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/*
* Copyright (c) 2017-2019 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/CL/CLTensor.h"
#include "arm_compute/runtime/CL/CLTensorAllocator.h"
#include "arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h"
#include "arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h"
#include "tests/CL/CLAccessor.h"
#include "tests/benchmark/fixtures/ConvolutionLayerFixture.h"
#include "tests/benchmark/fixtures/FFTConvolutionLayerFixture.h"
#include "tests/benchmark/fixtures/WinogradConvolutionLayerFixture.h"
#include "tests/datasets/system_tests/alexnet/AlexNetConvolutionLayerDataset.h"
#include "tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1ConvolutionLayerDataset.h"
#include "tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4ConvolutionLayerDataset.h"
#include "tests/datasets/system_tests/lenet5/LeNet5ConvolutionLayerDataset.h"
#include "tests/datasets/system_tests/mobilenet/MobileNetConvolutionLayerDataset.h"
#include "tests/datasets/system_tests/squeezenet/SqueezeNetConvolutionLayerDataset.h"
#include "tests/datasets/system_tests/vgg/vgg16/VGG16ConvolutionLayerDataset.h"
#include "tests/datasets/system_tests/yolo/v2/YOLOV2ConvolutionLayerDataset.h"
#include "tests/framework/Macros.h"
#include "tests/framework/datasets/Datasets.h"
#include "utils/TypePrinter.h"
#include <arm_compute/runtime/CL/functions/CLFFTConvolutionLayer.h>
#include <tests/datasets/SmallConvolutionLayerDataset.h>
#include <tests/datasets/system_tests/resnet12/ResNet12ConvolutionLayerDataset.h>
namespace arm_compute
{
namespace test
{
namespace benchmark
{
namespace
{
const auto data_types = framework::dataset::make("DataType", { DataType::F16, DataType::F32, DataType::QASYMM8 });
} // namespace
TEST_SUITE(CL)
using CLGEMMConvolutionLayerFixture = ConvolutionLayerFixture<CLTensor, CLGEMMConvolutionLayer, CLAccessor>;
using CLWinogradLayerFixture = WinogradConvolutionLayerFixture<CLTensor, CLWinogradConvolutionLayer, CLAccessor>;
using CLFFTConvolutionLayerFixture = FFTConvolutionLayerFixture<CLTensor, CLFFTConvolutionLayer, CLAccessor>;
REGISTER_FIXTURE_DATA_TEST_CASE(ResNet12FFTLayer, CLFFTConvolutionLayerFixture, framework::DatasetMode::ALL,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::ResNet12FFTConvolutionLayerDataset(),
framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
framework::dataset::make("DataType", { DataType::F32 })),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetWinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::ALL,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetWinogradLayerDataset(),
framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
framework::dataset::make("DataType", { DataType::F16, DataType::F32 })),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1WinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::ALL,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1WinogradLayerDataset(),
framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
framework::dataset::make("DataType", { DataType::F16, DataType::F32 })),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4WinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::ALL,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4WinogradLayerDataset(),
framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
framework::dataset::make("DataType", { DataType::F16, DataType::F32 })),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetWinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::ALL,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetWinogradLayerDataset(),
framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
framework::dataset::make("DataType", { DataType::F16, DataType::F32 })),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::ALL,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo",
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
data_types),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::ALL,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::ALL,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo",
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
data_types),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::ALL,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo",
ActivationLayerInfo())),
data_types),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::ALL,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo",
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
data_types),
framework::dataset::make("Batches", 1)));
REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::ALL,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo",
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
data_types),
framework::dataset::make("Batches", 1)));
TEST_SUITE(NIGHTLY)
REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo",
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
data_types),
framework::dataset::make("Batches", { 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("Batches", { 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo",
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
data_types),
framework::dataset::make("Batches", { 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo",
ActivationLayerInfo())),
data_types),
framework::dataset::make("Batches", { 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo",
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
data_types),
framework::dataset::make("Batches", { 4, 8 })));
// 8 batches use about 1.8GB of memory which is too much for most devices!
REGISTER_FIXTURE_DATA_TEST_CASE(VGG16ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo",
ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
data_types),
framework::dataset::make("Batches", { 1, 4 })));
REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
data_types),
framework::dataset::make("Batches", { 1, 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetWinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::NIGHTLY,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetWinogradLayerDataset(),
framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
framework::dataset::make("DataType", { DataType::F16, DataType::F32 })),
framework::dataset::make("Batches", { 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1WinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::NIGHTLY,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1WinogradLayerDataset(),
framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
framework::dataset::make("DataType", { DataType::F16, DataType::F32 })),
framework::dataset::make("Batches", { 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4WinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::NIGHTLY,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4WinogradLayerDataset(),
framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
framework::dataset::make("DataType", { DataType::F16, DataType::F32 })),
framework::dataset::make("Batches", { 4, 8 })));
REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetWinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::NIGHTLY,
framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetWinogradLayerDataset(),
framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
framework::dataset::make("DataType", { DataType::F16, DataType::F32 })),
framework::dataset::make("Batches", { 4, 8 })));
TEST_SUITE_END()
TEST_SUITE_END()
} // namespace benchmark
} // namespace test
} // namespace arm_compute
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