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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 "NEON/Helper.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/Reference.h"
#include "tests/validation_old/Validation.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/NEON/functions/NEMinMaxLocation.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 Neon MinMaxLocation function.
*
* @param[in] shape Shape of the input and output tensors.
* @param[in] dt_in Data type of first input tensor.
* @param[out] min Minimum value of tensor
* @param[out] max Maximum value of tensor
* @param[out] min_loc Array with locations of minimum values
* @param[out] max_loc Array with locations of maximum values
* @param[out] min_count Number of minimum values found
* @param[out] max_count Number of maximum values found
*
* @return Computed output tensor.
*/
void compute_min_max_location(const TensorShape &shape, DataType dt_in, void *min, void *max,
Coordinates2DArray &min_loc, Coordinates2DArray &max_loc, uint32_t &min_count, uint32_t &max_count)
{
// Create tensor
Tensor src = create_tensor<Tensor>(shape, dt_in);
// Create and configure min_max_location configure function
NEMinMaxLocation min_max_loc;
min_max_loc.configure(&src, min, max, &min_loc, &max_loc, &min_count, &max_count);
// Allocate tensors
src.allocator()->allocate();
BOOST_TEST(!src.info()->is_resizable());
// Fill tensors
library->fill_tensor_uniform(Accessor(src), 0);
// Compute function
min_max_loc.run();
}
void validate_configuration(const Tensor &src, TensorShape shape)
{
BOOST_TEST(src.info()->is_resizable());
// Create output storage
int32_t min;
int32_t max;
Coordinates2DArray min_loc;
Coordinates2DArray max_loc;
uint32_t min_count;
uint32_t max_count;
// Create and configure function
NEMinMaxLocation min_max_loc;
min_max_loc.configure(&src, &min, &max, &min_loc, &max_loc, &min_count, &max_count);
// Validate valid region
const ValidRegion valid_region = shape_to_valid_region(shape);
validate(src.info()->valid_region(), valid_region);
// Validate padding
const PaddingSize padding = PaddingCalculator(shape.x(), 1).required_padding();
validate(src.info()->padding(), padding);
}
} // namespace
#ifndef DOXYGEN_SKIP_THIS
BOOST_AUTO_TEST_SUITE(NEON)
BOOST_AUTO_TEST_SUITE(MinMaxLocation)
BOOST_AUTO_TEST_SUITE(Integer)
BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
BOOST_DATA_TEST_CASE(Configuration, (Small2DShapes() + Large2DShapes()) * boost::unit_test::data::make({ DataType::U8, DataType::S16 }),
shape, dt)
{
// Create tensor
Tensor src = create_tensor<Tensor>(shape, dt);
src.info()->set_format(dt == DataType::U8 ? Format::U8 : Format::S16);
validate_configuration(src, shape);
}
BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
BOOST_DATA_TEST_CASE(RunSmall, Small2DShapes() * boost::unit_test::data::make({ DataType::U8, DataType::S16 }),
shape, dt)
{
// Create output storage
int32_t min;
int32_t max;
Coordinates2DArray min_loc(shape.total_size());
Coordinates2DArray max_loc(shape.total_size());
uint32_t min_count;
uint32_t max_count;
int32_t ref_min;
int32_t ref_max;
Coordinates2DArray ref_min_loc(shape.total_size());
Coordinates2DArray ref_max_loc(shape.total_size());
uint32_t ref_min_count;
uint32_t ref_max_count;
// Compute function
compute_min_max_location(shape, dt, &min, &max, min_loc, max_loc, min_count, max_count);
// Compute reference
Reference::compute_reference_min_max_location(shape, dt, &ref_min, &ref_max, ref_min_loc, ref_max_loc, ref_min_count, ref_max_count);
// Validate output
validate_min_max_loc(min, ref_min, max, ref_max, min_loc, ref_min_loc, max_loc, ref_max_loc, min_count, ref_min_count, max_count, ref_max_count);
}
BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
BOOST_DATA_TEST_CASE(RunLarge, Large2DShapes() * boost::unit_test::data::make({ DataType::U8, DataType::S16 }),
shape, dt)
{
// Create output storage
int32_t min;
int32_t max;
Coordinates2DArray min_loc(shape.total_size());
Coordinates2DArray max_loc(shape.total_size());
uint32_t min_count;
uint32_t max_count;
int32_t ref_min;
int32_t ref_max;
Coordinates2DArray ref_min_loc(shape.total_size());
Coordinates2DArray ref_max_loc(shape.total_size());
uint32_t ref_min_count;
uint32_t ref_max_count;
// Compute function
compute_min_max_location(shape, dt, &min, &max, min_loc, max_loc, min_count, max_count);
// Compute reference
Reference::compute_reference_min_max_location(shape, dt, &ref_min, &ref_max, ref_min_loc, ref_max_loc, ref_min_count, ref_max_count);
// Validate output
validate_min_max_loc(min, ref_min, max, ref_max, min_loc, ref_min_loc, max_loc, ref_max_loc, min_count, ref_min_count, max_count, ref_max_count);
}
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE(Float)
BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
BOOST_DATA_TEST_CASE(RunSmall, Small2DShapes() * DataType::F32,
shape, dt)
{
// Create output storage
float min;
float max;
Coordinates2DArray min_loc(shape.total_size());
Coordinates2DArray max_loc(shape.total_size());
uint32_t min_count;
uint32_t max_count;
float ref_min;
float ref_max;
Coordinates2DArray ref_min_loc(shape.total_size());
Coordinates2DArray ref_max_loc(shape.total_size());
uint32_t ref_min_count;
uint32_t ref_max_count;
// Compute function
compute_min_max_location(shape, dt, &min, &max, min_loc, max_loc, min_count, max_count);
// Compute reference
Reference::compute_reference_min_max_location(shape, dt, &ref_min, &ref_max, ref_min_loc, ref_max_loc, ref_min_count, ref_max_count);
// Validate output
validate_min_max_loc(min, ref_min, max, ref_max, min_loc, ref_min_loc, max_loc, ref_max_loc, min_count, ref_min_count, max_count, ref_max_count);
}
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
#endif /* DOXYGEN_SKIP_THIS */
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