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1 
2 /* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
3 
4 Licensed under the Apache License, Version 2.0 (the "License");
5 you may not use this file except in compliance with the License.
6 You may obtain a copy of the License at
7 
8     http://www.apache.org/licenses/LICENSE-2.0
9 
10 Unless required by applicable law or agreed to in writing, software
11 distributed under the License is distributed on an "AS IS" BASIS,
12 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 See the License for the specific language governing permissions and
14 limitations under the License.
15 ==============================================================================*/
16 #include <cstdarg>
17 #include <gtest/gtest.h>
18 #include "tensorflow/lite/interpreter.h"
19 #include "tensorflow/lite/kernels/register.h"
20 #include "tensorflow/lite/kernels/test_util.h"
21 #include "tensorflow/lite/model.h"
22 
23 namespace tflite {
24 namespace {
25 
26 using ::testing::ElementsAreArray;
27 
28 template <typename T>
29 class SparseToDenseOpModel : public SingleOpModel {
30  public:
SparseToDenseOpModel(std::initializer_list<int> indices_shape,std::initializer_list<int> output_shape_shape,std::initializer_list<int> values_shape,T default_value,TensorType tensor_index_type,TensorType tensor_input_type)31   SparseToDenseOpModel(std::initializer_list<int> indices_shape,
32                        std::initializer_list<int> output_shape_shape,
33                        std::initializer_list<int> values_shape, T default_value,
34                        TensorType tensor_index_type,
35                        TensorType tensor_input_type) {
36     indices_ = AddInput(tensor_index_type);
37     output_shape_ = AddInput(TensorType_INT32);
38     values_ = AddInput(tensor_input_type);
39     default_value_ = AddInput(tensor_input_type);
40     output_ = AddOutput(tensor_input_type);
41 
42     SetBuiltinOp(BuiltinOperator_SPARSE_TO_DENSE,
43                  BuiltinOptions_SparseToDenseOptions,
44                  CreateSparseToDenseOptions(builder_, false).Union());
45     BuildInterpreter({indices_shape, output_shape_shape, values_shape, {1}});
46 
47     PopulateTensor<T>(default_value_, {default_value});
48   }
49 
indices()50   int indices() { return indices_; }
output_shape()51   int output_shape() { return output_shape_; }
values()52   int values() { return values_; }
53 
GetOutput()54   std::vector<T> GetOutput() { return ExtractVector<T>(output_); }
GetOutputShape()55   std::vector<int> GetOutputShape() { return GetTensorShape(output_); }
56 
57  private:
58   int indices_;
59   int output_shape_;
60   int values_;
61   int default_value_;
62   int output_;
63 };
64 
TEST(SparseToDenseOpModelTest,ZeroDimensionTest)65 TEST(SparseToDenseOpModelTest, ZeroDimensionTest) {
66   SparseToDenseOpModel<float> m({1}, {1}, {1}, 0, TensorType_INT32,
67                                 TensorType_FLOAT32);
68   m.PopulateTensor<int32_t>(m.indices(), {3});
69   m.PopulateTensor<int32_t>(m.output_shape(), {5});
70   m.PopulateTensor<float>(m.values(), {7});
71   m.Invoke();
72 
73   EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 0, 0, 7, 0}));
74   EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({5}));
75 }
76 
TEST(SparseToDenseOpModelTest,OneDimensionTest)77 TEST(SparseToDenseOpModelTest, OneDimensionTest) {
78   SparseToDenseOpModel<float> m({3}, {1}, {3}, 0, TensorType_INT32,
79                                 TensorType_FLOAT32);
80   m.PopulateTensor<int32_t>(m.indices(), {1, 3, 5});
81   m.PopulateTensor<int32_t>(m.output_shape(), {7});
82   m.PopulateTensor<float>(m.values(), {2, 4, 6});
83   m.Invoke();
84 
85   EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 2, 0, 4, 0, 6, 0}));
86   EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({7}));
87 }
88 
TEST(SparseToDenseOpModelTest,TwoDimensionsTest)89 TEST(SparseToDenseOpModelTest, TwoDimensionsTest) {
90   SparseToDenseOpModel<float> m({3, 3}, {3}, {3}, 0, TensorType_INT32,
91                                 TensorType_FLOAT32);
92   m.PopulateTensor<int32_t>(m.indices(), {0, 0, 0, 1, 2, 1, 2, 0, 1});
93   m.PopulateTensor<int32_t>(m.output_shape(), {3, 3, 3});
94   m.PopulateTensor<float>(m.values(), {2, 4, 6});
95   m.Invoke();
96 
97   EXPECT_THAT(m.GetOutput(),
98               ElementsAreArray({2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
99                                 0, 0, 4, 0, 0, 6, 0, 0, 0, 0, 0, 0, 0}));
100   EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({3, 3, 3}));
101 }
102 
TEST(SparseToDenseOpModelTest,DefaultValueTest)103 TEST(SparseToDenseOpModelTest, DefaultValueTest) {
104   SparseToDenseOpModel<float> m({3, 3}, {3}, {3}, -1, TensorType_INT32,
105                                 TensorType_FLOAT32);
106   m.PopulateTensor<int32_t>(m.indices(), {0, 0, 0, 1, 2, 1, 2, 0, 1});
107   m.PopulateTensor<int32_t>(m.output_shape(), {3, 3, 3});
108   m.PopulateTensor<float>(m.values(), {2, 4, 6});
109   m.Invoke();
110 
111   EXPECT_THAT(
112       m.GetOutput(),
113       ElementsAreArray({2,  -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
114                         -1, -1, 4,  -1, -1, 6,  -1, -1, -1, -1, -1, -1, -1}));
115   EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({3, 3, 3}));
116 }
117 
TEST(SparseToDenseOpModelTest,IntegerValueTest)118 TEST(SparseToDenseOpModelTest, IntegerValueTest) {
119   SparseToDenseOpModel<int32_t> m({3, 3}, {3}, {3}, -1, TensorType_INT32,
120                                   TensorType_INT32);
121   m.PopulateTensor<int32_t>(m.indices(), {0, 0, 0, 1, 2, 1, 2, 0, 1});
122   m.PopulateTensor<int32_t>(m.output_shape(), {3, 3, 3});
123   m.PopulateTensor<int32_t>(m.values(), {2, 4, 6});
124   m.Invoke();
125 
126   EXPECT_THAT(
127       m.GetOutput(),
128       ElementsAreArray({2,  -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
129                         -1, -1, 4,  -1, -1, 6,  -1, -1, -1, -1, -1, -1, -1}));
130   EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({3, 3, 3}));
131 }
132 
TEST(SparseToDenseOpModelTest,Int64IndexTest)133 TEST(SparseToDenseOpModelTest, Int64IndexTest) {
134   SparseToDenseOpModel<float> m({3, 3}, {3}, {3}, -1, TensorType_INT64,
135                                 TensorType_FLOAT32);
136   m.PopulateTensor<int64_t>(m.indices(), {0, 0, 0, 1, 2, 1, 2, 0, 1});
137   m.PopulateTensor<int32_t>(m.output_shape(), {3, 3, 3});
138   m.PopulateTensor<float>(m.values(), {2, 4, 6});
139   m.Invoke();
140 
141   EXPECT_THAT(
142       m.GetOutput(),
143       ElementsAreArray({2,  -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
144                         -1, -1, 4,  -1, -1, 6,  -1, -1, -1, -1, -1, -1, -1}));
145   EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({3, 3, 3}));
146 }
147 
148 }  // namespace
149 }  // namespace tflite
150 
main(int argc,char ** argv)151 int main(int argc, char** argv) {
152   ::tflite::LogToStderr();
153   ::testing::InitGoogleTest(&argc, argv);
154   return RUN_ALL_TESTS();
155 }
156