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231 lines
8.3 KiB
C++
231 lines
8.3 KiB
C++
// 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_PADDING_H
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#define EIGEN_CXX11_TENSOR_TENSOR_PADDING_H
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namespace Eigen {
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/** \class TensorPadding
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* \ingroup CXX11_Tensor_Module
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*
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* \brief Tensor padding class.
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* At the moment only 0-padding is supported.
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*
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*/
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namespace internal {
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template<typename PaddingDimensions, typename XprType>
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struct traits<TensorPaddingOp<PaddingDimensions, 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 PaddingDimensions, typename XprType>
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struct eval<TensorPaddingOp<PaddingDimensions, XprType>, Eigen::Dense>
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{
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typedef const TensorPaddingOp<PaddingDimensions, XprType>& type;
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};
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template<typename PaddingDimensions, typename XprType>
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struct nested<TensorPaddingOp<PaddingDimensions, XprType>, 1, typename eval<TensorPaddingOp<PaddingDimensions, XprType> >::type>
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{
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typedef TensorPaddingOp<PaddingDimensions, XprType> type;
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};
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} // end namespace internal
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template<typename PaddingDimensions, typename XprType>
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class TensorPaddingOp : public TensorBase<TensorPaddingOp<PaddingDimensions, XprType>, ReadOnlyAccessors>
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{
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public:
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typedef typename Eigen::internal::traits<TensorPaddingOp>::Scalar Scalar;
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typedef typename Eigen::internal::traits<TensorPaddingOp>::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<TensorPaddingOp>::type Nested;
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typedef typename Eigen::internal::traits<TensorPaddingOp>::StorageKind StorageKind;
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typedef typename Eigen::internal::traits<TensorPaddingOp>::Index Index;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorPaddingOp(const XprType& expr, const PaddingDimensions& padding_dims)
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: m_xpr(expr), m_padding_dims(padding_dims) {}
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EIGEN_DEVICE_FUNC
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const PaddingDimensions& padding() const { return m_padding_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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protected:
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typename XprType::Nested m_xpr;
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const PaddingDimensions m_padding_dims;
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};
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// Eval as rvalue
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template<typename PaddingDimensions, typename ArgType, typename Device>
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struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device>
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{
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typedef TensorPaddingOp<PaddingDimensions, ArgType> XprType;
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typedef typename XprType::Index Index;
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static const int NumDims = internal::array_size<PaddingDimensions>::value;
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typedef DSizes<Index, NumDims> Dimensions;
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enum {
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IsAligned = false,
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PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
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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), m_padding(op.padding())
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{
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// Compute dimensions
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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] += m_padding[i].first + m_padding[i].second;
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}
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const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
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m_inputStrides[0] = 1;
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m_outputStrides[0] = 1;
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for (int i = 1; i < NumDims; ++i) {
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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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}
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m_outputStrides[NumDims] = m_outputStrides[NumDims-1] * m_dimensions[NumDims-1];
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}
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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*) {
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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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if (idx < m_padding[i].first || idx >= m_dimensions[i] - m_padding[i].second) {
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return Scalar(0);
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}
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inputIndex += (idx - m_padding[i].first) * m_inputStrides[i];
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index -= idx * m_outputStrides[i];
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}
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if (index < m_padding[0].first || index >= m_dimensions[0] - m_padding[0].second) {
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return Scalar(0);
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}
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inputIndex += (index - m_padding[0].first);
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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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static const int packetSize = internal::unpacket_traits<PacketReturnType>::size;
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EIGEN_STATIC_ASSERT(packetSize > 1, YOU_MADE_A_PROGRAMMING_MISTAKE)
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eigen_assert(index+packetSize-1 < dimensions().TotalSize());
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const Index initialIndex = index;
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Index inputIndex = 0;
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for (int i = NumDims - 1; i > 0; --i) {
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const int first = index;
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const int last = index + packetSize - 1;
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const int lastPaddedLeft = m_padding[i].first * m_outputStrides[i];
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const int firstPaddedRight = (m_dimensions[i] - m_padding[i].second) * m_outputStrides[i];
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const int lastPaddedRight = m_outputStrides[i+1];
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if (last < lastPaddedLeft) {
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// all the coefficient are in the padding zone.
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return internal::pset1<PacketReturnType>(Scalar(0));
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}
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else if (first >= firstPaddedRight && last < lastPaddedRight) {
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// all the coefficient are in the padding zone.
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return internal::pset1<PacketReturnType>(Scalar(0));
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}
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else if (first >= lastPaddedLeft && last < firstPaddedRight) {
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// all the coefficient are between the 2 padding zones.
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const Index idx = index / m_outputStrides[i];
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inputIndex += (idx - m_padding[i].first) * m_inputStrides[i];
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index -= idx * m_outputStrides[i];
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}
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else {
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// Every other case
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return packetWithPossibleZero(initialIndex);
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}
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}
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const Index last = index + packetSize - 1;
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const Index first = index;
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const int lastPaddedLeft = m_padding[0].first;
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const int firstPaddedRight = (m_dimensions[0] - m_padding[0].second);
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const int lastPaddedRight = m_outputStrides[1];
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if (last < lastPaddedLeft) {
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// all the coefficient are in the padding zone.
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return internal::pset1<PacketReturnType>(Scalar(0));
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}
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else if (first >= firstPaddedRight && last < lastPaddedRight) {
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// all the coefficient are in the padding zone.
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return internal::pset1<PacketReturnType>(Scalar(0));
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}
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else if (first >= lastPaddedLeft && last < firstPaddedRight) {
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// all the coefficient are between the 2 padding zones.
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inputIndex += (index - m_padding[0].first);
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return m_impl.template packet<Unaligned>(inputIndex);
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}
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// Every other case
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return packetWithPossibleZero(initialIndex);
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}
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Scalar* data() const { return NULL; }
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protected:
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetWithPossibleZero(Index index) const
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{
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static const int packetSize = internal::unpacket_traits<PacketReturnType>::size;
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EIGEN_ALIGN_DEFAULT typename internal::remove_const<CoeffReturnType>::type values[packetSize];
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for (int i = 0; i < packetSize; ++i) {
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values[i] = coeff(index+i);
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}
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PacketReturnType rslt = internal::pload<PacketReturnType>(values);
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return rslt;
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}
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PaddingDimensions m_padding;
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Dimensions m_dimensions;
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array<Index, NumDims+1> 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_PADDING_H
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