155 lines
6.2 KiB
C++
155 lines
6.2 KiB
C++
/*
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* Copyright (c) 2018 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#ifndef ARM_COMPUTE_TEST_LAPLACIAN_PYRAMID_FIXTURE
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#define ARM_COMPUTE_TEST_LAPLACIAN_PYRAMID_FIXTURE
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#include "arm_compute/core/IPyramid.h"
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#include "arm_compute/core/PyramidInfo.h"
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#include "arm_compute/core/TensorShape.h"
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#include "arm_compute/core/Types.h"
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#include "tests/AssetsLibrary.h"
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#include "tests/Globals.h"
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#include "tests/IAccessor.h"
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#include "tests/framework/Asserts.h"
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#include "tests/framework/Fixture.h"
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#include "tests/validation/reference/LaplacianPyramid.h"
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namespace arm_compute
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{
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namespace test
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{
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namespace validation
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{
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template <typename TensorType, typename AccessorType, typename FunctionType, typename T, typename U, typename PyramidType>
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class LaplacianPyramidValidationFixture : public framework::Fixture
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{
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public:
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template <typename...>
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void setup(TensorShape input_shape, BorderMode border_mode, size_t num_levels, Format format_in, Format format_out)
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{
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std::mt19937 generator(library->seed());
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std::uniform_int_distribution<T> distribution_u8(0, 255);
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const T constant_border_value = distribution_u8(generator);
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_pyramid_levels = num_levels;
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_border_mode = border_mode;
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_target = compute_target(input_shape, border_mode, constant_border_value, format_in, format_out);
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_reference = compute_reference(input_shape, border_mode, constant_border_value, format_in, format_out);
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}
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protected:
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template <typename V>
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void fill(V &&tensor)
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{
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library->fill_tensor_uniform(tensor, 0);
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}
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PyramidType compute_target(const TensorShape &input_shape, BorderMode border_mode, T constant_border_value,
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Format format_in, Format format_out)
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{
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// Create pyramid
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PyramidType pyramid{};
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// Create Pyramid Info
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PyramidInfo pyramid_info(_pyramid_levels, SCALE_PYRAMID_HALF, input_shape, format_out);
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// Use conservative padding strategy to fit all subsequent kernels
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pyramid.init_auto_padding(pyramid_info);
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// Create tensors
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TensorType src = create_tensor<TensorType>(input_shape, format_in);
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// The first two dimensions of the output tensor must match the first
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// two dimensions of the tensor in the last level of the pyramid
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TensorShape dst_shape(input_shape);
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dst_shape.set(0, pyramid.get_pyramid_level(_pyramid_levels - 1)->info()->dimension(0));
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dst_shape.set(1, pyramid.get_pyramid_level(_pyramid_levels - 1)->info()->dimension(1));
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// The lowest resolution tensor necessary to reconstruct the input
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// tensor from the pyramid.
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_dst_target = create_tensor<TensorType>(dst_shape, format_out);
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// Create and configure function
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FunctionType laplacian_pyramid;
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laplacian_pyramid.configure(&src, &pyramid, &_dst_target, border_mode, constant_border_value);
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ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
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ARM_COMPUTE_EXPECT(_dst_target.info()->is_resizable(), framework::LogLevel::ERRORS);
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// Allocate tensors
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src.allocator()->allocate();
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_dst_target.allocator()->allocate();
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ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
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ARM_COMPUTE_EXPECT(!_dst_target.info()->is_resizable(), framework::LogLevel::ERRORS);
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pyramid.allocate();
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for(size_t i = 0; i < pyramid_info.num_levels(); ++i)
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{
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ARM_COMPUTE_EXPECT(!pyramid.get_pyramid_level(i)->info()->is_resizable(), framework::LogLevel::ERRORS);
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}
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// Fill tensors
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fill(AccessorType(src));
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// Compute function
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laplacian_pyramid.run();
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return pyramid;
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}
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std::vector<SimpleTensor<U>> compute_reference(const TensorShape &shape, BorderMode border_mode, T constant_border_value,
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Format format_in, Format format_out)
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{
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// Create reference
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SimpleTensor<T> src{ shape, format_in };
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// The first two dimensions of the output tensor must match the first
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// two dimensions of the tensor in the last level of the pyramid
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TensorShape dst_shape(shape);
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dst_shape.set(0, static_cast<float>(shape[0] + 1) / static_cast<float>(std::pow(2, _pyramid_levels - 1)));
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dst_shape.set(1, static_cast<float>(shape[1] + 1) / static_cast<float>(std::pow(2, _pyramid_levels - 1)));
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_dst_reference = SimpleTensor<U>(dst_shape, format_out);
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// Fill reference
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fill(src);
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return reference::laplacian_pyramid<T, U>(src, _dst_reference, _pyramid_levels, border_mode, constant_border_value);
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}
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size_t _pyramid_levels{};
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BorderMode _border_mode{};
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SimpleTensor<U> _dst_reference{};
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TensorType _dst_target{};
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PyramidType _target{};
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std::vector<SimpleTensor<U>> _reference{};
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};
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} // namespace validation
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} // namespace test
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} // namespace arm_compute
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#endif /* ARM_COMPUTE_TEST_LAPLACIAN_PYRAMID_FIXTURE */
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