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Diffstat (limited to 'unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h')
| -rw-r--r-- | unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h | 109 |
1 files changed, 109 insertions, 0 deletions
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h b/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h new file mode 100644 index 000000000..52b803d7f --- /dev/null +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h @@ -0,0 +1,109 @@ +// 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_FORWARD_DECLARATIONS_H +#define EIGEN_CXX11_TENSOR_TENSOR_FORWARD_DECLARATIONS_H + +namespace Eigen { + +// MakePointer class is used as a container of the adress space of the pointer +// on the host and on the device. From the host side it generates the T* pointer +// and when EIGEN_USE_SYCL is used it construct a buffer with a map_allocator to +// T* m_data on the host. It is always called on the device. +// Specialisation of MakePointer class for creating the sycl buffer with +// map_allocator. +template<typename T> struct MakePointer { + typedef T* Type; +}; + +template<typename PlainObjectType, int Options_ = Unaligned, template <class> class MakePointer_ = MakePointer> class TensorMap; +template<typename Scalar_, int NumIndices_, int Options_ = 0, typename IndexType = DenseIndex> class Tensor; +template<typename Scalar_, typename Dimensions, int Options_ = 0, typename IndexType = DenseIndex> class TensorFixedSize; +template<typename PlainObjectType> class TensorRef; +template<typename Derived, int AccessLevel> class TensorBase; + +template<typename NullaryOp, typename PlainObjectType> class TensorCwiseNullaryOp; +template<typename UnaryOp, typename XprType> class TensorCwiseUnaryOp; +template<typename BinaryOp, typename LeftXprType, typename RightXprType> class TensorCwiseBinaryOp; +template<typename TernaryOp, typename Arg1XprType, typename Arg2XprType, typename Arg3XprType> class TensorCwiseTernaryOp; +template<typename IfXprType, typename ThenXprType, typename ElseXprType> class TensorSelectOp; +template<typename Op, typename Dims, typename XprType, template <class> class MakePointer_ = MakePointer > class TensorReductionOp; +template<typename XprType> class TensorIndexTupleOp; +template<typename ReduceOp, typename Dims, typename XprType> class TensorTupleReducerOp; +template<typename Axis, typename LeftXprType, typename RightXprType> class TensorConcatenationOp; +template<typename Dimensions, typename LeftXprType, typename RightXprType> class TensorContractionOp; +template<typename TargetType, typename XprType> class TensorConversionOp; +template<typename Dimensions, typename InputXprType, typename KernelXprType> class TensorConvolutionOp; +template<typename FFT, typename XprType, int FFTDataType, int FFTDirection> class TensorFFTOp; +template<typename PatchDim, typename XprType> class TensorPatchOp; +template<DenseIndex Rows, DenseIndex Cols, typename XprType> class TensorImagePatchOp; +template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType> class TensorVolumePatchOp; +template<typename Broadcast, typename XprType> class TensorBroadcastingOp; +template<DenseIndex DimId, typename XprType> class TensorChippingOp; +template<typename NewDimensions, typename XprType> class TensorReshapingOp; +template<typename XprType> class TensorLayoutSwapOp; +template<typename StartIndices, typename Sizes, typename XprType> class TensorSlicingOp; +template<typename ReverseDimensions, typename XprType> class TensorReverseOp; +template<typename PaddingDimensions, typename XprType> class TensorPaddingOp; +template<typename Shuffle, typename XprType> class TensorShufflingOp; +template<typename Strides, typename XprType> class TensorStridingOp; +template<typename StartIndices, typename StopIndices, typename Strides, typename XprType> class TensorStridingSlicingOp; +template<typename Strides, typename XprType> class TensorInflationOp; +template<typename Generator, typename XprType> class TensorGeneratorOp; +template<typename LeftXprType, typename RightXprType> class TensorAssignOp; +template<typename Op, typename XprType> class TensorScanOp; + +template<typename CustomUnaryFunc, typename XprType> class TensorCustomUnaryOp; +template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType> class TensorCustomBinaryOp; + +template<typename XprType, template <class> class MakePointer_ = MakePointer> class TensorEvalToOp; +template<typename XprType, template <class> class MakePointer_ = MakePointer> class TensorForcedEvalOp; + +template<typename ExpressionType, typename DeviceType> class TensorDevice; +template<typename Derived, typename Device> struct TensorEvaluator; + +struct DefaultDevice; +struct ThreadPoolDevice; +struct GpuDevice; +struct SyclDevice; + +enum FFTResultType { + RealPart = 0, + ImagPart = 1, + BothParts = 2 +}; + +enum FFTDirection { + FFT_FORWARD = 0, + FFT_REVERSE = 1 +}; + + +namespace internal { + +template <typename Device, typename Expression> +struct IsVectorizable { + static const bool value = TensorEvaluator<Expression, Device>::PacketAccess; +}; + +template <typename Expression> +struct IsVectorizable<GpuDevice, Expression> { + static const bool value = TensorEvaluator<Expression, GpuDevice>::PacketAccess && + TensorEvaluator<Expression, GpuDevice>::IsAligned; +}; + +template <typename Expression, typename Device, + bool Vectorizable = IsVectorizable<Device, Expression>::value> +class TensorExecutor; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_CXX11_TENSOR_TENSOR_FORWARD_DECLARATIONS_H |