diff --git a/samples/cpp/benchmark_app/inputs_filling.cpp b/samples/cpp/benchmark_app/inputs_filling.cpp index 6665bfa644d..7468fb858aa 100644 --- a/samples/cpp/benchmark_app/inputs_filling.cpp +++ b/samples/cpp/benchmark_app/inputs_filling.cpp @@ -366,7 +366,7 @@ ov::Tensor get_random_tensor(const std::pair(input_shape, ",")); input_shape << shape.back(); - slog::info << " " << item.first << ": " << get_shape_string(item.second.dataShape); + slog::info << " " << item.first << " : " << item.second.dataShape; } slog::info << slog::endl; diff --git a/samples/cpp/benchmark_app/utils.cpp b/samples/cpp/benchmark_app/utils.cpp index b3ad6bc776a..2b97b15072b 100644 --- a/samples/cpp/benchmark_app/utils.cpp +++ b/samples/cpp/benchmark_app/utils.cpp @@ -209,12 +209,6 @@ size_t get_batch_size(const benchmark_app::InputsInfo& inputs_info) { return batch_size; } -std::string get_shape_string(const ov::Shape& shape) { - std::stringstream ss; - ss << shape; - return ss.str(); -} - std::string get_shapes_string(const benchmark_app::PartialShapes& shapes) { std::stringstream ss; for (auto& shape : shapes) { @@ -264,36 +258,6 @@ std::map> parse_scale_or_mean(const std::string& return return_value; } -std::vector parse_partial_shape(const std::string& partial_shape) { - std::vector shape; - for (auto& dim : split(partial_shape, ',')) { - if (dim == "?" || dim == "-1") { - shape.push_back(ngraph::Dimension::dynamic()); - } else { - const std::string range_divider = ".."; - size_t range_index = dim.find(range_divider); - if (range_index != std::string::npos) { - std::string min = dim.substr(0, range_index); - std::string max = dim.substr(range_index + range_divider.length()); - shape.push_back(ngraph::Dimension(min.empty() ? 0 : std::stoi(min), - max.empty() ? ngraph::Interval::s_max : std::stoi(max))); - } else { - shape.push_back(std::stoi(dim)); - } - } - } - - return shape; -} - -ov::Shape parse_data_shape(const std::string& dataShapeStr) { - std::vector shape; - for (auto& dim : split(dataShapeStr, ',')) { - shape.push_back(std::stoi(dim)); - } - return shape; -} - std::pair> parse_input_files(const std::string& file_paths_string) { auto search_string = file_paths_string; std::string input_name = ""; @@ -486,7 +450,7 @@ std::vector get_inputs_info(const std::string& shape_ } std::vector info_maps; - for (size_t i = 0; i < min_size; ++i) { + for (size_t input_id = 0; input_id < min_size; ++input_id) { benchmark_app::InputsInfo info_map; bool is_there_at_least_one_batch_dim = false; @@ -501,7 +465,6 @@ std::vector get_inputs_info(const std::string& shape_ "layout command line parameter doesn't support multiple layouts for one input."); } info.layout = ov::Layout(layout_map.at(name)[0]); - // reshape_required = true; } else { info.layout = dynamic_cast(*item.get_node()).get_layout(); } @@ -544,7 +507,7 @@ std::vector get_inputs_info(const std::string& shape_ throw std::logic_error( "shape command line parameter doesn't support multiple shapes for one input."); } - info.partialShape = parse_partial_shape(shape_map.at(name)[0]); + info.partialShape = shape_map.at(name)[0]; reshape_required = true; } else { info.partialShape = item.get_partial_shape(); @@ -557,7 +520,7 @@ std::vector get_inputs_info(const std::string& shape_ // Tensor Shape if (info.partialShape.is_dynamic() && data_shapes_map.count(name)) { - info.dataShape = parse_data_shape(data_shapes_map.at(name)[i % data_shapes_map.at(name).size()]); + info.dataShape = data_shapes_map.at(name)[input_id % data_shapes_map.at(name).size()]; } else if (info.partialShape.is_dynamic() && fileNames.count(filesInputName) && info.is_image()) { auto& namesVector = fileNames.at(filesInputName); if (contains_binaries(namesVector)) { diff --git a/samples/cpp/benchmark_app/utils.hpp b/samples/cpp/benchmark_app/utils.hpp index ba2fdedd145..0c84832dd6c 100644 --- a/samples/cpp/benchmark_app/utils.hpp +++ b/samples/cpp/benchmark_app/utils.hpp @@ -59,14 +59,11 @@ uint32_t device_default_device_duration_in_seconds(const std::string& device); std::map parse_value_per_device(const std::vector& devices, const std::string& values_string); void parse_value_for_virtual_device(const std::string& device, std::map& values_string); -std::string get_shape_string(const ov::Shape& shape); std::string get_shapes_string(const benchmark_app::PartialShapes& shapes); size_t get_batch_size(const benchmark_app::InputsInfo& inputs_info); std::vector split(const std::string& s, char delim); std::map> parse_scale_or_mean(const std::string& scale_mean, const benchmark_app::InputsInfo& inputs_info); -std::vector parse_partial_shape(const std::string& partial_shape); -ov::Shape parse_data_shape(const std::string& dataShapeStr); std::pair> parse_input_files(const std::string& file_paths_string); std::map> parse_input_arguments(const std::vector& args); diff --git a/tools/benchmark_tool/openvino/tools/benchmark/utils/utils.py b/tools/benchmark_tool/openvino/tools/benchmark/utils/utils.py index 485af64c3c6..81651ec95cf 100644 --- a/tools/benchmark_tool/openvino/tools/benchmark/utils/utils.py +++ b/tools/benchmark_tool/openvino/tools/benchmark/utils/utils.py @@ -143,7 +143,6 @@ def parse_input_output_precision(arg_map: str): def print_inputs_and_outputs_info(model: Model): - inputs = model.inputs logger.info("Model inputs:") for input in inputs: @@ -154,7 +153,7 @@ def print_inputs_and_outputs_info(model: Model): if node_name=="": node_name = "***NO_NAME***" logger.info(f" {in_name} (node: {node_name}) : {input.element_type.get_type_name()} / " - f"{str(input.node.layout)} / {'{'}{','.join(str(x) for x in input.partial_shape)}{'}'}") + f"{str(input.node.layout)} / {input.partial_shape}") outputs = model.outputs logger.info("Model outputs:") @@ -166,7 +165,7 @@ def print_inputs_and_outputs_info(model: Model): if node_name=="": node_name = "***NO_NAME***" logger.info(f" {out_name} (node: {node_name}) : {output.element_type.get_type_name()} / " - f"{str(output.node.layout)} / {'{'}{','.join(str(x) for x in output.partial_shape)}{'}'}") + f"{str(output.node.layout)} / {output.partial_shape}") def get_number_iterations(number_iterations: int, nireq: int, num_shapes: int, api_type: str):