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https://gitlab.com/libeigen/eigen.git
synced 2026-04-10 11:34:33 +08:00
Pulled latest update from the eigen main codebase
This commit is contained in:
3
unsupported/Eigen/CXX11/src/CMakeLists.txt
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3
unsupported/Eigen/CXX11/src/CMakeLists.txt
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@@ -0,0 +1,3 @@
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add_subdirectory(Core)
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add_subdirectory(Tensor)
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add_subdirectory(TensorSymmetry)
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1
unsupported/Eigen/CXX11/src/Core/CMakeLists.txt
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1
unsupported/Eigen/CXX11/src/Core/CMakeLists.txt
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@@ -0,0 +1 @@
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add_subdirectory(util)
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6
unsupported/Eigen/CXX11/src/Core/util/CMakeLists.txt
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6
unsupported/Eigen/CXX11/src/Core/util/CMakeLists.txt
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@@ -0,0 +1,6 @@
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FILE(GLOB Eigen_CXX11_Core_util_SRCS "*.h")
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INSTALL(FILES
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${Eigen_CXX11_Core_util_SRCS}
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DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/CXX11/src/Core/util COMPONENT Devel
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)
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6
unsupported/Eigen/CXX11/src/Tensor/CMakeLists.txt
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6
unsupported/Eigen/CXX11/src/Tensor/CMakeLists.txt
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@@ -0,0 +1,6 @@
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FILE(GLOB Eigen_CXX11_Tensor_SRCS "*.h")
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INSTALL(FILES
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${Eigen_CXX11_Tensor_SRCS}
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DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/CXX11/src/Tensor COMPONENT Devel
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)
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@@ -526,48 +526,101 @@ class TensorBase<Derived, WriteAccessors> : public TensorBase<Derived, ReadOnlyA
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}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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TensorLayoutSwapOp<Derived>
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const TensorLayoutSwapOp<const Derived>
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swap_layout() const {
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return TensorLayoutSwapOp<const Derived>(derived());
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}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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TensorLayoutSwapOp<Derived>
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swap_layout() {
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return TensorLayoutSwapOp<Derived>(derived());
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}
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template <typename Axis, typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorConcatenationOp<const Axis, const Derived, const OtherDerived>
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concatenate(const OtherDerived& other, const Axis& axis) const {
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return TensorConcatenationOp<const Axis, const Derived, const OtherDerived>(derived(), other, axis);
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}
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template <typename Axis, typename OtherDerived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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TensorConcatenationOp<const Axis, Derived, OtherDerived>
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concatenate(const OtherDerived& other, const Axis& axis) const {
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return TensorConcatenationOp<const Axis, Derived, OtherDerived>(derived(), other.derived(), axis);
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concatenate(const OtherDerived& other, const Axis& axis) {
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return TensorConcatenationOp<const Axis, Derived, OtherDerived>(derived(), other, axis);
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}
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template <typename NewDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorReshapingOp<const NewDimensions, const Derived>
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reshape(const NewDimensions& newDimensions) const {
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return TensorReshapingOp<const NewDimensions, const Derived>(derived(), newDimensions);
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}
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template <typename NewDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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TensorReshapingOp<const NewDimensions, Derived>
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reshape(const NewDimensions& newDimensions) const {
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reshape(const NewDimensions& newDimensions) {
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return TensorReshapingOp<const NewDimensions, Derived>(derived(), newDimensions);
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}
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template <typename StartIndices, typename Sizes> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorSlicingOp<const StartIndices, const Sizes, const Derived>
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slice(const StartIndices& startIndices, const Sizes& sizes) const {
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return TensorSlicingOp<const StartIndices, const Sizes, const Derived>(derived(), startIndices, sizes);
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}
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template <typename StartIndices, typename Sizes> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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TensorSlicingOp<const StartIndices, const Sizes, Derived>
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slice(const StartIndices& startIndices, const Sizes& sizes) const {
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slice(const StartIndices& startIndices, const Sizes& sizes) {
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return TensorSlicingOp<const StartIndices, const Sizes, Derived>(derived(), startIndices, sizes);
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}
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template <DenseIndex DimId> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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TensorChippingOp<DimId, Derived>
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const TensorChippingOp<DimId, const Derived>
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chip(const Index offset) const {
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return TensorChippingOp<DimId, const Derived>(derived(), offset, DimId);
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}
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template <Index DimId> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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TensorChippingOp<DimId, Derived>
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chip(const Index offset) {
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return TensorChippingOp<DimId, Derived>(derived(), offset, DimId);
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}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorChippingOp<Dynamic, const Derived>
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chip(const Index offset, const Index dim) const {
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return TensorChippingOp<Dynamic, const Derived>(derived(), offset, dim);
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}
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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TensorChippingOp<Dynamic, Derived>
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chip(const Index offset, const Index dim) const {
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chip(const Index offset, const Index dim) {
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return TensorChippingOp<Dynamic, Derived>(derived(), offset, dim);
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}
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template <typename ReverseDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorReverseOp<const ReverseDimensions, const Derived>
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reverse(const ReverseDimensions& rev) const {
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return TensorReverseOp<const ReverseDimensions, const Derived>(derived(), rev);
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}
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template <typename ReverseDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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TensorReverseOp<const ReverseDimensions, Derived>
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reverse(const ReverseDimensions& rev) const {
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reverse(const ReverseDimensions& rev) {
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return TensorReverseOp<const ReverseDimensions, Derived>(derived(), rev);
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}
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template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorShufflingOp<const Shuffle, const Derived>
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shuffle(const Shuffle& shuffle) const {
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return TensorShufflingOp<const Shuffle, const Derived>(derived(), shuffle);
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}
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template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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TensorShufflingOp<const Shuffle, Derived>
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shuffle(const Shuffle& shuffle) const {
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shuffle(const Shuffle& shuffle) {
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return TensorShufflingOp<const Shuffle, Derived>(derived(), shuffle);
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}
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template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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const TensorStridingOp<const Strides, const Derived>
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stride(const Strides& strides) const {
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return TensorStridingOp<const Strides, const Derived>(derived(), strides);
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}
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template <typename Strides> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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TensorStridingOp<const Strides, Derived>
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stride(const Strides& strides) const {
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stride(const Strides& strides) {
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return TensorStridingOp<const Strides, Derived>(derived(), strides);
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}
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@@ -21,8 +21,7 @@ namespace Eigen {
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* Example:
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* C.device(EIGEN_GPU) = A + B;
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*
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* Todo: thread pools.
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* Todo: operator +=, -=, *= and so on.
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* Todo: operator *= and /=.
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*/
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template <typename ExpressionType, typename DeviceType> class TensorDevice {
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@@ -50,6 +49,18 @@ template <typename ExpressionType, typename DeviceType> class TensorDevice {
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return *this;
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}
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE TensorDevice& operator-=(const OtherDerived& other) {
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typedef typename OtherDerived::Scalar Scalar;
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typedef TensorCwiseBinaryOp<internal::scalar_difference_op<Scalar>, const ExpressionType, const OtherDerived> Difference;
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Difference difference(m_expression, other);
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typedef TensorAssignOp<ExpressionType, const Difference> Assign;
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Assign assign(m_expression, difference);
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static const bool Vectorize = TensorEvaluator<const Assign, DeviceType>::PacketAccess;
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internal::TensorExecutor<const Assign, DeviceType, Vectorize>::run(assign, m_device);
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return *this;
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}
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protected:
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const DeviceType& m_device;
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ExpressionType& m_expression;
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@@ -82,6 +93,18 @@ template <typename ExpressionType> class TensorDevice<ExpressionType, ThreadPool
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return *this;
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}
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE TensorDevice& operator-=(const OtherDerived& other) {
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typedef typename OtherDerived::Scalar Scalar;
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typedef TensorCwiseBinaryOp<internal::scalar_difference_op<Scalar>, const ExpressionType, const OtherDerived> Difference;
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Difference difference(m_expression, other);
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typedef TensorAssignOp<ExpressionType, const Difference> Assign;
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Assign assign(m_expression, difference);
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static const bool Vectorize = TensorEvaluator<const Assign, ThreadPoolDevice>::PacketAccess;
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internal::TensorExecutor<const Assign, ThreadPoolDevice, Vectorize>::run(assign, m_device);
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return *this;
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}
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protected:
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const ThreadPoolDevice& m_device;
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ExpressionType& m_expression;
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@@ -114,6 +137,18 @@ template <typename ExpressionType> class TensorDevice<ExpressionType, GpuDevice>
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return *this;
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}
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template<typename OtherDerived>
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EIGEN_STRONG_INLINE TensorDevice& operator-=(const OtherDerived& other) {
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typedef typename OtherDerived::Scalar Scalar;
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typedef TensorCwiseBinaryOp<internal::scalar_difference_op<Scalar>, const ExpressionType, const OtherDerived> Difference;
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Difference difference(m_expression, other);
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typedef TensorAssignOp<ExpressionType, const Difference> Assign;
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Assign assign(m_expression, difference);
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static const bool Vectorize = TensorEvaluator<const Assign, GpuDevice>::PacketAccess;
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internal::TensorExecutor<const Assign, GpuDevice, Vectorize>::run(assign, m_device);
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return *this;
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}
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protected:
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const GpuDevice& m_device;
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ExpressionType m_expression;
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@@ -77,7 +77,7 @@ template <typename T> struct MeanReducer
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}
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template <typename Packet>
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalizeBoth(const T saccum, const Packet& vaccum) const {
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return (saccum + predux(vaccum)) / (scalarCount_ + packetCount_ * packet_traits<Packet>::size);
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return (saccum + predux(vaccum)) / (scalarCount_ + packetCount_ * unpacket_traits<Packet>::size);
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}
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protected:
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@@ -30,14 +30,14 @@ std::ostream& operator << (std::ostream& os, const TensorBase<T, ReadOnlyAccesso
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typedef typename internal::remove_const<typename T::Scalar>::type Scalar;
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typedef typename T::Index Index;
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typedef typename TensorEvaluator<const TensorForcedEvalOp<const T>, DefaultDevice>::Dimensions Dimensions;
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const Index total_size = internal::array_prod(tensor.dimensions());
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const Index total_size = tensor.dimensions().TotalSize();
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// Print the tensor as a 1d vector or a 2d matrix.
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if (internal::array_size<Dimensions>::value == 1) {
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Map<const Array<Scalar, Dynamic, 1> > array(const_cast<Scalar*>(tensor.data()), total_size);
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os << array;
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} else {
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const Index first_dim = tensor.dimensions()[0];
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const Index first_dim = Eigen::internal::array_get<0>(tensor.dimensions());
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static const int layout = TensorEvaluator<const TensorForcedEvalOp<const T>, DefaultDevice>::Layout;
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Map<const Array<Scalar, Dynamic, Dynamic, layout> > matrix(const_cast<Scalar*>(tensor.data()), first_dim, total_size/first_dim);
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os << matrix;
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@@ -65,7 +65,7 @@ struct traits<Tensor<Scalar_, NumIndices_, Options_> >
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static const int Layout = Options_ & RowMajor ? RowMajor : ColMajor;
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enum {
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Options = Options_,
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Flags = compute_tensor_flags<Scalar_, Options_>::ret | LvalueBit,
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Flags = compute_tensor_flags<Scalar_, Options_>::ret | (is_const<Scalar_>::value ? 0 : LvalueBit),
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};
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};
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@@ -80,7 +80,7 @@ struct traits<TensorFixedSize<Scalar_, Dimensions, Options_> >
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static const int Layout = Options_ & RowMajor ? RowMajor : ColMajor;
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enum {
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Options = Options_,
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Flags = compute_tensor_flags<Scalar_, Options_>::ret | LvalueBit,
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Flags = compute_tensor_flags<Scalar_, Options_>::ret | (is_const<Scalar_>::value ? 0: LvalueBit),
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};
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};
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@@ -97,7 +97,7 @@ struct traits<TensorMap<PlainObjectType, Options_> >
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static const int Layout = BaseTraits::Layout;
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enum {
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Options = Options_,
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Flags = ((BaseTraits::Flags | LvalueBit) & ~AlignedBit) | (Options&Aligned ? AlignedBit : 0),
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Flags = (BaseTraits::Flags & ~AlignedBit) | (Options&Aligned ? AlignedBit : 0),
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};
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};
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@@ -113,7 +113,7 @@ struct traits<TensorRef<PlainObjectType> >
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static const int Layout = BaseTraits::Layout;
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enum {
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Options = BaseTraits::Options,
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Flags = ((BaseTraits::Flags | LvalueBit) & ~AlignedBit) | (Options&Aligned ? AlignedBit : 0),
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Flags = (BaseTraits::Flags & ~AlignedBit) | (Options&Aligned ? AlignedBit : 0),
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};
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};
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@@ -0,0 +1,8 @@
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FILE(GLOB Eigen_CXX11_TensorSymmetry_SRCS "*.h")
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INSTALL(FILES
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${Eigen_CXX11_TensorSymmetry_SRCS}
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DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/CXX11/src/TensorSymmetry COMPONENT Devel
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)
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add_subdirectory(util)
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@@ -0,0 +1,6 @@
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FILE(GLOB Eigen_CXX11_TensorSymmetry_util_SRCS "*.h")
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INSTALL(FILES
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${Eigen_CXX11_TensorSymmetry_util_SRCS}
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DESTINATION ${INCLUDE_INSTALL_DIR}/unsupported/Eigen/CXX11/src/TensorSymmetry/util COMPONENT Devel
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)
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