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diff --git a/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorStorage.h b/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorStorage.h
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+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2013 Christian Seiler <christian@iwakd.de>
+//
+// 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_TENSORSTORAGE_H
+#define EIGEN_CXX11_TENSOR_TENSORSTORAGE_H
+
+#ifdef EIGEN_TENSOR_STORAGE_CTOR_PLUGIN
+  #define EIGEN_INTERNAL_TENSOR_STORAGE_CTOR_PLUGIN EIGEN_TENSOR_STORAGE_CTOR_PLUGIN;
+#else
+  #define EIGEN_INTERNAL_TENSOR_STORAGE_CTOR_PLUGIN
+#endif
+
+namespace Eigen {
+
+/** \internal
+  *
+  * \class TensorStorage
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Stores the data of a tensor
+  *
+  * This class stores the data of fixed-size, dynamic-size or mixed tensors
+  * in a way as compact as possible.
+  *
+  * \sa Tensor
+  */
+template<typename T, typename Dimensions, int Options_> class TensorStorage;
+
+
+// Pure fixed-size storage
+template<typename T, int Options_, typename FixedDimensions>
+class TensorStorage<T, FixedDimensions, Options_>
+{
+ private:
+  static const std::size_t Size = FixedDimensions::total_size;
+
+  EIGEN_ALIGN_DEFAULT T m_data[Size];
+  FixedDimensions m_dimensions;
+
+ public:
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE TensorStorage() {
+    EIGEN_STATIC_ASSERT(Size == FixedDimensions::total_size, YOU_MADE_A_PROGRAMMING_MISTAKE)
+  }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE T *data() { return m_data; }
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const T *data() const { return m_data; }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE const FixedDimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC
+  EIGEN_STRONG_INLINE DenseIndex size() const { return m_dimensions.TotalSize(); }
+};
+
+
+// pure dynamic
+template<typename T, int Options_, typename IndexType, std::size_t NumIndices_>
+class TensorStorage<T, DSizes<IndexType, NumIndices_>, Options_>
+{
+  public:
+    typedef IndexType Index;
+    typedef DSizes<IndexType, NumIndices_> Dimensions;
+    typedef TensorStorage<T, DSizes<IndexType, NumIndices_>, Options_> Self;
+
+    EIGEN_DEVICE_FUNC TensorStorage()
+      : m_data(NumIndices_ ? 0 : internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(1))
+      , m_dimensions() {}
+
+    EIGEN_DEVICE_FUNC TensorStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(NumIndices_ ? 0 : internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(1))
+      , m_dimensions(internal::template repeat<NumIndices_, Index>(0)) {}
+
+    EIGEN_DEVICE_FUNC TensorStorage(Index size, const array<Index, NumIndices_>& dimensions)
+        : m_data(internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(size)), m_dimensions(dimensions)
+      { EIGEN_INTERNAL_TENSOR_STORAGE_CTOR_PLUGIN }
+
+    EIGEN_DEVICE_FUNC TensorStorage(const Self& other)
+      : m_data(internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(internal::array_prod(other.m_dimensions)))
+      , m_dimensions(other.m_dimensions)
+    {
+      internal::smart_copy(other.m_data, other.m_data+internal::array_prod(other.m_dimensions), m_data);
+    }
+    EIGEN_DEVICE_FUNC Self& operator=(const Self& other)
+    {
+      if (this != &other) {
+        Self tmp(other);
+        this->swap(tmp);
+      }
+      return *this;
+    }
+
+    EIGEN_DEVICE_FUNC  ~TensorStorage() { internal::conditional_aligned_delete_auto<T,(Options_&DontAlign)==0>(m_data, internal::array_prod(m_dimensions)); }
+    EIGEN_DEVICE_FUNC  void swap(Self& other)
+    { numext::swap(m_data,other.m_data); numext::swap(m_dimensions,other.m_dimensions); }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const {return m_dimensions;}
+
+    EIGEN_DEVICE_FUNC void resize(Index size, const array<Index, NumIndices_>& nbDimensions)
+    {
+      const Index currentSz = internal::array_prod(m_dimensions);
+      if(size != currentSz)
+      {
+        internal::conditional_aligned_delete_auto<T,(Options_&DontAlign)==0>(m_data, currentSz);
+        if (size)
+          m_data = internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(size);
+        else
+          m_data = 0;
+        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+      }
+      m_dimensions = nbDimensions;
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T *data() { return m_data; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const T *data() const { return m_data; }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index size() const { return m_dimensions.TotalSize(); }
+
+ private:
+  T *m_data;
+  Dimensions m_dimensions;
+};
+
+
+// pure dynamic
+template<typename T, int Options_>
+class TensorStorage<T, VSizes<DenseIndex>, Options_>
+{
+    T* m_data;
+    VSizes<DenseIndex> m_dimensions;
+    typedef TensorStorage<T, VSizes<DenseIndex>, Options_> Self_;
+
+  public:
+    EIGEN_DEVICE_FUNC TensorStorage() : m_data(0), m_dimensions() {}
+
+    template <DenseIndex NumDims>
+    EIGEN_DEVICE_FUNC TensorStorage(const array<DenseIndex, NumDims>& dimensions)
+      {
+        m_dimensions.resize(NumDims);
+        for (int i = 0; i < NumDims; ++i) {
+          m_dimensions[i] = dimensions[i];
+        }
+        const DenseIndex size = array_prod(dimensions);
+        m_data = internal::conditional_managed_new_auto<T,(Options_&DontAlign)==0,(Options_&AllocateUVM)>(size);
+        EIGEN_INTERNAL_TENSOR_STORAGE_CTOR_PLUGIN
+      }
+
+    EIGEN_DEVICE_FUNC TensorStorage(const std::vector<DenseIndex>& dimensions)
+        : m_dimensions(dimensions)
+      {
+        const DenseIndex size = internal::array_prod(dimensions);
+        m_data = internal::conditional_managed_new_auto<T,(Options_&DontAlign)==0,(Options_&AllocateUVM)>(size);
+        EIGEN_INTERNAL_TENSOR_STORAGE_CTOR_PLUGIN
+      }
+
+#ifdef EIGEN_HAS_VARIADIC_TEMPLATES
+    template<typename... IndexTypes> EIGEN_DEVICE_FUNC
+    TensorStorage(IndexTypes... dimensions) {
+      const int NumDims = sizeof...(dimensions);
+      m_dimensions.resize(NumDims);
+      const array<DenseIndex, NumDims> dim{{dimensions...}};
+      DenseIndex size = 1;
+      for (int i = 0; i < NumDims; ++i) {
+        size *= dim[i];
+        m_dimensions[i] = dim[i];
+      }
+      m_data = internal::conditional_managed_new_auto<T,(Options_&DontAlign)==0,(Options_&AllocateUVM)>(size);
+      EIGEN_INTERNAL_TENSOR_STORAGE_CTOR_PLUGIN
+    }
+#endif
+
+    EIGEN_DEVICE_FUNC TensorStorage(const Self_& other)
+      : m_data(internal::conditional_managed_new_auto<T,(Options_&DontAlign)==0,(Options_&AllocateUVM)>(internal::array_prod(other.m_dimensions)))
+      , m_dimensions(other.m_dimensions)
+    {
+      internal::smart_copy(other.m_data, other.m_data+internal::array_prod(other.m_dimensions), m_data);
+    }
+
+    EIGEN_DEVICE_FUNC Self_& operator=(const Self_& other)
+    {
+      if (this != &other) {
+        Self_ tmp(other);
+        this->swap(tmp);
+      }
+      return *this;
+    }
+
+    EIGEN_DEVICE_FUNC ~TensorStorage()
+    {
+      internal::conditional_managed_delete_auto<T,(Options_&DontAlign)==0,(Options_&AllocateUVM)>(m_data, internal::array_prod(m_dimensions));
+    }
+
+    EIGEN_DEVICE_FUNC void swap(Self_& other)
+    { std::swap(m_data,other.m_data); std::swap(m_dimensions,other.m_dimensions); }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const VSizes<DenseIndex>& dimensions() const { return m_dimensions; }
+
+    template <typename NewDimensions> EIGEN_DEVICE_FUNC
+    void resize(DenseIndex size, const NewDimensions& nbDimensions)
+    {
+      const DenseIndex currentSz = internal::array_prod(m_dimensions);
+      if(size != currentSz)
+      {
+        internal::conditional_managed_delete_auto<T,(Options_&DontAlign)==0,(Options_&AllocateUVM)>(m_data, currentSz);
+        if (size)
+          m_data = internal::conditional_managed_new_auto<T,(Options_&DontAlign)==0,(Options_&AllocateUVM)>(size);
+        else
+          m_data = 0;
+        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+      }
+      m_dimensions.resize(internal::array_size<NewDimensions>::value);
+      for (int i = 0; i < internal::array_size<NewDimensions>::value; ++i) {
+        m_dimensions[i] = nbDimensions[i];
+      }
+    }
+    EIGEN_DEVICE_FUNC void resize(DenseIndex size, const std::vector<DenseIndex>& nbDimensions)
+    {
+      const DenseIndex currentSz = internal::array_prod(m_dimensions);
+      if(size != currentSz)
+      {
+        internal::conditional_managed_delete_auto<T,(Options_&DontAlign)==0,(Options_&AllocateUVM)>(m_data, currentSz);
+        if (size)
+          m_data = internal::conditional_managed_new_auto<T,(Options_&DontAlign)==0,(Options_&AllocateUVM)>(size);
+        else
+          m_data = 0;
+        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+      }
+      m_dimensions = nbDimensions;
+    }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T *data() { return m_data; }
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const T *data() const { return m_data; }
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DenseIndex size() const { return m_dimensions.TotalSize(); }
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSORSTORAGE_H