1 /* Copyright 2017 The TensorFlow Authors. All Rights Reserved. 2 3 Licensed under the Apache License, Version 2.0 (the "License"); 4 you may not use this file except in compliance with the License. 5 You may obtain a copy of the License at 6 7 http://www.apache.org/licenses/LICENSE-2.0 8 9 Unless required by applicable law or agreed to in writing, software 10 distributed under the License is distributed on an "AS IS" BASIS, 11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 See the License for the specific language governing permissions and 13 limitations 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 21 namespace tflite { 22 namespace { 23 24 using ::testing::ElementsAreArray; 25 26 class PadOpModel : public SingleOpModel { 27 public: 28 void SetInput(std::initializer_list<float> data) { 29 PopulateTensor<float>(input_, data); 30 } 31 32 void SetPaddings(std::initializer_list<int> paddings) { 33 PopulateTensor<int>(paddings_, paddings); 34 } 35 36 std::vector<float> GetOutput() { return ExtractVector<float>(output_); } 37 std::vector<int> GetOutputShape() { return GetTensorShape(output_); } 38 39 protected: 40 int input_; 41 int output_; 42 int paddings_; 43 }; 44 45 // Tests case where paddings is a const tensor. 46 // 47 // Example usage is as follows: 48 // PadOpDynamicModel m(input_shape, paddings_shape, paddings_data); 49 // m.SetInput(input_data); 50 // m.Invoke(); 51 class PadOpConstModel : public PadOpModel { 52 public: 53 PadOpConstModel(std::initializer_list<int> input_shape, 54 std::initializer_list<int> paddings_shape, 55 std::initializer_list<int> paddings) { 56 input_ = AddInput(TensorType_FLOAT32); 57 paddings_ = AddConstInput(TensorType_INT32, paddings, paddings_shape); 58 output_ = AddOutput(TensorType_FLOAT32); 59 60 SetBuiltinOp(BuiltinOperator_PAD, BuiltinOptions_PadOptions, 61 CreatePadOptions(builder_).Union()); 62 BuildInterpreter({input_shape}); 63 } 64 }; 65 66 // Test case where paddings is a non-const tensor. 67 // 68 // Example usage is as follows: 69 // PadOpDynamicModel m(input_shape, paddings_shape); 70 // m.SetInput(input_data); 71 // m.SetPaddings(paddings_data); 72 // m.Invoke(); 73 class PadOpDynamicModel : public PadOpModel { 74 public: 75 PadOpDynamicModel(std::initializer_list<int> input_shape, 76 std::initializer_list<int> paddings_shape) { 77 input_ = AddInput(TensorType_FLOAT32); 78 paddings_ = AddInput(TensorType_INT32); 79 output_ = AddOutput(TensorType_FLOAT32); 80 81 SetBuiltinOp(BuiltinOperator_PAD, BuiltinOptions_PadOptions, 82 CreatePadOptions(builder_).Union()); 83 BuildInterpreter({input_shape, paddings_shape}); 84 } 85 }; 86 87 TEST(PadOpTest, TooManyDimensions) { 88 EXPECT_DEATH( 89 PadOpConstModel({1, 2, 3, 4, 5, 6, 7, 8, 9}, {9, 2}, 90 {1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9}), 91 "dims != 4"); 92 } 93 94 TEST(PadOpTest, UnequalDimensions) { 95 EXPECT_DEATH(PadOpConstModel({1, 1, 2, 1}, {3, 2}, {1, 1, 2, 2, 3, 3}), 96 "3 != 4"); 97 } 98 99 TEST(PadOpTest, InvalidPadValue) { 100 EXPECT_DEATH( 101 PadOpConstModel({1, 1, 2, 1}, {4, 2}, {0, 0, 1, -1, 2, -1, 0, 0}), 102 "Pad value has to be greater than equal to 0."); 103 } 104 105 TEST(PadOpTest, SimpleConstTest) { 106 // Padding is represented as four 2-D lists representing above padding and 107 // below padding (i.e. {{0, 0}, {1, 1}, {1, 1}, {0, 0}}). 108 PadOpConstModel m({1, 2, 2, 1}, {4, 2}, {0, 0, 1, 1, 1, 1, 0, 0}); 109 m.SetInput({1, 2, 3, 4}); 110 m.Invoke(); 111 EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 0, 0, 0, 0, 1, 2, 0, 0, 3, 4, 112 0, 0, 0, 0, 0})); 113 EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1})); 114 } 115 116 TEST(PadOpTest, SimpleDynamicTest) { 117 PadOpDynamicModel m({1, 2, 2, 1}, {4, 2}); 118 m.SetInput({1, 2, 3, 4}); 119 m.SetPaddings({0, 0, 1, 1, 1, 1, 0, 0}); 120 m.Invoke(); 121 EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 0, 0, 0, 0, 1, 2, 0, 0, 3, 4, 122 0, 0, 0, 0, 0})); 123 EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1})); 124 } 125 126 TEST(PadOpTest, AdvancedConstTest) { 127 PadOpConstModel m({1, 2, 3, 1}, {4, 2}, {0, 0, 0, 2, 1, 3, 0, 0}); 128 m.SetInput({1, 2, 3, 4, 5, 6}); 129 m.Invoke(); 130 EXPECT_THAT(m.GetOutput(), 131 ElementsAreArray({0, 1, 2, 3, 0, 0, 0, 0, 4, 5, 6, 0, 0, 0, 132 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0})); 133 EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 7, 1})); 134 } 135 136 TEST(PadOpTest, AdvancedDynamicTest) { 137 PadOpDynamicModel m({1, 2, 3, 1}, {4, 2}); 138 m.SetInput({1, 2, 3, 4, 5, 6}); 139 m.SetPaddings({0, 0, 0, 2, 1, 3, 0, 0}); 140 m.Invoke(); 141 EXPECT_THAT(m.GetOutput(), 142 ElementsAreArray({0, 1, 2, 3, 0, 0, 0, 0, 4, 5, 6, 0, 0, 0, 143 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0})); 144 EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 7, 1})); 145 } 146 147 } // namespace 148 } // namespace tflite 149 150 int main(int argc, char** argv) { 151 ::tflite::LogToStderr(); 152 ::testing::InitGoogleTest(&argc, argv); 153 return RUN_ALL_TESTS(); 154 } 155
