def main(network, dataset, config_file, experiment_id, restore_path):
environment.init(experiment_id)
config = config_util.load_from_experiment()
if config_file:
config = config_util.merge(config, config_util.load(config_file))
if network:
network_class = module_loader.load_network_class(network)
config.NETWORK_CLASS = network_class
if dataset:
dataset_class = module_loader.load_dataset_class(dataset)
config.DATASET_CLASS = dataset_class
executor.init_logging(config)
config_util.display(config)
evaluate(config, restore_path)
def run(network, dataset, config_file, experiment_id, recreate):
environment.init(experiment_id)
config = config_util.load(config_file)
if network:
network_class = module_loader.load_network_class(network)
config.NETWORK_CLASS = network_class
if dataset:
dataset_class = module_loader.load_dataset_class(dataset)
config.DATASET_CLASS = dataset_class
config_util.display(config)
executor.init_logging(config)
executor.prepare_dirs(recreate)
config_util.copy_to_experiment_dir(config_file)
config_util.save_yaml(environment.EXPERIMENT_DIR, config)
start_training(config)