TensorInflation.h
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1 // This file is part of Eigen, a lightweight C++ template library
2 // for linear algebra.
3 //
4 // Copyright (C) 2015 Ke Yang <yangke@gmail.com>
5 //
6 // This Source Code Form is subject to the terms of the Mozilla
7 // Public License v. 2.0. If a copy of the MPL was not distributed
8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9 
10 #ifndef EIGEN_CXX11_TENSOR_TENSOR_INFLATION_H
11 #define EIGEN_CXX11_TENSOR_TENSOR_INFLATION_H
12 
13 namespace Eigen {
14 
22 namespace internal {
23 template<typename Strides, typename XprType>
24 struct traits<TensorInflationOp<Strides, XprType> > : public traits<XprType>
25 {
26  typedef typename XprType::Scalar Scalar;
28  typedef typename XprTraits::StorageKind StorageKind;
29  typedef typename XprTraits::Index Index;
30  typedef typename XprType::Nested Nested;
32  static const int NumDimensions = XprTraits::NumDimensions;
33  static const int Layout = XprTraits::Layout;
34 };
35 
36 template<typename Strides, typename XprType>
37 struct eval<TensorInflationOp<Strides, XprType>, Eigen::Dense>
38 {
40 };
41 
42 template<typename Strides, typename XprType>
43 struct nested<TensorInflationOp<Strides, XprType>, 1, typename eval<TensorInflationOp<Strides, XprType> >::type>
44 {
46 };
47 
48 } // end namespace internal
49 
50 template<typename Strides, typename XprType>
51 class TensorInflationOp : public TensorBase<TensorInflationOp<Strides, XprType>, ReadOnlyAccessors>
52 {
53  public:
56  typedef typename XprType::CoeffReturnType CoeffReturnType;
60 
61  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorInflationOp(const XprType& expr, const Strides& strides)
62  : m_xpr(expr), m_strides(strides) {}
63 
64  EIGEN_DEVICE_FUNC
65  const Strides& strides() const { return m_strides; }
66 
67  EIGEN_DEVICE_FUNC
69  expression() const { return m_xpr; }
70 
71  protected:
72  typename XprType::Nested m_xpr;
73  const Strides m_strides;
74 };
75 
76 // Eval as rvalue
77 template<typename Strides, typename ArgType, typename Device>
78 struct TensorEvaluator<const TensorInflationOp<Strides, ArgType>, Device>
79 {
81  typedef typename XprType::Index Index;
84  typedef typename XprType::Scalar Scalar;
88 
89  enum {
90  IsAligned = /*TensorEvaluator<ArgType, Device>::IsAligned*/ false,
92  BlockAccess = false,
94  CoordAccess = false, // to be implemented
95  RawAccess = false
96  };
97 
98  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
99  : m_impl(op.expression(), device), m_strides(op.strides())
100  {
101  m_dimensions = m_impl.dimensions();
102  // Expand each dimension to the inflated dimension.
103  for (int i = 0; i < NumDims; ++i) {
104  m_dimensions[i] = (m_dimensions[i] - 1) * op.strides()[i] + 1;
105  }
106 
107  // Remember the strides for fast division.
108  for (int i = 0; i < NumDims; ++i) {
109  m_fastStrides[i] = internal::TensorIntDivisor<Index>(m_strides[i]);
110  }
111 
112  const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
113  if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
114  m_outputStrides[0] = 1;
115  m_inputStrides[0] = 1;
116  for (int i = 1; i < NumDims; ++i) {
117  m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1];
118  m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1];
119  }
120  } else { // RowMajor
121  m_outputStrides[NumDims-1] = 1;
122  m_inputStrides[NumDims-1] = 1;
123  for (int i = NumDims - 2; i >= 0; --i) {
124  m_outputStrides[i] = m_outputStrides[i+1] * m_dimensions[i+1];
125  m_inputStrides[i] = m_inputStrides[i+1] * input_dims[i+1];
126  }
127  }
128  }
129 
130  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
131 
132  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
133  m_impl.evalSubExprsIfNeeded(NULL);
134  return true;
135  }
136  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
137  m_impl.cleanup();
138  }
139 
140  // Computes the input index given the output index. Returns true if the output
141  // index doesn't fall into a hole.
142  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool getInputIndex(Index index, Index* inputIndex) const
143  {
144  eigen_assert(index < dimensions().TotalSize());
145  *inputIndex = 0;
146  if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
147  for (int i = NumDims - 1; i > 0; --i) {
148  const Index idx = index / m_outputStrides[i];
149  if (idx != idx / m_fastStrides[i] * m_strides[i]) {
150  return false;
151  }
152  *inputIndex += idx / m_strides[i] * m_inputStrides[i];
153  index -= idx * m_outputStrides[i];
154  }
155  if (index != index / m_fastStrides[0] * m_strides[0]) {
156  return false;
157  }
158  *inputIndex += index / m_strides[0];
159  return true;
160  } else {
161  for (int i = 0; i < NumDims - 1; ++i) {
162  const Index idx = index / m_outputStrides[i];
163  if (idx != idx / m_fastStrides[i] * m_strides[i]) {
164  return false;
165  }
166  *inputIndex += idx / m_strides[i] * m_inputStrides[i];
167  index -= idx * m_outputStrides[i];
168  }
169  if (index != index / m_fastStrides[NumDims-1] * m_strides[NumDims-1]) {
170  return false;
171  }
172  *inputIndex += index / m_strides[NumDims - 1];
173  }
174  return true;
175  }
176 
177  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
178  {
179  Index inputIndex = 0;
180  if (getInputIndex(index, &inputIndex)) {
181  return m_impl.coeff(inputIndex);
182  } else {
183  return Scalar(0);
184  }
185  }
186 
187  // TODO(yangke): optimize this function so that we can detect and produce
188  // all-zero packets
189  template<int LoadMode>
190  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
191  {
192  EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
193  eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
194 
196  for (int i = 0; i < PacketSize; ++i) {
197  values[i] = coeff(index+i);
198  }
199  PacketReturnType rslt = internal::pload<PacketReturnType>(values);
200  return rslt;
201  }
202 
203  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
204  const double compute_cost = NumDims * (3 * TensorOpCost::DivCost<Index>() +
205  3 * TensorOpCost::MulCost<Index>() +
206  2 * TensorOpCost::AddCost<Index>());
207  const double input_size = m_impl.dimensions().TotalSize();
208  const double output_size = m_dimensions.TotalSize();
209  if (output_size == 0)
210  return TensorOpCost();
211  return m_impl.costPerCoeff(vectorized) +
212  TensorOpCost(sizeof(CoeffReturnType) * input_size / output_size, 0,
213  compute_cost, vectorized, PacketSize);
214  }
215 
216  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
217 
218  protected:
219  Dimensions m_dimensions;
223  const Strides m_strides;
225 };
226 
227 } // end namespace Eigen
228 
229 #endif // EIGEN_CXX11_TENSOR_TENSOR_INFLATION_H
SCALAR Scalar
Definition: bench_gemm.cpp:33
#define EIGEN_STRONG_INLINE
Definition: Macros.h:494
Eigen::internal::traits< TensorInflationOp >::Index Index
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions & dimensions() const
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorInflationOp(const XprType &expr, const Strides &strides)
leaf::MyValues values
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool getInputIndex(Index index, Index *inputIndex) const
Namespace containing all symbols from the Eigen library.
Definition: jet.h:637
A cost model used to limit the number of threads used for evaluating tensor expression.
#define EIGEN_STATIC_ASSERT(CONDITION, MSG)
Definition: StaticAssert.h:124
vector< size_t > dimensions(L.begin(), L.end())
Eigen::internal::traits< TensorInflationOp >::Scalar Scalar
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions & dimensions() const
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const
Eigen::NumTraits< Scalar >::Real RealScalar
EIGEN_DEVICE_FUNC const internal::remove_all< typename XprType::Nested >::type & expression() const
EIGEN_DEFAULT_DENSE_INDEX_TYPE Index
The Index type as used for the API.
Definition: Meta.h:33
#define eigen_assert(x)
Definition: Macros.h:579
#define NULL
Definition: ccolamd.c:609
array< internal::TensorIntDivisor< Index >, NumDims > m_fastStrides
Eigen::internal::traits< TensorInflationOp >::StorageKind StorageKind
The tensor base class.
Definition: TensorBase.h:829
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
XprType::CoeffReturnType CoeffReturnType
#define EIGEN_ALIGN_MAX
Definition: Macros.h:757
EIGEN_DEVICE_FUNC const Strides & strides() const
Eigen::internal::nested< TensorInflationOp >::type Nested
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType &op, const Device &device)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar *)


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autogenerated on Sat May 8 2021 02:45:30