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Class Hierarchy
This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 1234567]
 CEigen::AntiHermiticity< One_, Two_ >
 CEigen::AntiSymmetry< One_, Two_ >
 CEigen::ArpackGeneralizedSelfAdjointEigenSolver< MatrixType, MatrixSolver, BisSPD >
 Carray
 CEigen::internal::auto_diff_special_op< DerivativeType, !internal::is_same< internal::traits< internal::remove_all_t< DerivativeType > >::Scalar, NumTraits< internal::traits< internal::remove_all_t< DerivativeType > >::Scalar >::Real >::value >
 CEigen::AutoDiffVector< ValueType, JacobianType >
 Cbinary_op_base
 CEigen::TensorEvaluator< const TensorBroadcastingOp< Broadcast, ArgType >, Device >::BlockBroadcastingIteratorState
 CEigen::TensorEvaluator< const TensorBroadcastingOp< Broadcast, ArgType >, Device >::BlockBroadcastingParams
 CEigen::TensorEvaluator< const TensorGeneratorOp< Generator, ArgType >, Device >::BlockIteratorState
 CEigen::TensorEvaluator< const TensorPaddingOp< PaddingDimensions, ArgType >, Device >::BlockIteratorState
 CEigen::TensorEvaluator< const TensorReshapingOp< NewDimensions, ArgType >, Device >::BlockIteratorState
 CEigen::TensorEvaluator< const TensorReverseOp< ReverseDimensions, ArgType >, Device >::BlockIteratorState
 CEigen::TensorReductionEvaluatorBase< const TensorReductionOp< Op, Dims, ArgType, MakePointer_ >, Device >::BlockIteratorState
 CEigen::BlockVectorReturn< BlockSparseMatrixT, VectorType >
 CEigen::BlockVectorView< BlockSparseMatrixT, VectorType >
 CEigen::CleanedUpDerType< DerType >
 CEigen::Cond< cond >
 CEigen::ConversionSubExprEval< SameType, Eval, EvalPointerType >
 CEigen::ConversionSubExprEval< true, Eval, EvalPointerType >
 CEigen::DefaultDevice
 CEigen::DenseFunctor< Scalar_, NX, NY >
 CEigen::DimensionList< Index, Rank >
 CEigen::DynamicSGroupDynamic symmetry group
 CEigen::DynamicSkylineMatrix< Scalar_, Flags_ >
 CEigen::EigenBase< class > [external]
 CEigen::EigenBase< Derived > [external]
 CEigen::EigenConvolutionKernel< Evaluator, CoeffReturnType, KernelType, Index, InputDims, Kernel_accessor, Buffer_accessor, Conv_Dim >
 CEigen::EigenConvolutionKernel< Evaluator, CoeffReturnType, KernelType, Index, InputDims, Kernel_accessor, Buffer_accessor, convolution_type::CONV1D >
 CEigen::EigenConvolutionKernel< Evaluator, CoeffReturnType, KernelType, Index, InputDims, Kernel_accessor, Buffer_accessor, convolution_type::CONV2D >
 CEigen::EigenConvolutionKernel< Evaluator, CoeffReturnType, KernelType, Index, InputDims, Kernel_accessor, Buffer_accessor, convolution_type::CONV3D >
 CEigen::EulerSystem< _AlphaAxis, _BetaAxis, _GammaAxis >Represents a fixed Euler rotation system
 Cevaluator
 CEigen::FABSum< Scalar, Width >
 Cfalse_type
 CEigen::FFT< T_Scalar, T_Impl >
 CFunctor
 CFunctor_
 CEigen::DynamicSGroup::Generator
 CEigen::AlignedVector3< Scalar_ >::generic_assign_selector< XprType, Size >
 CEigen::AlignedVector3< Scalar_ >::generic_assign_selector< XprType, 3 >
 CEigen::AlignedVector3< Scalar_ >::generic_assign_selector< XprType, 4 >
 CEigen::GenericNumTraits< class > [external]
 CGenericNumTraits< double > [external]
 CEigen::GenericNumTraits< mpfr::mpreal > [external]
 CEigen::DynamicSGroup::GroupElement
 CEigen::Hermiticity< One_, Two_ >
 CEigen::HybridNonLinearSolver< FunctorType, Scalar >Finds a zero of a system of n nonlinear functions in n variables by a modification of the Powell hybrid method ("dogleg")
 CEigen::IndexPair< Idx >
 CEigen::internal::IndexTuple< FirstType, OtherTypes... >
 CEigen::SkylineMatrix< Scalar_, Options_ >::InnerLowerIterator
 CEigen::SkylineMatrix< Scalar_, Options_ >::InnerUpperIterator
 CEigen::TensorEvaluator< const TensorContractionOp< Indices, LeftArgType, RightArgType, OutputKernelType >, Eigen::SyclDevice >::input_mapper_propertis< lhs_inner_dim_contiguous, rhs_inner_dim_contiguous, rhs_inner_dim_reordered >
 CEigen::Tensor< Scalar_, NumIndices_, Options_, IndexType_ >::isOfNormalIndex< CustomIndices >
 CEigen::IterScaling< MatrixType_ >Iterative scaling algorithm to equilibrate rows and column norms in matrices
 CEigen::KahanSum< Scalar >Kahan algorithm based accumulator
 CEigen::KdBVH< Scalar_, Dim_, _Object >A simple bounding volume hierarchy based on AlignedBox
 CEigen::internal::kissfft_impl< Scalar_ >
 CEigen::internal::kissfft_impl< T >
 CEigen::MakeComplex< NeedUprade >
 CEigen::MakeComplex< false >
 CEigen::MakeComplex< true >
 CEigen::MakePointer< T >
 CEigen::MappedSkylineMatrix< Scalar_, Flags_ >
 CEigen::MatrixMarketIterator< Scalar >Iterator to browse matrices from a specified folder
 CEigen::max_n_1< n >
 CEigen::max_n_1< 0 >
 CEigen::NNLS< MatrixType_ >Implementation of the Non-Negative Least Squares (NNLS) algorithm
 Cinternal::no_assignment_operator
 Cno_assignment_operator
 Cinternal::noncopyable
 CEigen::NoOpOutputKernel
 Cnumeric_limits
 CEigen::NumTraits< type2index< n > >
 Cinternal::packet_traits
 CEigen::PacketConverter< TensorEvaluator, SrcPacket, TgtPacket, SrcCoeffRatio, TgtCoeffRatio >
 CEigen::PacketConverter< TensorEvaluator, SrcPacket, TgtPacket, 1, 1 >
 CEigen::PacketConverter< TensorEvaluator, SrcPacket, TgtPacket, 1, TgtCoeffRatio >
 CEigen::PacketConverter< TensorEvaluator, SrcPacket, TgtPacket, 2, 1 >
 CEigen::PacketConverter< TensorEvaluator, SrcPacket, TgtPacket, 4, 1 >
 CEigen::PacketConverter< TensorEvaluator, SrcPacket, TgtPacket, 8, 1 >
 CEigen::TensorEvaluator< const TensorShufflingOp< Shuffle, ArgType >, Device >::PacketLoader< LoadMode, Self, ImplPacketAccess >
 CEigen::TensorEvaluator< const TensorShufflingOp< Shuffle, ArgType >, Device >::PacketLoader< LoadMode, Self, true >
 CEigen::Pair< U, V >
 CEigen::HybridNonLinearSolver< FunctorType, Scalar >::Parameters
 CEigen::LevenbergMarquardt< FunctorType_ >::Parameters
 CEigen::PartOf< ResultType >
 CEigen::PartOf< ImagPart >
 CEigen::PartOf< RealPart >
 CEigen::PolynomialSolverBase< Scalar_, Deg_ >Defined to be inherited by polynomial solvers: it provides convenient methods such as
 CEigen::PolynomialSolverBase< Scalar_, 1 >
 CProductBase
 CEigen::RandomSetter< SparseMatrixType, MapTraits, OuterPacketBits >The RandomSetter is a wrapper object allowing to set/update a sparse matrix with random access
 CEigen::ReturnByValue< class > [external]
 CEigen::ReturnByValue< Derived > [external]
 CEigen::ReturnByValue< fft_fwd_proxy< T_SrcMat, T_FftIfc > > [external]
 CEigen::ReturnByValue< fft_inv_proxy< T_SrcMat, T_FftIfc > > [external]
 CEigen::ReturnByValue< MatrixPowerParenthesesReturnValue< MatrixType > > [external]
 Cinternal::tensor_symmetry_pre_analysis::root_type
 CEigen::RotationBase< EulerAngles< Scalar_, _System >, 3 > [external]
 Chip_impl::Scalar_accessor< typename, typename, int >
 CEigen::ScalarBinaryOpTraits< AutoDiffScalar< DerType >, typename DerType::Scalar, BinOp >
 CEigen::ScalarBinaryOpTraits< typename DerType::Scalar, AutoDiffScalar< DerType >, BinOp >
 CEigen::RandomSetter< SparseMatrixType, MapTraits, OuterPacketBits >::ScalarWrapper
 CEigen::Sizes< Indices >
 CEigen::SkylineInplaceLU< MatrixType >Inplace LU decomposition of a skyline matrix and associated features
 CEigen::SkylineProduct< Lhs, Rhs, ProductMode >
 CEigen::SkylineProductReturnType< Lhs, Rhs, ProductMode >
 CEigen::SkylineStorage< Scalar >
 CEigen::SkylineVector< Scalar_, Flags_ >
 CEigen::SparseFunctor< Scalar_, Index_ >
 CEigen::SparseInverse< Scalar >Calculate sparse subset of inverse of sparse matrix
 CEigen::SparseSolverBase< class > [external]
 CEigen::SparseSolverBase< IncompleteLU< Scalar_ > > [external]
 CEigen::Spline< Scalar_, Dim_, Degree_ >A class representing multi-dimensional spline curves
 CEigen::SplineFitting< SplineType >Spline fitting methods
 CEigen::SplineTraits< SplineType, DerivativeOrder >
 CEigen::SplineTraits< Spline >
 CEigen::SplineTraits< Spline< Scalar_, Dim_, Degree_ > >
 CEigen::SplineTraits< Spline< Scalar_, Dim_, Degree_ >, Dynamic >Compile-time attributes of the Spline class for Dynamic degree
 CEigen::StaticSGroup< Gen >Static symmetry group
 CEigen::StdMapTraits< Scalar >
 CEigen::StdUnorderedMapTraits< Scalar >
 CEigen::Symmetry< One_, Two_ >
 CTensorAssignThe tensor assignment class
 CEigen::TensorAsyncDevice< ExpressionType, DeviceType, DoneCallback >Pseudo expression providing an operator = that will evaluate its argument asynchronously on the specified device. Currently only ThreadPoolDevice implements proper asynchronous execution, while the default and GPU devices just run the expression synchronously and call m_done() on completion.
 CEigen::TensorBase< Derived, AccessLevel >The tensor base class
 CEigen::TensorBase< Tensor< Scalar_, NumIndices_, Options_, IndexType_ > >
 CEigen::TensorBase< TensorAssignOp< LhsXprType, RhsXprType > >
 CEigen::TensorBase< TensorBroadcastingOp< Broadcast, XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorChippingOp< DimId, XprType > >
 CEigen::TensorBase< TensorConcatenationOp< Axis, LhsXprType, RhsXprType >, WriteAccessors >
 CEigen::TensorBase< TensorContractionOp< Indices, LhsXprType, RhsXprType, const NoOpOutputKernel >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorConversionOp< TargetType, XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorConvolutionOp< Indices, InputXprType, KernelXprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorCustomBinaryOp< CustomBinaryFunc, LhsXprType, RhsXprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorCustomUnaryOp< CustomUnaryFunc, XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorCwiseBinaryOp< BinaryOp, LhsXprType, RhsXprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorCwiseNullaryOp< NullaryOp, XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorCwiseTernaryOp< TernaryOp, Arg1XprType, Arg2XprType, Arg3XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorCwiseUnaryOp< UnaryOp, XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorEvalToOp< XprType, MakePointer_ >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorFFTOp< FFT, XprType, FFTResultType, FFTDir >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorFixedSize< Scalar_, Dimensions_, Options_, IndexType > >
 CEigen::TensorBase< TensorForcedEvalOp< XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorGeneratorOp< Generator, XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorImagePatchOp< Rows, Cols, XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorIndexPairOp< XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorInflationOp< Strides, XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorLayoutSwapOp< XprType >, WriteAccessors >
 CEigen::TensorBase< TensorMap< PlainObjectType, Options_, MakePointer_ > >
 CEigen::TensorBase< TensorPaddingOp< PaddingDimensions, XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorPairReducerOp< ReduceOp, Dims, XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorPatchOp< PatchDim, XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorReductionOp< Op, Dims, XprType, MakePointer_ >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorRef< PlainObjectType > >
 CEigen::TensorBase< TensorReshapingOp< NewDimensions, XprType >, WriteAccessors >
 CEigen::TensorBase< TensorReverseOp< ReverseDimensions, XprType >, WriteAccessors >
 CEigen::TensorBase< TensorScanOp< Op, XprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorSelectOp< IfXprType, ThenXprType, ElseXprType >, ReadOnlyAccessors >
 CEigen::TensorBase< TensorShufflingOp< Shuffle, XprType > >
 CEigen::TensorBase< TensorSlicingOp< StartIndices, Sizes, XprType > >
 CEigen::TensorBase< TensorStridingOp< Strides, XprType > >
 CEigen::TensorBase< TensorStridingSlicingOp< StartIndices, StopIndices, Strides, XprType > >
 CEigen::TensorBase< TensorTraceOp< Dims, XprType > >
 CEigen::TensorBase< TensorVolumePatchOp< Planes, Rows, Cols, XprType >, ReadOnlyAccessors >
 CTensorBroadcastingTensor broadcasting class
 CTensorContractionTensor contraction class
 CEigen::TensorContractionEvaluatorBase< Derived >
 CEigen::TensorContractionEvaluatorBase< TensorEvaluator< const TensorContractionOp< Indices, LeftArgType, RightArgType, OutputKernelType >, Device > >
 CEigen::TensorContractionEvaluatorBase< TensorEvaluator< const TensorContractionOp< Indices, LeftArgType, RightArgType, OutputKernelType >, Eigen::SyclDevice > >
 CEigen::TensorContractionParams
 CEigen::TensorEvaluator< const TensorConversionOp< TargetType, ArgType >, Device >::TensorConversionOpBlockFactory
 CTensorConvolutionTensor convolution class
 CEigen::TensorCostModel< Device >
 CEigen::TensorDevice< ExpressionType, DeviceType >Pseudo expression providing an operator = that will evaluate its argument on the specified computing 'device' (GPU, thread pool, ...)
 CEigen::TensorEvaluator< Derived, Device >A cost model used to limit the number of threads used for evaluating tensor expression
 CEigen::TensorEvaluator< Arg1Type, Device >
 CEigen::TensorEvaluator< Arg2Type, Device >
 CEigen::TensorEvaluator< Arg3Type, Device >
 CEigen::TensorEvaluator< ArgType, Device >
 CEigen::TensorEvaluator< const Derived, Device >
 CEigen::TensorEvaluator< const Eigen::TensorIndexPairOp< ArgType >, Device >
 CEigen::TensorEvaluator< const Eigen::TensorReductionOp< ReduceOp, Dims, const Eigen::TensorIndexPairOp< ArgType > >, Device >
 CEigen::TensorEvaluator< const TensorAssignOp< LeftArgType, RightArgType >, Device >
 CEigen::TensorEvaluator< const TensorBroadcastingOp< Broadcast, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorChippingOp< DimId, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorConcatenationOp< Axis, LeftArgType, RightArgType >, Device >
 CEigen::TensorEvaluator< const TensorConversionOp< TargetType, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorConvolutionOp< Indices, InputArgType, KernelArgType >, Device >
 CEigen::TensorEvaluator< const TensorConvolutionOp< Indices, InputArgType, KernelArgType >, Eigen::SyclDevice >
 CEigen::TensorEvaluator< const TensorCustomBinaryOp< CustomBinaryFunc, LhsXprType, RhsXprType >, Device >
 CEigen::TensorEvaluator< const TensorCustomUnaryOp< CustomUnaryFunc, XprType >, Device >
 CEigen::TensorEvaluator< const TensorCwiseBinaryOp< BinaryOp, LeftArgType, RightArgType >, Device >
 CEigen::TensorEvaluator< const TensorCwiseNullaryOp< NullaryOp, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorCwiseTernaryOp< TernaryOp, Arg1Type, Arg2Type, Arg3Type >, Device >
 CEigen::TensorEvaluator< const TensorCwiseUnaryOp< UnaryOp, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorEvalToOp< ArgType, MakePointer_ >, Device >
 CEigen::TensorEvaluator< const TensorFFTOp< FFT, ArgType, FFTResultType, FFTDir >, Device >
 CEigen::TensorEvaluator< const TensorForcedEvalOp< ArgType_ >, Device >
 CEigen::TensorEvaluator< const TensorGeneratorOp< Generator, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorImagePatchOp< Rows, Cols, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorIndexPairOp< ArgType >, Device >
 CEigen::TensorEvaluator< const TensorInflationOp< Strides, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorLayoutSwapOp< ArgType >, Device >
 CEigen::TensorEvaluator< const TensorPaddingOp< PaddingDimensions, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorPairReducerOp< ReduceOp, Dims, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorPatchOp< PatchDim, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorRef< Derived >, Device >
 CEigen::TensorEvaluator< const TensorReshapingOp< NewDimensions, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorReverseOp< ReverseDimensions, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorScanOp< Op, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorSelectOp< IfArgType, ThenArgType, ElseArgType >, Device >
 CEigen::TensorEvaluator< const TensorShufflingOp< Shuffle, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorSlicingOp< StartIndices, Sizes, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorStridingOp< Strides, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorStridingSlicingOp< StartIndices, StopIndices, Strides, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorTraceOp< Dims, ArgType >, Device >
 CEigen::TensorEvaluator< const TensorVolumePatchOp< Planes, Rows, Cols, ArgType >, Device >
 CEigen::TensorEvaluator< ElseArgType, Device >
 CEigen::TensorEvaluator< EvalLeftArgType, Device >
 CEigen::TensorEvaluator< EvalRightArgType, Device >
 CEigen::TensorEvaluator< IfArgType, Device >
 CEigen::TensorEvaluator< InputArgType, Device >
 CEigen::TensorEvaluator< InputArgType, Eigen::SyclDevice >
 CEigen::TensorEvaluator< KernelArgType, Device >
 CEigen::TensorEvaluator< KernelArgType, Eigen::SyclDevice >
 CEigen::TensorEvaluator< LeftArgType, Device >
 CEigen::TensorEvaluator< RightArgType, Device >
 CEigen::TensorEvaluator< ThenArgType, Device >
 CTensorExecutorThe tensor executor class
 CTensorExprTensor expression classes
 CTensorFFTTensor FFT class
 CTensorForcedEvalTensor reshaping class
 CTensorImagePatchPatch extraction specialized for image processing. This assumes that the input has a least 3 dimensions ordered as follow: 1st dimension: channels (of size d) 2nd dimension: rows (of size r) 3rd dimension: columns (of size c) There can be additional dimensions such as time (for video) or batch (for bulk processing after the first 3. Calling the image patch code with patch_rows and patch_cols is equivalent to calling the regular patch extraction code with parameters d, patch_rows, patch_cols, and 1 for all the additional dimensions
 CTensorIndexPairTensor + Index Pair class
 CTensorInflationTensor inflation class
 CTensorInitializerHelper template to initialize Tensors from std::initializer_lists
 CEigen::TensorIOFormat
 CTensorKChippingReshapingA chip is a thin slice, corresponding to a column or a row in a 2-d tensor
 CTensorLayoutSwapSwap the layout from col-major to row-major, or row-major to col-major, and invert the order of the dimensions
 CEigen::TensorOpCost
 CTensorPaddingTensor padding class. At the moment only padding with a constant value is supported
 CTensorPairIndexConverts to Tensor<Pair<Index, Scalar> > and reduces to Tensor<Index>
 CTensorPatchTensor patch class
 CTensorReductionTensor reduction class
 CEigen::TensorReductionEvaluatorBase< ArgType, Device >
 CEigen::TensorReductionEvaluatorBase< const TensorReductionOp< Op, Dims, ArgType, MakePointer_ >, Device >
 CEigen::TensorReductionEvaluatorBase< const TensorReductionOp< Op, Dims, ArgType, MakePointer_ >, Eigen::SyclDevice >
 CTensorReshapingTensor reshaping class
 CTensorReverseTensor reverse elements class
 CTensorScanTensor scan class
 CEigen::TensorEvaluator< const TensorSelectOp< IfArgType, ThenArgType, ElseArgType >, Device >::TensorSelectOpBlockFactory
 CTensorShufflingTensor shuffling class
 CTensorSlicingTensor slicing class
 CEigen::TensorStorage< T, FixedDimensions, Options_ >
 CEigen::TensorStorage< Scalar, Dimensions, Options >
 CEigen::TensorStorage< Scalar, Eigen::DSizes, Options >
 CEigen::TensorStorage< T, DSizes< IndexType, NumIndices_ >, Options_ >
 CTensorStridingTensor striding class
 CTensorTraceTensor Trace class
 CTensorVolumePatchPatch extraction specialized for processing of volumetric data. This assumes that the input has a least 4 dimensions ordered as follows:
 CEigen::TensorWithFormat< T, Layout, rank >
 CEigen::TensorWithFormat< T, ColMajor, 0 >
 CEigen::TensorWithFormat< T, ColMajor, rank >
 CEigen::TensorWithFormat< T, RowMajor, rank >
 Ctraits
 CEigen::TensorEvaluator< const TensorContractionOp< Indices, LeftArgType, RightArgType, OutputKernelType >, Eigen::SyclDevice >::TripleDim
 Ctrue_type
 CEigen::type2index< n >
 CEigen::type2indexpair< f, s >
 CEigen::KdBVH< Scalar_, Dim_, _Object >::VectorComparator
 CEigen::TensorEvaluator< const TensorConversionOp< TargetType, ArgType >, Device >::TensorConversionOpBlockFactory::XprType< ArgXprType >
 CEigen::TensorEvaluator< const TensorSelectOp< IfArgType, ThenArgType, ElseArgType >, Device >::TensorSelectOpBlockFactory::XprType< IfArgXprType, ThenArgXprType, ElseArgXprType >
 Carray< Index, NumDims >