2 * Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
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
8 * http://www.apache.org/licenses/LICENSE-2.0
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.
17 #include "kernels/AveragePool2D.h"
18 #include "kernels/TestUtils.h"
20 namespace luci_interpreter
27 using namespace testing;
29 TEST(AveragePool2DTest, Float)
31 Shape input_shape{1, 3, 5, 1};
32 std::vector<float> input_data{
37 Tensor input_tensor = makeInputTensor<DataType::FLOAT32>(input_shape, input_data);
38 Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
40 Pool2DParams params{};
41 params.padding = Padding::VALID;
42 params.filter_height = 2;
43 params.filter_width = 3;
44 params.stride_height = 1;
45 params.stride_width = 2;
46 params.activation = Activation::RELU6;
48 AveragePool2D kernel(&input_tensor, &output_tensor, params);
52 std::vector<float> ref_output_data{
56 EXPECT_THAT(extractTensorData<float>(output_tensor),
57 ElementsAreArray(ArrayFloatNear(ref_output_data)));
58 EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray({1, 2, 2, 1}));
61 TEST(AveragePool2DTest, Uint8_0)
63 std::pair<float, int32_t> quant_param = quantizationParams<uint8_t>(-15.9375f, 15.9375f);
64 Tensor input_tensor{DataType::U8, {1, 2, 4, 1}, {{quant_param.first}, {quant_param.second}}, ""};
65 Tensor output_tensor = makeOutputTensor(DataType::U8, quant_param.first, quant_param.second);
67 std::vector<uint8_t> quant_input = quantize<uint8_t>(
72 quant_param.first, quant_param.second);
73 input_tensor.writeData(quant_input.data(), quant_input.size() * sizeof(uint8_t));
75 Pool2DParams params{};
76 params.padding = Padding::VALID;
77 params.filter_height = 2;
78 params.filter_width = 2;
79 params.stride_height = 2;
80 params.stride_width = 2;
81 params.activation = Activation::RELU6;
83 AveragePool2D kernel(&input_tensor, &output_tensor, params);
87 EXPECT_THAT(dequantize(extractTensorData<uint8_t>(output_tensor), output_tensor.scale(),
88 output_tensor.zero_point()),
89 ElementsAreArray(ArrayFloatNear({0.0, 6.0})));
90 EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray({1, 1, 2, 1}));
93 TEST(AveragePool2DTest, Uint8_1)
95 std::pair<float, int32_t> quant_param = quantizationParams<uint8_t>(-15.9375f, 15.9375f);
96 Tensor input_tensor{DataType::U8, {1, 2, 4, 1}, {{quant_param.first}, {quant_param.second}}, ""};
97 Tensor output_tensor = makeOutputTensor(DataType::U8, quant_param.first, quant_param.second);
99 std::vector<uint8_t> quant_input = quantize<uint8_t>(
104 quant_param.first, quant_param.second);
105 input_tensor.writeData(quant_input.data(), quant_input.size() * sizeof(uint8_t));
107 Pool2DParams params{};
108 params.padding = Padding::VALID;
109 params.filter_height = 2;
110 params.filter_width = 2;
111 params.stride_height = 2;
112 params.stride_width = 2;
113 params.activation = Activation::RELU6;
115 AveragePool2D kernel(&input_tensor, &output_tensor, params);
119 EXPECT_THAT(dequantize(extractTensorData<uint8_t>(output_tensor), output_tensor.scale(),
120 output_tensor.zero_point()),
121 ElementsAreArray(ArrayFloatNear({2.75, 6.0})));
122 EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray({1, 1, 2, 1}));
125 TEST(AveragePool2DTest, Invalid_Input_Shape_NEG)
127 Shape input_shape{1, 3, 5};
128 std::vector<float> input_data{
129 -4, -3, -2, -1, 0, //
133 Tensor input_tensor = makeInputTensor<DataType::FLOAT32>(input_shape, input_data);
134 Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
136 Pool2DParams params{};
137 params.padding = Padding::VALID;
138 params.filter_height = 2;
139 params.filter_width = 3;
140 params.stride_height = 1;
141 params.stride_width = 2;
142 params.activation = Activation::RELU6;
144 AveragePool2D kernel(&input_tensor, &output_tensor, params);
145 EXPECT_ANY_THROW(kernel.configure());
148 TEST(AveragePool2DTest, In_Out_Type_NEG)
150 Shape input_shape{1, 3, 5, 1};
151 std::vector<float> input_data{
152 -4, -3, -2, -1, 0, //
156 Tensor input_tensor = makeInputTensor<DataType::FLOAT32>(input_shape, input_data);
157 Tensor output_tensor = makeOutputTensor(DataType::U8);
159 Pool2DParams params{};
160 params.padding = Padding::VALID;
161 params.filter_height = 2;
162 params.filter_width = 3;
163 params.stride_height = 1;
164 params.stride_width = 2;
165 params.activation = Activation::RELU6;
167 AveragePool2D kernel(&input_tensor, &output_tensor, params);
168 EXPECT_ANY_THROW(kernel.configure());
171 TEST(AveragePool2DTest, Quant_Param_NEG)
173 std::pair<float, int32_t> quant_param1 = quantizationParams<uint8_t>(-15.9375f, 15.9375f);
174 std::pair<float, int32_t> quant_param2 = quantizationParams<uint8_t>(-7.875f, 7.875f);
176 DataType::U8, {1, 2, 4, 1}, {{quant_param1.first}, {quant_param1.second}}, ""};
177 Tensor output_tensor = makeOutputTensor(DataType::U8, quant_param2.first, quant_param2.second);
179 std::vector<uint8_t> quant_input = quantize<uint8_t>(
184 quant_param1.first, quant_param1.second);
185 input_tensor.writeData(quant_input.data(), quant_input.size() * sizeof(uint8_t));
187 Pool2DParams params{};
188 params.padding = Padding::VALID;
189 params.filter_height = 2;
190 params.filter_width = 2;
191 params.stride_height = 2;
192 params.stride_width = 2;
193 params.activation = Activation::RELU6;
195 AveragePool2D kernel(&input_tensor, &output_tensor, params);
196 EXPECT_ANY_THROW(kernel.configure());
200 } // namespace kernels
201 } // namespace luci_interpreter