def load_and_cache_examples(args, tokenizer, websites):
    r"""
    Load and process the raw data.
    """
    # if args.local_rank not in [-1, 0]:
    #    torch.distributed.barrier()  # Make sure only the first process in distributed training process the dataset,
    # and the others will use the cache

    feature_dicts = {}

    for website in websites:
        features_per_website = load_and_cache_one_website(args, tokenizer, website)
        feature_dicts[website] = features_per_website

    return feature_dicts

    Load and process the raw data.
    
markuplm/examples/fine_tuning/run_swde/run.py