2 * Copyright (c) 2021 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/PadV2.h"
18 #include "kernels/TestUtils.h"
19 #include "luci_interpreter/TestMemoryManager.h"
21 namespace luci_interpreter
28 using namespace testing;
30 float GetTolerance(float min, float max) { return (max - min) / 255.0; }
34 std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
35 float kQuantizedTolerance = GetTolerance(-1.0, 1.0);
36 std::pair<float, int32_t> quant_param = quantizationParams<uint8_t>(-1.0f, 1.0f);
37 std::vector<float> input_data{-0.8, 0.2, 0.9, 0.7, 0.1, -0.3};
38 std::vector<int32_t> paddings_data{0, 0, 0, 2, 1, 3, 0, 0};
39 std::vector<float> constant_values_data{0.5};
40 Tensor input_tensor = makeInputTensor<DataType::U8>(
41 {1, 2, 3, 1}, quant_param.first, quant_param.second, input_data, memory_manager.get());
42 Tensor paddings_tensor =
43 makeInputTensor<DataType::S32>({4, 2}, paddings_data, memory_manager.get());
44 Tensor constant_values = makeInputTensor<DataType::U8>(
45 {1}, quant_param.first, quant_param.second, constant_values_data, memory_manager.get());
46 Tensor output_tensor = makeOutputTensor(DataType::U8, quant_param.first, quant_param.second);
48 PadV2 kernel(&input_tensor, &paddings_tensor, &constant_values, &output_tensor);
50 memory_manager->allocate_memory(output_tensor);
53 std::vector<float> ref_output_data = {
54 0.5, -0.8, 0.2, 0.9, 0.5, 0.5, 0.5, 0.5, 0.7, 0.1, -0.3, 0.5, 0.5, 0.5, //
55 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5}; //
56 EXPECT_THAT(dequantizeTensorData(output_tensor),
57 FloatArrayNear(ref_output_data, kQuantizedTolerance));
58 EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray({1, 4, 7, 1}));
63 std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
64 std::vector<float> input_data{1, 2, 3, 4, 5, 6};
65 std::vector<int32_t> paddings_data{1, 0, 0, 2, 0, 3, 0, 0};
66 std::vector<float> constant_values_data{7};
68 makeInputTensor<DataType::FLOAT32>({1, 2, 3, 1}, input_data, memory_manager.get());
69 Tensor paddings_tensor =
70 makeInputTensor<DataType::S32>({4, 2}, paddings_data, memory_manager.get());
71 Tensor constant_values =
72 makeInputTensor<DataType::FLOAT32>({1}, constant_values_data, memory_manager.get());
73 Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
75 PadV2 kernel(&input_tensor, &paddings_tensor, &constant_values, &output_tensor);
77 memory_manager->allocate_memory(output_tensor);
80 std::vector<float> ref_output_data{7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7,
81 7, 7, 7, 7, 7, 7, 7, 7, 1, 2, 3, 7, 7, 7, 4, 5,
82 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7};
83 std::initializer_list<int32_t> ref_output_shape{2, 4, 6, 1};
84 EXPECT_THAT(extractTensorData<float>(output_tensor), FloatArrayNear(ref_output_data));
85 EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(ref_output_shape));
89 } // namespace kernels
90 } // namespace luci_interpreter