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Show model version in b_main

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This commit is contained in:
Ricardo Montañana Gómez
2024-04-09 23:20:19 +02:00
parent 72ea62f783
commit 5ec7fe8d00
2 changed files with 8 additions and 5 deletions
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10
src/commands/b_main.cpp
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@@ -28,7 +28,7 @@ void manageArguments(argparse::ArgumentParser& program)
}
throw std::runtime_error("Dataset must be one of: " + datasets.toString());
}
);
);
program.add_argument("--hyperparameters").default_value("{}").help("Hyperparameters passed to the model in Experiment");
program.add_argument("--hyper-file").default_value("").help("Hyperparameters file name." \
"Mutually exclusive with hyperparameters. This file should contain hyperparameters for each dataset in json format.");
@@ -41,7 +41,7 @@ void manageArguments(argparse::ArgumentParser& program)
}
throw std::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("--no-train-score").help("Don't compute train score").default_value(false).implicit_value(true);
@@ -62,8 +62,8 @@ void manageArguments(argparse::ArgumentParser& program)
catch (...) {
throw std::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);
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);
}
int main(int argc, char** argv)
@@ -129,7 +129,7 @@ int main(int argc, char** argv)
*/
auto env = platform::DotEnv();
auto experiment = platform::Experiment();
experiment.setTitle(title).setLanguage("cpp").setLanguageVersion("14.0.3");
experiment.setTitle(title).setLanguage("c++").setLanguageVersion("13.2.1");
experiment.setDiscretized(discretize_dataset).setModel(model_name).setPlatform(env.get("platform"));
experiment.setStratified(stratified).setNFolds(n_folds).setScoreName("accuracy");
experiment.setHyperparameters(test_hyperparams);