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249 lines
9.1 KiB
C++
249 lines
9.1 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_PATCH_H
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#define EIGEN_CXX11_TENSOR_TENSOR_PATCH_H
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namespace Eigen {
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/** \class TensorPatch
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* \ingroup CXX11_Tensor_Module
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*
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* \brief Tensor patch 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 PatchDim, typename XprType>
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struct traits<TensorPatchOp<PatchDim, XprType> > : public traits<XprType>
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{
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typedef typename XprType::Scalar Scalar;
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typedef traits<XprType> XprTraits;
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typedef typename packet_traits<Scalar>::type Packet;
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typedef typename XprTraits::StorageKind StorageKind;
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typedef typename XprTraits::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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static const int NumDimensions = XprTraits::NumDimensions + 1;
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static const int Layout = XprTraits::Layout;
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};
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template<typename PatchDim, typename XprType>
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struct eval<TensorPatchOp<PatchDim, XprType>, Eigen::Dense>
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{
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typedef const TensorPatchOp<PatchDim, XprType>& type;
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};
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template<typename PatchDim, typename XprType>
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struct nested<TensorPatchOp<PatchDim, XprType>, 1, typename eval<TensorPatchOp<PatchDim, XprType> >::type>
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{
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typedef TensorPatchOp<PatchDim, XprType> type;
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};
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} // end namespace internal
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template<typename PatchDim, typename XprType>
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class TensorPatchOp : public TensorBase<TensorPatchOp<PatchDim, XprType>, ReadOnlyAccessors>
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{
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public:
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typedef typename Eigen::internal::traits<TensorPatchOp>::Scalar Scalar;
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typedef typename Eigen::internal::traits<TensorPatchOp>::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<TensorPatchOp>::type Nested;
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typedef typename Eigen::internal::traits<TensorPatchOp>::StorageKind StorageKind;
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typedef typename Eigen::internal::traits<TensorPatchOp>::Index Index;
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorPatchOp(const XprType& expr, const PatchDim& patch_dims)
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: m_xpr(expr), m_patch_dims(patch_dims) {}
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EIGEN_DEVICE_FUNC
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const PatchDim& patch_dims() const { return m_patch_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 PatchDim m_patch_dims;
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};
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// Eval as rvalue
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template<typename PatchDim, typename ArgType, typename Device>
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struct TensorEvaluator<const TensorPatchOp<PatchDim, ArgType>, Device>
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{
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typedef TensorPatchOp<PatchDim, 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 + 1;
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typedef DSizes<Index, NumDims> Dimensions;
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typedef typename XprType::Scalar Scalar;
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enum {
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IsAligned = false,
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PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
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Layout = TensorEvaluator<ArgType, Device>::Layout,
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CoordAccess = true,
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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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// Only column major tensors are supported for now.
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EIGEN_STATIC_ASSERT((static_cast<int>(Layout) == static_cast<int>(ColMajor)), YOU_MADE_A_PROGRAMMING_MISTAKE);
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Index num_patches = 1;
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const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
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const PatchDim& patch_dims = op.patch_dims();
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for (int i = 0; i < NumDims-1; ++i) {
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m_dimensions[i] = patch_dims[i];
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num_patches *= (input_dims[i] - patch_dims[i] + 1);
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}
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m_dimensions[NumDims-1] = num_patches;
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m_inputStrides[0] = 1;
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m_patchStrides[0] = 1;
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for (int i = 1; i < NumDims-1; ++i) {
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m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1];
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m_patchStrides[i] = m_patchStrides[i-1] * (input_dims[i-1] - patch_dims[i-1] + 1);
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}
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m_outputStrides[0] = 1;
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for (int i = 1; i < NumDims; ++i) {
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m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1];
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}
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}
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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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// Find the location of the first element of the patch.
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Index patchIndex = index / m_outputStrides[NumDims - 1];
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// Find the offset of the element wrt the location of the first element.
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Index patchOffset = index - patchIndex * m_outputStrides[NumDims - 1];
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Index inputIndex = 0;
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for (int i = NumDims - 2; i > 0; --i) {
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const Index patchIdx = patchIndex / m_patchStrides[i];
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patchIndex -= patchIdx * m_patchStrides[i];
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const Index offsetIdx = patchOffset / m_outputStrides[i];
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patchOffset -= offsetIdx * m_outputStrides[i];
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inputIndex += (patchIdx + offsetIdx) * m_inputStrides[i];
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}
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inputIndex += (patchIndex + patchOffset);
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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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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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Index indices[2] = {index, index + packetSize - 1};
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Index patchIndices[2] = {indices[0] / m_outputStrides[NumDims - 1],
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indices[1] / m_outputStrides[NumDims - 1]};
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Index patchOffsets[2] = {indices[0] - patchIndices[0] * m_outputStrides[NumDims - 1],
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indices[1] - patchIndices[1] * m_outputStrides[NumDims - 1]};
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Index inputIndices[2] = {0, 0};
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for (int i = NumDims - 2; i > 0; --i) {
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const Index patchIdx[2] = {patchIndices[0] / m_patchStrides[i],
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patchIndices[1] / m_patchStrides[i]};
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patchIndices[0] -= patchIdx[0] * m_patchStrides[i];
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patchIndices[1] -= patchIdx[1] * m_patchStrides[i];
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const Index offsetIdx[2] = {patchOffsets[0] / m_outputStrides[i],
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patchOffsets[1] / m_outputStrides[i]};
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patchOffsets[0] -= offsetIdx[0] * m_outputStrides[i];
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patchOffsets[1] -= offsetIdx[1] * m_outputStrides[i];
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inputIndices[0] += (patchIdx[0] + offsetIdx[0]) * m_inputStrides[i];
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inputIndices[1] += (patchIdx[1] + offsetIdx[1]) * m_inputStrides[i];
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}
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inputIndices[0] += (patchIndices[0] + patchOffsets[0]);
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inputIndices[1] += (patchIndices[1] + patchOffsets[1]);
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if (inputIndices[1] - inputIndices[0] == packetSize - 1) {
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PacketReturnType rslt = m_impl.template packet<Unaligned>(inputIndices[0]);
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return rslt;
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}
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else {
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EIGEN_ALIGN_DEFAULT CoeffReturnType values[packetSize];
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values[0] = m_impl.coeff(inputIndices[0]);
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values[packetSize-1] = m_impl.coeff(inputIndices[1]);
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for (int i = 1; i < packetSize-1; ++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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}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(const array<Index, NumDims>& coords) const
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{
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// Location of the first element of the patch.
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const Index patchIndex = coords[NumDims - 1];
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if (TensorEvaluator<ArgType, Device>::CoordAccess) {
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array<Index, NumDims-1> inputCoords;
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for (int i = NumDims - 2; i > 0; --i) {
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const Index patchIdx = patchIndex / m_patchStrides[i];
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patchIndex -= patchIdx * m_patchStrides[i];
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const Index offsetIdx = coords[i];
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inputCoords[i] = coords[i] + patchIdx;
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}
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inputCoords[0] = (patchIndex + coords[0]);
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return m_impl.coeff(inputCoords);
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}
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else {
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Index inputIndex = 0;
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for (int i = NumDims - 2; i > 0; --i) {
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const Index patchIdx = patchIndex / m_patchStrides[i];
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patchIndex -= patchIdx * m_patchStrides[i];
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const Index offsetIdx = coords[i];
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inputIndex += (patchIdx + offsetIdx) * m_inputStrides[i];
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}
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inputIndex += (patchIndex + coords[0]);
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return m_impl.coeff(inputIndex);
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}
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}
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EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
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protected:
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Dimensions m_dimensions;
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array<Index, NumDims> m_outputStrides;
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array<Index, NumDims-1> m_inputStrides;
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array<Index, NumDims-1> m_patchStrides;
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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_PATCH_H
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