cxx11_tensor_custom_op.cpp
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1 // This file is part of Eigen, a lightweight C++ template library
2 // for linear algebra.
3 //
4 // Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@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 #include "main.h"
11 
12 #include <Eigen/CXX11/Tensor>
13 
14 using Eigen::Tensor;
15 
16 
17 struct InsertZeros {
20  result[0] = input.dimension(0) * 2;
21  result[1] = input.dimension(1) * 2;
22  return result;
23  }
24 
25  template <typename Output, typename Device>
26  void eval(const Tensor<float, 2>& input, Output& output, const Device& device) const
27  {
29  strides[0] = 2;
30  strides[1] = 2;
31  output.stride(strides).device(device) = input;
32 
34  Eigen::DSizes<DenseIndex, 2> extents(output.dimension(0)-1, output.dimension(1)-1);
35  output.slice(offsets, extents).stride(strides).device(device) = input.constant(0.0f);
36  }
37 };
38 
39 static void test_custom_unary_op()
40 {
41  Tensor<float, 2> tensor(3,5);
42  tensor.setRandom();
43 
44  Tensor<float, 2> result = tensor.customOp(InsertZeros());
45  VERIFY_IS_EQUAL(result.dimension(0), 6);
46  VERIFY_IS_EQUAL(result.dimension(1), 10);
47 
48  for (int i = 0; i < 6; i+=2) {
49  for (int j = 0; j < 10; j+=2) {
50  VERIFY_IS_EQUAL(result(i, j), tensor(i/2, j/2));
51  }
52  }
53  for (int i = 1; i < 6; i+=2) {
54  for (int j = 1; j < 10; j+=2) {
55  VERIFY_IS_EQUAL(result(i, j), 0);
56  }
57  }
58 }
59 
60 
61 struct BatchMatMul {
62  DSizes<DenseIndex, 3> dimensions(const Tensor<float, 3>& input1, const Tensor<float, 3>& input2) const {
64  result[0] = input1.dimension(0);
65  result[1] = input2.dimension(1);
66  result[2] = input2.dimension(2);
67  return result;
68  }
69 
70  template <typename Output, typename Device>
71  void eval(const Tensor<float, 3>& input1, const Tensor<float, 3>& input2,
72  Output& output, const Device& device) const
73  {
75  array<DimPair, 1> dims;
76  dims[0] = DimPair(1, 0);
77  for (int i = 0; i < output.dimension(2); ++i) {
78  output.template chip<2>(i).device(device) = input1.chip<2>(i).contract(input2.chip<2>(i), dims);
79  }
80  }
81 };
82 
83 
84 static void test_custom_binary_op()
85 {
86  Tensor<float, 3> tensor1(2,3,5);
87  tensor1.setRandom();
88  Tensor<float, 3> tensor2(3,7,5);
89  tensor2.setRandom();
90 
91  Tensor<float, 3> result = tensor1.customOp(tensor2, BatchMatMul());
92  for (int i = 0; i < 5; ++i) {
94  array<DimPair, 1> dims;
95  dims[0] = DimPair(1, 0);
96  Tensor<float, 2> reference = tensor1.chip<2>(i).contract(tensor2.chip<2>(i), dims);
97  TensorRef<Tensor<float, 2> > val = result.chip<2>(i);
98  for (int j = 0; j < 2; ++j) {
99  for (int k = 0; k < 7; ++k) {
100  VERIFY_IS_APPROX(val(j, k), reference(j, k));
101  }
102  }
103  }
104 }
105 
106 
107 EIGEN_DECLARE_TEST(cxx11_tensor_custom_op)
108 {
111 }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor< Scalar_, NumIndices_, Options_, IndexType_ > & setRandom()
Definition: TensorBase.h:996
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorChippingOp< DimId, const Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > chip(const Index offset) const
Definition: TensorBase.h:1090
static void test_custom_unary_op()
DSizes< DenseIndex, 3 > dimensions(const Tensor< float, 3 > &input1, const Tensor< float, 3 > &input2) const
DSizes< DenseIndex, 2 > dimensions(const Tensor< float, 2 > &input) const
#define VERIFY_IS_APPROX(a, b)
#define VERIFY_IS_EQUAL(a, b)
Definition: main.h:386
Values result
Tensor< float, 1 >::DimensionPair DimPair
EIGEN_ALWAYS_INLINE DSizes< IndexType, NumDims > strides(const DSizes< IndexType, NumDims > &dimensions)
Definition: TensorBlock.h:26
EIGEN_DECLARE_TEST(cxx11_tensor_custom_op)
Point2(* f)(const Point3 &, OptionalJacobian< 2, 3 >)
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void eval(const Tensor< float, 2 > &input, Output &output, const Device &device) const
#define CALL_SUBTEST(FUNC)
Definition: main.h:399
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index dimension(std::size_t n) const
Definition: Tensor.h:101
void eval(const Tensor< float, 3 > &input1, const Tensor< float, 3 > &input2, Output &output, const Device &device) const
A reference to a tensor expression The expression will be evaluated lazily (as much as possible)...
static void test_custom_binary_op()
std::ptrdiff_t j
The tensor class.
Definition: Tensor.h:63


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autogenerated on Tue Jul 4 2023 02:34:07