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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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149
unsupported/Eigen/CXX11/src/Tensor/TensorAssign.h
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@@ -16,21 +16,20 @@
namespace Eigen {
/** \class TensorAssign
* \ingroup CXX11_Tensor_Module
*
* \brief The tensor assignment class.
*
* This class is represents the assignment of the values resulting from the evaluation of
* the rhs expression to the memory locations denoted by the lhs expression.
*/
* \ingroup CXX11_Tensor_Module
*
* \brief The tensor assignment class.
*
* This class is represents the assignment of the values resulting from the evaluation of
* the rhs expression to the memory locations denoted by the lhs expression.
*/
namespace internal {
template<typename LhsXprType, typename RhsXprType>
struct traits<TensorAssignOp<LhsXprType, RhsXprType> >
{
template <typename LhsXprType, typename RhsXprType>
struct traits<TensorAssignOp<LhsXprType, RhsXprType> > {
typedef typename LhsXprType::Scalar Scalar;
typedef typename traits<LhsXprType>::StorageKind StorageKind;
typedef typename promote_index_type<typename traits<LhsXprType>::Index,
typename traits<RhsXprType>::Index>::type Index;
typedef
typename promote_index_type<typename traits<LhsXprType>::Index, typename traits<RhsXprType>::Index>::type Index;
typedef typename LhsXprType::Nested LhsNested;
typedef typename RhsXprType::Nested RhsNested;
typedef std::remove_reference_t<LhsNested> LhsNested_;
@@ -39,31 +38,24 @@ struct traits<TensorAssignOp<LhsXprType, RhsXprType> >
static constexpr int Layout = internal::traits<LhsXprType>::Layout;
typedef typename traits<LhsXprType>::PointerType PointerType;
enum {
Flags = 0
};
enum { Flags = 0 };
};
template<typename LhsXprType, typename RhsXprType>
struct eval<TensorAssignOp<LhsXprType, RhsXprType>, Eigen::Dense>
{
template <typename LhsXprType, typename RhsXprType>
struct eval<TensorAssignOp<LhsXprType, RhsXprType>, Eigen::Dense> {
typedef const TensorAssignOp<LhsXprType, RhsXprType>& type;
};
template<typename LhsXprType, typename RhsXprType>
struct nested<TensorAssignOp<LhsXprType, RhsXprType>, 1, typename eval<TensorAssignOp<LhsXprType, RhsXprType> >::type>
{
template <typename LhsXprType, typename RhsXprType>
struct nested<TensorAssignOp<LhsXprType, RhsXprType>, 1, typename eval<TensorAssignOp<LhsXprType, RhsXprType> >::type> {
typedef TensorAssignOp<LhsXprType, RhsXprType> type;
};
} // end namespace internal
template<typename LhsXprType, typename RhsXprType>
class TensorAssignOp : public TensorBase<TensorAssignOp<LhsXprType, RhsXprType> >
{
public:
template <typename LhsXprType, typename RhsXprType>
class TensorAssignOp : public TensorBase<TensorAssignOp<LhsXprType, RhsXprType> > {
public:
typedef typename Eigen::internal::traits<TensorAssignOp>::Scalar Scalar;
typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
typedef typename LhsXprType::CoeffReturnType CoeffReturnType;
@@ -76,24 +68,22 @@ class TensorAssignOp : public TensorBase<TensorAssignOp<LhsXprType, RhsXprType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorAssignOp(LhsXprType& lhs, const RhsXprType& rhs)
: m_lhs_xpr(lhs), m_rhs_xpr(rhs) {}
/** \returns the nested expressions */
EIGEN_DEVICE_FUNC
internal::remove_all_t<typename LhsXprType::Nested>&
lhsExpression() const { return *((internal::remove_all_t<typename LhsXprType::Nested>*)&m_lhs_xpr); }
/** \returns the nested expressions */
EIGEN_DEVICE_FUNC internal::remove_all_t<typename LhsXprType::Nested>& lhsExpression() const {
return *((internal::remove_all_t<typename LhsXprType::Nested>*)&m_lhs_xpr);
}
EIGEN_DEVICE_FUNC
const internal::remove_all_t<typename RhsXprType::Nested>&
rhsExpression() const { return m_rhs_xpr; }
EIGEN_DEVICE_FUNC const internal::remove_all_t<typename RhsXprType::Nested>& rhsExpression() const {
return m_rhs_xpr;
}
protected:
internal::remove_all_t<typename LhsXprType::Nested>& m_lhs_xpr;
const internal::remove_all_t<typename RhsXprType::Nested>& m_rhs_xpr;
protected:
internal::remove_all_t<typename LhsXprType::Nested>& m_lhs_xpr;
const internal::remove_all_t<typename RhsXprType::Nested>& m_rhs_xpr;
};
template<typename LeftArgType, typename RightArgType, typename Device>
struct TensorEvaluator<const TensorAssignOp<LeftArgType, RightArgType>, Device>
{
template <typename LeftArgType, typename RightArgType, typename Device>
struct TensorEvaluator<const TensorAssignOp<LeftArgType, RightArgType>, Device> {
typedef TensorAssignOp<LeftArgType, RightArgType> XprType;
typedef typename XprType::Index Index;
typedef typename XprType::Scalar Scalar;
@@ -108,37 +98,32 @@ struct TensorEvaluator<const TensorAssignOp<LeftArgType, RightArgType>, Device>
static constexpr int Layout = TensorEvaluator<LeftArgType, Device>::Layout;
enum {
IsAligned = int(TensorEvaluator<LeftArgType, Device>::IsAligned) &
int(TensorEvaluator<RightArgType, Device>::IsAligned),
PacketAccess = int(TensorEvaluator<LeftArgType, Device>::PacketAccess) &
int(TensorEvaluator<RightArgType, Device>::PacketAccess),
BlockAccess = int(TensorEvaluator<LeftArgType, Device>::BlockAccess) &
int(TensorEvaluator<RightArgType, Device>::BlockAccess),
IsAligned =
int(TensorEvaluator<LeftArgType, Device>::IsAligned) & int(TensorEvaluator<RightArgType, Device>::IsAligned),
PacketAccess = int(TensorEvaluator<LeftArgType, Device>::PacketAccess) &
int(TensorEvaluator<RightArgType, Device>::PacketAccess),
BlockAccess = int(TensorEvaluator<LeftArgType, Device>::BlockAccess) &
int(TensorEvaluator<RightArgType, Device>::BlockAccess),
PreferBlockAccess = int(TensorEvaluator<LeftArgType, Device>::PreferBlockAccess) |
int(TensorEvaluator<RightArgType, Device>::PreferBlockAccess),
RawAccess = TensorEvaluator<LeftArgType, Device>::RawAccess
RawAccess = TensorEvaluator<LeftArgType, Device>::RawAccess
};
//===- Tensor block evaluation strategy (see TensorBlock.h) -------------===//
typedef internal::TensorBlockDescriptor<NumDims, Index> TensorBlockDesc;
typedef internal::TensorBlockScratchAllocator<Device> TensorBlockScratch;
typedef typename TensorEvaluator<const RightArgType, Device>::TensorBlock
RightTensorBlock;
typedef typename TensorEvaluator<const RightArgType, Device>::TensorBlock RightTensorBlock;
//===--------------------------------------------------------------------===//
TensorEvaluator(const XprType& op, const Device& device) :
m_leftImpl(op.lhsExpression(), device),
m_rightImpl(op.rhsExpression(), device)
{
EIGEN_STATIC_ASSERT(
(static_cast<int>(TensorEvaluator<LeftArgType, Device>::Layout) ==
static_cast<int>(TensorEvaluator<RightArgType, Device>::Layout)),
YOU_MADE_A_PROGRAMMING_MISTAKE);
TensorEvaluator(const XprType& op, const Device& device)
: m_leftImpl(op.lhsExpression(), device), m_rightImpl(op.rhsExpression(), device) {
EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<LeftArgType, Device>::Layout) ==
static_cast<int>(TensorEvaluator<RightArgType, Device>::Layout)),
YOU_MADE_A_PROGRAMMING_MISTAKE);
}
EIGEN_DEVICE_FUNC const Dimensions& dimensions() const
{
EIGEN_DEVICE_FUNC const Dimensions& dimensions() const {
// The dimensions of the lhs and the rhs tensors should be equal to prevent
// overflows and ensure the result is fully initialized.
// TODO: use left impl instead if right impl dimensions are known at compile time.
@@ -157,11 +142,9 @@ struct TensorEvaluator<const TensorAssignOp<LeftArgType, RightArgType>, Device>
#ifdef EIGEN_USE_THREADS
template <typename EvalSubExprsCallback>
EIGEN_STRONG_INLINE void evalSubExprsIfNeededAsync(
EvaluatorPointerType, EvalSubExprsCallback done) {
EIGEN_STRONG_INLINE void evalSubExprsIfNeededAsync(EvaluatorPointerType, EvalSubExprsCallback done) {
m_leftImpl.evalSubExprsIfNeededAsync(nullptr, [this, done](bool) {
m_rightImpl.evalSubExprsIfNeededAsync(
m_leftImpl.data(), [done](bool need_assign) { done(need_assign); });
m_rightImpl.evalSubExprsIfNeededAsync(m_leftImpl.data(), [done](bool need_assign) { done(need_assign); });
});
}
#endif // EIGEN_USE_THREADS
@@ -175,45 +158,34 @@ struct TensorEvaluator<const TensorAssignOp<LeftArgType, RightArgType>, Device>
m_leftImpl.coeffRef(i) = m_rightImpl.coeff(i);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalPacket(Index i) const {
const int LhsStoreMode = TensorEvaluator<LeftArgType, Device>::IsAligned ? Aligned : Unaligned;
const int RhsLoadMode = TensorEvaluator<RightArgType, Device>::IsAligned ? Aligned : Unaligned;
m_leftImpl.template writePacket<LhsStoreMode>(i, m_rightImpl.template packet<RhsLoadMode>(i));
}
EIGEN_DEVICE_FUNC CoeffReturnType coeff(Index index) const
{
return m_leftImpl.coeff(index);
}
template<int LoadMode>
EIGEN_DEVICE_FUNC PacketReturnType packet(Index index) const
{
EIGEN_DEVICE_FUNC CoeffReturnType coeff(Index index) const { return m_leftImpl.coeff(index); }
template <int LoadMode>
EIGEN_DEVICE_FUNC PacketReturnType packet(Index index) const {
return m_leftImpl.template packet<LoadMode>(index);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
costPerCoeff(bool vectorized) const {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
// We assume that evalPacket or evalScalar is called to perform the
// assignment and account for the cost of the write here, but reduce left
// cost by one load because we are using m_leftImpl.coeffRef.
TensorOpCost left = m_leftImpl.costPerCoeff(vectorized);
return m_rightImpl.costPerCoeff(vectorized) +
TensorOpCost(
numext::maxi(0.0, left.bytes_loaded() - sizeof(CoeffReturnType)),
left.bytes_stored(), left.compute_cycles()) +
TensorOpCost(numext::maxi(0.0, left.bytes_loaded() - sizeof(CoeffReturnType)), left.bytes_stored(),
left.compute_cycles()) +
TensorOpCost(0, sizeof(CoeffReturnType), 0, vectorized, PacketSize);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
internal::TensorBlockResourceRequirements getResourceRequirements() const {
return internal::TensorBlockResourceRequirements::merge(
m_leftImpl.getResourceRequirements(),
m_rightImpl.getResourceRequirements());
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE internal::TensorBlockResourceRequirements getResourceRequirements() const {
return internal::TensorBlockResourceRequirements::merge(m_leftImpl.getResourceRequirements(),
m_rightImpl.getResourceRequirements());
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalBlock(
TensorBlockDesc& desc, TensorBlockScratch& scratch) {
if (TensorEvaluator<LeftArgType, Device>::RawAccess &&
m_leftImpl.data() != NULL) {
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalBlock(TensorBlockDesc& desc, TensorBlockScratch& scratch) {
if (TensorEvaluator<LeftArgType, Device>::RawAccess && m_leftImpl.data() != NULL) {
// If destination has raw data access, we pass it as a potential
// destination for a block descriptor evaluation.
desc.template AddDestinationBuffer<Layout>(
@@ -236,7 +208,6 @@ struct TensorEvaluator<const TensorAssignOp<LeftArgType, RightArgType>, Device>
TensorEvaluator<RightArgType, Device> m_rightImpl;
};
}
} // namespace Eigen
#endif // EIGEN_CXX11_TENSOR_TENSOR_ASSIGN_H
#endif // EIGEN_CXX11_TENSOR_TENSOR_ASSIGN_H