Georgios Pinitas | f554be7 | 2018-12-03 16:02:47 +0000 | [diff] [blame] | 1 | /* |
SiCong Li | 4841c97 | 2021-02-03 12:17:35 +0000 | [diff] [blame] | 2 | * Copyright (c) 2018-2021 Arm Limited. |
Georgios Pinitas | f554be7 | 2018-12-03 16:02:47 +0000 | [diff] [blame] | 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | #include "arm_compute/graph.h" |
| 25 | #include "support/ToolchainSupport.h" |
| 26 | #include "utils/CommonGraphOptions.h" |
| 27 | #include "utils/GraphUtils.h" |
| 28 | #include "utils/Utils.h" |
| 29 | |
| 30 | using namespace arm_compute::utils; |
| 31 | using namespace arm_compute::graph::frontend; |
| 32 | using namespace arm_compute::graph_utils; |
| 33 | |
| 34 | /** Example demonstrating how to implement ResNet12 network using the Compute Library's graph API */ |
| 35 | class GraphResNet12Example : public Example |
| 36 | { |
| 37 | public: |
| 38 | GraphResNet12Example() |
| 39 | : cmd_parser(), common_opts(cmd_parser), model_input_width(nullptr), model_input_height(nullptr), common_params(), graph(0, "ResNet12") |
| 40 | { |
| 41 | model_input_width = cmd_parser.add_option<SimpleOption<unsigned int>>("image-width", 192); |
| 42 | model_input_height = cmd_parser.add_option<SimpleOption<unsigned int>>("image-height", 128); |
| 43 | |
| 44 | // Add model id option |
| 45 | model_input_width->set_help("Input image width."); |
| 46 | model_input_height->set_help("Input image height."); |
| 47 | } |
| 48 | GraphResNet12Example(const GraphResNet12Example &) = delete; |
| 49 | GraphResNet12Example &operator=(const GraphResNet12Example &) = delete; |
Matthew Bentham | f5f2391 | 2020-03-05 22:32:16 +0000 | [diff] [blame] | 50 | ~GraphResNet12Example() override = default; |
Georgios Pinitas | f554be7 | 2018-12-03 16:02:47 +0000 | [diff] [blame] | 51 | bool do_setup(int argc, char **argv) override |
| 52 | { |
| 53 | // Parse arguments |
| 54 | cmd_parser.parse(argc, argv); |
Georgios Pinitas | cd60a5f | 2019-08-21 17:06:54 +0100 | [diff] [blame] | 55 | cmd_parser.validate(); |
Georgios Pinitas | f554be7 | 2018-12-03 16:02:47 +0000 | [diff] [blame] | 56 | |
| 57 | // Consume common parameters |
| 58 | common_params = consume_common_graph_parameters(common_opts); |
| 59 | |
| 60 | // Return when help menu is requested |
| 61 | if(common_params.help) |
| 62 | { |
| 63 | cmd_parser.print_help(argv[0]); |
| 64 | return false; |
| 65 | } |
| 66 | |
| 67 | // Get input image width and height |
| 68 | const unsigned int image_width = model_input_width->value(); |
| 69 | const unsigned int image_height = model_input_height->value(); |
| 70 | |
| 71 | // Checks |
| 72 | ARM_COMPUTE_EXIT_ON_MSG(arm_compute::is_data_type_quantized_asymmetric(common_params.data_type), "QASYMM8 not supported for this graph"); |
| 73 | |
| 74 | // Print parameter values |
| 75 | std::cout << common_params << std::endl; |
| 76 | std::cout << "Image width: " << image_width << std::endl; |
| 77 | std::cout << "Image height: " << image_height << std::endl; |
| 78 | |
| 79 | // Get trainable parameters data path |
| 80 | const std::string data_path = common_params.data_path; |
| 81 | const std::string model_path = "/cnn_data/resnet12_model/"; |
| 82 | |
| 83 | // Create a preprocessor object |
Georgios Pinitas | 40f51a6 | 2020-11-21 03:04:18 +0000 | [diff] [blame] | 84 | std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(); |
Georgios Pinitas | f554be7 | 2018-12-03 16:02:47 +0000 | [diff] [blame] | 85 | |
| 86 | // Create input descriptor |
Georgios Pinitas | 450dfb1 | 2021-06-15 10:11:47 +0100 | [diff] [blame] | 87 | const TensorShape tensor_shape = permute_shape(TensorShape(image_width, image_height, 3U, common_params.batches), DataLayout::NCHW, common_params.data_layout); |
Georgios Pinitas | f554be7 | 2018-12-03 16:02:47 +0000 | [diff] [blame] | 88 | TensorDescriptor input_descriptor = TensorDescriptor(tensor_shape, common_params.data_type).set_layout(common_params.data_layout); |
| 89 | |
| 90 | // Set weights trained layout |
| 91 | const DataLayout weights_layout = DataLayout::NCHW; |
| 92 | |
| 93 | graph << common_params.target |
| 94 | << common_params.fast_math_hint |
| 95 | << InputLayer(input_descriptor, get_input_accessor(common_params, std::move(preprocessor), false /* Do not convert to BGR */)) |
| 96 | << ConvolutionLayer( |
| 97 | 9U, 9U, 64U, |
| 98 | get_weights_accessor(data_path, "conv1_weights.npy", weights_layout), |
| 99 | get_weights_accessor(data_path, "conv1_biases.npy", weights_layout), |
| 100 | PadStrideInfo(1, 1, 4, 4)) |
| 101 | .set_name("conv1/convolution") |
| 102 | << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv1/Relu"); |
| 103 | |
| 104 | add_residual_block(data_path, "block1", weights_layout); |
| 105 | add_residual_block(data_path, "block2", weights_layout); |
| 106 | add_residual_block(data_path, "block3", weights_layout); |
| 107 | add_residual_block(data_path, "block4", weights_layout); |
| 108 | |
| 109 | graph << ConvolutionLayer( |
| 110 | 3U, 3U, 64U, |
| 111 | get_weights_accessor(data_path, "conv10_weights.npy", weights_layout), |
| 112 | get_weights_accessor(data_path, "conv10_biases.npy"), |
| 113 | PadStrideInfo(1, 1, 1, 1)) |
| 114 | .set_name("conv10/convolution") |
| 115 | << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv10/Relu") |
| 116 | << ConvolutionLayer( |
| 117 | 3U, 3U, 64U, |
| 118 | get_weights_accessor(data_path, "conv11_weights.npy", weights_layout), |
| 119 | get_weights_accessor(data_path, "conv11_biases.npy"), |
| 120 | PadStrideInfo(1, 1, 1, 1)) |
| 121 | .set_name("conv11/convolution") |
| 122 | << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv11/Relu") |
| 123 | << ConvolutionLayer( |
| 124 | 9U, 9U, 3U, |
| 125 | get_weights_accessor(data_path, "conv12_weights.npy", weights_layout), |
| 126 | get_weights_accessor(data_path, "conv12_biases.npy"), |
| 127 | PadStrideInfo(1, 1, 4, 4)) |
| 128 | .set_name("conv12/convolution") |
| 129 | << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH)).set_name("conv12/Tanh") |
| 130 | << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LINEAR, 0.58f, 0.5f)).set_name("conv12/Linear") |
Georgios Pinitas | 40f51a6 | 2020-11-21 03:04:18 +0000 | [diff] [blame] | 131 | << OutputLayer(std::make_unique<DummyAccessor>(0)); |
Georgios Pinitas | f554be7 | 2018-12-03 16:02:47 +0000 | [diff] [blame] | 132 | |
| 133 | // Finalize graph |
| 134 | GraphConfig config; |
| 135 | config.num_threads = common_params.threads; |
| 136 | config.use_tuner = common_params.enable_tuner; |
Vidhya Sudhan Loganathan | 050471e | 2019-04-25 09:27:24 +0100 | [diff] [blame] | 137 | config.tuner_mode = common_params.tuner_mode; |
Michele Di Giorgio | 1df9cca | 2019-01-17 13:20:32 +0000 | [diff] [blame] | 138 | config.tuner_file = common_params.tuner_file; |
SiCong Li | 4841c97 | 2021-02-03 12:17:35 +0000 | [diff] [blame] | 139 | config.mlgo_file = common_params.mlgo_file; |
Michele Di Giorgio | 1df9cca | 2019-01-17 13:20:32 +0000 | [diff] [blame] | 140 | |
Georgios Pinitas | f554be7 | 2018-12-03 16:02:47 +0000 | [diff] [blame] | 141 | graph.finalize(common_params.target, config); |
| 142 | |
| 143 | return true; |
| 144 | } |
| 145 | |
| 146 | void do_run() override |
| 147 | { |
| 148 | // Run graph |
| 149 | graph.run(); |
| 150 | } |
| 151 | |
| 152 | private: |
| 153 | CommandLineParser cmd_parser; |
| 154 | CommonGraphOptions common_opts; |
| 155 | SimpleOption<unsigned int> *model_input_width{ nullptr }; |
| 156 | SimpleOption<unsigned int> *model_input_height{ nullptr }; |
| 157 | CommonGraphParams common_params; |
| 158 | Stream graph; |
| 159 | |
| 160 | void add_residual_block(const std::string &data_path, const std::string &name, DataLayout weights_layout) |
| 161 | { |
| 162 | std::stringstream unit_path_ss; |
| 163 | unit_path_ss << data_path << name << "_"; |
| 164 | std::stringstream unit_name_ss; |
| 165 | unit_name_ss << name << "/"; |
| 166 | |
| 167 | std::string unit_path = unit_path_ss.str(); |
| 168 | std::string unit_name = unit_name_ss.str(); |
| 169 | |
| 170 | SubStream left(graph); |
| 171 | SubStream right(graph); |
| 172 | |
| 173 | right << ConvolutionLayer( |
| 174 | 3U, 3U, 64U, |
| 175 | get_weights_accessor(data_path, unit_path + "conv1_weights.npy", weights_layout), |
| 176 | get_weights_accessor(data_path, unit_path + "conv1_biases.npy", weights_layout), |
| 177 | PadStrideInfo(1, 1, 1, 1)) |
| 178 | .set_name(unit_name + "conv1/convolution") |
| 179 | << BatchNormalizationLayer( |
| 180 | get_weights_accessor(data_path, unit_path + "conv1_BatchNorm_moving_mean.npy"), |
| 181 | get_weights_accessor(data_path, unit_path + "conv1_BatchNorm_moving_variance.npy"), |
| 182 | get_weights_accessor(data_path, unit_path + "conv1_BatchNorm_gamma.npy"), |
| 183 | get_weights_accessor(data_path, unit_path + "conv1_BatchNorm_beta.npy"), |
| 184 | 0.0000100099996416f) |
| 185 | .set_name(unit_name + "conv1/BatchNorm") |
| 186 | << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name(unit_name + "conv1/Relu") |
| 187 | |
| 188 | << ConvolutionLayer( |
| 189 | 3U, 3U, 64U, |
| 190 | get_weights_accessor(data_path, unit_path + "conv2_weights.npy", weights_layout), |
| 191 | get_weights_accessor(data_path, unit_path + "conv2_biases.npy", weights_layout), |
| 192 | PadStrideInfo(1, 1, 1, 1)) |
| 193 | .set_name(unit_name + "conv2/convolution") |
| 194 | << BatchNormalizationLayer( |
| 195 | get_weights_accessor(data_path, unit_path + "conv2_BatchNorm_moving_mean.npy"), |
| 196 | get_weights_accessor(data_path, unit_path + "conv2_BatchNorm_moving_variance.npy"), |
| 197 | get_weights_accessor(data_path, unit_path + "conv2_BatchNorm_gamma.npy"), |
| 198 | get_weights_accessor(data_path, unit_path + "conv2_BatchNorm_beta.npy"), |
| 199 | 0.0000100099996416f) |
| 200 | .set_name(unit_name + "conv2/BatchNorm") |
| 201 | << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name(unit_name + "conv2/Relu"); |
| 202 | |
| 203 | graph << EltwiseLayer(std::move(left), std::move(right), EltwiseOperation::Add).set_name(unit_name + "add"); |
| 204 | } |
| 205 | }; |
| 206 | |
| 207 | /** Main program for ResNet12 |
| 208 | * |
| 209 | * Model is based on: |
| 210 | * https://arxiv.org/pdf/1709.01118.pdf |
| 211 | * "WESPE: Weakly Supervised Photo Enhancer for Digital Cameras" |
| 212 | * Andrey Ignatov, Nikolay Kobyshev, Kenneth Vanhoey, Radu Timofte, Luc Van Gool |
| 213 | * |
| 214 | * @note To list all the possible arguments execute the binary appended with the --help option |
| 215 | * |
| 216 | * @param[in] argc Number of arguments |
| 217 | * @param[in] argv Arguments |
| 218 | */ |
| 219 | int main(int argc, char **argv) |
| 220 | { |
| 221 | return arm_compute::utils::run_example<GraphResNet12Example>(argc, argv); |
| 222 | } |