Function train

graphgym/train.py:49–84

r""" The core training pipeline Args: loggers: List of loggers loaders: List of loaders model: GNN model optimizer: PyTorch optimizer scheduler: PyTorch learning rate scheduler

(loggers, loaders, model, optimizer, scheduler)

def train(loggers, loaders, model, optimizer, scheduler):
    r"""
    The core training pipeline

    Args:
        loggers: List of loggers
        loaders: List of loaders
        model: GNN model
        optimizer: PyTorch optimizer
        scheduler: PyTorch learning rate scheduler

    """
    start_epoch = 0
    if cfg.train.auto_resume:
        start_epoch = load_ckpt(model, optimizer, scheduler)
    if start_epoch == cfg.optim.max_epoch:
        logging.info('Checkpoint found, Task already done')
    else:
        logging.info('Start from epoch {}'.format(start_epoch))

    num_splits = len(loggers)
    for cur_epoch in range(start_epoch, cfg.optim.max_epoch):
        train_epoch(loggers[0], loaders[0], model, optimizer, scheduler)
        loggers[0].write_epoch(cur_epoch)
        if is_eval_epoch(cur_epoch):
            for i in range(1, num_splits):
                eval_epoch(loggers[i], loaders[i], model)
                loggers[i].write_epoch(cur_epoch)
        if is_ckpt_epoch(cur_epoch):
            save_ckpt(model, optimizer, scheduler, cur_epoch)
    for logger in loggers:
        logger.close()
    if cfg.train.ckpt_clean:
        clean_ckpt()

    logging.info('Task done, results saved in {}'.format(cfg.out_dir))