j,
                                                   const PacketBlock<Packet, n>& block) const {
    EIGEN_UNUSED_VARIABLE(to);
    EIGEN_UNUSED_VARIABLE(stride);
    EIGEN_UNUSED_VARIABLE(i);
    EIGEN_UNUSED_VARIABLE(j);
    EIGEN_UNUSED_VARIABLE(block);
  }
};

template <typename Scalar, typename Index, int StorageOrder, int AlignmentType>
class blas_data_mapper<Scalar, Index, StorageOrder, AlignmentType, 1> {
 public:
  using LinearMapper = BlasLinearMapper<Scalar, Index, AlignmentType>;
  using SubMapper = blas_data_mapper<Scalar, Index, StorageOrder, AlignmentType>;
  using VectorMapper = BlasVectorMapper<Scalar, Index>;

  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE blas_data_mapper(Scalar* data, Index stride, Index incr = 1)
      : m_data(data), m_stride(stride) {
    EIGEN_ONLY_USED_FOR_DEBUG(incr);
    eigen_assert(incr == 1);
  }

  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE SubMapper getSubMapper(Index i, Index j) const {
    return SubMapper(&operator()(i, j), m_stride);
  }

  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE LinearMapper getLinearMapper(Index i, Index j) const {
    return LinearMapper(&operator()(i, j));
  }

  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE VectorMapper getVectorMapper(Index i, Index j) const {
    return VectorMapper(&operator()(i, j));
  }

  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void prefetch(Index i, Index j) const { internal::prefetch(&operator()(i, j)); }

  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE Scalar& operator()(Index i, Index j) const {
    return m_data[StorageOrder == RowMajor ? j + i * m_stride : i + j * m_stride];
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketType loadPacket(Index i, Index j) const {
    return ploadt<PacketType, AlignmentType>(&operator()(i, j));
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketType loadPacketPartial(Index i, Index j, Index n,
                                                                     Index offset = 0) const {
    return ploadt_partial<PacketType, AlignmentType>(&operator()(i, j), n, offset);
  }

  template <typename PacketT, int AlignmentT>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketT load(Index i, Index j) const {
    return ploadt<PacketT, AlignmentT>(&operator()(i, j));
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void storePacket(Index i, Index j, const PacketType& p) const {
    pstoret<Scalar, PacketType, AlignmentType>(&operator()(i, j), p);
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void storePacketPartial(Index i, Index j, const PacketType& p, Index n,
                                                                Index offset = 0) const {
    pstoret_partial<Scalar, PacketType, AlignmentType>(&operator()(i, j), p, n, offset);
  }

  template <typename SubPacket>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void scatterPacket(Index i, Index j, const SubPacket& p) const {
    pscatter<Scalar, SubPacket>(&operator()(i, j), p, m_stride);
  }

  template <typename SubPacket>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE SubPacket gatherPacket(Index i, Index j) const {
    return pgather<Scalar, SubPacket>(&operator()(i, j), m_stride);
  }

  EIGEN_DEVICE_FUNC constexpr const Index stride() const { return m_stride; }
  EIGEN_DEVICE_FUNC constexpr const Index incr() const { return 1; }
  EIGEN_DEVICE_FUNC constexpr const Scalar* data() const { return m_data; }

  EIGEN_DEVICE_FUNC Index firstAligned(Index size) const {
    if (std::uintptr_t(m_data) % sizeof(Scalar)) {
      return -1;
    }
    return internal::first_default_aligned(m_data, size);
  }

  template <typename SubPacket, int n>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void storePacketBlock(Index i, Index j,
                                                              const PacketBlock<SubPacket, n>& block) const {
    PacketBlockManagement<Index, Scalar, SubPacket, n, n - 1, StorageOrder> pbm;
    pbm.store(m_data, m_stride, i, j, block);
  }

 protected:
  Scalar* EIGEN_RESTRICT m_data;
  const Index m_stride;
};

// Implementation of non-natural increment (i.e. inner-stride != 1)
// The exposed API is not complete yet compared to the Incr==1 case
// because some features makes less sense in this case.
template <typename Scalar, typename Index, int AlignmentType, int Incr>
class BlasLinearMapper {
 public:
  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE BlasLinearMapper(Scalar* data, Index incr)
      : m_data(data), m_incr(incr) {}

  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void prefetch(int i) const { internal::prefetch(&operator()(i)); }

  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE Scalar& operator()(Index i) const {
    return m_data[i * m_incr.value()];
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketType loadPacket(Index i) const {
    return pgather<Scalar, PacketType>(m_data + i * m_incr.value(), m_incr.value());
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketType loadPacketPartial(Index i, Index n, Index /*offset*/ = 0) const {
    return pgather_partial<Scalar, PacketType>(m_data + i * m_incr.value(), m_incr.value(), n);
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void storePacket(Index i, const PacketType& p) const {
    pscatter<Scalar, PacketType>(m_data + i * m_incr.value(), p, m_incr.value());
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void storePacketPartial(Index i, const PacketType& p, Index n,
                                                                Index /*offset*/ = 0) const {
    pscatter_partial<Scalar, PacketType>(m_data + i * m_incr.value(), p, m_incr.value(), n);
  }

 protected:
  Scalar* m_data;
  const internal::variable_if_dynamic<Index, Incr> m_incr;
};

template <typename Scalar, typename Index, int StorageOrder, int AlignmentType, int Incr>
class blas_data_mapper {
 public:
  using LinearMapper = BlasLinearMapper<Scalar, Index, AlignmentType, Incr>;
  using SubMapper = blas_data_mapper;

  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE blas_data_mapper(Scalar* data, Index stride, Index incr)
      : m_data(data), m_stride(stride), m_incr(incr) {}

  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE SubMapper getSubMapper(Index i, Index j) const {
    return SubMapper(&operator()(i, j), m_stride, m_incr.value());
  }

  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE LinearMapper getLinearMapper(Index i, Index j) const {
    return LinearMapper(&operator()(i, j), m_incr.value());
  }

  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void prefetch(Index i, Index j) const { internal::prefetch(&operator()(i, j)); }

  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE Scalar& operator()(Index i, Index j) const {
    return m_data[StorageOrder == RowMajor ? j * m_incr.value() + i * m_stride : i * m_incr.value() + j * m_stride];
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketType loadPacket(Index i, Index j) const {
    return pgather<Scalar, PacketType>(&operator()(i, j), m_incr.value());
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketType loadPacketPartial(Index i, Index j, Index n,
                                                                     Index /*offset*/ = 0) const {
    return pgather_partial<Scalar, PacketType>(&operator()(i, j), m_incr.value(), n);
  }

  template <typename PacketT, int AlignmentT>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketT load(Index i, Index j) const {
    return pgather<Scalar, PacketT>(&operator()(i, j), m_incr.value());
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void storePacket(Index i, Index j, const PacketType& p) const {
    pscatter<Scalar, PacketType>(&operator()(i, j), p, m_incr.value());
  }

  template <typename PacketType>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void storePacketPartial(Index i, Index j, const PacketType& p, Index n,
                                                                Index /*offset*/ = 0) const {
    pscatter_partial<Scalar, PacketType>(&operator()(i, j), p, m_incr.value(), n);
  }

  template <typename SubPacket>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void scatterPacket(Index i, Index j, const SubPacket& p) const {
    pscatter<Scalar, SubPacket>(&operator()(i, j), p, m_stride);
  }

  template <typename SubPacket>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE SubPacket gatherPacket(Index i, Index j) const {
    return pgather<Scalar, SubPacket>(&operator()(i, j), m_stride);
  }

  // storePacketBlock_helper defines a way to access values inside the PacketBlock, this is essentially required by the
  // Complex types.
  template <typename SubPacket, typename Scalar_, int n, int idx>
  struct storePacketBlock_helper {
    storePacketBlock_helper<SubPacket, Scalar_, n, idx - 1> spbh;
    EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void store(
        const blas_data_mapper<Scalar, Index, StorageOrder, AlignmentType, Incr>* sup, Index i, Index j,
        const PacketBlock<SubPacket, n>& block) const {
      spbh.store(sup, i, j, block);
      sup->template storePacket<SubPacket>(i, j + idx, block.packet[idx]);
    }
  };

  template <typename SubPacket, int n, int idx>
  struct storePacketBlock_helper<SubPacket, std::complex<float>, n, idx> {
    storePacketBlock_helper<SubPacket, std::complex<float>, n, idx - 1> spbh;
    EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void store(
        const blas_data_mapper<Scalar, Index, StorageOrder, AlignmentType, Incr>* sup, Index i, Index j,
        const PacketBlock<SubPacket, n>& block) const {
      spbh.store(sup, i, j, block);
      sup->template storePacket<SubPacket>(i, j + idx, block.packet[idx]);
    }
  };

  template <typename SubPacket, int n, int idx>
  struct storePacketBlock_helper<SubPacket, std::complex<double>, n, idx> {
    storePacketBlock_helper<SubPacket, std::complex<double>, n, idx - 1> spbh;
    EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void store(
        const blas_data_mapper<Scalar, Index, StorageOrder, AlignmentType, Incr>* sup, Index i, Index j,
        const PacketBlock<SubPacket, n>& block) const {
      spbh.store(sup, i, j, block);
      for (int l = 0; l < unpacket_traits<SubPacket>::size; l++) {
        std::complex<double>* v = &sup->operator()(i + l, j + idx);
        v->real(block.packet[idx].v[2 * l + 0]);
        v->imag(block.packet[idx].v[2 * l + 1]);
      }
    }
  };

  template <typename SubPacket, typename Scalar_, int n>
  struct storePacketBlock_helper<SubPacket, Scalar_, n, -1> {
    EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void store(
        const blas_data_mapper<Scalar, Index, StorageOrder, AlignmentType, Incr>*, Index, Index,
        const PacketBlock<SubPacket, n>&) const {}
  };

  template <typename SubPacket, int n>
  struct storePacketBlock_helper<SubPacket, std::complex<float>, n, -1> {
    EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void store(
        const blas_data_mapper<Scalar, Index, StorageOrder, AlignmentType, Incr>*, Index, Index,
        const PacketBlock<SubPacket, n>&) const {}
  };

  template <typename SubPacket, int n>
  struct storePacketBlock_helper<SubPacket, std::complex<double>, n, -1> {
    EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void store(
        const blas_data_mapper<Scalar, Index, StorageOrder, AlignmentType, Incr>*, Index, Index,
        const PacketBlock<SubPacket, n>&) const {}
  };
  // This function stores a PacketBlock on m_data, this approach is really quite slow compare to Incr=1 and should be
  // avoided when possible.
  template <typename SubPacket, int n>
  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void storePacketBlock(Index i, Index j,
                                                              const PacketBlock<SubPacket, n>& block) const {
    storePacketBlock_helper<SubPacket, Scalar, n, n - 1> spb;
    spb.store(this, i, j, block);
  }

  EIGEN_DEVICE_FUNC constexpr const Index stride() const { return m_stride; }
  EIGEN_DEVICE_FUNC constexpr const Index incr() const { return m_incr.value(); }
  EIGEN_DEVICE_FUNC constexpr Scalar* data() const { return m_data; }

 protected:
  Scalar* EIGEN_RESTRICT m_data;
  const Index m_stride;
  const internal::variable_if_dynamic<Index, Incr> m_incr;
};

// lightweight helper class to access matrix coefficients (const version)
template <typename Scalar, typename Index, int StorageOrder>
class const_blas_data_mapper : public blas_data_mapper<const Scalar, Index, StorageOrder> {
 public:
  using SubMapper = const_blas_data_mapper<Scalar, Index, StorageOrder>;

  EIGEN_ALWAYS_INLINE const_blas_data_mapper(const Scalar* data, Index stride)
      : blas_data_mapper<const Scalar, Index, StorageOrder>(data, stride) {}

  EIGEN_ALWAYS_INLINE SubMapper getSubMapper(Index i, Index j) const {
    return SubMapper(&(this->operator()(i, j)), this->m_stride);
  }
};

/* Helper class to analyze the factors of a Product expression.
 * In particular it allows to pop out operator-, scalar multiples,
 * and conjugate */
template <typename XprType>
struct blas_traits {
  using Scalar = typename traits<XprType>::Scalar;
  using ExtractType = const XprType&;
  using ExtractType_ = XprType;
  enum {
    IsComplex = NumTraits<Scalar>::IsComplex,
    IsTransposed = false,
    NeedToConjugate = false,
    HasUsableDirectAccess =
        ((int(XprType::Flags) & DirectAccessBit) &&
         (bool(XprType::IsVectorAtCompileTime) || int(inner_stride_at_compile_time<XprType>::value) == 1))
            ? 1
            : 0,
    HasScalarFactor = false
  };
  using DirectLinearAccessType =
      std::conditional_t<bool(HasUsableDirectAccess), ExtractType, typename ExtractType_::PlainObject>;
  EIGEN_DEVICE_FUNC static inline EIGEN_DEVICE_FUNC ExtractType extract(const XprType& x) { return x; }
  EIGEN_DEVICE_FUNC static inline EIGEN_DEVICE_FUNC const Scalar extractScalarFactor(const XprType&) {
    return Scalar(1);
  }
};

// pop conjugate
template <typename Scalar, typename NestedXpr>
struct blas_traits<CwiseUnaryOp<scalar_conjugate_op<Scalar>, NestedXpr> > : blas_traits<NestedXpr> {
  using Base = blas_traits<NestedXpr>;
  using XprType = CwiseUnaryOp<scalar_conjugate_op<Scalar>, NestedXpr>;
  using ExtractType = typename Base::ExtractType;

  enum { IsComplex = NumTraits<Scalar>::IsComplex, NeedToConjugate = Base::NeedToConjugate ? 0 : IsComplex };
  EIGEN_DEVICE_FUNC static inline ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); }
  EIGEN_DEVICE_FUNC static inline Scalar extractScalarFactor(const XprType& x) {
    return conj(Base::extractScalarFactor(x.nestedExpression()));
  }
};

// pop scalar multiple
template <typename Scalar, typename NestedXpr, typename Plain>
struct blas_traits<
    CwiseBinaryOp<scalar_product_op<Scalar>, const CwiseNullaryOp<scalar_constant_op<Scalar>, Plain>, NestedXpr> >
    : blas_traits<NestedXpr> {
  enum { HasScalarFactor = true };
  using Base = blas_traits<NestedXpr>;
  using XprType =
      CwiseBinaryOp<scalar_product_op<Scalar>, const CwiseNullaryOp<scalar_constant_op<Scalar>, Plain>, NestedXpr>;
  using ExtractType = typename Base::ExtractType;
  EIGEN_DEVICE_FUNC static inline EIGEN_DEVICE_FUNC ExtractType extract(const XprType& x) {
    return Base::extract(x.rhs());
  }
  EIGEN_DEVICE_FUNC static inline EIGEN_DEVICE_FUNC Scalar extractScalarFactor(const XprType& x) {
    return x.lhs().functor().m_other * Base::extractScalarFactor(x.rhs());
  }
};
template <typename Scalar, typename NestedXpr, typename Plain>
struct blas_traits<
    CwiseBinaryOp<scalar_product_op<Scalar>, NestedXpr, const CwiseNullaryOp<scalar_constant_op<Scalar>, Plain> > >
    : blas_traits<NestedXpr> {
  enum { HasScalarFactor = true };
  using Base = blas_traits<NestedXpr>;
  using XprType =
      CwiseBinaryOp<scalar_product_op<Scalar>, NestedXpr, const CwiseNullaryOp<scalar_constant_op<Scalar>, Plain>>;
  using ExtractType = typename Base::ExtractType;
  EIGEN_DEVICE_FUNC static inline ExtractType extract(const XprType& x) { return Base::extract(x.lhs()); }
  EIGEN_DEVICE_FUNC static inline Scalar extractScalarFactor(const XprType& x) {
    return Base::extractScalarFactor(x.lhs()) * x.rhs().functor().m_other;
  }
};
template <typename Scalar, typename Plain1, typename Plain2>
struct blas_traits<CwiseBinaryOp<scalar_product_op<Scalar>, const CwiseNullaryOp<scalar_constant_op<Scalar>, Plain1>,
                                 const CwiseNullaryOp<scalar_constant_op<Scalar>, Plain2> > >
    : blas_traits<CwiseNullaryOp<scalar_constant_op<Scalar>, Plain1> > {};

// pop opposite
template <typename Scalar, typename NestedXpr>
struct blas_traits<CwiseUnaryOp<scalar_opposite_op<Scalar>, NestedXpr> > : blas_traits<NestedXpr> {
  enum { HasScalarFactor = true };
  using Base = blas_traits<NestedXpr>;
  using XprType = CwiseUnaryOp<scalar_opposite_op<Scalar>, NestedXpr>;
  using ExtractType = typename Base::ExtractType;
  EIGEN_DEVICE_FUNC static inline ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); }
  EIGEN_DEVICE_FUNC static inline Scalar extractScalarFactor(const XprType& x) {
    return -Base::extractScalarFactor(x.nestedExpression());
  }
};

// pop/push transpose
template <typename NestedXpr>
struct blas_traits<Transpose<NestedXpr> > : blas_traits<NestedXpr> {
  using Scalar = typename NestedXpr::Scalar;
  using Base = blas_traits<NestedXpr>;
  using XprType = Transpose<NestedXpr>;
  using ExtractType = Transpose<const typename Base::ExtractType_>;  // const to get rid of a compile error; anyway blas
                                                                     // traits are only used on the RHS
  using ExtractType_ = Transpose<const typename Base::ExtractType_>;
  using DirectLinearAccessType =
      std::conditional_t<bool(Base::HasUsableDirectAccess), ExtractType, typename ExtractType::PlainObject>;
  enum { IsTransposed = Base::IsTransposed ? 0 : 1 };
  EIGEN_DEVICE_FUNC static inline ExtractType extract(const XprType& x) {
    return ExtractType(Base::extract(x.nestedExpression()));
  }
  EIGEN_DEVICE_FUNC static inline Scalar extractScalarFactor(const XprType& x) {
    return Base::extractScalarFactor(x.nestedExpression());
  }
};

template <typename T>
struct blas_traits<const T> : blas_traits<T> {};

template <typename T, bool HasUsableDirectAccess = blas_traits<T>::HasUsableDirectAccess>
struct extract_data_selector {
  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE static const typename T::Scalar* run(const T& m) {
    return blas_traits<T>::extract(m).data();
  }
};

template <typename T>
struct extract_data_selector<T, false> {
  EIGEN_DEVICE_FUNC constexpr static typename T::Scalar* run(const T&) { return 0; }
};

template <typename T>
EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE const typename T::Scalar* extract_data(const T& m) {
  return extract_data_selector<T>::run(m);
}

/**
 * \c combine_scalar_factors extracts and multiplies factors from GEMM and GEMV products.
 * There is a specialization for booleans
 */
template <typename ResScalar, typename Lhs, typename Rhs>
struct combine_scalar_factors_impl {
  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE static ResScalar run(const Lhs& lhs, const Rhs& rhs) {
    return blas_traits<Lhs>::extractScalarFactor(lhs) * blas_traits<Rhs>::extractScalarFactor(rhs);
  }
  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE static ResScalar run(const ResScalar& alpha, const Lhs& lhs,
                                                                       const Rhs& rhs) {
    return alpha * blas_traits<Lhs>::extractScalarFactor(lhs) * blas_traits<Rhs>::extractScalarFactor(rhs);
  }
};
template <typename Lhs, typename Rhs>
struct combine_scalar_factors_impl<bool, Lhs, Rhs> {
  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE static bool run(const Lhs& lhs, const Rhs& rhs) {
    return blas_traits<Lhs>::extractScalarFactor(lhs) && blas_traits<Rhs>::extractScalarFactor(rhs);
  }
  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE static bool run(const bool& alpha, const Lhs& lhs, const Rhs& rhs) {
    return alpha && blas_traits<Lhs>::extractScalarFactor(lhs) && blas_traits<Rhs>::extractScalarFactor(rhs);
  }
};

template <typename ResScalar, typename Lhs, typename Rhs>
EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE ResScalar combine_scalar_factors(const ResScalar& alpha, const Lhs& lhs,
                                                                                 const Rhs& rhs) {
  return combine_scalar_factors_impl<ResScalar, Lhs, Rhs>::run(alpha, lhs, rhs);
}
template <typename ResScalar, typename Lhs, typename Rhs>
EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE ResScalar combine_scalar_factors(const Lhs& lhs, const Rhs& rhs) {
  return combine_scalar_factors_impl<ResScalar, Lhs, Rhs>::run(lhs, rhs);
}

}  // end namespace internal

}  // end namespace Eigen

#endif  // EIGEN_BLASUTIL_H