| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2017 Gagan Goel <gagan.nith@gmail.com> |
| // Copyright (C) 2017 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_TRACE_H |
| #define EIGEN_CXX11_TENSOR_TENSOR_TRACE_H |
| |
| #include "./InternalHeaderCheck.h" |
| |
| namespace Eigen { |
| |
| /** \class TensorTrace |
| * \ingroup CXX11_Tensor_Module |
| * |
| * \brief Tensor Trace class. |
| * |
| * |
| */ |
| |
| namespace internal { |
| template<typename Dims, typename XprType> |
| struct traits<TensorTraceOp<Dims, 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 std::remove_reference_t<Nested> Nested_; |
| static constexpr int NumDimensions = XprTraits::NumDimensions - array_size<Dims>::value; |
| static constexpr int Layout = XprTraits::Layout; |
| }; |
| |
| template<typename Dims, typename XprType> |
| struct eval<TensorTraceOp<Dims, XprType>, Eigen::Dense> |
| { |
| typedef const TensorTraceOp<Dims, XprType>& type; |
| }; |
| |
| template<typename Dims, typename XprType> |
| struct nested<TensorTraceOp<Dims, XprType>, 1, typename eval<TensorTraceOp<Dims, XprType> >::type> |
| { |
| typedef TensorTraceOp<Dims, XprType> type; |
| }; |
| |
| } // end namespace internal |
| |
| |
| template<typename Dims, typename XprType> |
| class TensorTraceOp : public TensorBase<TensorTraceOp<Dims, XprType> > |
| { |
| public: |
| typedef typename Eigen::internal::traits<TensorTraceOp>::Scalar Scalar; |
| typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; |
| typedef typename XprType::CoeffReturnType CoeffReturnType; |
| typedef typename Eigen::internal::nested<TensorTraceOp>::type Nested; |
| typedef typename Eigen::internal::traits<TensorTraceOp>::StorageKind StorageKind; |
| typedef typename Eigen::internal::traits<TensorTraceOp>::Index Index; |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorTraceOp(const XprType& expr, const Dims& dims) |
| : m_xpr(expr), m_dims(dims) { |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const Dims& dims() const { return m_dims; } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| const internal::remove_all_t<typename XprType::Nested>& expression() const { return m_xpr; } |
| |
| protected: |
| typename XprType::Nested m_xpr; |
| const Dims m_dims; |
| }; |
| |
| |
| // Eval as rvalue |
| template<typename Dims, typename ArgType, typename Device> |
| struct TensorEvaluator<const TensorTraceOp<Dims, ArgType>, Device> |
| { |
| typedef TensorTraceOp<Dims, ArgType> XprType; |
| static constexpr int NumInputDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value; |
| static constexpr int NumReducedDims = internal::array_size<Dims>::value; |
| static constexpr int NumOutputDims = NumInputDims - NumReducedDims; |
| typedef typename XprType::Index Index; |
| typedef DSizes<Index, NumOutputDims> Dimensions; |
| typedef typename XprType::Scalar Scalar; |
| typedef typename XprType::CoeffReturnType CoeffReturnType; |
| typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType; |
| static constexpr int PacketSize = internal::unpacket_traits<PacketReturnType>::size; |
| typedef StorageMemory<CoeffReturnType, Device> Storage; |
| typedef typename Storage::Type EvaluatorPointerType; |
| |
| static constexpr int Layout = TensorEvaluator<ArgType, Device>::Layout; |
| enum { |
| IsAligned = false, |
| PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess, |
| BlockAccess = false, |
| PreferBlockAccess = TensorEvaluator<ArgType, Device>::PreferBlockAccess, |
| CoordAccess = false, |
| RawAccess = false |
| }; |
| |
| //===- Tensor block evaluation strategy (see TensorBlock.h) -------------===// |
| typedef internal::TensorBlockNotImplemented TensorBlock; |
| //===--------------------------------------------------------------------===// |
| |
| EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device) |
| : m_impl(op.expression(), device), m_traceDim(1), m_device(device) |
| { |
| |
| EIGEN_STATIC_ASSERT((NumOutputDims >= 0), YOU_MADE_A_PROGRAMMING_MISTAKE); |
| EIGEN_STATIC_ASSERT((NumReducedDims >= 2) || ((NumReducedDims == 0) && (NumInputDims == 0)), YOU_MADE_A_PROGRAMMING_MISTAKE); |
| |
| for (int i = 0; i < NumInputDims; ++i) { |
| m_reduced[i] = false; |
| } |
| |
| const Dims& op_dims = op.dims(); |
| for (int i = 0; i < NumReducedDims; ++i) { |
| eigen_assert(op_dims[i] >= 0); |
| eigen_assert(op_dims[i] < NumInputDims); |
| m_reduced[op_dims[i]] = true; |
| } |
| |
| // All the dimensions should be distinct to compute the trace |
| int num_distinct_reduce_dims = 0; |
| for (int i = 0; i < NumInputDims; ++i) { |
| if (m_reduced[i]) { |
| ++num_distinct_reduce_dims; |
| } |
| } |
| |
| EIGEN_ONLY_USED_FOR_DEBUG(num_distinct_reduce_dims); |
| eigen_assert(num_distinct_reduce_dims == NumReducedDims); |
| |
| // Compute the dimensions of the result. |
| const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions(); |
| |
| int output_index = 0; |
| int reduced_index = 0; |
| for (int i = 0; i < NumInputDims; ++i) { |
| if (m_reduced[i]) { |
| m_reducedDims[reduced_index] = input_dims[i]; |
| if (reduced_index > 0) { |
| // All the trace dimensions must have the same size |
| eigen_assert(m_reducedDims[0] == m_reducedDims[reduced_index]); |
| } |
| ++reduced_index; |
| } |
| else { |
| m_dimensions[output_index] = input_dims[i]; |
| ++output_index; |
| } |
| } |
| |
| if (NumReducedDims != 0) { |
| m_traceDim = m_reducedDims[0]; |
| } |
| |
| // Compute the output strides |
| if (NumOutputDims > 0) { |
| if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { |
| m_outputStrides[0] = 1; |
| for (int i = 1; i < NumOutputDims; ++i) { |
| m_outputStrides[i] = m_outputStrides[i - 1] * m_dimensions[i - 1]; |
| } |
| } |
| else { |
| m_outputStrides.back() = 1; |
| for (int i = NumOutputDims - 2; i >= 0; --i) { |
| m_outputStrides[i] = m_outputStrides[i + 1] * m_dimensions[i + 1]; |
| } |
| } |
| } |
| |
| // Compute the input strides |
| if (NumInputDims > 0) { |
| array<Index, NumInputDims> input_strides; |
| if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { |
| input_strides[0] = 1; |
| for (int i = 1; i < NumInputDims; ++i) { |
| input_strides[i] = input_strides[i - 1] * input_dims[i - 1]; |
| } |
| } |
| else { |
| input_strides.back() = 1; |
| for (int i = NumInputDims - 2; i >= 0; --i) { |
| input_strides[i] = input_strides[i + 1] * input_dims[i + 1]; |
| } |
| } |
| |
| output_index = 0; |
| reduced_index = 0; |
| for (int i = 0; i < NumInputDims; ++i) { |
| if(m_reduced[i]) { |
| m_reducedStrides[reduced_index] = input_strides[i]; |
| ++reduced_index; |
| } |
| else { |
| m_preservedStrides[output_index] = input_strides[i]; |
| ++output_index; |
| } |
| } |
| } |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { |
| return m_dimensions; |
| } |
| |
| EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType /*data*/) { |
| m_impl.evalSubExprsIfNeeded(NULL); |
| return true; |
| } |
| |
| EIGEN_STRONG_INLINE void cleanup() { |
| m_impl.cleanup(); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const |
| { |
| // Initialize the result |
| CoeffReturnType result = internal::cast<int, CoeffReturnType>(0); |
| Index index_stride = 0; |
| for (int i = 0; i < NumReducedDims; ++i) { |
| index_stride += m_reducedStrides[i]; |
| } |
| |
| // If trace is requested along all dimensions, starting index would be 0 |
| Index cur_index = 0; |
| if (NumOutputDims != 0) |
| cur_index = firstInput(index); |
| for (Index i = 0; i < m_traceDim; ++i) { |
| result += m_impl.coeff(cur_index); |
| cur_index += index_stride; |
| } |
| |
| return result; |
| } |
| |
| template<int LoadMode> |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const { |
| eigen_assert(index + PacketSize - 1 < dimensions().TotalSize()); |
| |
| EIGEN_ALIGN_MAX std::remove_const_t<CoeffReturnType> values[PacketSize]; |
| for (int i = 0; i < PacketSize; ++i) { |
| values[i] = coeff(index + i); |
| } |
| PacketReturnType result = internal::ploadt<PacketReturnType, LoadMode>(values); |
| return 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_impl.bind(cgh); |
| } |
| #endif |
| |
| protected: |
| // Given the output index, finds the first index in the input tensor used to compute the trace |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index firstInput(Index index) const { |
| Index startInput = 0; |
| if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { |
| for (int i = NumOutputDims - 1; i > 0; --i) { |
| const Index idx = index / m_outputStrides[i]; |
| startInput += idx * m_preservedStrides[i]; |
| index -= idx * m_outputStrides[i]; |
| } |
| startInput += index * m_preservedStrides[0]; |
| } |
| else { |
| for (int i = 0; i < NumOutputDims - 1; ++i) { |
| const Index idx = index / m_outputStrides[i]; |
| startInput += idx * m_preservedStrides[i]; |
| index -= idx * m_outputStrides[i]; |
| } |
| startInput += index * m_preservedStrides[NumOutputDims - 1]; |
| } |
| return startInput; |
| } |
| |
| Dimensions m_dimensions; |
| TensorEvaluator<ArgType, Device> m_impl; |
| // Initialize the size of the trace dimension |
| Index m_traceDim; |
| const Device EIGEN_DEVICE_REF m_device; |
| array<bool, NumInputDims> m_reduced; |
| array<Index, NumReducedDims> m_reducedDims; |
| array<Index, NumOutputDims> m_outputStrides; |
| array<Index, NumReducedDims> m_reducedStrides; |
| array<Index, NumOutputDims> m_preservedStrides; |
| }; |
| |
| |
| } // End namespace Eigen |
| |
| #endif // EIGEN_CXX11_TENSOR_TENSOR_TRACE_H |