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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2014 Navdeep Jaitly <ndjaitly@google.com>
// 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_CXX11_TENSOR_TENSOR_REVERSE_H
#define EIGEN_CXX11_TENSOR_TENSOR_REVERSE_H
namespace Eigen {
/** \class TensorReverse
* \ingroup CXX11_Tensor_Module
*
* \brief Tensor reverse elements class.
*
*/
namespace internal {
template<typename ReverseDimensions, typename XprType>
struct traits<TensorReverseOp<ReverseDimensions,
XprType> > : public traits<XprType>
{
typedef typename XprType::Scalar Scalar;
typedef traits<XprType> XprTraits;
typedef typename XprTraits::StorageKind StorageKind;
typedef typename XprTraits::Index Index;
typedef typename XprType::Nested Nested;
typedef typename remove_reference<Nested>::type _Nested;
static const int NumDimensions = XprTraits::NumDimensions;
static const int Layout = XprTraits::Layout;
};
template<typename ReverseDimensions, typename XprType>
struct eval<TensorReverseOp<ReverseDimensions, XprType>, Eigen::Dense>
{
typedef const TensorReverseOp<ReverseDimensions, XprType>& type;
};
template<typename ReverseDimensions, typename XprType>
struct nested<TensorReverseOp<ReverseDimensions, XprType>, 1,
typename eval<TensorReverseOp<ReverseDimensions, XprType> >::type>
{
typedef TensorReverseOp<ReverseDimensions, XprType> type;
};
} // end namespace internal
template<typename ReverseDimensions, typename XprType>
class TensorReverseOp : public TensorBase<TensorReverseOp<ReverseDimensions,
XprType>, WriteAccessors>
{
public:
typedef typename Eigen::internal::traits<TensorReverseOp>::Scalar Scalar;
typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename Eigen::internal::nested<TensorReverseOp>::type Nested;
typedef typename Eigen::internal::traits<TensorReverseOp>::StorageKind
StorageKind;
typedef typename Eigen::internal::traits<TensorReverseOp>::Index Index;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorReverseOp(
const XprType& expr, const ReverseDimensions& reverse_dims)
: m_xpr(expr), m_reverse_dims(reverse_dims) { }
EIGEN_DEVICE_FUNC
const ReverseDimensions& reverse() const { return m_reverse_dims; }
EIGEN_DEVICE_FUNC
const typename internal::remove_all<typename XprType::Nested>::type&
expression() const { return m_xpr; }
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE TensorReverseOp& operator = (const TensorReverseOp& other)
{
typedef TensorAssignOp<TensorReverseOp, const TensorReverseOp> Assign;
Assign assign(*this, other);
internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
return *this;
}
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE TensorReverseOp& operator = (const OtherDerived& other)
{
typedef TensorAssignOp<TensorReverseOp, const OtherDerived> Assign;
Assign assign(*this, other);
internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
return *this;
}
protected:
typename XprType::Nested m_xpr;
const ReverseDimensions m_reverse_dims;
};
// Eval as rvalue
template<typename ReverseDimensions, typename ArgType, typename Device>
struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device>
{
typedef TensorReverseOp<ReverseDimensions, ArgType> XprType;
typedef typename XprType::Index Index;
static const int NumDims = internal::array_size<ReverseDimensions>::value;
typedef DSizes<Index, NumDims> Dimensions;
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
enum {
IsAligned = false,
PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
Layout = TensorEvaluator<ArgType, Device>::Layout,
CoordAccess = false, // to be implemented
RawAccess = false
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op,
const Device& device)
: m_impl(op.expression(), device), m_reverse(op.reverse())
{
// Reversing a scalar isn't supported yet. It would be a no-op anyway.
EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
// Compute strides
m_dimensions = m_impl.dimensions();
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
m_strides[0] = 1;
for (int i = 1; i < NumDims; ++i) {
m_strides[i] = m_strides[i-1] * m_dimensions[i-1];
}
} else {
m_strides[NumDims-1] = 1;
for (int i = NumDims - 2; i >= 0; --i) {
m_strides[i] = m_strides[i+1] * m_dimensions[i+1];
}
}
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const Dimensions& dimensions() const { return m_dimensions; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
m_impl.evalSubExprsIfNeeded(NULL);
return true;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
m_impl.cleanup();
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index reverseIndex(
Index index) const {
eigen_assert(index < dimensions().TotalSize());
Index inputIndex = 0;
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
for (int i = NumDims - 1; i > 0; --i) {
Index idx = index / m_strides[i];
index -= idx * m_strides[i];
if (m_reverse[i]) {
idx = m_dimensions[i] - idx - 1;
}
inputIndex += idx * m_strides[i] ;
}
if (m_reverse[0]) {
inputIndex += (m_dimensions[0] - index - 1);
} else {
inputIndex += index;
}
} else {
for (int i = 0; i < NumDims - 1; ++i) {
Index idx = index / m_strides[i];
index -= idx * m_strides[i];
if (m_reverse[i]) {
idx = m_dimensions[i] - idx - 1;
}
inputIndex += idx * m_strides[i] ;
}
if (m_reverse[NumDims-1]) {
inputIndex += (m_dimensions[NumDims-1] - index - 1);
} else {
inputIndex += index;
}
}
return inputIndex;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(
Index index) const {
return m_impl.coeff(reverseIndex(index));
}
template<int LoadMode>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
PacketReturnType packet(Index index) const
{
EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
// TODO(ndjaitly): write a better packing routine that uses
// local structure.
EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type
values[PacketSize];
for (int i = 0; i < PacketSize; ++i) {
values[i] = coeff(index+i);
}
PacketReturnType rslt = internal::pload<PacketReturnType>(values);
return rslt;
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
double compute_cost = NumDims * (2 * TensorOpCost::AddCost<Index>() +
2 * TensorOpCost::MulCost<Index>() +
TensorOpCost::DivCost<Index>());
for (int i = 0; i < NumDims; ++i) {
if (m_reverse[i]) {
compute_cost += 2 * TensorOpCost::AddCost<Index>();
}
}
return m_impl.costPerCoeff(vectorized) +
TensorOpCost(0, 0, compute_cost, false /* vectorized */, PacketSize);
}
EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
protected:
Dimensions m_dimensions;
array<Index, NumDims> m_strides;
TensorEvaluator<ArgType, Device> m_impl;
ReverseDimensions m_reverse;
};
// Eval as lvalue
template <typename ReverseDimensions, typename ArgType, typename Device>
struct TensorEvaluator<TensorReverseOp<ReverseDimensions, ArgType>, Device>
: public TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>,
Device> {
typedef TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>,
Device> Base;
typedef TensorReverseOp<ReverseDimensions, ArgType> XprType;
typedef typename XprType::Index Index;
static const int NumDims = internal::array_size<ReverseDimensions>::value;
typedef DSizes<Index, NumDims> Dimensions;
enum {
IsAligned = false,
PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
Layout = TensorEvaluator<ArgType, Device>::Layout,
CoordAccess = false, // to be implemented
RawAccess = false
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op,
const Device& device)
: Base(op, device) {}
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const Dimensions& dimensions() const { return this->m_dimensions; }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
return this->m_impl.coeffRef(this->reverseIndex(index));
}
template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
void writePacket(Index index, const PacketReturnType& x) {
EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
// This code is pilfered from TensorMorphing.h
EIGEN_ALIGN_MAX CoeffReturnType values[PacketSize];
internal::pstore<CoeffReturnType, PacketReturnType>(values, x);
for (int i = 0; i < PacketSize; ++i) {
this->coeffRef(index+i) = values[i];
}
}
};
} // end namespace Eigen
#endif // EIGEN_CXX11_TENSOR_TENSOR_REVERSE_H