From 2859a31ac80af86fa58e5347be50d32fd07bcd3c Mon Sep 17 00:00:00 2001
From: Benoit Steiner <benoit.steiner.goog@gmail.com>
Date: Mon, 9 Jun 2014 09:42:34 -0700
Subject: [PATCH] Fixed compilation error

---
 unsupported/Eigen/CXX11/src/Tensor/TensorMap.h | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h b/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
index 3a2ff5b30..3a06170fa 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
@@ -54,18 +54,18 @@ template<typename PlainObjectType, int Options_> class TensorMap : public Tensor
       PacketAccess = true,
     };
 
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension) : m_data(dataPtr), m_dimensions(array<DenseIndex, NumIndices>(firstDimension)) {
-      // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
-      EIGEN_STATIC_ASSERT(1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
-    }
-
 #ifdef EIGEN_HAS_VARIADIC_TEMPLATES
     template<typename... IndexTypes> EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension, IndexTypes... otherDimensions) : m_data(dataPtr), m_dimensions(array<DenseIndex, NumIndices>({{firstDimension, otherDimensions...}})) {
       // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
       EIGEN_STATIC_ASSERT(sizeof...(otherDimensions) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
     }
+#else
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension) : m_data(dataPtr), m_dimensions(array<DenseIndex, NumIndices>(firstDimension)) {
+      // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
+      EIGEN_STATIC_ASSERT(1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    }
 #endif
 
     inline TensorMap(PointerArgType dataPtr, const array<Index, NumIndices>& dimensions)