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/MaxPool2D.h"
18 #include "kernels/TestUtils.h"
19 #include "luci_interpreter/TestMemoryManager.h"
21 namespace luci_interpreter
28 using namespace testing;
30 class MaxPool2DTest : public ::testing::Test
33 void SetUp() override { _memory_manager = std::make_unique<TestMemoryManager>(); }
35 std::unique_ptr<IMemoryManager> _memory_manager;
38 TEST_F(MaxPool2DTest, Float)
40 Shape input_shape{1, 3, 5, 1};
41 std::vector<float> input_data{
43 -7, -6, -5, -4, -3, //
47 makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
48 Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
50 Pool2DParams params{};
51 params.padding = Padding::VALID;
52 params.filter_height = 2;
53 params.filter_width = 3;
54 params.stride_height = 1;
55 params.stride_width = 2;
56 params.activation = Activation::RELU6;
58 MaxPool2D kernel(&input_tensor, &output_tensor, params);
60 _memory_manager->allocate_memory(output_tensor);
63 std::vector<float> ref_output_data{
67 std::initializer_list<int32_t> ref_output_shape{1, 2, 2, 1};
68 EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data));
69 EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(ref_output_shape));
72 TEST_F(MaxPool2DTest, Uint8)
74 std::pair<float, int32_t> quant_param = quantizationParams<uint8_t>(-15.9375, 15.9375);
75 std::vector<float> input_data{
79 Tensor input_tensor = makeInputTensor<DataType::U8>(
80 {1, 2, 4, 1}, quant_param.first, quant_param.second, input_data, _memory_manager.get());
81 Tensor output_tensor = makeOutputTensor(DataType::U8, quant_param.first, quant_param.second);
83 Pool2DParams params{};
84 params.padding = Padding::VALID;
85 params.filter_height = 2;
86 params.filter_width = 2;
87 params.stride_height = 2;
88 params.stride_width = 2;
89 params.activation = Activation::RELU6;
91 MaxPool2D kernel(&input_tensor, &output_tensor, params);
93 _memory_manager->allocate_memory(output_tensor);
96 std::vector<float> ref_output_data{0.0, 6.0};
97 std::initializer_list<int32_t> ref_output_shape{1, 1, 2, 1};
98 EXPECT_THAT(dequantizeTensorData(output_tensor), FloatArrayNear(ref_output_data));
99 EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(ref_output_shape));
102 TEST_F(MaxPool2DTest, SInt16)
104 Shape input_shape{1, 3, 5, 1};
105 std::vector<int32_t> ref_output_shape{1, 2, 2, 1};
106 std::vector<float> input_data{
108 -7, -6, -5, -4, -3, //
111 std::vector<float> ref_output_data{
116 Tensor input_tensor =
117 makeInputTensor<DataType::S16>(input_shape, 0.2, 0, input_data, _memory_manager.get());
118 Tensor output_tensor = makeOutputTensor(DataType::S16, 0.2, 0);
120 Pool2DParams params{};
121 params.padding = Padding::VALID;
122 params.filter_height = 2;
123 params.filter_width = 3;
124 params.stride_height = 1;
125 params.stride_width = 2;
126 params.activation = Activation::RELU6;
128 MaxPool2D kernel(&input_tensor, &output_tensor, params);
130 _memory_manager->allocate_memory(output_tensor);
133 EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(ref_output_shape));
134 EXPECT_THAT(dequantizeTensorData(output_tensor), FloatArrayNear(ref_output_data));
138 } // namespace kernels
139 } // namespace luci_interpreter