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authorGravatar Benoit Steiner <benoit.steiner.goog@gmail.com>2016-05-27 12:22:25 -0700
committerGravatar Benoit Steiner <benoit.steiner.goog@gmail.com>2016-05-27 12:22:25 -0700
commitabc815798b21ce99c28444d7df5b48573de3e237 (patch)
tree1da04fe66a1560267a1a6ac3d80bcc3632abad81 /unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h
parent570753759291b60b031d9afd285b3e1efe4f63bc (diff)
Added a new operation to enable more powerful tensorindexing.
Diffstat (limited to 'unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h')
-rw-r--r--unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h279
1 files changed, 279 insertions, 0 deletions
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h b/unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h
index 75d54759b..359fd243a 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorMorphing.h
@@ -603,6 +603,285 @@ struct TensorEvaluator<TensorSlicingOp<StartIndices, Sizes, ArgType>, Device>
};
+
+namespace internal {
+template<typename StartIndices, typename StopIndices, typename Strides, typename XprType>
+struct traits<TensorStridingSlicingOp<StartIndices, StopIndices, Strides, 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 = array_size<StartIndices>::value;
+ static const int Layout = XprTraits::Layout;
+};
+
+template<typename StartIndices, typename StopIndices, typename Strides, typename XprType>
+struct eval<TensorStridingSlicingOp<StartIndices, StopIndices, Strides, XprType>, Eigen::Dense>
+{
+ typedef const TensorStridingSlicingOp<StartIndices, StopIndices, Strides, XprType>& type;
+};
+
+template<typename StartIndices, typename StopIndices, typename Strides, typename XprType>
+struct nested<TensorStridingSlicingOp<StartIndices, StopIndices, Strides, XprType>, 1, typename eval<TensorStridingSlicingOp<StartIndices, StopIndices, Strides, XprType> >::type>
+{
+ typedef TensorStridingSlicingOp<StartIndices, StopIndices, Strides, XprType> type;
+};
+
+} // end namespace internal
+
+
+template<typename StartIndices, typename StopIndices, typename Strides, typename XprType>
+class TensorStridingSlicingOp : public TensorBase<TensorStridingSlicingOp<StartIndices, StopIndices, Strides, XprType> >
+{
+ public:
+ typedef typename internal::traits<TensorStridingSlicingOp>::Scalar Scalar;
+ typedef typename XprType::CoeffReturnType CoeffReturnType;
+ typedef typename internal::nested<TensorStridingSlicingOp>::type Nested;
+ typedef typename internal::traits<TensorStridingSlicingOp>::StorageKind StorageKind;
+ typedef typename internal::traits<TensorStridingSlicingOp>::Index Index;
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorStridingSlicingOp(
+ const XprType& expr, const StartIndices& startIndices,
+ const StopIndices& stopIndices, const Strides& strides)
+ : m_xpr(expr), m_startIndices(startIndices), m_stopIndices(stopIndices),
+ m_strides(strides) {}
+
+ EIGEN_DEVICE_FUNC
+ const StartIndices& startIndices() const { return m_startIndices; }
+ EIGEN_DEVICE_FUNC
+ const StartIndices& stopIndices() const { return m_stopIndices; }
+ EIGEN_DEVICE_FUNC
+ const StartIndices& strides() const { return m_strides; }
+
+ EIGEN_DEVICE_FUNC
+ const typename internal::remove_all<typename XprType::Nested>::type&
+ expression() const { return m_xpr; }
+
+ EIGEN_DEVICE_FUNC
+ EIGEN_STRONG_INLINE TensorStridingSlicingOp& operator = (const TensorStridingSlicingOp& other)
+ {
+ typedef TensorAssignOp<TensorStridingSlicingOp, const TensorStridingSlicingOp> Assign;
+ Assign assign(*this, other);
+ internal::TensorExecutor<const Assign, DefaultDevice>::run(
+ assign, DefaultDevice());
+ return *this;
+ }
+
+ template<typename OtherDerived>
+ EIGEN_DEVICE_FUNC
+ EIGEN_STRONG_INLINE TensorStridingSlicingOp& operator = (const OtherDerived& other)
+ {
+ typedef TensorAssignOp<TensorStridingSlicingOp, const OtherDerived> Assign;
+ Assign assign(*this, other);
+ internal::TensorExecutor<const Assign, DefaultDevice>::run(
+ assign, DefaultDevice());
+ return *this;
+ }
+
+ protected:
+ typename XprType::Nested m_xpr;
+ const StartIndices m_startIndices;
+ const StopIndices m_stopIndices;
+ const Strides m_strides;
+};
+
+// Eval as rvalue
+template<typename StartIndices, typename StopIndices, typename Strides, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorStridingSlicingOp<StartIndices, StopIndices, Strides, ArgType>, Device>
+{
+ typedef TensorStridingSlicingOp<StartIndices, StopIndices, Strides, ArgType> XprType;
+ static const int NumDims = internal::array_size<Strides>::value;
+
+ enum {
+ // Alignment can't be guaranteed at compile time since it depends on the
+ // slice offsets and sizes.
+ IsAligned = false,
+ PacketAccess = false,
+ BlockAccess = false,
+ Layout = TensorEvaluator<ArgType, Device>::Layout,
+ RawAccess = false
+ };
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+ : m_impl(op.expression(), device), m_device(device), m_strides(op.strides())
+ {
+ auto clamp = [](Index value, Index min, Index max){
+ return numext::maxi(min,numext::mini(max,value));
+ };
+ // Handle degenerate intervals by gracefully clamping and allowing m_dimensions to be zero
+ DSizes<Index,NumDims> startIndicesClamped, stopIndicesClamped;
+ for (int i = 0; i < internal::array_size<Dimensions>::value; ++i) {
+ eigen_assert(m_strides[i] != 0 && "0 stride is invalid");
+ if(m_strides[i]>0){
+ startIndicesClamped[i] = clamp(op.startIndices()[i], 0, m_impl.dimensions()[i]);
+ stopIndicesClamped[i] = clamp(op.stopIndices()[i], 0, m_impl.dimensions()[i]);
+ }else{
+ /* implies m_strides[i]<0 by assert */
+ startIndicesClamped[i] = clamp(op.startIndices()[i], -1, m_impl.dimensions()[i] - 1);
+ stopIndicesClamped[i] = clamp(op.stopIndices()[i], -1, m_impl.dimensions()[i] - 1);
+ }
+ m_startIndices[i] = startIndicesClamped[i];
+ }
+
+ const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+
+ // check for degenerate intervals and compute output tensor shape
+ bool degenerate = false;;
+ for(int i = 0; i < NumDims; i++){
+ Index interval = stopIndicesClamped[i] - startIndicesClamped[i];
+ if(interval == 0 || ((interval<0) != (m_strides[i]<0))){
+ m_dimensions[i] = 0;
+ degenerate = true;
+ }else{
+ m_dimensions[i] = interval / m_strides[i]
+ + (interval % m_strides[i] != 0 ? 1 : 0);
+ eigen_assert(m_dimensions[i] >= 0);
+ }
+ }
+ Strides output_dims = m_dimensions;
+
+ if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+ m_inputStrides[0] = m_strides[0];
+ m_offsets[0] = startIndicesClamped[0];
+ Index previousDimProduct = 1;
+ for (int i = 1; i < NumDims; ++i) {
+ previousDimProduct *= input_dims[i-1];
+ m_inputStrides[i] = previousDimProduct * m_strides[i];
+ m_offsets[i] = startIndicesClamped[i] * previousDimProduct;
+ }
+
+ // Don't initialize m_fastOutputStrides[0] since it won't ever be accessed.
+ m_outputStrides[0] = 1;
+ for (int i = 1; i < NumDims; ++i) {
+ m_outputStrides[i] = m_outputStrides[i-1] * output_dims[i-1];
+ // NOTE: if tensor is degenerate, we send 1 to prevent TensorIntDivisor constructor crash
+ m_fastOutputStrides[i] = internal::TensorIntDivisor<Index>(degenerate ? 1 : m_outputStrides[i]);
+ }
+ } else {
+ m_inputStrides[NumDims-1] = m_strides[NumDims-1];
+ m_offsets[NumDims-1] = startIndicesClamped[NumDims-1];
+ Index previousDimProduct = 1;
+ for (int i = NumDims - 2; i >= 0; --i) {
+ previousDimProduct *= input_dims[i+1];
+ m_inputStrides[i] = previousDimProduct * m_strides[i];
+ m_offsets[i] = startIndicesClamped[i] * previousDimProduct;
+ }
+
+ m_outputStrides[NumDims-1] = 1;
+ for (int i = NumDims - 2; i >= 0; --i) {
+ m_outputStrides[i] = m_outputStrides[i+1] * output_dims[i+1];
+ // NOTE: if tensor is degenerate, we send 1 to prevent TensorIntDivisor constructor crash
+ m_fastOutputStrides[i] = internal::TensorIntDivisor<Index>(degenerate ? 1 : m_outputStrides[i]);
+ }
+ }
+ m_block_total_size_max = numext::maxi(static_cast<std::size_t>(1),
+ device.lastLevelCacheSize() /
+ sizeof(Scalar));
+ }
+
+ typedef typename XprType::Index Index;
+ typedef typename XprType::Scalar Scalar;
+ typedef typename internal::remove_const<Scalar>::type ScalarNonConst;
+ typedef typename XprType::CoeffReturnType CoeffReturnType;
+ typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+ typedef Strides Dimensions;
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType*) {
+ m_impl.evalSubExprsIfNeeded(NULL);
+ return true;
+ }
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+ m_impl.cleanup();
+ }
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+ {
+ return m_impl.coeff(srcCoeff(index));
+ }
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+ return m_impl.costPerCoeff(vectorized) + TensorOpCost(0, 0, NumDims);
+ }
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar* data() const {
+ return nullptr;
+ }
+
+ protected:
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index srcCoeff(Index index) const
+ {
+ Index inputIndex = 0;
+ if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+ for (int i = NumDims - 1; i >= 0; --i) {
+ const Index idx = index / m_fastOutputStrides[i];
+ inputIndex += idx * m_inputStrides[i] + m_offsets[i];
+ index -= idx * m_outputStrides[i];
+ }
+ } else {
+ for (int i = 0; i < NumDims; ++i) {
+ const Index idx = index / m_fastOutputStrides[i];
+ inputIndex += idx * m_inputStrides[i] + m_offsets[i];
+ index -= idx * m_outputStrides[i];
+ }
+ }
+ return inputIndex;
+ }
+
+ array<Index, NumDims> m_outputStrides;
+ array<internal::TensorIntDivisor<Index>, NumDims> m_fastOutputStrides;
+ array<Index, NumDims> m_inputStrides;
+ TensorEvaluator<ArgType, Device> m_impl;
+ const Device& m_device;
+ DSizes<Index, NumDims> m_startIndices; // clamped startIndices
+ DSizes<Index, NumDims> m_dimensions;
+ DSizes<Index, NumDims> m_offsets; // offset in a flattened shape
+ const Strides m_strides;
+ std::size_t m_block_total_size_max;
+};
+
+// Eval as lvalue
+template<typename StartIndices, typename StopIndices, typename Strides, typename ArgType, typename Device>
+struct TensorEvaluator<TensorStridingSlicingOp<StartIndices, StopIndices, Strides, ArgType>, Device>
+ : public TensorEvaluator<const TensorStridingSlicingOp<StartIndices, StopIndices, Strides, ArgType>, Device>
+{
+ typedef TensorEvaluator<const TensorStridingSlicingOp<StartIndices, StopIndices, Strides, ArgType>, Device> Base;
+ typedef TensorStridingSlicingOp<StartIndices, StopIndices, Strides, ArgType> XprType;
+ static const int NumDims = internal::array_size<Strides>::value;
+
+ enum {
+ IsAligned = false,
+ PacketAccess = false,
+ BlockAccess = false,
+ Layout = TensorEvaluator<ArgType, Device>::Layout,
+ CoordAccess = TensorEvaluator<ArgType, Device>::CoordAccess,
+ RawAccess = false
+ };
+
+ EIGEN_DEVICE_FUNC 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 internal::remove_const<Scalar>::type ScalarNonConst;
+ typedef typename XprType::CoeffReturnType CoeffReturnType;
+ typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+ typedef Strides Dimensions;
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType& coeffRef(Index index)
+ {
+ return this->m_impl.coeffRef(this->srcCoeff(index));
+ }
+};
+
+
} // end namespace Eigen
#endif // EIGEN_CXX11_TENSOR_TENSOR_MORPHING_H