1/* Copyright 2017 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
16#include <vector>
17
18#include <gtest/gtest.h>
19#include "tensorflow/contrib/lite/interpreter.h"
20#include "tensorflow/contrib/lite/kernels/register.h"
21#include "tensorflow/contrib/lite/kernels/test_util.h"
22#include "tensorflow/contrib/lite/model.h"
23
24namespace tflite {
25namespace {
26
27using ::testing::ElementsAre;
28
29class LSHProjectionOpModel : public SingleOpModel {
30 public:
31  LSHProjectionOpModel(LSHProjectionType type,
32                       std::initializer_list<int> hash_shape,
33                       std::initializer_list<int> input_shape,
34                       std::initializer_list<int> weight_shape) {
35    hash_ = AddInput(TensorType_FLOAT32);
36    input_ = AddInput(TensorType_INT32);
37    if (weight_shape.size() > 0) {
38      weight_ = AddInput(TensorType_FLOAT32);
39    }
40    output_ = AddOutput(TensorType_INT32);
41
42    SetBuiltinOp(BuiltinOperator_LSH_PROJECTION,
43                 BuiltinOptions_LSHProjectionOptions,
44                 CreateLSHProjectionOptions(builder_, type).Union());
45    if (weight_shape.size() > 0) {
46      BuildInterpreter({hash_shape, input_shape, weight_shape});
47    } else {
48      BuildInterpreter({hash_shape, input_shape});
49    }
50
51    output_size_ = 1;
52    for (int i : hash_shape) {
53      output_size_ *= i;
54      if (type == LSHProjectionType_SPARSE) {
55        break;
56      }
57    }
58  }
59  void SetInput(std::initializer_list<int> data) {
60    PopulateTensor(input_, data);
61  }
62
63  void SetHash(std::initializer_list<float> data) {
64    PopulateTensor(hash_, data);
65  }
66
67  void SetWeight(std::initializer_list<float> f) { PopulateTensor(weight_, f); }
68
69  std::vector<int> GetOutput() { return ExtractVector<int>(output_); }
70
71 private:
72  int input_;
73  int hash_;
74  int weight_;
75  int output_;
76
77  int output_size_;
78};
79
80TEST(LSHProjectionOpTest2, Dense1DInputs) {
81  LSHProjectionOpModel m(LSHProjectionType_DENSE, {3, 2}, {5}, {5});
82
83  m.SetInput({12345, 54321, 67890, 9876, -12345678});
84  m.SetHash({0.123, 0.456, -0.321, 1.234, 5.678, -4.321});
85  m.SetWeight({1.0, 1.0, 1.0, 1.0, 1.0});
86
87  m.Invoke();
88
89  EXPECT_THAT(m.GetOutput(), ElementsAre(0, 0, 0, 1, 0, 0));
90}
91
92TEST(LSHProjectionOpTest2, Sparse1DInputs) {
93  LSHProjectionOpModel m(LSHProjectionType_SPARSE, {3, 2}, {5}, {});
94
95  m.SetInput({12345, 54321, 67890, 9876, -12345678});
96  m.SetHash({0.123, 0.456, -0.321, 1.234, 5.678, -4.321});
97
98  m.Invoke();
99
100  EXPECT_THAT(m.GetOutput(), ElementsAre(0 + 0, 4 + 1, 8 + 0));
101}
102
103TEST(LSHProjectionOpTest2, Sparse3DInputs) {
104  LSHProjectionOpModel m(LSHProjectionType_SPARSE, {3, 2}, {5, 2, 2}, {5});
105
106  m.SetInput({1234, 2345, 3456, 1234, 4567, 5678, 6789, 4567, 7891, 8912,
107              9123, 7890, -987, -876, -765, -987, -543, -432, -321, -543});
108  m.SetHash({0.123, 0.456, -0.321, 1.234, 5.678, -4.321});
109  m.SetWeight({0.12, 0.34, 0.56, 0.67, 0.78});
110
111  m.Invoke();
112
113  EXPECT_THAT(m.GetOutput(), ElementsAre(0 + 2, 4 + 1, 8 + 1));
114}
115
116}  // namespace
117}  // namespace tflite
118
119int main(int argc, char** argv) {
120  ::tflite::LogToStderr();
121  ::testing::InitGoogleTest(&argc, argv);
122  return RUN_ALL_TESTS();
123}
124