| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com> |
| // |
| // This Source Code Form is subject to the terms of the Mozilla |
| // Public License v. 2.0. If a copy of the MPL was not distributed |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| |
| #ifndef EIGEN_CXX11_TENSOR_TENSOR_CUSTOM_OP_H |
| #define EIGEN_CXX11_TENSOR_TENSOR_CUSTOM_OP_H |
| |
| #include "./InternalHeaderCheck.h" |
| |
| namespace Eigen { |
| |
| /** \class TensorCustomUnaryOp |
| * \ingroup CXX11_Tensor_Module |
| * |
| * \brief Tensor custom class. |
| * |
| * |
| */ |
| namespace internal { |
| template<typename CustomUnaryFunc, typename XprType> |
| struct traits<TensorCustomUnaryOp<CustomUnaryFunc, XprType> > |
| { |
| typedef typename XprType::Scalar Scalar; |
| typedef typename XprType::StorageKind StorageKind; |
| typedef typename XprType::Index Index; |
| typedef typename XprType::Nested Nested; |
| typedef std::remove_reference_t<Nested> Nested_; |
| static constexpr int NumDimensions = traits<XprType>::NumDimensions; |
| static constexpr int Layout = traits<XprType>::Layout; |
| typedef typename traits<XprType>::PointerType PointerType; |
| }; |
| |
| template<typename CustomUnaryFunc, typename XprType> |
| struct eval<TensorCustomUnaryOp<CustomUnaryFunc, XprType>, Eigen::Dense> |
| { |
| typedef const TensorCustomUnaryOp<CustomUnaryFunc, XprType>EIGEN_DEVICE_REF type; |
| }; |
| |
| template<typename CustomUnaryFunc, typename XprType> |
| struct nested<TensorCustomUnaryOp<CustomUnaryFunc, XprType> > |
| { |
| typedef TensorCustomUnaryOp<CustomUnaryFunc, XprType> type; |
| }; |
| |
| } // end namespace internal |
| |
| |
| |
| template<typename CustomUnaryFunc, typename XprType> |
| class TensorCustomUnaryOp : public TensorBase<TensorCustomUnaryOp<CustomUnaryFunc, XprType>, ReadOnlyAccessors> |
| { |
| public: |
| typedef typename internal::traits<TensorCustomUnaryOp>::Scalar Scalar; |
| typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; |
| typedef typename XprType::CoeffReturnType CoeffReturnType; |
| typedef typename internal::nested<TensorCustomUnaryOp>::type Nested; |
| typedef typename internal::traits<TensorCustomUnaryOp>::StorageKind StorageKind; |
| typedef typename internal::traits<TensorCustomUnaryOp>::Index Index; |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorCustomUnaryOp(const XprType& expr, const CustomUnaryFunc& func) |
| : m_expr(expr), m_func(func) {} |
| |
| EIGEN_DEVICE_FUNC |
| const CustomUnaryFunc& func() const { return m_func; } |
| |
| EIGEN_DEVICE_FUNC |
| const internal::remove_all_t<typename XprType::Nested>& |
| expression() const { return m_expr; } |
| |
| protected: |
| typename XprType::Nested m_expr; |
| const CustomUnaryFunc m_func; |
| }; |
| |
| |
| // Eval as rvalue |
| template<typename CustomUnaryFunc, typename XprType, typename Device> |
| struct TensorEvaluator<const TensorCustomUnaryOp<CustomUnaryFunc, XprType>, Device> |
| { |
| typedef TensorCustomUnaryOp<CustomUnaryFunc, XprType> ArgType; |
| typedef typename internal::traits<ArgType>::Index Index; |
| static constexpr int NumDims = internal::traits<ArgType>::NumDimensions; |
| typedef DSizes<Index, NumDims> Dimensions; |
| typedef std::remove_const_t<typename ArgType::Scalar> Scalar; |
| typedef std::remove_const_t<typename XprType::CoeffReturnType> CoeffReturnType; |
| typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType; |
| static constexpr int PacketSize = PacketType<CoeffReturnType, Device>::size; |
| typedef typename Eigen::internal::traits<XprType>::PointerType TensorPointerType; |
| typedef StorageMemory<CoeffReturnType, Device> Storage; |
| typedef typename Storage::Type EvaluatorPointerType; |
| |
| static constexpr int Layout = TensorEvaluator<XprType, Device>::Layout; |
| enum { |
| IsAligned = false, |
| PacketAccess = (PacketType<CoeffReturnType, Device>::size > 1), |
| BlockAccess = false, |
| PreferBlockAccess = false, |
| CoordAccess = false, // to be implemented |
| RawAccess = false |
| }; |
| |
| //===- Tensor block evaluation strategy (see TensorBlock.h) -------------===// |
| typedef internal::TensorBlockNotImplemented TensorBlock; |
| //===--------------------------------------------------------------------===// |
| |
| EIGEN_STRONG_INLINE TensorEvaluator(const ArgType& op, const Device& device) |
| : m_op(op), m_device(device), m_result(NULL) |
| { |
| m_dimensions = op.func().dimensions(op.expression()); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; } |
| |
| EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType data) { |
| if (data) { |
| evalTo(data); |
| return false; |
| } else { |
| m_result = static_cast<EvaluatorPointerType>(m_device.get( (CoeffReturnType*) |
| m_device.allocate_temp(dimensions().TotalSize() * sizeof(Scalar)))); |
| evalTo(m_result); |
| return true; |
| } |
| } |
| |
| EIGEN_STRONG_INLINE void cleanup() { |
| if (m_result) { |
| m_device.deallocate_temp(m_result); |
| m_result = NULL; |
| } |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { |
| return m_result[index]; |
| } |
| |
| template<int LoadMode> |
| EIGEN_DEVICE_FUNC PacketReturnType packet(Index index) const { |
| return internal::ploadt<PacketReturnType, LoadMode>(m_result + index); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const { |
| // TODO(rmlarsen): Extend CustomOp API to return its cost estimate. |
| return TensorOpCost(sizeof(CoeffReturnType), 0, 0, vectorized, PacketSize); |
| } |
| |
| EIGEN_DEVICE_FUNC EvaluatorPointerType data() const { return m_result; } |
| |
| #ifdef EIGEN_USE_SYCL |
| // binding placeholder accessors to a command group handler for SYCL |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void bind(cl::sycl::handler &cgh) const { |
| m_result.bind(cgh); |
| } |
| #endif |
| |
| protected: |
| void evalTo(EvaluatorPointerType data) { |
| TensorMap<Tensor<CoeffReturnType, NumDims, Layout, Index> > result(m_device.get(data), m_dimensions); |
| m_op.func().eval(m_op.expression(), result, m_device); |
| } |
| |
| Dimensions m_dimensions; |
| const ArgType m_op; |
| const Device EIGEN_DEVICE_REF m_device; |
| EvaluatorPointerType m_result; |
| }; |
| |
| |
| |
| /** \class TensorCustomBinaryOp |
| * \ingroup CXX11_Tensor_Module |
| * |
| * \brief Tensor custom class. |
| * |
| * |
| */ |
| namespace internal { |
| template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType> |
| struct traits<TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType> > |
| { |
| typedef typename internal::promote_storage_type<typename LhsXprType::Scalar, |
| typename RhsXprType::Scalar>::ret Scalar; |
| typedef typename internal::promote_storage_type<typename LhsXprType::CoeffReturnType, |
| typename RhsXprType::CoeffReturnType>::ret CoeffReturnType; |
| typedef typename promote_storage_type<typename traits<LhsXprType>::StorageKind, |
| typename traits<RhsXprType>::StorageKind>::ret StorageKind; |
| typedef typename promote_index_type<typename traits<LhsXprType>::Index, |
| typename traits<RhsXprType>::Index>::type Index; |
| typedef typename LhsXprType::Nested LhsNested; |
| typedef typename RhsXprType::Nested RhsNested; |
| typedef std::remove_reference_t<LhsNested> LhsNested_; |
| typedef std::remove_reference_t<RhsNested> RhsNested_; |
| static constexpr int NumDimensions = traits<LhsXprType>::NumDimensions; |
| static constexpr int Layout = traits<LhsXprType>::Layout; |
| typedef std::conditional_t<Pointer_type_promotion<typename LhsXprType::Scalar, Scalar>::val, |
| typename traits<LhsXprType>::PointerType, typename traits<RhsXprType>::PointerType> PointerType; |
| }; |
| |
| template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType> |
| struct eval<TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType>, Eigen::Dense> |
| { |
| typedef const TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType>& type; |
| }; |
| |
| template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType> |
| struct nested<TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType> > |
| { |
| typedef TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType> type; |
| }; |
| |
| } // end namespace internal |
| |
| |
| |
| template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType> |
| class TensorCustomBinaryOp : public TensorBase<TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType>, ReadOnlyAccessors> |
| { |
| public: |
| typedef typename internal::traits<TensorCustomBinaryOp>::Scalar Scalar; |
| typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; |
| typedef typename internal::traits<TensorCustomBinaryOp>::CoeffReturnType CoeffReturnType; |
| typedef typename internal::nested<TensorCustomBinaryOp>::type Nested; |
| typedef typename internal::traits<TensorCustomBinaryOp>::StorageKind StorageKind; |
| typedef typename internal::traits<TensorCustomBinaryOp>::Index Index; |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorCustomBinaryOp(const LhsXprType& lhs, const RhsXprType& rhs, const CustomBinaryFunc& func) |
| |
| : m_lhs_xpr(lhs), m_rhs_xpr(rhs), m_func(func) {} |
| |
| EIGEN_DEVICE_FUNC |
| const CustomBinaryFunc& func() const { return m_func; } |
| |
| EIGEN_DEVICE_FUNC |
| const internal::remove_all_t<typename LhsXprType::Nested>& |
| lhsExpression() const { return m_lhs_xpr; } |
| |
| EIGEN_DEVICE_FUNC |
| const internal::remove_all_t<typename RhsXprType::Nested>& |
| rhsExpression() const { return m_rhs_xpr; } |
| |
| protected: |
| typename LhsXprType::Nested m_lhs_xpr; |
| typename RhsXprType::Nested m_rhs_xpr; |
| const CustomBinaryFunc m_func; |
| }; |
| |
| |
| // Eval as rvalue |
| template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType, typename Device> |
| struct TensorEvaluator<const TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType>, Device> |
| { |
| typedef TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType> XprType; |
| typedef typename internal::traits<XprType>::Index Index; |
| static constexpr int NumDims = internal::traits<XprType>::NumDimensions; |
| typedef DSizes<Index, NumDims> Dimensions; |
| typedef typename XprType::Scalar Scalar; |
| typedef std::remove_const_t<typename XprType::CoeffReturnType> CoeffReturnType; |
| typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType; |
| static constexpr int PacketSize = PacketType<CoeffReturnType, Device>::size; |
| |
| typedef typename Eigen::internal::traits<XprType>::PointerType TensorPointerType; |
| typedef StorageMemory<CoeffReturnType, Device> Storage; |
| typedef typename Storage::Type EvaluatorPointerType; |
| |
| static constexpr int Layout = TensorEvaluator<LhsXprType, Device>::Layout; |
| enum { |
| IsAligned = false, |
| PacketAccess = (PacketType<CoeffReturnType, Device>::size > 1), |
| BlockAccess = false, |
| PreferBlockAccess = false, |
| CoordAccess = false, // to be implemented |
| RawAccess = false |
| }; |
| |
| //===- Tensor block evaluation strategy (see TensorBlock.h) -------------===// |
| typedef internal::TensorBlockNotImplemented TensorBlock; |
| //===--------------------------------------------------------------------===// |
| |
| EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device) |
| : m_op(op), m_device(device), m_result(NULL) |
| { |
| m_dimensions = op.func().dimensions(op.lhsExpression(), op.rhsExpression()); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; } |
| |
| EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType data) { |
| if (data) { |
| evalTo(data); |
| return false; |
| } else { |
| m_result = static_cast<EvaluatorPointerType>(m_device.get( (CoeffReturnType*) |
| m_device.allocate_temp(dimensions().TotalSize() * sizeof(CoeffReturnType)))); |
| evalTo(m_result); |
| return true; |
| } |
| } |
| |
| EIGEN_STRONG_INLINE void cleanup() { |
| if (m_result != NULL) { |
| m_device.deallocate_temp(m_result); |
| m_result = NULL; |
| } |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { |
| return m_result[index]; |
| } |
| |
| template<int LoadMode> |
| EIGEN_DEVICE_FUNC PacketReturnType packet(Index index) const { |
| return internal::ploadt<PacketReturnType, LoadMode>(m_result + index); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const { |
| // TODO(rmlarsen): Extend CustomOp API to return its cost estimate. |
| return TensorOpCost(sizeof(CoeffReturnType), 0, 0, vectorized, PacketSize); |
| } |
| |
| EIGEN_DEVICE_FUNC EvaluatorPointerType data() const { return m_result; } |
| |
| #ifdef EIGEN_USE_SYCL |
| // binding placeholder accessors to a command group handler for SYCL |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void bind(cl::sycl::handler &cgh) const { |
| m_result.bind(cgh); |
| } |
| #endif |
| |
| protected: |
| void evalTo(EvaluatorPointerType data) { |
| TensorMap<Tensor<CoeffReturnType, NumDims, Layout> > result(m_device.get(data), m_dimensions); |
| m_op.func().eval(m_op.lhsExpression(), m_op.rhsExpression(), result, m_device); |
| } |
| |
| Dimensions m_dimensions; |
| const XprType m_op; |
| const Device EIGEN_DEVICE_REF m_device; |
| EvaluatorPointerType m_result; |
| }; |
| |
| |
| } // end namespace Eigen |
| |
| #endif // EIGEN_CXX11_TENSOR_TENSOR_CUSTOM_OP_H |