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_1(configs):
"""
This function generates the table 1 from the paper.
"""
table = get_table1(configs)
table.write(
os.path.join(configs['output_path'], 'tables_and_plots/table1.tex'))
def test_table1_number_of_configs(self):
"""
We have 1 experiment for 4 languages so 4 configs
"""
table1 = get_table1(self.CONFIGS)
configs = [
c for _, e in table1.get_experiments()
for c in e.get_parameters_combinations()
]
self.assertEqual(4,
len(configs),
msg="Table 1 should have 4 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.")