Const correctness in TensorMap<const Tensor<T, ...>> expressions

3 files changed, 74 insertions, 34 deletions

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h b/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
index a95f22631..3cca0c7e9 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
@@ -20,6 +20,7 @@ namespace Eigen {
 // map_allocator.
 template<typename T> struct MakePointer {
   typedef T* Type;
+  typedef const T* ConstType;
 };
 
 template <typename T>
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h b/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
index 395cdf9c8..b28cd822f 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
@@ -42,13 +42,27 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
     typedef typename NumTraits<Scalar>::Real RealScalar;
     typedef typename Base::CoeffReturnType CoeffReturnType;
 
-  /*    typedef typename internal::conditional<
-                         bool(internal::is_lvalue<PlainObjectType>::value),
-                         Scalar *,
-                         const Scalar *>::type
-                     PointerType;*/
     typedef typename MakePointer_<Scalar>::Type PointerType;
-    typedef PointerType PointerArgType;
+    typedef typename MakePointer_<Scalar>::ConstType PointerConstType;
+
+    // WARN: PointerType still can be a pointer to const (const Scalar*), for
+    // example in TensorMap<Tensor<const Scalar, ...>> expression. This type of
+    // expression should be illegal, but adding this restriction is not possible
+    // in practice (see https://bitbucket.org/eigen/eigen/pull-requests/488).
+    typedef typename internal::conditional<
+        bool(internal::is_lvalue<PlainObjectType>::value),
+        PointerType,      // use simple pointer in lvalue expressions
+        PointerConstType  // use const pointer in rvalue expressions
+        >::type StoragePointerType;
+
+    // If TensorMap was constructed over rvalue expression (e.g. const Tensor),
+    // we should return a reference to const from operator() (and others), even
+    // if TensorMap itself is not const.
+    typedef typename internal::conditional<
+        bool(internal::is_lvalue<PlainObjectType>::value),
+        Scalar&,
+        const Scalar&
+        >::type StorageRefType;
 
     static const int Options = Options_;
 
@@ -63,47 +77,47 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
     };
 
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr) : m_data(dataPtr), m_dimensions() {
+    EIGEN_STRONG_INLINE TensorMap(StoragePointerType dataPtr) : m_data(dataPtr), m_dimensions() {
       // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
       EIGEN_STATIC_ASSERT((0 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
     }
 
 #if EIGEN_HAS_VARIADIC_TEMPLATES
     template<typename... IndexTypes> EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension, IndexTypes... otherDimensions) : m_data(dataPtr), m_dimensions(firstDimension, otherDimensions...) {
+    EIGEN_STRONG_INLINE TensorMap(StoragePointerType dataPtr, Index firstDimension, IndexTypes... otherDimensions) : m_data(dataPtr), m_dimensions(firstDimension, otherDimensions...) {
       // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
       EIGEN_STATIC_ASSERT((sizeof...(otherDimensions) + 1 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
     }
 #else
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension) : m_data(dataPtr), m_dimensions(firstDimension) {
+    EIGEN_STRONG_INLINE TensorMap(StoragePointerType dataPtr, Index firstDimension) : m_data(dataPtr), m_dimensions(firstDimension) {
       // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
       EIGEN_STATIC_ASSERT((1 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
     }
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2) : m_data(dataPtr), m_dimensions(dim1, dim2) {
+    EIGEN_STRONG_INLINE TensorMap(StoragePointerType dataPtr, Index dim1, Index dim2) : m_data(dataPtr), m_dimensions(dim1, dim2) {
       EIGEN_STATIC_ASSERT(2 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
     }
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3) {
+    EIGEN_STRONG_INLINE TensorMap(StoragePointerType dataPtr, Index dim1, Index dim2, Index dim3) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3) {
       EIGEN_STATIC_ASSERT(3 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
     }
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3, Index dim4) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3, dim4) {
+    EIGEN_STRONG_INLINE TensorMap(StoragePointerType dataPtr, Index dim1, Index dim2, Index dim3, Index dim4) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3, dim4) {
       EIGEN_STATIC_ASSERT(4 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
     }
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3, Index dim4, Index dim5) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3, dim4, dim5) {
+    EIGEN_STRONG_INLINE TensorMap(StoragePointerType dataPtr, Index dim1, Index dim2, Index dim3, Index dim4, Index dim5) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3, dim4, dim5) {
       EIGEN_STATIC_ASSERT(5 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
     }
 #endif
 
-   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, const array<Index, NumIndices>& dimensions)
+   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(StoragePointerType dataPtr, const array<Index, NumIndices>& dimensions)
       : m_data(dataPtr), m_dimensions(dimensions)
     { }
 
     template <typename Dimensions>
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, const Dimensions& dimensions)
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(StoragePointerType dataPtr, const Dimensions& dimensions)
       : m_data(dataPtr), m_dimensions(dimensions)
     { }
 
@@ -120,9 +134,9 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Index size() const { return m_dimensions.TotalSize(); }
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE PointerType data() { return m_data; }
+    EIGEN_STRONG_INLINE StoragePointerType data() { return m_data; }
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE const PointerType data() const { return m_data; }
+    EIGEN_STRONG_INLINE PointerConstType data() const { return m_data; }
 
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE const Scalar& operator()(const array<Index, NumIndices>& indices) const
@@ -213,7 +227,7 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
 #endif
 
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(const array<Index, NumIndices>& indices)
+    EIGEN_STRONG_INLINE StorageRefType operator()(const array<Index, NumIndices>& indices)
     {
       //      eigen_assert(checkIndexRange(indices));
       if (PlainObjectType::Options&RowMajor) {
@@ -226,14 +240,14 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
     }
 
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()()
+    EIGEN_STRONG_INLINE StorageRefType operator()()
     {
       EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE)
       return m_data[0];
     }
 
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(Index index)
+    EIGEN_STRONG_INLINE StorageRefType operator()(Index index)
     {
       eigen_internal_assert(index >= 0 && index < size());
       return m_data[index];
@@ -241,7 +255,7 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
 
 #if EIGEN_HAS_VARIADIC_TEMPLATES
     template<typename... IndexTypes> EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(Index firstIndex, Index secondIndex, IndexTypes... otherIndices)
+    EIGEN_STRONG_INLINE StorageRefType operator()(Index firstIndex, Index secondIndex, IndexTypes... otherIndices)
     {
       static_assert(sizeof...(otherIndices) + 2 == NumIndices || NumIndices == Dynamic, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor.");
        eigen_assert(internal::all((Eigen::NumTraits<Index>::highest() >= otherIndices)...));
@@ -256,7 +270,7 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
     }
 #else
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1)
+    EIGEN_STRONG_INLINE StorageRefType operator()(Index i0, Index i1)
     {
        if (PlainObjectType::Options&RowMajor) {
          const Index index = i1 + i0 * m_dimensions[1];
@@ -267,7 +281,7 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
       }
     }
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2)
+    EIGEN_STRONG_INLINE StorageRefType operator()(Index i0, Index i1, Index i2)
     {
        if (PlainObjectType::Options&RowMajor) {
          const Index index = i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0);
@@ -278,7 +292,7 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
       }
     }
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3)
+    EIGEN_STRONG_INLINE StorageRefType operator()(Index i0, Index i1, Index i2, Index i3)
     {
       if (PlainObjectType::Options&RowMajor) {
         const Index index = i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0));
@@ -289,7 +303,7 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
       }
     }
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4)
+    EIGEN_STRONG_INLINE StorageRefType operator()(Index i0, Index i1, Index i2, Index i3, Index i4)
     {
       if (PlainObjectType::Options&RowMajor) {
         const Index index = i4 + m_dimensions[4] * (i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0)));
@@ -320,7 +334,7 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
     }
 
   private:
-    typename MakePointer_<Scalar>::Type m_data;
+    StoragePointerType m_data;
     Dimensions m_dimensions;
 };
 
diff --git a/unsupported/test/cxx11_tensor_map.cpp b/unsupported/test/cxx11_tensor_map.cpp
index ce608aca7..dc8532f5c 100644
--- a/unsupported/test/cxx11_tensor_map.cpp
+++ b/unsupported/test/cxx11_tensor_map.cpp
@@ -19,8 +19,8 @@ static void test_0d()
   Tensor<int, 0> scalar1;
   Tensor<int, 0, RowMajor> scalar2;
 
-  TensorMap<Tensor<const int, 0> > scalar3(scalar1.data());
-  TensorMap<Tensor<const int, 0, RowMajor> > scalar4(scalar2.data());
+  TensorMap<const Tensor<int, 0> > scalar3(scalar1.data());
+  TensorMap<const Tensor<int, 0, RowMajor> > scalar4(scalar2.data());
 
   scalar1() = 7;
   scalar2() = 13;
@@ -37,8 +37,8 @@ static void test_1d()
   Tensor<int, 1> vec1(6);
   Tensor<int, 1, RowMajor> vec2(6);
 
-  TensorMap<Tensor<const int, 1> > vec3(vec1.data(), 6);
-  TensorMap<Tensor<const int, 1, RowMajor> > vec4(vec2.data(), 6);
+  TensorMap<const Tensor<int, 1> > vec3(vec1.data(), 6);
+  TensorMap<const Tensor<int, 1, RowMajor> > vec4(vec2.data(), 6);
 
   vec1(0) = 4;  vec2(0) = 0;
   vec1(1) = 8;  vec2(1) = 1;
@@ -85,8 +85,8 @@ static void test_2d()
   mat2(1,1) = 4;
   mat2(1,2) = 5;
 
-  TensorMap<Tensor<const int, 2> > mat3(mat1.data(), 2, 3);
-  TensorMap<Tensor<const int, 2, RowMajor> > mat4(mat2.data(), 2, 3);
+  TensorMap<const Tensor<int, 2> > mat3(mat1.data(), 2, 3);
+  TensorMap<const Tensor<int, 2, RowMajor> > mat4(mat2.data(), 2, 3);
 
   VERIFY_IS_EQUAL(mat3.rank(), 2);
   VERIFY_IS_EQUAL(mat3.size(), 6);
@@ -129,8 +129,8 @@ static void test_3d()
     }
   }
 
-  TensorMap<Tensor<const int, 3> > mat3(mat1.data(), 2, 3, 7);
-  TensorMap<Tensor<const int, 3, RowMajor> > mat4(mat2.data(), 2, 3, 7);
+  TensorMap<const Tensor<int, 3> > mat3(mat1.data(), 2, 3, 7);
+  TensorMap<const Tensor<int, 3, RowMajor> > mat4(mat2.data(), 2, 3, 7);
 
   VERIFY_IS_EQUAL(mat3.rank(), 3);
   VERIFY_IS_EQUAL(mat3.size(), 2*3*7);
@@ -265,6 +265,29 @@ static void test_casting()
   VERIFY_IS_EQUAL(sum1, 861);
 }
 
+template<typename T>
+static const T& add_const(T& value) {
+  return value;
+}
+
+static void test_0d_const_tensor()
+{
+  Tensor<int, 0> scalar1;
+  Tensor<int, 0, RowMajor> scalar2;
+
+  TensorMap<const Tensor<int, 0> > scalar3(add_const(scalar1).data());
+  TensorMap<const Tensor<int, 0, RowMajor> > scalar4(add_const(scalar2).data());
+
+  scalar1() = 7;
+  scalar2() = 13;
+
+  VERIFY_IS_EQUAL(scalar1.rank(), 0);
+  VERIFY_IS_EQUAL(scalar1.size(), 1);
+
+  VERIFY_IS_EQUAL(scalar3(), 7);
+  VERIFY_IS_EQUAL(scalar4(), 13);
+}
+
 EIGEN_DECLARE_TEST(cxx11_tensor_map)
 {
   CALL_SUBTEST(test_0d());
@@ -274,4 +297,6 @@ EIGEN_DECLARE_TEST(cxx11_tensor_map)
 
   CALL_SUBTEST(test_from_tensor());
   CALL_SUBTEST(test_casting());
+
+  CALL_SUBTEST(test_0d_const_tensor());
 }