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diff --git a/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorTrueIndices.h b/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorTrueIndices.h
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+++ b/third_party/eigen3/unsupported/Eigen/CXX11/src/Tensor/TensorTrueIndices.h
@@ -0,0 +1,250 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2015 Eugene Brevdo <ebrevdo@google.com>
+//                    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_TRUE_INDICES_H
+#define EIGEN_CXX11_TENSOR_TENSOR_TRUE_INDICES_H
+namespace Eigen {
+
+/** \class TensorTrueIndices
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor provide indices of true values class.
+  *
+  */
+namespace internal {
+template<typename XprType>
+struct traits<TensorTrueIndicesOp<XprType> > : public traits<XprType>
+{
+  typedef DenseIndex Scalar;
+  typedef DenseIndex CoeffReturnType;
+  typedef traits<XprType> XprTraits;
+  //typedef typename packet_traits<Scalar>::type Packet;
+  typedef typename XprTraits::StorageKind StorageKind;
+  typedef typename XprTraits::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+  static const int NumDimensions = 2; // XprTraits::NumDimensions;
+  static const int Layout = XprTraits::Layout;
+};
+
+template<typename XprType>
+struct eval<TensorTrueIndicesOp<XprType>, Eigen::Dense>
+{
+  typedef const TensorTrueIndicesOp<XprType>& type;
+};
+
+template<typename XprType>
+struct nested<TensorTrueIndicesOp<XprType>, 1,
+            typename eval<TensorTrueIndicesOp<XprType> >::type>
+{
+  typedef TensorTrueIndicesOp<XprType> type;
+};
+
+}  // end namespace internal
+
+template<typename XprType>
+class TensorTrueIndicesOp : public TensorBase<TensorTrueIndicesOp<XprType>, WriteAccessors>
+{
+  public:
+    typedef typename Eigen::internal::traits<TensorTrueIndicesOp>::Scalar Scalar;
+    //typedef typename Eigen::internal::traits<TensorTrueIndicesOp>::Packet Packet;
+    typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+    typedef typename Eigen::internal::traits<TensorTrueIndicesOp>::CoeffReturnType CoeffReturnType;
+    typedef typename internal::packet_traits<CoeffReturnType>::type PacketReturnType;
+    typedef typename Eigen::internal::nested<TensorTrueIndicesOp>::type Nested;
+    typedef typename Eigen::internal::traits<TensorTrueIndicesOp>::StorageKind
+                                                                    StorageKind;
+    typedef typename Eigen::internal::traits<TensorTrueIndicesOp>::Index Index;
+
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorTrueIndicesOp(
+        const XprType& expr, const CoeffReturnType& not_found = -1)
+        : m_xpr(expr), m_not_found(not_found) {
+    }
+
+    EIGEN_DEVICE_FUNC
+    const CoeffReturnType& not_found() const { return m_not_found; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorTrueIndicesOp& operator = (const TensorTrueIndicesOp& other)
+    {
+      typedef TensorAssignOp<TensorTrueIndicesOp, const TensorTrueIndicesOp> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(
+          assign, DefaultDevice());
+      return *this;
+    }
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorTrueIndicesOp& operator = (const OtherDerived& other)
+    {
+      typedef TensorAssignOp<TensorTrueIndicesOp, const OtherDerived> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice>::run(
+          assign, DefaultDevice());
+      return *this;
+    }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    CoeffReturnType m_not_found;
+};
+
+// Eval as rvalue
+template<typename ArgType, typename Device>
+struct TensorEvaluator<const TensorTrueIndicesOp<ArgType>, Device>
+{
+  typedef TensorTrueIndicesOp<ArgType> XprType;
+  typedef typename XprType::Index InputIndex;
+  typedef typename XprType::Index Index;
+  static const int NumDims = 2;
+  typedef DSizes<Index, 2> Dimensions;
+  typedef typename TensorEvaluator<ArgType, Device>::Dimensions InputDimensions;
+  static const int NumInputDims = internal::array_size<InputDimensions>::value;
+
+  enum {
+    IsAligned = true,
+    PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
+    BlockAccess = false,
+    Layout = TensorEvaluator<ArgType, Device>::Layout,
+    CoordAccess = false,  // to be implemented
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op,
+                                                        const Device& device)
+      : m_impl(op.expression(), device), m_not_found(op.not_found())
+  {
+    // Store original dimensions
+    m_orig_dimensions = m_impl.dimensions();
+
+    // Calculate output dimensions
+    m_dimensions[0] = m_orig_dimensions.TotalSize();
+    m_dimensions[1] = NumInputDims;
+
+    // Calculate strides of input expression
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      m_strides[0] = 1;
+      for (int i = 1; i < NumInputDims; ++i) {
+        m_strides[i] = m_strides[i-1] * m_orig_dimensions[i-1];
+      }
+    } else {
+      m_strides[NumInputDims-1] = 1;
+      for (int i = NumInputDims - 2; i >= 0; --i) {
+        m_strides[i] = m_strides[i+1] * m_orig_dimensions[i+1];
+      }
+    }
+  }
+
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename XprType::PacketReturnType PacketReturnType;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  const Dimensions& dimensions() const { return m_dimensions; }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE InputIndex origIndices(
+      Index index) const {
+    eigen_assert(index < dimensions().TotalSize());
+    Index inputIndex = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      inputIndex = index % m_dimensions[0];
+    } else {
+      inputIndex = index / m_dimensions[1];
+    }
+    return inputIndex;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE int whichDim(
+      Index index) const {
+    eigen_assert(index < dimensions().TotalSize());
+    int inputDim = 0;
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      inputDim = index / m_dimensions[0];
+    } else {
+      inputDim = index % m_dimensions[1];
+    }
+    return inputDim;
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType origDim(
+      int dim, InputIndex index) const {
+    eigen_assert(index < m_orig_dimensions.TotalSize());
+    eigen_assert(dim > -1 && dim < m_orig_dimensions.size());
+    if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
+      for (int i = NumInputDims - 1; i > 0; --i) {
+        Index idx = index / m_strides[i];
+        if (i == dim) return idx;  // Found our dimension
+        index -= idx * m_strides[i];
+      }
+      return index;
+    } else {
+      for (int i = 0; i < NumInputDims - 1; ++i) {
+        Index idx = index / m_strides[i];
+        if (i == dim) return idx;  // Found our dimension
+        index -= idx * m_strides[i];
+      }
+      return index;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(
+      Index index) const  {
+    InputIndex orig_index = origIndices(index);
+    if (m_impl.coeff(orig_index))
+      return origDim(whichDim(index), orig_index);
+    else {
+      return m_not_found;
+    }
+  }
+
+  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+  PacketReturnType packet(Index index) const
+  {
+    const int packetSize = internal::unpacket_traits<PacketReturnType>::size;
+    EIGEN_STATIC_ASSERT(packetSize > 1, YOU_MADE_A_PROGRAMMING_MISTAKE)
+    eigen_assert(index+packetSize-1 < dimensions().TotalSize());
+
+    // TODO(ndjaitly): write a better packing routine that uses
+    // local structure.
+    EIGEN_ALIGN_DEFAULT typename internal::remove_const<CoeffReturnType>::type
+                                                            values[packetSize];
+    for (int i = 0; i < packetSize; ++i) {
+      values[i] = coeff(index+i);
+    }
+    PacketReturnType rslt = internal::pload<PacketReturnType>(values);
+    return rslt;
+  }
+
+  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
+
+ protected:
+  InputDimensions m_orig_dimensions;
+  Dimensions m_dimensions;
+  TensorEvaluator<ArgType, Device> m_impl;
+  array<Index, NumInputDims> m_strides;
+  CoeffReturnType m_not_found;
+};
+
+}  // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_TRUE_INDICES_H