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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 "AssetsLibrary.h"
#include "CL/CLAccessor.h"
#include "Globals.h"
#include "PaddingCalculator.h"
#include "TypePrinter.h"
#include "Utils.h"
#include "validation/Datasets.h"
#include "validation/Helpers.h"
#include "validation/Reference.h"
#include "validation/Validation.h"
#include "validation/ValidationUserConfiguration.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/CL/functions/CLNonLinearFilter.h"
#include "arm_compute/runtime/Tensor.h"
#include "arm_compute/runtime/TensorAllocator.h"
#include "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 CL tensor.
*/
CLTensor 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
CLTensor src = create_tensor<CLTensor>(shape, DataType::U8);
CLTensor dst = create_tensor<CLTensor>(shape, DataType::U8);
// Create and configure function
CLNonLinearFilter 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(CLAccessor(src), 0);
// Compute function
filter.run();
return dst;
}
} // namespace
#ifndef DOXYGEN_SKIP_THIS
BOOST_AUTO_TEST_SUITE(CL)
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 })
* boost::unit_test::data::make({ MatrixPattern::BOX, MatrixPattern::CROSS, MatrixPattern::DISK }) * 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
CLTensor src = create_tensor<CLTensor>(shape, DataType::U8);
CLTensor dst = create_tensor<CLTensor>(shape, DataType::U8);
BOOST_TEST(src.info()->is_resizable());
BOOST_TEST(dst.info()->is_resizable());
// Create and configure function
CLNonLinearFilter 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 })
* boost::unit_test::data::make({ MatrixPattern::BOX, MatrixPattern::CROSS, MatrixPattern::DISK }) * 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
CLTensor 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(CLAccessor(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 })
* boost::unit_test::data::make({ MatrixPattern::BOX, MatrixPattern::CROSS, MatrixPattern::DISK }) * 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
CLTensor 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(CLAccessor(dst), ref_dst, valid_region);
}
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
#endif /* DOXYGEN_SKIP_THIS */
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