443 lines
19 KiB
C++
443 lines
19 KiB
C++
// Copyright (C) 2018-2020 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#include <cstdlib>
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#include <iostream>
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#include <fstream>
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#include <algorithm>
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#include <chrono>
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#include <unordered_map>
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#include <map>
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#include <vector>
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#include <string>
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#include <gflags/gflags.h>
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#include "inference_engine.hpp"
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#include <vpu/vpu_plugin_config.hpp>
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#include <vpu/private_plugin_config.hpp>
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#include <vpu/utils/string.hpp>
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#include "samples/common.hpp"
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static constexpr char help_message[] = "Optional. Print the usage message.";
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static constexpr char model_message[] = "Required. Path to the XML model.";
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static constexpr char targetDeviceMessage[] = "Required. Specify a target device for which executable network will be compiled."
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"Use \"-d HETERO:<comma-separated_devices_list>\" format to specify HETERO plugin. "
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"Use \"-d MULTI:<comma-separated_devices_list>\" format to specify MULTI plugin. "
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"The application looks for a suitable plugin for the specified device.";
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static constexpr char output_message[] = "Optional. Path to the output file. Default value: \"<model_xml_file>.blob\".";
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static constexpr char config_message[] = "Optional. Path to the configuration file. Default value: \"config\".";
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static constexpr char number_of_shaves_message[] = "Optional. Specifies number of shaves."
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" Should be set with \"VPU_NUMBER_OF_CMX_SLICES\"."
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" Overwrites value from config.";
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static constexpr char number_of_cmx_slices_message[] = "Optional. Specifies number of CMX slices."
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" Should be set with \"VPU_NUMBER_OF_SHAVES\"."
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" Overwrites value from config.";
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static constexpr char tiling_cmx_limit_message[] = "Optional. Specifies CMX limit for data tiling."
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" Value should be equal or greater than -1."
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" Overwrites value from config.";
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static constexpr char inputs_precision_message[] = "Optional. Specifies precision for all input layers of the network."
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" Supported values: FP32, FP16, U8. Default value: FP16.";
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static constexpr char outputs_precision_message[] = "Optional. Specifies precision for all output layers of the network."
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" Supported values: FP32, FP16, U8. Default value: FP16.";
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static constexpr char iop_message[] = "Optional. Specifies precision for input and output layers by name.\n"
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" By default, all inputs and outputs have the FP16 precision.\n"
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" Available precisions: FP32, FP16, U8.\n"
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" Example: -iop \"input:FP16, output:FP16\".\n"
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" Notice that quotes are required.\n"
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" Overwrites precision from ip and op options for specified layers.";
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static constexpr char inputs_layout_message[] = "Optional. Specifies layout for all input layers of the network."
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" Supported values: NCHW, NHWC, NC, C.";
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static constexpr char outputs_layout_message[] = "Optional. Specifies layout for all input layers of the network."
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" Supported values: NCHW, NHWC, NC, C.";
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static constexpr char dla_arch_name[] = "Optional. Specify architecture name used to compile executable network for FPGA device.";
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DEFINE_bool(h, false, help_message);
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DEFINE_string(m, "", model_message);
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DEFINE_string(d, "", targetDeviceMessage);
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DEFINE_string(o, "", output_message);
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DEFINE_string(c, "config", config_message);
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DEFINE_string(ip, "", inputs_precision_message);
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DEFINE_string(op, "", outputs_precision_message);
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DEFINE_string(iop, "", iop_message);
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DEFINE_string(il, "", inputs_layout_message);
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DEFINE_string(ol, "", outputs_layout_message);
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DEFINE_string(VPU_NUMBER_OF_SHAVES, "", number_of_shaves_message);
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DEFINE_string(VPU_NUMBER_OF_CMX_SLICES, "", number_of_cmx_slices_message);
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DEFINE_string(VPU_TILING_CMX_LIMIT_KB, "", tiling_cmx_limit_message);
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DEFINE_string(DLA_ARCH_NAME, "", dla_arch_name);
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static void showUsage() {
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std::cout << std::endl;
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std::cout << "compile_tool [OPTIONS]" << std::endl;
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std::cout << "[OPTIONS]:" << std::endl;
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std::cout << " -h " << help_message << std::endl;
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std::cout << " -m <value> " << model_message << std::endl;
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std::cout << " -d <value> " << targetDeviceMessage << std::endl;
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std::cout << " -o <value> " << output_message << std::endl;
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std::cout << " -c <value> " << config_message << std::endl;
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std::cout << " -ip <value> " << inputs_precision_message << std::endl;
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std::cout << " -op <value> " << outputs_precision_message << std::endl;
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std::cout << " -iop \"<value>\" " << iop_message << std::endl;
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std::cout << " -il <value> " << inputs_layout_message << std::endl;
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std::cout << " -ol <value> " << outputs_layout_message << std::endl;
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std::cout << " " << std::endl;
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std::cout << " VPU options: " << std::endl;
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std::cout << " -VPU_NUMBER_OF_SHAVES <value> " << number_of_shaves_message << std::endl;
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std::cout << " -VPU_NUMBER_OF_CMX_SLICES <value> " << number_of_cmx_slices_message << std::endl;
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std::cout << " -VPU_TILING_CMX_LIMIT_KB <value> " << tiling_cmx_limit_message << std::endl;
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std::cout << " DLA options: " << std::endl;
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std::cout << " -DLA_ARCH_NAME <value> " << dla_arch_name << std::endl;
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std::cout << std::endl;
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}
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static bool parseCommandLine(int *argc, char ***argv, InferenceEngine::Core& ie) {
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gflags::ParseCommandLineNonHelpFlags(argc, argv, true);
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if (FLAGS_h) {
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showUsage();
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return false;
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}
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if (FLAGS_m.empty()) {
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throw std::invalid_argument("Path to model xml file is required");
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}
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if (FLAGS_d.empty()) {
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throw std::invalid_argument("Target device name is required");
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}
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if (std::string::npos != FLAGS_d.find("MYRIAD")) {
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std::vector<std::string> myriadDeviceIds = ie.GetMetric("MYRIAD", METRIC_KEY(AVAILABLE_DEVICES));
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}
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if (1 < *argc) {
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std::stringstream message;
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message << "Unknown arguments: ";
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for (auto arg = 1; arg < *argc; arg++) {
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message << argv[arg];
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if (arg < *argc) {
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message << " ";
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}
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}
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throw std::invalid_argument(message.str());
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}
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return true;
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}
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static std::map<std::string, std::string> parseConfig(const std::string& configName, char comment = '#') {
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std::map<std::string, std::string> config;
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std::ifstream file{configName};
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if (file.is_open()) {
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std::string key, value;
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while (file >> key >> value) {
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if (key.empty() || key[0] == comment) {
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continue;
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}
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config[key] = value;
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}
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}
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return config;
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}
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static std::map<std::string, std::string> configure(const std::string &configFile, const std::string &xmlFileName) {
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auto config = parseConfig(configFile);
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IE_SUPPRESS_DEPRECATED_START
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config[VPU_MYRIAD_CONFIG_KEY(PLATFORM)] = "VPU_MYRIAD_2480";
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IE_SUPPRESS_DEPRECATED_END
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if (!FLAGS_VPU_NUMBER_OF_SHAVES.empty()) {
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config[InferenceEngine::MYRIAD_NUMBER_OF_SHAVES] = FLAGS_VPU_NUMBER_OF_SHAVES;
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}
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if (!FLAGS_VPU_NUMBER_OF_CMX_SLICES.empty()) {
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config[InferenceEngine::MYRIAD_NUMBER_OF_CMX_SLICES] = FLAGS_VPU_NUMBER_OF_CMX_SLICES;
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}
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if (!FLAGS_VPU_TILING_CMX_LIMIT_KB.empty()) {
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config[InferenceEngine::MYRIAD_TILING_CMX_LIMIT_KB] = FLAGS_VPU_TILING_CMX_LIMIT_KB;
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}
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if (!FLAGS_DLA_ARCH_NAME.empty()) {
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config["DLIA_ARCH_NAME"] = FLAGS_DLA_ARCH_NAME;
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}
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return config;
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}
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static std::map<std::string, std::string> parsePrecisions(const std::string &iop) {
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std::string user_input = iop;
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user_input.erase(std::remove_if(user_input.begin(), user_input.end(), ::isspace), user_input.end());
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std::vector<std::string> inputs;
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vpu::splitStringList(user_input, inputs, ',');
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std::map<std::string, std::string> precisions;
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for (auto &&input : inputs) {
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std::vector<std::string> precision;
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vpu::splitStringList(input, precision, ':');
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if (precision.size() != 2) {
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throw std::invalid_argument("Invalid precision " + input + ". Expected layer_name : precision_value");
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}
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precisions[precision[0]] = precision[1];
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}
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return precisions;
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}
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using supported_precisions_t = std::unordered_map<std::string, InferenceEngine::Precision>;
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using supported_layouts_t = std::unordered_map<std::string, InferenceEngine::Layout>;
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using matchLayoutToDims_t = std::unordered_map<size_t, size_t>;
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static InferenceEngine::Layout getLayout(const std::string &value,
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const supported_layouts_t &supported_layouts) {
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std::string upper_value = value;
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std::transform(value.begin(), value.end(), upper_value.begin(), ::toupper);
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auto layout = supported_layouts.find(upper_value);
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if (layout == supported_layouts.end()) {
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throw std::logic_error("\"" + value + "\"" + " is not a valid layout.");
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}
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return layout->second;
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}
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static InferenceEngine::Precision getPrecision(const std::string &value,
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const supported_precisions_t &supported_precisions,
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const std::string& error_report = std::string()) {
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std::string upper_value = value;
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std::transform(value.begin(), value.end(), upper_value.begin(), ::toupper);
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auto precision = supported_precisions.find(upper_value);
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if (precision == supported_precisions.end()) {
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std::string report = error_report.empty() ? ("") : (" " + error_report);
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throw std::logic_error("\"" + value + "\"" + " is not a valid precision" + report);
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}
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return precision->second;
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}
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static InferenceEngine::Precision getInputPrecision(const std::string &value) {
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static const supported_precisions_t supported_precisions = {
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{ "FP32", InferenceEngine::Precision::FP32 },
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{ "FP16", InferenceEngine::Precision::FP16 },
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{ "U8", InferenceEngine::Precision::U8 }
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};
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return getPrecision(value, supported_precisions, "for input layer");
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}
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static InferenceEngine::Precision getOutputPrecision(const std::string &value) {
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static const supported_precisions_t supported_precisions = {
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{ "FP32", InferenceEngine::Precision::FP32 },
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{ "FP16", InferenceEngine::Precision::FP16 }
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};
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return getPrecision(value, supported_precisions, "for output layer");
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}
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static InferenceEngine::Layout getLayout(const std::string &value) {
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static const supported_layouts_t supported_layouts = {
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{ "NCHW", InferenceEngine::Layout::NCHW },
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{ "NHWC", InferenceEngine::Layout::NHWC },
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{ "CHW", InferenceEngine::Layout::CHW },
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{ "NC", InferenceEngine::Layout::NC },
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{ "C", InferenceEngine::Layout::C }
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};
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return getLayout(value, supported_layouts);
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}
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static bool isMatchLayoutToDims(const InferenceEngine::Layout& layout, const size_t dimension) {
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static const matchLayoutToDims_t matchLayoutToDims = {
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{static_cast<size_t>(InferenceEngine::Layout::NCHW), 4 },
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{static_cast<size_t>(InferenceEngine::Layout::NHWC), 4 },
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{static_cast<size_t>(InferenceEngine::Layout::CHW), 3 },
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{static_cast<size_t>(InferenceEngine::Layout::NC), 2 },
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{static_cast<size_t>(InferenceEngine::Layout::C), 1 }};
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auto dims = matchLayoutToDims.find(static_cast<size_t>(layout));
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if (dims == matchLayoutToDims.end()) {
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throw std::logic_error("Layout is not valid.");
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}
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return dimension == dims->second;
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}
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bool isFP16(InferenceEngine::Precision precision) {
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return precision == InferenceEngine::Precision::FP16;
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}
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bool isFP32(InferenceEngine::Precision precision) {
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return precision == InferenceEngine::Precision::FP32;
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}
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bool isU8(InferenceEngine::Precision precision) {
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return precision == InferenceEngine::Precision::U8;
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}
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bool isFloat(InferenceEngine::Precision precision) {
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return isFP16(precision) || isFP32(precision);
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}
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static void setPrecisions(const InferenceEngine::CNNNetwork &network, const std::string &iop) {
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auto user_precisions_map = parsePrecisions(iop);
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auto inputs = network.getInputsInfo();
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auto outputs = network.getOutputsInfo();
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for (auto &&item : user_precisions_map) {
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std::string layer_name = item.first;
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std::string user_precision = item.second;
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auto input = inputs.find(layer_name);
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auto output = outputs.find(layer_name);
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if (input != inputs.end()) {
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const auto input_precision = input->second->getPrecision();
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if ((isFloat(input_precision) && isFloat(getInputPrecision(user_precision))) ||
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(isFP16(input_precision) && isU8(getInputPrecision(user_precision)))) {
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input->second->setPrecision(getInputPrecision(user_precision));
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}
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} else if (output != outputs.end()) {
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const auto output_precision = output->second->getPrecision();
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if (isFloat(output_precision) && isFloat(getOutputPrecision(user_precision))) {
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output->second->setPrecision(getOutputPrecision(user_precision));
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}
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} else {
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throw std::logic_error(layer_name + " is not an input neither output");
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}
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}
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}
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static void setDefaultIOPrecisions(InferenceEngine::CNNNetwork &network, const std::string & device) {
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bool isMyriad = FLAGS_d.find("MYRIAD") != std::string::npos;
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if (isMyriad) {
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const InferenceEngine::Precision fp16 = InferenceEngine::Precision::FP16;
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for (auto &&layer : network.getInputsInfo()) {
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if (isFP32(layer.second->getPrecision())) {
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layer.second->setPrecision(fp16);
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}
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}
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for (auto &&layer : network.getOutputsInfo()) {
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if (isFP32(layer.second->getPrecision())) {
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layer.second->setPrecision(fp16);
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}
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}
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}
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}
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static void processPrecisions(InferenceEngine::CNNNetwork &network,
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const std::string &inputs_precision, const std::string &outputs_precision,
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const std::string &iop) {
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if (!inputs_precision.empty()) {
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auto precision = getInputPrecision(inputs_precision);
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for (auto &&layer : network.getInputsInfo()) {
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const auto layerPrecision = layer.second->getPrecision();
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if ((isFloat(layerPrecision) && isFloat(precision)) ||
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(isFloat(layerPrecision) && isU8(precision))) {
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layer.second->setPrecision(precision);
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}
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}
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}
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if (!outputs_precision.empty()) {
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auto precision = getOutputPrecision(outputs_precision);
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for (auto &&layer : network.getOutputsInfo()) {
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const auto layerPrecision = layer.second->getPrecision();
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if (isFloat(layerPrecision) && isFloat(precision)) {
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layer.second->setPrecision(precision);
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}
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}
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}
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if (!iop.empty()) {
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setPrecisions(network, iop);
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}
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}
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static void processLayout(InferenceEngine::CNNNetwork &network,
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const std::string &inputs_layout, const std::string &outputs_layout) {
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if (!inputs_layout.empty()) {
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auto layout = getLayout(inputs_layout);
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for (auto &&layer : network.getInputsInfo()) {
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if (isMatchLayoutToDims(layout, layer.second->getTensorDesc().getDims().size())) {
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layer.second->setLayout(layout);
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}
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}
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}
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if (!outputs_layout.empty()) {
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auto layout = getLayout(outputs_layout);
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for (auto &&layer : network.getOutputsInfo()) {
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if (isMatchLayoutToDims(layout, layer.second->getTensorDesc().getDims().size())) {
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layer.second->setLayout(layout);
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}
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}
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}
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}
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std::string getFileNameFromPath(const std::string& path,
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#if defined(_WIN32)
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const std::string sep = "\\") {
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#else
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const std::string sep = "/") {
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#endif
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auto pos = path.rfind(sep);
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if (std::string::npos == pos) {
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return path;
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} else {
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return path.substr(pos + 1);
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}
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}
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using TimeDiff = std::chrono::milliseconds;
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int main(int argc, char *argv[]) {
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TimeDiff loadNetworkTimeElapsed {0};
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try {
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std::cout << "Inference Engine: " << InferenceEngine::GetInferenceEngineVersion() << std::endl;
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InferenceEngine::Core ie;
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if (!parseCommandLine(&argc, &argv, ie)) {
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return EXIT_SUCCESS;
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}
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auto network = ie.ReadNetwork(FLAGS_m);
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setDefaultIOPrecisions(network, FLAGS_d);
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processPrecisions(network, FLAGS_ip, FLAGS_op, FLAGS_iop);
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processLayout(network, FLAGS_il, FLAGS_ol);
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auto timeBeforeLoadNetwork = std::chrono::steady_clock::now();
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auto executableNetwork = ie.LoadNetwork(network, FLAGS_d, configure(FLAGS_c, FLAGS_m));
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loadNetworkTimeElapsed = std::chrono::duration_cast<TimeDiff>(std::chrono::steady_clock::now() - timeBeforeLoadNetwork);
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std::string outputName = FLAGS_o;
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if (outputName.empty()) {
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outputName = getFileNameFromPath(fileNameNoExt(FLAGS_m)) + ".blob";
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}
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std::ofstream outputFile{outputName};
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if (!outputFile) {
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std::cout << "Output file " << outputName << " can't be opened for writing" << std::endl;
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return EXIT_FAILURE;
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} else {
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executableNetwork.Export(outputFile);
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}
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} catch (const std::exception &error) {
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std::cerr << error.what() << std::endl;
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return EXIT_FAILURE;
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} catch (...) {
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std::cerr << "Unknown/internal exception happened." << std::endl;
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return EXIT_FAILURE;
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}
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std::cout << "Done. LoadNetwork time elapsed: " << loadNetworkTimeElapsed.count() << " ms" << std::endl;
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return EXIT_SUCCESS;
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}
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