| /* |
| * 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/NEConvolutionLayer.h" |
| #include "arm_compute/runtime/NEON/functions/NEWinogradConvolutionLayer.h" |
| #include "arm_compute/runtime/Tensor.h" |
| #include "arm_compute/runtime/TensorAllocator.h" |
| #include "tests/NEON/Accessor.h" |
| #include "tests/benchmark/fixtures/ConvolutionLayerFixture.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" |
| |
| 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, DataType::QASYMM8 }); |
| #else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| const auto data_types = framework::dataset::make("DataType", { DataType::F32, DataType::QASYMM8 }); |
| |
| #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ |
| } // namespace |
| |
| using NEGEMMConvolutionLayerFixture = ConvolutionLayerFixture<Tensor, NEGEMMConvolutionLayer, Accessor>; |
| |
| TEST_SUITE(NEON) |
| #if defined(__aarch64__) |
| using NEWinogradConvolutionLayerFixture = WinogradConvolutionLayerFixture<Tensor, NEWinogradConvolutionLayer, Accessor>; |
| |
| REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetWinogradLayer, NEWinogradConvolutionLayerFixture, 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::F32)), |
| framework::dataset::make("Batches", 1))); |
| |
| REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1WinogradLayer, NEWinogradConvolutionLayerFixture, 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::F32)), |
| framework::dataset::make("Batches", 1))); |
| |
| REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4WinogradLayer, NEWinogradConvolutionLayerFixture, framework::DatasetMode::ALL, |
| framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4WinogradLayerDataset(), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo())), |
| framework::dataset::make("DataType", DataType::F32)), |
| framework::dataset::make("Batches", 1))); |
| |
| REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetWinogradLayer, NEWinogradConvolutionLayerFixture, framework::DatasetMode::ALL, |
| framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetWinogradLayerDataset(), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo())), |
| framework::dataset::make("DataType", DataType::F32)), |
| framework::dataset::make("Batches", 1))); |
| #endif /* __aarch64__ */ |
| |
| REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, NEGEMMConvolutionLayerFixture, 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, NEGEMMConvolutionLayerFixture, 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, NEGEMMConvolutionLayerFixture, 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, NEGEMMConvolutionLayerFixture, 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, NEGEMMConvolutionLayerFixture, 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, NEGEMMConvolutionLayerFixture, 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, NEGEMMConvolutionLayerFixture, 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, NEGEMMConvolutionLayerFixture, 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, NEGEMMConvolutionLayerFixture, 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, NEGEMMConvolutionLayerFixture, 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, NEGEMMConvolutionLayerFixture, 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 2GB of memory which is too much for most devices! |
| REGISTER_FIXTURE_DATA_TEST_CASE(VGG16ConvolutionLayer, NEGEMMConvolutionLayerFixture, 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, 2 }))); |
| |
| REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2ConvolutionLayer, NEGEMMConvolutionLayerFixture, 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 }))); |
| |
| #if defined(__aarch64__) |
| REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetWinogradLayer, NEWinogradConvolutionLayerFixture, 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::F32)), |
| framework::dataset::make("Batches", { 4, 8 }))); |
| |
| REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1WinogradLayer, NEWinogradConvolutionLayerFixture, 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::F32)), |
| framework::dataset::make("Batches", { 4, 8 }))); |
| |
| REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4WinogradLayer, NEWinogradConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, |
| framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4WinogradLayerDataset(), |
| framework::dataset::make("ActivationInfo", ActivationLayerInfo())), |
| framework::dataset::make("DataType", DataType::F32)), |
| framework::dataset::make("Batches", { 4, 8 }))); |
| |
| REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetWinogradLayer, NEWinogradConvolutionLayerFixture, 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::F32)), |
| framework::dataset::make("Batches", { 4, 8 }))); |
| #endif /* __aarch64__ */ |
| |
| TEST_SUITE_END() |
| TEST_SUITE_END() |
| } // namespace benchmark |
| } // namespace test |
| } // namespace arm_compute |