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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.
+ */
+#ifndef __ARM_COMPUTE_TEST_BENCHMARK_LENET5_H__
+#define __ARM_COMPUTE_TEST_BENCHMARK_LENET5_H__
+
+#include "TensorLibrary.h"
+#include "Utils.h"
+
+#include "benchmark/Profiler.h"
+#include "benchmark/WallClockTimer.h"
+
+#include "model_objects/LeNet5.h"
+
+using namespace arm_compute;
+using namespace arm_compute::test;
+using namespace arm_compute::test::benchmark;
+
+namespace arm_compute
+{
+namespace test
+{
+namespace benchmark
+{
+template <typename TensorType,
+ typename Accessor,
+ typename ActivationLayerFunction,
+ typename ConvolutionLayerFunction,
+ typename FullyConnectedLayerFunction,
+ typename PoolingLayerFunction,
+ typename SoftmaxLayerFunction>
+class LeNet5Fixture : public ::benchmark::Fixture
+{
+public:
+ void SetUp(::benchmark::State &state) override
+ {
+ profiler.add(std::make_shared<WallClockTimer>());
+
+ network.build(static_cast<unsigned int>(state.range(0)));
+ network.fill_random();
+ }
+
+ void TearDown(::benchmark::State &state) override
+ {
+ profiler.submit(state);
+ network.clear();
+ }
+
+ Profiler profiler{};
+ model_objects::LeNet5<TensorType,
+ Accessor,
+ ActivationLayerFunction,
+ ConvolutionLayerFunction,
+ FullyConnectedLayerFunction,
+ PoolingLayerFunction,
+ SoftmaxLayerFunction>
+ network{};
+};
+} // namespace benchmark
+} // namespace test
+} // namespace arm_compute
+#endif //__ARM_COMPUTE_TEST_BENCHMARK_LENET5_H__