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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 */