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authorGravatar Benoit Steiner <benoit.steiner.goog@gmail.com>2015-06-30 15:36:29 -0700
committerGravatar Benoit Steiner <benoit.steiner.goog@gmail.com>2015-06-30 15:36:29 -0700
commitf1f480b116913b9c90fce0626f1643eb9f021003 (patch)
treeb45dbfadc6cc8540d2fbd62904747ead0020b38b /unsupported/Eigen/CXX11
parentdc31fcb9ba064f2124827aefb2ca5857327c005e (diff)
Added support for user defined custom tensor op.
Diffstat (limited to 'unsupported/Eigen/CXX11')
-rw-r--r--unsupported/Eigen/CXX11/Tensor1
-rw-r--r--unsupported/Eigen/CXX11/src/Tensor/TensorBase.h12
-rw-r--r--unsupported/Eigen/CXX11/src/Tensor/TensorCustomOp.h310
-rw-r--r--unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h3
-rw-r--r--unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h6
5 files changed, 329 insertions, 3 deletions
diff --git a/unsupported/Eigen/CXX11/Tensor b/unsupported/Eigen/CXX11/Tensor
index 50753a53a..3f9aa1026 100644
--- a/unsupported/Eigen/CXX11/Tensor
+++ b/unsupported/Eigen/CXX11/Tensor
@@ -91,6 +91,7 @@
#include "unsupported/Eigen/CXX11/src/Tensor/TensorReverse.h"
#include "unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h"
#include "unsupported/Eigen/CXX11/src/Tensor/TensorStriding.h"
+#include "unsupported/Eigen/CXX11/src/Tensor/TensorCustomOp.h"
#include "unsupported/Eigen/CXX11/src/Tensor/TensorEvalTo.h"
#include "unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h"
#include "unsupported/Eigen/CXX11/src/Tensor/TensorGenerator.h"
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h b/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
index b5bdf9d8e..1c31b9d28 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
@@ -481,6 +481,18 @@ class TensorBase<Derived, ReadOnlyAccessors>
return TensorStridingOp<const Strides, const Derived>(derived(), strides);
}
+ // Added support for custom unary and binary operations
+ template <typename CustomUnaryFunc>
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+ const TensorCustomUnaryOp<const CustomUnaryFunc, const Derived> customOp(const CustomUnaryFunc& op) const {
+ return TensorCustomUnaryOp<const CustomUnaryFunc, const Derived>(derived(), op);
+ }
+ template <typename OtherDerived, typename CustomBinaryFunc>
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+ const TensorCustomBinaryOp<const CustomBinaryFunc, const Derived, const OtherDerived> customOp(const OtherDerived& other, const CustomBinaryFunc& op) const {
+ return TensorCustomBinaryOp<const CustomBinaryFunc, const Derived, const OtherDerived>(derived(), other, op);
+ }
+
// Force the evaluation of the expression.
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
const TensorForcedEvalOp<const Derived> eval() const {
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorCustomOp.h b/unsupported/Eigen/CXX11/src/Tensor/TensorCustomOp.h
new file mode 100644
index 000000000..0157f6fab
--- /dev/null
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorCustomOp.h
@@ -0,0 +1,310 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2014 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_CUSTOM_OP_H
+#define EIGEN_CXX11_TENSOR_TENSOR_CUSTOM_OP_H
+
+namespace Eigen {
+
+/** \class TensorCustomUnaryOp
+ * \ingroup CXX11_Tensor_Module
+ *
+ * \brief Tensor custom class.
+ *
+ *
+ */
+namespace internal {
+template<typename CustomUnaryFunc, typename XprType>
+struct traits<TensorCustomUnaryOp<CustomUnaryFunc, XprType> >
+{
+ typedef typename XprType::Scalar Scalar;
+ typedef typename packet_traits<Scalar>::type Packet;
+ typedef typename XprType::StorageKind StorageKind;
+ typedef typename XprType::Index Index;
+ typedef typename XprType::Nested Nested;
+ typedef typename remove_reference<Nested>::type _Nested;
+ static const int NumDimensions = traits<XprType>::NumDimensions;
+ static const int Layout = traits<XprType>::Layout;
+};
+
+template<typename CustomUnaryFunc, typename XprType>
+struct eval<TensorCustomUnaryOp<CustomUnaryFunc, XprType>, Eigen::Dense>
+{
+ typedef const TensorCustomUnaryOp<CustomUnaryFunc, XprType>& type;
+};
+
+template<typename CustomUnaryFunc, typename XprType>
+struct nested<TensorCustomUnaryOp<CustomUnaryFunc, XprType> >
+{
+ typedef TensorCustomUnaryOp<CustomUnaryFunc, XprType> type;
+};
+
+} // end namespace internal
+
+
+
+template<typename CustomUnaryFunc, typename XprType>
+class TensorCustomUnaryOp : public TensorBase<TensorCustomUnaryOp<CustomUnaryFunc, XprType>, ReadOnlyAccessors>
+{
+ public:
+ typedef typename internal::traits<TensorCustomUnaryOp>::Scalar Scalar;
+ typedef typename internal::traits<TensorCustomUnaryOp>::Packet Packet;
+ typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+ typedef typename XprType::CoeffReturnType CoeffReturnType;
+ typedef typename XprType::PacketReturnType PacketReturnType;
+ typedef typename internal::nested<TensorCustomUnaryOp>::type Nested;
+ typedef typename internal::traits<TensorCustomUnaryOp>::StorageKind StorageKind;
+ typedef typename internal::traits<TensorCustomUnaryOp>::Index Index;
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorCustomUnaryOp(const XprType& expr, const CustomUnaryFunc& func)
+ : m_expr(expr), m_func(func) {}
+
+ EIGEN_DEVICE_FUNC
+ const CustomUnaryFunc& func() const { return m_func; }
+
+ EIGEN_DEVICE_FUNC
+ const typename internal::remove_all<typename XprType::Nested>::type&
+ expression() const { return m_expr; }
+
+ protected:
+ typename XprType::Nested m_expr;
+ const CustomUnaryFunc m_func;
+};
+
+
+// Eval as rvalue
+template<typename CustomUnaryFunc, typename XprType, typename Device>
+struct TensorEvaluator<const TensorCustomUnaryOp<CustomUnaryFunc, XprType>, Device>
+{
+ typedef TensorCustomUnaryOp<CustomUnaryFunc, XprType> ArgType;
+ typedef typename internal::traits<ArgType>::Index Index;
+ static const int NumDims = internal::traits<ArgType>::NumDimensions;
+ typedef DSizes<Index, NumDims> Dimensions;
+ typedef
+ typename internal::remove_const<typename ArgType::Scalar>::type Scalar;
+
+ enum {
+ IsAligned = false,
+ PacketAccess = (internal::packet_traits<Scalar>::size > 1),
+ BlockAccess = false,
+ Layout = TensorEvaluator<XprType, Device>::Layout,
+ CoordAccess = false, // to be implemented
+ };
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const ArgType& op, const Device& device)
+ : m_op(op), m_device(device), m_result(NULL)
+ {
+ m_dimensions = op.func().dimensions(op.expression());
+ }
+
+ typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
+ typedef typename XprType::PacketReturnType PacketReturnType;
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType* data) {
+ if (data) {
+ evalTo(data);
+ return false;
+ } else {
+ m_result = static_cast<CoeffReturnType*>(
+ m_device.allocate(dimensions().TotalSize() * sizeof(Scalar)));
+ evalTo(m_result);
+ return true;
+ }
+ }
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+ if (m_result != NULL) {
+ m_device.deallocate(m_result);
+ m_result = NULL;
+ }
+ }
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
+ return m_result[index];
+ }
+
+ template<int LoadMode>
+ EIGEN_DEVICE_FUNC PacketReturnType packet(Index index) const {
+ return internal::ploadt<PacketReturnType, LoadMode>(m_result + index);
+ }
+
+ EIGEN_DEVICE_FUNC CoeffReturnType* data() const { return m_result; }
+
+ protected:
+ EIGEN_DEVICE_FUNC void evalTo(Scalar* data) {
+ TensorMap<Tensor<CoeffReturnType, NumDims, Layout, Index> > result(
+ data, m_dimensions);
+ m_op.func().eval(m_op.expression(), result, m_device);
+ }
+
+ Dimensions m_dimensions;
+ const ArgType m_op;
+ const Device& m_device;
+ CoeffReturnType* m_result;
+};
+
+
+
+/** \class TensorCustomBinaryOp
+ * \ingroup CXX11_Tensor_Module
+ *
+ * \brief Tensor custom class.
+ *
+ *
+ */
+namespace internal {
+template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType>
+struct traits<TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType> >
+{
+ typedef typename internal::promote_storage_type<typename LhsXprType::Scalar,
+ typename RhsXprType::Scalar>::ret Scalar;
+ typedef typename packet_traits<Scalar>::type Packet;
+ typedef typename internal::promote_storage_type<typename LhsXprType::CoeffReturnType,
+ typename RhsXprType::CoeffReturnType>::ret CoeffReturnType;
+ typedef typename internal::promote_storage_type<typename LhsXprType::PacketReturnType,
+ typename RhsXprType::PacketReturnType>::ret PacketReturnType;
+ typedef typename promote_storage_type<typename traits<LhsXprType>::StorageKind,
+ typename traits<RhsXprType>::StorageKind>::ret StorageKind;
+ 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 typename remove_reference<LhsNested>::type _LhsNested;
+ typedef typename remove_reference<RhsNested>::type _RhsNested;
+ static const int NumDimensions = traits<LhsXprType>::NumDimensions;
+ static const int Layout = traits<LhsXprType>::Layout;
+};
+
+template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType>
+struct eval<TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType>, Eigen::Dense>
+{
+ typedef const TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType>& type;
+};
+
+template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType>
+struct nested<TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType> >
+{
+ typedef TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType> type;
+};
+
+} // end namespace internal
+
+
+
+template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType>
+class TensorCustomBinaryOp : public TensorBase<TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType>, ReadOnlyAccessors>
+{
+ public:
+ typedef typename internal::traits<TensorCustomBinaryOp>::Scalar Scalar;
+ typedef typename internal::traits<TensorCustomBinaryOp>::Packet Packet;
+ typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+ typedef typename internal::traits<TensorCustomBinaryOp>::CoeffReturnType CoeffReturnType;
+ typedef typename internal::traits<TensorCustomBinaryOp>::PacketReturnType PacketReturnType;
+ typedef typename internal::nested<TensorCustomBinaryOp>::type Nested;
+ typedef typename internal::traits<TensorCustomBinaryOp>::StorageKind StorageKind;
+ typedef typename internal::traits<TensorCustomBinaryOp>::Index Index;
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorCustomBinaryOp(const LhsXprType& lhs, const RhsXprType& rhs, const CustomBinaryFunc& func)
+
+ : m_lhs_xpr(lhs), m_rhs_xpr(rhs), m_func(func) {}
+
+ EIGEN_DEVICE_FUNC
+ const CustomBinaryFunc& func() const { return m_func; }
+
+ EIGEN_DEVICE_FUNC
+ const typename internal::remove_all<typename LhsXprType::Nested>::type&
+ lhsExpression() const { return m_lhs_xpr; }
+
+ EIGEN_DEVICE_FUNC
+ const typename internal::remove_all<typename RhsXprType::Nested>::type&
+ rhsExpression() const { return m_rhs_xpr; }
+
+ protected:
+ typename LhsXprType::Nested m_lhs_xpr;
+ typename RhsXprType::Nested m_rhs_xpr;
+ const CustomBinaryFunc m_func;
+};
+
+
+// Eval as rvalue
+template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType, typename Device>
+struct TensorEvaluator<const TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType>, Device>
+{
+ typedef TensorCustomBinaryOp<CustomBinaryFunc, LhsXprType, RhsXprType> XprType;
+ typedef typename internal::traits<XprType>::Index Index;
+ static const int NumDims = internal::traits<XprType>::NumDimensions;
+ typedef DSizes<Index, NumDims> Dimensions;
+ typedef typename XprType::Scalar Scalar;
+
+ enum {
+ IsAligned = false,
+ PacketAccess = (internal::packet_traits<Scalar>::size > 1),
+ BlockAccess = false,
+ Layout = TensorEvaluator<LhsXprType, Device>::Layout,
+ CoordAccess = false, // to be implemented
+ };
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+ : m_op(op), m_device(device), m_result(NULL)
+ {
+ m_dimensions = op.func().dimensions(op.lhsExpression(), op.rhsExpression());
+ }
+
+ typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
+ typedef typename XprType::PacketReturnType PacketReturnType;
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType* data) {
+ if (data) {
+ evalTo(data);
+ return false;
+ } else {
+ m_result = static_cast<Scalar *>(m_device.allocate(dimensions().TotalSize() * sizeof(Scalar)));
+ evalTo(m_result);
+ return true;
+ }
+ }
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+ if (m_result != NULL) {
+ m_device.deallocate(m_result);
+ m_result = NULL;
+ }
+ }
+
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const {
+ return m_result[index];
+ }
+
+ template<int LoadMode>
+ EIGEN_DEVICE_FUNC PacketReturnType packet(Index index) const {
+ return internal::ploadt<PacketReturnType, LoadMode>(m_result + index);
+ }
+
+ EIGEN_DEVICE_FUNC CoeffReturnType* data() const { return m_result; }
+
+ protected:
+ EIGEN_DEVICE_FUNC void evalTo(Scalar* data) {
+ TensorMap<Tensor<Scalar, NumDims, Layout> > result(data, m_dimensions);
+ m_op.func().eval(m_op.lhsExpression(), m_op.rhsExpression(), result, m_device);
+ }
+
+ Dimensions m_dimensions;
+ const XprType m_op;
+ const Device& m_device;
+ CoeffReturnType* m_result;
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_CUSTOM_OP_H
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h b/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
index a3fb26acc..7df8d1453 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h
@@ -42,6 +42,9 @@ template<typename Strides, typename XprType> class TensorStridingOp;
template<typename Generator, typename XprType> class TensorGeneratorOp;
template<typename LeftXprType, typename RightXprType> class TensorAssignOp;
+template<typename CustomUnaryFunc, typename XprType> class TensorCustomUnaryOp;
+template<typename CustomBinaryFunc, typename LhsXprType, typename RhsXprType> class TensorCustomBinaryOp;
+
template<typename XprType> class TensorEvalToOp;
template<typename XprType> class TensorForcedEvalOp;
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h b/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h
index 757d6cb38..2e6b93bfb 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorTraits.h
@@ -156,9 +156,9 @@ struct eval<const TensorRef<PlainObjectType>, Eigen::Dense>
};
// TODO nested<> does not exist anymore in Eigen/Core, and it thus has to be removed in favor of ref_selector.
-template<typename T, int n=1, typename PlainObject = void> struct nested
-{
- typedef typename ref_selector<T>::type type;
+template<typename T, int n=1, typename PlainObject = void> struct nested
+{
+ typedef typename ref_selector<T>::type type;
};
template <typename Scalar_, std::size_t NumIndices_, int Options_, typename IndexType_>