| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2014 Navdeep Jaitly <ndjaitly@google.com> |
| // 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_REVERSE_H |
| #define EIGEN_CXX11_TENSOR_TENSOR_REVERSE_H |
| namespace Eigen { |
| |
| /** \class TensorReverse |
| * \ingroup CXX11_Tensor_Module |
| * |
| * \brief Tensor reverse elements class. |
| * |
| */ |
| namespace internal { |
| template<typename ReverseDimensions, typename XprType> |
| struct traits<TensorReverseOp<ReverseDimensions, |
| XprType> > : public traits<XprType> |
| { |
| typedef typename XprType::Scalar Scalar; |
| typedef traits<XprType> XprTraits; |
| typedef typename XprTraits::StorageKind StorageKind; |
| typedef typename XprTraits::Index Index; |
| typedef typename XprType::Nested Nested; |
| typedef typename remove_reference<Nested>::type _Nested; |
| static const int NumDimensions = XprTraits::NumDimensions; |
| static const int Layout = XprTraits::Layout; |
| }; |
| |
| template<typename ReverseDimensions, typename XprType> |
| struct eval<TensorReverseOp<ReverseDimensions, XprType>, Eigen::Dense> |
| { |
| typedef const TensorReverseOp<ReverseDimensions, XprType>& type; |
| }; |
| |
| template<typename ReverseDimensions, typename XprType> |
| struct nested<TensorReverseOp<ReverseDimensions, XprType>, 1, |
| typename eval<TensorReverseOp<ReverseDimensions, XprType> >::type> |
| { |
| typedef TensorReverseOp<ReverseDimensions, XprType> type; |
| }; |
| |
| } // end namespace internal |
| |
| template<typename ReverseDimensions, typename XprType> |
| class TensorReverseOp : public TensorBase<TensorReverseOp<ReverseDimensions, |
| XprType>, WriteAccessors> |
| { |
| public: |
| typedef typename Eigen::internal::traits<TensorReverseOp>::Scalar Scalar; |
| typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; |
| typedef typename XprType::CoeffReturnType CoeffReturnType; |
| typedef typename Eigen::internal::nested<TensorReverseOp>::type Nested; |
| typedef typename Eigen::internal::traits<TensorReverseOp>::StorageKind |
| StorageKind; |
| typedef typename Eigen::internal::traits<TensorReverseOp>::Index Index; |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorReverseOp( |
| const XprType& expr, const ReverseDimensions& reverse_dims) |
| : m_xpr(expr), m_reverse_dims(reverse_dims) { } |
| |
| EIGEN_DEVICE_FUNC |
| const ReverseDimensions& reverse() const { return m_reverse_dims; } |
| |
| EIGEN_DEVICE_FUNC |
| const typename internal::remove_all<typename XprType::Nested>::type& |
| expression() const { return m_xpr; } |
| |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE TensorReverseOp& operator = (const TensorReverseOp& other) |
| { |
| typedef TensorAssignOp<TensorReverseOp, const TensorReverseOp> Assign; |
| Assign assign(*this, other); |
| internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice()); |
| return *this; |
| } |
| |
| template<typename OtherDerived> |
| EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE TensorReverseOp& operator = (const OtherDerived& other) |
| { |
| typedef TensorAssignOp<TensorReverseOp, const OtherDerived> Assign; |
| Assign assign(*this, other); |
| internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice()); |
| return *this; |
| } |
| |
| protected: |
| typename XprType::Nested m_xpr; |
| const ReverseDimensions m_reverse_dims; |
| }; |
| |
| // Eval as rvalue |
| template<typename ReverseDimensions, typename ArgType, typename Device> |
| struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device> |
| { |
| typedef TensorReverseOp<ReverseDimensions, ArgType> XprType; |
| typedef typename XprType::Index Index; |
| static const int NumDims = internal::array_size<ReverseDimensions>::value; |
| typedef DSizes<Index, NumDims> Dimensions; |
| typedef typename XprType::Scalar Scalar; |
| typedef typename XprType::CoeffReturnType CoeffReturnType; |
| typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType; |
| static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size; |
| |
| enum { |
| IsAligned = false, |
| PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess, |
| Layout = TensorEvaluator<ArgType, Device>::Layout, |
| CoordAccess = false, // to be implemented |
| RawAccess = false |
| }; |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, |
| const Device& device) |
| : m_impl(op.expression(), device), m_reverse(op.reverse()) |
| { |
| // Reversing a scalar isn't supported yet. It would be a no-op anyway. |
| EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE); |
| |
| // Compute strides |
| m_dimensions = m_impl.dimensions(); |
| if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { |
| m_strides[0] = 1; |
| for (int i = 1; i < NumDims; ++i) { |
| m_strides[i] = m_strides[i-1] * m_dimensions[i-1]; |
| } |
| } else { |
| m_strides[NumDims-1] = 1; |
| for (int i = NumDims - 2; i >= 0; --i) { |
| m_strides[i] = m_strides[i+1] * m_dimensions[i+1]; |
| } |
| } |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const Dimensions& dimensions() const { return m_dimensions; } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) { |
| m_impl.evalSubExprsIfNeeded(NULL); |
| return true; |
| } |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() { |
| m_impl.cleanup(); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index reverseIndex( |
| Index index) const { |
| eigen_assert(index < dimensions().TotalSize()); |
| Index inputIndex = 0; |
| if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { |
| for (int i = NumDims - 1; i > 0; --i) { |
| Index idx = index / m_strides[i]; |
| index -= idx * m_strides[i]; |
| if (m_reverse[i]) { |
| idx = m_dimensions[i] - idx - 1; |
| } |
| inputIndex += idx * m_strides[i] ; |
| } |
| if (m_reverse[0]) { |
| inputIndex += (m_dimensions[0] - index - 1); |
| } else { |
| inputIndex += index; |
| } |
| } else { |
| for (int i = 0; i < NumDims - 1; ++i) { |
| Index idx = index / m_strides[i]; |
| index -= idx * m_strides[i]; |
| if (m_reverse[i]) { |
| idx = m_dimensions[i] - idx - 1; |
| } |
| inputIndex += idx * m_strides[i] ; |
| } |
| if (m_reverse[NumDims-1]) { |
| inputIndex += (m_dimensions[NumDims-1] - index - 1); |
| } else { |
| inputIndex += index; |
| } |
| } |
| return inputIndex; |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff( |
| Index index) const { |
| return m_impl.coeff(reverseIndex(index)); |
| } |
| |
| template<int LoadMode> |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| PacketReturnType packet(Index index) const |
| { |
| EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE) |
| eigen_assert(index+PacketSize-1 < dimensions().TotalSize()); |
| |
| // TODO(ndjaitly): write a better packing routine that uses |
| // local structure. |
| EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type |
| values[PacketSize]; |
| for (int i = 0; i < PacketSize; ++i) { |
| values[i] = coeff(index+i); |
| } |
| PacketReturnType rslt = internal::pload<PacketReturnType>(values); |
| return rslt; |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const { |
| double compute_cost = NumDims * (2 * TensorOpCost::AddCost<Index>() + |
| 2 * TensorOpCost::MulCost<Index>() + |
| TensorOpCost::DivCost<Index>()); |
| for (int i = 0; i < NumDims; ++i) { |
| if (m_reverse[i]) { |
| compute_cost += 2 * TensorOpCost::AddCost<Index>(); |
| } |
| } |
| return m_impl.costPerCoeff(vectorized) + |
| TensorOpCost(0, 0, compute_cost, false /* vectorized */, PacketSize); |
| } |
| |
| EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; } |
| |
| protected: |
| Dimensions m_dimensions; |
| array<Index, NumDims> m_strides; |
| TensorEvaluator<ArgType, Device> m_impl; |
| ReverseDimensions m_reverse; |
| }; |
| |
| // Eval as lvalue |
| |
| template <typename ReverseDimensions, typename ArgType, typename Device> |
| struct TensorEvaluator<TensorReverseOp<ReverseDimensions, ArgType>, Device> |
| : public TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, |
| Device> { |
| typedef TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, |
| Device> Base; |
| typedef TensorReverseOp<ReverseDimensions, ArgType> XprType; |
| typedef typename XprType::Index Index; |
| static const int NumDims = internal::array_size<ReverseDimensions>::value; |
| typedef DSizes<Index, NumDims> Dimensions; |
| |
| enum { |
| IsAligned = false, |
| PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess, |
| Layout = TensorEvaluator<ArgType, Device>::Layout, |
| CoordAccess = false, // to be implemented |
| RawAccess = false |
| }; |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, |
| const Device& device) |
| : Base(op, device) {} |
| |
| typedef typename XprType::Scalar Scalar; |
| typedef typename XprType::CoeffReturnType CoeffReturnType; |
| typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType; |
| static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size; |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const Dimensions& dimensions() const { return this->m_dimensions; } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { |
| return this->m_impl.coeffRef(this->reverseIndex(index)); |
| } |
| |
| template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| void writePacket(Index index, const PacketReturnType& x) { |
| EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE) |
| eigen_assert(index+PacketSize-1 < dimensions().TotalSize()); |
| |
| // This code is pilfered from TensorMorphing.h |
| EIGEN_ALIGN_MAX CoeffReturnType values[PacketSize]; |
| internal::pstore<CoeffReturnType, PacketReturnType>(values, x); |
| for (int i = 0; i < PacketSize; ++i) { |
| this->coeffRef(index+i) = values[i]; |
| } |
| } |
| |
| }; |
| |
| |
| } // end namespace Eigen |
| |
| #endif // EIGEN_CXX11_TENSOR_TENSOR_REVERSE_H |