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 "tensorflow/contrib/lite/kernels/internal/tensor_utils.h" 16 #include <gmock/gmock.h> 17 #include "tensorflow/contrib/lite/builtin_op_data.h" 18 #include "tensorflow/contrib/lite/kernels/test_util.h" 19 20 namespace tflite { 21 namespace tensor_utils { 22 23 TEST(uKernels, ClipTest) { 24 constexpr int kVectorSize = 10; 25 constexpr float kAbsLimit = 2.0; 26 static float input[kVectorSize] = {0.0, -0.5, 1.0, -1.5, 2.0, 27 -2.5, 3.0, -3.5, 4.0, -4.5}; 28 std::vector<float> output(kVectorSize); 29 ClipVector(input, kVectorSize, kAbsLimit, output.data()); 30 EXPECT_THAT(output, 31 ElementsAreArray(ArrayFloatNear( 32 {0.0, -0.5, 1.0, -1.5, 2.0, -2.0, 2.0, -2.0, 2.0, -2.0}))); 33 } 34 35 TEST(uKernels, MatrixBatchVectorMultiplyAccumulateTest) { 36 constexpr int kRow = 3; 37 constexpr int kCol = 4; 38 constexpr int kBatch = 2; 39 static float matrix[kRow * kCol] = {1.0, 2.0, 3.0, 4.0, // 40 -1.0, -2.0, -3.0, -4.0, // 41 1.0, -2.0, 3.0, -4.0}; 42 static float vector[kCol * kBatch] = {1.0, -1.0, 1.0, -1.0, // 43 2.0, -2.0, 2.0, -2.0}; 44 std::vector<float> output(kRow * kBatch); 45 std::fill(output.begin(), output.end(), 3.0); 46 MatrixBatchVectorMultiplyAccumulate(matrix, kRow, kCol, vector, kBatch, 47 output.data(), /*result_stride=*/1); 48 EXPECT_THAT(output, ElementsAreArray(ArrayFloatNear({1., 5., 13., // 49 -1., 7., 23.}))); 50 51 std::vector<float> output_with_stride2(kRow * kBatch * 2); 52 std::fill(output_with_stride2.begin(), output_with_stride2.end(), 3.0); 53 MatrixBatchVectorMultiplyAccumulate(matrix, kRow, kCol, vector, kBatch, 54 output_with_stride2.data(), 55 /*result_stride=*/2); 56 EXPECT_THAT(output_with_stride2, 57 ElementsAreArray(ArrayFloatNear({1., 3., 5., 3., 13., 3., // 58 -1., 3., 7., 3., 23., 3.}))); 59 } 60 61 TEST(uKernels, VectorVectorCwiseProductTest) { 62 constexpr int kVectorSize = 10; 63 static float input1[kVectorSize] = {0.0, -0.5, 1.0, -1.5, 2.0, 64 -2.5, 3.0, -3.5, 4.0, -4.5}; 65 static float input2[kVectorSize] = {0.1, -0.1, 0.1, -0.1, 0.1, 66 -0.1, 0.1, -0.1, 0.1, -0.1}; 67 std::vector<float> output(kVectorSize); 68 VectorVectorCwiseProduct(input1, input2, kVectorSize, output.data()); 69 EXPECT_THAT(output, 70 ElementsAreArray(ArrayFloatNear( 71 {0.0, 0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45}))); 72 } 73 74 TEST(uKernels, VectorVectorCwiseProductAccumulateTest) { 75 constexpr int kVectorSize = 10; 76 static float input1[kVectorSize] = {0.0, -0.5, 1.0, -1.5, 2.0, 77 -2.5, 3.0, -3.5, 4.0, -4.5}; 78 static float input2[kVectorSize] = {0.1, -0.1, 0.1, -0.1, 0.1, 79 -0.1, 0.1, -0.1, 0.1, -0.1}; 80 std::vector<float> output(kVectorSize); 81 std::fill(output.begin(), output.end(), 1.0); 82 VectorVectorCwiseProductAccumulate(input1, input2, kVectorSize, 83 output.data()); 84 EXPECT_THAT(output, 85 ElementsAreArray(ArrayFloatNear( 86 {1.0, 1.05, 1.1, 1.15, 1.2, 1.25, 1.3, 1.35, 1.4, 1.45}))); 87 } 88 89 TEST(uKernels, VectorBatchVectorAssignTest) { 90 constexpr int kVectorSize = 5; 91 constexpr int kBatchSize = 3; 92 static float input[kVectorSize] = {0.0, -0.5, 1.0, -1.5, 2.0}; 93 std::vector<float> output(kVectorSize * kBatchSize); 94 VectorBatchVectorAssign(input, kVectorSize, kBatchSize, output.data()); 95 EXPECT_THAT(output, ElementsAreArray(ArrayFloatNear( 96 {0.0, -0.5, 1.0, -1.5, 2.0, 0.0, -0.5, 1.0, -1.5, 2.0, 97 0.0, -0.5, 1.0, -1.5, 2.0}))); 98 } 99 100 TEST(uKernels, ApplySigmoidToVectorTest) { 101 constexpr int kVectorSize = 5; 102 static float input[kVectorSize] = {0.0, -0.5, 1.0, -1.5, 2.0}; 103 std::vector<float> output(kVectorSize); 104 ApplySigmoidToVector(input, kVectorSize, output.data()); 105 EXPECT_THAT(output, ElementsAreArray(ArrayFloatNear( 106 {0.5, 0.377541, 0.731059, 0.182426, 0.880797}))); 107 } 108 109 TEST(uKernels, ApplyActivationToVectorTest) { 110 constexpr int kVectorSize = 5; 111 static float input[kVectorSize] = {0.0, -0.5, 1.0, -1.5, 2.0}; 112 std::vector<float> output(kVectorSize); 113 ApplyActivationToVector(input, kVectorSize, kTfLiteActRelu, output.data()); 114 EXPECT_THAT(output, 115 ElementsAreArray(ArrayFloatNear({0.0, 0.0, 1.0, 0.0, 2.0}))); 116 117 ApplyActivationToVector(input, kVectorSize, kTfLiteActTanh, output.data()); 118 EXPECT_THAT(output, ElementsAreArray(ArrayFloatNear( 119 {0.0, -0.462117, 0.761594, -0.905148, 0.964028}))); 120 } 121 122 TEST(uKernels, CopyVectorTest) { 123 constexpr int kVectorSize = 5; 124 static float input[kVectorSize] = {0.0, -0.5, 1.0, -1.5, 2.0}; 125 std::vector<float> output(kVectorSize); 126 CopyVector(input, kVectorSize, output.data()); 127 EXPECT_THAT(output, 128 ElementsAreArray(ArrayFloatNear({0.0, -0.5, 1.0, -1.5, 2.0}))); 129 } 130 131 TEST(uKernels, Sub1VectorTest) { 132 constexpr int kVectorSize = 5; 133 static float input[kVectorSize] = {0.0, -0.5, 1.0, -1.5, 2.0}; 134 std::vector<float> output(kVectorSize); 135 Sub1Vector(input, kVectorSize, output.data()); 136 EXPECT_THAT(output, 137 ElementsAreArray(ArrayFloatNear({1.0, 1.5, 0.0, 2.5, -1.0}))); 138 } 139 140 TEST(uKernels, ZeroVectorTest) { 141 constexpr int kVectorSize = 5; 142 std::vector<float> output(kVectorSize); 143 ZeroVector(output.data(), kVectorSize); 144 EXPECT_THAT(output, 145 ElementsAreArray(ArrayFloatNear({0.0, 0.0, 0.0, 0.0, 0.0}))); 146 } 147 148 TEST(uKernels, BatchVectorBatchVectorDotProductTest) { 149 constexpr int kVectorSize = 5; 150 constexpr int kBatch = 2; 151 static float input1[kVectorSize * kBatch] = {0.0, -0.5, 1.0, -1.5, 2.0, 152 -2.5, 3.0, -3.5, 4.0, -4.5}; 153 static float input2[kVectorSize * kBatch] = {0.1, -0.1, 0.1, -0.1, 0.1, 154 -0.1, 0.1, -0.1, 0.1, -0.1}; 155 std::vector<float> output(kBatch); 156 BatchVectorBatchVectorDotProduct(input1, input2, kVectorSize, kBatch, 157 output.data(), /*result_stride=*/1); 158 EXPECT_THAT(output, ElementsAreArray(ArrayFloatNear({0.5, 1.75}))); 159 } 160 161 TEST(uKernels, VectorShiftLeftTest) { 162 constexpr int kVectorSize = 5; 163 static float input[kVectorSize] = {0.0, -0.5, 1.0, -1.5, 2.0}; 164 std::vector<float> result(kVectorSize); 165 VectorShiftLeft(input, kVectorSize, 3.0); 166 result.assign(input, input + kVectorSize); 167 EXPECT_THAT(result, 168 ElementsAreArray(ArrayFloatNear({-0.5, 1.0, -1.5, 2.0, 3.0}))); 169 } 170 171 TEST(uKernels, ReductionSumVectorTest) { 172 constexpr int kInputVectorSize = 10; 173 constexpr int kOutputVectorSize1 = 5; 174 constexpr int kReductionSize1 = 2; 175 static float input[kInputVectorSize] = {0.0, -0.5, 1.0, -1.5, 2.0, 176 0.0, -0.5, 1.0, 1.0, 2.0}; 177 std::vector<float> result1(kOutputVectorSize1); 178 ReductionSumVector(input, result1.data(), kOutputVectorSize1, 179 kReductionSize1); 180 EXPECT_THAT(result1, 181 ElementsAreArray(ArrayFloatNear({-0.5, -0.5, 2.0, 0.5, 3.0}))); 182 183 constexpr int kOutputVectorSize2 = 2; 184 constexpr int kReductionSize2 = 5; 185 std::vector<float> result2(kOutputVectorSize2); 186 ReductionSumVector(input, result2.data(), kOutputVectorSize2, 187 kReductionSize2); 188 EXPECT_THAT(result2, ElementsAreArray(ArrayFloatNear({1.0, 3.5}))); 189 } 190 191 } // namespace tensor_utils 192 } // namespace tflite 193
