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173 lines
5.7 KiB
C
173 lines
5.7 KiB
C
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// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#ifndef EIGEN_CXX11_TENSOR_TENSOR_STRIDING_H
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#define EIGEN_CXX11_TENSOR_TENSOR_STRIDING_H
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namespace Eigen {
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/** \class TensorStriding
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* \ingroup CXX11_Tensor_Module
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*
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* \brief Tensor striding class.
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*
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*
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*/
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namespace internal {
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template<typename Strides, typename XprType>
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struct traits<TensorStridingOp<Strides, XprType> > : public traits<XprType>
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{
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typedef typename XprType::Scalar Scalar;
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typedef typename internal::packet_traits<Scalar>::type Packet;
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typedef typename traits<XprType>::StorageKind StorageKind;
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typedef typename traits<XprType>::Index Index;
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typedef typename XprType::Nested Nested;
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typedef typename remove_reference<Nested>::type _Nested;
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};
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template<typename Strides, typename XprType>
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struct eval<TensorStridingOp<Strides, XprType>, Eigen::Dense>
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{
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typedef const TensorStridingOp<Strides, XprType>& type;
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};
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template<typename Strides, typename XprType>
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struct nested<TensorStridingOp<Strides, XprType>, 1, typename eval<TensorStridingOp<Strides, XprType> >::type>
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{
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typedef TensorStridingOp<Strides, XprType> type;
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};
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} // end namespace internal
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template<typename Strides, typename XprType>
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class TensorStridingOp : public TensorBase<TensorStridingOp<Strides, XprType>, WriteAccessors>
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{
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public:
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typedef typename Eigen::internal::traits<TensorStridingOp>::Scalar Scalar;
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typedef typename Eigen::internal::traits<TensorStridingOp>::Packet Packet;
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typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
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typedef typename XprType::CoeffReturnType CoeffReturnType;
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typedef typename XprType::PacketReturnType PacketReturnType;
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typedef typename Eigen::internal::nested<TensorStridingOp>::type Nested;
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typedef typename Eigen::internal::traits<TensorStridingOp>::StorageKind StorageKind;
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typedef typename Eigen::internal::traits<TensorStridingOp>::Index Index;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorStridingOp(const XprType& expr, const Strides& dims)
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: m_xpr(expr), m_dims(dims) {}
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EIGEN_DEVICE_FUNC
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const Strides& strides() const { return m_dims; }
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EIGEN_DEVICE_FUNC
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const typename internal::remove_all<typename XprType::Nested>::type&
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expression() const { return m_xpr; }
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template<typename OtherDerived>
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EIGEN_DEVICE_FUNC
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EIGEN_STRONG_INLINE TensorStridingOp& operator = (const OtherDerived& other)
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{
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typedef TensorAssignOp<TensorStridingOp, const OtherDerived> Assign;
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Assign assign(*this, other);
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internal::TensorExecutor<const Assign, DefaultDevice, false>::run(assign, DefaultDevice());
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return *this;
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}
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protected:
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typename XprType::Nested m_xpr;
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const Strides m_dims;
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};
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// Eval as rvalue
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template<typename Strides, typename ArgType, typename Device>
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struct TensorEvaluator<const TensorStridingOp<Strides, ArgType>, Device>
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{
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typedef TensorStridingOp<Strides, ArgType> XprType;
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typedef typename XprType::Index Index;
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static const int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
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typedef DSizes<Index, NumDims> Dimensions;
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enum {
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IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/false,
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PacketAccess = /*TensorEvaluator<ArgType, Device>::PacketAccess*/false,
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};
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
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: m_impl(op.expression(), device)
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{
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m_dimensions = m_impl.dimensions();
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for (int i = 0; i < NumDims; ++i) {
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m_dimensions[i] = ceilf(static_cast<float>(m_dimensions[i]) / op.strides()[i]);
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}
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const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
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for (int i = 0; i < NumDims; ++i) {
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if (i > 0) {
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m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1];
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m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1];
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} else {
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m_inputStrides[0] = 1;
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m_outputStrides[0] = 1;
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}
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}
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for (int i = 0; i < NumDims; ++i) {
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m_inputStrides[i] *= op.strides()[i];
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}
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}
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// typedef typename XprType::Index Index;
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typedef typename XprType::Scalar Scalar;
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typedef typename XprType::CoeffReturnType CoeffReturnType;
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typedef typename XprType::PacketReturnType PacketReturnType;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* data) {
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m_impl.evalSubExprsIfNeeded(NULL);
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return true;
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}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
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m_impl.cleanup();
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}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
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{
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Index inputIndex = 0;
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for (int i = NumDims - 1; i > 0; --i) {
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const Index idx = index / m_outputStrides[i];
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inputIndex += idx * m_inputStrides[i];
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index -= idx * m_outputStrides[i];
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}
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inputIndex += index * m_inputStrides[0];
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return m_impl.coeff(inputIndex);
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}
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/* template<int LoadMode>
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
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{
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return m_impl.template packet<LoadMode>(index);
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}*/
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Scalar* data() const { return NULL; }
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protected:
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// Strides m_strides;
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Dimensions m_dimensions;
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array<Index, NumDims> m_outputStrides;
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array<Index, NumDims> m_inputStrides;
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TensorEvaluator<ArgType, Device> m_impl;
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};
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} // end namespace Eigen
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#endif // EIGEN_CXX11_TENSOR_TENSOR_STRIDING_H
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