/* * 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 class LaplacianPyramidValidationFixture : public framework::Fixture { public: template 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 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 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(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(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> compute_reference(const TensorShape &shape, BorderMode border_mode, T constant_border_value, Format format_in, Format format_out) { // Create reference SimpleTensor 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(shape[0] + 1) / static_cast(std::pow(2, _pyramid_levels - 1))); dst_shape.set(1, static_cast(shape[1] + 1) / static_cast(std::pow(2, _pyramid_levels - 1))); _dst_reference = SimpleTensor(dst_shape, format_out); // Fill reference fill(src); return reference::laplacian_pyramid(src, _dst_reference, _pyramid_levels, border_mode, constant_border_value); } size_t _pyramid_levels{}; BorderMode _border_mode{}; SimpleTensor _dst_reference{}; TensorType _dst_target{}; PyramidType _target{}; std::vector> _reference{}; }; } // namespace validation } // namespace test } // namespace arm_compute #endif /* ARM_COMPUTE_TEST_LAPLACIAN_PYRAMID_FIXTURE */