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Diffstat (limited to 'unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h')
| -rw-r--r-- | unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h | 397 |
1 files changed, 397 insertions, 0 deletions
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h b/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h new file mode 100644 index 000000000..647bcf108 --- /dev/null +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h @@ -0,0 +1,397 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2014 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_PADDING_H +#define EIGEN_CXX11_TENSOR_TENSOR_PADDING_H + +namespace Eigen { + +/** \class TensorPadding + * \ingroup CXX11_Tensor_Module + * + * \brief Tensor padding class. + * At the moment only padding with a constant value is supported. + * + */ +namespace internal { +template<typename PaddingDimensions, typename XprType> +struct traits<TensorPaddingOp<PaddingDimensions, 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 typename remove_reference<Nested>::type _Nested; + static const int NumDimensions = XprTraits::NumDimensions; + static const int Layout = XprTraits::Layout; +}; + +template<typename PaddingDimensions, typename XprType> +struct eval<TensorPaddingOp<PaddingDimensions, XprType>, Eigen::Dense> +{ + typedef const TensorPaddingOp<PaddingDimensions, XprType>& type; +}; + +template<typename PaddingDimensions, typename XprType> +struct nested<TensorPaddingOp<PaddingDimensions, XprType>, 1, typename eval<TensorPaddingOp<PaddingDimensions, XprType> >::type> +{ + typedef TensorPaddingOp<PaddingDimensions, XprType> type; +}; + +} // end namespace internal + + + +template<typename PaddingDimensions, typename XprType> +class TensorPaddingOp : public TensorBase<TensorPaddingOp<PaddingDimensions, XprType>, ReadOnlyAccessors> +{ + public: + typedef typename Eigen::internal::traits<TensorPaddingOp>::Scalar Scalar; + typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + typedef typename Eigen::internal::nested<TensorPaddingOp>::type Nested; + typedef typename Eigen::internal::traits<TensorPaddingOp>::StorageKind StorageKind; + typedef typename Eigen::internal::traits<TensorPaddingOp>::Index Index; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorPaddingOp(const XprType& expr, const PaddingDimensions& padding_dims, const Scalar padding_value) + : m_xpr(expr), m_padding_dims(padding_dims), m_padding_value(padding_value) {} + + EIGEN_DEVICE_FUNC + const PaddingDimensions& padding() const { return m_padding_dims; } + EIGEN_DEVICE_FUNC + Scalar padding_value() const { return m_padding_value; } + + EIGEN_DEVICE_FUNC + const typename internal::remove_all<typename XprType::Nested>::type& + expression() const { return m_xpr; } + + protected: + typename XprType::Nested m_xpr; + const PaddingDimensions m_padding_dims; + const Scalar m_padding_value; +}; + + +// Eval as rvalue +template<typename PaddingDimensions, typename ArgType, typename Device> +struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device> +{ + typedef TensorPaddingOp<PaddingDimensions, ArgType> XprType; + typedef typename XprType::Index Index; + static const int NumDims = internal::array_size<PaddingDimensions>::value; + typedef DSizes<Index, NumDims> Dimensions; + typedef typename XprType::Scalar Scalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType; + static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size; + + enum { + IsAligned = true, + PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess, + Layout = TensorEvaluator<ArgType, Device>::Layout, + CoordAccess = true, + RawAccess = false + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device) + : m_impl(op.expression(), device), m_padding(op.padding()), m_paddingValue(op.padding_value()) + { + // The padding op doesn't change the rank of the tensor. Directly padding a scalar would lead + // to a vector, which doesn't make sense. Instead one should reshape the scalar into a vector + // of 1 element first and then pad. + EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE); + + // Compute dimensions + m_dimensions = m_impl.dimensions(); + for (int i = 0; i < NumDims; ++i) { + m_dimensions[i] += m_padding[i].first + m_padding[i].second; + } + const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions(); + if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { + m_inputStrides[0] = 1; + m_outputStrides[0] = 1; + for (int i = 1; i < NumDims; ++i) { + m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1]; + m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1]; + } + m_outputStrides[NumDims] = m_outputStrides[NumDims-1] * m_dimensions[NumDims-1]; + } else { + m_inputStrides[NumDims - 1] = 1; + m_outputStrides[NumDims] = 1; + for (int i = NumDims - 2; i >= 0; --i) { + m_inputStrides[i] = m_inputStrides[i+1] * input_dims[i+1]; + m_outputStrides[i+1] = m_outputStrides[i+2] * m_dimensions[i+1]; + } + m_outputStrides[0] = m_outputStrides[1] * m_dimensions[0]; + } + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) { + m_impl.evalSubExprsIfNeeded(NULL); + return true; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() { + m_impl.cleanup(); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const + { + eigen_assert(index < dimensions().TotalSize()); + Index inputIndex = 0; + if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { + for (int i = NumDims - 1; i > 0; --i) { + const Index idx = index / m_outputStrides[i]; + if (isPaddingAtIndexForDim(idx, i)) { + return m_paddingValue; + } + inputIndex += (idx - m_padding[i].first) * m_inputStrides[i]; + index -= idx * m_outputStrides[i]; + } + if (isPaddingAtIndexForDim(index, 0)) { + return m_paddingValue; + } + inputIndex += (index - m_padding[0].first); + } else { + for (int i = 0; i < NumDims - 1; ++i) { + const Index idx = index / m_outputStrides[i+1]; + if (isPaddingAtIndexForDim(idx, i)) { + return m_paddingValue; + } + inputIndex += (idx - m_padding[i].first) * m_inputStrides[i]; + index -= idx * m_outputStrides[i+1]; + } + if (isPaddingAtIndexForDim(index, NumDims-1)) { + return m_paddingValue; + } + inputIndex += (index - m_padding[NumDims-1].first); + } + return m_impl.coeff(inputIndex); + } + + template<int LoadMode> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const + { + if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { + return packetColMajor(index); + } + return packetRowMajor(index); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const { + TensorOpCost cost = m_impl.costPerCoeff(vectorized); + if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { + for (int i = 0; i < NumDims; ++i) + updateCostPerDimension(cost, i, i == 0); + } else { + for (int i = NumDims - 1; i >= 0; --i) + updateCostPerDimension(cost, i, i == NumDims - 1); + } + return cost; + } + + EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; } + + private: + EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool isPaddingAtIndexForDim( + Index index, int dim_index) const { +#if defined(EIGEN_HAS_INDEX_LIST) + return (!internal::index_pair_first_statically_eq<PaddingDimensions>(dim_index, 0) && + index < m_padding[dim_index].first) || + (!internal::index_pair_second_statically_eq<PaddingDimensions>(dim_index, 0) && + index >= m_dimensions[dim_index] - m_padding[dim_index].second); +#else + return (index < m_padding[dim_index].first) || + (index >= m_dimensions[dim_index] - m_padding[dim_index].second); +#endif + } + + EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool isLeftPaddingCompileTimeZero( + int dim_index) const { +#if defined(EIGEN_HAS_INDEX_LIST) + return internal::index_pair_first_statically_eq<PaddingDimensions>(dim_index, 0); +#else + EIGEN_UNUSED_VARIABLE(dim_index); + return false; +#endif + } + + EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool isRightPaddingCompileTimeZero( + int dim_index) const { +#if defined(EIGEN_HAS_INDEX_LIST) + return internal::index_pair_second_statically_eq<PaddingDimensions>(dim_index, 0); +#else + EIGEN_UNUSED_VARIABLE(dim_index); + return false; +#endif + } + + + void updateCostPerDimension(TensorOpCost& cost, int i, bool first) const { + const double in = static_cast<double>(m_impl.dimensions()[i]); + const double out = in + m_padding[i].first + m_padding[i].second; + if (out == 0) + return; + const double reduction = in / out; + cost *= reduction; + if (first) { + cost += TensorOpCost(0, 0, 2 * TensorOpCost::AddCost<Index>() + + reduction * (1 * TensorOpCost::AddCost<Index>())); + } else { + cost += TensorOpCost(0, 0, 2 * TensorOpCost::AddCost<Index>() + + 2 * TensorOpCost::MulCost<Index>() + + reduction * (2 * TensorOpCost::MulCost<Index>() + + 1 * TensorOpCost::DivCost<Index>())); + } + } + + protected: + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetColMajor(Index index) const + { + EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE) + eigen_assert(index+PacketSize-1 < dimensions().TotalSize()); + + const Index initialIndex = index; + Index inputIndex = 0; + for (int i = NumDims - 1; i > 0; --i) { + const Index first = index; + const Index last = index + PacketSize - 1; + const Index lastPaddedLeft = m_padding[i].first * m_outputStrides[i]; + const Index firstPaddedRight = (m_dimensions[i] - m_padding[i].second) * m_outputStrides[i]; + const Index lastPaddedRight = m_outputStrides[i+1]; + + if (!isLeftPaddingCompileTimeZero(i) && last < lastPaddedLeft) { + // all the coefficient are in the padding zone. + return internal::pset1<PacketReturnType>(m_paddingValue); + } + else if (!isRightPaddingCompileTimeZero(i) && first >= firstPaddedRight && last < lastPaddedRight) { + // all the coefficient are in the padding zone. + return internal::pset1<PacketReturnType>(m_paddingValue); + } + else if ((isLeftPaddingCompileTimeZero(i) && isRightPaddingCompileTimeZero(i)) || (first >= lastPaddedLeft && last < firstPaddedRight)) { + // all the coefficient are between the 2 padding zones. + const Index idx = index / m_outputStrides[i]; + inputIndex += (idx - m_padding[i].first) * m_inputStrides[i]; + index -= idx * m_outputStrides[i]; + } + else { + // Every other case + return packetWithPossibleZero(initialIndex); + } + } + + const Index last = index + PacketSize - 1; + const Index first = index; + const Index lastPaddedLeft = m_padding[0].first; + const Index firstPaddedRight = (m_dimensions[0] - m_padding[0].second); + const Index lastPaddedRight = m_outputStrides[1]; + + if (!isLeftPaddingCompileTimeZero(0) && last < lastPaddedLeft) { + // all the coefficient are in the padding zone. + return internal::pset1<PacketReturnType>(m_paddingValue); + } + else if (!isRightPaddingCompileTimeZero(0) && first >= firstPaddedRight && last < lastPaddedRight) { + // all the coefficient are in the padding zone. + return internal::pset1<PacketReturnType>(m_paddingValue); + } + else if ((isLeftPaddingCompileTimeZero(0) && isRightPaddingCompileTimeZero(0)) || (first >= lastPaddedLeft && last < firstPaddedRight)) { + // all the coefficient are between the 2 padding zones. + inputIndex += (index - m_padding[0].first); + return m_impl.template packet<Unaligned>(inputIndex); + } + // Every other case + return packetWithPossibleZero(initialIndex); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetRowMajor(Index index) const + { + EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE) + eigen_assert(index+PacketSize-1 < dimensions().TotalSize()); + + const Index initialIndex = index; + Index inputIndex = 0; + + for (int i = 0; i < NumDims - 1; ++i) { + const Index first = index; + const Index last = index + PacketSize - 1; + const Index lastPaddedLeft = m_padding[i].first * m_outputStrides[i+1]; + const Index firstPaddedRight = (m_dimensions[i] - m_padding[i].second) * m_outputStrides[i+1]; + const Index lastPaddedRight = m_outputStrides[i]; + + if (!isLeftPaddingCompileTimeZero(i) && last < lastPaddedLeft) { + // all the coefficient are in the padding zone. + return internal::pset1<PacketReturnType>(m_paddingValue); + } + else if (!isRightPaddingCompileTimeZero(i) && first >= firstPaddedRight && last < lastPaddedRight) { + // all the coefficient are in the padding zone. + return internal::pset1<PacketReturnType>(m_paddingValue); + } + else if ((isLeftPaddingCompileTimeZero(i) && isRightPaddingCompileTimeZero(i)) || (first >= lastPaddedLeft && last < firstPaddedRight)) { + // all the coefficient are between the 2 padding zones. + const Index idx = index / m_outputStrides[i+1]; + inputIndex += (idx - m_padding[i].first) * m_inputStrides[i]; + index -= idx * m_outputStrides[i+1]; + } + else { + // Every other case + return packetWithPossibleZero(initialIndex); + } + } + + const Index last = index + PacketSize - 1; + const Index first = index; + const Index lastPaddedLeft = m_padding[NumDims-1].first; + const Index firstPaddedRight = (m_dimensions[NumDims-1] - m_padding[NumDims-1].second); + const Index lastPaddedRight = m_outputStrides[NumDims-1]; + + if (!isLeftPaddingCompileTimeZero(NumDims-1) && last < lastPaddedLeft) { + // all the coefficient are in the padding zone. + return internal::pset1<PacketReturnType>(m_paddingValue); + } + else if (!isRightPaddingCompileTimeZero(NumDims-1) && first >= firstPaddedRight && last < lastPaddedRight) { + // all the coefficient are in the padding zone. + return internal::pset1<PacketReturnType>(m_paddingValue); + } + else if ((isLeftPaddingCompileTimeZero(NumDims-1) && isRightPaddingCompileTimeZero(NumDims-1)) || (first >= lastPaddedLeft && last < firstPaddedRight)) { + // all the coefficient are between the 2 padding zones. + inputIndex += (index - m_padding[NumDims-1].first); + return m_impl.template packet<Unaligned>(inputIndex); + } + // Every other case + return packetWithPossibleZero(initialIndex); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetWithPossibleZero(Index index) const + { + EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize]; + for (int i = 0; i < PacketSize; ++i) { + values[i] = coeff(index+i); + } + PacketReturnType rslt = internal::pload<PacketReturnType>(values); + return rslt; + } + + Dimensions m_dimensions; + array<Index, NumDims+1> m_outputStrides; + array<Index, NumDims> m_inputStrides; + TensorEvaluator<ArgType, Device> m_impl; + PaddingDimensions m_padding; + + Scalar m_paddingValue; +}; + + + + +} // end namespace Eigen + +#endif // EIGEN_CXX11_TENSOR_TENSOR_PADDING_H |