GitHub-Proxy/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2025-04-20 08:39:37 +08:00
Code Issues Packages Projects Releases Wiki Activity

Added support for empty dimensions

Browse Source
This commit is contained in:
Benoit Steiner 2015-10-26 11:21:27 -07:00
parent ded4336988
commit 9f721384e0
1 changed files with 17 additions and 18 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

35
unsupported/Eigen/CXX11/src/Tensor/TensorDimensions.h
View File

@ -52,8 +52,8 @@ struct fixed_size_tensor_index_linearization_helper
static inline Index run(array<Index, NumIndices> const& indices, static inline Index run(array<Index, NumIndices> const& indices,
const Dimensions& dimensions) const Dimensions& dimensions)
{ {
return array_get<RowMajor ? n : (NumIndices - n - 1)>(indices) + return array_get<RowMajor ? n - 1 : (NumIndices - n)>(indices) +
dget<RowMajor ? n : (NumIndices - n - 1), Dimensions>::value * dget<RowMajor ? n - 1 : (NumIndices - n), Dimensions>::value *
fixed_size_tensor_index_linearization_helper<Index, NumIndices, n - 1, RowMajor>::run(indices, dimensions); fixed_size_tensor_index_linearization_helper<Index, NumIndices, n - 1, RowMajor>::run(indices, dimensions);
} }
}; };
@ -62,10 +62,9 @@ template<typename Index, std::size_t NumIndices, bool RowMajor>
struct fixed_size_tensor_index_linearization_helper<Index, NumIndices, 0, RowMajor> struct fixed_size_tensor_index_linearization_helper<Index, NumIndices, 0, RowMajor>
{ {
template <typename Dimensions> EIGEN_DEVICE_FUNC template <typename Dimensions> EIGEN_DEVICE_FUNC
static inline Index run(array<Index, NumIndices> const& indices, static inline Index run(array<Index, NumIndices> const&, const Dimensions&)
const Dimensions&)
{ {
return array_get<RowMajor ? 0 : NumIndices - 1>(indices); return 0;
} }
}; };
@ -135,11 +134,11 @@ struct Sizes : internal::numeric_list<std::ptrdiff_t, Indices...> {
template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
size_t IndexOfColMajor(const array<DenseIndex, Base::count>& indices) const { size_t IndexOfColMajor(const array<DenseIndex, Base::count>& indices) const {
return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count - 1, false>::run(indices, *static_cast<const Base*>(this)); 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 template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
size_t IndexOfRowMajor(const array<DenseIndex, Base::count>& indices) const { size_t IndexOfRowMajor(const array<DenseIndex, Base::count>& indices) const {
return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count - 1, true>::run(indices, *static_cast<const Base*>(this)); return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, true>::run(indices, *static_cast<const Base*>(this));
} }
}; };
@ -222,11 +221,11 @@ template <std::size_t V1=0, std::size_t V2=0, std::size_t V3=0, std::size_t V4=0
template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
size_t IndexOfColMajor(const array<DenseIndex, Base::count>& indices) const { size_t IndexOfColMajor(const array<DenseIndex, Base::count>& indices) const {
return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count - 1, false>::run(indices, *reinterpret_cast<const Base*>(this)); 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 template <typename DenseIndex> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
size_t IndexOfRowMajor(const array<DenseIndex, Base::count>& indices) const { size_t IndexOfRowMajor(const array<DenseIndex, Base::count>& indices) const {
return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count - 1, true>::run(indices, *reinterpret_cast<const Base*>(this)); return internal::fixed_size_tensor_index_linearization_helper<DenseIndex, Base::count, Base::count, true>::run(indices, *reinterpret_cast<const Base*>(this));
} }
}; };
@ -402,22 +401,22 @@ template <std::size_t n, std::size_t V1, std::size_t V2, std::size_t V3, std::si
template <typename Dims1, typename Dims2, size_t n, size_t m> template <typename Dims1, typename Dims2, size_t n, size_t m>
struct sizes_match_up_to_dim { struct sizes_match_below_dim {
static inline bool run(Dims1&, Dims2&) { static inline bool run(Dims1& dims1, Dims2& dims2) {
return false; return false;
} }
}; };
template <typename Dims1, typename Dims2, size_t n> template <typename Dims1, typename Dims2, size_t n>
struct sizes_match_up_to_dim<Dims1, Dims2, n, n> { struct sizes_match_below_dim<Dims1, Dims2, n, n> {
static inline bool run(Dims1& dims1, Dims2& dims2) { static inline bool run(Dims1& dims1, Dims2& dims2) {
return (array_get<n>(dims1) == array_get<n>(dims2)) & return (array_get<n-1>(dims1) == array_get<n-1>(dims2)) &
sizes_match_up_to_dim<Dims1, Dims2, n-1, n-1>::run(dims1, dims2); sizes_match_below_dim<Dims1, Dims2, n-1, n-1>::run(dims1, dims2);
} }
}; };
template <typename Dims1, typename Dims2> template <typename Dims1, typename Dims2>
struct sizes_match_up_to_dim<Dims1, Dims2, 0, 0> { struct sizes_match_below_dim<Dims1, Dims2, 0, 0> {
static inline bool run(Dims1& dims1, Dims2& dims2) { static inline bool run(Dims1&, Dims2&) {
return (array_get<0>(dims1) == array_get<0>(dims2)); return true;
} }
}; };
@ -426,7 +425,7 @@ struct sizes_match_up_to_dim<Dims1, Dims2, 0, 0> {
template <typename Dims1, typename Dims2> template <typename Dims1, typename Dims2>
bool dimensions_match(Dims1& dims1, Dims2& dims2) { bool dimensions_match(Dims1& dims1, Dims2& dims2) {
return internal::sizes_match_up_to_dim<Dims1, Dims2, internal::array_size<Dims1>::value-1, internal::array_size<Dims2>::value-1>::run(dims1, 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 } // end namespace Eigen