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Replace Eigen type metaprogramming with corresponding std types and make use of alias templates

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This commit is contained in:
Erik Schultheis
2022-03-16 16:43:40 +00:00
committed by Antonio Sánchez
parent 514f90c9ff
commit 421cbf0866
191 changed files with 1147 additions and 1221 deletions
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24
unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
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@@ -30,7 +30,7 @@ struct traits<TensorBroadcastingOp<Broadcast, XprType> > : public traits<XprType
typedef typename XprTraits::StorageKind StorageKind;
typedef typename XprTraits::Index Index;
typedef typename XprType::Nested Nested;
typedef typename remove_reference<Nested>::type Nested_;
typedef std::remove_reference_t<Nested> Nested_;
static const int NumDimensions = XprTraits::NumDimensions;
static const int Layout = XprTraits::Layout;
typedef typename XprTraits::PointerType PointerType;
@@ -85,7 +85,7 @@ class TensorBroadcastingOp : public TensorBase<TensorBroadcastingOp<Broadcast, X
const Broadcast& broadcast() const { return m_broadcast; }
EIGEN_DEVICE_FUNC
const typename internal::remove_all<typename XprType::Nested>::type&
const internal::remove_all_t<typename XprType::Nested>&
expression() const { return m_xpr; }
protected:
@@ -118,11 +118,11 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
BlockAccess = TensorEvaluator<ArgType, Device>::BlockAccess,
PreferBlockAccess = true,
Layout = TensorEvaluator<ArgType, Device>::Layout,
RawAccess = false
};
static constexpr int Layout = TensorEvaluator<ArgType, Device>::Layout;
typedef typename internal::remove_const<Scalar>::type ScalarNoConst;
typedef std::remove_const_t<Scalar> ScalarNoConst;
// We do block based broadcasting using a trick with 2x tensor rank and 0
// strides. See block method implementation for details.
@@ -231,7 +231,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE CoeffReturnType coeff(Index index) const
{
if (internal::is_input_scalar<typename internal::remove_all<InputDimensions>::type>::value) {
if (internal::is_input_scalar<internal::remove_all_t<InputDimensions>>::value) {
return m_impl.coeff(0);
}
@@ -324,7 +324,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
template<int LoadMode>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE PacketReturnType packet(Index index) const
{
if (internal::is_input_scalar<typename internal::remove_all<InputDimensions>::type>::value) {
if (internal::is_input_scalar<internal::remove_all_t<InputDimensions>>::value) {
return internal::pset1<PacketReturnType>(m_impl.coeff(0));
}
@@ -372,7 +372,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
{
eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
EIGEN_ALIGN_MAX std::remove_const_t<CoeffReturnType> values[PacketSize];
Index startDim, endDim;
Index inputIndex, outputOffset, batchedIndex;
@@ -424,7 +424,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
if (inputIndex + PacketSize <= M) {
return m_impl.template packet<Unaligned>(inputIndex);
} else {
EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
EIGEN_ALIGN_MAX std::remove_const_t<CoeffReturnType> values[PacketSize];
EIGEN_UNROLL_LOOP
for (int i = 0; i < PacketSize; ++i) {
if (inputIndex > M - 1) {
@@ -453,7 +453,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
if (outputOffset + PacketSize <= M) {
return internal::pset1<PacketReturnType>(m_impl.coeff(inputIndex));
} else {
EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
EIGEN_ALIGN_MAX std::remove_const_t<CoeffReturnType> values[PacketSize];
EIGEN_UNROLL_LOOP
for (int i = 0; i < PacketSize; ++i) {
if (outputOffset < M) {
@@ -512,7 +512,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
if (innermostLoc + PacketSize <= m_impl.dimensions()[0]) {
return m_impl.template packet<Unaligned>(inputIndex);
} else {
EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
EIGEN_ALIGN_MAX std::remove_const_t<CoeffReturnType> values[PacketSize];
values[0] = m_impl.coeff(inputIndex);
EIGEN_UNROLL_LOOP
for (int i = 1; i < PacketSize; ++i) {
@@ -569,7 +569,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
if (innermostLoc + PacketSize <= m_impl.dimensions()[NumDims-1]) {
return m_impl.template packet<Unaligned>(inputIndex);
} else {
EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
EIGEN_ALIGN_MAX std::remove_const_t<CoeffReturnType> values[PacketSize];
values[0] = m_impl.coeff(inputIndex);
EIGEN_UNROLL_LOOP
for (int i = 1; i < PacketSize; ++i) {
@@ -1074,7 +1074,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
protected:
const Device EIGEN_DEVICE_REF m_device;
const typename internal::remove_reference<Broadcast>::type m_broadcast;
const std::remove_reference_t<Broadcast> m_broadcast;
Dimensions m_dimensions;
array<Index, NumDims> m_outputStrides;
array<Index, NumDims> m_inputStrides;