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John Richardson2d008a42018-03-22 13:48:41 +00001/*
2 * Copyright (c) 2018 ARM Limited.
3 *
4 * SPDX-License-Identifier: MIT
5 *
6 * Permission is hereby granted, free of charge, to any person obtaining a copy
7 * of this software and associated documentation files (the "Software"), to
8 * deal in the Software without restriction, including without limitation the
9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10 * sell copies of the Software, and to permit persons to whom the Software is
11 * furnished to do so, subject to the following conditions:
12 *
13 * The above copyright notice and this permission notice shall be included in all
14 * copies or substantial portions of the Software.
15 *
16 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22 * SOFTWARE.
23 */
24#ifndef ARM_COMPUTE_TEST_LAPLACIAN_PYRAMID_FIXTURE
25#define ARM_COMPUTE_TEST_LAPLACIAN_PYRAMID_FIXTURE
26
27#include "arm_compute/core/IPyramid.h"
28#include "arm_compute/core/PyramidInfo.h"
29#include "arm_compute/core/TensorShape.h"
30#include "arm_compute/core/Types.h"
31#include "tests/AssetsLibrary.h"
32#include "tests/Globals.h"
33#include "tests/IAccessor.h"
34#include "tests/framework/Asserts.h"
35#include "tests/framework/Fixture.h"
36#include "tests/validation/reference/LaplacianPyramid.h"
37
38namespace arm_compute
39{
40namespace test
41{
42namespace validation
43{
44template <typename TensorType, typename AccessorType, typename FunctionType, typename T, typename U, typename PyramidType>
45class LaplacianPyramidValidationFixture : public framework::Fixture
46{
47public:
48 template <typename...>
49 void setup(TensorShape input_shape, BorderMode border_mode, size_t num_levels, Format format_in, Format format_out)
50 {
51 std::mt19937 generator(library->seed());
52 std::uniform_int_distribution<T> distribution_u8(0, 255);
53 const T constant_border_value = distribution_u8(generator);
54
55 _pyramid_levels = num_levels;
56 _border_mode = border_mode;
57
58 _target = compute_target(input_shape, border_mode, constant_border_value, format_in, format_out);
59 _reference = compute_reference(input_shape, border_mode, constant_border_value, format_in, format_out);
60 }
61
62protected:
63 template <typename V>
64 void fill(V &&tensor)
65 {
66 library->fill_tensor_uniform(tensor, 0);
67 }
68
69 PyramidType compute_target(const TensorShape &input_shape, BorderMode border_mode, T constant_border_value,
70 Format format_in, Format format_out)
71 {
72 // Create pyramid
73 PyramidType pyramid{};
74
75 // Create Pyramid Info
76 PyramidInfo pyramid_info(_pyramid_levels, SCALE_PYRAMID_HALF, input_shape, format_out);
77
78 // Use conservative padding strategy to fit all subsequent kernels
79 pyramid.init_auto_padding(pyramid_info);
80
81 // Create tensors
82 TensorType src = create_tensor<TensorType>(input_shape, format_in);
83
84 // The first two dimensions of the output tensor must match the first
85 // two dimensions of the tensor in the last level of the pyramid
86 TensorShape dst_shape(input_shape);
87 dst_shape.set(0, pyramid.get_pyramid_level(_pyramid_levels - 1)->info()->dimension(0));
88 dst_shape.set(1, pyramid.get_pyramid_level(_pyramid_levels - 1)->info()->dimension(1));
89
90 // The lowest resolution tensor necessary to reconstruct the input
91 // tensor from the pyramid.
92 _dst_target = create_tensor<TensorType>(dst_shape, format_out);
93
94 // Create and configure function
95 FunctionType laplacian_pyramid;
96 laplacian_pyramid.configure(&src, &pyramid, &_dst_target, border_mode, constant_border_value);
97
98 ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
99 ARM_COMPUTE_EXPECT(_dst_target.info()->is_resizable(), framework::LogLevel::ERRORS);
100
101 // Allocate tensors
102 src.allocator()->allocate();
103 _dst_target.allocator()->allocate();
104
105 ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
106 ARM_COMPUTE_EXPECT(!_dst_target.info()->is_resizable(), framework::LogLevel::ERRORS);
107
108 pyramid.allocate();
109
110 for(size_t i = 0; i < pyramid_info.num_levels(); ++i)
111 {
112 ARM_COMPUTE_EXPECT(!pyramid.get_pyramid_level(i)->info()->is_resizable(), framework::LogLevel::ERRORS);
113 }
114
115 // Fill tensors
116 fill(AccessorType(src));
117
118 // Compute function
119 laplacian_pyramid.run();
120
121 return pyramid;
122 }
123
124 std::vector<SimpleTensor<U>> compute_reference(const TensorShape &shape, BorderMode border_mode, T constant_border_value,
125 Format format_in, Format format_out)
126 {
127 // Create reference
128 SimpleTensor<T> src{ shape, format_in };
129
130 // The first two dimensions of the output tensor must match the first
131 // two dimensions of the tensor in the last level of the pyramid
132 TensorShape dst_shape(shape);
133 dst_shape.set(0, static_cast<float>(shape[0] + 1) / static_cast<float>(std::pow(2, _pyramid_levels - 1)));
134 dst_shape.set(1, static_cast<float>(shape[1] + 1) / static_cast<float>(std::pow(2, _pyramid_levels - 1)));
135
136 _dst_reference = SimpleTensor<U>(dst_shape, format_out);
137
138 // Fill reference
139 fill(src);
140
141 return reference::laplacian_pyramid<T, U>(src, _dst_reference, _pyramid_levels, border_mode, constant_border_value);
142 }
143
144 size_t _pyramid_levels{};
145 BorderMode _border_mode{};
146 SimpleTensor<U> _dst_reference{};
147 TensorType _dst_target{};
148 PyramidType _target{};
149 std::vector<SimpleTensor<U>> _reference{};
150};
151} // namespace validation
152} // namespace test
153} // namespace arm_compute
154#endif /* ARM_COMPUTE_TEST_LAPLACIAN_PYRAMID_FIXTURE */