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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 "Globals.h"
#include "NEON/Helper.h"
#include "NEON/NEAccessor.h"
#include "TensorLibrary.h"
#include "TypePrinter.h"
#include "Utils.h"
#include "dataset/ThresholdDataset.h"
#include "validation/Datasets.h"
#include "validation/Reference.h"
#include "validation/Validation.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/NEON/functions/NEThreshold.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::neon;
using namespace arm_compute::test::validation;
namespace
{
/** Compute Threshold function.
*
* @param[in] shape Shape of the input and output tensors.
* @param[in] threshold Threshold. When the threshold type is RANGE, this is used as the lower threshold.
* @param[in] false_value value to set when the condition is not respected.
* @param[in] true_value value to set when the condition is respected.
* @param[in] type Thresholding type. Either RANGE or BINARY.
* @param[in] upper Upper threshold. Only used when the thresholding type is RANGE.
*
* @return Computed output tensor.
*/
Tensor compute_threshold(const TensorShape &shape, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper)
{
// Create tensors
Tensor src1 = create_tensor(shape, DataType::U8);
Tensor dst = create_tensor(shape, DataType::U8);
// Create and configure function
NEThreshold thrsh;
thrsh.configure(&src1, &dst, threshold, false_value, true_value, type, upper);
// Allocate tensors
src1.allocator()->allocate();
dst.allocator()->allocate();
BOOST_TEST(!src1.info()->is_resizable());
BOOST_TEST(!dst.info()->is_resizable());
// Fill tensors
library->fill_tensor_uniform(NEAccessor(src1), 0);
// Compute function
thrsh.run();
return dst;
}
} // namespace
#ifndef DOXYGEN_SKIP_THIS
BOOST_AUTO_TEST_SUITE(NEON)
BOOST_AUTO_TEST_SUITE(Threshold)
BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
BOOST_DATA_TEST_CASE(Configuration,
(SmallShapes() + LargeShapes()) * ThresholdDataset(),
shape, thrshConf)
{
// Create tensors
Tensor src1 = create_tensor(shape, DataType::U8);
Tensor dst = create_tensor(shape, DataType::U8);
BOOST_TEST(src1.info()->is_resizable());
BOOST_TEST(dst.info()->is_resizable());
// Create and configure function
NEThreshold thrsh;
thrsh.configure(&src1, &dst, thrshConf.threshold, thrshConf.false_value, thrshConf.true_value, thrshConf.type, thrshConf.upper);
// Validate valid region
const ValidRegion valid_region = shape_to_valid_region(shape);
validate(src1.info()->valid_region(), valid_region);
validate(dst.info()->valid_region(), valid_region);
// Validate padding
const PaddingSize padding(0, required_padding(shape.x(), 16), 0, 0);
validate(src1.info()->padding(), padding);
validate(dst.info()->padding(), padding);
}
BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
BOOST_DATA_TEST_CASE(RunSmall,
SmallShapes() * ThresholdDataset(),
shape, thrshConf)
{
// Compute function
Tensor dst = compute_threshold(shape, thrshConf.threshold, thrshConf.false_value, thrshConf.true_value, thrshConf.type, thrshConf.upper);
// Compute reference
RawTensor ref_dst = Reference::compute_reference_threshold(shape, thrshConf.threshold, thrshConf.false_value, thrshConf.true_value, thrshConf.type, thrshConf.upper);
// Validate output
validate(NEAccessor(dst), ref_dst);
}
BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
BOOST_DATA_TEST_CASE(RunLarge,
LargeShapes() * ThresholdDataset(),
shape, thrshConf)
{
// Compute function
Tensor dst = compute_threshold(shape, thrshConf.threshold, thrshConf.false_value, thrshConf.true_value, thrshConf.type, thrshConf.upper);
// Compute reference
RawTensor ref_dst = Reference::compute_reference_threshold(shape, thrshConf.threshold, thrshConf.false_value, thrshConf.true_value, thrshConf.type, thrshConf.upper);
// Validate output
validate(NEAccessor(dst), ref_dst);
}
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
#endif