Can now use the tensor 'reverse' operation as a lvalue

unsupported/Eigen/CXX11/src/Tensor/TensorBase.h

@@ -549,6 +549,11 @@ class TensorBase<Derived, WriteAccessors> : public TensorBase<Derived, ReadOnlyA
     chip(const Index offset, const Index dim) const {
       return TensorChippingOp<Dynamic, Derived>(derived(), offset, dim);
     }
+    template <typename ReverseDimensions> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    TensorReverseOp<const ReverseDimensions, Derived>
+    reverse(const ReverseDimensions& rev) const {
+      return TensorReverseOp<const ReverseDimensions, Derived>(derived(), rev);
+    }
     template <typename Shuffle> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     TensorShufflingOp<const Shuffle, Derived>
     shuffle(const Shuffle& shuffle) const {

unsupported/Eigen/CXX11/src/Tensor/TensorReverse.h

@@ -49,12 +49,9 @@ struct nested<TensorReverseOp<ReverseDimensions, XprType>, 1,
 
 }  // end namespace internal
 
-
-
-
 template<typename ReverseDimensions, typename XprType>
 class TensorReverseOp : public TensorBase<TensorReverseOp<ReverseDimensions,
-                                          XprType>, ReadOnlyAccessors>
+                                          XprType>, WriteAccessors>
 {
   public:
   typedef typename Eigen::internal::traits<TensorReverseOp>::Scalar Scalar;
@@ -67,8 +64,8 @@ class TensorReverseOp : public TensorBase<TensorReverseOp<ReverseDimensions,
                                                                     StorageKind;
   typedef typename Eigen::internal::traits<TensorReverseOp>::Index Index;
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorReverseOp(const XprType& expr,
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorReverseOp(
-                                          const ReverseDimensions& reverse_dims)
+      const XprType& expr, const ReverseDimensions& reverse_dims)
       : m_xpr(expr), m_reverse_dims(reverse_dims) {}
 
     EIGEN_DEVICE_FUNC
@@ -78,12 +75,30 @@ class TensorReverseOp : public TensorBase<TensorReverseOp<ReverseDimensions,
     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, false>::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, false>::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>
@@ -134,8 +149,8 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
     m_impl.cleanup();
   }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  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)) {
@@ -152,7 +167,6 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
       } else {
         inputIndex += index;
       }
-      return m_impl.coeff(inputIndex);
     } else {
       for (int i = 0; i < NumDims - 1; ++i) {
         Index idx = index / m_strides[i];
@@ -167,8 +181,13 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
       } else {
         inputIndex += index;
       }
-      return m_impl.coeff(inputIndex);
     }
+    return inputIndex;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(
+      Index index) const  {
+    return m_impl.coeff(reverseIndex(index));
   }
 
   template<int LoadMode>
@@ -199,7 +218,55 @@ struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device
   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
+  };
+  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 XprType::PacketReturnType PacketReturnType;
+
+  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) {
+    const int packetSize = internal::unpacket_traits<PacketReturnType>::size;
+    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_DEFAULT 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

unsupported/test/cxx11_tensor_reverse.cpp

@@ -94,7 +94,7 @@ static void test_simple_reverse()
 
 
 template <int DataLayout>
-static void test_expr_reverse()
+static void test_expr_reverse(bool LValue)
 {
   Tensor<float, 4, DataLayout> tensor(2,3,5,7);
   tensor.setRandom();
@@ -105,9 +105,12 @@ static void test_expr_reverse()
   dim_rev[2] = false;
   dim_rev[3] = true;
 
-
+  Tensor<float, 4, DataLayout> expected(2, 3, 5, 7);
-  Tensor<float, 4, DataLayout> expected;
+  if (LValue) {
+    expected.reverse(dim_rev) = tensor;
+  } else {
     expected = tensor.reverse(dim_rev);
+  }
 
   Tensor<float, 4, DataLayout> result(2,3,5,7);
 
@@ -117,8 +120,13 @@ static void test_expr_reverse()
   array<ptrdiff_t, 4> dst_slice_start{{0,0,0,0}};
 
   for (int i = 0; i < 5; ++i) {
+    if (LValue) {
+      result.slice(dst_slice_start, dst_slice_dim).reverse(dim_rev) =
+          tensor.slice(src_slice_start, src_slice_dim);
+    } else {
       result.slice(dst_slice_start, dst_slice_dim) =
           tensor.slice(src_slice_start, src_slice_dim).reverse(dim_rev);
+    }
     src_slice_start[2] += 1;
     dst_slice_start[2] += 1;
   }
@@ -141,8 +149,13 @@ static void test_expr_reverse()
   dst_slice_start[2] = 0;
   result.setRandom();
   for (int i = 0; i < 5; ++i) {
+     if (LValue) {
+       result.slice(dst_slice_start, dst_slice_dim).reverse(dim_rev) =
+           tensor.slice(dst_slice_start, dst_slice_dim);
+     } else {
        result.slice(dst_slice_start, dst_slice_dim) =
            tensor.reverse(dim_rev).slice(dst_slice_start, dst_slice_dim);
+     }
     dst_slice_start[2] += 1;
   }
 
@@ -162,6 +175,8 @@ void test_cxx11_tensor_reverse()
 {
   CALL_SUBTEST(test_simple_reverse<ColMajor>());
   CALL_SUBTEST(test_simple_reverse<RowMajor>());
-  CALL_SUBTEST(test_expr_reverse<ColMajor>());
+  CALL_SUBTEST(test_expr_reverse<ColMajor>(true));
-  CALL_SUBTEST(test_expr_reverse<RowMajor>());
+  CALL_SUBTEST(test_expr_reverse<RowMajor>(true));
+  CALL_SUBTEST(test_expr_reverse<ColMajor>(false));
+  CALL_SUBTEST(test_expr_reverse<RowMajor>(false));
 }