1 files changed, 0 insertions, 320 deletions
diff --git a/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h b/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
deleted file mode 100644
index 908bdc38ad..0000000000
--- a/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorMap.h
+++ /dev/null
@@ -1,320 +0,0 @@
-// 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_MAP_H
-#define EIGEN_CXX11_TENSOR_TENSOR_MAP_H
-
-namespace Eigen {
-
-/** \class TensorMap
-  * \ingroup CXX11_Tensor_Module
-  *
-  * \brief A tensor expression mapping an existing array of data.
-  *
-  */
-
-template<typename PlainObjectType, int Options_> class TensorMap : public TensorBase<TensorMap<PlainObjectType, Options_> >
-{
-  public:
-    typedef TensorMap<PlainObjectType, Options_> Self;
-    typedef typename PlainObjectType::Base Base;
-    typedef typename Eigen::internal::nested<Self>::type Nested;
-    typedef typename internal::traits<PlainObjectType>::StorageKind StorageKind;
-    typedef typename internal::traits<PlainObjectType>::Index Index;
-    typedef typename internal::traits<PlainObjectType>::Scalar Scalar;
-    typedef typename internal::packet_traits<Scalar>::type Packet;
-    typedef typename NumTraits<Scalar>::Real RealScalar;
-    typedef typename Base::CoeffReturnType CoeffReturnType;
-
-  /*    typedef typename internal::conditional<
-                         bool(internal::is_lvalue<PlainObjectType>::value),
-                         Scalar *,
-                         const Scalar *>::type
-                     PointerType;*/
-    typedef Scalar* PointerType;
-    typedef PointerType PointerArgType;
-
-    static const int Options = Options_;
-
-    static const Index NumIndices = PlainObjectType::NumIndices;
-    typedef typename PlainObjectType::Dimensions Dimensions;
-
-    enum {
-      IsAligned = ((int(Options_) & Aligned) == Aligned),
-      PacketAccess = (internal::packet_traits<Scalar>::size > 1),
-      BlockAccess = false,
-      Layout = PlainObjectType::Layout,
-      CoordAccess = true,
-    };
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr) : m_data(dataPtr), m_dimensions() {
-      // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
-      EIGEN_STATIC_ASSERT((0 == NumIndices || NumIndices == Dynamic), 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(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 || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
-    }
-#else
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension) : m_data(dataPtr), m_dimensions(firstDimension) {
-      // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
-      EIGEN_STATIC_ASSERT((1 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
-    }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2) : m_data(dataPtr), m_dimensions(dim1, dim2) {
-      EIGEN_STATIC_ASSERT(2 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
-    }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3) {
-      EIGEN_STATIC_ASSERT(3 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
-    }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3, Index dim4) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3, dim4) {
-      EIGEN_STATIC_ASSERT(4 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
-    }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3, Index dim4, Index dim5) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3, dim4, dim5) {
-      EIGEN_STATIC_ASSERT(5 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
-    }
-#endif
-
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, const array<Index, NumIndices>& dimensions)
-      : m_data(dataPtr), m_dimensions(dimensions)
-    { }
-
-    template <typename Dimensions>
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, const Dimensions& dimensions)
-      : m_data(dataPtr), m_dimensions(dimensions)
-    { }
-
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PlainObjectType& tensor)
-      : m_data(tensor.data()), m_dimensions(tensor.dimensions())
-    { }
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Index rank() const { return m_dimensions.rank(); }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Index dimension(Index n) const { return m_dimensions[n]; }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Index size() const { return m_dimensions.TotalSize(); }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar* data() { return m_data; }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE const Scalar* data() const { return m_data; }
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE const Scalar& operator()(const array<Index, NumIndices>& indices) const
-    {
-      //      eigen_assert(checkIndexRange(indices));
-      if (PlainObjectType::Options&RowMajor) {
-        const Index index = m_dimensions.IndexOfRowMajor(indices);
-        return m_data[index];
-      } else {
-        const Index index = m_dimensions.IndexOfColMajor(indices);
-        return m_data[index];
-      }
-    }
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE const Scalar& operator()() const
-    {
-      EIGEN_STATIC_ASSERT(NumIndices == 0 || NumIndices == Dynamic, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor.");
-      eigen_assert(rank() == 0);
-      return m_data[0];
-    }
-
-#ifdef EIGEN_HAS_VARIADIC_TEMPLATES
-    template<typename... IndexTypes> EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE const Scalar& operator()(Index firstIndex, IndexTypes... otherIndices) const
-    {
-      static_assert(sizeof...(otherIndices) + 1 == NumIndices, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor.");
-      if (PlainObjectType::Options&RowMajor) {
-        const Index index = m_dimensions.IndexOfRowMajor(array<Index, NumIndices>{{firstIndex, otherIndices...}});
-        return m_data[index];
-      } else {
-        const Index index = m_dimensions.IndexOfColMajor(array<Index, NumIndices>{{firstIndex, otherIndices...}});
-        return m_data[index];
-      }
-    }
-#else
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE const Scalar& operator()(Index index) const
-    {
-      eigen_internal_assert(index >= 0 && index < size());
-      return m_data[index];
-    }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1) const
-    {
-      if (PlainObjectType::Options&RowMajor) {
-        const Index index = i1 + i0 * m_dimensions[0];
-        return m_data[index];
-      } else {
-        const Index index = i0 + i1 * m_dimensions[0];
-        return m_data[index];
-      }
-    }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2) const
-    {
-      if (PlainObjectType::Options&RowMajor) {
-         const Index index = i2 + m_dimensions[1] * (i1 + m_dimensions[0] * i0);
-         return m_data[index];
-      } else {
-         const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * i2);
-        return m_data[index];
-      }
-    }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3) const
-    {
-      if (PlainObjectType::Options&RowMajor) {
-        const Index index = i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0));
-        return m_data[index];
-      } else {
-        const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * i3));
-        return m_data[index];
-      }
-    }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4) const
-    {
-      if (PlainObjectType::Options&RowMajor) {
-        const Index index = i4 + m_dimensions[4] * (i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0)));
-        return m_data[index];
-      } else {
-        const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * (i3 + m_dimensions[3] * i4)));
-        return m_data[index];
-      }
-    }
-#endif
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(const array<Index, NumIndices>& indices)
-    {
-      //      eigen_assert(checkIndexRange(indices));
-      if (PlainObjectType::Options&RowMajor) {
-        const Index index = m_dimensions.IndexOfRowMajor(indices);
-        return m_data[index];
-      } else {
-        const Index index = m_dimensions.IndexOfColMajor(indices);
-        return m_data[index];
-      }
-    }
-
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()()
-    {
-      static_assert(NumIndices == 0 || NumIndices == Dynamic, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor.");
-      eigen_internal_assert(rank() == 0);
-      return m_data[0];
-    }
-
-#ifdef EIGEN_HAS_VARIADIC_TEMPLATES
-    template<typename... IndexTypes> EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(Index firstIndex, IndexTypes... otherIndices)
-    {
-      static_assert(sizeof...(otherIndices) + 1 == NumIndices || NumIndices == Dynamic, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor.");
-      const std::size_t NumDims = sizeof...(otherIndices) + 1;
-      if (PlainObjectType::Options&RowMajor) {
-        const array<Index, NumDims> dims = {firstIndex, otherIndices...};
-        const Index index = m_dimensions.IndexOfRowMajor(dims);
-        return m_data[index];
-      } else {
-        const array<Index, NumDims> dims = {firstIndex, otherIndices...};
-        const Index index = m_dimensions.IndexOfColMajor(dims);
-        return m_data[index];
-      }
-    }
-#else
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(Index index)
-    {
-      eigen_internal_assert(index >= 0 && index < size());
-      return m_data[index];
-    }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1)
-    {
-       if (PlainObjectType::Options&RowMajor) {
-         const Index index = i1 + i0 * m_dimensions[0];
-        return m_data[index];
-      } else {
-        const Index index = i0 + i1 * m_dimensions[0];
-        return m_data[index];
-      }
-    }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2)
-    {
-       if (PlainObjectType::Options&RowMajor) {
-         const Index index = i2 + m_dimensions[1] * (i1 + m_dimensions[0] * i0);
-        return m_data[index];
-      } else {
-         const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * i2);
-        return m_data[index];
-      }
-    }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3)
-    {
-      if (PlainObjectType::Options&RowMajor) {
-        const Index index = i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0));
-        return m_data[index];
-      } else {
-        const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * i3));
-        return m_data[index];
-      }
-    }
-    EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4)
-    {
-      if (PlainObjectType::Options&RowMajor) {
-        const Index index = i4 + m_dimensions[4] * (i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0)));
-        return m_data[index];
-      } else {
-        const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * (i3 + m_dimensions[3] * i4)));
-        return m_data[index];
-      }
-    }
-#endif
-
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Self& operator=(const Self& other)
-    {
-      typedef TensorAssignOp<Self, const Self> Assign;
-      Assign assign(*this, other);
-      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
-      return *this;
-    }
-
-    template<typename OtherDerived>
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    Self& operator=(const OtherDerived& other)
-    {
-      typedef TensorAssignOp<Self, const OtherDerived> Assign;
-      Assign assign(*this, other);
-      internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
-      return *this;
-    }
-
-  private:
-    Scalar* m_data;
-    Dimensions m_dimensions;
-};
-
-} // end namespace Eigen
-
-#endif // EIGEN_CXX11_TENSOR_TENSOR_MAP_H