From f697df723798779bc29d9f7299bb5398767d5db0 Mon Sep 17 00:00:00 2001
From: Benoit Steiner <benoit.steiner.goog@gmail.com>
Date: Wed, 14 Jan 2015 15:38:48 -0800
Subject: Improved support for RowMajor tensors Misc fixes and API cleanups.

---
 .../Eigen/CXX11/src/Tensor/TensorForcedEval.h      | 24 +++++++++++++++-------
 1 file changed, 17 insertions(+), 7 deletions(-)

(limited to 'unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h')

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h b/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h
index cb14cc7f7..a9501336e 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h
@@ -25,11 +25,14 @@ struct traits<TensorForcedEvalOp<XprType> >
 {
   // Type promotion to handle the case where the types of the lhs and the rhs are different.
   typedef typename XprType::Scalar Scalar;
-  typedef typename internal::packet_traits<Scalar>::type Packet;
+  typedef traits<XprType> XprTraits;
+  typedef typename packet_traits<Scalar>::type Packet;
   typedef typename traits<XprType>::StorageKind StorageKind;
   typedef typename traits<XprType>::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;
 
   enum {
     Flags = 0,
@@ -59,8 +62,8 @@ class TensorForcedEvalOp : public TensorBase<TensorForcedEvalOp<XprType> >
   typedef typename Eigen::internal::traits<TensorForcedEvalOp>::Scalar Scalar;
   typedef typename Eigen::internal::traits<TensorForcedEvalOp>::Packet Packet;
   typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
-  typedef typename XprType::CoeffReturnType CoeffReturnType;
-  typedef typename XprType::PacketReturnType PacketReturnType;
+  typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
+  typedef typename internal::remove_const<typename XprType::PacketReturnType>::type PacketReturnType;
   typedef typename Eigen::internal::nested<TensorForcedEvalOp>::type Nested;
   typedef typename Eigen::internal::traits<TensorForcedEvalOp>::StorageKind StorageKind;
   typedef typename Eigen::internal::traits<TensorForcedEvalOp>::Index Index;
@@ -88,6 +91,7 @@ struct TensorEvaluator<const TensorForcedEvalOp<ArgType>, Device>
   enum {
     IsAligned = true,
     PacketAccess = (internal::packet_traits<Scalar>::size > 1),
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
   };
 
   EIGEN_DEVICE_FUNC TensorEvaluator(const XprType& op, const Device& device)
@@ -100,10 +104,16 @@ struct TensorEvaluator<const TensorForcedEvalOp<ArgType>, Device>
 
   EIGEN_DEVICE_FUNC const Dimensions& dimensions() const { return m_impl.dimensions(); }
 
-  EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
+  EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType*) {
     m_impl.evalSubExprsIfNeeded(NULL);
-    m_buffer = (Scalar*)m_device.allocate(m_impl.dimensions().TotalSize() * sizeof(Scalar));
-
+    const Index numValues = m_impl.dimensions().TotalSize();
+    m_buffer = (CoeffReturnType*)m_device.allocate(numValues * sizeof(CoeffReturnType));
+    // Should initialize the memory in case we're dealing with non POD types.
+    if (!internal::is_arithmetic<CoeffReturnType>::value) {
+      for (Index i = 0; i < numValues; ++i) {
+        new(m_buffer+i) CoeffReturnType();
+      }
+    }
     typedef TensorEvalToOp<const ArgType> EvalTo;
     EvalTo evalToTmp(m_buffer, m_op);
     internal::TensorExecutor<const EvalTo, Device, TensorEvaluator<ArgType, Device>::PacketAccess>::run(evalToTmp, m_device);
@@ -132,7 +142,7 @@ struct TensorEvaluator<const TensorForcedEvalOp<ArgType>, Device>
   TensorEvaluator<ArgType, Device> m_impl;
   const ArgType m_op;
   const Device& m_device;
-  Scalar* m_buffer;
+  CoeffReturnType* m_buffer;
 };
 
 
-- 
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