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398 lines
15 KiB
C++
398 lines
15 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 padding with a constant value 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 traits<XprType> XprTraits;
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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;
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static const int Layout = XprTraits::Layout;
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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::NumTraits<Scalar>::Real RealScalar;
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typedef typename XprType::CoeffReturnType CoeffReturnType;
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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, const Scalar padding_value)
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: m_xpr(expr), m_padding_dims(padding_dims), m_padding_value(padding_value) {}
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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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Scalar padding_value() const { return m_padding_value; }
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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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const Scalar m_padding_value;
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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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typedef typename XprType::Scalar Scalar;
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typedef typename XprType::CoeffReturnType CoeffReturnType;
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typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
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static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
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enum {
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IsAligned = true,
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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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RawAccess = 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), m_padding(op.padding()), m_paddingValue(op.padding_value())
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{
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// The padding op doesn't change the rank of the tensor. Directly padding a scalar would lead
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// to a vector, which doesn't make sense. Instead one should reshape the scalar into a vector
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// of 1 element first and then pad.
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EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
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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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if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
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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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} else {
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m_inputStrides[NumDims - 1] = 1;
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m_outputStrides[NumDims] = 1;
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for (int i = NumDims - 2; i >= 0; --i) {
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m_inputStrides[i] = m_inputStrides[i+1] * input_dims[i+1];
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m_outputStrides[i+1] = m_outputStrides[i+2] * m_dimensions[i+1];
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}
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m_outputStrides[0] = m_outputStrides[1] * m_dimensions[0];
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}
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}
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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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eigen_assert(index < dimensions().TotalSize());
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Index inputIndex = 0;
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if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
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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 (isPaddingAtIndexForDim(idx, i)) {
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return m_paddingValue;
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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 (isPaddingAtIndexForDim(index, 0)) {
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return m_paddingValue;
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}
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inputIndex += (index - m_padding[0].first);
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} else {
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for (int i = 0; i < NumDims - 1; ++i) {
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const Index idx = index / m_outputStrides[i+1];
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if (isPaddingAtIndexForDim(idx, i)) {
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return m_paddingValue;
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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+1];
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}
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if (isPaddingAtIndexForDim(index, NumDims-1)) {
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return m_paddingValue;
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}
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inputIndex += (index - m_padding[NumDims-1].first);
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}
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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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if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
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return packetColMajor(index);
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}
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return packetRowMajor(index);
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}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
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TensorOpCost cost = m_impl.costPerCoeff(vectorized);
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if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
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for (int i = 0; i < NumDims; ++i)
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updateCostPerDimension(cost, i, i == 0);
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} else {
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for (int i = NumDims - 1; i >= 0; --i)
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updateCostPerDimension(cost, i, i == NumDims - 1);
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}
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return cost;
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}
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EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
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private:
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EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool isPaddingAtIndexForDim(
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Index index, int dim_index) const {
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#if defined(EIGEN_HAS_INDEX_LIST)
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return (!internal::index_pair_first_statically_eq<PaddingDimensions>(dim_index, 0) &&
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index < m_padding[dim_index].first) ||
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(!internal::index_pair_second_statically_eq<PaddingDimensions>(dim_index, 0) &&
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index >= m_dimensions[dim_index] - m_padding[dim_index].second);
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#else
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return (index < m_padding[dim_index].first) ||
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(index >= m_dimensions[dim_index] - m_padding[dim_index].second);
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#endif
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}
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EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool isLeftPaddingCompileTimeZero(
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int dim_index) const {
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#if defined(EIGEN_HAS_INDEX_LIST)
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return internal::index_pair_first_statically_eq<PaddingDimensions>(dim_index, 0);
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#else
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EIGEN_UNUSED_VARIABLE(dim_index);
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return false;
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#endif
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}
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EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool isRightPaddingCompileTimeZero(
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int dim_index) const {
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#if defined(EIGEN_HAS_INDEX_LIST)
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return internal::index_pair_second_statically_eq<PaddingDimensions>(dim_index, 0);
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#else
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EIGEN_UNUSED_VARIABLE(dim_index);
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return false;
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#endif
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}
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void updateCostPerDimension(TensorOpCost& cost, int i, bool first) const {
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const double in = static_cast<double>(m_impl.dimensions()[i]);
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const double out = in + m_padding[i].first + m_padding[i].second;
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if (out == 0)
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return;
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const double reduction = in / out;
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cost *= reduction;
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if (first) {
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cost += TensorOpCost(0, 0, 2 * TensorOpCost::AddCost<Index>() +
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reduction * (1 * TensorOpCost::AddCost<Index>()));
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} else {
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cost += TensorOpCost(0, 0, 2 * TensorOpCost::AddCost<Index>() +
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2 * TensorOpCost::MulCost<Index>() +
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reduction * (2 * TensorOpCost::MulCost<Index>() +
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1 * TensorOpCost::DivCost<Index>()));
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}
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}
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protected:
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetColMajor(Index index) const
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{
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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 Index first = index;
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const Index last = index + PacketSize - 1;
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const Index lastPaddedLeft = m_padding[i].first * m_outputStrides[i];
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const Index firstPaddedRight = (m_dimensions[i] - m_padding[i].second) * m_outputStrides[i];
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const Index lastPaddedRight = m_outputStrides[i+1];
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if (!isLeftPaddingCompileTimeZero(i) && last < lastPaddedLeft) {
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// all the coefficient are in the padding zone.
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return internal::pset1<PacketReturnType>(m_paddingValue);
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}
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else if (!isRightPaddingCompileTimeZero(i) && first >= firstPaddedRight && last < lastPaddedRight) {
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// all the coefficient are in the padding zone.
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return internal::pset1<PacketReturnType>(m_paddingValue);
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}
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else if ((isLeftPaddingCompileTimeZero(i) && isRightPaddingCompileTimeZero(i)) || (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 Index lastPaddedLeft = m_padding[0].first;
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const Index firstPaddedRight = (m_dimensions[0] - m_padding[0].second);
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const Index lastPaddedRight = m_outputStrides[1];
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if (!isLeftPaddingCompileTimeZero(0) && last < lastPaddedLeft) {
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// all the coefficient are in the padding zone.
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return internal::pset1<PacketReturnType>(m_paddingValue);
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}
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else if (!isRightPaddingCompileTimeZero(0) && first >= firstPaddedRight && last < lastPaddedRight) {
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// all the coefficient are in the padding zone.
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return internal::pset1<PacketReturnType>(m_paddingValue);
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}
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else if ((isLeftPaddingCompileTimeZero(0) && isRightPaddingCompileTimeZero(0)) || (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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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetRowMajor(Index index) const
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{
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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 = 0; i < NumDims - 1; ++i) {
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const Index first = index;
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const Index last = index + PacketSize - 1;
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const Index lastPaddedLeft = m_padding[i].first * m_outputStrides[i+1];
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const Index firstPaddedRight = (m_dimensions[i] - m_padding[i].second) * m_outputStrides[i+1];
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const Index lastPaddedRight = m_outputStrides[i];
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if (!isLeftPaddingCompileTimeZero(i) && last < lastPaddedLeft) {
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// all the coefficient are in the padding zone.
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return internal::pset1<PacketReturnType>(m_paddingValue);
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}
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else if (!isRightPaddingCompileTimeZero(i) && first >= firstPaddedRight && last < lastPaddedRight) {
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// all the coefficient are in the padding zone.
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return internal::pset1<PacketReturnType>(m_paddingValue);
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}
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else if ((isLeftPaddingCompileTimeZero(i) && isRightPaddingCompileTimeZero(i)) || (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+1];
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inputIndex += (idx - m_padding[i].first) * m_inputStrides[i];
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index -= idx * m_outputStrides[i+1];
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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 Index lastPaddedLeft = m_padding[NumDims-1].first;
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const Index firstPaddedRight = (m_dimensions[NumDims-1] - m_padding[NumDims-1].second);
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const Index lastPaddedRight = m_outputStrides[NumDims-1];
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if (!isLeftPaddingCompileTimeZero(NumDims-1) && last < lastPaddedLeft) {
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// all the coefficient are in the padding zone.
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return internal::pset1<PacketReturnType>(m_paddingValue);
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}
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else if (!isRightPaddingCompileTimeZero(NumDims-1) && first >= firstPaddedRight && last < lastPaddedRight) {
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// all the coefficient are in the padding zone.
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return internal::pset1<PacketReturnType>(m_paddingValue);
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}
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else if ((isLeftPaddingCompileTimeZero(NumDims-1) && isRightPaddingCompileTimeZero(NumDims-1)) || (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[NumDims-1].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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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetWithPossibleZero(Index index) const
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{
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EIGEN_ALIGN_MAX 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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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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PaddingDimensions m_padding;
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Scalar m_paddingValue;
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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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