| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. | |
| // SPDX-FileCopyrightText: The Eigen Authors | |
| // SPDX-License-Identifier: MPL-2.0 | |
| #ifndef EIGEN_TENSOR_TENSOR_VOLUME_PATCH_H | |
| #define EIGEN_TENSOR_TENSOR_VOLUME_PATCH_H | |
| // IWYU pragma: private | |
| #include "./InternalHeaderCheck.h" | |
| namespace Eigen { | |
| namespace internal { | |
| template <DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType> | |
| struct traits<TensorVolumePatchOp<Planes, Rows, Cols, XprType>> : traits<XprType> { | |
| typedef std::remove_const_t<typename XprType::Scalar> Scalar; | |
| typedef traits<XprType> XprTraits; | |
| typedef typename XprTraits::StorageKind StorageKind; | |
| typedef typename XprTraits::Index Index; | |
| static constexpr int NumDimensions = XprTraits::NumDimensions + 1; | |
| static constexpr int Layout = XprTraits::Layout; | |
| typedef typename XprTraits::PointerType PointerType; | |
| }; | |
| template <DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType> | |
| struct eval<TensorVolumePatchOp<Planes, Rows, Cols, XprType>, Eigen::Dense> { | |
| typedef const TensorVolumePatchOp<Planes, Rows, Cols, XprType>& type; | |
| }; | |
| } // end namespace internal | |
| /** | |
| * \ingroup Tensor_Module | |
| * | |
| * \brief Patch extraction specialized for processing of volumetric data. | |
| * This assumes that the input has at least 4 dimensions ordered as follows: | |
| * - channels | |
| * - planes | |
| * - rows | |
| * - columns | |
| * - (optional) additional dimensions such as time or batch size. | |
| * Calling the volume patch code with patch_planes, patch_rows, and patch_cols | |
| * is equivalent to calling the regular patch extraction code with parameters | |
| * d, patch_planes, patch_rows, patch_cols, and 1 for all the additional | |
| * dimensions. | |
| */ | |
| template <DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType> | |
| class TensorVolumePatchOp : public TensorBase<TensorVolumePatchOp<Planes, Rows, Cols, XprType>, ReadOnlyAccessors> { | |
| public: | |
| typedef typename Eigen::internal::traits<TensorVolumePatchOp>::Scalar Scalar; | |
| typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; | |
| typedef typename XprType::CoeffReturnType CoeffReturnType; | |
| typedef typename Eigen::internal::ref_selector<TensorVolumePatchOp>::type Nested; | |
| typedef typename Eigen::internal::traits<TensorVolumePatchOp>::StorageKind StorageKind; | |
| typedef typename Eigen::internal::traits<TensorVolumePatchOp>::Index Index; | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorVolumePatchOp( | |
| const XprType& expr, DenseIndex patch_planes, DenseIndex patch_rows, DenseIndex patch_cols, | |
| DenseIndex plane_strides, DenseIndex row_strides, DenseIndex col_strides, DenseIndex in_plane_strides, | |
| DenseIndex in_row_strides, DenseIndex in_col_strides, DenseIndex plane_inflate_strides, | |
| DenseIndex row_inflate_strides, DenseIndex col_inflate_strides, PaddingType padding_type, Scalar padding_value) | |
| : m_xpr(expr), | |
| m_patch_planes(patch_planes), | |
| m_patch_rows(patch_rows), | |
| m_patch_cols(patch_cols), | |
| m_plane_strides(plane_strides), | |
| m_row_strides(row_strides), | |
| m_col_strides(col_strides), | |
| m_in_plane_strides(in_plane_strides), | |
| m_in_row_strides(in_row_strides), | |
| m_in_col_strides(in_col_strides), | |
| m_plane_inflate_strides(plane_inflate_strides), | |
| m_row_inflate_strides(row_inflate_strides), | |
| m_col_inflate_strides(col_inflate_strides), | |
| m_padding_explicit(false), | |
| m_padding_top_z(0), | |
| m_padding_bottom_z(0), | |
| m_padding_top(0), | |
| m_padding_bottom(0), | |
| m_padding_left(0), | |
| m_padding_right(0), | |
| m_padding_type(padding_type), | |
| m_padding_value(padding_value) {} | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorVolumePatchOp( | |
| const XprType& expr, DenseIndex patch_planes, DenseIndex patch_rows, DenseIndex patch_cols, | |
| DenseIndex plane_strides, DenseIndex row_strides, DenseIndex col_strides, DenseIndex in_plane_strides, | |
| DenseIndex in_row_strides, DenseIndex in_col_strides, DenseIndex plane_inflate_strides, | |
| DenseIndex row_inflate_strides, DenseIndex col_inflate_strides, DenseIndex padding_top_z, | |
| DenseIndex padding_bottom_z, DenseIndex padding_top, DenseIndex padding_bottom, DenseIndex padding_left, | |
| DenseIndex padding_right, Scalar padding_value) | |
| : m_xpr(expr), | |
| m_patch_planes(patch_planes), | |
| m_patch_rows(patch_rows), | |
| m_patch_cols(patch_cols), | |
| m_plane_strides(plane_strides), | |
| m_row_strides(row_strides), | |
| m_col_strides(col_strides), | |
| m_in_plane_strides(in_plane_strides), | |
| m_in_row_strides(in_row_strides), | |
| m_in_col_strides(in_col_strides), | |
| m_plane_inflate_strides(plane_inflate_strides), | |
| m_row_inflate_strides(row_inflate_strides), | |
| m_col_inflate_strides(col_inflate_strides), | |
| m_padding_explicit(true), | |
| m_padding_top_z(padding_top_z), | |
| m_padding_bottom_z(padding_bottom_z), | |
| m_padding_top(padding_top), | |
| m_padding_bottom(padding_bottom), | |
| m_padding_left(padding_left), | |
| m_padding_right(padding_right), | |
| m_padding_type(PADDING_VALID), | |
| m_padding_value(padding_value) {} | |
| EIGEN_DEVICE_FUNC DenseIndex patch_planes() const { return m_patch_planes; } | |
| EIGEN_DEVICE_FUNC DenseIndex patch_rows() const { return m_patch_rows; } | |
| EIGEN_DEVICE_FUNC DenseIndex patch_cols() const { return m_patch_cols; } | |
| EIGEN_DEVICE_FUNC DenseIndex plane_strides() const { return m_plane_strides; } | |
| EIGEN_DEVICE_FUNC DenseIndex row_strides() const { return m_row_strides; } | |
| EIGEN_DEVICE_FUNC DenseIndex col_strides() const { return m_col_strides; } | |
| EIGEN_DEVICE_FUNC DenseIndex in_plane_strides() const { return m_in_plane_strides; } | |
| EIGEN_DEVICE_FUNC DenseIndex in_row_strides() const { return m_in_row_strides; } | |
| EIGEN_DEVICE_FUNC DenseIndex in_col_strides() const { return m_in_col_strides; } | |
| EIGEN_DEVICE_FUNC DenseIndex plane_inflate_strides() const { return m_plane_inflate_strides; } | |
| EIGEN_DEVICE_FUNC DenseIndex row_inflate_strides() const { return m_row_inflate_strides; } | |
| EIGEN_DEVICE_FUNC DenseIndex col_inflate_strides() const { return m_col_inflate_strides; } | |
| EIGEN_DEVICE_FUNC bool padding_explicit() const { return m_padding_explicit; } | |
| EIGEN_DEVICE_FUNC DenseIndex padding_top_z() const { return m_padding_top_z; } | |
| EIGEN_DEVICE_FUNC DenseIndex padding_bottom_z() const { return m_padding_bottom_z; } | |
| EIGEN_DEVICE_FUNC DenseIndex padding_top() const { return m_padding_top; } | |
| EIGEN_DEVICE_FUNC DenseIndex padding_bottom() const { return m_padding_bottom; } | |
| EIGEN_DEVICE_FUNC DenseIndex padding_left() const { return m_padding_left; } | |
| EIGEN_DEVICE_FUNC DenseIndex padding_right() const { return m_padding_right; } | |
| EIGEN_DEVICE_FUNC PaddingType padding_type() const { return m_padding_type; } | |
| EIGEN_DEVICE_FUNC Scalar padding_value() const { return m_padding_value; } | |
| EIGEN_DEVICE_FUNC const internal::remove_all_t<typename XprType::Nested>& expression() const { return m_xpr; } | |
| protected: | |
| typename XprType::Nested m_xpr; | |
| const DenseIndex m_patch_planes; | |
| const DenseIndex m_patch_rows; | |
| const DenseIndex m_patch_cols; | |
| const DenseIndex m_plane_strides; | |
| const DenseIndex m_row_strides; | |
| const DenseIndex m_col_strides; | |
| const DenseIndex m_in_plane_strides; | |
| const DenseIndex m_in_row_strides; | |
| const DenseIndex m_in_col_strides; | |
| const DenseIndex m_plane_inflate_strides; | |
| const DenseIndex m_row_inflate_strides; | |
| const DenseIndex m_col_inflate_strides; | |
| const bool m_padding_explicit; | |
| const DenseIndex m_padding_top_z; | |
| const DenseIndex m_padding_bottom_z; | |
| const DenseIndex m_padding_top; | |
| const DenseIndex m_padding_bottom; | |
| const DenseIndex m_padding_left; | |
| const DenseIndex m_padding_right; | |
| const PaddingType m_padding_type; | |
| const Scalar m_padding_value; | |
| }; | |
| // Eval as rvalue | |
| template <DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename ArgType, typename Device> | |
| struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, Device> { | |
| typedef TensorVolumePatchOp<Planes, Rows, Cols, ArgType> XprType; | |
| typedef typename XprType::Index Index; | |
| static constexpr int NumInputDims = | |
| internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value; | |
| static constexpr int NumDims = NumInputDims + 1; | |
| typedef DSizes<Index, NumDims> Dimensions; | |
| typedef std::remove_const_t<typename XprType::Scalar> Scalar; | |
| typedef typename XprType::CoeffReturnType CoeffReturnType; | |
| typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType; | |
| static constexpr int PacketSize = PacketType<CoeffReturnType, Device>::size; | |
| typedef StorageMemory<CoeffReturnType, Device> Storage; | |
| typedef typename Storage::Type EvaluatorPointerType; | |
| static constexpr int Layout = TensorEvaluator<ArgType, Device>::Layout; | |
| enum { | |
| IsAligned = false, | |
| PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess, | |
| // block() reads the argument one coefficient at a time through coeff() -- | |
| // the contract the scalar executors already rely on for every evaluator -- | |
| // so it requires no capability bit from the argument (same as | |
| // TensorReverse). | |
| BlockAccess = true, | |
| // The coeff/packet path pays ~10 divisions of index math per element; the | |
| // block path amortizes all of it over whole depth runs. | |
| PreferBlockAccess = true, | |
| CoordAccess = false, | |
| RawAccess = false | |
| }; | |
| //===- Tensor block evaluation strategy (see TensorBlock.h) -------------===// | |
| typedef internal::TensorBlockDescriptor<NumDims, Index> TensorBlockDesc; | |
| typedef internal::TensorBlockScratchAllocator<Device> TensorBlockScratch; | |
| typedef typename internal::TensorMaterializedBlock<Scalar, NumDims, Layout, Index> TensorBlock; | |
| //===--------------------------------------------------------------------===// | |
| EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device) | |
| : m_impl(op.expression(), device), m_device(device) { | |
| EIGEN_STATIC_ASSERT((NumDims >= 5), YOU_MADE_A_PROGRAMMING_MISTAKE); | |
| m_paddingValue = op.padding_value(); | |
| const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions(); | |
| // Cache a few variables. | |
| EIGEN_IF_CONSTEXPR (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { | |
| m_inputDepth = input_dims[0]; | |
| m_inputPlanes = input_dims[1]; | |
| m_inputRows = input_dims[2]; | |
| m_inputCols = input_dims[3]; | |
| } else { | |
| m_inputDepth = input_dims[NumInputDims - 1]; | |
| m_inputPlanes = input_dims[NumInputDims - 2]; | |
| m_inputRows = input_dims[NumInputDims - 3]; | |
| m_inputCols = input_dims[NumInputDims - 4]; | |
| } | |
| m_plane_strides = op.plane_strides(); | |
| m_row_strides = op.row_strides(); | |
| m_col_strides = op.col_strides(); | |
| // Input strides and effective input/patch size | |
| m_in_plane_strides = op.in_plane_strides(); | |
| m_in_row_strides = op.in_row_strides(); | |
| m_in_col_strides = op.in_col_strides(); | |
| m_plane_inflate_strides = op.plane_inflate_strides(); | |
| m_row_inflate_strides = op.row_inflate_strides(); | |
| m_col_inflate_strides = op.col_inflate_strides(); | |
| // The "effective" spatial size after inflating data with zeros. | |
| m_input_planes_eff = (m_inputPlanes - 1) * m_plane_inflate_strides + 1; | |
| m_input_rows_eff = (m_inputRows - 1) * m_row_inflate_strides + 1; | |
| m_input_cols_eff = (m_inputCols - 1) * m_col_inflate_strides + 1; | |
| m_patch_planes_eff = op.patch_planes() + (op.patch_planes() - 1) * (m_in_plane_strides - 1); | |
| m_patch_rows_eff = op.patch_rows() + (op.patch_rows() - 1) * (m_in_row_strides - 1); | |
| m_patch_cols_eff = op.patch_cols() + (op.patch_cols() - 1) * (m_in_col_strides - 1); | |
| if (op.padding_explicit()) { | |
| m_outputPlanes = | |
| numext::ceil((m_input_planes_eff + op.padding_top_z() + op.padding_bottom_z() - m_patch_planes_eff + 1.0) / | |
| static_cast<double>(m_plane_strides)); | |
| m_outputRows = numext::ceil((m_input_rows_eff + op.padding_top() + op.padding_bottom() - m_patch_rows_eff + 1.0) / | |
| static_cast<double>(m_row_strides)); | |
| m_outputCols = numext::ceil((m_input_cols_eff + op.padding_left() + op.padding_right() - m_patch_cols_eff + 1.0) / | |
| static_cast<double>(m_col_strides)); | |
| m_planePaddingTop = op.padding_top_z(); | |
| m_rowPaddingTop = op.padding_top(); | |
| m_colPaddingLeft = op.padding_left(); | |
| } else { | |
| // Computing padding from the type | |
| switch (op.padding_type()) { | |
| case PADDING_VALID: | |
| m_outputPlanes = | |
| numext::ceil((m_input_planes_eff - m_patch_planes_eff + 1.0) / static_cast<double>(m_plane_strides)); | |
| m_outputRows = numext::ceil((m_input_rows_eff - m_patch_rows_eff + 1.0) / static_cast<double>(m_row_strides)); | |
| m_outputCols = numext::ceil((m_input_cols_eff - m_patch_cols_eff + 1.0) / static_cast<double>(m_col_strides)); | |
| m_planePaddingTop = 0; | |
| m_rowPaddingTop = 0; | |
| m_colPaddingLeft = 0; | |
| break; | |
| case PADDING_SAME: { | |
| m_outputPlanes = numext::ceil(m_input_planes_eff / static_cast<double>(m_plane_strides)); | |
| m_outputRows = numext::ceil(m_input_rows_eff / static_cast<double>(m_row_strides)); | |
| m_outputCols = numext::ceil(m_input_cols_eff / static_cast<double>(m_col_strides)); | |
| const Index dz = (m_outputPlanes - 1) * m_plane_strides + m_patch_planes_eff - m_input_planes_eff; | |
| const Index dy = (m_outputRows - 1) * m_row_strides + m_patch_rows_eff - m_input_rows_eff; | |
| const Index dx = (m_outputCols - 1) * m_col_strides + m_patch_cols_eff - m_input_cols_eff; | |
| // Clip negative padding to zero, as TensorFlow and the image-patch op do. | |
| m_planePaddingTop = numext::maxi<Index>(0, dz) / 2; | |
| m_rowPaddingTop = numext::maxi<Index>(0, dy) / 2; | |
| m_colPaddingLeft = numext::maxi<Index>(0, dx) / 2; | |
| break; | |
| } | |
| default: { | |
| eigen_assert(false && "unexpected padding"); | |
| return; | |
| } | |
| } | |
| } | |
| eigen_assert(m_outputRows > 0); | |
| eigen_assert(m_outputCols > 0); | |
| eigen_assert(m_outputPlanes > 0); | |
| // Dimensions for result of extraction. | |
| EIGEN_IF_CONSTEXPR (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { | |
| // ColMajor | |
| // 0: depth | |
| // 1: patch_planes | |
| // 2: patch_rows | |
| // 3: patch_cols | |
| // 4: number of patches | |
| // 5 and beyond: anything else (such as batch). | |
| m_dimensions[0] = input_dims[0]; | |
| m_dimensions[1] = op.patch_planes(); | |
| m_dimensions[2] = op.patch_rows(); | |
| m_dimensions[3] = op.patch_cols(); | |
| m_dimensions[4] = m_outputPlanes * m_outputRows * m_outputCols; | |
| for (int i = 5; i < NumDims; ++i) { | |
| m_dimensions[i] = input_dims[i - 1]; | |
| } | |
| } else { | |
| // RowMajor | |
| // NumDims-1: depth | |
| // NumDims-2: patch_planes | |
| // NumDims-3: patch_rows | |
| // NumDims-4: patch_cols | |
| // NumDims-5: number of patches | |
| // NumDims-6 and beyond: anything else (such as batch). | |
| m_dimensions[NumDims - 1] = input_dims[NumInputDims - 1]; | |
| m_dimensions[NumDims - 2] = op.patch_planes(); | |
| m_dimensions[NumDims - 3] = op.patch_rows(); | |
| m_dimensions[NumDims - 4] = op.patch_cols(); | |
| m_dimensions[NumDims - 5] = m_outputPlanes * m_outputRows * m_outputCols; | |
| for (int i = NumDims - 6; i >= 0; --i) { | |
| m_dimensions[i] = input_dims[i]; | |
| } | |
| } | |
| // Strides for the output tensor. | |
| EIGEN_IF_CONSTEXPR (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { | |
| m_rowStride = m_dimensions[1]; | |
| m_colStride = m_dimensions[2] * m_rowStride; | |
| m_patchStride = m_colStride * m_dimensions[3] * m_dimensions[0]; | |
| m_otherStride = m_patchStride * m_dimensions[4]; | |
| } else { | |
| m_rowStride = m_dimensions[NumDims - 2]; | |
| m_colStride = m_dimensions[NumDims - 3] * m_rowStride; | |
| m_patchStride = m_colStride * m_dimensions[NumDims - 4] * m_dimensions[NumDims - 1]; | |
| m_otherStride = m_patchStride * m_dimensions[NumDims - 5]; | |
| } | |
| // Strides for navigating through the input tensor. | |
| m_planeInputStride = m_inputDepth; | |
| m_rowInputStride = m_inputDepth * m_inputPlanes; | |
| m_colInputStride = m_inputDepth * m_inputRows * m_inputPlanes; | |
| m_otherInputStride = m_inputDepth * m_inputRows * m_inputCols * m_inputPlanes; | |
| m_outputPlanesRows = m_outputPlanes * m_outputRows; | |
| // Fast representations of different variables. | |
| m_fastOtherStride = internal::TensorIntDivisor<Index>(m_otherStride); | |
| m_fastPatchStride = internal::TensorIntDivisor<Index>(m_patchStride); | |
| m_fastColStride = internal::TensorIntDivisor<Index>(m_colStride); | |
| m_fastRowStride = internal::TensorIntDivisor<Index>(m_rowStride); | |
| m_fastInputRowStride = internal::TensorIntDivisor<Index>(m_row_inflate_strides); | |
| m_fastInputColStride = internal::TensorIntDivisor<Index>(m_col_inflate_strides); | |
| m_fastInputPlaneStride = internal::TensorIntDivisor<Index>(m_plane_inflate_strides); | |
| m_fastInputColsEff = internal::TensorIntDivisor<Index>(m_input_cols_eff); | |
| m_fastOutputPlanes = internal::TensorIntDivisor<Index>(m_outputPlanes); | |
| m_fastOutputPlanesRows = internal::TensorIntDivisor<Index>(m_outputPlanesRows); | |
| EIGEN_IF_CONSTEXPR (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { | |
| m_fastOutputDepth = internal::TensorIntDivisor<Index>(m_dimensions[0]); | |
| } else { | |
| m_fastOutputDepth = internal::TensorIntDivisor<Index>(m_dimensions[NumDims - 1]); | |
| } | |
| } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; } | |
| EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType /*data*/) { | |
| m_impl.evalSubExprsIfNeeded(nullptr); | |
| return true; | |
| } | |
| #ifdef EIGEN_USE_THREADS | |
| template <typename EvalSubExprsCallback> | |
| EIGEN_STRONG_INLINE void evalSubExprsIfNeededAsync(EvaluatorPointerType /*data*/, EvalSubExprsCallback done) { | |
| m_impl.evalSubExprsIfNeededAsync(nullptr, [done](bool) { done(true); }); | |
| } | |
| #endif // EIGEN_USE_THREADS | |
| EIGEN_STRONG_INLINE void cleanup() { m_impl.cleanup(); } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { | |
| // Patch index corresponding to the passed in index. | |
| const Index patchIndex = index / m_fastPatchStride; | |
| // Spatial offset within the patch. This has to be translated into 3D | |
| // coordinates within the patch. | |
| const Index patchOffset = (index - patchIndex * m_patchStride) / m_fastOutputDepth; | |
| // Batch, etc. | |
| const Index otherIndex = (NumDims == 5) ? 0 : index / m_fastOtherStride; | |
| const Index patch3DIndex = (NumDims == 5) ? patchIndex : (index - otherIndex * m_otherStride) / m_fastPatchStride; | |
| // Calculate column index in the input original tensor. | |
| const Index colIndex = patch3DIndex / m_fastOutputPlanesRows; | |
| const Index colOffset = patchOffset / m_fastColStride; | |
| const Index inputCol = colIndex * m_col_strides + colOffset * m_in_col_strides - m_colPaddingLeft; | |
| const Index origInputCol = | |
| (m_col_inflate_strides == 1) ? inputCol : ((inputCol >= 0) ? (inputCol / m_fastInputColStride) : 0); | |
| if (inputCol < 0 || inputCol >= m_input_cols_eff || | |
| ((m_col_inflate_strides != 1) && (inputCol != origInputCol * m_col_inflate_strides))) { | |
| return Scalar(m_paddingValue); | |
| } | |
| // Calculate row index in the original input tensor. | |
| const Index rowIndex = (patch3DIndex - colIndex * m_outputPlanesRows) / m_fastOutputPlanes; | |
| const Index rowOffset = (patchOffset - colOffset * m_colStride) / m_fastRowStride; | |
| const Index inputRow = rowIndex * m_row_strides + rowOffset * m_in_row_strides - m_rowPaddingTop; | |
| const Index origInputRow = | |
| (m_row_inflate_strides == 1) ? inputRow : ((inputRow >= 0) ? (inputRow / m_fastInputRowStride) : 0); | |
| if (inputRow < 0 || inputRow >= m_input_rows_eff || | |
| ((m_row_inflate_strides != 1) && (inputRow != origInputRow * m_row_inflate_strides))) { | |
| return Scalar(m_paddingValue); | |
| } | |
| // Calculate plane index in the original input tensor. | |
| const Index planeIndex = patch3DIndex - m_outputPlanes * (colIndex * m_outputRows + rowIndex); | |
| const Index planeOffset = patchOffset - colOffset * m_colStride - rowOffset * m_rowStride; | |
| const Index inputPlane = planeIndex * m_plane_strides + planeOffset * m_in_plane_strides - m_planePaddingTop; | |
| const Index origInputPlane = | |
| (m_plane_inflate_strides == 1) ? inputPlane : ((inputPlane >= 0) ? (inputPlane / m_fastInputPlaneStride) : 0); | |
| if (inputPlane < 0 || inputPlane >= m_input_planes_eff || | |
| ((m_plane_inflate_strides != 1) && (inputPlane != origInputPlane * m_plane_inflate_strides))) { | |
| return Scalar(m_paddingValue); | |
| } | |
| constexpr int depth_index = static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 0 : NumDims - 1; | |
| const Index depth = index - (index / m_fastOutputDepth) * m_dimensions[depth_index]; | |
| const Index inputIndex = depth + origInputRow * m_rowInputStride + origInputCol * m_colInputStride + | |
| origInputPlane * m_planeInputStride + otherIndex * m_otherInputStride; | |
| return m_impl.coeff(inputIndex); | |
| } | |
| template <int LoadMode> | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const { | |
| eigen_assert(index + PacketSize - 1 < dimensions().TotalSize()); | |
| if (m_in_row_strides != 1 || m_in_col_strides != 1 || m_row_inflate_strides != 1 || m_col_inflate_strides != 1 || | |
| m_in_plane_strides != 1 || m_plane_inflate_strides != 1) { | |
| return packetWithPossibleZero(index); | |
| } | |
| const Index indices[2] = {index, index + PacketSize - 1}; | |
| const Index patchIndex = indices[0] / m_fastPatchStride; | |
| if (patchIndex != indices[1] / m_fastPatchStride) { | |
| return packetWithPossibleZero(index); | |
| } | |
| const Index otherIndex = (NumDims == 5) ? 0 : indices[0] / m_fastOtherStride; | |
| eigen_assert(otherIndex == indices[1] / m_fastOtherStride); | |
| // Find the offset of the element wrt the location of the first element. | |
| Index first_entry = (indices[0] - patchIndex * m_patchStride) / m_fastOutputDepth; | |
| Index second_entry = PacketSize == 1 ? first_entry : (indices[1] - patchIndex * m_patchStride) / m_fastOutputDepth; | |
| const Index patchOffsets[2] = {first_entry, second_entry}; | |
| const Index patch3DIndex = | |
| (NumDims == 5) ? patchIndex : (indices[0] - otherIndex * m_otherStride) / m_fastPatchStride; | |
| eigen_assert(patch3DIndex == (indices[1] - otherIndex * m_otherStride) / m_fastPatchStride); | |
| const Index colIndex = patch3DIndex / m_fastOutputPlanesRows; | |
| const Index colOffsets[2] = {patchOffsets[0] / m_fastColStride, patchOffsets[1] / m_fastColStride}; | |
| // Calculate col indices in the original input tensor. | |
| const Index inputCols[2] = {colIndex * m_col_strides + colOffsets[0] - m_colPaddingLeft, | |
| colIndex * m_col_strides + colOffsets[1] - m_colPaddingLeft}; | |
| if (inputCols[1] < 0 || inputCols[0] >= m_inputCols) { | |
| return internal::pset1<PacketReturnType>(Scalar(m_paddingValue)); | |
| } | |
| if (inputCols[0] != inputCols[1]) { | |
| return packetWithPossibleZero(index); | |
| } | |
| const Index rowIndex = (patch3DIndex - colIndex * m_outputPlanesRows) / m_fastOutputPlanes; | |
| const Index rowOffsets[2] = {(patchOffsets[0] - colOffsets[0] * m_colStride) / m_fastRowStride, | |
| (patchOffsets[1] - colOffsets[1] * m_colStride) / m_fastRowStride}; | |
| eigen_assert(rowOffsets[0] <= rowOffsets[1]); | |
| // Calculate row indices in the original input tensor. | |
| const Index inputRows[2] = {rowIndex * m_row_strides + rowOffsets[0] - m_rowPaddingTop, | |
| rowIndex * m_row_strides + rowOffsets[1] - m_rowPaddingTop}; | |
| if (inputRows[1] < 0 || inputRows[0] >= m_inputRows) { | |
| return internal::pset1<PacketReturnType>(Scalar(m_paddingValue)); | |
| } | |
| if (inputRows[0] != inputRows[1]) { | |
| return packetWithPossibleZero(index); | |
| } | |
| const Index planeIndex = patch3DIndex - m_outputPlanes * (colIndex * m_outputRows + rowIndex); | |
| const Index planeOffsets[2] = {patchOffsets[0] - colOffsets[0] * m_colStride - rowOffsets[0] * m_rowStride, | |
| patchOffsets[1] - colOffsets[1] * m_colStride - rowOffsets[1] * m_rowStride}; | |
| eigen_assert(planeOffsets[0] <= planeOffsets[1]); | |
| const Index inputPlanes[2] = {planeIndex * m_plane_strides + planeOffsets[0] - m_planePaddingTop, | |
| planeIndex * m_plane_strides + planeOffsets[1] - m_planePaddingTop}; | |
| if (inputPlanes[1] < 0 || inputPlanes[0] >= m_inputPlanes) { | |
| return internal::pset1<PacketReturnType>(Scalar(m_paddingValue)); | |
| } | |
| if (inputPlanes[0] >= 0 && inputPlanes[1] < m_inputPlanes) { | |
| // no padding | |
| constexpr int depth_index = static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 0 : NumDims - 1; | |
| const Index depth = index - (index / m_fastOutputDepth) * m_dimensions[depth_index]; | |
| const Index inputIndex = depth + inputRows[0] * m_rowInputStride + inputCols[0] * m_colInputStride + | |
| m_planeInputStride * inputPlanes[0] + otherIndex * m_otherInputStride; | |
| return m_impl.template packet<Unaligned>(inputIndex); | |
| } | |
| return packetWithPossibleZero(index); | |
| } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE internal::TensorBlockResourceRequirements getResourceRequirements() const { | |
| const size_t target_size = m_device.firstLevelCacheSize(); | |
| // In-bounds output coefficients read the argument once and every output | |
| // coefficient is stored once (padding runs make this a slight | |
| // over-estimate). Pass the full cost explicitly rather than adding to | |
| // skewed()'s default load+store seed, which would double-count the | |
| // baseline byte traffic and halve the tile size. | |
| const TensorOpCost cost_per_coeff = m_impl.costPerCoeff(/*vectorized=*/false) + TensorOpCost(0, sizeof(Scalar), 0); | |
| return internal::TensorBlockResourceRequirements::withShapeAndSize<Scalar>( | |
| internal::TensorBlockShapeType::kSkewedInnerDims, target_size, cost_per_coeff); | |
| } | |
| // Materializes the block by iterating patch/col/row/plane coordinates and | |
| // either copying the (always input-contiguous) depth run or filling it with | |
| // the padding value. All per-coordinate index math and bounds checks are | |
| // amortized over a whole depth run instead of paid per coefficient. | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorBlock block(TensorBlockDesc& desc, TensorBlockScratch& scratch, | |
| bool /*root_of_expr_ast*/ = false) const { | |
| constexpr bool is_col_major = static_cast<int>(Layout) == static_cast<int>(ColMajor); | |
| if (desc.size() == 0) { | |
| return TensorBlock(internal::TensorBlockKind::kView, nullptr, desc.dimensions()); | |
| } | |
| typename TensorBlock::Storage block_storage = TensorBlock::prepareStorage(desc, scratch); | |
| Scalar* block_buffer = block_storage.data(); | |
| // Output coordinates of the block's corner. | |
| const DSizes<Index, NumDims> output_strides = internal::strides<Layout>(m_dimensions); | |
| array<Index, NumDims> coords; | |
| Index remaining = desc.offset(); | |
| EIGEN_IF_CONSTEXPR (is_col_major) { | |
| for (int i = NumDims - 1; i > 0; --i) { | |
| coords[i] = remaining / output_strides[i]; | |
| remaining -= coords[i] * output_strides[i]; | |
| } | |
| coords[0] = remaining; | |
| } else { | |
| for (int i = 0; i < NumDims - 1; ++i) { | |
| coords[i] = remaining / output_strides[i]; | |
| remaining -= coords[i] * output_strides[i]; | |
| } | |
| coords[NumDims - 1] = remaining; | |
| } | |
| // Output dimensions: depth, patch plane/row/col offset, 3d patch index. | |
| const int dd = is_col_major ? 0 : NumDims - 1; | |
| const int nd = is_col_major ? 1 : NumDims - 2; | |
| const int rd = is_col_major ? 2 : NumDims - 3; | |
| const int cd = is_col_major ? 3 : NumDims - 4; | |
| const int pd = is_col_major ? 4 : NumDims - 5; | |
| const Index depth_start = coords[dd]; | |
| const Index depth_size = desc.dimension(dd); | |
| const Index plane_start = coords[nd]; | |
| const Index plane_size = desc.dimension(nd); | |
| const Index row_start = coords[rd]; | |
| const Index row_size = desc.dimension(rd); | |
| const Index col_start = coords[cd]; | |
| const Index col_size = desc.dimension(cd); | |
| const Index patch_start = coords[pd]; | |
| const Index patch_size = desc.dimension(pd); | |
| // Odometer over the remaining (batch etc.) dimensions, tracking the input | |
| // offset they contribute. | |
| array<Index, NumDims> other_sizes; | |
| array<Index, NumDims> other_src_stride; | |
| array<Index, NumDims> other_count; | |
| int num_other = 0; | |
| Index src_other = 0; | |
| { | |
| Index in_stride = m_otherInputStride; | |
| for (int k = 5; k < NumDims; ++k) { | |
| const int d = is_col_major ? k : NumDims - 1 - k; | |
| other_sizes[num_other] = desc.dimension(d); | |
| other_src_stride[num_other] = in_stride; | |
| other_count[num_other] = 0; | |
| src_other += coords[d] * in_stride; | |
| in_stride *= m_dimensions[d]; | |
| ++num_other; | |
| } | |
| } | |
| typedef internal::StridedLinearBufferCopy<Scalar, Index> LinCopy; | |
| // The loop nest below visits the block in exactly its memory order (the | |
| // storage returned by prepareStorage() is dense with the block's own | |
| // layout-order strides), so the destination is one running cursor. | |
| Index dst = 0; | |
| for (;;) { | |
| for (Index p = 0; p < patch_size; ++p) { | |
| const Index patch3DIndex = patch_start + p; | |
| const Index colIndex = patch3DIndex / m_fastOutputPlanesRows; | |
| const Index rowIndex = (patch3DIndex - colIndex * m_outputPlanesRows) / m_fastOutputPlanes; | |
| const Index planeIndex = patch3DIndex - m_outputPlanes * (colIndex * m_outputRows + rowIndex); | |
| for (Index c = 0; c < col_size; ++c) { | |
| const Index colOffset = col_start + c; | |
| const Index inputCol = colIndex * m_col_strides + colOffset * m_in_col_strides - m_colPaddingLeft; | |
| Index origInputCol = inputCol; | |
| bool col_valid = inputCol >= 0 && inputCol < m_input_cols_eff; | |
| if (col_valid && m_col_inflate_strides != 1) { | |
| origInputCol = inputCol / m_fastInputColStride; | |
| col_valid = (inputCol == origInputCol * m_col_inflate_strides); | |
| } | |
| for (Index r = 0; r < row_size; ++r) { | |
| const Index rowOffset = row_start + r; | |
| bool row_valid = col_valid; | |
| Index origInputRow = 0; | |
| if (row_valid) { | |
| const Index inputRow = rowIndex * m_row_strides + rowOffset * m_in_row_strides - m_rowPaddingTop; | |
| row_valid = inputRow >= 0 && inputRow < m_input_rows_eff; | |
| if (row_valid) { | |
| origInputRow = inputRow; | |
| if (m_row_inflate_strides != 1) { | |
| origInputRow = inputRow / m_fastInputRowStride; | |
| row_valid = (inputRow == origInputRow * m_row_inflate_strides); | |
| } | |
| } | |
| } | |
| for (Index n = 0; n < plane_size; ++n) { | |
| const Index planeOffset = plane_start + n; | |
| bool valid = row_valid; | |
| Index origInputPlane = 0; | |
| if (valid) { | |
| const Index inputPlane = | |
| planeIndex * m_plane_strides + planeOffset * m_in_plane_strides - m_planePaddingTop; | |
| valid = inputPlane >= 0 && inputPlane < m_input_planes_eff; | |
| if (valid) { | |
| origInputPlane = inputPlane; | |
| if (m_plane_inflate_strides != 1) { | |
| origInputPlane = inputPlane / m_fastInputPlaneStride; | |
| valid = (inputPlane == origInputPlane * m_plane_inflate_strides); | |
| } | |
| } | |
| } | |
| if (valid) { | |
| const Index src = depth_start + origInputPlane * m_planeInputStride + origInputRow * m_rowInputStride + | |
| origInputCol * m_colInputStride + src_other; | |
| for (Index d = 0; d < depth_size; ++d) { | |
| block_buffer[dst + d] = m_impl.coeff(src + d); | |
| } | |
| } else { | |
| LinCopy::template Run<LinCopy::Kind::FillLinear>(typename LinCopy::Dst(dst, 1, block_buffer), | |
| typename LinCopy::Src(0, 0, &m_paddingValue), | |
| depth_size); | |
| } | |
| dst += depth_size; | |
| } | |
| } | |
| } | |
| } | |
| int k = 0; | |
| for (; k < num_other; ++k) { | |
| if (++other_count[k] < other_sizes[k]) { | |
| src_other += other_src_stride[k]; | |
| break; | |
| } | |
| other_count[k] = 0; | |
| src_other -= other_src_stride[k] * (other_sizes[k] - 1); | |
| } | |
| if (k == num_other) break; | |
| } | |
| eigen_assert(dst == desc.size()); | |
| return block_storage.AsTensorMaterializedBlock(); | |
| } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const { | |
| const double compute_cost = | |
| 10 * TensorOpCost::DivCost<Index>() + 21 * TensorOpCost::MulCost<Index>() + 8 * TensorOpCost::AddCost<Index>(); | |
| return TensorOpCost(0, 0, compute_cost, vectorized, PacketSize); | |
| } | |
| EIGEN_DEVICE_FUNC EvaluatorPointerType data() const { return nullptr; } | |
| const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index planePaddingTop() const { return m_planePaddingTop; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rowPaddingTop() const { return m_rowPaddingTop; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index colPaddingLeft() const { return m_colPaddingLeft; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index outputPlanes() const { return m_outputPlanes; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index outputRows() const { return m_outputRows; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index outputCols() const { return m_outputCols; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index userPlaneStride() const { return m_plane_strides; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index userRowStride() const { return m_row_strides; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index userColStride() const { return m_col_strides; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index userInPlaneStride() const { return m_in_plane_strides; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index userInRowStride() const { return m_in_row_strides; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index userInColStride() const { return m_in_col_strides; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index planeInflateStride() const { return m_plane_inflate_strides; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rowInflateStride() const { return m_row_inflate_strides; } | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index colInflateStride() const { return m_col_inflate_strides; } | |
| protected: | |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetWithPossibleZero(Index index) const { | |
| EIGEN_ALIGN_TO_BOUNDARY(internal::unpacket_traits<PacketReturnType>::alignment) | |
| std::remove_const_t<CoeffReturnType> values[PacketSize]; | |
| EIGEN_UNROLL_LOOP | |
| for (int i = 0; i < PacketSize; ++i) { | |
| values[i] = coeff(index + i); | |
| } | |
| PacketReturnType rslt = internal::pload<PacketReturnType>(values); | |
| return rslt; | |
| } | |
| Dimensions m_dimensions; | |
| // Parameters passed to the constructor. | |
| Index m_plane_strides; | |
| Index m_row_strides; | |
| Index m_col_strides; | |
| Index m_outputPlanes; | |
| Index m_outputRows; | |
| Index m_outputCols; | |
| Index m_planePaddingTop; | |
| Index m_rowPaddingTop; | |
| Index m_colPaddingLeft; | |
| Index m_in_plane_strides; | |
| Index m_in_row_strides; | |
| Index m_in_col_strides; | |
| Index m_plane_inflate_strides; | |
| Index m_row_inflate_strides; | |
| Index m_col_inflate_strides; | |
| // Cached input size. | |
| Index m_inputDepth; | |
| Index m_inputPlanes; | |
| Index m_inputRows; | |
| Index m_inputCols; | |
| // Other cached variables. | |
| Index m_outputPlanesRows; | |
| // Effective input/patch post-inflation size. | |
| Index m_input_planes_eff; | |
| Index m_input_rows_eff; | |
| Index m_input_cols_eff; | |
| Index m_patch_planes_eff; | |
| Index m_patch_rows_eff; | |
| Index m_patch_cols_eff; | |
| // Strides for the output tensor. | |
| Index m_otherStride; | |
| Index m_patchStride; | |
| Index m_rowStride; | |
| Index m_colStride; | |
| // Strides for the input tensor. | |
| Index m_planeInputStride; | |
| Index m_rowInputStride; | |
| Index m_colInputStride; | |
| Index m_otherInputStride; | |
| internal::TensorIntDivisor<Index> m_fastOtherStride; | |
| internal::TensorIntDivisor<Index> m_fastPatchStride; | |
| internal::TensorIntDivisor<Index> m_fastColStride; | |
| internal::TensorIntDivisor<Index> m_fastRowStride; | |
| internal::TensorIntDivisor<Index> m_fastInputPlaneStride; | |
| internal::TensorIntDivisor<Index> m_fastInputRowStride; | |
| internal::TensorIntDivisor<Index> m_fastInputColStride; | |
| internal::TensorIntDivisor<Index> m_fastInputColsEff; | |
| internal::TensorIntDivisor<Index> m_fastOutputPlanesRows; | |
| internal::TensorIntDivisor<Index> m_fastOutputPlanes; | |
| internal::TensorIntDivisor<Index> m_fastOutputDepth; | |
| Scalar m_paddingValue; | |
| TensorEvaluator<ArgType, Device> m_impl; | |
| const Device EIGEN_DEVICE_REF m_device; | |
| }; | |
| } // end namespace Eigen | |
| #endif // EIGEN_TENSOR_TENSOR_VOLUME_PATCH_H |