Files
BayesNet/src/Platform/main.cc

124 lines
5.0 KiB
C++

#include <iostream>
#include <argparse/argparse.hpp>
#include <nlohmann/json.hpp>
#include "Experiment.h"
#include "Datasets.h"
#include "DotEnv.h"
#include "Models.h"
#include "modelRegister.h"
#include "Paths.h"
using namespace std;
using json = nlohmann::json;
argparse::ArgumentParser manageArguments(int argc, char** argv)
{
auto env = platform::DotEnv();
argparse::ArgumentParser program("main");
program.add_argument("-d", "--dataset").default_value("").help("Dataset file name");
program.add_argument("--hyperparameters").default_value("{}").help("Hyperparamters passed to the model in Experiment");
program.add_argument("-m", "--model")
.help("Model to use " + platform::Models::instance()->toString())
.action([](const std::string& value) {
static const vector<string> choices = platform::Models::instance()->getNames();
if (find(choices.begin(), choices.end(), value) != choices.end()) {
return value;
}
throw runtime_error("Model must be one of " + platform::Models::instance()->toString());
}
);
program.add_argument("--title").default_value("").help("Experiment title");
program.add_argument("--discretize").help("Discretize input dataset").default_value((bool)stoi(env.get("discretize"))).implicit_value(true);
program.add_argument("--save").help("Save result (always save if no dataset is supplied)").default_value(false).implicit_value(true);
program.add_argument("--stratified").help("If Stratified KFold is to be done").default_value((bool)stoi(env.get("stratified"))).implicit_value(true);
program.add_argument("-f", "--folds").help("Number of folds").default_value(stoi(env.get("n_folds"))).scan<'i', int>().action([](const string& value) {
try {
auto k = stoi(value);
if (k < 2) {
throw runtime_error("Number of folds must be greater than 1");
}
return k;
}
catch (const runtime_error& err) {
throw runtime_error(err.what());
}
catch (...) {
throw runtime_error("Number of folds must be an integer");
}});
auto seed_values = env.getSeeds();
program.add_argument("-s", "--seeds").nargs(1, 10).help("Random seeds. Set to -1 to have pseudo random").scan<'i', int>().default_value(seed_values);
try {
program.parse_args(argc, argv);
auto file_name = program.get<string>("dataset");
auto model_name = program.get<string>("model");
auto discretize_dataset = program.get<bool>("discretize");
auto stratified = program.get<bool>("stratified");
auto n_folds = program.get<int>("folds");
auto seeds = program.get<vector<int>>("seeds");
auto title = program.get<string>("title");
auto hyperparameters = program.get<string>("hyperparameters");
auto saveResults = program.get<bool>("save");
if (title == "" && file_name == "") {
throw runtime_error("title is mandatory if dataset is not provided");
}
}
catch (const exception& err) {
cerr << err.what() << endl;
cerr << program;
exit(1);
}
return program;
}
int main(int argc, char** argv)
{
auto program = manageArguments(argc, argv);
auto file_name = program.get<string>("dataset");
auto model_name = program.get<string>("model");
auto discretize_dataset = program.get<bool>("discretize");
auto stratified = program.get<bool>("stratified");
auto n_folds = program.get<int>("folds");
auto seeds = program.get<vector<int>>("seeds");
auto hyperparameters = program.get<string>("hyperparameters");
vector<string> filesToTest;
auto datasets = platform::Datasets(discretize_dataset, platform::Paths::datasets());
auto title = program.get<string>("title");
auto saveResults = program.get<bool>("save");
if (file_name != "") {
if (!datasets.isDataset(file_name)) {
cerr << "Dataset " << file_name << " not found" << endl;
exit(1);
}
if (title == "") {
title = "Test " + file_name + " " + model_name + " " + to_string(n_folds) + " folds";
}
filesToTest.push_back(file_name);
} else {
filesToTest = datasets.getNames();
saveResults = true;
}
/*
* Begin Processing
*/
auto env = platform::DotEnv();
auto experiment = platform::Experiment();
experiment.setTitle(title).setLanguage("cpp").setLanguageVersion("14.0.3");
experiment.setDiscretized(discretize_dataset).setModel(model_name).setPlatform(env.get("platform"));
experiment.setStratified(stratified).setNFolds(n_folds).setScoreName("accuracy");
experiment.setHyperparameters(json::parse(hyperparameters));
for (auto seed : seeds) {
experiment.addRandomSeed(seed);
}
platform::Timer timer;
timer.start();
experiment.go(filesToTest);
experiment.setDuration(timer.getDuration());
if (saveResults) {
experiment.save(platform::Paths::results());
}
experiment.report();
cout << "Done!" << endl;
return 0;
}