/* * 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 "Globals.h" #include "NEON/NEAccessor.h" #include "TensorLibrary.h" #include "benchmark/Datasets.h" #include "benchmark/Profiler.h" #include "benchmark/WallClockTimer.h" #include "dataset/ConvolutionLayerDataset.h" #include "arm_compute/core/Helpers.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 "benchmark/benchmark_api.h" using namespace arm_compute; using namespace arm_compute::test; using namespace arm_compute::test::benchmark; using namespace arm_compute::test::neon; #include "benchmark/common/ConvolutionLayer.h" namespace { using ConvolutionLayerDirectAlexNet = ConvolutionLayer; } // namespace BENCHMARK_DEFINE_F(ConvolutionLayerDirectAlexNet, neon_alexnet) (::benchmark::State &state) { while(state.KeepRunning()) { // Run function profiler.start(); conv_layer->run(); profiler.stop(); } } // Registr only the 3x3 convolution layers BENCHMARK_REGISTER_F(ConvolutionLayerDirectAlexNet, neon_alexnet) ->Threads(1) ->Apply(DataSetArgBatched); BENCHMARK_REGISTER_F(ConvolutionLayerDirectAlexNet, neon_alexnet) ->Threads(1) ->Apply(DataSetArgBatched); BENCHMARK_REGISTER_F(ConvolutionLayerDirectAlexNet, neon_alexnet) ->Threads(1) ->Apply(DataSetArgBatched);