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- // Copyright (c) 2018-2019
- // Cem Bassoy
- //
- // Distributed under the Boost Software License, Version 1.0. (See
- // accompanying file LICENSE_1_0.txt or copy at
- // http://www.boost.org/LICENSE_1_0.txt)
- //
- // The authors gratefully acknowledge the support of
- // Fraunhofer and Google in producing this work
- // which started as a Google Summer of Code project.
- //
- /// \file tensor.hpp Definition for the tensor template class
- #ifndef BOOST_UBLAS_TENSOR_IMPL_HPP
- #define BOOST_UBLAS_TENSOR_IMPL_HPP
- #include <boost/config.hpp>
- #include <initializer_list>
- #include "algorithms.hpp"
- #include "expression.hpp"
- #include "expression_evaluation.hpp"
- #include "extents.hpp"
- #include "strides.hpp"
- #include "index.hpp"
- namespace boost { namespace numeric { namespace ublas {
- template<class T, class F, class A>
- class tensor;
- template<class T, class F, class A>
- class matrix;
- template<class T, class A>
- class vector;
- ///** \brief Base class for Tensor container models
- // *
- // * it does not model the Tensor concept but all derived types should.
- // * The class defines a common base type and some common interface for all
- // * statically derived Tensor classes
- // * We implement the casts to the statically derived type.
- // */
- //template<class C>
- //class tensor_container:
- // public detail::tensor_expression<C>
- //{
- //public:
- // static const unsigned complexity = 0;
- // typedef C container_type;
- // typedef tensor_tag type_category;
- // BOOST_UBLAS_INLINE
- // const container_type &operator () () const {
- // return *static_cast<const container_type *> (this);
- // }
- // BOOST_UBLAS_INLINE
- // container_type &operator () () {
- // return *static_cast<container_type *> (this);
- // }
- //};
- /** @brief A dense tensor of values of type \c T.
- *
- * For a \f$n\f$-dimensional tensor \f$v\f$ and \f$0\leq i < n\f$ every element \f$v_i\f$ is mapped
- * to the \f$i\f$-th element of the container. A storage type \c A can be specified which defaults to \c unbounded_array.
- * Elements are constructed by \c A, which need not initialise their value.
- *
- * @tparam T type of the objects stored in the tensor (like int, double, complex,...)
- * @tparam A The type of the storage array of the tensor. Default is \c unbounded_array<T>. \c <bounded_array<T> and \c std::vector<T> can also be used
- */
- template<class T, class F = first_order, class A = std::vector<T,std::allocator<T>> >
- class tensor:
- public detail::tensor_expression<tensor<T, F, A>,tensor<T, F, A>>
- {
- static_assert( std::is_same<F,first_order>::value ||
- std::is_same<F,last_order >::value, "boost::numeric::tensor template class only supports first- or last-order storage formats.");
- using self_type = tensor<T, F, A>;
- public:
- template<class derived_type>
- using tensor_expression_type = detail::tensor_expression<self_type,derived_type>;
- template<class derived_type>
- using matrix_expression_type = matrix_expression<derived_type>;
- template<class derived_type>
- using vector_expression_type = vector_expression<derived_type>;
- using super_type = tensor_expression_type<self_type>;
- // static_assert(std::is_same_v<tensor_expression_type<self_type>, detail::tensor_expression<tensor<T,F,A>,tensor<T,F,A>>>, "tensor_expression_type<self_type>");
- using array_type = A;
- using layout_type = F;
- using size_type = typename array_type::size_type;
- using difference_type = typename array_type::difference_type;
- using value_type = typename array_type::value_type;
- using reference = typename array_type::reference;
- using const_reference = typename array_type::const_reference;
- using pointer = typename array_type::pointer;
- using const_pointer = typename array_type::const_pointer;
- using iterator = typename array_type::iterator;
- using const_iterator = typename array_type::const_iterator;
- using reverse_iterator = typename array_type::reverse_iterator;
- using const_reverse_iterator = typename array_type::const_reverse_iterator;
- using tensor_temporary_type = self_type;
- using storage_category = dense_tag;
- using strides_type = basic_strides<std::size_t,layout_type>;
- using extents_type = shape;
- using matrix_type = matrix<value_type,layout_type,array_type>;
- using vector_type = vector<value_type,array_type>;
- /** @brief Constructs a tensor.
- *
- * @note the tensor is empty.
- * @note the tensor needs to reshaped for further use.
- *
- */
- BOOST_UBLAS_INLINE
- constexpr tensor ()
- : tensor_expression_type<self_type>() // container_type
- , extents_()
- , strides_()
- , data_()
- {
- }
- /** @brief Constructs a tensor with an initializer list
- *
- * By default, its elements are initialized to 0.
- *
- * @code tensor<float> A{4,2,3}; @endcode
- *
- * @param l initializer list for setting the dimension extents of the tensor
- */
- explicit BOOST_UBLAS_INLINE
- tensor (std::initializer_list<size_type> l)
- : tensor_expression_type<self_type>()
- , extents_ (std::move(l))
- , strides_ (extents_)
- , data_ (extents_.product())
- {
- }
- /** @brief Constructs a tensor with a \c shape
- *
- * By default, its elements are initialized to 0.
- *
- * @code tensor<float> A{extents{4,2,3}}; @endcode
- *
- * @param s initial tensor dimension extents
- */
- explicit BOOST_UBLAS_INLINE
- tensor (extents_type const& s)
- : tensor_expression_type<self_type>() //tensor_container<self_type>()
- , extents_ (s)
- , strides_ (extents_)
- , data_ (extents_.product())
- {}
- /** @brief Constructs a tensor with a \c shape and initiates it with one-dimensional data
- *
- * @code tensor<float> A{extents{4,2,3}, array }; @endcode
- *
- *
- * @param s initial tensor dimension extents
- * @param a container of \c array_type that is copied according to the storage layout
- */
- BOOST_UBLAS_INLINE
- tensor (extents_type const& s, const array_type &a)
- : tensor_expression_type<self_type>() //tensor_container<self_type>()
- , extents_ (s)
- , strides_ (extents_)
- , data_ (a)
- {
- if(this->extents_.product() != this->data_.size())
- throw std::runtime_error("Error in boost::numeric::ublas::tensor: size of provided data and specified extents do not match.");
- }
- /** @brief Constructs a tensor using a shape tuple and initiates it with a value.
- *
- * @code tensor<float> A{extents{4,2,3}, 1 }; @endcode
- *
- * @param e initial tensor dimension extents
- * @param i initial value of all elements of type \c value_type
- */
- BOOST_UBLAS_INLINE
- tensor (extents_type const& e, const value_type &i)
- : tensor_expression_type<self_type>() //tensor_container<self_type> ()
- , extents_ (e)
- , strides_ (extents_)
- , data_ (extents_.product(), i)
- {}
- /** @brief Constructs a tensor from another tensor
- *
- * @param v tensor to be copied.
- */
- BOOST_UBLAS_INLINE
- tensor (const tensor &v)
- : tensor_expression_type<self_type>()
- , extents_ (v.extents_)
- , strides_ (v.strides_)
- , data_ (v.data_ )
- {}
- /** @brief Constructs a tensor from another tensor
- *
- * @param v tensor to be moved.
- */
- BOOST_UBLAS_INLINE
- tensor (tensor &&v)
- : tensor_expression_type<self_type>() //tensor_container<self_type> ()
- , extents_ (std::move(v.extents_))
- , strides_ (std::move(v.strides_))
- , data_ (std::move(v.data_ ))
- {}
- /** @brief Constructs a tensor with a matrix
- *
- * \note Initially the tensor will be two-dimensional.
- *
- * @param v matrix to be copied.
- */
- BOOST_UBLAS_INLINE
- tensor (const matrix_type &v)
- : tensor_expression_type<self_type>()
- , extents_ ()
- , strides_ ()
- , data_ (v.data())
- {
- if(!data_.empty()){
- extents_ = extents_type{v.size1(),v.size2()};
- strides_ = strides_type(extents_);
- }
- }
- /** @brief Constructs a tensor with a matrix
- *
- * \note Initially the tensor will be two-dimensional.
- *
- * @param v matrix to be moved.
- */
- BOOST_UBLAS_INLINE
- tensor (matrix_type &&v)
- : tensor_expression_type<self_type>()
- , extents_ {}
- , strides_ {}
- , data_ {}
- {
- if(v.size1()*v.size2() != 0){
- extents_ = extents_type{v.size1(),v.size2()};
- strides_ = strides_type(extents_);
- data_ = std::move(v.data());
- }
- }
- /** @brief Constructs a tensor using a \c vector
- *
- * @note It is assumed that vector is column vector
- * @note Initially the tensor will be one-dimensional.
- *
- * @param v vector to be copied.
- */
- BOOST_UBLAS_INLINE
- tensor (const vector_type &v)
- : tensor_expression_type<self_type>()
- , extents_ ()
- , strides_ ()
- , data_ (v.data())
- {
- if(!data_.empty()){
- extents_ = extents_type{data_.size(),1};
- strides_ = strides_type(extents_);
- }
- }
- /** @brief Constructs a tensor using a \c vector
- *
- * @param v vector to be moved.
- */
- BOOST_UBLAS_INLINE
- tensor (vector_type &&v)
- : tensor_expression_type<self_type>()
- , extents_ {}
- , strides_ {}
- , data_ {}
- {
- if(v.size() != 0){
- extents_ = extents_type{v.size(),1};
- strides_ = strides_type(extents_);
- data_ = std::move(v.data());
- }
- }
- /** @brief Constructs a tensor with another tensor with a different layout
- *
- * @param other tensor with a different layout to be copied.
- */
- BOOST_UBLAS_INLINE
- template<class other_layout>
- tensor (const tensor<value_type, other_layout> &other)
- : tensor_expression_type<self_type> ()
- , extents_ (other.extents())
- , strides_ (other.extents())
- , data_ (other.extents().product())
- {
- copy(this->rank(), this->extents().data(),
- this->data(), this->strides().data(),
- other.data(), other.strides().data());
- }
- /** @brief Constructs a tensor with an tensor expression
- *
- * @code tensor<float> A = B + 3 * C; @endcode
- *
- * @note type must be specified of tensor must be specified.
- * @note dimension extents are extracted from tensors within the expression.
- *
- * @param expr tensor expression
- */
- BOOST_UBLAS_INLINE
- template<class derived_type>
- tensor (const tensor_expression_type<derived_type> &expr)
- : tensor_expression_type<self_type> ()
- , extents_ ( detail::retrieve_extents(expr) )
- , strides_ ( extents_ )
- , data_ ( extents_.product() )
- {
- static_assert( detail::has_tensor_types<self_type, tensor_expression_type<derived_type>>::value,
- "Error in boost::numeric::ublas::tensor: expression does not contain a tensor. cannot retrieve shape.");
- detail::eval( *this, expr );
- }
- /** @brief Constructs a tensor with a matrix expression
- *
- * @code tensor<float> A = B + 3 * C; @endcode
- *
- * @note matrix expression is evaluated and pushed into a temporary matrix before assignment.
- * @note extents are automatically extracted from the temporary matrix
- *
- * @param expr matrix expression
- */
- BOOST_UBLAS_INLINE
- template<class derived_type>
- tensor (const matrix_expression_type<derived_type> &expr)
- : tensor( matrix_type ( expr ) )
- {
- }
- /** @brief Constructs a tensor with a vector expression
- *
- * @code tensor<float> A = b + 3 * b; @endcode
- *
- * @note matrix expression is evaluated and pushed into a temporary matrix before assignment.
- * @note extents are automatically extracted from the temporary matrix
- *
- * @param expr vector expression
- */
- BOOST_UBLAS_INLINE
- template<class derived_type>
- tensor (const vector_expression_type<derived_type> &expr)
- : tensor( vector_type ( expr ) )
- {
- }
- /** @brief Evaluates the tensor_expression and assigns the results to the tensor
- *
- * @code A = B + C * 2; @endcode
- *
- * @note rank and dimension extents of the tensors in the expressions must conform with this tensor.
- *
- * @param expr expression that is evaluated.
- */
- BOOST_UBLAS_INLINE
- template<class derived_type>
- tensor &operator = (const tensor_expression_type<derived_type> &expr)
- {
- detail::eval(*this, expr);
- return *this;
- }
- tensor& operator=(tensor other)
- {
- swap (*this, other);
- return *this;
- }
- tensor& operator=(const_reference v)
- {
- std::fill(this->begin(), this->end(), v);
- return *this;
- }
- /** @brief Returns true if the tensor is empty (\c size==0) */
- BOOST_UBLAS_INLINE
- bool empty () const {
- return this->data_.empty();
- }
- /** @brief Returns the size of the tensor */
- BOOST_UBLAS_INLINE
- size_type size () const {
- return this->data_.size ();
- }
- /** @brief Returns the size of the tensor */
- BOOST_UBLAS_INLINE
- size_type size (size_type r) const {
- return this->extents_.at(r);
- }
- /** @brief Returns the number of dimensions/modes of the tensor */
- BOOST_UBLAS_INLINE
- size_type rank () const {
- return this->extents_.size();
- }
- /** @brief Returns the number of dimensions/modes of the tensor */
- BOOST_UBLAS_INLINE
- size_type order () const {
- return this->extents_.size();
- }
- /** @brief Returns the strides of the tensor */
- BOOST_UBLAS_INLINE
- strides_type const& strides () const {
- return this->strides_;
- }
- /** @brief Returns the extents of the tensor */
- BOOST_UBLAS_INLINE
- extents_type const& extents () const {
- return this->extents_;
- }
- /** @brief Returns a \c const reference to the container. */
- BOOST_UBLAS_INLINE
- const_pointer data () const {
- return this->data_.data();
- }
- /** @brief Returns a \c const reference to the container. */
- BOOST_UBLAS_INLINE
- pointer data () {
- return this->data_.data();
- }
- /** @brief Element access using a single index.
- *
- * @code auto a = A[i]; @endcode
- *
- * @param i zero-based index where 0 <= i < this->size()
- */
- BOOST_UBLAS_INLINE
- const_reference operator [] (size_type i) const {
- return this->data_[i];
- }
- /** @brief Element access using a single index.
- *
- *
- * @code A[i] = a; @endcode
- *
- * @param i zero-based index where 0 <= i < this->size()
- */
- BOOST_UBLAS_INLINE
- reference operator [] (size_type i)
- {
- return this->data_[i];
- }
- /** @brief Element access using a multi-index or single-index.
- *
- *
- * @code auto a = A.at(i,j,k); @endcode or
- * @code auto a = A.at(i); @endcode
- *
- * @param i zero-based index where 0 <= i < this->size() if sizeof...(is) == 0, else 0<= i < this->size(0)
- * @param is zero-based indices where 0 <= is[r] < this->size(r) where 0 < r < this->rank()
- */
- template<class ... size_types>
- BOOST_UBLAS_INLINE
- const_reference at (size_type i, size_types ... is) const {
- if constexpr (sizeof...(is) == 0)
- return this->data_[i];
- else
- return this->data_[detail::access<0ul>(size_type(0),this->strides_,i,std::forward<size_types>(is)...)];
- }
- /** @brief Element access using a multi-index or single-index.
- *
- *
- * @code A.at(i,j,k) = a; @endcode or
- * @code A.at(i) = a; @endcode
- *
- * @param i zero-based index where 0 <= i < this->size() if sizeof...(is) == 0, else 0<= i < this->size(0)
- * @param is zero-based indices where 0 <= is[r] < this->size(r) where 0 < r < this->rank()
- */
- BOOST_UBLAS_INLINE
- template<class ... size_types>
- reference at (size_type i, size_types ... is) {
- if constexpr (sizeof...(is) == 0)
- return this->data_[i];
- else
- return this->data_[detail::access<0ul>(size_type(0),this->strides_,i,std::forward<size_types>(is)...)];
- }
- /** @brief Element access using a single index.
- *
- *
- * @code A(i) = a; @endcode
- *
- * @param i zero-based index where 0 <= i < this->size()
- */
- BOOST_UBLAS_INLINE
- const_reference operator()(size_type i) const {
- return this->data_[i];
- }
- /** @brief Element access using a single index.
- *
- * @code A(i) = a; @endcode
- *
- * @param i zero-based index where 0 <= i < this->size()
- */
- BOOST_UBLAS_INLINE
- reference operator()(size_type i){
- return this->data_[i];
- }
- /** @brief Generates a tensor index for tensor contraction
- *
- *
- * @code auto Ai = A(_i,_j,k); @endcode
- *
- * @param i placeholder
- * @param is zero-based indices where 0 <= is[r] < this->size(r) where 0 < r < this->rank()
- */
- BOOST_UBLAS_INLINE
- template<std::size_t I, class ... index_types>
- decltype(auto) operator() (index::index_type<I> p, index_types ... ps) const
- {
- constexpr auto N = sizeof...(ps)+1;
- if( N != this->rank() )
- throw std::runtime_error("Error in boost::numeric::ublas::operator(): size of provided index_types does not match with the rank.");
- return std::make_pair( std::cref(*this), std::make_tuple( p, std::forward<index_types>(ps)... ) );
- }
- /** @brief Reshapes the tensor
- *
- *
- * (1) @code A.reshape(extents{m,n,o}); @endcode or
- * (2) @code A.reshape(extents{m,n,o},4); @endcode
- *
- * If the size of this smaller than the specified extents than
- * default constructed (1) or specified (2) value is appended.
- *
- * @note rank of the tensor might also change.
- *
- * @param e extents with which the tensor is reshaped.
- * @param v value which is appended if the tensor is enlarged.
- */
- BOOST_UBLAS_INLINE
- void reshape (extents_type const& e, value_type v = value_type{})
- {
- this->extents_ = e;
- this->strides_ = strides_type(this->extents_);
- if(e.product() != this->size())
- this->data_.resize (this->extents_.product(), v);
- }
- friend void swap(tensor& lhs, tensor& rhs) {
- std::swap(lhs.data_ , rhs.data_ );
- std::swap(lhs.extents_, rhs.extents_);
- std::swap(lhs.strides_, rhs.strides_);
- }
- /// \brief return an iterator on the first element of the tensor
- BOOST_UBLAS_INLINE
- const_iterator begin () const {
- return data_.begin ();
- }
- /// \brief return an iterator on the first element of the tensor
- BOOST_UBLAS_INLINE
- const_iterator cbegin () const {
- return data_.cbegin ();
- }
- /// \brief return an iterator after the last element of the tensor
- BOOST_UBLAS_INLINE
- const_iterator end () const {
- return data_.end();
- }
- /// \brief return an iterator after the last element of the tensor
- BOOST_UBLAS_INLINE
- const_iterator cend () const {
- return data_.cend ();
- }
- /// \brief Return an iterator on the first element of the tensor
- BOOST_UBLAS_INLINE
- iterator begin () {
- return data_.begin();
- }
- /// \brief Return an iterator at the end of the tensor
- BOOST_UBLAS_INLINE
- iterator end () {
- return data_.end();
- }
- /// \brief Return a const reverse iterator before the first element of the reversed tensor (i.e. end() of normal tensor)
- BOOST_UBLAS_INLINE
- const_reverse_iterator rbegin () const {
- return data_.rbegin();
- }
- /// \brief Return a const reverse iterator before the first element of the reversed tensor (i.e. end() of normal tensor)
- BOOST_UBLAS_INLINE
- const_reverse_iterator crbegin () const {
- return data_.crbegin();
- }
- /// \brief Return a const reverse iterator on the end of the reverse tensor (i.e. first element of the normal tensor)
- BOOST_UBLAS_INLINE
- const_reverse_iterator rend () const {
- return data_.rend();
- }
- /// \brief Return a const reverse iterator on the end of the reverse tensor (i.e. first element of the normal tensor)
- BOOST_UBLAS_INLINE
- const_reverse_iterator crend () const {
- return data_.crend();
- }
- /// \brief Return a const reverse iterator before the first element of the reversed tensor (i.e. end() of normal tensor)
- BOOST_UBLAS_INLINE
- reverse_iterator rbegin () {
- return data_.rbegin();
- }
- /// \brief Return a const reverse iterator on the end of the reverse tensor (i.e. first element of the normal tensor)
- BOOST_UBLAS_INLINE
- reverse_iterator rend () {
- return data_.rend();
- }
- #if 0
- // -------------
- // Serialization
- // -------------
- /// Serialize a tensor into and archive as defined in Boost
- /// \param ar Archive object. Can be a flat file, an XML file or any other stream
- /// \param file_version Optional file version (not yet used)
- template<class Archive>
- void serialize(Archive & ar, const unsigned int /* file_version */){
- ar & serialization::make_nvp("data",data_);
- }
- #endif
- private:
- extents_type extents_;
- strides_type strides_;
- array_type data_;
- };
- }}} // namespaces
- #endif
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