def main()

in floresv1/scripts/train.py [0:0]

• 38 lines of code
• 6 McCabe index (conditional complexity)

def main():
    parser = argparse.ArgumentParser()
    parser.add_argument('--config', '-c', required=True, help='pipeline config')
    parser.add_argument('--databin', '-d', required=True, help='initial databin')
    args = parser.parse_args()

    configs = read_config(args.config)
    workdir = os.path.join(os.path.dirname(os.path.abspath(__file__)), '../experiments')
    #cuda_visible_devices=args.cuda_visible_devices or list(range(torch.cuda.device_count()))

    initial_databin = args.databin
    for i in range(len(configs)):
        (name, config) = configs[i]
        src = config['src']
        tgt = config['tgt']
        direction = f"{src}-{tgt}"
        print(f"Start {name} iteration, {direction}")
        iter_workdir = os.path.join(workdir, name, direction)
        # train
        model_dir = os.path.join(iter_workdir, 'model')
        train(src, tgt, config['train'], model_dir, initial_databin)
        checkpoint_path = os.path.join(model_dir, 'checkpoint_best.pt')
        # eval
        lenpen = config['translate']['lenpen']
        eval_output = os.path.join(model_dir, 'eval.txt')
        if check_last_line(eval_output, "BLEU"):
            print(check_output(f"tail -n 1 {eval_output}", shell=True).decode('utf-8').strip())
        else:
            print(eval_bleu(
                config['src'], config['tgt'],
                'test', lenpen,
                args.databin, checkpoint_path,
                os.path.join(model_dir, 'eval.txt')
            ))
        # Early exit to skip back-translation for the last iteration
        if i == len(configs) - 1:
            break
        # translate
        translate_output = os.path.join(iter_workdir, 'synthetic')
        translate(config['src'], config['tgt'], checkpoint_path, lenpen, translate_output, config['translate']['mono'], config['translate']['max_token'])
        # generate databin
        databin_folder = os.path.join(translate_output, 'bt')
        initial_databin = build_bt_databin(
            config['tgt'], config['src'],
            os.path.join(translate_output, 'generated'), args.databin, databin_folder
        )