fix(lifetime): extending the lifetime of temporary objects

examples/tensor/simple_expressions.cpp

@@ -65,6 +65,53 @@ int main()
     std::cout << "% --------------------------- " << std::endl << std::endl;
     std::cout << "F=" << F << ";" << std::endl << std::endl;
 
+    // Calling overloaded operators
+    // and mixing expression templates with prvalues, rvalues, and lvalues
+    {
+      // NOLINT(cppcoreguidelines-avoid-magic-numbers,readability-magic-numbers)
+      auto G = tensor(shape{3,3}, 3.f);
+      auto E_9 = G + G + G;
+
+      // formatted output
+      std::cout << "% --------------------------- " << std::endl;
+      std::cout << "% --------------------------- " << std::endl << std::endl;
+      std::cout << "E(9)=" << tensor(E_9) << ";" << std::endl << std::endl;
+
+      // NOLINT(cppcoreguidelines-avoid-magic-numbers,readability-magic-numbers)
+      auto E_6 = G + 3.f;
+
+      // formatted output
+      std::cout << "% --------------------------- " << std::endl;
+      std::cout << "% --------------------------- " << std::endl << std::endl;
+      std::cout << "E(6)=" << tensor(E_6) << ";" << std::endl << std::endl;
+
+      // NOLINT(cppcoreguidelines-avoid-magic-numbers,readability-magic-numbers)
+      auto const four = 4.f;
+      auto E_10 = E_6 + four;
+
+      // formatted output
+      std::cout << "% --------------------------- " << std::endl;
+      std::cout << "% --------------------------- " << std::endl << std::endl;
+      std::cout << "E(10)=" << tensor(E_10) << ";" << std::endl << std::endl;
+
+      // NOLINT(cppcoreguidelines-avoid-magic-numbers,readability-magic-numbers)
+      auto E_23 = E_10 + E_10 + tensor(shape{3,3}, 3.f);
+
+      // formatted output
+      std::cout << "% --------------------------- " << std::endl;
+      std::cout << "% --------------------------- " << std::endl << std::endl;
+      std::cout << "E(23)=" << tensor(E_23) << ";" << std::endl << std::endl;
+
+      // NOLINT(cppcoreguidelines-avoid-magic-numbers,readability-magic-numbers)
+      auto E_9_7 = tensor(shape{3,3}, 5.4f) + 4.3f;
+
+      // formatted output
+      std::cout << "% --------------------------- " << std::endl;
+      std::cout << "% --------------------------- " << std::endl << std::endl;
+      std::cout << "E(9.7)=" << tensor(E_9_7) << ";" << std::endl << std::endl;
+
+    }
+
   }  catch (const std::exception& e) {
     std::cerr << "Cought exception " << e.what();
     std::cerr << "in the main function of simple expression." << std::endl;

include/boost/numeric/ublas/tensor/expression.hpp

@@ -1,5 +1,6 @@
 //
 //  Copyright (c) 2018-2019, Cem Bassoy, [email protected]
+// 	Copyright (c) 2022, Amit Singh, [email protected]
 //
 //  Distributed under the Boost Software License, Version 1.0. (See
 //  accompanying file LICENSE_1_0.txt or copy at
@@ -13,13 +14,68 @@
 #define BOOST_UBLAS_TENSOR_EXPRESSIONS_HPP
 
 #include <cstddef>
+#include <type_traits>
 #include <boost/numeric/ublas/expression_types.hpp>
 
 #include "tags.hpp"
 
 namespace boost::numeric::ublas::detail
 {
 
+template<class T, class E>
+struct tensor_expression;
+
+template<class T, class EL, class ER, class OP>
+struct binary_tensor_expression;
+
+template<class T, class E, class OP>
+struct unary_tensor_expression;
+
+template<typename E1, typename E2>
+concept same_exp = std::is_same_v< std::decay_t<E1>, std::decay_t<E2> >;
+
+template<typename T>
+struct does_exp_need_cast : std::false_type{};
+
+template<typename T>
+static constexpr bool does_exp_need_cast_v = does_exp_need_cast< std::decay_t<T> >::value;
+
+template<typename E, typename T>
+struct does_exp_need_cast< tensor_expression<T,E> > : std::true_type{};
+
+template<typename E, typename T>
+constexpr auto is_tensor_expression_impl(tensor_expression<T,E> const*) -> std::true_type;
+
+constexpr auto is_tensor_expression_impl(void const*) -> std::false_type;
+
+template<typename E>
+constexpr auto is_matrix_expression_impl(matrix_expression<E> const*) -> std::true_type;
+
+constexpr auto is_matrix_expression_impl(void const*) -> std::false_type;
+
+template<typename E>
+constexpr auto is_vector_expression_impl(vector_expression<E> const*) -> std::true_type;
+
+constexpr auto is_vector_expression_impl(void const*) -> std::false_type;
+
+template<typename E>
+concept TensorExpression = decltype(is_tensor_expression_impl(static_cast<std::decay_t<E> const*>(nullptr)))::value;
+
+// TODO: Remove this concept in the future when we have our own implementation of matrices.
+template<typename E>
+concept MatrixExpression = decltype(is_matrix_expression_impl(static_cast<std::decay_t<E> const*>(nullptr)))::value;
+
+// TODO: Remove this concept in the future when we have our own implementation of vectors.
+template<typename E>
+concept VectorExpression = decltype(is_vector_expression_impl(static_cast<std::decay_t<E> const*>(nullptr)))::value;
+
+template<typename Exp>
+using expression_operand_t = std::conditional_t<
+    !std::is_lvalue_reference_v<Exp>,
+    std::decay_t<Exp>,
+    std::add_lvalue_reference_t< std::add_const_t< std::decay_t<Exp> > >
+>;
+
 /** @\brief base class for tensor expressions
  *
  * \note implements crtp - no use of virtual function calls
@@ -30,7 +86,7 @@ namespace boost::numeric::ublas::detail
  **/
 template<class T, class E>
 struct tensor_expression
-    : public ublas_expression<E>
+    : public ublas_expression<E> // DISCUSS: Do we really need to do derive from ublas_expression?
 {
     //	static const unsigned complexity = 0;
     using expression_type = E;
@@ -40,11 +96,12 @@ struct tensor_expression
     inline
     constexpr auto const& operator()() const noexcept { return *static_cast<const expression_type*> (this); }
 
-    ~tensor_expression() = default;
+    constexpr tensor_expression(tensor_expression&&) noexcept = default;
+    constexpr tensor_expression& operator=(tensor_expression&&) noexcept = default;
+    constexpr ~tensor_expression() = default;
+
     tensor_expression(const tensor_expression&) = delete;
-    tensor_expression(tensor_expression&&) noexcept = delete;
     tensor_expression& operator=(const tensor_expression&) = delete;
-    tensor_expression& operator=(tensor_expression&&) noexcept = delete;
 
 
 protected :
@@ -58,72 +115,76 @@ struct binary_tensor_expression
 {
     using self_type = binary_tensor_expression<T,EL,ER,OP>;
     using tensor_type  = T;
-    using binary_operation = OP;
-    using expression_type_left  = EL;
-    using expression_type_right = ER;
+    using binary_operation = std::decay_t<OP>;
+    using expression_type_left  = expression_operand_t<EL>;
+    using expression_type_right = expression_operand_t<ER>;
     using derived_type =  tensor_expression <tensor_type,self_type>;
 
     using size_type = typename tensor_type::size_type;
 
-    explicit constexpr binary_tensor_expression(expression_type_left  const& l, expression_type_right const& r, binary_operation o) : el(l) , er(r) , op(std::move(o)) {}
-    constexpr binary_tensor_expression(binary_tensor_expression&& l) noexcept = delete;
-    constexpr binary_tensor_expression& operator=(binary_tensor_expression&& l) noexcept = delete;
-    ~binary_tensor_expression() = default;
-
     binary_tensor_expression() = delete;
+
+    template<same_exp<EL> LeftExp, same_exp<ER> RightExp, typename OPType>
+    explicit constexpr binary_tensor_expression(LeftExp&& l, RightExp&& r, OPType&& o) 
+        : el(std::forward<LeftExp>(l)) 
+        , er(std::forward<RightExp>(r)) 
+        , op(std::forward<OPType>(o)) 
+    {}
+    constexpr binary_tensor_expression(binary_tensor_expression&& l) noexcept = default;
+    constexpr binary_tensor_expression& operator=(binary_tensor_expression&& l) noexcept = default;
+    constexpr ~binary_tensor_expression() = default;
+
     binary_tensor_expression(const binary_tensor_expression& l) = delete;
     binary_tensor_expression& operator=(binary_tensor_expression const& l) noexcept = delete;
 
 
+    [[nodiscard]] inline 
+    constexpr decltype(auto) operator()(size_type i) const 
+        requires (does_exp_need_cast_v<expression_type_left> && does_exp_need_cast_v<expression_type_right>)
+    { 
+        return op(el()(i), er()(i));
+    }
+
+    [[nodiscard]] inline 
+    constexpr decltype(auto) operator()(size_type i) const 
+        requires (does_exp_need_cast_v<expression_type_left> && !does_exp_need_cast_v<expression_type_right>)
+    { 
+        return op(el()(i), er(i));
+    }
+
+    [[nodiscard]] inline 
+    constexpr decltype(auto) operator()(size_type i) const 
+        requires (!does_exp_need_cast_v<expression_type_left> && does_exp_need_cast_v<expression_type_right>)
+    { 
+        return op(el(i), er()(i));
+    }
 
     [[nodiscard]] inline 
-    constexpr decltype(auto) operator()(size_type i) const { return op(el(i), er(i)); }
+    constexpr decltype(auto) operator()(size_type i) const { 
+        return op(el(i), er(i)); 
+    }
 
-    expression_type_left const& el;
-    expression_type_right const& er;
+    expression_type_left el;
+    expression_type_right er;
     binary_operation op;
 };
 
 /// @brief helper function to simply instantiation of lambda proxy class
-template<class T1, class T2, class EL, class ER, class OP>
+template<typename T, typename EL, typename ER, typename OP>
+    requires (
+        ( MatrixExpression<EL> || VectorExpression<EL> || TensorExpression<EL> ) &&
+        ( MatrixExpression<ER> || VectorExpression<ER> || TensorExpression<ER> ) 
+    )
 [[nodiscard]] inline
-constexpr auto make_binary_tensor_expression( tensor_expression<T1,EL> const& el, tensor_expression<T2,ER> const& er, OP op) noexcept
+constexpr auto make_binary_tensor_expression( EL&& el, ER&& er, OP&& op) noexcept
 {
-    static_assert( std::is_same_v< typename T1::value_type, typename T2::value_type>,
-        "boost::numeric::ublas::make_binary_tensor_expression(T1,T2) : LHS tensor and RHS tensor should have same value type"
+    return binary_tensor_expression<T,EL,ER,OP>( 
+        std::forward<EL>(el), 
+        std::forward<ER>(er), 
+        std::forward<OP>(op)
     );
-    return binary_tensor_expression<T1,EL,ER,OP>( el(), er(), op) ;
-}
-
-template<class T, class EL, class ER, class OP>
-[[nodiscard]] inline
-constexpr auto make_binary_tensor_expression( matrix_expression<EL> const& el, tensor_expression<T,ER> const& er, OP op) noexcept
-{
-    return binary_tensor_expression<T,EL,ER,OP>( el(), er(), op) ;
 }
 
-template<class T, class EL, class ER, class OP>
-[[nodiscard]] inline
-constexpr auto make_binary_tensor_expression( tensor_expression<T,EL> const& el, matrix_expression<ER> const& er, OP op) noexcept
-{
-    return binary_tensor_expression<T,EL,ER,OP>( el(), er(), op) ;
-}
-
-template<class T, class EL, class ER, class OP>
-[[nodiscard]] inline
-constexpr auto make_binary_tensor_expression( vector_expression<EL> const& el, tensor_expression<T,ER> const& er, OP op) noexcept
-{
-    return binary_tensor_expression<T,EL,ER,OP>( el(), er(), op) ;
-}
-
-template<class T, class EL, class ER, class OP>
-[[nodiscard]] inline
-constexpr auto make_binary_tensor_expression( tensor_expression<T,EL> const& el, vector_expression<ER> const& er, OP op) noexcept
-{
-    return binary_tensor_expression<T,EL,ER,OP>( el(), er(), op) ;
-}
-
-
 
 template<class T, class E, class OP>
 struct unary_tensor_expression
@@ -132,51 +193,53 @@ struct unary_tensor_expression
 
     using self_type = unary_tensor_expression<T,E,OP>;
     using tensor_type  = T;
-    using expression_type = E;
-    using unary_operation = OP;
+    using expression_type = expression_operand_t<E>;
+    using unary_operation = std::decay_t<OP>;
     using derived_type = tensor_expression <T, unary_tensor_expression<T,E,OP>>;
 
     using size_type = typename tensor_type::size_type;
 
-    explicit constexpr unary_tensor_expression(expression_type const& ee, unary_operation o) : e(ee) , op(std::move(o)) {}
-    constexpr unary_tensor_expression(unary_tensor_expression&& l) noexcept = delete;
-    constexpr unary_tensor_expression& operator=(unary_tensor_expression&& l) noexcept = delete;
+    template<same_exp<E> Exp, typename OPType>
+    explicit constexpr unary_tensor_expression(Exp&& ee, OPType&& o) 
+        : e(std::forward<Exp>(ee))
+        , op(std::forward<OPType>(o)) 
+    {}
+    constexpr unary_tensor_expression(unary_tensor_expression&& l) noexcept = default;
+    constexpr unary_tensor_expression& operator=(unary_tensor_expression&& l) noexcept = default;
+    constexpr ~unary_tensor_expression() = default;
 
     constexpr unary_tensor_expression() = delete;
     unary_tensor_expression(unary_tensor_expression const& l) = delete;
     unary_tensor_expression& operator=(unary_tensor_expression const& l) noexcept = delete;
-    ~unary_tensor_expression() = default;
 
     [[nodiscard]] inline constexpr
-      decltype(auto) operator()(size_type i) const { return op(e(i)); }
+    decltype(auto) operator()(size_type i) const 
+        requires does_exp_need_cast_v<expression_type>
+    {
+        return op(e()(i));
+    }
+
+    [[nodiscard]] inline constexpr
+    decltype(auto) operator()(size_type i) const { 
+        return op(e(i));
+    }
 
-    E const& e;
-    OP op;
+    expression_type e;
+    unary_operation op;
 };
 
 // \brief helper function to simply instantiation of lambda proxy class
-template<class T, class E, class OP>
-[[nodiscard]] inline
-constexpr auto make_unary_tensor_expression( tensor_expression<T,E> const& e, OP op) noexcept
-{
-    return unary_tensor_expression<T,E,OP>( e() , op);
-}
-
-template<class T, class E, class OP>
-[[nodiscard]] inline
-constexpr auto make_unary_tensor_expression( matrix_expression<E> const& e, OP op) noexcept
-{
-    return unary_tensor_expression<T,E,OP>( e() , op);
-}
-
-template<class T, class E, class OP>
+template<typename T, typename E, typename OP>
+    requires ( MatrixExpression<E> || VectorExpression<E> || TensorExpression<E> )
 [[nodiscard]] inline
-constexpr auto make_unary_tensor_expression( vector_expression<E> const& e, OP op) noexcept
+constexpr auto make_unary_tensor_expression( E&& e, OP&& op) noexcept
 {
-    return unary_tensor_expression<T,E,OP>( e() , op);
+    return unary_tensor_expression<T, E, OP>( 
+        std::forward<E>(e), 
+        std::forward<OP>(op)
+    );
 }
 
-
 } // namespace boost::numeric::ublas::detail
 
 #endif // BOOST_UBLAS_TENSOR_EXPRESSIONS_HPP