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

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This commit is contained in:
Eugene Zhulenev 2019-08-28 17:46:05 -07:00
parent 1187bb65ad
commit bc40d4522c
3 changed files with 74 additions and 34 deletions
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1
unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
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@ -20,6 +20,7 @@ namespace Eigen {
// map_allocator. // map_allocator.
template<typename T> struct MakePointer { template<typename T> struct MakePointer {
typedef T* Type; typedef T* Type;
typedef const T* ConstType;
}; };
template <typename T> template <typename T>

66
unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
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@ -42,13 +42,27 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
typedef typename NumTraits<Scalar>::Real RealScalar; typedef typename NumTraits<Scalar>::Real RealScalar;
typedef typename Base::CoeffReturnType CoeffReturnType; 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 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_; static const int Options = Options_;
@ -63,47 +77,47 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
}; };
EIGEN_DEVICE_FUNC 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. // 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) EIGEN_STATIC_ASSERT((0 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
} }
#if EIGEN_HAS_VARIADIC_TEMPLATES #if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes> EIGEN_DEVICE_FUNC 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. // 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) EIGEN_STATIC_ASSERT((sizeof...(otherDimensions) + 1 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
} }
#else #else
EIGEN_DEVICE_FUNC 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. // 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_STATIC_ASSERT((1 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
} }
EIGEN_DEVICE_FUNC 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_STATIC_ASSERT(2 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
} }
EIGEN_DEVICE_FUNC 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_STATIC_ASSERT(3 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
} }
EIGEN_DEVICE_FUNC 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_STATIC_ASSERT(4 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
} }
EIGEN_DEVICE_FUNC 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) EIGEN_STATIC_ASSERT(5 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
} }
#endif #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) : m_data(dataPtr), m_dimensions(dimensions)
{ } { }
template <typename 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) : m_data(dataPtr), m_dimensions(dimensions)
{ } { }
@ -120,9 +134,9 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
EIGEN_DEVICE_FUNC EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Index size() const { return m_dimensions.TotalSize(); } EIGEN_STRONG_INLINE Index size() const { return m_dimensions.TotalSize(); }
EIGEN_DEVICE_FUNC EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE PointerType data() { return m_data; } EIGEN_STRONG_INLINE StoragePointerType data() { return m_data; }
EIGEN_DEVICE_FUNC 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_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& operator()(const array<Index, NumIndices>& indices) const 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 #endif
EIGEN_DEVICE_FUNC 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)); // eigen_assert(checkIndexRange(indices));
if (PlainObjectType::Options&RowMajor) { if (PlainObjectType::Options&RowMajor) {
@ -226,14 +240,14 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
} }
EIGEN_DEVICE_FUNC EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& operator()() EIGEN_STRONG_INLINE StorageRefType operator()()
{ {
EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE) EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE)
return m_data[0]; return m_data[0];
} }
EIGEN_DEVICE_FUNC EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& operator()(Index index) EIGEN_STRONG_INLINE StorageRefType operator()(Index index)
{ {
eigen_internal_assert(index >= 0 && index < size()); eigen_internal_assert(index >= 0 && index < size());
return m_data[index]; return m_data[index];
@ -241,7 +255,7 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
#if EIGEN_HAS_VARIADIC_TEMPLATES #if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes> EIGEN_DEVICE_FUNC 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."); 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)...)); eigen_assert(internal::all((Eigen::NumTraits<Index>::highest() >= otherIndices)...));
@ -256,7 +270,7 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
} }
#else #else
EIGEN_DEVICE_FUNC 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) { if (PlainObjectType::Options&RowMajor) {
const Index index = i1 + i0 * m_dimensions[1]; 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_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) { if (PlainObjectType::Options&RowMajor) {
const Index index = i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0); 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_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) { if (PlainObjectType::Options&RowMajor) {
const Index index = i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0)); 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_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) { if (PlainObjectType::Options&RowMajor) {
const Index index = i4 + m_dimensions[4] * (i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0))); 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: private:
typename MakePointer_<Scalar>::Type m_data; StoragePointerType m_data;
Dimensions m_dimensions; Dimensions m_dimensions;
}; };

41
unsupported/test/cxx11_tensor_map.cpp
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@ -19,8 +19,8 @@ static void test_0d()
Tensor<int, 0> scalar1; Tensor<int, 0> scalar1;
Tensor<int, 0, RowMajor> scalar2; Tensor<int, 0, RowMajor> scalar2;
TensorMap<Tensor<const int, 0> > scalar3(scalar1.data()); TensorMap<const Tensor<int, 0> > scalar3(scalar1.data());
TensorMap<Tensor<const int, 0, RowMajor> > scalar4(scalar2.data()); TensorMap<const Tensor<int, 0, RowMajor> > scalar4(scalar2.data());
scalar1() = 7; scalar1() = 7;
scalar2() = 13; scalar2() = 13;
@ -37,8 +37,8 @@ static void test_1d()
Tensor<int, 1> vec1(6); Tensor<int, 1> vec1(6);
Tensor<int, 1, RowMajor> vec2(6); Tensor<int, 1, RowMajor> vec2(6);
TensorMap<Tensor<const int, 1> > vec3(vec1.data(), 6); TensorMap<const Tensor<int, 1> > vec3(vec1.data(), 6);
TensorMap<Tensor<const int, 1, RowMajor> > vec4(vec2.data(), 6); TensorMap<const Tensor<int, 1, RowMajor> > vec4(vec2.data(), 6);
vec1(0) = 4; vec2(0) = 0; vec1(0) = 4; vec2(0) = 0;
vec1(1) = 8; vec2(1) = 1; vec1(1) = 8; vec2(1) = 1;
@ -85,8 +85,8 @@ static void test_2d()
mat2(1,1) = 4; mat2(1,1) = 4;
mat2(1,2) = 5; mat2(1,2) = 5;
TensorMap<Tensor<const int, 2> > mat3(mat1.data(), 2, 3); TensorMap<const Tensor<int, 2> > mat3(mat1.data(), 2, 3);
TensorMap<Tensor<const int, 2, RowMajor> > mat4(mat2.data(), 2, 3); TensorMap<const Tensor<int, 2, RowMajor> > mat4(mat2.data(), 2, 3);
VERIFY_IS_EQUAL(mat3.rank(), 2); VERIFY_IS_EQUAL(mat3.rank(), 2);
VERIFY_IS_EQUAL(mat3.size(), 6); 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<const Tensor<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, RowMajor> > mat4(mat2.data(), 2, 3, 7);
VERIFY_IS_EQUAL(mat3.rank(), 3); VERIFY_IS_EQUAL(mat3.rank(), 3);
VERIFY_IS_EQUAL(mat3.size(), 2*3*7); VERIFY_IS_EQUAL(mat3.size(), 2*3*7);
@ -265,6 +265,29 @@ static void test_casting()
VERIFY_IS_EQUAL(sum1, 861); 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) EIGEN_DECLARE_TEST(cxx11_tensor_map)
{ {
CALL_SUBTEST(test_0d()); CALL_SUBTEST(test_0d());
@ -274,4 +297,6 @@ EIGEN_DECLARE_TEST(cxx11_tensor_map)
CALL_SUBTEST(test_from_tensor()); CALL_SUBTEST(test_from_tensor());
CALL_SUBTEST(test_casting()); CALL_SUBTEST(test_casting());
CALL_SUBTEST(test_0d_const_tensor());
} }