/* * 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/NEDirectConvolutionLayer.h" #include "arm_compute/runtime/Tensor.h" #include "arm_compute/runtime/TensorAllocator.h" #include "tests/NEON/Accessor.h" #include "tests/benchmark/fixtures/DirectConvolutionLayerFixture.h" #include "tests/datasets/DirectConvolutionLayerDataset.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/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 { // Special data types for networks that need 5x5 direct convolution #ifdef ARM_COMPUTE_ENABLE_F16 const auto data_types = framework::dataset::make("DataType", { DataType::F16, DataType::F32 }); #else /* ARM_COMPUTE_ENABLE_F16 */ const auto data_types = framework::dataset::make("DataType", { DataType::F32 }); #endif /* ARM_COMPUTE_ENABLE_F16 */ } // namespace using NEDirectConvolutionLayerFixture = DirectConvolutionLayerFixture; TEST_SUITE(NEON) REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::ALL, framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::ALL, framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::ALL, framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo())), data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, NEDirectConvolutionLayerFixture, 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))); TEST_SUITE(NIGHTLY) REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo())), data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, NEDirectConvolutionLayerFixture, 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 }))); REGISTER_FIXTURE_DATA_TEST_CASE(VGG16DirectConvolutionLayer, NEDirectConvolutionLayerFixture, 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(YOLOV2DirectConvolutionLayer, NEDirectConvolutionLayerFixture, 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 }))); TEST_SUITE_END() TEST_SUITE_END() } // namespace benchmark } // namespace test } // namespace arm_compute