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-rw-r--r--tests/validation_old/NEON/NonLinearFilter.cpp203
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diff --git a/tests/validation_old/NEON/NonLinearFilter.cpp b/tests/validation_old/NEON/NonLinearFilter.cpp
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-/*
- * Copyright (c) 2017 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.
- */
-#include "NEON/Accessor.h"
-#include "PaddingCalculator.h"
-#include "TypePrinter.h"
-#include "Utils.h"
-#include "tests/AssetsLibrary.h"
-#include "tests/Globals.h"
-#include "tests/validation_old/Datasets.h"
-#include "tests/validation_old/Helpers.h"
-#include "tests/validation_old/Reference.h"
-#include "tests/validation_old/Validation.h"
-#include "tests/validation_old/ValidationUserConfiguration.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NENonLinearFilter.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "tests/validation_old/boost_wrapper.h"
-
-#include <random>
-#include <string>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::validation;
-
-namespace
-{
-/** Compute NonLinearFilter function.
- *
- * @param[in] input Shape of the input and output tensors.
- * @param[in] function Non linear function to perform
- * @param[in] mask_size Mask size. Supported sizes: 3, 5
- * @param[in] pattern Mask pattern
- * @param[in] mask The given mask. Will be used only if pattern is specified to PATTERN_OTHER
- * @param[in] border_mode Strategy to use for borders.
- * @param[in] constant_border_value (Optional) Constant value to use for borders if border_mode is set to CONSTANT.
- *
- * @return Computed output tensor.
- */
-Tensor compute_non_linear_filter(const TensorShape &shape, NonLinearFilterFunction function, unsigned int mask_size,
- MatrixPattern pattern, const uint8_t *mask, BorderMode border_mode,
- uint8_t constant_border_value)
-{
- // Create tensors
- Tensor src = create_tensor<Tensor>(shape, DataType::U8);
- Tensor dst = create_tensor<Tensor>(shape, DataType::U8);
-
- // Create and configure function
- NENonLinearFilter filter;
- filter.configure(&src, &dst, function, mask_size, pattern, mask, border_mode, constant_border_value);
-
- // Allocate tensors
- src.allocator()->allocate();
- dst.allocator()->allocate();
-
- BOOST_TEST(!src.info()->is_resizable());
- BOOST_TEST(!dst.info()->is_resizable());
-
- // Fill tensors
- library->fill_tensor_uniform(Accessor(src), 0);
-
- // Compute function
- filter.run();
-
- return dst;
-}
-} // namespace
-
-#ifndef DOXYGEN_SKIP_THIS
-BOOST_AUTO_TEST_SUITE(NEON)
-BOOST_AUTO_TEST_SUITE(NonLinearFilter)
-
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
-BOOST_DATA_TEST_CASE(Configuration, (SmallShapes() + LargeShapes())
- * NonLinearFilterFunctions() * boost::unit_test::data::make({ 3U, 5U })
- * MatrixPatterns() * BorderModes(),
- shape, function, mask_size, pattern, border_mode)
-{
- std::mt19937 generator(user_config.seed.get());
- std::uniform_int_distribution<uint8_t> distribution_u8(0, 255);
- const uint8_t constant_border_value = distribution_u8(generator);
-
- // Create the mask
- uint8_t mask[mask_size * mask_size];
- fill_mask_from_pattern(mask, mask_size, mask_size, pattern);
- const auto half_mask_size = static_cast<int>(mask_size / 2);
-
- // Create tensors
- Tensor src = create_tensor<Tensor>(shape, DataType::U8);
- Tensor dst = create_tensor<Tensor>(shape, DataType::U8);
-
- BOOST_TEST(src.info()->is_resizable());
- BOOST_TEST(dst.info()->is_resizable());
-
- // Create and configure function
- NENonLinearFilter filter;
- filter.configure(&src, &dst, function, mask_size, pattern, mask, border_mode, constant_border_value);
-
- // Validate valid region
- const ValidRegion src_valid_region = shape_to_valid_region(shape);
- const ValidRegion dst_valid_region = shape_to_valid_region(shape, border_mode == BorderMode::UNDEFINED, BorderSize(half_mask_size));
-
- validate(src.info()->valid_region(), src_valid_region);
- validate(dst.info()->valid_region(), dst_valid_region);
-
- // Validate padding
- PaddingCalculator calculator(shape.x(), ((MatrixPattern::OTHER == pattern) ? 1 : 8));
- calculator.set_border_mode(border_mode);
- calculator.set_border_size(half_mask_size);
-
- const PaddingSize write_padding = calculator.required_padding(PaddingCalculator::Option::EXCLUDE_BORDER);
-
- calculator.set_accessed_elements(16);
- calculator.set_access_offset(-half_mask_size);
-
- const PaddingSize read_padding = calculator.required_padding(PaddingCalculator::Option::INCLUDE_BORDER);
-
- validate(src.info()->padding(), read_padding);
- validate(dst.info()->padding(), write_padding);
-}
-
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
-BOOST_DATA_TEST_CASE(RunSmall, SmallShapes()
- * NonLinearFilterFunctions() * boost::unit_test::data::make({ 3U, 5U })
- * MatrixPatterns() * BorderModes(),
- shape, function, mask_size, pattern, border_mode)
-{
- std::mt19937 generator(user_config.seed.get());
- std::uniform_int_distribution<uint8_t> distribution_u8(0, 255);
- const uint8_t constant_border_value = distribution_u8(generator);
-
- // Create the mask
- uint8_t mask[mask_size * mask_size];
- fill_mask_from_pattern(mask, mask_size, mask_size, pattern);
-
- // Compute function
- Tensor dst = compute_non_linear_filter(shape, function, mask_size, pattern, mask, border_mode, constant_border_value);
-
- // Compute reference
- RawTensor ref_dst = Reference::compute_reference_non_linear_filter(shape, function, mask_size, pattern, mask, border_mode, constant_border_value);
-
- // Calculate valid region
- const ValidRegion valid_region = shape_to_valid_region(shape, border_mode == BorderMode::UNDEFINED, BorderSize(static_cast<int>(mask_size / 2)));
-
- // Validate output
- validate(Accessor(dst), ref_dst, valid_region);
-}
-
-BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
-BOOST_DATA_TEST_CASE(RunLarge, LargeShapes()
- * NonLinearFilterFunctions() * boost::unit_test::data::make({ 3U, 5U })
- * MatrixPatterns() * BorderModes(),
- shape, function, mask_size, pattern, border_mode)
-{
- std::mt19937 generator(user_config.seed.get());
- std::uniform_int_distribution<uint8_t> distribution_u8(0, 255);
- const uint8_t constant_border_value = distribution_u8(generator);
-
- // Create the mask
- uint8_t mask[mask_size * mask_size];
- fill_mask_from_pattern(mask, mask_size, mask_size, pattern);
-
- // Compute function
- Tensor dst = compute_non_linear_filter(shape, function, mask_size, pattern, mask, border_mode, constant_border_value);
-
- // Compute reference
- RawTensor ref_dst = Reference::compute_reference_non_linear_filter(shape, function, mask_size, pattern, mask, border_mode, constant_border_value);
-
- // Calculate valid region
- const ValidRegion valid_region = shape_to_valid_region(shape, border_mode == BorderMode::UNDEFINED, BorderSize(static_cast<int>(mask_size / 2)));
-
- // Validate output
- validate(Accessor(dst), ref_dst, valid_region);
-}
-
-BOOST_AUTO_TEST_SUITE_END()
-BOOST_AUTO_TEST_SUITE_END()
-#endif /* DOXYGEN_SKIP_THIS */
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