unsupported/Eigen/CXX11/src/Tensor/TensorFixedSize.h

// 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_FIXED_SIZE_H
#define EIGEN_CXX11_TENSOR_TENSOR_FIXED_SIZE_H

// IWYU pragma: private
#include "./InternalHeaderCheck.h"

namespace Eigen {

/** \class TensorFixedSize
 * \ingroup CXX11_Tensor_Module
 *
 * \brief The fixed sized version of the tensor class.
 *
 * The fixed sized equivalent of
 * Eigen::Tensor<float, 3> t(3, 5, 7);
 * is
 * Eigen::TensorFixedSize<float, Sizes<3,5,7>> t;
 */

template <typename Scalar_, typename Dimensions_, int Options_, typename IndexType>
class TensorFixedSize : public TensorBase<TensorFixedSize<Scalar_, Dimensions_, Options_, IndexType> > {
 public:
  typedef TensorFixedSize<Scalar_, Dimensions_, Options_, IndexType> Self;
  typedef TensorBase<TensorFixedSize<Scalar_, Dimensions_, Options_, IndexType> > Base;
  typedef typename Eigen::internal::nested<Self>::type Nested;
  typedef typename internal::traits<Self>::StorageKind StorageKind;
  typedef typename internal::traits<Self>::Index Index;
  typedef Scalar_ Scalar;
  typedef typename NumTraits<Scalar>::Real RealScalar;
  typedef typename Base::CoeffReturnType CoeffReturnType;

  static constexpr int Options = Options_;
  static constexpr int Layout = Options_ & RowMajor ? RowMajor : ColMajor;

  enum {
    IsAligned = bool(EIGEN_MAX_ALIGN_BYTES > 0),
    PacketAccess = (internal::packet_traits<Scalar>::size > 1),
    BlockAccess = false,
    PreferBlockAccess = false,
    CoordAccess = true,
    RawAccess = true
  };

  //===- Tensor block evaluation strategy (see TensorBlock.h) -------------===//
  typedef internal::TensorBlockNotImplemented TensorBlock;
  //===--------------------------------------------------------------------===//

  typedef Dimensions_ Dimensions;
  static constexpr std::size_t NumIndices = Dimensions::count;

 protected:
  TensorStorage<Scalar, Dimensions, Options> m_storage;

 public:
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rank() const { return NumIndices; }
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index dimension(std::size_t n) const { return m_storage.dimensions()[n]; }
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions dimensions() const { return m_storage.dimensions(); }
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index size() const { return m_storage.size(); }
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar* data() { return m_storage.data(); }
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar* data() const { return m_storage.data(); }

  // This makes EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
  // work, because that uses base().coeffRef() - and we don't yet
  // implement a similar class hierarchy
  inline Self& base() { return *this; }
  inline const Self& base() const { return *this; }

  template <typename... IndexTypes>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(Index firstIndex, IndexTypes... otherIndices) const {
    // The number of indices used to access a tensor coefficient must be equal to the rank of the tensor.
    EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
    return coeff(array<Index, NumIndices>{{firstIndex, otherIndices...}});
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(const array<Index, NumIndices>& indices) const {
    eigen_internal_assert(checkIndexRange(indices));
    return m_storage.data()[linearizedIndex(indices)];
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(Index index) const {
    eigen_internal_assert(index >= 0 && index < size());
    return m_storage.data()[index];
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff() const {
    EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
    return m_storage.data()[0];
  }

  template <typename... IndexTypes>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index firstIndex, IndexTypes... otherIndices) {
    // The number of indices used to access a tensor coefficient must be equal to the rank of the tensor.
    EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
    return coeffRef(array<Index, NumIndices>{{firstIndex, otherIndices...}});
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(const array<Index, NumIndices>& indices) {
    eigen_internal_assert(checkIndexRange(indices));
    return m_storage.data()[linearizedIndex(indices)];
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
    eigen_internal_assert(index >= 0 && index < size());
    return m_storage.data()[index];
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef() {
    EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
    return m_storage.data()[0];
  }

  template <typename... IndexTypes>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& operator()(Index firstIndex, IndexTypes... otherIndices) const {
    // The number of indices used to access a tensor coefficient must be equal to the rank of the tensor.
    EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
    return this->operator()(array<Index, NumIndices>{{firstIndex, otherIndices...}});
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& operator()(const array<Index, NumIndices>& indices) const {
    eigen_assert(checkIndexRange(indices));
    return coeff(indices);
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& operator()(Index index) const {
    eigen_internal_assert(index >= 0 && index < size());
    return coeff(index);
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& operator()() const {
    EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
    return coeff();
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& operator[](Index index) const {
    // The bracket operator is only for vectors, use the parenthesis operator instead.
    EIGEN_STATIC_ASSERT(NumIndices == 1, YOU_MADE_A_PROGRAMMING_MISTAKE);
    return coeff(index);
  }

  template <typename... IndexTypes>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& operator()(Index firstIndex, IndexTypes... otherIndices) {
    // The number of indices used to access a tensor coefficient must be equal to the rank of the tensor.
    EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 1 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
    return operator()(array<Index, NumIndices>{{firstIndex, otherIndices...}});
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& operator()(const array<Index, NumIndices>& indices) {
    eigen_assert(checkIndexRange(indices));
    return coeffRef(indices);
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& operator()(Index index) {
    eigen_assert(index >= 0 && index < size());
    return coeffRef(index);
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& operator()() {
    EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
    return coeffRef();
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& operator[](Index index) {
    // The bracket operator is only for vectors, use the parenthesis operator instead
    EIGEN_STATIC_ASSERT(NumIndices == 1, YOU_MADE_A_PROGRAMMING_MISTAKE)
    return coeffRef(index);
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorFixedSize() : m_storage() {}

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorFixedSize(const Self& other) : Base(other), m_storage(other.m_storage) {}

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorFixedSize(Self&& other) : m_storage(other.m_storage) {}

  template <typename OtherDerived>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorFixedSize(const TensorBase<OtherDerived, ReadOnlyAccessors>& other) {
    typedef TensorAssignOp<TensorFixedSize, const OtherDerived> Assign;
    Assign assign(*this, other.derived());
    internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
  }
  template <typename OtherDerived>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorFixedSize(const TensorBase<OtherDerived, WriteAccessors>& other) {
    typedef TensorAssignOp<TensorFixedSize, const OtherDerived> Assign;
    Assign assign(*this, other.derived());
    internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
  }

  // FIXME: check that the dimensions of other match the dimensions of *this.
  // Unfortunately this isn't possible yet when the rhs is an expression.
  EIGEN_TENSOR_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(TensorFixedSize)

 protected:
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool checkIndexRange(const array<Index, NumIndices>& /*indices*/) const {
    using internal::array_apply_and_reduce;
    using internal::array_zip_and_reduce;
    using internal::greater_equal_zero_op;
    using internal::lesser_op;
    using internal::logical_and_op;

    return true;
    // check whether the indices are all >= 0
    /*       array_apply_and_reduce<logical_and_op, greater_equal_zero_op>(indices) &&
  // check whether the indices fit in the dimensions
  array_zip_and_reduce<logical_and_op, lesser_op>(indices, m_storage.dimensions());*/
  }

  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index linearizedIndex(const array<Index, NumIndices>& indices) const {
    if (Options & RowMajor) {
      return m_storage.dimensions().IndexOfRowMajor(indices);
    } else {
      return m_storage.dimensions().IndexOfColMajor(indices);
    }
  }
};

}  // end namespace Eigen

#endif  // EIGEN_CXX11_TENSOR_TENSOR_FIXED_SIZE_H