| /* |
| * 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_CONVOLUTION_LAYER_H__ |
| #define __ARM_COMPUTE_TEST_BENCHMARK_CONVOLUTION_LAYER_H__ |
| |
| #include "TensorLibrary.h" |
| #include "Utils.h" |
| #include "dataset/ConvolutionLayerDataset.h" |
| |
| #include <memory> |
| |
| using namespace arm_compute; |
| using namespace arm_compute::test; |
| using namespace arm_compute::test::benchmark; |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace benchmark |
| { |
| template <typename DataSet, typename TensorType, typename Accessor, typename Function, DataType dt = DataType::F32> |
| class ConvolutionLayer : public ::benchmark::Fixture |
| { |
| public: |
| void SetUp(::benchmark::State &state) override |
| { |
| profiler.add(std::make_shared<WallClockTimer>()); |
| |
| const ConvolutionLayerDataObject conv_obj = *(DataSet().begin() + state.range(0)); |
| |
| // Set batched in source and destination shapes |
| const unsigned int batches = state.range(1); |
| const unsigned int fixed_point_position = 4; |
| TensorShape src_shape = conv_obj.src_shape; |
| TensorShape dst_shape = conv_obj.dst_shape; |
| src_shape.set(3 /* batch */, batches); |
| dst_shape.set(3 /* batch */, batches); |
| |
| // Create tensors |
| src = create_tensor(src_shape, dt, 1, fixed_point_position); |
| weights = create_tensor(conv_obj.weights_shape, dt, 1, fixed_point_position); |
| bias = create_tensor(conv_obj.bias_shape, dt, 1, fixed_point_position); |
| dst = create_tensor(dst_shape, dt, 1, fixed_point_position); |
| |
| // Create and configure function |
| conv_layer = std::unique_ptr<Function>(new Function()); |
| conv_layer->configure(&src, &weights, &bias, &dst, conv_obj.info); |
| |
| // Allocate tensors |
| src.allocator()->allocate(); |
| weights.allocator()->allocate(); |
| bias.allocator()->allocate(); |
| dst.allocator()->allocate(); |
| |
| // Fill tensors |
| library->fill_tensor_uniform(Accessor(src), 0); |
| library->fill_tensor_uniform(Accessor(weights), 1); |
| library->fill_tensor_uniform(Accessor(bias), 2); |
| } |
| |
| void TearDown(::benchmark::State &state) override |
| { |
| conv_layer.reset(); |
| |
| src.allocator()->free(); |
| weights.allocator()->free(); |
| bias.allocator()->free(); |
| dst.allocator()->free(); |
| |
| profiler.submit(state); |
| } |
| |
| std::unique_ptr<Function> conv_layer{ nullptr }; |
| Profiler profiler{}; |
| |
| private: |
| TensorType src{}; |
| TensorType weights{}; |
| TensorType bias{}; |
| TensorType dst{}; |
| }; |
| } // namespace benchmark |
| } // namespace test |
| } // namespace arm_compute |
| #endif //__ARM_COMPUTE_TEST_BENCHMARK_CONVOLUTION_LAYER_H__ |