def main(args): run_launcher = default_launcher mlflow.set_tracking_uri(DEFAULT_LOCAL_MLFLOW_OUTPUT) cuda = args['cuda'] launcher = Launcher(run_launcher, cuda) logging.info("Lauching experiments for Table 1") table1 = get_table1(args) launcher.run_experiment_for_table(table1) logging.info("Done.") logging.info("Lauching experiments for Table 2") table2 = get_table2(args) launcher.run_experiment_for_table(table2) logging.info("Done.") logging.info("Lauching experiments for Table 3") table3 = get_table3(args) launcher.run_experiment_for_table(table3) logging.info("Done.") logging.info("Lauching experiments for grid search experiments") table4 = get_grid_search_experiments(base_configs) launcher.run_experiment_for_table(table4) logging.info("Done.")
def generate_table_2(configs): """ This function generates the table 2 from the paper. """ table = get_table2(configs) table.write( os.path.join(configs['output_path'], 'tables_and_plots/table2.tex'))
def test_table2_number_of_configs(self): """ We have 8 experiment (including original) for 4 languages so 32 configs """ table1 = get_table2(self.CONFIGS) configs = [ c for _, e in table1.get_experiments() for c in e.get_parameters_combinations() ] self.assertEqual(32, len(configs), msg="Table 2 should have 32 configurations")
def main(args): run_launcher = default_launcher mlflow.set_tracking_uri(DEFAULT_LOCAL_MLFLOW_OUTPUT) num_runs = args['num_runs'] cuda = args['cuda'] launcher = Launcher(run_launcher, cuda) logging.info("Lauching experiments for Table 1") table1 = get_table1(args) launcher.run_experiment_for_table(table1) table1.write(os.path.join(args['output_path'], 'tables_and_plots/table1.tex')) logging.info("Done.") logging.info("Lauching experiments for Table 2") table2 = get_table2(args) launcher.run_experiment_for_table(table2) table2.write(os.path.join(args['output_path'], 'tables_and_plots/table2.tex')) logging.info("Done.")