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This commit is contained in:
Tobias Wood
2023-11-29 11:12:48 +00:00
parent 9ea520fc45
commit f38e16c193
534 changed files with 103368 additions and 116934 deletions
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159
unsupported/Eigen/CXX11/src/Tensor/TensorLayoutSwap.h
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@@ -16,31 +16,30 @@
namespace Eigen {
/** \class TensorLayoutSwap
* \ingroup CXX11_Tensor_Module
*
* \brief Swap the layout from col-major to row-major, or row-major
* to col-major, and invert the order of the dimensions.
*
* Beware: the dimensions are reversed by this operation. If you want to
* preserve the ordering of the dimensions, you need to combine this
* operation with a shuffle.
*
* \example:
* Tensor<float, 2, ColMajor> input(2, 4);
* Tensor<float, 2, RowMajor> output = input.swap_layout();
* eigen_assert(output.dimension(0) == 4);
* eigen_assert(output.dimension(1) == 2);
*
* array<int, 2> shuffle(1, 0);
* output = input.swap_layout().shuffle(shuffle);
* eigen_assert(output.dimension(0) == 2);
* eigen_assert(output.dimension(1) == 4);
*
*/
* \ingroup CXX11_Tensor_Module
*
* \brief Swap the layout from col-major to row-major, or row-major
* to col-major, and invert the order of the dimensions.
*
* Beware: the dimensions are reversed by this operation. If you want to
* preserve the ordering of the dimensions, you need to combine this
* operation with a shuffle.
*
* \example:
* Tensor<float, 2, ColMajor> input(2, 4);
* Tensor<float, 2, RowMajor> output = input.swap_layout();
* eigen_assert(output.dimension(0) == 4);
* eigen_assert(output.dimension(1) == 2);
*
* array<int, 2> shuffle(1, 0);
* output = input.swap_layout().shuffle(shuffle);
* eigen_assert(output.dimension(0) == 2);
* eigen_assert(output.dimension(1) == 4);
*
*/
namespace internal {
template<typename XprType>
struct traits<TensorLayoutSwapOp<XprType> > : public traits<XprType>
{
template <typename XprType>
struct traits<TensorLayoutSwapOp<XprType> > : public traits<XprType> {
typedef typename XprType::Scalar Scalar;
typedef traits<XprType> XprTraits;
typedef typename XprTraits::StorageKind StorageKind;
@@ -52,57 +51,48 @@ struct traits<TensorLayoutSwapOp<XprType> > : public traits<XprType>
typedef typename XprTraits::PointerType PointerType;
};
template<typename XprType>
struct eval<TensorLayoutSwapOp<XprType>, Eigen::Dense>
{
template <typename XprType>
struct eval<TensorLayoutSwapOp<XprType>, Eigen::Dense> {
typedef const TensorLayoutSwapOp<XprType>& type;
};
template<typename XprType>
struct nested<TensorLayoutSwapOp<XprType>, 1, typename eval<TensorLayoutSwapOp<XprType> >::type>
{
template <typename XprType>
struct nested<TensorLayoutSwapOp<XprType>, 1, typename eval<TensorLayoutSwapOp<XprType> >::type> {
typedef TensorLayoutSwapOp<XprType> type;
};
} // end namespace internal
template <typename XprType>
class TensorLayoutSwapOp : public TensorBase<TensorLayoutSwapOp<XprType>, WriteAccessors> {
public:
typedef TensorBase<TensorLayoutSwapOp<XprType>, WriteAccessors> Base;
typedef typename Eigen::internal::traits<TensorLayoutSwapOp>::Scalar Scalar;
typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
typedef std::remove_const_t<typename XprType::CoeffReturnType> CoeffReturnType;
typedef typename Eigen::internal::nested<TensorLayoutSwapOp>::type Nested;
typedef typename Eigen::internal::traits<TensorLayoutSwapOp>::StorageKind StorageKind;
typedef typename Eigen::internal::traits<TensorLayoutSwapOp>::Index Index;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorLayoutSwapOp(const XprType& expr) : m_xpr(expr) {}
template<typename XprType>
class TensorLayoutSwapOp : public TensorBase<TensorLayoutSwapOp<XprType>, WriteAccessors>
{
public:
typedef TensorBase<TensorLayoutSwapOp<XprType>, WriteAccessors> Base;
typedef typename Eigen::internal::traits<TensorLayoutSwapOp>::Scalar Scalar;
typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
typedef std::remove_const_t<typename XprType::CoeffReturnType> CoeffReturnType;
typedef typename Eigen::internal::nested<TensorLayoutSwapOp>::type Nested;
typedef typename Eigen::internal::traits<TensorLayoutSwapOp>::StorageKind StorageKind;
typedef typename Eigen::internal::traits<TensorLayoutSwapOp>::Index Index;
EIGEN_DEVICE_FUNC const internal::remove_all_t<typename XprType::Nested>& expression() const { return m_xpr; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorLayoutSwapOp(const XprType& expr)
: m_xpr(expr) {}
EIGEN_DEVICE_FUNC
const internal::remove_all_t<typename XprType::Nested>&
expression() const { return m_xpr; }
EIGEN_TENSOR_INHERIT_ASSIGNMENT_OPERATORS(TensorLayoutSwapOp)
protected:
typename XprType::Nested m_xpr;
EIGEN_TENSOR_INHERIT_ASSIGNMENT_OPERATORS(TensorLayoutSwapOp)
protected:
typename XprType::Nested m_xpr;
};
// Eval as rvalue
template<typename ArgType, typename Device>
struct TensorEvaluator<const TensorLayoutSwapOp<ArgType>, Device>
{
template <typename ArgType, typename Device>
struct TensorEvaluator<const TensorLayoutSwapOp<ArgType>, Device> {
typedef TensorLayoutSwapOp<ArgType> XprType;
typedef typename XprType::Index Index;
static constexpr int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
typedef DSizes<Index, NumDims> Dimensions;
static constexpr int Layout = (TensorEvaluator<ArgType, Device>::Layout == static_cast<int>(ColMajor)) ? RowMajor : ColMajor;
static constexpr int Layout =
(TensorEvaluator<ArgType, Device>::Layout == static_cast<int>(ColMajor)) ? RowMajor : ColMajor;
enum {
IsAligned = TensorEvaluator<ArgType, Device>::IsAligned,
PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
@@ -116,11 +106,9 @@ struct TensorEvaluator<const TensorLayoutSwapOp<ArgType>, Device>
typedef internal::TensorBlockNotImplemented TensorBlock;
//===--------------------------------------------------------------------===//
EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
: m_impl(op.expression(), device)
{
for(int i = 0; i < NumDims; ++i) {
m_dimensions[i] = m_impl.dimensions()[NumDims-1-i];
EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device) : m_impl(op.expression(), device) {
for (int i = 0; i < NumDims; ++i) {
m_dimensions[i] = m_impl.dimensions()[NumDims - 1 - i];
}
}
@@ -132,21 +120,13 @@ struct TensorEvaluator<const TensorLayoutSwapOp<ArgType>, Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType data) {
return m_impl.evalSubExprsIfNeeded(data);
}
EIGEN_STRONG_INLINE void cleanup() {
m_impl.cleanup();
}
EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType data) { return m_impl.evalSubExprsIfNeeded(data); }
EIGEN_STRONG_INLINE void cleanup() { m_impl.cleanup(); }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
{
return m_impl.coeff(index);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { return m_impl.coeff(index); }
template<int LoadMode>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
{
template <int LoadMode>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const {
return m_impl.template packet<LoadMode>(index);
}
@@ -154,9 +134,7 @@ struct TensorEvaluator<const TensorLayoutSwapOp<ArgType>, Device>
return m_impl.costPerCoeff(vectorized);
}
EIGEN_DEVICE_FUNC typename Storage::Type data() const {
return constCast(m_impl.data());
}
EIGEN_DEVICE_FUNC typename Storage::Type data() const { return constCast(m_impl.data()); }
const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
@@ -165,16 +143,15 @@ struct TensorEvaluator<const TensorLayoutSwapOp<ArgType>, Device>
Dimensions m_dimensions;
};
// Eval as lvalue
template<typename ArgType, typename Device>
struct TensorEvaluator<TensorLayoutSwapOp<ArgType>, Device>
: public TensorEvaluator<const TensorLayoutSwapOp<ArgType>, Device>
{
template <typename ArgType, typename Device>
struct TensorEvaluator<TensorLayoutSwapOp<ArgType>, Device>
: public TensorEvaluator<const TensorLayoutSwapOp<ArgType>, Device> {
typedef TensorEvaluator<const TensorLayoutSwapOp<ArgType>, Device> Base;
typedef TensorLayoutSwapOp<ArgType> XprType;
static constexpr int Layout = (TensorEvaluator<ArgType, Device>::Layout == static_cast<int>(ColMajor)) ? RowMajor : ColMajor;
static constexpr int Layout =
(TensorEvaluator<ArgType, Device>::Layout == static_cast<int>(ColMajor)) ? RowMajor : ColMajor;
enum {
IsAligned = TensorEvaluator<ArgType, Device>::IsAligned,
PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
@@ -187,26 +164,22 @@ template<typename ArgType, typename Device>
typedef internal::TensorBlockNotImplemented TensorBlock;
//===--------------------------------------------------------------------===//
EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
: Base(op, device)
{ }
EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device) : Base(op, device) {}
typedef typename XprType::Index Index;
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType& coeffRef(Index index) const
{
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType& coeffRef(Index index) const {
return this->m_impl.coeffRef(index);
}
template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
void writePacket(Index index, const PacketReturnType& x) const
{
template <int StoreMode>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index index, const PacketReturnType& x) const {
this->m_impl.template writePacket<StoreMode>(index, x);
}
};
} // end namespace Eigen
} // end namespace Eigen
#endif // EIGEN_CXX11_TENSOR_TENSOR_LAYOUT_SWAP_H
#endif // EIGEN_CXX11_TENSOR_TENSOR_LAYOUT_SWAP_H