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diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h b/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h
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+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorForcedEval.h
@@ -0,0 +1,167 @@
+// 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_FORCED_EVAL_H
+#define EIGEN_CXX11_TENSOR_TENSOR_FORCED_EVAL_H
+
+namespace Eigen {
+
+/** \class TensorForcedEval
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor reshaping class.
+  *
+  *
+  */
+/// template <class> class MakePointer_ is added to convert the host pointer to the device pointer.
+/// It is added due to the fact that for our device compiler T* is not allowed.
+/// If we wanted to use the same Evaluator functions we have to convert that type to our pointer T.
+/// This is done through our MakePointer_ class. By default the Type in the MakePointer_<T> is T* .
+/// Therefore, by adding the default value, we managed to convert the type and it does not break any
+/// existing code as its default value is T*.
+namespace internal {
+template<typename XprType, template <class> class MakePointer_>
+struct traits<TensorForcedEvalOp<XprType, MakePointer_> >
+{
+  // Type promotion to handle the case where the types of the lhs and the rhs are different.
+  typedef typename XprType::Scalar Scalar;
+  typedef traits<XprType> XprTraits;
+  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
+  };
+  template <class T> struct MakePointer {
+    // Intermediate typedef to workaround MSVC issue.
+    typedef MakePointer_<T> MakePointerT;
+    typedef typename MakePointerT::Type Type;
+  };
+};
+
+template<typename XprType, template <class> class MakePointer_>
+struct eval<TensorForcedEvalOp<XprType, MakePointer_>, Eigen::Dense>
+{
+  typedef const TensorForcedEvalOp<XprType, MakePointer_>& type;
+};
+
+template<typename XprType, template <class> class MakePointer_>
+struct nested<TensorForcedEvalOp<XprType, MakePointer_>, 1, typename eval<TensorForcedEvalOp<XprType, MakePointer_> >::type>
+{
+  typedef TensorForcedEvalOp<XprType, MakePointer_> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename XprType, template <class> class MakePointer_>
+class TensorForcedEvalOp : public TensorBase<TensorForcedEvalOp<XprType, MakePointer_>, ReadOnlyAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorForcedEvalOp>::Scalar Scalar;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename internal::remove_const<typename XprType::CoeffReturnType>::type CoeffReturnType;
+  typedef typename Eigen::internal::nested<TensorForcedEvalOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorForcedEvalOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorForcedEvalOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorForcedEvalOp(const XprType& expr)
+      : m_xpr(expr) {}
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+  protected:
+    typename XprType::Nested m_xpr;
+};
+
+
+template<typename ArgType, typename Device, template <class> class MakePointer_>
+struct TensorEvaluator<const TensorForcedEvalOp<ArgType, MakePointer_>, Device>
+{
+  typedef TensorForcedEvalOp<ArgType, MakePointer_> XprType;
+  typedef typename ArgType::Scalar Scalar;
+  typedef typename TensorEvaluator<ArgType, Device>::Dimensions Dimensions;
+  typedef typename XprType::Index Index;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
+  static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
+
+  enum {
+    IsAligned = true,
+    PacketAccess = (PacketSize > 1),
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    RawAccess = true
+  };
+
+  EIGEN_DEVICE_FUNC TensorEvaluator(const XprType& op, const Device& device)
+	/// op_ is used for sycl
+      : m_impl(op.expression(), device), m_op(op.expression()), m_device(device), m_buffer(NULL)
+  { }
+
+  EIGEN_DEVICE_FUNC const Dimensions& dimensions() const { return m_impl.dimensions(); }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(CoeffReturnType*) {
+    const Index numValues =  internal::array_prod(m_impl.dimensions());
+    m_buffer = (CoeffReturnType*)m_device.allocate(numValues * sizeof(CoeffReturnType));
+    // Should initialize the memory in case we're dealing with non POD types.
+    if (NumTraits<CoeffReturnType>::RequireInitialization) {
+      for (Index i = 0; i < numValues; ++i) {
+        new(m_buffer+i) CoeffReturnType();
+      }
+    }
+    typedef TensorEvalToOp< const typename internal::remove_const<ArgType>::type > EvalTo;
+    EvalTo evalToTmp(m_buffer, m_op);
+    const bool PacketAccess = internal::IsVectorizable<Device, const ArgType>::value;
+    internal::TensorExecutor<const EvalTo, typename internal::remove_const<Device>::type, PacketAccess>::run(evalToTmp, m_device);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_device.deallocate(m_buffer);
+    m_buffer = NULL;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    return m_buffer[index];
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    return internal::ploadt<PacketReturnType, LoadMode>(m_buffer + index);
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
+    return TensorOpCost(sizeof(CoeffReturnType), 0, 0, vectorized, PacketSize);
+  }
+
+  EIGEN_DEVICE_FUNC typename MakePointer<Scalar>::Type data() const { return m_buffer; }
+
+  /// required by sycl in order to extract the sycl accessor
+  const TensorEvaluator<ArgType, Device>& impl() { return m_impl; }
+  /// used by sycl in order to build the sycl buffer
+  const Device& device() const{return m_device;}
+ private:
+  TensorEvaluator<ArgType, Device> m_impl;
+  const ArgType m_op;
+  const Device& m_device;
+  typename MakePointer<CoeffReturnType>::Type m_buffer;
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_FORCED_EVAL_H