def main():
t = time()
conf_code = extract_config_code()
check_flags()
print(get_model_info_as_str())
data = SiameseModelData(FLAGS.dataset_train)
dist_sim_calculator = DistSimCalculator(FLAGS.dataset_train, FLAGS.ds_metric, FLAGS.ds_algo)
model = create_model(FLAGS.model, data.input_dim(), data, dist_sim_calculator)
os.environ["CUDA_VISIBLE_DEVICES"] = str(FLAGS.gpu)
config = tf.compat.v1.ConfigProto()
config.gpu_options.allow_growth = True
sess = tf.compat.v1.Session(config=config)
saver = Saver(sess)
sess.run(tf.compat.v1.global_variables_initializer())
train_costs, train_times = train_loop(data, model, saver, sess)
test(data, model, saver, sess)
saver.save_conf_code(conf_code)
overall_time = convert_long_time_to_str(time() - t)
print(overall_time, saver.get_log_dir())
saver.save_overall_time(overall_time)
return train_costs, train_times
