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Require recent GCC and MSCV and removed EIGEN_HAS_CXX14 and some other feature test macros

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This commit is contained in:
Erik Schultheis
2021-12-01 00:48:34 +00:00
committed by Rasmus Munk Larsen
parent 085c2fc5d5
commit ec2fd0f7ed
39 changed files with 52 additions and 702 deletions
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80
unsupported/Eigen/CXX11/src/Tensor/Tensor.h
View File

@@ -113,7 +113,6 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
inline Self& base() { return *this; }
inline const Self& base() const { return *this; }
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(Index firstIndex, Index secondIndex, IndexTypes... otherIndices) const
{
@@ -121,7 +120,6 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
return coeff(array<Index, NumIndices>{{firstIndex, secondIndex, otherIndices...}});
}
#endif
// normal indices
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(const array<Index, NumIndices>& indices) const
@@ -153,7 +151,6 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
return m_storage.data()[index];
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes>
inline Scalar& coeffRef(Index firstIndex, Index secondIndex, IndexTypes... otherIndices)
{
@@ -161,7 +158,6 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
return coeffRef(array<Index, NumIndices>{{firstIndex, secondIndex, otherIndices...}});
}
#endif
// normal indices
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(const array<Index, NumIndices>& indices)
@@ -193,7 +189,6 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
return m_storage.data()[index];
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes>
inline const Scalar& operator()(Index firstIndex, Index secondIndex, IndexTypes... otherIndices) const
{
@@ -201,28 +196,6 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
return this->operator()(array<Index, NumIndices>{{firstIndex, secondIndex, otherIndices...}});
}
#else
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1) const
{
return coeff(array<Index, 2>(i0, i1));
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2) const
{
return coeff(array<Index, 3>(i0, i1, i2));
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3) const
{
return coeff(array<Index, 4>(i0, i1, i2, i3));
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4) const
{
return coeff(array<Index, 5>(i0, i1, i2, i3, i4));
}
#endif
// custom indices
#ifdef EIGEN_HAS_SFINAE
@@ -260,7 +233,6 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
return coeff(index);
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes>
inline Scalar& operator()(Index firstIndex, Index secondIndex, IndexTypes... otherIndices)
{
@@ -268,28 +240,6 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
return operator()(array<Index, NumIndices>{{firstIndex, secondIndex, otherIndices...}});
}
#else
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1)
{
return coeffRef(array<Index, 2>(i0, i1));
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2)
{
return coeffRef(array<Index, 3>(i0, i1, i2));
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3)
{
return coeffRef(array<Index, 4>(i0, i1, i2, i3));
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4)
{
return coeffRef(array<Index, 5>(i0, i1, i2, i3, i4));
}
#endif
// normal indices
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& operator()(const array<Index, NumIndices>& indices)
@@ -339,7 +289,6 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
{
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor(Index firstDimension, IndexTypes... otherDimensions)
: m_storage(firstDimension, otherDimensions...)
@@ -347,33 +296,6 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
// 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, YOU_MADE_A_PROGRAMMING_MISTAKE)
}
#else
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Tensor(Index dim1)
: m_storage(dim1, array<Index, 1>(dim1))
{
EIGEN_STATIC_ASSERT(1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor(Index dim1, Index dim2)
: m_storage(dim1*dim2, array<Index, 2>(dim1, dim2))
{
EIGEN_STATIC_ASSERT(2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor(Index dim1, Index dim2, Index dim3)
: m_storage(dim1*dim2*dim3, array<Index, 3>(dim1, dim2, dim3))
{
EIGEN_STATIC_ASSERT(3 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor(Index dim1, Index dim2, Index dim3, Index dim4)
: m_storage(dim1*dim2*dim3*dim4, array<Index, 4>(dim1, dim2, dim3, dim4))
{
EIGEN_STATIC_ASSERT(4 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor(Index dim1, Index dim2, Index dim3, Index dim4, Index dim5)
: m_storage(dim1*dim2*dim3*dim4*dim5, array<Index, 5>(dim1, dim2, dim3, dim4, dim5))
{
EIGEN_STATIC_ASSERT(5 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
}
#endif
/** Normal Dimension */
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Tensor(const array<Index, NumIndices>& dimensions)
@@ -434,7 +356,6 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
return *this;
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes> EIGEN_DEVICE_FUNC
void resize(Index firstDimension, IndexTypes... otherDimensions)
{
@@ -442,7 +363,6 @@ class Tensor : public TensorBase<Tensor<Scalar_, NumIndices_, Options_, IndexTyp
EIGEN_STATIC_ASSERT(sizeof...(otherDimensions) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
resize(array<Index, NumIndices>{{firstDimension, otherDimensions...}});
}
#endif
/** Normal Dimension */
EIGEN_DEVICE_FUNC void resize(const array<Index, NumIndices>& dimensions)

2
unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
View File

@@ -1012,7 +1012,6 @@ class TensorBase : public TensorBase<Derived, ReadOnlyAccessors> {
return derived() = this->template random<RandomGenerator>();
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Derived& setValues(
const typename internal::Initializer<Derived, NumDimensions>::InitList& vals) {
@@ -1020,7 +1019,6 @@ class TensorBase : public TensorBase<Derived, ReadOnlyAccessors> {
internal::initialize_tensor<Derived, NumDimensions>(eval, vals);
return derived();
}
#endif // EIGEN_HAS_VARIADIC_TEMPLATES
template<typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
Derived& operator+=(const OtherDerived& other) {

35
unsupported/Eigen/CXX11/src/Tensor/TensorDimensions.h
View File

@@ -111,12 +111,10 @@ struct Sizes {
explicit EIGEN_DEVICE_FUNC Sizes(const array<DenseIndex, Base::count>& /*indices*/) {
// todo: add assertion
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
template <typename... DenseIndex> EIGEN_DEVICE_FUNC Sizes(DenseIndex...) { }
explicit EIGEN_DEVICE_FUNC Sizes(std::initializer_list<std::ptrdiff_t> /*l*/) {
// todo: add assertion
}
#endif
template <typename T> Sizes& operator = (const T& /*other*/) {
// add assertion failure if the size of other is different
@@ -173,17 +171,17 @@ template <std::ptrdiff_t V1=0, std::ptrdiff_t V2=0, std::ptrdiff_t V3=0, std::pt
explicit Sizes(const array<DenseIndex, Base::count>& /*indices*/) {
// todo: add assertion
}
template <typename T> Sizes& operator = (const T& /*other*/) {
// add assertion failure if the size of other is different
return *this;
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
template <typename... DenseIndex> Sizes(DenseIndex... /*indices*/) { }
explicit Sizes(std::initializer_list<std::ptrdiff_t>) {
// todo: add assertion
}
#else
EIGEN_DEVICE_FUNC explicit Sizes(const DenseIndex) {
}
EIGEN_DEVICE_FUNC Sizes(const DenseIndex, const DenseIndex) {
@@ -337,39 +335,10 @@ struct DSizes : array<DenseIndex, NumDims> {
}
#endif
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes> EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE explicit DSizes(DenseIndex firstDimension, DenseIndex secondDimension, IndexTypes... otherDimensions) : Base({{firstDimension, secondDimension, otherDimensions...}}) {
EIGEN_STATIC_ASSERT(sizeof...(otherDimensions) + 2 == NumDims, YOU_MADE_A_PROGRAMMING_MISTAKE)
}
#else
EIGEN_DEVICE_FUNC DSizes(const DenseIndex i0, const DenseIndex i1) {
eigen_assert(NumDims == 2);
(*this)[0] = i0;
(*this)[1] = i1;
}
EIGEN_DEVICE_FUNC DSizes(const DenseIndex i0, const DenseIndex i1, const DenseIndex i2) {
eigen_assert(NumDims == 3);
(*this)[0] = i0;
(*this)[1] = i1;
(*this)[2] = i2;
}
EIGEN_DEVICE_FUNC DSizes(const DenseIndex i0, const DenseIndex i1, const DenseIndex i2, const DenseIndex i3) {
eigen_assert(NumDims == 4);
(*this)[0] = i0;
(*this)[1] = i1;
(*this)[2] = i2;
(*this)[3] = i3;
}
EIGEN_DEVICE_FUNC DSizes(const DenseIndex i0, const DenseIndex i1, const DenseIndex i2, const DenseIndex i3, const DenseIndex i4) {
eigen_assert(NumDims == 5);
(*this)[0] = i0;
(*this)[1] = i1;
(*this)[2] = i2;
(*this)[3] = i3;
(*this)[4] = i4;
}
#endif
EIGEN_DEVICE_FUNC DSizes& operator = (const array<DenseIndex, NumDims>& other) {
*static_cast<Base*>(this) = other;

99
unsupported/Eigen/CXX11/src/Tensor/TensorFixedSize.h
View File

@@ -74,7 +74,6 @@ class TensorFixedSize : public TensorBase<TensorFixedSize<Scalar_, Dimensions_,
inline Self& base() { return *this; }
inline const Self& base() const { return *this; }
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(Index firstIndex, IndexTypes... otherIndices) const
{
@@ -82,7 +81,6 @@ class TensorFixedSize : public TensorBase<TensorFixedSize<Scalar_, Dimensions_,
EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
return coeff(array<Index, NumIndices>{{firstIndex, otherIndices...}});
}
#endif
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& coeff(const array<Index, NumIndices>& indices) const
@@ -106,7 +104,6 @@ class TensorFixedSize : public TensorBase<TensorFixedSize<Scalar_, Dimensions_,
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index firstIndex, IndexTypes... otherIndices)
{
@@ -114,7 +111,6 @@ class TensorFixedSize : public TensorBase<TensorFixedSize<Scalar_, Dimensions_,
EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
return coeffRef(array<Index, NumIndices>{{firstIndex, otherIndices...}});
}
#endif
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& coeffRef(const array<Index, NumIndices>& indices)
@@ -137,7 +133,6 @@ class TensorFixedSize : public TensorBase<TensorFixedSize<Scalar_, Dimensions_,
return m_storage.data()[0];
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& operator()(Index firstIndex, IndexTypes... otherIndices) const
{
@@ -145,53 +140,6 @@ class TensorFixedSize : public TensorBase<TensorFixedSize<Scalar_, Dimensions_,
EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
return this->operator()(array<Index, NumIndices>{{firstIndex, otherIndices...}});
}
#else
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1) const
{
if (Options&RowMajor) {
const Index index = i1 + i0 * m_storage.dimensions()[1];
return m_storage.data()[index];
} else {
const Index index = i0 + i1 * m_storage.dimensions()[0];
return m_storage.data()[index];
}
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2) const
{
if (Options&RowMajor) {
const Index index = i2 + m_storage.dimensions()[2] * (i1 + m_storage.dimensions()[1] * i0);
return m_storage.data()[index];
} else {
const Index index = i0 + m_storage.dimensions()[0] * (i1 + m_storage.dimensions()[1] * i2);
return m_storage.data()[index];
}
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3) const
{
if (Options&RowMajor) {
const Index index = i3 + m_storage.dimensions()[3] * (i2 + m_storage.dimensions()[2] * (i1 + m_storage.dimensions()[1] * i0));
return m_storage.data()[index];
} else {
const Index index = i0 + m_storage.dimensions()[0] * (i1 + m_storage.dimensions()[1] * (i2 + m_storage.dimensions()[2] * i3));
return m_storage.data()[index];
}
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4) const
{
if (Options&RowMajor) {
const Index index = i4 + m_storage.dimensions()[4] * (i3 + m_storage.dimensions()[3] * (i2 + m_storage.dimensions()[2] * (i1 + m_storage.dimensions()[1] * i0)));
return m_storage.data()[index];
} else {
const Index index = i0 + m_storage.dimensions()[0] * (i1 + m_storage.dimensions()[1] * (i2 + m_storage.dimensions()[2] * (i3 + m_storage.dimensions()[3] * i4)));
return m_storage.data()[index];
}
}
#endif
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar& operator()(const array<Index, NumIndices>& indices) const
@@ -222,7 +170,6 @@ class TensorFixedSize : public TensorBase<TensorFixedSize<Scalar_, Dimensions_,
return coeff(index);
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& operator()(Index firstIndex, IndexTypes... otherIndices)
{
@@ -230,52 +177,6 @@ class TensorFixedSize : public TensorBase<TensorFixedSize<Scalar_, Dimensions_,
EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
return operator()(array<Index, NumIndices>{{firstIndex, otherIndices...}});
}
#else
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1)
{
if (Options&RowMajor) {
const Index index = i1 + i0 * m_storage.dimensions()[1];
return m_storage.data()[index];
} else {
const Index index = i0 + i1 * m_storage.dimensions()[0];
return m_storage.data()[index];
}
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2)
{
if (Options&RowMajor) {
const Index index = i2 + m_storage.dimensions()[2] * (i1 + m_storage.dimensions()[1] * i0);
return m_storage.data()[index];
} else {
const Index index = i0 + m_storage.dimensions()[0] * (i1 + m_storage.dimensions()[1] * i2);
return m_storage.data()[index];
}
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3)
{
if (Options&RowMajor) {
const Index index = i3 + m_storage.dimensions()[3] * (i2 + m_storage.dimensions()[2] * (i1 + m_storage.dimensions()[1] * i0));
return m_storage.data()[index];
} else {
const Index index = i0 + m_storage.dimensions()[0] * (i1 + m_storage.dimensions()[1] * (i2 + m_storage.dimensions()[2] * i3));
return m_storage.data()[index];
}
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4)
{
if (Options&RowMajor) {
const Index index = i4 + m_storage.dimensions()[4] * (i3 + m_storage.dimensions()[3] * (i2 + m_storage.dimensions()[2] * (i1 + m_storage.dimensions()[1] * i0)));
return m_storage.data()[index];
} else {
const Index index = i0 + m_storage.dimensions()[0] * (i1 + m_storage.dimensions()[1] * (i2 + m_storage.dimensions()[2] * (i3 + m_storage.dimensions()[3] * i4)));
return m_storage.data()[index];
}
}
#endif
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& operator()(const array<Index, NumIndices>& indices)

2
unsupported/Eigen/CXX11/src/Tensor/TensorIndexList.h
View File

@@ -12,7 +12,7 @@
#include "./InternalHeaderCheck.h"
#if EIGEN_HAS_CONSTEXPR && EIGEN_HAS_VARIADIC_TEMPLATES
#if EIGEN_HAS_CONSTEXPR
#define EIGEN_HAS_INDEX_LIST

4
unsupported/Eigen/CXX11/src/Tensor/TensorInitializer.h
View File

@@ -10,8 +10,6 @@
#ifndef EIGEN_CXX11_TENSOR_TENSOR_INITIALIZER_H
#define EIGEN_CXX11_TENSOR_TENSOR_INITIALIZER_H
#if EIGEN_HAS_VARIADIC_TEMPLATES
#include <initializer_list>
#include "./InternalHeaderCheck.h"
@@ -79,6 +77,4 @@ void initialize_tensor(TensorEvaluator<Derived, DefaultDevice>& tensor,
} // namespace internal
} // namespace Eigen
#endif // EIGEN_HAS_VARIADIC_TEMPLATES
#endif // EIGEN_CXX11_TENSOR_TENSOR_INITIALIZER_H

13
unsupported/Eigen/CXX11/src/Tensor/TensorMacros.h
View File

@@ -28,15 +28,10 @@
// SFINAE requires variadic templates
#if !defined(EIGEN_GPUCC)
#if EIGEN_HAS_VARIADIC_TEMPLATES
// SFINAE doesn't work for gcc <= 4.7
#ifdef EIGEN_COMP_GNUC
#if EIGEN_GNUC_AT_LEAST(4,8)
#define EIGEN_HAS_SFINAE
#endif
#else
#define EIGEN_HAS_SFINAE
#endif
#ifdef EIGEN_COMP_GNUC
#define EIGEN_HAS_SFINAE
#else
#define EIGEN_HAS_SFINAE
#endif
#endif

118
unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
View File

@@ -84,35 +84,11 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
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(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(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(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(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(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(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(StoragePointerType dataPtr, const array<Index, NumIndices>& dimensions)
: m_data(dataPtr), m_dimensions(dimensions)
@@ -167,7 +143,6 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
return m_data[index];
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes> EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE StorageRefType operator()(Index firstIndex, Index secondIndex, IndexTypes... otherIndices) const
{
@@ -181,52 +156,6 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
return m_data[index];
}
}
#else
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE StorageRefType operator()(Index i0, Index i1) const
{
if (PlainObjectType::Options&RowMajor) {
const Index index = i1 + i0 * m_dimensions[1];
return m_data[index];
} else {
const Index index = i0 + i1 * m_dimensions[0];
return m_data[index];
}
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE StorageRefType operator()(Index i0, Index i1, Index i2) const
{
if (PlainObjectType::Options&RowMajor) {
const Index index = i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0);
return m_data[index];
} else {
const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * i2);
return m_data[index];
}
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE StorageRefType operator()(Index i0, Index i1, Index i2, Index i3) const
{
if (PlainObjectType::Options&RowMajor) {
const Index index = i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0));
return m_data[index];
} else {
const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * i3));
return m_data[index];
}
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE StorageRefType operator()(Index i0, Index i1, Index i2, Index i3, Index i4) const
{
if (PlainObjectType::Options&RowMajor) {
const Index index = i4 + m_dimensions[4] * (i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0)));
return m_data[index];
} else {
const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * (i3 + m_dimensions[3] * i4)));
return m_data[index];
}
}
#endif
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE StorageRefType operator()(const array<Index, NumIndices>& indices)
@@ -255,7 +184,6 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
return m_data[index];
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes> EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE StorageRefType operator()(Index firstIndex, Index secondIndex, IndexTypes... otherIndices)
{
@@ -270,52 +198,6 @@ template<typename PlainObjectType, int Options_, template <class> class MakePoin
return m_data[index];
}
}
#else
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE StorageRefType operator()(Index i0, Index i1)
{
if (PlainObjectType::Options&RowMajor) {
const Index index = i1 + i0 * m_dimensions[1];
return m_data[index];
} else {
const Index index = i0 + i1 * m_dimensions[0];
return m_data[index];
}
}
EIGEN_DEVICE_FUNC
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);
return m_data[index];
} else {
const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * i2);
return m_data[index];
}
}
EIGEN_DEVICE_FUNC
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));
return m_data[index];
} else {
const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * i3));
return m_data[index];
}
}
EIGEN_DEVICE_FUNC
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)));
return m_data[index];
} else {
const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * (i3 + m_dimensions[3] * i4)));
return m_data[index];
}
}
#endif
EIGEN_TENSOR_INHERIT_ASSIGNMENT_OPERATORS(TensorMap)

2
unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
View File

@@ -108,7 +108,7 @@ struct preserve_inner_most_dims {
static const bool value = false;
};
#if EIGEN_HAS_CONSTEXPR && EIGEN_HAS_VARIADIC_TEMPLATES
#if EIGEN_HAS_CONSTEXPR
template <typename ReducedDims, int NumTensorDims>
struct are_inner_most_dims<ReducedDims, NumTensorDims, ColMajor>{
static const bool tmp1 = indices_statically_known_to_increase<ReducedDims>();

80
unsupported/Eigen/CXX11/src/Tensor/TensorRef.h
View File

@@ -206,7 +206,6 @@ template<typename PlainObjectType> class TensorRef : public TensorBase<TensorRef
return m_evaluator->coeff(index);
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... IndexTypes> EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar operator()(Index firstIndex, IndexTypes... otherIndices) const
{
@@ -221,85 +220,6 @@ template<typename PlainObjectType> class TensorRef : public TensorBase<TensorRef
const array<Index, num_indices> indices{{firstIndex, otherIndices...}};
return coeffRef(indices);
}
#else
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar operator()(Index i0, Index i1) const
{
array<Index, 2> indices;
indices[0] = i0;
indices[1] = i1;
return coeff(indices);
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar operator()(Index i0, Index i1, Index i2) const
{
array<Index, 3> indices;
indices[0] = i0;
indices[1] = i1;
indices[2] = i2;
return coeff(indices);
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar operator()(Index i0, Index i1, Index i2, Index i3) const
{
array<Index, 4> indices;
indices[0] = i0;
indices[1] = i1;
indices[2] = i2;
indices[3] = i3;
return coeff(indices);
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar operator()(Index i0, Index i1, Index i2, Index i3, Index i4) const
{
array<Index, 5> indices;
indices[0] = i0;
indices[1] = i1;
indices[2] = i2;
indices[3] = i3;
indices[4] = i4;
return coeff(indices);
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& coeffRef(Index i0, Index i1)
{
array<Index, 2> indices;
indices[0] = i0;
indices[1] = i1;
return coeffRef(indices);
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& coeffRef(Index i0, Index i1, Index i2)
{
array<Index, 3> indices;
indices[0] = i0;
indices[1] = i1;
indices[2] = i2;
return coeffRef(indices);
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3)
{
array<Index, 4> indices;
indices[0] = i0;
indices[1] = i1;
indices[2] = i2;
indices[3] = i3;
return coeffRef(indices);
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE Scalar& coeffRef(Index i0, Index i1, Index i2, Index i3, Index i4)
{
array<Index, 5> indices;
indices[0] = i0;
indices[1] = i1;
indices[2] = i2;
indices[3] = i3;
indices[4] = i4;
return coeffRef(indices);
}
#endif
template <std::size_t NumIndices> EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const Scalar coeff(const array<Index, NumIndices>& indices) const

2
unsupported/Eigen/CXX11/src/Tensor/TensorStorage.h
View File

@@ -88,12 +88,10 @@ class TensorStorage<T, DSizes<IndexType, NumIndices_>, Options_>
: m_data(internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(size)), m_dimensions(dimensions)
{ EIGEN_INTERNAL_TENSOR_STORAGE_CTOR_PLUGIN }
#if EIGEN_HAS_VARIADIC_TEMPLATES
template <typename... DenseIndex>
EIGEN_DEVICE_FUNC TensorStorage(DenseIndex... indices) : m_dimensions(indices...) {
m_data = internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(internal::array_prod(m_dimensions));
}
#endif
EIGEN_DEVICE_FUNC TensorStorage(const Self& other)
: m_data(internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(internal::array_prod(other.m_dimensions)))

4
unsupported/Eigen/CXX11/src/ThreadPool/ThreadLocal.h
View File

@@ -18,9 +18,7 @@
#else
#if ((EIGEN_COMP_GNUC && EIGEN_GNUC_AT_LEAST(4, 8)) || \
__has_feature(cxx_thread_local) || \
(EIGEN_COMP_MSVC >= 1900) )
#if ((EIGEN_COMP_GNUC) || __has_feature(cxx_thread_local) || EIGEN_COMP_MSVC )
#define EIGEN_THREAD_LOCAL static thread_local
#endif

10
unsupported/Eigen/CXX11/src/util/EmulateArray.h
View File

@@ -10,10 +10,8 @@
#ifndef EIGEN_EMULATE_ARRAY_H
#define EIGEN_EMULATE_ARRAY_H
// The array class is only available starting with cxx11. Emulate our own here
// if needed. Beware, msvc still doesn't advertise itself as a c++11 compiler!
// Moreover, CUDA doesn't support the STL containers, so we use our own instead.
#if (__cplusplus <= 199711L && EIGEN_COMP_MSVC < 1900) || defined(EIGEN_GPUCC) || defined(EIGEN_AVOID_STL_ARRAY)
// CUDA doesn't support the STL containers, so we use our own instead.
#if defined(EIGEN_GPUCC) || defined(EIGEN_AVOID_STL_ARRAY)
namespace Eigen {
template <typename T, size_t n> class array {
@@ -152,13 +150,11 @@ template <typename T, size_t n> class array {
values[7] = v8;
}
#if EIGEN_HAS_VARIADIC_TEMPLATES
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE array(std::initializer_list<T> l) {
eigen_assert(l.size() == n);
internal::smart_copy(l.begin(), l.end(), values);
}
#endif
};
@@ -202,12 +198,10 @@ template <typename T> class array<T, 0> {
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE array() : dummy() { }
#if EIGEN_HAS_VARIADIC_TEMPLATES
EIGEN_DEVICE_FUNC array(std::initializer_list<T> l) : dummy() {
EIGEN_UNUSED_VARIABLE(l);
eigen_assert(l.size() == 0);
}
#endif
private:
T dummy;

21
unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h
View File

@@ -22,17 +22,8 @@ public:
AutoDiffJacobian(const Functor& f) : Functor(f) {}
// forward constructors
#if EIGEN_HAS_VARIADIC_TEMPLATES
template<typename... T>
AutoDiffJacobian(const T& ...Values) : Functor(Values...) {}
#else
template<typename T0>
AutoDiffJacobian(const T0& a0) : Functor(a0) {}
template<typename T0, typename T1>
AutoDiffJacobian(const T0& a0, const T1& a1) : Functor(a0, a1) {}
template<typename T0, typename T1, typename T2>
AutoDiffJacobian(const T0& a0, const T1& a1, const T2& a2) : Functor(a0, a1, a2) {}
#endif
typedef typename Functor::InputType InputType;
typedef typename Functor::ValueType ValueType;
@@ -52,7 +43,6 @@ public:
typedef Matrix<ActiveScalar, InputsAtCompileTime, 1> ActiveInput;
typedef Matrix<ActiveScalar, ValuesAtCompileTime, 1> ActiveValue;
#if EIGEN_HAS_VARIADIC_TEMPLATES
// Some compilers don't accept variadic parameters after a default parameter,
// i.e., we can't just write _jac=0 but we need to overload operator():
EIGEN_STRONG_INLINE
@@ -63,19 +53,12 @@ public:
template<typename... ParamsType>
void operator() (const InputType& x, ValueType* v, JacobianType* _jac,
const ParamsType&... Params) const
#else
void operator() (const InputType& x, ValueType* v, JacobianType* _jac=0) const
#endif
{
eigen_assert(v!=0);
if (!_jac)
{
#if EIGEN_HAS_VARIADIC_TEMPLATES
Functor::operator()(x, v, Params...);
#else
Functor::operator()(x, v);
#endif
return;
}
@@ -91,11 +74,7 @@ public:
for (Index i=0; i<jac.cols(); i++)
ax[i].derivatives() = DerivativeType::Unit(x.rows(),i);
#if EIGEN_HAS_VARIADIC_TEMPLATES
Functor::operator()(ax, &av, Params...);
#else
Functor::operator()(ax, &av);
#endif
for (Index i=0; i<jac.rows(); i++)
{