Added support for padding, stridding, and shuffling

1 files changed, 168 insertions, 0 deletions

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h b/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h
new file mode 100644
index 000000000..4dfc99203
--- /dev/null
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorShuffling.h
@@ -0,0 +1,168 @@
+// 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_SHUFFLING_H
+#define EIGEN_CXX11_TENSOR_TENSOR_SHUFFLING_H
+
+namespace Eigen {
+
+/** \class TensorShuffling
+  * \ingroup CXX11_Tensor_Module
+  *
+  * \brief Tensor shuffling class.
+  *
+  *
+  */
+namespace internal {
+template<typename Shuffle, typename XprType>
+struct traits<TensorShufflingOp<Shuffle, XprType> > : public traits<XprType>
+{
+  typedef typename XprType::Scalar Scalar;
+  typedef typename internal::packet_traits<Scalar>::type Packet;
+  typedef typename traits<XprType>::StorageKind StorageKind;
+  typedef typename traits<XprType>::Index Index;
+  typedef typename XprType::Nested Nested;
+  typedef typename remove_reference<Nested>::type _Nested;
+};
+
+template<typename Shuffle, typename XprType>
+struct eval<TensorShufflingOp<Shuffle, XprType>, Eigen::Dense>
+{
+  typedef const TensorShufflingOp<Shuffle, XprType>& type;
+};
+
+template<typename Shuffle, typename XprType>
+struct nested<TensorShufflingOp<Shuffle, XprType>, 1, typename eval<TensorShufflingOp<Shuffle, XprType> >::type>
+{
+  typedef TensorShufflingOp<Shuffle, XprType> type;
+};
+
+}  // end namespace internal
+
+
+
+template<typename Shuffle, typename XprType>
+class TensorShufflingOp : public TensorBase<TensorShufflingOp<Shuffle, XprType>, WriteAccessors>
+{
+  public:
+  typedef typename Eigen::internal::traits<TensorShufflingOp>::Scalar Scalar;
+  typedef typename Eigen::internal::traits<TensorShufflingOp>::Packet Packet;
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename XprType::PacketReturnType PacketReturnType;
+  typedef typename Eigen::internal::nested<TensorShufflingOp>::type Nested;
+  typedef typename Eigen::internal::traits<TensorShufflingOp>::StorageKind StorageKind;
+  typedef typename Eigen::internal::traits<TensorShufflingOp>::Index Index;
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorShufflingOp(const XprType& expr, const Shuffle& shuffle)
+      : m_xpr(expr), m_shuffle(shuffle) {}
+
+    EIGEN_DEVICE_FUNC
+    const Shuffle& shuffle() const { return m_shuffle; }
+
+    EIGEN_DEVICE_FUNC
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    expression() const { return m_xpr; }
+
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    EIGEN_STRONG_INLINE TensorShufflingOp& operator = (const OtherDerived& other)
+    {
+      typedef TensorAssignOp<TensorShufflingOp, const OtherDerived> Assign;
+      Assign assign(*this, other);
+      internal::TensorExecutor<const Assign, DefaultDevice, false>::run(assign, DefaultDevice());
+      return *this;
+    }
+
+  protected:
+    typename XprType::Nested m_xpr;
+    const Shuffle m_shuffle;
+};
+
+
+// Eval as rvalue
+template<typename Shuffle, typename ArgType, typename Device>
+struct TensorEvaluator<const TensorShufflingOp<Shuffle, ArgType>, Device>
+{
+  typedef TensorShufflingOp<Shuffle, ArgType> XprType;
+  typedef typename XprType::Index Index;
+  static const int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
+  typedef DSizes<Index, NumDims> Dimensions;
+
+  enum {
+    IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/false,
+    PacketAccess = /*TensorEvaluator<ArgType, Device>::PacketAccess*/false,
+  };
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
+      : m_impl(op.expression(), device), m_shuffle(op.shuffle())
+  {
+    const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
+    for (int i = 0; i < NumDims; ++i) {
+      m_dimensions[i] = input_dims[m_shuffle[i]];
+    }
+
+    for (int i = 0; i < NumDims; ++i) {
+      if (i > 0) {
+        m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1];
+        m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1];
+      } else {
+        m_inputStrides[0] = 1;
+        m_outputStrides[0] = 1;
+      }
+    }
+  }
+
+  //  typedef typename XprType::Index Index;
+  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* data) {
+    m_impl.evalSubExprsIfNeeded(NULL);
+    return true;
+  }
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
+    m_impl.cleanup();
+  }
+
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+  {
+    Index inputIndex = 0;
+    for (int i = NumDims - 1; i > 0; --i) {
+      const Index idx = index / m_outputStrides[i];
+      inputIndex += idx * m_inputStrides[m_shuffle[i]];
+      index -= idx * m_outputStrides[i];
+    }
+    inputIndex += index * m_inputStrides[m_shuffle[0]];
+    return m_impl.coeff(inputIndex);
+  }
+
+  /*  template<int LoadMode>
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+  {
+    return m_impl.template packet<LoadMode>(index);
+    }*/
+
+  Scalar* data() const { return NULL; }
+
+ protected:
+  Dimensions m_dimensions;
+  Shuffle m_shuffle;
+  array<Index, NumDims> m_outputStrides;
+  array<Index, NumDims> m_inputStrides;
+  TensorEvaluator<ArgType, Device> m_impl;
+};
+
+
+} // end namespace Eigen
+
+#endif // EIGEN_CXX11_TENSOR_TENSOR_SHUFFLING_H