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/*
* Copyright (c) 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.
*/
#ifndef ARM_COMPUTE_TEST_LAPLACIAN_PYRAMID_FIXTURE
#define ARM_COMPUTE_TEST_LAPLACIAN_PYRAMID_FIXTURE
#include "arm_compute/core/IPyramid.h"
#include "arm_compute/core/PyramidInfo.h"
#include "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
#include "tests/AssetsLibrary.h"
#include "tests/Globals.h"
#include "tests/IAccessor.h"
#include "tests/framework/Asserts.h"
#include "tests/framework/Fixture.h"
#include "tests/validation/reference/LaplacianPyramid.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
template <typename TensorType, typename AccessorType, typename FunctionType, typename T, typename U, typename PyramidType>
class LaplacianPyramidValidationFixture : public framework::Fixture
{
public:
template <typename...>
void setup(TensorShape input_shape, BorderMode border_mode, size_t num_levels, Format format_in, Format format_out)
{
std::mt19937 generator(library->seed());
std::uniform_int_distribution<T> distribution_u8(0, 255);
const T constant_border_value = distribution_u8(generator);
_pyramid_levels = num_levels;
_border_mode = border_mode;
_target = compute_target(input_shape, border_mode, constant_border_value, format_in, format_out);
_reference = compute_reference(input_shape, border_mode, constant_border_value, format_in, format_out);
}
protected:
template <typename V>
void fill(V &&tensor)
{
library->fill_tensor_uniform(tensor, 0);
}
PyramidType compute_target(const TensorShape &input_shape, BorderMode border_mode, T constant_border_value,
Format format_in, Format format_out)
{
// Create pyramid
PyramidType pyramid{};
// Create Pyramid Info
PyramidInfo pyramid_info(_pyramid_levels, SCALE_PYRAMID_HALF, input_shape, format_out);
// Use conservative padding strategy to fit all subsequent kernels
pyramid.init_auto_padding(pyramid_info);
// Create tensors
TensorType src = create_tensor<TensorType>(input_shape, format_in);
// The first two dimensions of the output tensor must match the first
// two dimensions of the tensor in the last level of the pyramid
TensorShape dst_shape(input_shape);
dst_shape.set(0, pyramid.get_pyramid_level(_pyramid_levels - 1)->info()->dimension(0));
dst_shape.set(1, pyramid.get_pyramid_level(_pyramid_levels - 1)->info()->dimension(1));
// The lowest resolution tensor necessary to reconstruct the input
// tensor from the pyramid.
_dst_target = create_tensor<TensorType>(dst_shape, format_out);
// Create and configure function
FunctionType laplacian_pyramid;
laplacian_pyramid.configure(&src, &pyramid, &_dst_target, border_mode, constant_border_value);
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(_dst_target.info()->is_resizable(), framework::LogLevel::ERRORS);
// Allocate tensors
src.allocator()->allocate();
_dst_target.allocator()->allocate();
ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(!_dst_target.info()->is_resizable(), framework::LogLevel::ERRORS);
pyramid.allocate();
for(size_t i = 0; i < pyramid_info.num_levels(); ++i)
{
ARM_COMPUTE_EXPECT(!pyramid.get_pyramid_level(i)->info()->is_resizable(), framework::LogLevel::ERRORS);
}
// Fill tensors
fill(AccessorType(src));
// Compute function
laplacian_pyramid.run();
return pyramid;
}
std::vector<SimpleTensor<U>> compute_reference(const TensorShape &shape, BorderMode border_mode, T constant_border_value,
Format format_in, Format format_out)
{
// Create reference
SimpleTensor<T> src{ shape, format_in };
// The first two dimensions of the output tensor must match the first
// two dimensions of the tensor in the last level of the pyramid
TensorShape dst_shape(shape);
dst_shape.set(0, static_cast<float>(shape[0] + 1) / static_cast<float>(std::pow(2, _pyramid_levels - 1)));
dst_shape.set(1, static_cast<float>(shape[1] + 1) / static_cast<float>(std::pow(2, _pyramid_levels - 1)));
_dst_reference = SimpleTensor<U>(dst_shape, format_out);
// Fill reference
fill(src);
return reference::laplacian_pyramid<T, U>(src, _dst_reference, _pyramid_levels, border_mode, constant_border_value);
}
size_t _pyramid_levels{};
BorderMode _border_mode{};
SimpleTensor<U> _dst_reference{};
TensorType _dst_target{};
PyramidType _target{};
std::vector<SimpleTensor<U>> _reference{};
};
} // namespace validation
} // namespace test
} // namespace arm_compute
#endif /* ARM_COMPUTE_TEST_LAPLACIAN_PYRAMID_FIXTURE */
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