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+/*
+ * 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/Helper.h"
+#include "NEON/NEAccessor.h"
+#include "TensorLibrary.h"
+#include "benchmark/Datasets.h"
+#include "benchmark/Profiler.h"
+#include "benchmark/WallClockTimer.h"
+
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/NEON/functions/NEPoolingLayer.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/PoolingLayer.h"
+
+namespace
+{
+using PoolingLayerAlexNetF32 = PoolingLayer<AlexNetPoolingLayerDataset, Tensor, NEAccessor, NEPoolingLayer>;
+using PoolingLayerAlexNetQS8 = PoolingLayer<AlexNetPoolingLayerDataset, Tensor, NEAccessor, NEPoolingLayer, DataType::QS8>;
+using PoolingLayerLeNet5 = PoolingLayer<LeNet5PoolingLayerDataset, Tensor, NEAccessor, NEPoolingLayer>;
+using PoolingLayerGoogLeNet = PoolingLayer<GoogLeNetPoolingLayerDataset, Tensor, NEAccessor, NEPoolingLayer>;
+} // namespace
+
+// F32
+BENCHMARK_DEFINE_F(PoolingLayerAlexNetF32, neon_alexnet)
+(::benchmark::State &state)
+{
+ while(state.KeepRunning())
+ {
+ // Run function
+ profiler.start();
+ pool_layer.run();
+ profiler.stop();
+ }
+}
+
+BENCHMARK_REGISTER_F(PoolingLayerAlexNetF32, neon_alexnet)
+->Threads(1)
+->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 0, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerAlexNetF32, neon_alexnet)
+->Threads(1)
+->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 1, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerAlexNetF32, neon_alexnet)
+->Threads(1)
+->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 2, 1, 4, 8>);
+
+// QS8
+BENCHMARK_DEFINE_F(PoolingLayerAlexNetQS8, neon_alexnet)
+(::benchmark::State &state)
+{
+ while(state.KeepRunning())
+ {
+ // Run function
+ profiler.start();
+ pool_layer.run();
+ profiler.stop();
+ }
+}
+
+BENCHMARK_REGISTER_F(PoolingLayerAlexNetQS8, neon_alexnet)
+->Threads(1)
+->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 0, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerAlexNetQS8, neon_alexnet)
+->Threads(1)
+->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 1, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerAlexNetQS8, neon_alexnet)
+->Threads(1)
+->Apply(DataSetArgBatched<AlexNetPoolingLayerDataset, 2, 1, 4, 8>);
+
+BENCHMARK_DEFINE_F(PoolingLayerLeNet5, neon_lenet5)
+(::benchmark::State &state)
+{
+ while(state.KeepRunning())
+ {
+ // Run function
+ profiler.start();
+ pool_layer.run();
+ profiler.stop();
+ }
+}
+
+BENCHMARK_REGISTER_F(PoolingLayerLeNet5, neon_lenet5)
+->Threads(1)
+->Apply(DataSetArgBatched<LeNet5PoolingLayerDataset, 0, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerLeNet5, neon_lenet5)
+->Threads(1)
+->Apply(DataSetArgBatched<LeNet5PoolingLayerDataset, 1, 1, 4, 8>);
+
+BENCHMARK_DEFINE_F(PoolingLayerGoogLeNet, neon_googlenet)
+(::benchmark::State &state)
+{
+ while(state.KeepRunning())
+ {
+ // Run function
+ profiler.start();
+ pool_layer.run();
+ profiler.stop();
+ }
+}
+
+// FIXME: Add support for 7x7 pooling layer pool5/7x7_s1
+BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
+->Threads(1)
+->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 0, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
+->Threads(1)
+->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 1, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
+->Threads(1)
+->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 2, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
+->Threads(1)
+->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 3, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
+->Threads(1)
+->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 4, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
+->Threads(1)
+->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 5, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
+->Threads(1)
+->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 6, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
+->Threads(1)
+->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 7, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
+->Threads(1)
+->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 8, 1, 4, 8>);
+BENCHMARK_REGISTER_F(PoolingLayerGoogLeNet, neon_googlenet)
+->Threads(1)
+->Apply(DataSetArgBatched<GoogLeNetPoolingLayerDataset, 9, 1, 4, 8>);