TensorRef.h

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// 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_REF_H
#define EIGEN_CXX11_TENSOR_TENSOR_REF_H
 
// IWYU pragma: private
#include "./InternalHeaderCheck.h"
 
namespace Eigen {
 
namespace internal {
 
template <typename Dimensions, typename Scalar>
class TensorLazyBaseEvaluator {
 public:
  TensorLazyBaseEvaluator() : m_refcount(0) {}
  virtual ~TensorLazyBaseEvaluator() {}
 
  EIGEN_DEVICE_FUNC virtual const Dimensions& dimensions() const = 0;
  EIGEN_DEVICE_FUNC virtual const Scalar* data() const = 0;
 
  EIGEN_DEVICE_FUNC virtual const Scalar coeff(DenseIndex index) const = 0;
  EIGEN_DEVICE_FUNC virtual Scalar& coeffRef(DenseIndex index) = 0;
 
  void incrRefCount() { ++m_refcount; }
  void decrRefCount() { --m_refcount; }
  int refCount() const { return m_refcount; }
 
 private:
  // No copy, no assignment;
  TensorLazyBaseEvaluator(const TensorLazyBaseEvaluator& other);
  TensorLazyBaseEvaluator& operator=(const TensorLazyBaseEvaluator& other);
 
  int m_refcount;
};
 
template <typename Dimensions, typename Expr, typename Device>
class TensorLazyEvaluatorReadOnly
    : public TensorLazyBaseEvaluator<Dimensions, typename TensorEvaluator<Expr, Device>::Scalar> {
 public:
  //  typedef typename TensorEvaluator<Expr, Device>::Dimensions Dimensions;
  typedef typename TensorEvaluator<Expr, Device>::Scalar Scalar;
  typedef StorageMemory<Scalar, Device> Storage;
  typedef typename Storage::Type EvaluatorPointerType;
  typedef TensorEvaluator<Expr, Device> EvalType;
 
  TensorLazyEvaluatorReadOnly(const Expr& expr, const Device& device) : m_impl(expr, device), m_dummy(Scalar(0)) {
    m_dims = m_impl.dimensions();
    m_impl.evalSubExprsIfNeeded(NULL);
  }
  virtual ~TensorLazyEvaluatorReadOnly() { m_impl.cleanup(); }
 
  EIGEN_DEVICE_FUNC virtual const Dimensions& dimensions() const { return m_dims; }
  EIGEN_DEVICE_FUNC virtual const Scalar* data() const { return m_impl.data(); }
 
  EIGEN_DEVICE_FUNC virtual const Scalar coeff(DenseIndex index) const { return m_impl.coeff(index); }
  EIGEN_DEVICE_FUNC virtual Scalar& coeffRef(DenseIndex /*index*/) {
    eigen_assert(false && "can't reference the coefficient of a rvalue");
    return m_dummy;
  };
 
 protected:
  TensorEvaluator<Expr, Device> m_impl;
  Dimensions m_dims;
  Scalar m_dummy;
};
 
template <typename Dimensions, typename Expr, typename Device>
class TensorLazyEvaluatorWritable : public TensorLazyEvaluatorReadOnly<Dimensions, Expr, Device> {
 public:
  typedef TensorLazyEvaluatorReadOnly<Dimensions, Expr, Device> Base;
  typedef typename Base::Scalar Scalar;
  typedef StorageMemory<Scalar, Device> Storage;
  typedef typename Storage::Type EvaluatorPointerType;
 
  TensorLazyEvaluatorWritable(const Expr& expr, const Device& device) : Base(expr, device) {}
  virtual ~TensorLazyEvaluatorWritable() {}
 
  EIGEN_DEVICE_FUNC virtual Scalar& coeffRef(DenseIndex index) { return this->m_impl.coeffRef(index); }
};
 
template <typename Dimensions, typename Expr, typename Device>
class TensorLazyEvaluator : public std::conditional_t<bool(internal::is_lvalue<Expr>::value),
                                                      TensorLazyEvaluatorWritable<Dimensions, Expr, Device>,
                                                      TensorLazyEvaluatorReadOnly<Dimensions, const Expr, Device> > {
 public:
  typedef std::conditional_t<bool(internal::is_lvalue<Expr>::value),
                             TensorLazyEvaluatorWritable<Dimensions, Expr, Device>,
                             TensorLazyEvaluatorReadOnly<Dimensions, const Expr, Device> >
      Base;
  typedef typename Base::Scalar Scalar;
 
  TensorLazyEvaluator(const Expr& expr, const Device& device) : Base(expr, device) {}
  virtual ~TensorLazyEvaluator() {}
};
 
}  // namespace internal
 
template <typename PlainObjectType>
class TensorRef : public TensorBase<TensorRef<PlainObjectType> > {
 public:
  typedef TensorRef<PlainObjectType> 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 NumTraits<Scalar>::Real RealScalar;
  typedef typename Base::CoeffReturnType CoeffReturnType;
  typedef Scalar* PointerType;
  typedef PointerType PointerArgType;
 
  static constexpr Index NumIndices = PlainObjectType::NumIndices;
  typedef typename PlainObjectType::Dimensions Dimensions;
 
  static constexpr int Layout = PlainObjectType::Layout;
  enum {
    IsAligned = false,
    PacketAccess = false,
    BlockAccess = false,
    PreferBlockAccess = false,
    CoordAccess = false,  // to be implemented
    RawAccess = false
  };
 
  //===- Tensor block evaluation strategy (see TensorBlock.h) -----------===//
  typedef internal::TensorBlockNotImplemented TensorBlock;
  //===------------------------------------------------------------------===//
 
  EIGEN_STRONG_INLINE TensorRef() : m_evaluator(NULL) {}
 
  template <typename Expression>
  EIGEN_STRONG_INLINE TensorRef(const Expression& expr)
      : m_evaluator(new internal::TensorLazyEvaluator<Dimensions, Expression, DefaultDevice>(expr, DefaultDevice())) {
    m_evaluator->incrRefCount();
  }
 
  template <typename Expression>
  EIGEN_STRONG_INLINE TensorRef& operator=(const Expression& expr) {
    unrefEvaluator();
    m_evaluator = new internal::TensorLazyEvaluator<Dimensions, Expression, DefaultDevice>(expr, DefaultDevice());
    m_evaluator->incrRefCount();
    return *this;
  }
 
  ~TensorRef() { unrefEvaluator(); }
 
  TensorRef(const TensorRef& other) : TensorBase<TensorRef<PlainObjectType> >(other), m_evaluator(other.m_evaluator) {
    eigen_assert(m_evaluator->refCount() > 0);
    m_evaluator->incrRefCount();
  }
 
  TensorRef& operator=(const TensorRef& other) {
    if (this != &other) {
      unrefEvaluator();
      m_evaluator = other.m_evaluator;
      eigen_assert(m_evaluator->refCount() > 0);
      m_evaluator->incrRefCount();
    }
    return *this;
  }
 
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rank() const { return m_evaluator->dimensions().size(); }
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index dimension(Index n) const { return m_evaluator->dimensions()[n]; }
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_evaluator->dimensions(); }
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index size() const { return m_evaluator->dimensions().TotalSize(); }
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar* data() const { return m_evaluator->data(); }
 
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(Index index) const { return m_evaluator->coeff(index); }
 
  template <typename... IndexTypes>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator()(Index firstIndex, IndexTypes... otherIndices) const {
    const std::size_t num_indices = (sizeof...(otherIndices) + 1);
    const array<Index, num_indices> indices{{firstIndex, otherIndices...}};
    return coeff(indices);
  }
  template <typename... IndexTypes>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index firstIndex, IndexTypes... otherIndices) {
    const std::size_t num_indices = (sizeof...(otherIndices) + 1);
    const array<Index, num_indices> indices{{firstIndex, otherIndices...}};
    return coeffRef(indices);
  }
 
  template <std::size_t NumIndices>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(const array<Index, NumIndices>& indices) const {
    const Dimensions& dims = this->dimensions();
    Index index = 0;
    if (PlainObjectType::Options & RowMajor) {
      index += indices[0];
      for (size_t i = 1; i < NumIndices; ++i) {
        index = index * dims[i] + indices[i];
      }
    } else {
      index += indices[NumIndices - 1];
      for (int i = NumIndices - 2; i >= 0; --i) {
        index = index * dims[i] + indices[i];
      }
    }
    return m_evaluator->coeff(index);
  }
  template <std::size_t NumIndices>
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(const array<Index, NumIndices>& indices) {
    const Dimensions& dims = this->dimensions();
    Index index = 0;
    if (PlainObjectType::Options & RowMajor) {
      index += indices[0];
      for (size_t i = 1; i < NumIndices; ++i) {
        index = index * dims[i] + indices[i];
      }
    } else {
      index += indices[NumIndices - 1];
      for (int i = NumIndices - 2; i >= 0; --i) {
        index = index * dims[i] + indices[i];
      }
    }
    return m_evaluator->coeffRef(index);
  }
 
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index index) const { return m_evaluator->coeff(index); }
 
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { return m_evaluator->coeffRef(index); }
 
 private:
  EIGEN_STRONG_INLINE void unrefEvaluator() {
    if (m_evaluator) {
      m_evaluator->decrRefCount();
      if (m_evaluator->refCount() == 0) {
        delete m_evaluator;
      }
    }
  }
 
  internal::TensorLazyBaseEvaluator<Dimensions, Scalar>* m_evaluator;
};
 
// evaluator for rvalues
template <typename Derived, typename Device>
struct TensorEvaluator<const TensorRef<Derived>, Device> {
  typedef typename Derived::Index Index;
  typedef typename Derived::Scalar Scalar;
  typedef typename Derived::Scalar CoeffReturnType;
  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
  typedef typename Derived::Dimensions Dimensions;
  typedef StorageMemory<CoeffReturnType, Device> Storage;
  typedef typename Storage::Type EvaluatorPointerType;
 
  static constexpr int Layout = TensorRef<Derived>::Layout;
  enum {
    IsAligned = false,
    PacketAccess = false,
    BlockAccess = false,
    PreferBlockAccess = false,
    CoordAccess = false,  // to be implemented
    RawAccess = false
  };
 
  //===- Tensor block evaluation strategy (see TensorBlock.h) -------------===//
  typedef internal::TensorBlockNotImplemented TensorBlock;
  //===--------------------------------------------------------------------===//
 
  EIGEN_STRONG_INLINE TensorEvaluator(const TensorRef<Derived>& m, const Device&) : m_ref(m) {}
 
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_ref.dimensions(); }
 
  EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType) { return true; }
 
  EIGEN_STRONG_INLINE void cleanup() {}
 
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { return m_ref.coeff(index); }
 
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { return m_ref.coeffRef(index); }
 
  EIGEN_DEVICE_FUNC const Scalar* data() const { return m_ref.data(); }
 
 protected:
  TensorRef<Derived> m_ref;
};
 
// evaluator for lvalues
template <typename Derived, typename Device>
struct TensorEvaluator<TensorRef<Derived>, Device> : public TensorEvaluator<const TensorRef<Derived>, Device> {
  typedef typename Derived::Index Index;
  typedef typename Derived::Scalar Scalar;
  typedef typename Derived::Scalar CoeffReturnType;
  typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
  typedef typename Derived::Dimensions Dimensions;
 
  typedef TensorEvaluator<const TensorRef<Derived>, Device> Base;
 
  enum { IsAligned = false, PacketAccess = false, BlockAccess = false, PreferBlockAccess = false, RawAccess = false };
 
  //===- Tensor block evaluation strategy (see TensorBlock.h) -------------===//
  typedef internal::TensorBlockNotImplemented TensorBlock;
  //===--------------------------------------------------------------------===//
 
  EIGEN_STRONG_INLINE TensorEvaluator(TensorRef<Derived>& m, const Device& d) : Base(m, d) {}
 
  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { return this->m_ref.coeffRef(index); }
};
 
}  // end namespace Eigen
 
#endif  // EIGEN_CXX11_TENSOR_TENSOR_REF_H