| /* |
| * 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 */ |