| // 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_DIMENSIONS_H |
| #define EIGEN_CXX11_TENSOR_TENSOR_DIMENSIONS_H |
| |
| |
| namespace Eigen { |
| |
| /** \internal |
| * |
| * \class TensorDimensions |
| * \ingroup CXX11_Tensor_Module |
| * |
| * \brief Set of classes used to encode and store the dimensions of a Tensor. |
| * |
| * The Sizes class encodes as part of the type the number of dimensions and the |
| * sizes corresponding to each dimension. It uses no storage space since it is |
| * entirely known at compile time. |
| * The DSizes class is its dynamic sibling: the number of dimensions is known |
| * at compile time but the sizes are set during execution. |
| * |
| * \sa Tensor |
| */ |
| |
| // Boilerplate code |
| namespace internal { |
| |
| template<std::size_t n, typename Dimension> struct dget { |
| static const std::size_t value = get<n, Dimension>::value; |
| }; |
| |
| |
| template<typename Index, std::size_t NumIndices, std::size_t n, bool RowMajor> |
| struct fixed_size_tensor_index_linearization_helper |
| { |
| template <typename Dimensions> EIGEN_DEVICE_FUNC |
| static inline Index run(array<Index, NumIndices> const& indices, |
| const Dimensions& dimensions) |
| { |
| return array_get<RowMajor ? n - 1 : (NumIndices - n)>(indices) + |
| dget<RowMajor ? n - 1 : (NumIndices - n), Dimensions>::value * |
| fixed_size_tensor_index_linearization_helper<Index, NumIndices, n - 1, RowMajor>::run(indices, dimensions); |
| } |
| }; |
| |
| template<typename Index, std::size_t NumIndices, bool RowMajor> |
| struct fixed_size_tensor_index_linearization_helper<Index, NumIndices, 0, RowMajor> |
| { |
| template <typename Dimensions> EIGEN_DEVICE_FUNC |
| static inline Index run(array<Index, NumIndices> const&, const Dimensions&) |
| { |
| return 0; |
| } |
| }; |
| |
| template<typename Index, std::size_t n> |
| struct fixed_size_tensor_index_extraction_helper |
| { |
| template <typename Dimensions> EIGEN_DEVICE_FUNC |
| static inline Index run(const Index index, |
| const Dimensions& dimensions) |
| { |
| const Index mult = (index == n-1) ? 1 : 0; |
| return array_get<n-1>(dimensions) * mult + |
| fixed_size_tensor_index_extraction_helper<Index, n - 1>::run(index, dimensions); |
| } |
| }; |
| |
| template<typename Index> |
| struct fixed_size_tensor_index_extraction_helper<Index, 0> |
| { |
| template <typename Dimensions> EIGEN_DEVICE_FUNC |
| static inline Index run(const Index, |
| const Dimensions&) |
| { |
| return 0; |
| } |
| }; |
| |
| } // end namespace internal |
| |
| |
| // Fixed size |
| #ifndef EIGEN_EMULATE_CXX11_META_H |
| template <typename std::ptrdiff_t... Indices> |
| struct Sizes : internal::numeric_list<std::ptrdiff_t, Indices...> { |
| typedef internal::numeric_list<std::ptrdiff_t, Indices...> Base; |
| static const std::ptrdiff_t total_size = internal::arg_prod(Indices...); |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t rank() const { |
| return Base::count; |
| } |
| |
| static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t TotalSize() { |
| return internal::arg_prod(Indices...); |
| } |
| |
| EIGEN_DEVICE_FUNC Sizes() { } |
| template <typename DenseIndex> |
| explicit EIGEN_DEVICE_FUNC Sizes(const array<DenseIndex, Base::count>& /*indices*/) { |
| // todo: add assertion |
| } |
| #if EIGEN_HAS_VARIADIC_TEMPLATES |
| template <typename... DenseIndex> EIGEN_DEVICE_FUNC Sizes(DenseIndex...) { } |
| explicit EIGEN_DEVICE_FUNC Sizes(std::initializer_list<std::ptrdiff_t> /*l*/) { |
| // todo: add assertion |
| } |
| #endif |
| |
| template <typename T> Sizes& operator = (const T& /*other*/) { |
| // add assertion failure if the size of other is different |
| return *this; |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t operator[] (const std::size_t index) const { |
| return internal::fixed_size_tensor_index_extraction_helper<std::ptrdiff_t, Base::count>::run(index, *this); |
| } |
| |
| template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| size_t IndexOfColMajor(const array<DenseIndex, Base::count>& indices) const { |
| return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, false>::run(indices, *static_cast<const Base*>(this)); |
| } |
| template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| size_t IndexOfRowMajor(const array<DenseIndex, Base::count>& indices) const { |
| return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, true>::run(indices, *static_cast<const Base*>(this)); |
| } |
| }; |
| |
| namespace internal { |
| template <typename std::ptrdiff_t... Indices> |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t array_prod(const Sizes<Indices...>&) { |
| return Sizes<Indices...>::total_size; |
| } |
| } |
| |
| #else |
| |
| template <std::size_t n> |
| struct non_zero_size { |
| typedef internal::type2val<std::size_t, n> type; |
| }; |
| template <> |
| struct non_zero_size<0> { |
| typedef internal::null_type type; |
| }; |
| |
| template <std::size_t V1=0, std::size_t V2=0, std::size_t V3=0, std::size_t V4=0, std::size_t V5=0> struct Sizes { |
| typedef typename internal::make_type_list<typename non_zero_size<V1>::type, typename non_zero_size<V2>::type, typename non_zero_size<V3>::type, typename non_zero_size<V4>::type, typename non_zero_size<V5>::type >::type Base; |
| static const size_t count = Base::count; |
| static const std::size_t total_size = internal::arg_prod<Base>::value; |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t rank() const { |
| return count; |
| } |
| |
| static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t TotalSize() { |
| return internal::arg_prod<Base>::value; |
| } |
| |
| Sizes() { } |
| template <typename DenseIndex> |
| explicit Sizes(const array<DenseIndex, Base::count>& /*indices*/) { |
| // todo: add assertion |
| } |
| template <typename T> Sizes& operator = (const T& /*other*/) { |
| // add assertion failure if the size of other is different |
| return *this; |
| } |
| |
| #if EIGEN_HAS_VARIADIC_TEMPLATES |
| template <typename... DenseIndex> Sizes(DenseIndex... /*indices*/) { } |
| explicit Sizes(std::initializer_list<std::size_t>) { |
| // todo: add assertion |
| } |
| #else |
| EIGEN_DEVICE_FUNC explicit Sizes(const DenseIndex) { |
| } |
| EIGEN_DEVICE_FUNC Sizes(const DenseIndex, const DenseIndex) { |
| } |
| EIGEN_DEVICE_FUNC Sizes(const DenseIndex, const DenseIndex, const DenseIndex) { |
| } |
| EIGEN_DEVICE_FUNC Sizes(const DenseIndex, const DenseIndex, const DenseIndex, const DenseIndex) { |
| } |
| EIGEN_DEVICE_FUNC Sizes(const DenseIndex, const DenseIndex, const DenseIndex, const DenseIndex, const DenseIndex) { |
| } |
| #endif |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DenseIndex operator[] (const int index) const { |
| switch (index) { |
| case 0: |
| return internal::get<0, Base>::value; |
| case 1: |
| return internal::get<1, Base>::value; |
| case 2: |
| return internal::get<2, Base>::value; |
| case 3: |
| return internal::get<3, Base>::value; |
| case 4: |
| return internal::get<4, Base>::value; |
| default: |
| eigen_assert(false && "index overflow"); |
| return static_cast<DenseIndex>(-1); |
| } |
| } |
| |
| template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| size_t IndexOfColMajor(const array<DenseIndex, Base::count>& indices) const { |
| return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, false>::run(indices, *reinterpret_cast<const Base*>(this)); |
| } |
| template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| size_t IndexOfRowMajor(const array<DenseIndex, Base::count>& indices) const { |
| return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, true>::run(indices, *reinterpret_cast<const Base*>(this)); |
| } |
| }; |
| |
| namespace internal { |
| template <std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5> |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::size_t array_prod(const Sizes<V1, V2, V3, V4, V5>&) { |
| return Sizes<V1, V2, V3, V4, V5>::total_size; |
| } |
| } |
| |
| #endif |
| |
| // Boilerplate |
| namespace internal { |
| template<typename Index, std::size_t NumIndices, std::size_t n, bool RowMajor> |
| struct tensor_index_linearization_helper |
| { |
| static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| Index run(array<Index, NumIndices> const& indices, array<Index, NumIndices> const& dimensions) |
| { |
| return array_get<RowMajor ? n : (NumIndices - n - 1)>(indices) + |
| array_get<RowMajor ? n : (NumIndices - n - 1)>(dimensions) * |
| tensor_index_linearization_helper<Index, NumIndices, n - 1, RowMajor>::run(indices, dimensions); |
| } |
| }; |
| |
| template<typename Index, std::size_t NumIndices, bool RowMajor> |
| struct tensor_index_linearization_helper<Index, NumIndices, 0, RowMajor> |
| { |
| static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| Index run(array<Index, NumIndices> const& indices, array<Index, NumIndices> const&) |
| { |
| return array_get<RowMajor ? 0 : NumIndices - 1>(indices); |
| } |
| }; |
| } // end namespace internal |
| |
| |
| |
| // Dynamic size |
| template <typename DenseIndex, int NumDims> |
| struct DSizes : array<DenseIndex, NumDims> { |
| typedef array<DenseIndex, NumDims> Base; |
| static const int count = NumDims; |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE size_t rank() const { |
| return NumDims; |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DenseIndex TotalSize() const { |
| return (NumDims == 0) ? 1 : internal::array_prod(*static_cast<const Base*>(this)); |
| } |
| |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DSizes() { |
| for (int i = 0 ; i < NumDims; ++i) { |
| (*this)[i] = 0; |
| } |
| } |
| EIGEN_DEVICE_FUNC explicit DSizes(const array<DenseIndex, NumDims>& a) : Base(a) { } |
| |
| EIGEN_DEVICE_FUNC explicit DSizes(const DenseIndex i0) { |
| eigen_assert(NumDims == 1); |
| (*this)[0] = i0; |
| } |
| |
| #if EIGEN_HAS_VARIADIC_TEMPLATES |
| template<typename... IndexTypes> EIGEN_DEVICE_FUNC |
| EIGEN_STRONG_INLINE explicit DSizes(DenseIndex firstDimension, DenseIndex secondDimension, IndexTypes... otherDimensions) : Base({{firstDimension, secondDimension, otherDimensions...}}) { |
| EIGEN_STATIC_ASSERT(sizeof...(otherDimensions) + 2 == NumDims, YOU_MADE_A_PROGRAMMING_MISTAKE) |
| } |
| #else |
| EIGEN_DEVICE_FUNC DSizes(const DenseIndex i0, const DenseIndex i1) { |
| eigen_assert(NumDims == 2); |
| (*this)[0] = i0; |
| (*this)[1] = i1; |
| } |
| EIGEN_DEVICE_FUNC DSizes(const DenseIndex i0, const DenseIndex i1, const DenseIndex i2) { |
| eigen_assert(NumDims == 3); |
| (*this)[0] = i0; |
| (*this)[1] = i1; |
| (*this)[2] = i2; |
| } |
| EIGEN_DEVICE_FUNC DSizes(const DenseIndex i0, const DenseIndex i1, const DenseIndex i2, const DenseIndex i3) { |
| eigen_assert(NumDims == 4); |
| (*this)[0] = i0; |
| (*this)[1] = i1; |
| (*this)[2] = i2; |
| (*this)[3] = i3; |
| } |
| EIGEN_DEVICE_FUNC DSizes(const DenseIndex i0, const DenseIndex i1, const DenseIndex i2, const DenseIndex i3, const DenseIndex i4) { |
| eigen_assert(NumDims == 5); |
| (*this)[0] = i0; |
| (*this)[1] = i1; |
| (*this)[2] = i2; |
| (*this)[3] = i3; |
| (*this)[4] = i4; |
| } |
| #endif |
| |
| EIGEN_DEVICE_FUNC DSizes& operator = (const array<DenseIndex, NumDims>& other) { |
| *static_cast<Base*>(this) = other; |
| return *this; |
| } |
| |
| // A constexpr would be so much better here |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DenseIndex IndexOfColMajor(const array<DenseIndex, NumDims>& indices) const { |
| return internal::tensor_index_linearization_helper<DenseIndex, NumDims, NumDims - 1, false>::run(indices, *static_cast<const Base*>(this)); |
| } |
| EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DenseIndex IndexOfRowMajor(const array<DenseIndex, NumDims>& indices) const { |
| return internal::tensor_index_linearization_helper<DenseIndex, NumDims, NumDims - 1, true>::run(indices, *static_cast<const Base*>(this)); |
| } |
| }; |
| |
| |
| |
| |
| // Boilerplate |
| namespace internal { |
| template<typename Index, std::size_t NumIndices, std::size_t n, bool RowMajor> |
| struct tensor_vsize_index_linearization_helper |
| { |
| static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| Index run(array<Index, NumIndices> const& indices, std::vector<DenseIndex> const& dimensions) |
| { |
| return array_get<RowMajor ? n : (NumIndices - n - 1)>(indices) + |
| array_get<RowMajor ? n : (NumIndices - n - 1)>(dimensions) * |
| tensor_vsize_index_linearization_helper<Index, NumIndices, n - 1, RowMajor>::run(indices, dimensions); |
| } |
| }; |
| |
| template<typename Index, std::size_t NumIndices, bool RowMajor> |
| struct tensor_vsize_index_linearization_helper<Index, NumIndices, 0, RowMajor> |
| { |
| static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE |
| Index run(array<Index, NumIndices> const& indices, std::vector<DenseIndex> const&) |
| { |
| return array_get<RowMajor ? 0 : NumIndices - 1>(indices); |
| } |
| }; |
| } // end namespace internal |
| |
| |
| namespace internal { |
| |
| template <typename DenseIndex, int NumDims> struct array_size<const DSizes<DenseIndex, NumDims> > { |
| static const size_t value = NumDims; |
| }; |
| template <typename DenseIndex, int NumDims> struct array_size<DSizes<DenseIndex, NumDims> > { |
| static const size_t value = NumDims; |
| }; |
| #ifndef EIGEN_EMULATE_CXX11_META_H |
| template <typename std::ptrdiff_t... Indices> struct array_size<const Sizes<Indices...> > { |
| static const std::ptrdiff_t value = Sizes<Indices...>::count; |
| }; |
| template <typename std::ptrdiff_t... Indices> struct array_size<Sizes<Indices...> > { |
| static const std::ptrdiff_t value = Sizes<Indices...>::count; |
| }; |
| template <std::ptrdiff_t n, typename std::ptrdiff_t... Indices> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t array_get(const Sizes<Indices...>&) { |
| return get<n, internal::numeric_list<std::size_t, Indices...> >::value; |
| } |
| template <std::ptrdiff_t n> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::ptrdiff_t array_get(const Sizes<>&) { |
| eigen_assert(false && "should never be called"); |
| return -1; |
| } |
| #else |
| template <std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5> struct array_size<const Sizes<V1,V2,V3,V4,V5> > { |
| static const size_t value = Sizes<V1,V2,V3,V4,V5>::count; |
| }; |
| template <std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5> struct array_size<Sizes<V1,V2,V3,V4,V5> > { |
| static const size_t value = Sizes<V1,V2,V3,V4,V5>::count; |
| }; |
| template <std::size_t n, std::size_t V1, std::size_t V2, std::size_t V3, std::size_t V4, std::size_t V5> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE std::size_t array_get(const Sizes<V1,V2,V3,V4,V5>&) { |
| return get<n, typename Sizes<V1,V2,V3,V4,V5>::Base>::value; |
| } |
| |
| #endif |
| |
| |
| template <typename Dims1, typename Dims2, size_t n, size_t m> |
| struct sizes_match_below_dim { |
| static EIGEN_DEVICE_FUNC inline bool run(Dims1&, Dims2&) { |
| return false; |
| } |
| }; |
| template <typename Dims1, typename Dims2, size_t n> |
| struct sizes_match_below_dim<Dims1, Dims2, n, n> { |
| static EIGEN_DEVICE_FUNC inline bool run(Dims1& dims1, Dims2& dims2) { |
| return (array_get<n-1>(dims1) == array_get<n-1>(dims2)) & |
| sizes_match_below_dim<Dims1, Dims2, n-1, n-1>::run(dims1, dims2); |
| } |
| }; |
| template <typename Dims1, typename Dims2> |
| struct sizes_match_below_dim<Dims1, Dims2, 0, 0> { |
| static EIGEN_DEVICE_FUNC inline bool run(Dims1&, Dims2&) { |
| return true; |
| } |
| }; |
| |
| } // end namespace internal |
| |
| |
| template <typename Dims1, typename Dims2> |
| EIGEN_DEVICE_FUNC bool dimensions_match(Dims1& dims1, Dims2& dims2) { |
| return internal::sizes_match_below_dim<Dims1, Dims2, internal::array_size<Dims1>::value, internal::array_size<Dims2>::value>::run(dims1, dims2); |
| } |
| |
| } // end namespace Eigen |
| |
| #endif // EIGEN_CXX11_TENSOR_TENSOR_DIMENSIONS_H |