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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 "CL/CLAccessor.h"
#include "CL/CLArrayAccessor.h"
#include "TypePrinter.h"
#include "arm_compute/runtime/CL/CLArray.h"
#include "arm_compute/runtime/CL/functions/CLROIPoolingLayer.h"
#include "tests/Globals.h"
#include "tests/Utils.h"
#include "validation/Datasets.h"
#include "validation/Reference.h"
#include "validation/Validation.h"
#include "validation/ValidationUserConfiguration.h"
#include <random>
#include <vector>
using namespace arm_compute;
using namespace arm_compute::test;
using namespace arm_compute::test::validation;
namespace
{
CLTensor compute_roi_pooling_layer(const TensorShape &shape, DataType dt, const std::vector<ROI> &rois, ROIPoolingLayerInfo pool_info)
{
TensorShape shape_dst;
shape_dst.set(0, pool_info.pooled_width());
shape_dst.set(1, pool_info.pooled_height());
shape_dst.set(2, shape.z());
shape_dst.set(3, rois.size());
// Create tensors
CLTensor src = create_tensor<CLTensor>(shape, dt);
CLTensor dst = create_tensor<CLTensor>(shape_dst, dt);
// Create ROI array
CLArray<ROI> rois_array(rois.size());
fill_array(CLArrayAccessor<ROI>(rois_array), rois);
// Create and configure function
CLROIPoolingLayer roi_pool;
roi_pool.configure(&src, &rois_array, &dst, pool_info);
// Allocate tensors
src.allocator()->allocate();
dst.allocator()->allocate();
BOOST_TEST(!src.info()->is_resizable());
BOOST_TEST(!dst.info()->is_resizable());
// Fill tensors
std::uniform_real_distribution<> distribution(-1, 1);
library->fill(CLAccessor(src), distribution, 0);
// Compute function
roi_pool.run();
return dst;
}
} // namespace
#ifndef DOXYGEN_SKIP_THIS
BOOST_AUTO_TEST_SUITE(CL)
BOOST_AUTO_TEST_SUITE(ROIPoolingLayer)
BOOST_AUTO_TEST_SUITE(Float)
BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ DataType::F16, DataType::F32 }) * boost::unit_test::data::make({ 10, 20, 40 }) * boost::unit_test::data::make({ 7, 9 }) *
boost::unit_test::data::make({ 1.f / 8.f, 1.f / 16.f }),
dt, num_rois, roi_pool_size, roi_scale)
{
TensorShape shape(50U, 47U, 2U, 3U);
ROIPoolingLayerInfo pool_info(roi_pool_size, roi_pool_size, roi_scale);
// Construct ROI vector
std::vector<ROI> rois = generate_random_rois(shape, pool_info, num_rois, user_config.seed);
// Compute function
CLTensor dst = compute_roi_pooling_layer(shape, dt, rois, pool_info);
// Compute reference
RawTensor ref_dst = Reference::compute_reference_roi_pooling_layer(shape, dt, rois, pool_info);
// Validate output
validate(CLAccessor(dst), ref_dst);
}
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
#endif /* DOXYGEN_SKIP_THIS */
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