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Diffstat (limited to 'third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h')
-rw-r--r-- | third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h | 320 |
1 files changed, 0 insertions, 320 deletions
diff --git a/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h b/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h deleted file mode 100644 index 908bdc38ad..0000000000 --- a/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h +++ /dev/null @@ -1,320 +0,0 @@ -// 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_MAP_H -#define EIGEN_CXX11_TENSOR_TENSOR_MAP_H - -namespace Eigen { - -/** \class TensorMap - * \ingroup CXX11_Tensor_Module - * - * \brief A tensor expression mapping an existing array of data. - * - */ - -template<typename PlainObjectType, int Options_> class TensorMap : public TensorBase<TensorMap<PlainObjectType, Options_> > -{ - public: - typedef TensorMap<PlainObjectType, Options_> Self; - typedef typename PlainObjectType::Base Base; - typedef typename Eigen::internal::nested<Self>::type Nested; - typedef typename internal::traits<PlainObjectType>::StorageKind StorageKind; - typedef typename internal::traits<PlainObjectType>::Index Index; - typedef typename internal::traits<PlainObjectType>::Scalar Scalar; - typedef typename internal::packet_traits<Scalar>::type Packet; - typedef typename NumTraits<Scalar>::Real RealScalar; - typedef typename Base::CoeffReturnType CoeffReturnType; - - /* typedef typename internal::conditional< - bool(internal::is_lvalue<PlainObjectType>::value), - Scalar *, - const Scalar *>::type - PointerType;*/ - typedef Scalar* PointerType; - typedef PointerType PointerArgType; - - static const int Options = Options_; - - static const Index NumIndices = PlainObjectType::NumIndices; - typedef typename PlainObjectType::Dimensions Dimensions; - - enum { - IsAligned = ((int(Options_) & Aligned) == Aligned), - PacketAccess = (internal::packet_traits<Scalar>::size > 1), - BlockAccess = false, - Layout = PlainObjectType::Layout, - CoordAccess = true, - }; - - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr) : m_data(dataPtr), m_dimensions() { - // The number of dimensions used to construct a tensor must be equal to the rank of the tensor. - EIGEN_STATIC_ASSERT((0 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE) - } - -#ifdef EIGEN_HAS_VARIADIC_TEMPLATES - template<typename... IndexTypes> EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension, IndexTypes... otherDimensions) : m_data(dataPtr), m_dimensions(firstDimension, otherDimensions...) { - // The number of dimensions used to construct a tensor must be equal to the rank of the tensor. - EIGEN_STATIC_ASSERT((sizeof...(otherDimensions) + 1 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE) - } -#else - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension) : m_data(dataPtr), m_dimensions(firstDimension) { - // The number of dimensions used to construct a tensor must be equal to the rank of the tensor. - EIGEN_STATIC_ASSERT((1 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE) - } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2) : m_data(dataPtr), m_dimensions(dim1, dim2) { - EIGEN_STATIC_ASSERT(2 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE) - } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3) { - EIGEN_STATIC_ASSERT(3 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE) - } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3, Index dim4) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3, dim4) { - EIGEN_STATIC_ASSERT(4 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE) - } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3, Index dim4, Index dim5) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3, dim4, dim5) { - EIGEN_STATIC_ASSERT(5 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE) - } -#endif - - EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, const array<Index, NumIndices>& dimensions) - : m_data(dataPtr), m_dimensions(dimensions) - { } - - template <typename Dimensions> - EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, const Dimensions& dimensions) - : m_data(dataPtr), m_dimensions(dimensions) - { } - - EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PlainObjectType& tensor) - : m_data(tensor.data()), m_dimensions(tensor.dimensions()) - { } - - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE Index rank() const { return m_dimensions.rank(); } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE Index dimension(Index n) const { return m_dimensions[n]; } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE Index size() const { return m_dimensions.TotalSize(); } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE Scalar* data() { return m_data; } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE const Scalar* data() const { return m_data; } - - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE const Scalar& operator()(const array<Index, NumIndices>& indices) const - { - // eigen_assert(checkIndexRange(indices)); - if (PlainObjectType::Options&RowMajor) { - const Index index = m_dimensions.IndexOfRowMajor(indices); - return m_data[index]; - } else { - const Index index = m_dimensions.IndexOfColMajor(indices); - return m_data[index]; - } - } - - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE const Scalar& operator()() const - { - EIGEN_STATIC_ASSERT(NumIndices == 0 || NumIndices == Dynamic, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor."); - eigen_assert(rank() == 0); - return m_data[0]; - } - -#ifdef EIGEN_HAS_VARIADIC_TEMPLATES - template<typename... IndexTypes> EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE const Scalar& operator()(Index firstIndex, IndexTypes... otherIndices) const - { - static_assert(sizeof...(otherIndices) + 1 == NumIndices, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor."); - if (PlainObjectType::Options&RowMajor) { - const Index index = m_dimensions.IndexOfRowMajor(array<Index, NumIndices>{{firstIndex, otherIndices...}}); - return m_data[index]; - } else { - const Index index = m_dimensions.IndexOfColMajor(array<Index, NumIndices>{{firstIndex, otherIndices...}}); - return m_data[index]; - } - } -#else - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE const Scalar& operator()(Index index) const - { - eigen_internal_assert(index >= 0 && index < size()); - return m_data[index]; - } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1) const - { - if (PlainObjectType::Options&RowMajor) { - const Index index = i1 + i0 * m_dimensions[0]; - return m_data[index]; - } else { - const Index index = i0 + i1 * m_dimensions[0]; - return m_data[index]; - } - } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2) const - { - if (PlainObjectType::Options&RowMajor) { - const Index index = i2 + m_dimensions[1] * (i1 + m_dimensions[0] * i0); - return m_data[index]; - } else { - const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * i2); - return m_data[index]; - } - } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3) const - { - if (PlainObjectType::Options&RowMajor) { - const Index index = i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0)); - return m_data[index]; - } else { - const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * i3)); - return m_data[index]; - } - } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4) const - { - if (PlainObjectType::Options&RowMajor) { - const Index index = i4 + m_dimensions[4] * (i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0))); - return m_data[index]; - } else { - const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * (i3 + m_dimensions[3] * i4))); - return m_data[index]; - } - } -#endif - - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE Scalar& operator()(const array<Index, NumIndices>& indices) - { - // eigen_assert(checkIndexRange(indices)); - if (PlainObjectType::Options&RowMajor) { - const Index index = m_dimensions.IndexOfRowMajor(indices); - return m_data[index]; - } else { - const Index index = m_dimensions.IndexOfColMajor(indices); - return m_data[index]; - } - } - - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE Scalar& operator()() - { - static_assert(NumIndices == 0 || NumIndices == Dynamic, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor."); - eigen_internal_assert(rank() == 0); - return m_data[0]; - } - -#ifdef EIGEN_HAS_VARIADIC_TEMPLATES - template<typename... IndexTypes> EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE Scalar& operator()(Index firstIndex, IndexTypes... otherIndices) - { - static_assert(sizeof...(otherIndices) + 1 == NumIndices || NumIndices == Dynamic, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor."); - const std::size_t NumDims = sizeof...(otherIndices) + 1; - if (PlainObjectType::Options&RowMajor) { - const array<Index, NumDims> dims = {firstIndex, otherIndices...}; - const Index index = m_dimensions.IndexOfRowMajor(dims); - return m_data[index]; - } else { - const array<Index, NumDims> dims = {firstIndex, otherIndices...}; - const Index index = m_dimensions.IndexOfColMajor(dims); - return m_data[index]; - } - } -#else - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE Scalar& operator()(Index index) - { - eigen_internal_assert(index >= 0 && index < size()); - return m_data[index]; - } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1) - { - if (PlainObjectType::Options&RowMajor) { - const Index index = i1 + i0 * m_dimensions[0]; - return m_data[index]; - } else { - const Index index = i0 + i1 * m_dimensions[0]; - return m_data[index]; - } - } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2) - { - if (PlainObjectType::Options&RowMajor) { - const Index index = i2 + m_dimensions[1] * (i1 + m_dimensions[0] * i0); - return m_data[index]; - } else { - const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * i2); - return m_data[index]; - } - } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3) - { - if (PlainObjectType::Options&RowMajor) { - const Index index = i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0)); - return m_data[index]; - } else { - const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * i3)); - return m_data[index]; - } - } - EIGEN_DEVICE_FUNC - EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4) - { - if (PlainObjectType::Options&RowMajor) { - const Index index = i4 + m_dimensions[4] * (i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0))); - return m_data[index]; - } else { - const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * (i3 + m_dimensions[3] * i4))); - return m_data[index]; - } - } -#endif - - EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Self& operator=(const Self& other) - { - typedef TensorAssignOp<Self, const Self> Assign; - Assign assign(*this, other); - internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice()); - return *this; - } - - template<typename OtherDerived> - EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE - Self& operator=(const OtherDerived& other) - { - typedef TensorAssignOp<Self, const OtherDerived> Assign; - Assign assign(*this, other); - internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice()); - return *this; - } - - private: - Scalar* m_data; - Dimensions m_dimensions; -}; - -} // end namespace Eigen - -#endif // EIGEN_CXX11_TENSOR_TENSOR_MAP_H |