GitHub-Proxy/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2025-06-04 18:54:00 +08:00
Code Issues Packages Projects Releases Wiki Activity

Rollback or PR-746 and partial rollback of 668ab3fc47

Browse Source 
.

std::array is still not supported in CUDA device code on Windows.
This commit is contained in:
Rasmus Munk Larsen 2019-11-05 17:17:58 -08:00
parent 0c9745903a
commit ee404667e2
8 changed files with 314 additions and 115 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
Eigen/src/Core/DenseStorage.h
View File

@ -369,7 +369,7 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
, m_cols(other.m_cols) , m_cols(other.m_cols)
{ {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_rows*m_cols) EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_rows*m_cols)
std::copy(other.m_data, other.m_data+other.m_rows*other.m_cols, m_data); internal::smart_copy(other.m_data, other.m_data+other.m_rows*other.m_cols, m_data);
} }
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other) EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
{ {
@ -452,7 +452,7 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
, m_cols(other.m_cols) , m_cols(other.m_cols)
{ {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_cols*_Rows) EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_cols*_Rows)
std::copy(other.m_data, other.m_data+_Rows*m_cols, m_data); internal::smart_copy(other.m_data, other.m_data+_Rows*m_cols, m_data);
} }
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other) EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
{ {
@ -528,7 +528,7 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
, m_rows(other.m_rows) , m_rows(other.m_rows)
{ {
EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_rows*_Cols) EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_rows*_Cols)
std::copy(other.m_data, other.m_data+other.m_rows*_Cols, m_data); internal::smart_copy(other.m_data, other.m_data+other.m_rows*_Cols, m_data);
} }
EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other) EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
{ {

25
Eigen/src/Core/util/Memory.h
View File

@ -507,6 +507,31 @@ inline Index first_multiple(Index size, Index base)
return ((size+base-1)/base)*base; return ((size+base-1)/base)*base;
} }
// std::copy is much slower than memcpy, so let's introduce a smart_copy which
// use memcpy on trivial types, i.e., on types that does not require an initialization ctor.
template<typename T, bool UseMemcpy> struct smart_copy_helper;
template<typename T> EIGEN_DEVICE_FUNC void smart_copy(const T* start, const T* end, T* target)
{
smart_copy_helper<T,!NumTraits<T>::RequireInitialization>::run(start, end, target);
}
template<typename T> struct smart_copy_helper<T,true> {
EIGEN_DEVICE_FUNC static inline void run(const T* start, const T* end, T* target)
{
IntPtr size = IntPtr(end)-IntPtr(start);
if(size==0) return;
eigen_internal_assert(start!=0 && end!=0 && target!=0);
EIGEN_USING_STD(memcpy)
memcpy(target, start, size);
}
};
template<typename T> struct smart_copy_helper<T,false> {
EIGEN_DEVICE_FUNC static inline void run(const T* start, const T* end, T* target)
{ std::copy(start, end, target); }
};
// intelligent memmove. falls back to std::memmove for POD types, uses std::copy otherwise. // intelligent memmove. falls back to std::memmove for POD types, uses std::copy otherwise.
template<typename T, bool UseMemmove> struct smart_memmove_helper; template<typename T, bool UseMemmove> struct smart_memmove_helper;

20
Eigen/src/SparseCore/CompressedStorage.h
View File

@ -53,8 +53,8 @@ class CompressedStorage
resize(other.size()); resize(other.size());
if(other.size()>0) if(other.size()>0)
{ {
std::copy(other.m_values, other.m_values + m_size, m_values); internal::smart_copy(other.m_values, other.m_values + m_size, m_values);
std::copy(other.m_indices, other.m_indices + m_size, m_indices); internal::smart_copy(other.m_indices, other.m_indices + m_size, m_indices);
} }
return *this; return *this;
} }
@ -183,14 +183,14 @@ class CompressedStorage
internal::scoped_array<StorageIndex> newIndices(m_allocatedSize); internal::scoped_array<StorageIndex> newIndices(m_allocatedSize);
// copy first chunk // copy first chunk
std::copy(m_values, m_values +id, newValues.ptr()); internal::smart_copy(m_values, m_values +id, newValues.ptr());
std::copy(m_indices, m_indices+id, newIndices.ptr()); internal::smart_copy(m_indices, m_indices+id, newIndices.ptr());
// copy the rest // copy the rest
if(m_size>id) if(m_size>id)
{ {
std::copy(m_values +id, m_values +m_size, newValues.ptr() +id+1); internal::smart_copy(m_values +id, m_values +m_size, newValues.ptr() +id+1);
std::copy(m_indices+id, m_indices+m_size, newIndices.ptr()+id+1); internal::smart_copy(m_indices+id, m_indices+m_size, newIndices.ptr()+id+1);
} }
std::swap(m_values,newValues.ptr()); std::swap(m_values,newValues.ptr());
std::swap(m_indices,newIndices.ptr()); std::swap(m_indices,newIndices.ptr());
@ -218,8 +218,8 @@ class CompressedStorage
} }
else else
{ {
std::copy(m_values+from, m_values+from+chunkSize, m_values+to); internal::smart_copy(m_values+from, m_values+from+chunkSize, m_values+to);
std::copy(m_indices+from, m_indices+from+chunkSize, m_indices+to); internal::smart_copy(m_indices+from, m_indices+from+chunkSize, m_indices+to);
} }
} }
@ -251,8 +251,8 @@ class CompressedStorage
internal::scoped_array<StorageIndex> newIndices(size); internal::scoped_array<StorageIndex> newIndices(size);
Index copySize = (std::min)(size, m_size); Index copySize = (std::min)(size, m_size);
if (copySize>0) { if (copySize>0) {
std::copy(m_values, m_values+copySize, newValues.ptr()); internal::smart_copy(m_values, m_values+copySize, newValues.ptr());
std::copy(m_indices, m_indices+copySize, newIndices.ptr()); internal::smart_copy(m_indices, m_indices+copySize, newIndices.ptr());
} }
std::swap(m_values,newValues.ptr()); std::swap(m_values,newValues.ptr());
std::swap(m_indices,newIndices.ptr()); std::swap(m_indices,newIndices.ptr());

16
Eigen/src/SparseCore/SparseBlock.h
View File

@ -147,14 +147,14 @@ public:
// realloc manually to reduce copies // realloc manually to reduce copies
typename SparseMatrixType::Storage newdata(m_matrix.data().allocatedSize() - block_size + nnz); typename SparseMatrixType::Storage newdata(m_matrix.data().allocatedSize() - block_size + nnz);
std::copy(m_matrix.valuePtr(), m_matrix.valuePtr() + start, newdata.valuePtr()); internal::smart_copy(m_matrix.valuePtr(), m_matrix.valuePtr() + start, newdata.valuePtr());
std::copy(m_matrix.innerIndexPtr(), m_matrix.innerIndexPtr() + start, newdata.indexPtr()); internal::smart_copy(m_matrix.innerIndexPtr(), m_matrix.innerIndexPtr() + start, newdata.indexPtr());
std::copy(tmp.valuePtr() + tmp_start, tmp.valuePtr() + tmp_start + nnz, newdata.valuePtr() + start); internal::smart_copy(tmp.valuePtr() + tmp_start, tmp.valuePtr() + tmp_start + nnz, newdata.valuePtr() + start);
std::copy(tmp.innerIndexPtr() + tmp_start, tmp.innerIndexPtr() + tmp_start + nnz, newdata.indexPtr() + start); internal::smart_copy(tmp.innerIndexPtr() + tmp_start, tmp.innerIndexPtr() + tmp_start + nnz, newdata.indexPtr() + start);
std::copy(matrix.valuePtr()+end, matrix.valuePtr()+end + tail_size, newdata.valuePtr()+start+nnz); internal::smart_copy(matrix.valuePtr()+end, matrix.valuePtr()+end + tail_size, newdata.valuePtr()+start+nnz);
std::copy(matrix.innerIndexPtr()+end, matrix.innerIndexPtr()+end + tail_size, newdata.indexPtr()+start+nnz); internal::smart_copy(matrix.innerIndexPtr()+end, matrix.innerIndexPtr()+end + tail_size, newdata.indexPtr()+start+nnz);
newdata.resize(m_matrix.outerIndexPtr()[m_matrix.outerSize()] - block_size + nnz); newdata.resize(m_matrix.outerIndexPtr()[m_matrix.outerSize()] - block_size + nnz);
@ -175,8 +175,8 @@ public:
update_trailing_pointers = true; update_trailing_pointers = true;
} }
std::copy(tmp.valuePtr() + tmp_start, tmp.valuePtr() + tmp_start + nnz, matrix.valuePtr() + start); internal::smart_copy(tmp.valuePtr() + tmp_start, tmp.valuePtr() + tmp_start + nnz, matrix.valuePtr() + start);
std::copy(tmp.innerIndexPtr() + tmp_start, tmp.innerIndexPtr() + tmp_start + nnz, matrix.innerIndexPtr() + start); internal::smart_copy(tmp.innerIndexPtr() + tmp_start, tmp.innerIndexPtr() + tmp_start + nnz, matrix.innerIndexPtr() + start);
} }
// update outer index pointers and innerNonZeros // update outer index pointers and innerNonZeros

10
Eigen/src/SparseCore/SparseMatrix.h
View File

@ -767,7 +767,7 @@ class SparseMatrix
initAssignment(other); initAssignment(other);
if(other.isCompressed()) if(other.isCompressed())
{ {
std::copy(other.m_outerIndex, other.m_outerIndex + m_outerSize + 1, m_outerIndex); internal::smart_copy(other.m_outerIndex, other.m_outerIndex + m_outerSize + 1, m_outerIndex);
m_data = other.m_data; m_data = other.m_data;
} }
else else
@ -982,8 +982,8 @@ protected:
{ {
Index i = newEntries[k].i; Index i = newEntries[k].i;
Index p = newEntries[k].p; Index p = newEntries[k].p;
std::copy(m_data.valuePtr()+prev_p, m_data.valuePtr()+p, newData.valuePtr()+prev_p+k); internal::smart_copy(m_data.valuePtr()+prev_p, m_data.valuePtr()+p, newData.valuePtr()+prev_p+k);
std::copy(m_data.indexPtr()+prev_p, m_data.indexPtr()+p, newData.indexPtr()+prev_p+k); internal::smart_copy(m_data.indexPtr()+prev_p, m_data.indexPtr()+p, newData.indexPtr()+prev_p+k);
for(Index j=prev_i;j<i;++j) for(Index j=prev_i;j<i;++j)
m_outerIndex[j+1] += k; m_outerIndex[j+1] += k;
if(!isComp) if(!isComp)
@ -995,8 +995,8 @@ protected:
assignFunc.assignCoeff(newData.value(p+k), diaEval.coeff(i)); assignFunc.assignCoeff(newData.value(p+k), diaEval.coeff(i));
} }
{ {
std::copy(m_data.valuePtr()+prev_p, m_data.valuePtr()+m_data.size(), newData.valuePtr()+prev_p+n_entries); internal::smart_copy(m_data.valuePtr()+prev_p, m_data.valuePtr()+m_data.size(), newData.valuePtr()+prev_p+n_entries);
std::copy(m_data.indexPtr()+prev_p, m_data.indexPtr()+m_data.size(), newData.indexPtr()+prev_p+n_entries); internal::smart_copy(m_data.indexPtr()+prev_p, m_data.indexPtr()+m_data.size(), newData.indexPtr()+prev_p+n_entries);
for(Index j=prev_i+1;j<=m_outerSize;++j) for(Index j=prev_i+1;j<=m_outerSize;++j)
m_outerIndex[j] += n_entries; m_outerIndex[j] += n_entries;
} }

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

@ -96,7 +96,7 @@ class TensorStorage<T, DSizes<IndexType, NumIndices_>, Options_>
: m_data(internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(internal::array_prod(other.m_dimensions))) : m_data(internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(internal::array_prod(other.m_dimensions)))
, m_dimensions(other.m_dimensions) , m_dimensions(other.m_dimensions)
{ {
std::copy(other.m_data, other.m_data+internal::array_prod(other.m_dimensions), m_data); internal::smart_copy(other.m_data, other.m_data+internal::array_prod(other.m_dimensions), m_data);
} }
EIGEN_DEVICE_FUNC Self& operator=(const Self& other) EIGEN_DEVICE_FUNC Self& operator=(const Self& other)
{ {

89
unsupported/Eigen/CXX11/src/util/CXX11Meta.h
View File

@ -11,100 +11,13 @@
#define EIGEN_CXX11META_H #define EIGEN_CXX11META_H
#include <vector> #include <vector>
#include <array> #include "EmulateArray.h"
#include "CXX11Workarounds.h" #include "CXX11Workarounds.h"
namespace Eigen { namespace Eigen {
// Workaround for constructors used by legacy code calling Eigen::array.
template <typename T, size_t N>
class array : public std::array<T, N> {
public:
typedef std::array<T, N> Base;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
array() : Base() {}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
array(const T& v) : Base{{v}} {
EIGEN_STATIC_ASSERT(N == 1, YOU_MADE_A_PROGRAMMING_MISTAKE);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
array(const T& v1, const T& v2) : Base{{v1, v2}} {
EIGEN_STATIC_ASSERT(N == 2, YOU_MADE_A_PROGRAMMING_MISTAKE);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
array(const T& v1, const T& v2, const T& v3) : Base{{v1, v2, v3}} {
EIGEN_STATIC_ASSERT(N == 3, YOU_MADE_A_PROGRAMMING_MISTAKE);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
array(const T& v1, const T& v2, const T& v3, const T& v4)
: Base{{v1, v2, v3, v4}} {
EIGEN_STATIC_ASSERT(N == 4, YOU_MADE_A_PROGRAMMING_MISTAKE);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
array(const T& v1, const T& v2, const T& v3, const T& v4, const T& v5)
: Base{{v1, v2, v3, v4, v5}} {
EIGEN_STATIC_ASSERT(N == 5, YOU_MADE_A_PROGRAMMING_MISTAKE);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
array(const T& v1, const T& v2, const T& v3, const T& v4, const T& v5,
const T& v6) : Base{{v1, v2, v3, v4, v5, v6}} {
EIGEN_STATIC_ASSERT(N == 6, YOU_MADE_A_PROGRAMMING_MISTAKE);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
array(const T& v1, const T& v2, const T& v3, const T& v4, const T& v5,
const T& v6, const T& v7)
: Base{{v1, v2, v3, v4, v5, v6, v7}} {
EIGEN_STATIC_ASSERT(N == 7, YOU_MADE_A_PROGRAMMING_MISTAKE);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
array(const T& v1, const T& v2, const T& v3, const T& v4, const T& v5,
const T& v6, const T& v7, const T& v8)
: Base{{v1, v2, v3, v4, v5, v6, v7, v8}} {
EIGEN_STATIC_ASSERT(N == 8, YOU_MADE_A_PROGRAMMING_MISTAKE);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
array(std::initializer_list<T> l) {
eigen_assert(l.size() == N);
std::copy(l.begin(), l.end(), &this->front());
}
};
namespace internal { namespace internal {
template<typename T, std::size_t N> struct array_size<const array<T,N> > {
enum { value = N };
};
template<typename T, std::size_t N> struct array_size<array<T,N> > {
enum { value = N };
};
/* std::get is only constexpr in C++14, not yet in C++11
* - libstdc++ from version 4.7 onwards has it nevertheless,
* so use that
* - libstdc++ older versions: use _M_instance directly
* - libc++ all versions so far: use __elems_ directly
* - all other libs: use std::get to be portable, but
* this may not be constexpr
*/
#if defined(__GLIBCXX__) && __GLIBCXX__ < 20120322
#define STD_GET_ARR_HACK a._M_instance[I_]
#elif defined(_LIBCPP_VERSION)
#define STD_GET_ARR_HACK a.__elems_[I_]
#else
#define STD_GET_ARR_HACK std::template get<I_, T, N>(a)
#endif
template<std::size_t I_, class T, std::size_t N> constexpr inline T& array_get(std::array<T,N>& a) { return (T&) STD_GET_ARR_HACK; }
template<std::size_t I_, class T, std::size_t N> constexpr inline T&& array_get(std::array<T,N>&& a) { return (T&&) STD_GET_ARR_HACK; }
template<std::size_t I_, class T, std::size_t N> constexpr inline T const& array_get(std::array<T,N> const& a) { return (T const&) STD_GET_ARR_HACK; }
#undef STD_GET_ARR_HACK
/** \internal /** \internal
* \file CXX11/util/CXX11Meta.h * \file CXX11/util/CXX11Meta.h

261
unsupported/Eigen/CXX11/src/util/EmulateArray.h Normal file
View File

@ -0,0 +1,261 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#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)
namespace Eigen {
template <typename T, size_t n> class array {
public:
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE T& operator[] (size_t index) { eigen_internal_assert(index < size()); return values[index]; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const T& operator[] (size_t index) const { eigen_internal_assert(index < size()); return values[index]; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE T& at(size_t index) { eigen_assert(index < size()); return values[index]; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const T& at(size_t index) const { eigen_assert(index < size()); return values[index]; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE T& front() { return values[0]; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const T& front() const { return values[0]; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE T& back() { return values[n-1]; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const T& back() const { return values[n-1]; }
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
static std::size_t size() { return n; }
T values[n];
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE array() { }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE array(const T& v) {
EIGEN_STATIC_ASSERT(n==1, YOU_MADE_A_PROGRAMMING_MISTAKE)
values[0] = v;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE array(const T& v1, const T& v2) {
EIGEN_STATIC_ASSERT(n==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
values[0] = v1;
values[1] = v2;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE array(const T& v1, const T& v2, const T& v3) {
EIGEN_STATIC_ASSERT(n==3, YOU_MADE_A_PROGRAMMING_MISTAKE)
values[0] = v1;
values[1] = v2;
values[2] = v3;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE array(const T& v1, const T& v2, const T& v3,
const T& v4) {
EIGEN_STATIC_ASSERT(n==4, YOU_MADE_A_PROGRAMMING_MISTAKE)
values[0] = v1;
values[1] = v2;
values[2] = v3;
values[3] = v4;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE array(const T& v1, const T& v2, const T& v3, const T& v4,
const T& v5) {
EIGEN_STATIC_ASSERT(n==5, YOU_MADE_A_PROGRAMMING_MISTAKE)
values[0] = v1;
values[1] = v2;
values[2] = v3;
values[3] = v4;
values[4] = v5;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE array(const T& v1, const T& v2, const T& v3, const T& v4,
const T& v5, const T& v6) {
EIGEN_STATIC_ASSERT(n==6, YOU_MADE_A_PROGRAMMING_MISTAKE)
values[0] = v1;
values[1] = v2;
values[2] = v3;
values[3] = v4;
values[4] = v5;
values[5] = v6;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE array(const T& v1, const T& v2, const T& v3, const T& v4,
const T& v5, const T& v6, const T& v7) {
EIGEN_STATIC_ASSERT(n==7, YOU_MADE_A_PROGRAMMING_MISTAKE)
values[0] = v1;
values[1] = v2;
values[2] = v3;
values[3] = v4;
values[4] = v5;
values[5] = v6;
values[6] = v7;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE array(
const T& v1, const T& v2, const T& v3, const T& v4,
const T& v5, const T& v6, const T& v7, const T& v8) {
EIGEN_STATIC_ASSERT(n==8, YOU_MADE_A_PROGRAMMING_MISTAKE)
values[0] = v1;
values[1] = v2;
values[2] = v3;
values[3] = v4;
values[4] = v5;
values[5] = v6;
values[6] = v7;
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
};
// Specialize array for zero size
template <typename T> class array<T, 0> {
public:
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE T& operator[] (size_t) {
eigen_assert(false && "Can't index a zero size array");
return dummy;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const T& operator[] (size_t) const {
eigen_assert(false && "Can't index a zero size array");
return dummy;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE T& front() {
eigen_assert(false && "Can't index a zero size array");
return dummy;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const T& front() const {
eigen_assert(false && "Can't index a zero size array");
return dummy;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE T& back() {
eigen_assert(false && "Can't index a zero size array");
return dummy;
}
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE const T& back() const {
eigen_assert(false && "Can't index a zero size array");
return dummy;
}
static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::size_t size() { return 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;
};
// Comparison operator
// Todo: implement !=, <, <=, >, and >=
template<class T, std::size_t N>
EIGEN_DEVICE_FUNC bool operator==(const array<T,N>& lhs, const array<T,N>& rhs) {
for (std::size_t i = 0; i < N; ++i) {
if (lhs[i] != rhs[i]) {
return false;
}
}
return true;
}
namespace internal {
template<std::size_t I_, class T, std::size_t N>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T& array_get(array<T,N>& a) {
return a[I_];
}
template<std::size_t I_, class T, std::size_t N>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const T& array_get(const array<T,N>& a) {
return a[I_];
}
template<class T, std::size_t N> struct array_size<array<T,N> > {
enum { value = N };
};
template<class T, std::size_t N> struct array_size<array<T,N>& > {
enum { value = N };
};
template<class T, std::size_t N> struct array_size<const array<T,N> > {
enum { value = N };
};
template<class T, std::size_t N> struct array_size<const array<T,N>& > {
enum { value = N };
};
} // end namespace internal
} // end namespace Eigen
#else
// The compiler supports c++11, and we're not targeting cuda: use std::array as Eigen::array
#include <array>
namespace Eigen {
template <typename T, std::size_t N> using array = std::array<T, N>;
namespace internal {
/* std::get is only constexpr in C++14, not yet in C++11
* - libstdc++ from version 4.7 onwards has it nevertheless,
* so use that
* - libstdc++ older versions: use _M_instance directly
* - libc++ all versions so far: use __elems_ directly
* - all other libs: use std::get to be portable, but
* this may not be constexpr
*/
#if defined(__GLIBCXX__) && __GLIBCXX__ < 20120322
#define STD_GET_ARR_HACK a._M_instance[I_]
#elif defined(_LIBCPP_VERSION)
#define STD_GET_ARR_HACK a.__elems_[I_]
#else
#define STD_GET_ARR_HACK std::template get<I_, T, N>(a)
#endif
template<std::size_t I_, class T, std::size_t N> constexpr inline T& array_get(std::array<T,N>& a) { return (T&) STD_GET_ARR_HACK; }
template<std::size_t I_, class T, std::size_t N> constexpr inline T&& array_get(std::array<T,N>&& a) { return (T&&) STD_GET_ARR_HACK; }
template<std::size_t I_, class T, std::size_t N> constexpr inline T const& array_get(std::array<T,N> const& a) { return (T const&) STD_GET_ARR_HACK; }
#undef STD_GET_ARR_HACK
} // end namespace internal
} // end namespace Eigen
#endif
#endif // EIGEN_EMULATE_ARRAY_H