Anthony Barbier | 671a11e | 2018-07-06 15:11:36 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2017-2018 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 | #include "arm_compute/core/WindowIterator.h" |
| 25 | #include "tests/Utils.h" |
| 26 | #include "tests/framework/Asserts.h" |
| 27 | #include "tests/framework/Macros.h" |
| 28 | #include "tests/framework/datasets/Datasets.h" |
| 29 | #include "tests/validation/Validation.h" |
| 30 | #include "utils/TypePrinter.h" |
| 31 | |
| 32 | #include <stdexcept> |
| 33 | |
| 34 | using namespace arm_compute; |
| 35 | using namespace arm_compute::test; |
| 36 | using namespace arm_compute::test::validation; |
| 37 | |
| 38 | TEST_SUITE(UNIT) |
| 39 | TEST_SUITE(WindowIterator) |
| 40 | |
| 41 | template <typename Dim, typename... Dims> |
| 42 | Window create_window(Dim &&dim0, Dims &&... dims) |
| 43 | { |
| 44 | Window win; |
| 45 | const std::array < Dim, 1 + sizeof...(Dims) > dimensions{ { dim0, std::forward<Dims>(dims)... } }; |
| 46 | for(size_t i = 0; i < dimensions.size(); i++) |
| 47 | { |
| 48 | win.set(i, dimensions[i]); |
| 49 | } |
| 50 | return win; |
| 51 | } |
| 52 | |
| 53 | template <typename T> |
| 54 | std::vector<T> create_vector(std::initializer_list<T> list_objs) |
| 55 | { |
| 56 | std::vector<T> vec_objs; |
| 57 | for(auto it : list_objs) |
| 58 | { |
| 59 | vec_objs.push_back(it); |
| 60 | } |
| 61 | return vec_objs; |
| 62 | } |
| 63 | |
| 64 | DATA_TEST_CASE(WholeWindow, framework::DatasetMode::ALL, zip(framework::dataset::make("Window", { create_window(Window::Dimension(0, 1)), |
| 65 | create_window(Window::Dimension(1, 5, 2), Window::Dimension(3, 5)), |
| 66 | create_window(Window::Dimension(4, 16, 4), Window::Dimension(3, 13, 5), Window::Dimension(1, 3, 2)) |
| 67 | }), |
| 68 | framework::dataset::make("Expected", { create_vector({ Coordinates(0, 0) }), |
| 69 | create_vector({ Coordinates(1, 3), Coordinates(3, 3), Coordinates(1, 4), Coordinates(3, 4) }), |
| 70 | create_vector({ Coordinates(4, 3, 1), Coordinates(8, 3, 1), Coordinates(12, 3, 1), Coordinates(4, 8, 1), Coordinates(8, 8, 1), Coordinates(12, 8, 1) }) |
| 71 | })), |
| 72 | window, expected) |
| 73 | { |
| 74 | unsigned int i = 0; |
| 75 | int row_size = 0; |
| 76 | TensorShape window_shape = window.shape(); |
| 77 | Coordinates start_offset = index2coords(window_shape, 0); |
| 78 | Coordinates end_offset = index2coords(window_shape, window.num_iterations_total() - 1); |
| 79 | auto window_iterator = create_window_iterator(window, start_offset, end_offset, [&](const Coordinates & id) |
| 80 | { |
| 81 | ARM_COMPUTE_EXPECT_EQUAL(row_size, (window[0].end() - window[0].start()), framework::LogLevel::ERRORS); |
| 82 | ARM_COMPUTE_ASSERT(i < expected.size()); |
| 83 | Coordinates expected_coords = expected[i++]; |
| 84 | //Set number of dimensions to the maximum (To match the number of dimensions used by the id passed to the lambda function) |
| 85 | expected_coords.set_num_dimensions(Coordinates::num_max_dimensions); |
| 86 | ARM_COMPUTE_EXPECT_EQUAL(id, expected_coords, framework::LogLevel::ERRORS); |
| 87 | }); |
| 88 | window_iterator.iterate_3D([&](int start, int end) |
| 89 | { |
| 90 | ARM_COMPUTE_EXPECT_EQUAL(window[0].start(), start, framework::LogLevel::ERRORS); |
| 91 | ARM_COMPUTE_EXPECT_EQUAL(window[0].end(), end, framework::LogLevel::ERRORS); |
| 92 | ARM_COMPUTE_EXPECT(end > start, framework::LogLevel::ERRORS); |
| 93 | row_size = end - start; |
| 94 | }); |
| 95 | ARM_COMPUTE_EXPECT_EQUAL(i, expected.size(), framework::LogLevel::ERRORS); |
| 96 | } |
| 97 | |
| 98 | DATA_TEST_CASE(PartialWindow2D, framework::DatasetMode::ALL, zip(zip(zip(combine(framework::dataset::make("Window", |
Georgios Pinitas | fb0b280 | 2018-08-01 12:11:15 +0100 | [diff] [blame] | 99 | create_window(Window::Dimension(4, 20, 4), Window::Dimension(3, 32, 5), Window::Dimension(1, 2, 1))), |
Anthony Barbier | 671a11e | 2018-07-06 15:11:36 +0100 | [diff] [blame] | 100 | framework::dataset::make("Start", { 0, 1, 3, 2, 4 })), |
| 101 | framework::dataset::make("End", { 0, 2, 5, 8, 7 })), |
| 102 | framework::dataset::make("RowSize", |
| 103 | { |
| 104 | create_vector({ 4 }), |
| 105 | create_vector({ 8, 8 }), |
| 106 | create_vector({ 4, 8, 8 }), |
| 107 | create_vector({ 8, 8, 16, 16, 16, 16, 4 }), |
| 108 | create_vector({ 16, 16, 16, 16 }), |
| 109 | })), |
| 110 | framework::dataset::make("Expected", { create_vector({ Coordinates(4, 3, 1) }), create_vector({ Coordinates(8, 3, 1), Coordinates(12, 3, 1) }), create_vector({ Coordinates(16, 3, 1), Coordinates(4, 8, 1), Coordinates(8, 8, 1) }), create_vector({ Coordinates(12, 3, 1), Coordinates(16, 3, 1), Coordinates(4, 8, 1), Coordinates(8, 8, 1), Coordinates(12, 8, 1), Coordinates(16, 8, 1), Coordinates(4, 13, 1) }), create_vector({ Coordinates(4, 8, 1), Coordinates(8, 8, 1), Coordinates(12, 8, 1), Coordinates(16, 8, 1) }) })), |
| 111 | window, start, end, expected_row_size, expected) |
| 112 | { |
| 113 | unsigned int i = 0; |
| 114 | int row_size = 0; |
| 115 | TensorShape window_shape = window.shape(); |
| 116 | Coordinates start_offset = index2coords(window_shape, start); |
| 117 | Coordinates end_offset = index2coords(window_shape, end); |
| 118 | auto window_iterator = create_window_iterator(window, start_offset, end_offset, [&](const Coordinates & id) |
| 119 | { |
| 120 | ARM_COMPUTE_ASSERT(i < expected.size()); |
| 121 | ARM_COMPUTE_EXPECT_EQUAL(expected_row_size[i], row_size, framework::LogLevel::ERRORS); |
| 122 | Coordinates expected_coords = expected[i++]; |
| 123 | //Set number of dimensions to the maximum (To match the number of dimensions used by the id passed to the lambda function) |
| 124 | expected_coords.set_num_dimensions(Coordinates::num_max_dimensions); |
| 125 | ARM_COMPUTE_EXPECT_EQUAL(id, expected_coords, framework::LogLevel::ERRORS); |
| 126 | }); |
| 127 | window_iterator.iterate_3D([&](int start, int end) |
| 128 | { |
| 129 | ARM_COMPUTE_EXPECT(start >= window[0].start(), framework::LogLevel::ERRORS); |
| 130 | ARM_COMPUTE_EXPECT(end <= window[0].end(), framework::LogLevel::ERRORS); |
| 131 | ARM_COMPUTE_EXPECT(end > start, framework::LogLevel::ERRORS); |
| 132 | row_size = end - start; |
| 133 | }); |
| 134 | ARM_COMPUTE_EXPECT_EQUAL(i, expected.size(), framework::LogLevel::ERRORS); |
| 135 | } |
| 136 | |
| 137 | TEST_SUITE_END() |
| 138 | TEST_SUITE_END() |