139 lines
7.4 KiB
C++
139 lines
7.4 KiB
C++
/*
|
|
* Copyright (c) 2017-2018 Arm Limited.
|
|
*
|
|
* SPDX-License-Identifier: MIT
|
|
*
|
|
* Permission is hereby granted, free of charge, to any person obtaining a copy
|
|
* of this software and associated documentation files (the "Software"), to
|
|
* deal in the Software without restriction, including without limitation the
|
|
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
|
|
* sell copies of the Software, and to permit persons to whom the Software is
|
|
* furnished to do so, subject to the following conditions:
|
|
*
|
|
* The above copyright notice and this permission notice shall be included in all
|
|
* copies or substantial portions of the Software.
|
|
*
|
|
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
|
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
|
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
|
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
|
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
|
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
|
* SOFTWARE.
|
|
*/
|
|
#include "arm_compute/core/WindowIterator.h"
|
|
#include "tests/Utils.h"
|
|
#include "tests/framework/Asserts.h"
|
|
#include "tests/framework/Macros.h"
|
|
#include "tests/framework/datasets/Datasets.h"
|
|
#include "tests/validation/Validation.h"
|
|
#include "utils/TypePrinter.h"
|
|
|
|
#include <stdexcept>
|
|
|
|
using namespace arm_compute;
|
|
using namespace arm_compute::test;
|
|
using namespace arm_compute::test::validation;
|
|
|
|
TEST_SUITE(UNIT)
|
|
TEST_SUITE(WindowIterator)
|
|
|
|
template <typename Dim, typename... Dims>
|
|
Window create_window(Dim &&dim0, Dims &&... dims)
|
|
{
|
|
Window win;
|
|
const std::array < Dim, 1 + sizeof...(Dims) > dimensions{ { dim0, std::forward<Dims>(dims)... } };
|
|
for(size_t i = 0; i < dimensions.size(); i++)
|
|
{
|
|
win.set(i, dimensions[i]);
|
|
}
|
|
return win;
|
|
}
|
|
|
|
template <typename T>
|
|
std::vector<T> create_vector(std::initializer_list<T> list_objs)
|
|
{
|
|
std::vector<T> vec_objs;
|
|
for(auto it : list_objs)
|
|
{
|
|
vec_objs.push_back(it);
|
|
}
|
|
return vec_objs;
|
|
}
|
|
|
|
DATA_TEST_CASE(WholeWindow, framework::DatasetMode::ALL, zip(framework::dataset::make("Window", { create_window(Window::Dimension(0, 1)),
|
|
create_window(Window::Dimension(1, 5, 2), Window::Dimension(3, 5)),
|
|
create_window(Window::Dimension(4, 16, 4), Window::Dimension(3, 13, 5), Window::Dimension(1, 3, 2))
|
|
}),
|
|
framework::dataset::make("Expected", { create_vector({ Coordinates(0, 0) }),
|
|
create_vector({ Coordinates(1, 3), Coordinates(3, 3), Coordinates(1, 4), Coordinates(3, 4) }),
|
|
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) })
|
|
})),
|
|
window, expected)
|
|
{
|
|
unsigned int i = 0;
|
|
int row_size = 0;
|
|
TensorShape window_shape = window.shape();
|
|
Coordinates start_offset = index2coords(window_shape, 0);
|
|
Coordinates end_offset = index2coords(window_shape, window.num_iterations_total() - 1);
|
|
auto window_iterator = create_window_iterator(window, start_offset, end_offset, [&](const Coordinates & id)
|
|
{
|
|
ARM_COMPUTE_EXPECT_EQUAL(row_size, (window[0].end() - window[0].start()), framework::LogLevel::ERRORS);
|
|
ARM_COMPUTE_ASSERT(i < expected.size());
|
|
Coordinates expected_coords = expected[i++];
|
|
//Set number of dimensions to the maximum (To match the number of dimensions used by the id passed to the lambda function)
|
|
expected_coords.set_num_dimensions(Coordinates::num_max_dimensions);
|
|
ARM_COMPUTE_EXPECT_EQUAL(id, expected_coords, framework::LogLevel::ERRORS);
|
|
});
|
|
window_iterator.iterate_3D([&](int start, int end)
|
|
{
|
|
ARM_COMPUTE_EXPECT_EQUAL(window[0].start(), start, framework::LogLevel::ERRORS);
|
|
ARM_COMPUTE_EXPECT_EQUAL(window[0].end(), end, framework::LogLevel::ERRORS);
|
|
ARM_COMPUTE_EXPECT(end > start, framework::LogLevel::ERRORS);
|
|
row_size = end - start;
|
|
});
|
|
ARM_COMPUTE_EXPECT_EQUAL(i, expected.size(), framework::LogLevel::ERRORS);
|
|
}
|
|
|
|
DATA_TEST_CASE(PartialWindow2D, framework::DatasetMode::ALL, zip(zip(zip(combine(framework::dataset::make("Window",
|
|
create_window(Window::Dimension(4, 20, 4), Window::Dimension(3, 32, 5), Window::Dimension(1, 2, 1))),
|
|
framework::dataset::make("Start", { 0, 1, 3, 2, 4 })),
|
|
framework::dataset::make("End", { 0, 2, 5, 8, 7 })),
|
|
framework::dataset::make("RowSize",
|
|
{
|
|
create_vector({ 4 }),
|
|
create_vector({ 8, 8 }),
|
|
create_vector({ 4, 8, 8 }),
|
|
create_vector({ 8, 8, 16, 16, 16, 16, 4 }),
|
|
create_vector({ 16, 16, 16, 16 }),
|
|
})),
|
|
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) }) })),
|
|
window, start, end, expected_row_size, expected)
|
|
{
|
|
unsigned int i = 0;
|
|
int row_size = 0;
|
|
TensorShape window_shape = window.shape();
|
|
Coordinates start_offset = index2coords(window_shape, start);
|
|
Coordinates end_offset = index2coords(window_shape, end);
|
|
auto window_iterator = create_window_iterator(window, start_offset, end_offset, [&](const Coordinates & id)
|
|
{
|
|
ARM_COMPUTE_ASSERT(i < expected.size());
|
|
ARM_COMPUTE_EXPECT_EQUAL(expected_row_size[i], row_size, framework::LogLevel::ERRORS);
|
|
Coordinates expected_coords = expected[i++];
|
|
//Set number of dimensions to the maximum (To match the number of dimensions used by the id passed to the lambda function)
|
|
expected_coords.set_num_dimensions(Coordinates::num_max_dimensions);
|
|
ARM_COMPUTE_EXPECT_EQUAL(id, expected_coords, framework::LogLevel::ERRORS);
|
|
});
|
|
window_iterator.iterate_3D([&](int start, int end)
|
|
{
|
|
ARM_COMPUTE_EXPECT(start >= window[0].start(), framework::LogLevel::ERRORS);
|
|
ARM_COMPUTE_EXPECT(end <= window[0].end(), framework::LogLevel::ERRORS);
|
|
ARM_COMPUTE_EXPECT(end > start, framework::LogLevel::ERRORS);
|
|
row_size = end - start;
|
|
});
|
|
ARM_COMPUTE_EXPECT_EQUAL(i, expected.size(), framework::LogLevel::ERRORS);
|
|
}
|
|
|
|
TEST_SUITE_END()
|
|
TEST_SUITE_END()
|