diff options
Diffstat (limited to 'unsupported/Eigen/CXX11/src/Tensor/Tensor.h')
| -rw-r--r-- | unsupported/Eigen/CXX11/src/Tensor/Tensor.h | 37 |
1 files changed, 32 insertions, 5 deletions
diff --git a/unsupported/Eigen/CXX11/src/Tensor/Tensor.h b/unsupported/Eigen/CXX11/src/Tensor/Tensor.h index 1940a9692..8cac2bb12 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/Tensor.h +++ b/unsupported/Eigen/CXX11/src/Tensor/Tensor.h @@ -23,12 +23,12 @@ namespace Eigen { * The %Tensor class encompasses only dynamic-size objects so far. * * The first two template parameters are required: - * \tparam Scalar_ \anchor tensor_tparam_scalar Numeric type, e.g. float, double, int or std::complex<float>. + * \tparam Scalar_ Numeric type, e.g. float, double, int or `std::complex<float>`. * User defined scalar types are supported as well (see \ref user_defined_scalars "here"). * \tparam NumIndices_ Number of indices (i.e. rank of the tensor) * * The remaining template parameters are optional -- in most cases you don't have to worry about them. - * \tparam Options_ \anchor tensor_tparam_options A combination of either \b #RowMajor or \b #ColMajor, and of either + * \tparam Options_ A combination of either \b #RowMajor or \b #ColMajor, and of either * \b #AutoAlign or \b #DontAlign. * The former controls \ref TopicStorageOrders "storage order", and defaults to column-major. The latter controls alignment, which is required * for vectorization. It defaults to aligning tensors. Note that tensors currently do not support any operations that profit from vectorization. @@ -42,13 +42,13 @@ namespace Eigen { * \endcode * * This class can be extended with the help of the plugin mechanism described on the page - * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_TENSOR_PLUGIN. + * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_TENSOR_PLUGIN. * * <i><b>Some notes:</b></i> * * <dl> * <dt><b>Relation to other parts of Eigen:</b></dt> - * <dd>The midterm developement goal for this class is to have a similar hierarchy as Eigen uses for matrices, so that + * <dd>The midterm development goal for this class is to have a similar hierarchy as Eigen uses for matrices, so that * taking blocks or using tensors in expressions is easily possible, including an interface with the vector/matrix code * by providing .asMatrix() and .asVector() (or similar) methods for rank 2 and 1 tensors. However, currently, the %Tensor * class does not provide any of these features and is only available as a stand-alone class that just allows for @@ -112,7 +112,7 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp #if EIGEN_HAS_VARIADIC_TEMPLATES template<typename... IndexTypes> - EIGEN_DEVICE_FUNC inline const Scalar& coeff(Index firstIndex, Index secondIndex, IndexTypes... otherIndices) const + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(Index firstIndex, Index secondIndex, IndexTypes... otherIndices) const { // The number of indices used to access a tensor coefficient must be equal to the rank of the tensor. EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE) @@ -388,6 +388,7 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp resize(TensorEvaluator<const Assign, DefaultDevice>(assign, DefaultDevice()).dimensions()); internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice()); } + template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor(const TensorBase<OtherDerived, WriteAccessors>& other) @@ -398,6 +399,20 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice()); } + #if EIGEN_HAS_RVALUE_REFERENCES + EIGEN_DEVICE_FUNC + EIGEN_STRONG_INLINE Tensor(Self&& other) + : m_storage(std::move(other.m_storage)) + { + } + EIGEN_DEVICE_FUNC + EIGEN_STRONG_INLINE Tensor& operator=(Self&& other) + { + m_storage = std::move(other.m_storage); + return *this; + } + #endif + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor& operator=(const Tensor& other) { @@ -462,6 +477,18 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp // Nothing to do: rank 0 tensors have fixed size } +#ifdef EIGEN_HAS_INDEX_LIST + template <typename FirstType, typename... OtherTypes> + EIGEN_DEVICE_FUNC + void resize(const Eigen::IndexList<FirstType, OtherTypes...>& dimensions) { + array<Index, NumIndices> dims; + for (int i = 0; i < NumIndices; ++i) { + dims[i] = static_cast<Index>(dimensions[i]); + } + resize(dims); + } +#endif + /** Custom Dimension */ #ifdef EIGEN_HAS_SFINAE template<typename CustomDimension, |