From 51d15cc106d711648086fdc575fbd4ed773e5471 Mon Sep 17 00:00:00 2001 From: cc <52520497+juncaipeng@users.noreply.github.com> Date: Sun, 1 Mar 2020 15:11:37 +0800 Subject: [PATCH] Update benchmark to support setting model and param filename (#2993) * Update benchmark to support setting model and param filename --- lite/api/benchmark.cc | 86 ++++++++++++++++++++----------------------- 1 file changed, 40 insertions(+), 46 deletions(-) diff --git a/lite/api/benchmark.cc b/lite/api/benchmark.cc index ee236c1918..d53de7bf2e 100644 --- a/lite/api/benchmark.cc +++ b/lite/api/benchmark.cc @@ -29,22 +29,22 @@ DEFINE_string(model_dir, "", - "the path of the model, set model_dir when the model is no " - "combined formate. This option will be ignored if model_file " - "and param_file are exist."); -DEFINE_string(model_file, + "the path of the model, the model and param files is under " + "model_dir."); +DEFINE_string(model_filename, "", - "the path of model file, set model_file when the model is " - "combined formate."); -DEFINE_string(param_file, + "the filename of model file. When the model is combined formate, " + "please set model_file."); +DEFINE_string(param_filename, "", - "the path of param file, set param_file when the model is " + "the filename of param file, set param_file when the model is " "combined formate."); DEFINE_string(input_shape, "1,3,224,224", "set input shapes according to the model, " "separated by colon and comma, " - "such as 1,3,244,244:1,3,300,300."); + "such as 1,3,244,244"); +DEFINE_string(input_img_path, "", "the path of input image"); DEFINE_int32(warmup, 0, "warmup times"); DEFINE_int32(repeats, 1, "repeats times"); DEFINE_int32(power_mode, @@ -77,12 +77,13 @@ inline double GetCurrentUS() { return 1e+6 * time.tv_sec + time.tv_usec; } -void OutputOptModel(const std::string& save_optimized_model_dir, - const std::vector>& input_shapes) { +void OutputOptModel(const std::string& save_optimized_model_dir) { lite_api::CxxConfig config; config.set_model_dir(FLAGS_model_dir); - config.set_model_file(FLAGS_model_file); - config.set_param_file(FLAGS_param_file); + if (!FLAGS_model_filename.empty() && !FLAGS_param_filename.empty()) { + config.set_model_file(FLAGS_model_dir + "/" + FLAGS_model_filename); + config.set_param_file(FLAGS_model_dir + "/" + FLAGS_param_filename); + } std::vector vaild_places = { Place{TARGET(kARM), PRECISION(kFloat)}, }; @@ -106,7 +107,7 @@ void OutputOptModel(const std::string& save_optimized_model_dir, } #ifdef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK -void Run(const std::vector>& input_shapes, +void Run(const std::vector& input_shape, const std::string& model_dir, const std::string model_name) { // set config and create predictor @@ -118,17 +119,27 @@ void Run(const std::vector>& input_shapes, auto predictor = lite_api::CreatePaddlePredictor(config); // set input - for (int j = 0; j < input_shapes.size(); ++j) { - auto input_tensor = predictor->GetInput(j); - input_tensor->Resize(input_shapes[j]); - auto input_data = input_tensor->mutable_data(); - int input_num = 1; - for (size_t i = 0; i < input_shapes[j].size(); ++i) { - input_num *= input_shapes[j][i]; - } + auto input_tensor = predictor->GetInput(0); + input_tensor->Resize(input_shape); + auto input_data = input_tensor->mutable_data(); + int input_num = 1; + for (size_t i = 0; i < input_shape.size(); ++i) { + input_num *= input_shape[i]; + } + if (FLAGS_input_img_path.empty()) { for (int i = 0; i < input_num; ++i) { input_data[i] = 1.f; } + } else { + std::fstream fs(FLAGS_input_img_path); + if (!fs.is_open()) { + LOG(FATAL) << "open input image " << FLAGS_input_img_path << " error."; + } + for (int i = 0; i < input_num; i++) { + fs >> input_data[i]; + } + // LOG(INFO) << "input data:" << input_data[0] << " " << + // input_data[input_num-1]; } // warmup @@ -175,25 +186,12 @@ int main(int argc, char** argv) { exit(0); } + if (FLAGS_model_dir.back() == '/') { + FLAGS_model_dir.pop_back(); + } std::size_t found = FLAGS_model_dir.find_last_of("/"); std::string model_name = FLAGS_model_dir.substr(found + 1); - std::string save_optimized_model_dir = FLAGS_model_dir + "opt2"; - - auto split_string = - [](const std::string& str_in) -> std::vector { - std::vector str_out; - std::string tmp_str = str_in; - while (!tmp_str.empty()) { - size_t next_offset = tmp_str.find(":"); - str_out.push_back(tmp_str.substr(0, next_offset)); - if (next_offset == std::string::npos) { - break; - } else { - tmp_str = tmp_str.substr(next_offset + 1); - } - } - return str_out; - }; + std::string save_optimized_model_dir = FLAGS_model_dir + "_opt2"; auto get_shape = [](const std::string& str_shape) -> std::vector { std::vector shape; @@ -211,22 +209,18 @@ int main(int argc, char** argv) { return shape; }; - std::vector str_input_shapes = split_string(FLAGS_input_shape); - std::vector> input_shapes; - for (size_t i = 0; i < str_input_shapes.size(); ++i) { - input_shapes.push_back(get_shape(str_input_shapes[i])); - } + std::vector input_shape = get_shape(FLAGS_input_shape); // Output optimized model if needed if (FLAGS_run_model_optimize) { - paddle::lite_api::OutputOptModel(save_optimized_model_dir, input_shapes); + paddle::lite_api::OutputOptModel(save_optimized_model_dir); } #ifdef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK // Run inference using optimized model std::string run_model_dir = FLAGS_run_model_optimize ? save_optimized_model_dir : FLAGS_model_dir; - paddle::lite_api::Run(input_shapes, run_model_dir, model_name); + paddle::lite_api::Run(input_shape, run_model_dir, model_name); #endif return 0; } -- GitLab