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/*
* Copyright (c) 2017-2018 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 "arm_compute/core/TensorShape.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h"
#include "arm_compute/runtime/Tensor.h"
#include "arm_compute/runtime/TensorAllocator.h"
#include "tests/NEON/Accessor.h"
#include "tests/framework/Macros.h"
#include "tests/framework/datasets/Datasets.h"
#include "utils/TypePrinter.h"
#include "tests/benchmark/fixtures/BatchNormalizationLayerFixture.h"
#include "tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4BatchNormalizationLayerDataset.h"
#include "tests/datasets/system_tests/mobilenet/MobileNetBatchNormalizationLayerDataset.h"
#include "tests/datasets/system_tests/yolo/v2/YOLOV2BatchNormalizationLayerDataset.h"
namespace arm_compute
{
namespace test
{
namespace benchmark
{
namespace
{
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
const auto data_types = framework::dataset::make("DataType", { DataType::F16, DataType::F32 });
#else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
const auto data_types = framework::dataset::make("DataType", { DataType::F32 });
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
} // namespace
using NEBatchNormalizationLayerFixture = BatchNormalizationLayerFixture<Tensor, NEBatchNormalizationLayer, Accessor>;
TEST_SUITE(NEON)
REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
combine(combine(combine(combine(combine(datasets::MobileNetBatchNormalizationLayerDataset(),
combine(framework::dataset::make("UseGamma", { false, true }),
framework::dataset::make("UseBeta", { false, true }))),
framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
combine(combine(combine(combine(combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
combine(framework::dataset::make("UseGamma", { false, true }),
framework::dataset::make("UseBeta", { false, true }))),
framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::ALL,
combine(combine(combine(combine(combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
combine(framework::dataset::make("UseGamma", { false, true }),
framework::dataset::make("UseBeta", { false, true }))),
framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
framework::dataset::make("Batches", 1)));
TEST_SUITE(NIGHTLY)
REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetBatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
combine(combine(combine(combine(combine(datasets::MobileNetBatchNormalizationLayerDataset(),
combine(framework::dataset::make("UseGamma", { false, true }),
framework::dataset::make("UseBeta", { false, true }))),
framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
framework::dataset::make("Batches", { 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2BatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
combine(combine(combine(combine(combine(datasets::YOLOV2BatchNormalizationLayerDataset(),
combine(framework::dataset::make("UseGamma", { false, true }),
framework::dataset::make("UseBeta", { false, true }))),
framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
framework::dataset::make("Batches", { 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4BatchNormalizationLayer, NEBatchNormalizationLayerFixture, framework::DatasetMode::NIGHTLY,
combine(combine(combine(combine(combine(datasets::GoogLeNetInceptionV4BatchNormalizationLayerDataset(),
combine(framework::dataset::make("UseGamma", { false, true }),
framework::dataset::make("UseBeta", { false, true }))),
framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("DataLayout", { DataLayout::NCHW })),
framework::dataset::make("Batches", { 4, 8 })));
TEST_SUITE_END()
TEST_SUITE_END()
} // namespace benchmark
} // namespace test
} // namespace arm_compute
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