1/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
2
3Licensed under the Apache License, Version 2.0 (the "License");
4you may not use this file except in compliance with the License.
5You may obtain a copy of the License at
6
7    http://www.apache.org/licenses/LICENSE-2.0
8
9Unless required by applicable law or agreed to in writing, software
10distributed under the License is distributed on an "AS IS" BASIS,
11WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12See the License for the specific language governing permissions and
13limitations under the License.
14==============================================================================*/
15#include <gtest/gtest.h>
16#include "tensorflow/contrib/lite/interpreter.h"
17#include "tensorflow/contrib/lite/kernels/register.h"
18#include "tensorflow/contrib/lite/kernels/test_util.h"
19#include "tensorflow/contrib/lite/model.h"
20
21namespace tflite {
22namespace {
23
24using ::testing::ElementsAreArray;
25
26class BaseMeanOpModel : public SingleOpModel {
27 public:
28  void SetAxis(std::initializer_list<int> data) { PopulateTensor(axis_, data); }
29
30  template <class T>
31  void SetInput(std::initializer_list<T> data) {
32    PopulateTensor(input_, data);
33  }
34
35  template <class T>
36  std::vector<T> GetOutput() {
37    return ExtractVector<T>(output_);
38  }
39
40  std::vector<int> GetOutputShape() { return GetTensorShape(output_); }
41
42 protected:
43  int input_;
44  int axis_;
45  int output_;
46};
47
48// Model for the tests case where axis is a const tensor.
49class MeanOpConstModel : public BaseMeanOpModel {
50 public:
51  MeanOpConstModel(const TensorData& input, const TensorData& output,
52                   std::initializer_list<int> axis_shape,
53                   std::initializer_list<int> axis, bool keep_dims) {
54    input_ = AddInput(input);
55    axis_ = AddConstInput(TensorType_INT32, axis, axis_shape);
56    output_ = AddOutput(output);
57    SetBuiltinOp(BuiltinOperator_MEAN, BuiltinOptions_MeanOptions,
58                 CreateMeanOptions(builder_, keep_dims).Union());
59    BuildInterpreter({GetShape(input_)});
60  }
61};
62
63// Model for the tests case where axis is a dynamic tensor.
64class MeanOpDynamicModel : public BaseMeanOpModel {
65 public:
66  MeanOpDynamicModel(const TensorData& input, const TensorData& output,
67                     const TensorData& axis, bool keep_dims) {
68    input_ = AddInput(input);
69    axis_ = AddInput(axis);
70    output_ = AddOutput(output);
71    SetBuiltinOp(BuiltinOperator_MEAN, BuiltinOptions_MeanOptions,
72                 CreateMeanOptions(builder_, keep_dims).Union());
73    BuildInterpreter({GetShape(input_)});
74  }
75};
76
77TEST(ConstMeanOpTest, NotKeepDims) {
78  std::initializer_list<float> data = {
79      1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0,  10.0, 11.0, 12.0,
80      13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0};
81  MeanOpConstModel m({TensorType_FLOAT32, {4, 3, 2}}, {TensorType_FLOAT32, {2}},
82                     {4}, {1, 0, -3, -3}, false);
83  m.SetInput(data);
84  m.Invoke();
85  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2}));
86  EXPECT_THAT(m.GetOutput<float>(), ElementsAreArray(ArrayFloatNear({12, 13})));
87}
88
89TEST(ConstMeanOpTest, KeepDims) {
90  std::initializer_list<float> data = {
91      1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0,  10.0, 11.0, 12.0,
92      13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0};
93  MeanOpConstModel m({TensorType_FLOAT32, {4, 3, 2}}, {TensorType_FLOAT32, {3}},
94                     {2}, {0, 2}, true);
95  m.SetInput(data);
96  m.Invoke();
97  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 3, 1}));
98  EXPECT_THAT(m.GetOutput<float>(),
99              ElementsAreArray(ArrayFloatNear({10.5, 12.5, 14.5})));
100}
101
102TEST(DynamicMeanOpTest, NotKeepDims) {
103  std::initializer_list<float> data = {
104      1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0,  10.0, 11.0, 12.0,
105      13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0};
106  MeanOpDynamicModel m({TensorType_FLOAT32, {4, 3, 2}},
107                       {TensorType_FLOAT32, {2}}, {TensorType_INT32, {4}},
108                       false);
109  std::initializer_list<int> axis = {1, 0, -3, -3};
110  m.SetAxis(axis);
111  m.SetInput(data);
112  m.Invoke();
113  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2}));
114  EXPECT_THAT(m.GetOutput<float>(), ElementsAreArray(ArrayFloatNear({12, 13})));
115}
116
117TEST(DynamicMeanOpTest, KeepDims) {
118  std::initializer_list<float> data = {
119      1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0,  10.0, 11.0, 12.0,
120      13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0};
121  MeanOpDynamicModel m({TensorType_FLOAT32, {4, 3, 2}},
122                       {TensorType_FLOAT32, {3}}, {TensorType_INT32, {2}},
123                       true);
124  std::initializer_list<int> axis = {0, 2};
125  m.SetAxis(axis);
126  m.SetInput(data);
127  m.Invoke();
128  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 3, 1}));
129  EXPECT_THAT(m.GetOutput<float>(),
130              ElementsAreArray(ArrayFloatNear({10.5, 12.5, 14.5})));
131}
132
133}  // namespace
134}  // namespace tflite
135
136int main(int argc, char** argv) {
137  ::tflite::LogToStderr();
138  ::testing::InitGoogleTest(&argc, argv);
139  return RUN_ALL_TESTS();
140}
141